Type 2 diabetes biomarkers and uses thereof

Abstract
The present invention provides biomarkers, methods and kits for diagnosing and prognosing the development of impaired glucose tolerance in a subject and the progression of diabetes in a subject, as well as methods for identifying a compound that can inhibit the development of impaired glucose tolerance and/or type 2 diabetes; reduce or slow down the progression of normal glucose tolerance to impaired fasting glycaemia, to impaired glucose tolerance, and/or to diabetes; and/or reduce or inhibit the development of complications associated with the disease in a subject, and methods for inhibiting the development of impaired glucose tolerance and/or type 2 diabetes; reducing or slowing down the progression of normal glucose tolerance to impaired fasting glycaemia, to impaired glucose tolerance, and/or to diabetes; and/or reducing or inhibiting the development of complications associated with the disease in a subject.
Description
BACKGROUND OF THE INVENTION

Diabetes mellitus type 2 (also referred to as noninsulin-dependent diabetes mellitus (NIDDM) or adult-onset diabetes) is a metabolic disorder that is characterized by high blood glucose in the presence of insulin resistance and relative insulin deficiency. Type 2 diabetes is a progressive disease in which the risks of myocardial infarction, stroke, microvascular events and mortality are all strongly associated with hyperglycaemia. Type 2 diabetes is also a silent disease with significant declines in β-cell function and kidney damage often occurring before any symptoms of the disease manifest.


The progression from normal glucose tolerance (NGT) to type 2 diabetes involves intermediate stages of impaired fasting glucose (IFG) and impaired glucose tolerance (IGT), also known as prediabetes. The pathophysiology underlying the development of these glucose metabolic alterations is multifactorial and includes, for example, lifestyle and genetic factors. In particular, obesity is thought to be the primary cause of type 2 diabetes in people who are genetically predisposed to the disease and rates of type 2 diabetes have increased markedly over the last 50 years in parallel with obesity. As of 2010 there are approximately 285 million people with the disease compared to around 30 million in 1985.


Although numerous risk factors, such as age, body mass index (BMI), and ethnicity, have been associated with the development of prediabetes and type 2 diabetes, these are not adequate to accurately predict the risk of progression from normal glucose tolerance to impaired glucose tolerance and/or from impaired glucose tolerance to type 2 diabetes since the development and progression of diabetes is often silent with organ damage occurring before the onset of identifiable symptoms. In addition, although methods for determining whether a subject has impaired glucose tolerance and/or type 2 diabetes are known (e.g., glucose tolerance testing), such methods require overnight fasting and multiple blood draws over several hours and are often associated with side effects, such as, nausea, vomiting, abdominal bloating, and/or headache.


Accordingly, as early identification of subjects who have impaired glucose tolerance and/or type 2 diabetes and/or who are at risk of developing impaired glucose tolerance and/or type 2 diabetes and/or those that will respond to a particular therapy would decrease short-term and long-term complications associated with glucose imbalance, there is a need in the art for reliable and accurate methods of determining which subjects have or will develop impaired glucose tolerance and/or type 2 diabetes and/or respond to a therapy to permit early intervention.


SUMMARY OF THE INVENTION

The present invention is based, at least in part, on the discovery of markers that are associated with the development of impaired glucose tolerance and/or type 2 diabetes and the response of subjects having impaired glucose tolerance and/or type 2 diabetes to a treatment. Accordingly, the present invention provides sensitive and facile methods and kits for predicting whether a subject has or will develop impaired glucose tolerance, methods and kits for predicting whether a subject has or will develop diabetes, as well as methods for identifying a compound that can slow down the progression of impaired glucose tolerance and/or type 2 diabetes, methods of monitoring the effectiveness of a therapy in reducing the progression of impaired glucose tolerance and/or type 2 diabetes in a subject, and methods for inhibiting progression of impaired glucose tolerance and/or type 2 in a cell or a subject by measuring and identifying particular markers, or particular combinations of markers.


Accordingly, in one aspect the present invention provides methods for determining whether a subject has or will develop impaired glucose tolerance. The methods include determining the level of one or more markers of the invention, e.g., any one or more of the markers listed in any of Tables 1-3; USP9X; SEPT3; INS and SERPINB13; PPY and DAG1; INS, CPM, and MMP7; BTC, MMP7, and PPY; PPY, SEPT3, and PTPRJ; CPM, INS, MMP7, and LDLR, in a sample(s) from the subject; comparing the level of the one or more markers in the subject sample(s) with a level of the one or more markers in a control sample(s), wherein a difference in the level of the one or more markers in the subject sample(s) as compared to the level of the one or more markers in the control sample(s) indicates that the subject has or will develop impaired glucose tolerance.


In another aspect, the present invention provides methods for determining whether a subject has or will develop type 2 diabetes. The methods include determining the level of one or more markers of the invention, e.g., any one or more of the markers listed in any of Tables 1-3; USP9X; SEPT3; INS and SERPINB13; PPY and DAG1; INS, CPM, and MMP7; BTC, MMP7, and PPY; PPY, SEPT3, and PTPRJ; CPM, INS, MMP7, and LDLR, in a sample(s) from the subject; comparing the level of the one or more markers in the subject sample(s) with a level of the one or more markers in a control sample(s), wherein a difference in the level of the one or more markers in the subject sample(s) as compared to the level of the one or more markers in the control sample(s) indicates that the subject has or will develop type 2 diabetes.


In another aspect, the present invention provides methods for determining whether a subject will develop a type 2 diabetes-associated complication. The methods include determining the level of one or more markers of the invention, e.g., any one or more of the markers listed in any of Tables 1-3; USP9X; SEPT3; INS and SERPINB13; PPY and DAG1; INS, CPM, and MMP7; BTC, MMP7, and PPY; PPY, SEPT3, and PTPRJ; CPM, INS, MMP7, and LDLR, in a sample(s) from the subject; comparing the level of the one or more markers in the subject sample(s) with a level of the one or more markers in a control sample(s), wherein a difference in the level of the one or more markers in the subject sample(s) as compared to the level of the one or more markers in the control sample(s) indicates that the subject will develop a type 2 diabetes-associate complication.


In yet another aspect, the present invention provides methods for determining whether a subject having impaired glucose tolerance and/or type 2 diabetes will respond to a therapy. The methods include determining the level of one or more markers of the invention, e.g., any one or more of the markers listed in any of Tables 1-3; USP9X; SEPT3; INS and SERPINB13; PPY and DAG1; INS, CPM, and MMP7; BTC, MMP7, and PPY; PPY, SEPT3, and PTPRJ; CPM, INS, MMP7, and LDLR, in a sample(s) from the subject; comparing the level of the one or more markers in the subject sample(s) with a level of the one or more markers in a control sample(s), wherein a difference in the level of the one or more markers in the subject sample(s) as compared to the level of the one or more markers in the control sample(s) indicates that the subject will respond to the therapy.


In another aspect, the present invention provides methods for monitoring the effectiveness of a treatment in a subject having impaired glucose tolerance and/or type 2 diabetes. The methods include determining the level of one or more markers of the invention, e.g., any one or more of the markers listed in any of Tables 1-3; USP9X; SEPT3; INS and SERPINB13; PPY and DAG1; INS, CPM, and MMP7; BTC, MMP7, and PPY; PPY, SEPT3, and PTPRJ; CPM, INS, MMP7, and LDLR, in a first sample(s) from the subject prior to the initiation of the treatment; determining the level of one or more markers in a second sample(s) from the subject after at least a portion of the treatment has been administered; comparing the level of the one or more markers in the first sample(s) with a level of the one or more markers in the second sample(s), wherein a difference in the level of the one or more markers in the first sample(s) as compared to the level of the one or more markers in the second sample(s) indicates that the subject will respond to the treatment.


In one aspect, the present invention provides methods for identifying a compound that can inhibit the development of impaired glucose tolerance and/or type 2 diabetes, the method comprising contacting an aliquot of a sample(s) from the subject with each member of a library of compounds; determining the effect of a member of the library of compounds on the level and/or activity of one or more markers of the invention, e.g., any one or more of the markers listed in any of Tables 1-3; USP9X; SEPT3; INS and SERPINB13; PPY and DAG1; INS, CPM, and MMP7; BTC, MMP7, and PPY; PPY, SEPT3, and PTPRJ; CPM, INS, MMP7, and LDLR, in each of the aliquots; and selecting a member of the library of compounds which modulates the level and/or the activity of the one or more marker(s) of the invention in an aliquot as compared to the level and/or activity of the one or more marker(s) of the invention in a control sample, thereby identifying a compound that can inhibit the development of impaired glucose tolerance and/or type 2 diabetes.


In another aspect, the present invention provides methods for inhibiting the development of impaired glucose tolerance and/or type 2 diabetes in a subject. The methods include administering to the subject an effective amount of an agent that modulates the expression and/or activity of any one or more of the markers of the invention, e.g., any one or more of the markers listed in any of Tables 1-3; USP9X; SEPT3; INS and SERPINB13; PPY and DAG1; INS, CPM, and MMP7; BTC, MMP7, and PPY; PPY, SEPT3, and PTPRJ; CPM, INS, MMP7, and LDLR, thereby inhibiting the development of impaired glucose tolerance and/or type 2 diabetes in the subject.


In one embodiment the level in the subject sample(s) is determined by mass spectrometry. In one embodiment the mass spectrometry is matrix assisted laser desorption/time of flight (MALDI/TOF) mass spectrometry, liquid chromatography quadruple ion trap electrospray (LCQ-MS), or surface enhanced laser desorption ionization/time of flight (SELDI/TOF) mass spectrometry.


In another embodiment the level in the subject sample(s) is determined by immunoassay.


The sample(s) from the subject may be a fluid sample(s) or a tissue sample(s).


In one embodiment, the level of the marker is an expression level and/or activity of the marker.


In one embodiment the subject is at risk of developing type 2 diabetes.


In one aspect, the present invention provides kits for determining whether a subject has or will develop impaired glucose tolerance. The kits include reagents for determining the level of one or more markers, e.g., one or more markers listed in any of Tables 1-3; USP9X; SEPT3; INS and SERPINB13; PPY and DAG1; INS, CPM, and MMP7; BTC, MMP7, and PPY; PPY, SEPT3, and PTPRJ; CPM, INS, MMP7, and LDLR, in a subject sample(s) and instructions for use of the kit to determine whether the subject has or will develop impaired glucose tolerance.


In another aspect, the present invention provides kits for determining whether a subject has or will develop type 2 diabetes. The list include reagents for determining the level of one or more markers, e.g., one or more markers listed in any of Tables 1-3; USP9X; SEPT3; INS and SERPINB13; PPY and DAG1; INS, CPM, and MMP7; BTC, MMP7, and PPY; PPY, SEPT3, and PTPRJ; CPM, INS, MMP7, and LDLR, in a subject sample(s) and instructions for use of the kit to determine whether the subject has or will develop type 2 diabetes.


In yet another aspect, the present provides kits for determining whether a subject has or will develop type 2 diabetes complications. The kits include reagents for determining the level of one or more markers, e.g., one or more markers listed in any of Tables 1-3; USP9X; SEPT3; INS and SERPINB13; PPY and DAG1; INS, CPM, and MMP7; BTC, MMP7, and PPY; PPY, SEPT3, and PTPRJ; CPM, INS, MMP7, and LDLR, in a subject sample(s) and instructions for use of the kit to determine whether the subject has or will develop type 2 diabetes complications.


In another aspect, the present invention provides kits for determining whether a subject having impaired glucose tolerance and/or type 2 diabetes will respond to a treatment. The kits include reagents for determining the level of one or more markers, e.g., one or more markers listed in any of Tables 1-3; USP9X; SEPT3; INS and SERPINB13; PPY and DAG1; INS, CPM, and MMP7; BTC, MMP7, and PPY; PPY, SEPT3, and PTPRJ; CPM, INS, MMP7, and LDLR, in a subject sample(s) and instructions for use of the kit to determine whether the subject will respond to the treatment.


In yet another aspect, the present invention provides kits of monitoring the effectiveness of a treatment in a subject having impaired glucose tolerance and/or type 2 diabetes. The uts include reagents for determining the level of one or more markers, e.g., one or more markers listed in any of Tables 1-3; USP9X; SEPT3; INS and SERPINB13; PPY and DAG1; INS, CPM, and MMP7; BTC, MMP7, and PPY; PPY, SEPT3, and PTPRJ; CPM, INS, MMP7, and LDLR, in a subject sample(s) and instructions for use of the kit to monitor the effectiveness of the treatment.


In one embodiment, the kits further comprise reagents for obtaining a sample from a subject.


In one embodiment, the kits further comprise a control sample.


In one aspect, the present invention provides methods for identifying a type 2 diabetes marker. The methods include identifying proteins in the secretory vesicles of two or more organs from two or more species under steady state conditions; identifying proteins in the secretory vesicles of pancreatic β cells thereby generating a provisional list of steady state markers; identifying the markers in the provisional list of steady state markers from the two or more organs from the two or more species common to the markers in the secretory vesicles of pancreatic β cells and removing those markers from the provisional list of steady state markers, thereby generating a list of β cell mass markers; identifying proteins in the secretory vesicles of pancreatic β cells under dysfunctional conditions, identifying proteins in the secretory vesicles of pancreatic β cells under normal conditions, identifying the proteins that were differentially expressed under dysfunctional conditions and under normal conditions, thereby generating a provisional list of β cell function markers, determining the level of a β cell mass marker and/or a β cell function marker in a sample(s) form a test sample and a control sample, wherein a difference in the level of a marker in the control sample as compared to the level in the test sample identifies the marker as a type 2 diabetes biomarker.


In one embodiment, the test sample is from a subject having impaired glucose tolerance. In another embodiment, the test sample is from a subject having newly diagnosed type 2 diabetes. In yet another embodiment, the test sample is from a subject having established type 2 diabetes.


In one embodiment, the control sample is from a subject having normal glucose tolerance. In another embodiment, the control sample is from a subject having impaired glucose tolerance. In yet another embodiment, the control sample is from a subject having newly diagnosed type 2 diabetes.


In another aspect, the present invention provides methods for identifying a type 2 diabetes marker. The methods include identifying proteins differentially expressed in a sample(s) from a subject before and after treatment, thereby generating a list of therapeutic efficacy markers; determining the level of one or more of the markers in a first sample obtained from a subject having type 2 diabetes prior to providing at least a portion of a therapy to the subject; and determining the level of a protein in a second sample obtained from the subject following provision of at least a portion of the therapy, wherein a difference in the level of expression of the one or more markers in the second sample relative to the first sample identifies the protein as a type 2 diabetes marker.





BRIEF DESCRIPTION OF THE DRAWINGS


FIG. 1 depicts Western blots of proteins identified during the process of secreted proteins preparation. Cell or tissue homogenates were prepared by mechanical disruption and secretory pathway vesicles isolated by sucrose density centrifugation. The resultant vesicles were washed with salt to remove loosely attached proteins, opened with alkali, and the secretory protein contents retrieved by high speed centrifugation. Shown are western blots of starting materials (Hom), intermediate (SV) and final product (SC) preparations from a rat cell line (A) and human primary islets (B). The western blot markers were against specific intracellular compartments and indicate the progressive enrichment of secretory proteins during sample preparation. Hom: homogenate; SV: secretory vesicle; SC: secretory vesicle contents; Mb: membrane; PM: plasma membrane.





DETAILED DESCRIPTION OF THE INVENTION

The present invention is based, at least in part, on the discovery of markers that are associated with the development of impaired glucose tolerance and/or type 2 diabetes, the progression of type 2 diabetes, and the response of a subject having impaired glucose tolerance and/or type 2 diabetes to a treatment. In particular, biomarkers associated with type 2 diabetes have been discovered, prioritized, and validated in multiple in vitro experimental systems. The markers were identified as being expressed, e.g., essentially specifically expressed in β-cells, and/or as being involved, e.g., essentially specifically involved, in β-cell function, and/or as being involved in response to a therapeutic treatment.


Accordingly, the present invention provides sensitive and facile methods and kits for predicting whether a subject has or will develop impaired glucose tolerance, methods and kits for predicting whether a subject has or will develop diabetes, as well as methods for identifying a compound that can slow down the progression of impaired glucose tolerance and/or type 2 diabetes, methods of monitoring the effectiveness of a therapy in reducing the progression of impaired glucose tolerance and/or type 2 diabetes in a subject, and methods for inhibiting progression of impaired glucose tolerance and/or type 2 in a cell or a subject by measuring and identifying particular markers, or particular combinations of markers.


Various aspects of the invention are described in further detail in the following subsections:


I. Definitions

As used herein, each of the following terms has the meaning associated with it in this section.


The articles “a” and “an” are used herein to refer to one or to more than one (i.e. to at least one) of the grammatical object of the article. By way of example, “an element” means one element or more than one element.


A “marker” or “biomarker” is an organic biomolecule which is differentially present in a sample taken from a subject of one phenotypic status (e.g., having a disease) as compared with another phenotypic status (e.g., not having the disease). A biomarker is differentially present between different phenotypic statuses if the mean or median level, e.g., expression level, of the biomarker in the different groups is calculated to be statistically significant. Common tests for statistical significance include, among others, t-test, ANOVA, Kruskal-Wallis, Wilcoxon, Mann-Whitney and odds ratio. Biomarkers, alone or in combination, provide measures of relative risk that a subject belongs to one phenotypic status or another. As such, they are useful as markers for, e.g., disease (prognostics and diagnostics), therapeutic effectiveness of a drug (theranostics) and of drug toxicity.


In some embodiments, the accuracy of a marker(s) useful in the compositions and methods of the present invention may be characterized by a Receiver Operating Characteristic curve (“ROC curve”). An ROC is a plot of the true positive rate against the false positive rate for the different possible cutpoints of a diagnostic marker(s). An ROC curve shows the relationship between sensitivity and specificity. That is, an increase in sensitivity will be accompanied by a decrease in specificity. The closer the curve follows the left axis and then the top edge of the ROC space, the more accurate the marker(s). Conversely, the closer the curve comes to the 45-degree diagonal of the ROC graph, the less accurate the marker(s). The area under the ROC is a measure of a marker(s) accuracy. The accuracy of the marker(s) depends on how well the marker(s) separates the group being tested into those with and without the disease in question. An area under the curve (referred to as “AUC”) of 1 represents a perfect marker(s), while an area of 0.5 represents a less useful marker(s). Thus, in some embodiments, biomarkers and methods of the present invention have an AUC greater than about 0.50, an AUC greater than about 0.60, or an AUC greater than about 0.70.


“Type 2 diabetes” also referred to herein as “diabetes” is characterized by a combination of peripheral insulin resistance and inadequate insulin secretion by pancreatic beta cells. A “subject has diabetes” if the subject has a fasting plasma glucose (FPG) level of about 126 mg/dL (about 7.0 mmol/L) or higher; a 2-hour plasma glucose (PG) level of about 200 mg/dL (about 11.1 mmol/L) or higher during a 75-g oral glucose tolerance test (OGTT); a random plasma glucose of about 200 mg/dL (about 11.1 mmol/L) or higher in a subject having symptoms of hyperglycemia or hyperglycemic crisis; and/or a hemoglobin A1c (HbA1c) level of about 6.5% or higher.


A subject having “normal glucose tolerance” or “NGT” has a 2-hour plasma glucose (PG) level of less than about 140 mg/dL (less than about 7.8 mmol/L) during a 75-g oral glucose tolerance test (OGTT); a fasting plasma glucose (FPG) level of less than about 110 mg/dL (less than about 6.1 mmol/L); and/or a hemoglobin A1c (HbA1c) level of less than about 6%.


A “subject at risk of developing diabetes” is a subject that has a sustained blood pressure about 135/80 mm Hg or higher; is overweight (e.g., has a body mass index (BMI) greater than about 30 kg/m2); has a first-degree relative with diabetes; has an HDL level about 35 mg/dL or higher and/or triglyceride level less than about 250 mg/dL); is age 45 years or older; is female; has a history of gestational diabetes; has polycystic ovarian syndrome; has a condition associated with metabolic syndrome; is Hispanic; is African-American; and/or is Native-American. In addition, a number of medications and other diseases can put a subject at risk of developing diabetes. For example, glucocorticoids, thiazides, beta blockers, atypical antipsychotics, and statins may put a subject at risk of developing diabetes. Subjects who have previously had acromegaly, Cushing's syndrome, hyperthyroidism, pheochromocytoma, and certain cancers such as glucagonomas, and testosterone deficiency are also at risk of developing type 2 diabetes.


A subject, e.g., a subject at risk of developing diabetes, may be “pre-diabetic.” A subject is considered “pre-diabetic” if the subject has an impaired glucose tolerance. “Impaired glucose tolerance” is a state of hyperglycemia that is associated with insulin resistance and increased risk of cardiovascular pathology. A subject has impaired glucose tolerance when the subject has an intermediately raised glucose level after 2 hours, but less than would qualify for type 2 diabetes mellitus. The fasting glucose may be either normal or mildly elevated.


A subject having impaired glucose tolerance has a 2-hour plasma glucose (PG) level of about 140 mg/dL (about 7.8 mmol/L) or higher during a 75-g oral glucose tolerance test (OGTT) (e.g., between about 7.8 and 11 mmol/L); a fasting plasma glucose (FPG) level of less than about 126 mg/dL (less than about 7 mmol/L) (e.g., between about 95 and about 125 mg/dL); a hemoglobin A1c (HbA1c) level of about 6% or higher (e.g., between about 6.0 and 6.4); and/or a BMI about 24 kg/m2 or greater.


A subject, e.g., a subject at risk of developing diabetes, may have “impaired fasting glycaemia.” A subject having impaired fasting glycaemia has a 2-hour plasma glucose (PG) level of less than about 140 mg/dL (less than about 7.8 mmol/L) during a 75-g oral glucose tolerance test (OGTT); a fasting plasma glucose (FPG) level of less than about 126 mg/dL (less than about 7 mmol/L) (e.g., between about 110 and about 125 mg/dL); and/or a hemoglobin A1c (HbA1c) level of about 6% or higher (e.g., between about 6.0 and 6.4).


The term “diabetes has progressed” refers to the progression of normal glucose tolerance to impaired fasting glycaemia; the progression of normal glucose tolerance to impaired glucose tolerance; the progression of normal glucose tolerance to type 2 diabetes; the progression of impaired fasting glycaemia to impaired glucose tolerance; the progression of impaired fasting glycaemia to type 2 diabetes; and/or the progression of impaired glucose tolerance to type 2 diabetes in a subject.


A “level of a marker” or “the level of a biomarker” refers to an amount of a marker present in a sample being tested. A level of a marker may be either in absolute level or amount (e.g., μg/ml) or a relative level or amount (e.g., relative intensity of signals). A “higher level” or an “increase in the level” of marker refers to a level of a marker in a test sample that is greater than the standard error of the assay employed to assess the level of the marker, and is preferably at least twice, and more preferably three, four, five, six, seven, eight, nine, or ten or more times the level of marker in a control sample (e.g., a sample from a subject having normal glucose tolerance, a subject having impaired fasting glycaemia, a subject having impaired glucose tolerance, a subject having been diagnosed with type 2 diabetes in the previous 18 months, and/or, the average level of the marker in several control samples).


A “lower level” or a “decrease in the level” of a marker refers to a level of the marker in a test sample that is less than the standard error of the assay employed to assess the level of the marker, and preferably at least twice, and more preferably three, four, five, six, seven, eight, nine, or ten or more times less than the level of the marker in a control sample (e.g., a sample from a subject having normal glucose tolerance, a subject having impaired fasting glycaemia, a subject having impaired glucose tolerance, a subject having been diagnosed with type 2 diabetes in the previous 18 months, and/or, the average level of the marker in several control samples).


The term “known standard level” or “control level” refers to an accepted or pre-determined level of a marker which is used to compare the level of the marker in a sample derived from a subject. In one embodiment, the control level of a marker is based the level of the marker in a sample(s) from a subject(s) having normal glucose tolerance. In another embodiment, the control level of a marker is based on the level of the marker in a sample from a subject or subjects having impaired fasting glycaemia. In another embodiment, the control level of a marker is based on the level of the marker in a sample(s) from a subject having impaired glucose tolerance. In another embodiment, the control level of a marker is based on the level of the marker in a sample(s) from a subject having been diagnosed with type 2 diabetes with the previous 18 months. In one embodiment, the control level of a marker in a sample from a subject is a level of the marker previously determined in a sample(s) from the subject.


In yet another embodiment, the control level of a marker is based on the level of the marker in a sample from a subject(s) prior to the administration of a therapy for impaired fasting glycaemia, impaired glucose tolerance, and/or type 2 diabetes. In another embodiment, the control level of a marker is based on the level of the marker in a sample(s) from a subject(s) having impaired fasting glycaemia, impaired glucose tolerance, and/or type 2 diabetes that is not contacted with a test compound. In another embodiment, the control level of a marker is based on the level of the marker in a sample(s) from a subject(s) having normal glucose tolerance that is contacted with a test compound. In one embodiment, the control level of a marker is based on the expression level of the marker in a sample(s) from an animal model of impaired fasting glycaemia, impaired glucose tolerance, and/or type 2 diabetes, a cell, or a cell line derived from the animal model of impaired fasting glycaemia, impaired glucose tolerance, and/or type 2 diabetes.


Alternatively, and particularly as further information becomes available as a result of routine performance of the methods described herein, population-average values for “control” level of expression of a marker may be used. In other embodiments, the “control” level of a marker may be determined by determining the level of a marker in a subject sample obtained from a subject before the suspected onset of impaired fasting glycaemia, impaired glucose tolerance, and/or type 2 diabetes in the subject, from archived subject samples, and the like.


As used herein, the terms “patient” or “subject” refer to human and non-human animals, e.g., veterinary patients. The term “non-human animal” includes all vertebrates, e.g., mammals and non-mammals, such as non-human primates, mice, rabbits, sheep, dog, cat, horse, cow, chickens, amphibians, and reptiles. In one embodiment, the subject is a human.


In some embodiments, a subject has a body mass index (BMI) of less than about 40 kg/m2 (e.g., about 40 39, 38, 37, 36, 35, 34, 33, 32, 31, 30, 29, 28, 27, 26, 25, 24, 23, 22, 21, 20, 19, or about 18 kg/m2). In other embodiments, a subject has a body mass index (BMI) of greater than about 40 kg/m2 (e.g., about 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, or about 80 kg/m2).


The term “sample” as used herein refers to a collection of similar cells or tissue isolated from a subject, as well as tissues, cells and fluids present within a subject. The term “sample” includes any body fluid (e.g., blood fluids, lymph, gynecological fluids, cystic fluid, urine, ocular fluids and fluids collected by bronchial lavage and/or peritoneal rinsing), or a cell from a subject. In one embodiment, the tissue or cell is removed from the subject. In another embodiment, the tissue or cell is present within the subject. Other subject samples, include tear drops, serum, cerebrospinal fluid, feces, sputum and cell extracts. In one embodiment, the biological sample contains protein molecules from the test subject. In another embodiment, the biological sample may contain mRNA molecules from the test subject or genomic DNA molecules from the test subject.


The term “determining” means methods which include detecting the presence or absence of marker(s) in the sample, quantifying the amount of marker(s) in the sample, and/or qualifying the type of biomarker. Measuring can be accomplished by methods known in the art and those further described herein.


As used herein, the various forms of the term “modulate” are intended to include stimulation (e.g., increasing or upregulating a particular response or activity) and inhibition (e.g., decreasing or downregulating a particular response or activity).


A kit is any manufacture (e.g. a package or container) comprising at least one reagent, e.g. a probe, a primer, or an antibody, for specifically detecting a marker of the invention, the manufacture being promoted, distributed, or sold as a unit for performing the methods of the present invention. In certain embodiments, a lit may include a substrate, e.g., a substrate comprising a capture reagent for one or more markers of the invention and/or a capture reagent bound to one or more markers of the invention. In some embodiments, such kits comprise instructions for determining the level of a marker(s) using mass spectrometry.


II. Markers of the Invention

The present invention is based upon the discovery of markers that are essentially specifically expressed in pancreatic β-cells (Table 1), and/or as being essentially specifically involved in β-cell function (Table 2), and/or as being involved in response to a therapeutic treatment (Table 3). These markers have been shown to be differentially present in samples of subjects having impaired glucose tolerance and control subjects, and/or differentially present in samples of subjects having impaired glucose tolerance and subjects having newly diagnosed type 2 diabetes, and/or differentially present in samples of subjects having impaired glucose tolerance and subjects having established type 2 diabetes, and/or differentially present in samples of subjects having newly diagnosed type 2 diabetes and subjects having established type 2 diabetes, and/or differentially expressed in samples of subjects responsive to treatment with an insulin sensitizer and subjects non-responsive to an insulin sensitizer, and/or differentially expressed in samples of subjects responsive to treatment with an insulin sensitizer and a secretagogue and subjects non-responsive to an insulin sensitizer and a secretagogue, and/or differentially expressed in samples of subjects responsive to treatment with an insulin sensitizer, a secretagogue, and insulin and subjects non-responsive to an insulin sensitizer, a secretagogue, and insulin.


Accordingly, the level of any one marker or any combination of markers listed in Tables 1-3 found in a test sample compared to a control, or the presence or absence of one marker or combination of markers listed in Tables 1-3 in the test sample may be used in the methods and kits of the present invention.


The markers of the invention are listed in Tables 1-3. The nucleotide and amino acid sequences of the markers are known in the art and may be found in, for example, the GenBank Accession numbers listed in Tables 1-3, the entire contents of which are incorporated herein by reference.









TABLE 1







β-Cell Mass Markers of the Invention.











Marker
Protein

UNIPROT
GENBANK


Name
Description
UNIPROT_ID
ACCESSION
ACCESSION





ABCC8
ATP-binding
ABCC8_HUMAN
Q09428
NP_000343.2.



cassette sub-family


NM_000352.3.



C member 8


ACPP
Prostatic acid
PPAP_HUMAN
P15309
NP_001090.2



phosphatase


NM_001099.4






NP_001127666.1






NM_001134194.1


APLP1
Amyloid-like
APLP1_HUMAN
P51693
NP_001019978.1.



protein 1


NM_001024807.1.






NP_005157.1.






NM_005166.3.


APOL2
Apolipoprotein L2
APOL2_HUMAN
Q9BQE5
NP_112092.1






NM_030882.2






NP_663612.1






NM_145637.1


APP
Amyloid beta A4
A4_HUMAN
P05067
NP_000475.1



protein


NM_000484.3






NP_001129488.1.






NM_001136016.3






NP_001129601.1.






NM_001136129.2






NP_001129602.1.






NM_001136130.2






NP_001129603.1.






NM_001136131.2






NP_001191230.1.






NM_001204301.1.






NP_001191231.1.






NM_001204302.1.






NP_001191232.1.






NM_001204303.1.






NP_958816.1.






NM_201413.2.






NP_958817.1.






NM_201414.2.


ATP8A1
Probable
AT8A1_HUMAN
Q9Y2Q0
NP_001098999.1.



phospholipid-


NM_001105529.1.



transporting


NP_006086.1.



ATPase IA


NM_006095.2.


ATP9A
Probable
ATP9A_HUMAN
O75110
NP_006036.1.



phospholipid-


NM_006045.1.



transporting



ATPase IIA


BET1L
BET1-like protein
BET1L_HUMAN
Q9NYM9
NP_001092257.1.






NM_001098787.1.


BMP7
Bone
BMP7_HUMAN
P18075
NP_001710.1.



morphogenetic


NM_001719.2.



protein 7


BOLA1
BolA-like protein 1
BOLA1_HUMAN
Q9Y3E2
NP_057158.1.






NM_016074.3.


BTC
Probetacellulin
BTC_HUMAN
P35070
NP_001720.1.






NM_001729.2.


C12ORF23
UPF0444
CL023_HUMAN
Q8WUH6
NP_689474.1.



transmembrane


NM_152261.2.



protein C12orf23


C6ORF142
Muscular LMNA-
MLIP_HUMAN
Q5VWP3
NP_612636.2.



interacting protein


NM_138569.2.


C9ORF5
Transmembrane
TM245_HUMAN
Q9H330
NP_114401.2.



protein 245


NM_032012.3.


CADM1
Cell adhesion
CADM1_HUMAN
Q9BY67
NP_001091987.1.



molecule 1


NM_001098517.1.






NP_055148.3.






NM_014333.3.


CASC4
Protein CASC4
CASC4_HUMAN
Q6P4E1
NP_612432.2.






NM_138423.3.






NP_816929.1.






NM_177974.2.


CASR
Peripheral plasma
CASR_HUMAN
P41180
NP_000379.2



membrane protein


NM_000388.3



CASK


NP_001171536.1






NM_001178065.1


CBARA1
Calcium uptake
MICU1_HUMAN
Q9BPX6
NP_001182447.1.



protein 1,


NM_001195518.1.



mitochondrial


NP_001182448.1.






NM_001195519.1.






NP_006068.2.






NM_006077.3.


CCDC115
Coiled-coil domain-
CC115_HUMAN
Q96NT0
NP_115733.2.



containing protein


NM_032357.2.



115


CD47
Leukocyte surface
CD47_HUMAN
Q08722
NP_001768.1.



antigen CD47


NM_001777.3.






NP_942088.1.






NM_198793.2.


CD59
CD59 glycoprotein
CD59_HUMAN
P13987
NP_000602.1






NM_000611.5






NP_001120695.1






NM_001127223.1






NP_001120697.1






NM_001127225.1






NP_001120698.1






NM_001127226.1






NP_001120699.1






NM_001127227.1






NP_976074.1






NM_203329.2






NP_976075.1






NM_203330.2






NP_976076.1






NM_203331.2


CDCP1
CUB domain-
CDCP1_HUMAN
Q9H5V8
NP_073753.3.



containing


NM_022842.3.



protein 1


NP_835488.1.






NM_178181.1.


CFDP1
Craniofacial
CFDP1_HUMAN
Q9UEE9
NP_006315.1.



development


NM_006324.2.



protein 1


CHGB
Secretogranin-1
SCG1_HUMAN
P05060
NP_001810.2.






NM_001819.2.


CHKA
Choline kinase
CHKA_HUMAN
P35790
NP_001268.2.



alpha


NM_001277.2.






NP_997634.1.






NM_212469.1.


CLLD6
SPRY domain-
SPRY7_HUMAN
Q5W111
NP_001120954.1.



containing


NM_001127482.1.



protein 7


NP_065189.1.






NM_020456.2.


CNNM2
Metal transporter
CNNM2_HUMAN
Q9H8M5
NP_060119.3.



CNNM2


NM_017649.4.






NP_951058.1.






NM_199076.2.






NP_951059.1.






NM_199077.2.


CNP
2′,3′-cyclic-
CN37_HUMAN
P09543
NP_149124.3.



nucleotide 3′-


NM_033133.4.



phosphodiesterase


CNPY4
Protein canopy
CNPY4_HUMAN
Q8N129
NP_689968.1.



homolog 4


NM_152755.1.


CNTN1
Contactin-1
CNTN1_HUMAN
Q12860
NP_001242992.1






NM_001256063.1






NP_001242993.1






NM_001256064.1






NP_001834.2






NM_001843.3






NP_778203.1






NM_175038.2


COMMD10
COMM domain-
COMDA_HUMAN
Q9Y6G5
NP_057228.1.



containing


NM_016144.2.



protein 10


CPE
Carboxypeptidase E
CBPE_HUMAN
P16870
NP_001864.1






NM_001873.2


CSHL1
Chorionic
CSHL_HUMAN
Q14406
NP_072101.1.



somatomammotropin


NM_022579.1.



hormone-like 1


NP_072102.1.






NM_022580.1.






NP_072103.1.






NM_022581.1.


CSTF3
Cleavage
CSTF3_HUMAN
Q12996
NP_001028677.1



stimulation factor


NM_001033505.1



subunit 3


NP_001028678.1






NM_001033506.1






NP_001317.1






NM_001326.2


CYFIP1
Cytoplasmic FMR1-
CYFP1_HUMAN
Q7L576
NP_001028200.1.



interacting


NM_001033028.1.



protein 1


NP_055423.1.






NM_014608.2.


CYFIP2
Cytoplasmic FMR1-
CYFP2_HUMAN
Q96F07
NP_001032409.2.



interacting


NM_001037332.2.



protein 2


NP_001032410.1.






NM_001037333.1.






NP_055191.2.






NM_014376.2.


CYTL1
Cytokine-like
CYTL1_HUMAN
Q9NRR1
NP_061129.1.



protein 1


NM_018659.2.


CYTSA
Cytospin-A
CYTSA_HUMAN
Q69YQ0
NP_056145.3.






NM_015330.3.


DAG1
similar to
DAG1_HUMAN
Q14118
NP_001159400.2



Dystroglycan


-NM_001165928.3



precursor


NP_001171105.1






NM_001177634.2






NP_001171106.1






NM_001177635.2






NP_001171107.1






NM_001177636.2






NP_001171108.1






NM_001177637.2






NP_001171109.1






NM_001177638.2






NP_001171110.1






NM_001177639.2






NP_001171111.1






NM_001177640.2






NP_001171112.1






NM_001177641.2






NP_001171113.1






NM_001177642.2






NP_001171114.1






NM_001177643.2






NP_001171115.1






NM_001177644.2






NP_004384.4






NM_004393.5


DKK2
Dickkopf-related
DKK2_HUMAN
Q9UBU2
NP_055236.1.



protein 2


NM_014421.2.


DSCAML1
Down syndrome
DSCL1_HUMAN
Q8TD84
NP_065744.2.



cell adhesion


NM_020693.2.



molecule-like



protein 1


EDIL3
EGF-like repeat and
EDIL3_HUMAN
O43854
NP_005702.3.



discoidin 1-like


NM_005711.3.



domain-containing



protein 3


EMB
Embigin
EMB_HUMAN
Q6PCB8
NP_940851.1.






NM_198449.2.


ENPP1
Ectonucleotide
ENPP1_HUMAN
P22413
NP_006199.2.



pyrophosphatase/


NM_006208.2.



phosphodiesterase



family member 1


ENPP4
Ectonucleotide
ENPP4_HUMAN
Q9Y6X5
NP_055751.1.



pyrophosphatase/


NM_014936.4.



phosphodiesterase



family member 4


ENTPD3
Ectonucleoside
ENTP3_HUMAN
O75355
NP_001239.2.



triphosphate


NM_001248.2.



diphosphohydrolase 3


EPN2
Epsin-2
EPN2_HUMAN
O95208
NP_055779.2.






NM_014964.4.


ERO1LB
ERO1-like protein
ERO1B_HUMAN
Q86YB8
NP_063944.3.



beta


NM_019891.3.


ESYT2
Extended
ESYT2_HUMAN
A0FGR8
NP_065779.1.



synaptotagmin-2


NM_020728.2.


EXT1
Exostosin-1
EXT1_HUMAN
Q16394
NP_000118.2.






NM_000127.2.


FAM125A
Multivesicular body
F125A_HUMAN
Q96EY5
NP_612410.1.



subunit 12A


NM_138401.2.


FAM126A
Hyccin
HYCCI_HUMAN
Q9BYI3
NP_115970.2.






NM_032581.3.


FAM19A4
Protein FAM19A4
F19A4_HUMAN
Q96LR4
NP_001005527.1.






NM_001005527.2.






NP_872328.1.






NM_182522.4.


FAM20A
Protein FAM20A
FA20A_HUMAN
Q96MK3
NP_001230675.1.






NM_001243746.1.






NP_060035.2.






NM_017565.3.


FAM20B
Glycosaminoglycan
XYLK_HUMAN
O75063
NP_055679.1.



xylosylkinase


NM_014864.3.


FAM20C
Family with
DMP4_HUMAN
Q8IXL6
NP_064608.2



sequence similarity


NM_020223.3



20, member C


FAM3C
Protein FAM3C
FAM3C_HUMAN
Q92520
NP_001035109.1.






NM_001040020.1.






NP_055703.1.






NM_014888.2.


FAM75A6
Spermatogenesis-
S31A6_HUMAN
Q5VVP1
NP_001138668.1.



associated protein


NM_001145196.1.



31A6


FAM83F
Protein FAM83F
FA83F_HUMAN
Q8NEG4
NP_612444.2.






NM_138435.2.


FBXL2
F-box/LRR-repeat
FBXL2_HUMAN
Q9UKC9
NP_001165184.1.



protein 2


NM_001171713.1.






NP_036289.3.






NM_012157.3.


FGF12
Fibroblast growth
FGF12_HUMAN
P61328
NP_004104.3.



factor 12


NM_004113.5.






NP_066360.1.






NM_021032.4.


FGF19
Fibroblast growth
FGF19_HUMAN
O95750
NP_005108.1.



factor 19


NM_005117.2.


FKBP11
Peptidyl-prolyl cis-
FKB11_HUMAN
Q9NYL4
NP_001137253.1.



trans isomerase


NM_001143781.1.



FKBP11


NP_001137254.1.






NM_001143782.1.






NP_057678.1.






NM_016594.2.


FREM1
FRAS1-related
FREM1_HUMAN
Q5H8C1
NP_001171175.1.



extracellular matrix


NM_001177704.1.



protein 1


NP_659403.4.






NM_144966.5.


GALNT2
Polypeptide N-
GALT2_HUMAN
Q10471
NP_004472.1.



acetylgalactosaminyl-


NM_004481.3.



transferase 2


GAP43
Neuromodulin
NEUM_HUMAN
P17677
NP_001123536.1.






NM_001130064.1.






NP_002036.1.






NM_002045.3.


GLRX5
Glutaredoxin-
GLRX5_HUMAN
Q86SX6
NP_057501.2.



related protein 5,


NM_016417.2.



mitochondrial


GNPDA2
Glucosamine-6-
GNPI2_HUMAN
Q8TDQ7
NP_001257809.1.



phosphate


NM_001270880.1.



isomerase 2


NP_001257810.1.






NM_001270881.1.






NP_612208.1.






NM_138335.2.


GPR158
Probable G-protein
GP158_HUMAN
Q5T848
NP_065803.2.



coupled receptor


NM_020752.2.



158


GPRIN1
G protein-
GRIN1_HUMAN
Q7Z2K8
NP_443131.2.



regulated inducer


NM_052899.2.



of neurite



outgrowth 1


GREM1
Gremlin-1
GREM1_HUMAN
O60565
NP_001178252.1.






NM_001191323.1.






NP_037504.1.






NM_013372.6.


GREM2
Gremlin-2
GREM2_HUMAN
Q9H772
NP_071914.3.






M_022469.3.


GRK5
G protein-coupled
GRK5_HUMAN
P34947
NP_005299.1.



receptor kinase 5


NM_005308.2.


GUK1
Guanylate kinase
KGUA_HUMAN
Q16774
NP_000849.1.






NM_000858.5.






NP_001152862.1.






NM_001159390.1.






NP_001152863.1.






NM_001159391.1.






NP_001229768.1.






NM_001242839.1.


HERC4
Probable E3
HERC4_HUMAN
Q5GLZ8
NP_056416.2.



ubiquitin-protein


NM_015601.3.



ligase HERC4


NP_071362.1.






NM_022079.2.


HPCA
Neuron-specific
HPCA_HUMAN
P84074
NP_002134.2.



calcium-binding


NM_002143.2.



protein hippocalcin


HSP90B2P
Putative
ENPLL_HUMAN
Q58FF3
AY956768



endoplasmin-like


AAX38255.1.



protein


HSPA13
Heat shock 70 kDa
HSP13_HUMAN
P48723
NP_008879.3.



protein 13


NM_006948.4.


IDE
Insulin-degrading
IDE_HUMAN
P14735
NP_001159418.1.



enzyme


NM_001165946.1.






NP_004960.2.






NM_004969.3.


IGF1
Insulin-like growth
IGF1_HUMAN
P05019
NP_000609.1.



factor I


NM_000618.3.






NP_001104754.1.






NM_001111284.1.






NP_001104755.1.






NM_001111285.1.


IGFBP7
Insulin-like growth
IBP7_HUMAN
Q16270
NP_001544.1.



factor-binding


NM_001553.2.



protein 7


INS
Insulin-1
INS_HUMAN
P01308
NP_000198.1






NM_000207.2






NP_001172026.1






NM_001185097.1






NP_001172027.1






NM_001185098.1


IRS2
Insulin receptor
IRS2_HUMAN
Q9Y4H2
NP_003740.2.



substrate 2


NM_003749.2.


ITFG3
Protein ITFG3
ITFG3_HUMAN
Q9H0X4
NP_114428.1.






NM_032039.2.


ITM2B
Integral membrane
ITM2B_HUMAN
Q9Y287
NP_068839.1.



protein 2B


NM_021999.4.


ITPKB
Inositol-
IP3KB_HUMAN
P27987
NP_002212.3.



trisphosphate 3-


NM_002221.3.



kinase B


KIAA0564
von Willebrand
VWA8_HUMAN
A3KMH1
NP_001009814.1.



factor A domain-


NM_001009814.1.



containing protein 8


NP_055873.1.






NM_015058.1.


KIAA1324
UPF0577 protein
K1324_HUMAN
Q6UXG2
NP_001253977.1.



KIAA1324


NM_001267048.1.






NP_001253978.1.






NM_001267049.1.






NP_065826.2.






NM_020775.4.


KIDINS220
Kinase D-
KDIS_HUMAN
Q9ULH0
NP_065789.1.



interacting


NM_020738.2.



substrate of



220 kDa


LDLR
Low-density
LDLR_HUMAN
P01130
NP_000518.1



lipoprotein


NM_000527.4



receptor


NP_001182728.1






NM_001195799.1






NP_001182729.1






NM_001195800.1






NP_001182732.1






NM_001195803.1


LGALS8
Galectin-8
LEG8_HUMAN
O00214
NP_006490.3.






NM_006499.4.






NP_963837.1.






NM_201543.2.






NP_963838.1.






NM_201544.2.






NP_963839.1.






NM_201545.2.


LRRC8E
Leucine-rich
LRC8E_HUMAN
Q6NSJ5
NP_001255213.1.



repeat-containing


NM_001268284.1.



protein 8E


NP_001255214.1.






NM_001268285.1.






NP_079337.2.






NM_025061.4.


LSAMP
Limbic system-
LSAMP_HUMAN
Q13449
NP_002329.2.



associated


NM_002338.3.



membrane protein


MAP1B
Microtubule-
MAP1B_HUMAN
P46821
NP_005900.2.



associated protein


NM_005909.3.



1B


MBP
Myelin basic
MBP_HUMAN
P02686
NP_001020252.1.



protein


NM_001025081.1.






NP_001020261.1.






NM_001025090.1.






NP_001020263.1.






NM_001025092.1.






NP_001020271.1.






NM_001025100.1.






NP_001020272.1.






NM_001025101.1.






NP_002376.1.






NM_002385.2.


MCRS1
Microspherule
MCRS1_HUMAN
Q96EZ8
NP_001012300.1.



protein 1


NM_001012300.1.






NP_006328.2.






NM_006337.3.


MGAT1
Alpha-1,3-
MGAT1_HUMAN
P26572
NP_001108089.1



mannosyl-


NM_001114617.1



glycoprotein 2-beta-


NP_001108090.1



acetylglucosaminyl


NM_001114618.1



transferase


NP_001108091.1






NM_001114619.1






NP_001108092.1






NM_001114620.1






NP_002397.2






NM_002406.3


MIA3
Melanoma
MIA3_HUMAN
Q5JRA6
NP_940953.2.



inhibitory activity


NM_198551.2.



protein 3


MLN
Promotilin
MOTI_HUMAN
P12872
NP_001035198.1.






NM_001040109.1.






NP_001171627.1.






NM_001184698.1.






NP_002409.1.






NM_002418.2.


MPP2
MAGUK p55
MPP2_HUMAN
Q14168
NP_005365.3.



subfamily member 2


NM_005374.3.


MTHFD2
Bifunctional
MTDC_HUMAN
P13995
NP_006627.2.



methylenetetra-


NM_006636.3.



hydrofolate



dehydrogenase/



cyclohydrolase,



mitochondrial


MTUS1
Microtubule-
MTUS1_HUMAN
Q9ULD2
NP_001001924.1.



associated tumor


NM_001001924.2.



suppressor 1


NP_001001925.1.






NM_001001925.2.






NP_001001931.1.






NM_001001931.2.






NP_001159865.1.






NM_001166393.1.






NP_065800.1.






NM_020749.4.


MUC13
Mucin-13
MUC13_HUMAN
Q9H3R2
RefSeq NP_149038.3.






NM_033049.3.


MXRA7
Matrix-remodeling-
MXRA7_HUMAN
P84157
NP_001008528.1.



associated protein 7


NM_001008528.1.






NP_001008529.1.






NM_001008529.1.






NP_940932.2.






NM_198530.2.


NAAA
N-
NAAA_HUMAN
Q02083
NP_001035861.1.



acylethanolamine-


NM_001042402.1.



hydrolyzing acid


NP_055250.2.



amidase


NM_014435.3.


NAGLU
Alpha-
ANAG_HUMAN
P54802
NP_000254.2.



acetylglucosaminidase


NM_000263.3.


NCAM1
Neural cell
NCAM1_HUMAN
P13591
NP_000606.3.



adhesion molecule 1


NM_000615.6.






NP_001070150.1.






NM_001076682.3.






NP_001229537.1.






NM_001242608.1.






NP_851996.2.






NM_181351.4.


NECAB2
N-terminal EF-hand
NECA2_HUMAN
Q7Z6G3
NP_061938.2.



calcium-binding


NM_019065.2.



protein 2


NELL1
Protein kinase C-
NELL1_HUMAN
Q92832
NP_006148.2



binding protein


NM_006157.3



NELL1


NP_963845.1






NM_201551.1


NEO1
Neogenin
NEO1_HUMAN
Q92859
NP_001166094.1.






NM_001172623.1.






NP_002490.2.






NM_002499.3.


NFASC
Neurofascin
NFASC_HUMAN
O94856
NP_001005388.2.






NM_001005388.2.






NP_001005389.2.






NM_001005389.1.






NP_001153803.1.






NM_001160331.1.






NP_001153804.1.






NM_001160332.1.






NP_001153805.1.






NM_001160333.1.






NP_055905.2.






NM_015090.3.


NGRN
Neugrin
NGRN_HUMAN
Q9NPE2
NP_001028260.2.






NM_001033088.1.


NMU
Neuromedin U
NMU_HUMAN
P48645
NP_006672.1






NM_006681.2


NPTN
Neuroplastin
NPTN_HUMAN
Q9Y639
NP_001154835.1.






NM_001161363.1.






NP_001154836.1.






NM_001161364.1.






NP_036560.1.






NM_012428.3.






NP_059429.1.






NM_017455.3.


NPTX2
Neuronal
NPTX2_HUMAN
P47972
NP_002514.1.



pentraxin-2


NM_002523.2.


NPY
Pro-neuropeptide Y
NPY_HUMAN
P01303
NP_000896.1.






NM_000905.3.


NTNG1
Netrin-G1
NTNG1_HUMAN
Q9Y2I2
NP_001106697.1.






NM_001113226.1.






NP_001106699.1.






NM_001113228.1.






NP_055732.2.






NM_014917.2.


NXPH1
Neurexophilin-1
NXPH1_HUMAN
P58417
NP_689958.1.






NM_152745.2.


NXPH2
Neurexophilin-2
NXPH2_HUMAN
O95156
NP_009157.1.






NM_007226.2.


ODZ4
Teneurin-4
TEN4_HUMAN
Q6N022
NP_001092286.2.






NM_001098816.2.


P4HA2
Prolyl 4-
P4HA2_HUMAN
O15460
NP_001017973.1.



hydroxylase


NM_001017973.1.



subunit alpha-2


NP_001017974.1.






NM_001017974.1.






NP_001136070.1.






NM_001142598.1.






NP_001136071.1.






NM_001142599.1.






NP_004190.1.






NM_004199.2.


PAM
Peptidyl-glycine
AMD_HUMAN
P19021
NP_000910.2.



alpha-amidating


NM_000919.3.



monooxygenase


NP_001170777.1.






NM_001177306.1.






NP_620121.1.






NM_138766.2.






NP_620176.1.






NM_138821.2.






NP_620177.1.






NM_138822.2.


PAPPA2
Pappalysin-2
PAPP2_HUMAN
Q9BXP8
NP_064714.2.






NM_020318.2.






NP_068755.2.






NM_021936.2.


PCSK1
Neuroendocrine
NEC1_HUMAN
P29120
NP_000430.3.



convertase 1


NM_000439.4.


PCSK2
Neuroendocrine
NEC2_HUMAN
P16519
NP_001188457.1.



convertase 2


NM_001201528.1.






NP_001188458.1.






NM_001201529.1.






NP_002585.2.






NM_002594.3.


PDYN
Proenkephalin-B
PDYN_HUMAN
P01213
NP_001177821.1.






NM_001190892.1.






NP_001177827.1.






NM_001190898.2.






NP_001177828.1.






NM_001190899.2.






NP_001177829.1.






NM_001190900.1.






NP_077722.1.






NM_024411.4.


PIP4K2A
Phosphatidylinositol
PI42A_HUMAN
P48426
NP_005019.2.



5-phosphate 4-


NM_005028.4.



kinase type-2 alpha


PLBD2
Putative
PLBL2_HUMAN
Q8NHP8
NP_775813.2.



phospholipase B-like 2


NM_173542.3.


PLCB4
1-
PLCB4_HUMAN
Q15147
NP_000924.3.



phosphatidylinositol


NM_000933.3.



4,5-


NP_001166117.1.



bisphosphate


NM_001172646.1.



phosphodiesterase


NP_877949.2.



beta-4


NM_182797.2.


PLXNC1
Plexin-C1
PLXC1_HUMAN
O60486
NP_005752.1.






NM_005761.2.


PPAP2A
Lipid phosphate
LPP1_HUMAN
O14494
NP_003702.2.



phosphohydrolase 1


NM_003711.2.






NP_795714.1.






NM_176895.1.


PPFIA1
Liprin-alpha-1
LIPA1_HUMAN
Q13136
NP_003617.1.






NM_003626.3.






NP_803172.1.






NM_177423.2.


PPY
Pancreatic
PAHO_HUMAN
P01298
NP_002713.1



icosapeptide


NM_002722.3


PRNP
Major prion
PRIO_HUMAN
P04156
NP_000302.1.



protein


NM_000311.3.






NP_001073590.1.






NM_001080121.1.






NP_001073591.1.






NM_001080122.1.






NP_001073592.1.






NM_001080123.1.






NP_898902.1.






NM_183079.2.


PRSS3
Trypsin-3
TRY3_HUMAN
P35030
NP_001184026.2.






NM_001197097.2.






NP_002762.2.






NM_002771.3.






NP_031369.2.






NM_007343.3.


PTPRJ
Receptor-type
PTPRJ_HUMAN
Q12913
NP_001091973.1



tyrosine-protein


NM_001098503.1



phosphatase eta


NP_002834.3






NM_002843.3


PTPRN
Receptor-type
PTPRN_HUMAN
Q16849
NP_001186692.1.



tyrosine-protein


NM_001199763.1.



phosphatase-like N


NP_001186693.1.






NM_001199764.1.






NP_002837.1.






NM_002846.3.


PTPRN2
Receptor-type
PTPR2_HUMAN
Q92932
NP_002838.2.



tyrosine-protein


NM_002847.3.



phosphatase N2


NP_570857.2.






NM_130842.2.






NP_570858.2.






NM_130843.2.


PVR
Poliovirus receptor
PVR_HUMAN
P15151
NP_001129240.1.






NM_001135768.1.






NP_001129241.1.






NM_001135769.1.






NP_001129242.1.






NM_001135770.1.






NP_006496.3.






NM_006505.3.


QPCT
Glutaminyl-peptide
QPCT_HUMAN
Q16769
NP_036545.1.



cyclotransferase


NM_012413.3.


REG3G
Regenerating islet-
REG3G_HUMAN
Q6UW15
NP_001008388.1.



derived protein 3-


NM_001008387.2.



gamma


NP_001256969.1.






NM_001270040.1.






NP_940850.1.






NM_198448.3.


RGS7
Regulator of G-
RGS7_HUMAN
P49802
NP_002915.3.



protein signaling 7


NM_002924.4.


RIMBP2
RIMS-binding
RIMB2_HUMAN
O15034
NP_056162.4.



protein 2


NM_015347.4.


SCAMP1
Secretory carrier-
SCAM1_HUMAN
O15126
NP_004857.4.



associated


NM_004866.4.



membrane protein 1


SCAMP2
Secretory carrier-
SCAM2_HUMAN
O15127
NP_005688.2.



associated


NM_005697.3.



membrane protein 2


SCAMP3
Secretory carrier-
SCAM3_HUMAN
O14828
NP_005689.2.



associated


NM_005698.3.



membrane protein 3


NP_443069.1.






NM_052837.2.


SCG2
Secretogranin-2
SCG2_HUMAN
P13521
NP_003460.2.






NM_003469.4.


SCG3
Secretogranin-3
SCG3_HUMAN
Q8WXD2
NP_001158729.1.






NM_001165257.1.






NP_037375.2.






NM_013243.3.


SCG5
Neuroendocrine
7B2_HUMAN
P05408
NP_001138229.1.



protein 7B2


NM_001144757.1.






NP_003011.1.






NM_003020.3.


SCGN
Secretagogin
SEGN_HUMAN
O76038
NP_008929.2.






NM_006998.3.


SDK2
Protein sidekick-2
SDK2_HUMAN
Q58EX2
NP_001138424.1.






NM_001144952.1.


SEMA3A
Semaphorin-3A
SEM3A_HUMAN
Q14563
NP_006071.1.






NM_006080.2.


SEMA3C
Semaphorin-3C
SEM3C_HUMAN
Q99985
NP_006370.1.






NM_006379.3.


SEPT3
Neuronal-specific
SEPT3_HUMAN
Q9UH03
NP_061979.3



septin-3


NM_019106.5






NP_663786.2






NM_145733.2


SERPINB13
Serpin B13
SPB13_HUMAN
Q9UIV8
NP_036529.1






NM_012397.3


SERPINI1
Neuroserpin
NEUS_HUMAN
Q99574
NP_001116224.1.






NM_001122752.1.






NP_005016.1.






NM_005025.4.


SEZ6L2
Seizure 6-like
SE6L2_HUMAN
Q6UXD5
NP_001107571.1.



protein 2


NM_001114099.2.






NP_001107572.1.






NM_001114100.2.






NP_001230261.1.






NM_001243332.1.






NP_001230262.1.






NM_001243333.1.






NP_036542.1.






NM_012410.3.






NP_963869.2.






NM_201575.3.


SFT2D3
Vesicle transport
SFT2C_HUMAN
Q587I9
NP_116129.3.



protein SFT2C


NM_032740.3.


SHANK2
SH3 and multiple
SHAN2_HUMAN
Q9UPX8
NP_036441.2.



ankyrin repeat


NM_012309.3.



domains protein 2


SLC2A13
Proton myo-
MYCT_HUMAN
Q96QE2
NP_443117.3.



inositol


NM_052885.3.



cotransporter


SLC30A1
Zinc transporter 1
ZNT1_HUMAN
Q9Y6M5
NP_067017.2.






NM_021194.2.


SLC39A14
Zinc transporter
S39AE_HUMAN
Q15043
NP_001121903.1.



ZIP14


NM_001128431.2.






NP_001128625.1.






NM_001135153.1.






NP_001128626.1.






NM_001135154.1.






NP_056174.2.






NM_015359.4.


SLIT3
Slit homolog 3
SLIT3_HUMAN
O75094
NP_003053.1






NM_003062.2


SNAP25
Synaptosomal-
SNP25_HUMAN
P60880
NP_003072.2.



associated protein


NM_003081.3.



25


NP_570824.1.






NM_130811.2.


SNAPIN
SNARE-associated
SNAPN_HUMAN
O95295
NP_036569.1.



protein Snapin


NM_012437.5.


SORCS2
VPS10 domain-
SORC2_HUMAN
Q96PQ0
NP_065828.2.



containing receptor


NM_020777.2.



SorCS2


SPARCL1
SPARC-like protein 1
SPRL1_HUMAN
Q14515
NP_001121782.1.






NM_001128310.1.






NP_004675.3.






NM_004684.4.


SPCS3
Signal peptidase
SPCS3_HUMAN
P61009
NP_068747.1.



complex subunit 3


NM_021928.3.


SPOCK1
Testican-1
TICN1_HUMAN
Q08629
NP_004589.1.






NM_004598.3.


STK10
Serine/threonine-
STK10_HUMAN
O94804
NP_005981.3.



protein kinase 10


NM_005990.3.


STX1A
Syntaxin-1A
STX1A_HUMAN
Q16623
NP_001159375.1






NM_001165903.1






NP_004594.1






NM_004603.3


STX2
Syntaxin-2
STX2_HUMAN
P32856
NP_001971.2.






NM_001980.3.






NP_919337.1.






NM_194356.2.


SV2A
Synaptic vesicle
SV2A_HUMAN
Q7L0J3
NP_055664.3.



glycoprotein 2A


NM_014849.3.


SVIP
Small VCP/p97-
SVIP_HUMAN
Q8NHG7
NP_683691.1.



interacting protein


NM_148893.1.


SYN1
Synapsin-1
SYN1_HUMAN
P17600
NP_008881.2.






NM_006950.3.






NP_598006.1.






NM_133499.2.


SYNPO
Synaptopodin
SYNPO_HUMAN
Q8N3V7
NP_001103444.1.






NM_001109974.2.






NP_001159680.1.






NM_001166208.1.






NP_001159681.1.






NM_001166209.1.






NP_009217.3.






NM_007286.5.


SYT7
Synaptotagmin-7
SYT7_HUMAN
O43581
NP_004191.2.






NM_004200.3.


TACSTD2
Tumor-associated
TACD2_HUMAN
P09758
NP_002344.2.



calcium signal


NM_002353.2.



transducer 2


TCN2
Transcobalamin-2
TCO2_HUMAN
P20062
NP_000346.2.






NM_000355.3.






NP_001171655.1.






NM_001184726.1.


TLL2
Tolloid-like protein 2
TLL2_HUMAN
Q9Y6L7
NP_036597.1.






NM_012465.3.


TM9SF3
Transmembrane 9
TM9S3_HUMAN
Q9HD45
NP_064508.3.



superfamily


NM_020123.3.



member 3


TMEM106B
Transmembrane
T106B_HUMAN
Q9NUM4
NP_001127704.1.



protein 106B


NM_001134232.1.






NP_060844.2.






NM_018374.3.


TMEM119
Transmembrane
TM119_HUMAN
Q4V9L6
NP_859075.2.



protein 119


NM_181724.2.


TMEM132A
Transmembrane
T132A_HUMAN
Q24JP5
NP_060340.2.



protein 132A


NM_017870.3.






NP_821174.1.






NM_178031.2.


TMPRSS11F
Transmembrane
TM11F_HUMAN
Q6ZWK6
NP_997290.2.



protease serine 11F


NM_207407.2.


TNFSF11
Tumor necrosis
TNF11_HUMAN
O14788
NP_003692.1.



factor ligand


NM_003701.3.



superfamily


NP_143026.1.



member 11


NM_033012.3.


TNFSF4
Tumor necrosis
TNFL4_HUMAN
P23510
NP_003317.1.



factor ligand


NM_003326.3.



superfamily



member 4


TTC7B
Tetratricopeptide
TTC7B_HUMAN
Q86TV6
NP_001010854.1.



repeat protein 7B


NM_001010854.1.


TXNDC5
Thioredoxin
TXND5_HUMAN
Q8NBS9
NP_001139021.1.



domain-containing


NM_001145549.2.



protein 5


NP_110437.2.






NM_030810.3.


UBL3
Ubiquitin-like
UBL3_HUMAN
O95164
NP_009037.1.



protein 3


NM_007106.3.


UCHL1
Ubiquitin carboxyl-
UCHL1_HUMAN
P09936
NP_004172.2.



terminal hydrolase


NM_004181.4.



isozyme L1


VAMP4
Vesicle-associated
VAMP4_HUMAN
O75379
NP_001172056.1.



membrane protein 4


NM_001185127.1.






NP_003753.2.






NM_003762.4.


VAT1L
Synaptic vesicle
VAT1L_HUMAN
Q9HCJ6
NP_065978.1.



membrane protein


NM_020927.1.



VAT-1 homolog-like


VAV3
Guanine nucleotide
VAV3_HUMAN
Q9UKW4
NP_001073343.1.



exchange factor


NM_001079874.1.



VAV3


NP_006104.4.






NM_006113.4.


VGF
Neurosecretory
VGF_HUMAN
O15240
NP_003369.2.



protein VGF


NM_003378.3.


VWA5B2
von Willebrand
VW5B2_HUMAN
Q8N398
NP_612354.1.



factor A domain-


NM_138345.1.



containing protein



5B2


WFDC5
WAP four-disulfide
WFDC5_HUMAN
Q8TCV5
NP_663627.1.



core domain


NM_145652.3.



protein 5


WFS1
Wolframin
WFS1_HUMAN
O76024
NP_001139325.1.






NM_001145853.1.






NP_005996.2.






NM_006005.3.


WNT5A
Protein Wnt-5a
WNT5A_HUMAN
P41221
NP_001243034.1.






NM_001256105.1.






NP_003383.2.






NM_003392.4.


WNT9B
Protein Wnt-9b
WNT9B_HUMAN
O14905
NP_003387.1.






NM_003396.1.
















TABLE 2







β-Cell Function Markers of the Invention.











Marker
Protein

UNIPROT



Name
Description
UNIPROT_ID
ACCESSION
GENBANK ACCESSION





ABCC9
ATP-binding
ABCC9_HUMAN
O60706
NP_005682.2. NM_005691.2.



cassette sub-family


NP_064693.2. NM_020297.2.



C member 9


ASNS
Asparagine
ASNS_HUMAN
P08243
NP_001171546.1. NM_001178075.1.



synthetase


NP_001171547.1. NM_001178076.1.



[glutamine-


NP_001171548.1. NM_001178077.1.



hydrolyzing]


NP_001664.3. NM_001673.4.






NP_597680.2. NM_133436.3.






NP_899199.2. NM_183356.3.


GATC
Glutamyl-
GATC_HUMAN
O43716
NP_789788.1. NM_176818.2.



tRNA(Gln)



amidotransferase



subunit C,



mitochondrial


MMP7
Matrilysin
MMP7_HUMAN
P09237
NP_002414.1. NM_002423.3.


OLFM4
Olfactomedin-4
OLFM4_HUMAN
Q6UX06
NP_006409.3. NM_006418.4.


SERPINE1
Plasminogen
PAI1_HUMAN
P05121
NP_000593.1. NM_000602.4.



activator inhibitor 1


NP_001158885.1. NM_001165413.2.


SMPDL3B
Acid
ASM3B_HUMAN
Q92485
NP_001009568.1. NM_001009568.1.



sphingomyelinase-


NP_055289.2. NM_014474.2.



like



phosphodiesterase



3b


ADAM9
Disintegrin and
ADAM9_HUMAN
Q13443
NP_003807.1. NM_003816.2.



metalloproteinase



domain-containing



protein 9


C8orf55
UPF0670 protein
THEM6_HUMAN
Q8WUY1
NP_057731.1. NM_016647.2.



THEM6


CCL20
C-C motif
CCL20_HUMAN
P78556
NP_001123518.1. NM_001130046.1.



chemokine 20


NP_004582.1. NM_004591.2.


GDF15
Growth/
GDF15_HUMAN
Q99988
NP_004855.2. NM_004864.2.



differentiation



factor 15


IL32
Interleukin-32
IL32_HUMAN
P24001
NP_001012649.1. NM_001012631.1.






NP_001012650.1. NM_001012632.1.






NP_001012651.1. NM_001012633.1.






NP_001012652.1. NM_001012634.1.






NP_001012653.1. NM_001012635.1.






NP_001012736.1. NM_001012718.1.






NP_004212.4. NM_004221.4.


MMP14
Matrix
MMP14_HUMAN
P50281
NP_004986.1. NM_004995.2.



metalloproteinase-



14


SERPINB2
Plasminogen
PAI2_HUMAN
P05120
NP_001137290.1. NM_001143818.1.



activator inhibitor 2


NP_002566.1. NM_002575.2.


SPINT1
Kunitz-type
SPIT1_HUMAN
O43278
NP_001027539.1. NM_001032367.1.



protease inhibitor 1


NP_003701.1. NM_003710.3.






NP_857593.1. NM_181642.2.


TNFAIP2
Tumor necrosis
TNAP2_HUMAN
Q03169
NP_006282.2. NM_006291.2.



factor alpha-



induced protein 2


MMP1
Interstitial
MMP1_HUMAN
P03956
NP_002412.1. NM_002421.3.



collagenase


SPINT2
Kunitz-type
SPIT2_HUMAN
O43291
NP_001159575.1. NM_001166103.1.



protease inhibitor 2


NP_066925.1. NM_021102.3.


COL3A1
Collagen alpha-
CO3A1_HUMAN
P02461
NP_000081.1. NM_000090.3.



1(III) chain


YBX1
Nuclease-sensitive
YBOX1_HUMAN
P67809
NP_004550.2. NM_004559.3.



element-binding



protein 1


GHRL
Appetite-regulating
GHRL_HUMAN
Q9UBU3
NP_001128413.1. NM_001134941.1.



hormone


NP_001128416.1. NM_001134944.1.






NP_001128417.1. NM_001134945.1.






NP_001128418.1. NM_001134946.1.






NP_057446.1. NM_016362.3.


B4GALT1
Beta-1,4-
B4GT1_HUMAN
P15291
NP_001488.2. NM_001497.3.



galactosyltransferase 1


ACP2
Lysosomal acid
PPAL_HUMAN
P11117
NP_001601.1. NM_001610.2.



phosphatase


ACSL3
Long-chain-fatty-
ACSL3_HUMAN
O95573
NP_004448.2. NM_004457.3.



acid-CoA ligase 3


NP_976251.1. NM_203372.1.


ATP6AP2
Renin receptor
RENR_HUMAN
O75787
NP_005756.2. NM_005765.2.


B3GAT3
Galactosylgalactosyl-
B3GA3_HUMAN
O94766
NP_036332.2. NM_012200.3.



xylosylprotein 3-



beta-



glucuronosyltrans-



ferase 3


CA4
Carbonic
CAH4_HUMAN
P22748
NP_000708.1. NM_000717.3.



anhydrase 4


CAPNS1
Calpain small
CPNS1_HUMAN
P04632
NP_001003962.1. NM_001003962.1.



subunit 1


NP_001740.1. NM_001749.2.


CIB1
Calcium and
CIB1_HUMAN
Q99828
NP_006375.2. NM_006384.3.



integrin-binding



protein 1


CYB5R1
NADH-cytochrome
NB5R1_HUMAN
Q9UHQ9
NP_057327.2. NM_016243.2.



b5 reductase 1


EPHB2
Ephrin type-B
EPHB2_HUMAN
P29323
NP_004433.2. NM_004442.6.



receptor 2


NP_059145.2. NM_017449.3.


FUT3
Galactoside 3(4)-L-
FUT3_HUMAN
P21217
NP_000140.1. NM_000149.3.



fucosyltransferase


NP_001091108.1. NM_001097639.1.






NP_001091109.1. NM_001097640.1.






NP_001091110.1. NM_001097641.1.


FUT6
Alpha-(1,3)-
FUT6_HUMAN
P51993
NP_000141.1. NM_000150.2.



fucosyltransferase


NP_001035791.1. NM_001040701.1.


FXYD2
Sodium/potassium-
ATNG_HUMAN
P54710
NP_001671.2. NM_001680.4.



transporting


NP_067614.1. NM_021603.3.



ATPase subunit



gamma


HTATIP2
Oxidoreductase
HTAI2_HUMAN
Q9BUP3
NP_001091990.1. NM_001098520.1.



HTATIP2


NP_001091991.1. NM_001098521.1.






NP_001091992.1. NM_001098522.1.






NP_001091993.1. NM_001098523.1.






NP_006401.3. NM_006410.4.


LCN2
Neutrophil
NGAL_HUMAN
P80188
NP_005555.2. NM_005564.3.



gelatinase-



associated lipocalin


LMAN2
Vesicular integral-
LMAN2_HUMAN
Q12907
NP_006807.1. NM_006816.2.



membrane protein



VIP36


MAN1A2
Mannosyl-
MA1A2_HUMAN
O60476
NP_006690.1. NM_006699.3.



oligosaccharide



1,2-alpha-



mannosidase IB


PLSCR3
Phospholipid
PLS3_HUMAN
Q9NRY6
NP_001188505.1. NM_001201576.1.



scramblase 3


NP_065093.2. NM_020360.3.


PMVK
Phosphomevalonate
PMVK_HUMAN
Q15126
NP_006547.1. NM_006556.3.



kinase


PTTG1IP
Pituitary tumor-
PTTG_HUMAN
P53801
NP_004330.1. NM_004339.3.



transforming gene



1 protein-



interacting protein


TMED2
Transmembrane
TMED2_HUMAN
Q15363
NP_006806.1. NM_006815.3.



emp24 domain-



containing protein 2


VAMP1
Vesicle-associated
VAMP1_HUMAN
P23763
NP_055046.1. NM_014231.3.



membrane protein 1


NP_058439.1. NM_016830.2.






NP_954740.1. NM_199245.1.


VAMP7
Vesicle-associated
VAMP7_HUMAN
P51809
NP_001138621.1. NM_001145149.2.



membrane protein 7


NP_001172112.1. NM_001185183.1.






NP_005629.1. NM_005638.5.


ABHD12
Monoacylglycerol
ABD12_HUMAN
Q8N2K0
NP_001035937.1. NM_001042472.2.



lipase ABHD12


NP_056415.1. NM_015600.4.


ALG5
Dolichyl-phosphate
ALG5_HUMAN
Q9Y673
NP_001135836.1. NM_001142364.1.



beta-


NP_037470.1. NM_013338.4.



glucosyltransferase


ALOX12B
Arachidonate 12-
LX12B_HUMAN
O75342
NP_001130.1. NM_001139.2.



lipoxygenase, 12R-



type


AMPD3
AMP deaminase 3
AMPD3_HUMAN
Q01432
NP_000471.1. NM_000480.2.






NP_001020560.1. NM_001025389.1.






NP_001020561.1. NM_001025390.1.






NP_001165901.1. NM_001172430.1.






NP_001165902.1. NM_001172431.1.


API5
Apoptosis inhibitor 5
API5_HUMAN
Q9BZZ5
NP_001136402.1. NM_001142930.1.






NP_001136403.1. NM_001142931.1.






NP_001230676.1. NM_001243747.1.






NP_006586.1. NM_006595.3.


ARMC10
Armadillo repeat-
ARM10_HUMAN
Q8N2F6
NP_001154481.1. NM_001161009.2.



containing protein


NP_001154482.1. NM_001161010.2.



10


NP_001154483.1. NM_001161011.2.






NP_001154484.1. NM_001161012.2.






NP_001154485.1. NM_001161013.2.






NP_114111.2. NM_031905.4.


ARMCX3
Armadillo repeat-
ARMX3_HUMAN
Q9UH62
NP_057691.1. NM_016607.3.



containing X-linked


NP_808816.1. NM_177947.2.



protein 3


NP_808817.1. NM_177948.2.


ASPH
Aspartyl/asparaginyl
ASPH_HUMAN
Q12797
NP_001158222.1. NM_001164750.1.



beta-hydroxylase


NP_001158223.1. NM_001164751.1.






NP_001158225.1. NM_001164753.1.






NP_001158227.1. NM_001164755.1.






NP_001158228.1. NM_001164756.1.






NP_004309.2. NM_004318.3.






NP_064549.1. NM_020164.4.






NP_115855.1. NM_032466.3.






NP_115856.1. NM_032467.3.






NP_115857.1. NM_032468.4.


ATAD3A
ATPase family AAA
ATD3A_HUMAN
Q9NVI7
NP_001164006.1. NM_001170535.1.



domain-containing


NP_001164007.1. NM_001170536.1.



protein 3A


NP_060658.3. NM_018188.3.


ATAD3B
ATPase family AAA
ATD3B_HUMAN
Q5T9A4
NP_114127.3. NM_031921.4.



domain-containing



protein 3B


ATAD3C
ATPase family AAA
ATD3C_HUMAN
Q5T2N8
NP_001034300.2. NM_001039211.2.



domain-containing



protein 3C


BRP44
Mitochondrial
MPC2_HUMAN
O95563
NP_001137146.1. NM_001143674.2.



pyruvate carrier 2


NP_056230.1. NM_015415.3.


C19orf68
Uncharacterized
CS068_HUMAN
Q86XI8
BC043386



protein C19orf68


AAH43386.1.


CCDC56
Cytochrome C
COA3_HUMAN
Q9Y2R0
NP_001035521.1. NM_001040431.1.



oxidase assembly



factor 3 homolog,



mitochondrial


CEACAM7
Carcinoembryonic
CEAM7_HUMAN
Q14002
NP_008821.1. NM_006890.3.



antigen-related cell



adhesion molecule 7


CISD2
CDGSH iron-sulfur
CISD2_HUMAN
Q8N5K1
NP_001008389.1. NM_001008388.4.



domain-containing



protein 2


CPM
Carboxypeptidase M
CBPM_HUMAN
P14384
NP_001005502.1. NM_001005502.2.






NP_001865.1. NM_001874.4.






NP_938079.1. NM_198320.3.


CTBP1
C-terminal-binding
CTBP1_HUMAN
Q13363
NP_001012632.1. NM_001012614.1.



protein 1


NP_001319.1. NM_001328.2.


CTBP2
C-terminal-binding
CTBP2_HUMAN
P56545
NP_001077383.1. NM_001083914.1.



protein 2


NP_001320.1. NM_001329.2.






NP_073713.2. NM_022802.2.


CUZD1
CUB and zona
CUZD1_HUMAN
Q86UP6
NP_071317.2. NM_022034.5.



pellucida-like



domain-containing



protein 1


DDRGK1
DDRGK domain-
DDRGK_HUMAN
Q96HY6
NP_076424.1. NM_023935.1.



containing protein 1


DHRS7B
Dehydrogenase/
DRS7B_HUMAN
Q6IAN0
NP_056325.2. NM_015510.4.



reductase SDR family



member 7B


EDF1
Endothelial
EDF1_HUMAN
060869
NP_003783.1. NM_003792.2.



differentiation-


NP_694880.1. NM_153200.1.



related factor 1


ELMOD2
ELMO domain-
ELMD2_HUMAN
Q8IZ81
NP_714913.1. NM_153702.3.



containing protein 2


ENAH
Protein enabled
ENAH_HUMAN
Q8N8S7
NP_001008493.1. NM_001008493.1.



homolog


NP_060682.2. NM_018212.4.


FAM174A
Membrane protein
F174A_HUMAN
Q8TBP5
NP_940909.1. NM_198507.1.



FAM174A


FAP
Seprase
SEPR_HUMAN
Q12884
NP_004451.2. NM_004460.2.


FER
Tyrosine-protein
FER_HUMAN
P16591
NP_005237.2. NM_005246.2.



kinase Fer


GAD2
Glutamate
DCE2_HUMAN
Q05329
NP_000809.1. NM_000818.2.



decarboxylase 2


NP_001127838.1. NM_001134366.1.


GAPDHS
Glyceraldehyde-3-
G3PT_HUMAN
O14556
NP_055179.1. NM_014364.4.



phosphate



dehydrogenase,



testis-specific


HK2
Hexokinase-2
HXK2_HUMAN
P52789
NP_000180.2. NM_000189.4.


HK3
Hexokinase-3
HXK3_HUMAN
P52790
NP_002106.2. NM_002115.2.


HKDC1
Putative
HKDC1_HUMAN
Q2TB90
NP_079406.3. NM_025130.3.



hexokinase HKDC1


HSD17B2
Estradiol 17-beta-
DHB2_HUMAN
P37059
NP_002144.1. NM_002153.2.



dehydrogenase 2


HSF2BP
Heat shock factor
HSF2B_HUMAN
O75031
NP_008962.1. NM_007031.1.



2-binding protein


IFNGR1
Interferon gamma
INGR1_HUMAN
P15260
NP_000407.1. NM_000416.2.



receptor 1


ILF2
Interleukin
ILF2_HUMAN
Q12905
NP_001254738.1. NM_001267809.1.



enhancer-binding


NP_004506.2. NM_004515.3.



factor 2


ITGB6
Integrin beta-6
ITB6_HUMAN
P18564
NP_000879.2. NM_000888.3.


KIAA0090
ER membrane
EMC1_HUMAN
Q8N766
NP_001258356.1. NM_001271427.1.



protein complex


NP_001258357.1. NM_001271428.1.



subunit 1


NP_001258358.1. NM_001271429.1.






NP_055862.1. NM_015047.2.


KIAA0776
E3 UFM1-protein
UFL1_HUMAN
O94874
NP_056138.1. NM_015323.4.



ligase 1


KIAA2013
Uncharacterized
K2013_HUMAN
Q8IYS2
NP_612355.1. NM_138346.2.



protein KIAA2013


KLRAQ1
Protein
PPR21_HUMAN
Q6ZMI0
NP_001129101.1. NM_001135629.2.



phosphatase 1


NP_001180404.1. NM_001193475.1.



regulatory subunit


NP_694539.1. NM_152994.4.



21


LAMTOR1
Ragulator complex
LTOR1_HUMAN
Q6IAA8
NP_060377.1. NM_017907.2.



protein LAMTOR1


LAMTOR2
Ragulator complex
LTOR2_HUMAN
Q9Y2Q5
NP_001138736.1. NM_001145264.1.



protein LAMTOR2


NP_054736.1. NM_014017.3.


LAMTOR3
Ragulator complex
LTOR3_HUMAN
Q9UHA4
NP_068805.1. NM_021970.3.



protein LAMTOR3


LRRC63
Leucine-rich
LRC63_HUMAN
Q05C16
CAI12166.2.



repeat-containing


BC030276



protein 63


AAH30276.1.


MFN2
Mitofusin-2
MFN2_HUMAN
O95140
NP_001121132.1. NM_001127660.1.






NP_055689.1. NM_014874.3.


MGAT4B
Alpha-1,3-
MGT4B_HUMAN
Q9UQ53
NP_055090.1. NM_014275.4.



mannosyl-


NP_463459.1. NM_054013.3.



glycoprotein 4-beta



acetylglucosaminyl



transferase B


MLF2
Myeloid leukemia
MLF2_HUMAN
Q15773
NP_005430.1. NM_005439.2.



factor 2


MOGS
Mannosyl-
MOGS_HUMAN
Q13724
NP_001139630.1. NM_001146158.1.



oligosaccharide


NP_006293.2. NM_006302.2.



glucosidase


MTMR11
Myotubularin-
MTMRB_HUMAN
A4FU01
NP_001139334.1. NM_001145862.1.



related protein 11


NP_870988.2. NM_181873.3.


MTX1
Metaxin-1
MTX1_HUMAN
Q13505
NP_002446.2. NM_002455.3.






NP_942584.1. NM_198883.2.


NCEH1
Neutral cholesterol
NCEH1_HUMAN
Q6PIU2
NP_001139748.1. NM_001146276.1.



ester hydrolase 1


NP_001139749.1. NM_001146277.1.






NP_001139750.1. NM_001146278.1.






NP_065843.3. NM_020792.4.


OCIAD2
OCIA domain-
OCAD2_HUMAN
Q56VL3
NP_001014446.1. NM_001014446.1.



containing protein 2


NP_689611.1. NM_152398.2.


PDE8B
High affinity cAMP-
PDE8B_HUMAN
O95263
NP_001025022.1. NM_001029851.2.



specific and IBMX-


NP_001025023.1. NM_001029852.2.



insensitive 3′,5′-


NP_001025024.1. NM_001029853.2.



cyclic


NP_001025025.1. NM_001029854.2.



phosphodiesterase


NP_003710.1. NM_003719.3.



8B


PFKFB1
6-phosphofructo-2-
F261_HUMAN
P16118
NP_002616.2. NM_002625.2.



kinase/fructose-



2,6-bisphosphatase 1


PIGK
GPI-anchor
GPI8_HUMAN
Q92643
NP_005473.1. NM_005482.2.



transamidase


PLEKHH2
Pleckstrin
PKHH2_HUMAN
Q8IVE3
NP_742066.2. NM_172069.3.



homology domain-



containing family H



member 2


PRUNE2
Protein prune
PRUN2_HUMAN
Q8WUY3
NP_056040.2. NM_015225.2.



homolog 2


RDH11
Retinol
RDH11_HUMAN
Q8TC12
NP_057110.3. NM_016026.3.



dehydrogenase 11


RIC8A
Synembryn-A
RIC8A_HUMAN
Q9NPQ8
NP_068751.4. NM_021932.4.


RUFY3
Protein RUFY3
RUFY3_HUMAN
Q7L099
NP_001032519.1. NM_001037442.2.






NP_001124181.1. NM_001130709.1.






NP_055776.1. NM_014961.3.


SDK1
Protein sidekick-1
SDK1_HUMAN
Q7Z5N4
NP_689957.3. NM_152744.3.


SORCS3
VPS10 domain-
SORC3_HUMAN
Q9UPU3
NP_055793.1. NM_014978.1.



containing receptor



SorCS3


SPTLC1
Serine
SPTC1_HUMAN
O15269
NP_006406.1. NM_006415.2.



palmitoyltransferase 1


NP_847894.1. NM_178324.1.


STOML3
Stomatin-like
STML3_HUMAN
Q8TAV4
NP_001137505.1. NM_001144033.1.



protein 3


NP_660329.1. NM_145286.2.


STX1B
Syntaxin-1B
STX1B_HUMAN
P61266
NP_443106.1. NM_052874.3.


SYT5
Synaptotagmin-5
SYT5_HUMAN
O00445
NP_003171.2. NM_003180.2.


TBL2
Transducin beta-
TBL2_HUMAN
Q9Y4P3
NP_036585.1. NM_012453.2.



like protein 2


TGOLN2
Trans-Golgi
TGON2_HUMAN
O43493
NP_001193769.1. NM_001206840.1.



network integral


NP_001193770.1. NM_001206841.1.



membrane protein 2


NP_001193773.1. NM_001206844.1.






NP_006455.2. NM_006464.3.


THSD7A
Thrombospondin
THS7A_HUMAN
Q9UPZ6
NP_056019.1. NM_015204.2.



type-1 domain-



containing protein



7A


TMCO1
Transmembrane
TMCO1_HUMAN
Q9UM00
NP_061899.2. NM_019026.4.



and coiled-coil



domain-containing



protein 1


TMEM123
Porimin
PORIM_HUMAN
Q8N131
NP_443164.2. NM_052932.2.


TMPRSS13
Transmembrane
TMPSD_HUMAN
Q9BYE2
NP_001193719.1. NM_001206790.1.



protease serine 13


NP_001231924.1. NM_001244995.1.


TMX4
Thioredoxin-
TMX4_HUMAN
Q9H1E5
NP_066979.2. NM_021156.2.



related



transmembrane



protein 4


TNPO2
Transportin-2
TNPO2_HUMAN
O14787
NP_001129667.1. NM_001136195.1.






NP_001129668.1. NM_001136196.1.






NP_038461.2. NM_013433.4.


TPBG
Trophoblast
TPBG_HUMAN
Q13641
NP_001159864.1. NM_001166392.1.



glycoprotein


NP_006661.1. NM_006670.4.


TRIM42
Tripartite motif-
TRI42_HUMAN
Q8IWZ5
NP_689829.3. NM_152616.4.



containing protein



42


TTC37
Tetratricopeptide
TTC37_HUMAN
Q6PGP7
NP_055454.1. NM_014639.3.



repeat protein 37


USP9X
Probable ubiquitin
USP9X_HUMAN
Q93008
NP_001034679.2. NM_001039590.2.



carboxyl-terminal


NP_001034680.2. NM_001039591.2.



hydrolase FAF-X


VAPB
Vesicle-associated
VAPB_HUMAN
O95292
NP_001182606.1. NM_001195677.1.



membrane protein-


NP_004729.1. NM_004738.4.



associated protein



B/C


VNN2
Vascular non-
VNN2_HUMAN
O95498
NP_001229279.1. NM_001242350.1.



inflammatory


NP_004656.2. NM_004665.2.



molecule 2


NP_511043.1. NM_078488.1.


VPS26B
Vacuolar protein
VP26B_HUMAN
Q4G0F5
NP_443107.1. NM_052875.3.



sorting-associated



protein 26B


YTHDF2
YTH domain family
YTHD2_HUMAN
Q9Y5A9
NP_001166299.1. NM_001172828.1.



protein 2


NP_001166599.1. NM_001173128.1.






NP_057342.2. NM_016258.2.


ZFPL1
Zinc finger protein-
ZFPL1_HUMAN
O95159
NP_006773.2. NM_006782.3.



like 1
















TABLE 3







Therapeutic Efficacy Markers of the Invention.











Marker
Protein

UNIPROT
GENBANK


Name
Description
UNIPROT _ID
ACCESSION
ACCESSION





A2M
Alpha-2-
A2MG_HUMAN
P01023
NP_000005.2



macroglobulin


NM_000014.4


ABI3BP
Target of Nesh-SH3
TARSH_HUMAN
Q7Z7G0
NP_056244.2






NM_015429.3


ACE
Angiotensin-
ACE_HUMAN
P12821
NP_000780.1



converting enzyme


NM_000789.3






NP_001171528.1






NM_001178057.1






NP_690043.1






NM_152830.2


ACTN1
Alpha-actinin-1
ACTN1_HUMAN
P12814
NP_001093.1






NM_001102.3






NP_001123476.1






NM_001130004.1






NP_001123477.1






NM_001130005.1


AFM
Afamin
AFAM_HUMAN
P43652
NP_001124.1






NM_001133.2


AGT
Angiotensinogen
ANGT_HUMAN
P01019
NP_000020.1






NM_000029.3


ALCAM
CD166 antigen
CD166_HUMAN
Q13740
NP_001230209.1






NM_001243280.1






NP_001618.2






NM_001627.3


ALDOB
Fructose-
ALDOB_HUMAN
P05062
NP_000026.2



bisphosphate


NM_000035.3



aldolase B





AMBP
Protein AMBP
AMBP_HUMAN
P02760
NP_001624.1






NM_001633.3


ANPEP
Aminopeptidase N
AMPN_HUMAN
P15144
NP_001141.2






NM_001150.2


AOC3
Membrane primary
AOC3_HUMAN
Q16853
NP_003725.1



amine oxidase


NM_003734.2


APOA1
Apolipoprotein
APOA1_HUMAN
P02647
NP_000030.1



A-I


NM_000039.1


APOA2
Apolipoprotein
APOA2_HUMAN
P02652
NP_001634.1



A-II


NM_001643.1


APOA4
Apolipoprotein
APOA4_HUMAN
P06727
M13654; ; AAA51744.1;



A-IV


X13629; CAA31955.1;






BC074764; AAH74764.1;






BC113594; AAI13595.1;






BC113596; AAI13597.1;






M14566; AAA51748.1


APOB
Apolipoprotein
APOB_HUMAN
P04114
NP_000375.2



B-100


NM_000384.2


APOC2
Apolipoprotein
APOC2_HUMAN
P02655
NP_000474.2



C-II


NM_000483.4


APOC3
Apolipoprotein
APOC3_HUMAN
P02656
NP_000031.1



C-III


NM_000040.1


APOC4
Apolipoprotein
APOC4_HUMAN
P55056
NP_001637.1



C-IV


NM_001646.2


APOE
Apolipoprotein
APOE_HUMAN
P02649
NP_000032.1



E


NM_000041.2


ARHGDIA
Rho GDP-
GDIR1_HUMAN
P52565
NP_001172006.1



dissociation


NM_001185077.1



inhibitor 1


NP_001172007.1






NM_001185078.1






NP_004300.1






NM_004309.4


ARHGDIB
Rho GDP-
GDIR2_HUMAN
P52566
NP_001166.3



dissociation


NM_001175.4



inhibitor 2





ATRN
Attractin
ATRN_HUMAN
O75882
NP_001193976.1






NM_001207047.1






NP_647537.1






NM_139321.2






NP_647538.1






NM_139322.2.


AZGP1
Zinc-alpha-2-
ZA2G_HUMAN
P25311
NP_001176.1



glycoprotein


NM_001185.3


B2M
Beta-2-
B2MG_HUMAN
P61769
NP_004039.1



microglobulin


NM_004048.2


BST1
ADP-ribosyl cyclase
BST1_HUMAN
Q10588
NP_004325.2



2


NM_004334.2


BTD
Biotinidase
BTD_HUMAN
P43251
NP_000051.1






NM_000060.2


C1RL
Complement C1r
C1RL_HUMAN
Q9NZP8
NP_057630.2



subcomponent-like


NM_016546.2



protein





C4BPA
C4b-binding
C4BPA_HUMAN
P04003
NP_000706.1



protein alpha chain


NM_000715.3


C9
Complement
CO9_HUMAN
P02748
NP_001728.1



component C9


NM_001737.3


CA2
Carbonic
CAH2_HUMAN
P00918
NP_000058.1



anhydrase 2


NM_000067.2


CACNA2D1
Voltage-dependent
CA2D1_HUMAN
P54289
NP_000713.2



calcium channel


NM_000722.2



subunit alpha-2/






delta-1





CAP1
Adenylyl cyclase-
CAP1_HUMAN
Q01518
NP_001099000.1



associated protein 1


NM_001105530.1






NP_006358.1






NM_006367.3


CD14
Monocyte
CD14_HUMAN
P08571
NP_000582.1



differentiation


NM_000591.3



antigen CD14


NP_001035110.1






NM_001040021.2






NP_001167575.1






NM_001174104.1






NP_001167576.1






NM_001174105.1


CD163
Scavenger receptor
C163A_HUMAN
Q86VB7
NP_004235.4



cysteine-rich type 1


NM_004244.5



protein M130


NP_981961.2






NM_203416.3


CD5L
CD5 antigen-like
CD5L_HUMAN
O43866
NP_005885.1






NM_005894.2


CDH5
Cadherin-5
CADH5_HUMAN
P33151
NP_001786.2






NM_001795.3


CFD
Complement factor
FAD_HUMAN
P00746
NP_001919.2



D


NM_001928.2


CLEC3B
Tetranectin
TETN_HUMAN
P05452
NP_003269.2






NM_003278.2


CLSTN1
Calsyntenin-1
CSTN1_HUMAN
O94985
NP_001009566.1






NM_001009566.1






NP_055759.3






NM_014944.3


CNDP1
Beta-Ala-His
CNDP1_HUMAN
Q96KN2
NP_116038.4



dipeptidase


NM_032649.5


CNN2
Calponin-2
CNN2_HUMAN
Q99439
NP_004359.1






NM_004368.2






NP_958434.1






NM_201277.1


COL6A1
Collagen alpha-
CO6A1_HUMAN
P12109
NP_001839.2



1(VI) chain


NM_001848.2


COL6A3
Collagen alpha-
CO6A3_HUMAN
P12111
NP_004360.2



3(VI) chain


NM_004369.3






NP_476505.3






NM_057164.4






NP_476508.2






NM_057167.3


CORO1A
Coronin-1A
COR1A_HUMAN
P31146
NP_001180262.1






NM_001193333.2






NP_009005.1






NM_007074.3


CPB2
Carboxypeptidase
CBPB2_HUMAN
Q96IY4
NP_001863.2



B2


NM_001872.3


CRP
C-reactive protein
CRP_HUMAN
P02741
NP_000558.2






NM_000567.2


CRTAC1
Cartilage acidic
CRAC1_HUMAN
Q9NQ79
NP_001193457.1



protein 1


NM_001206528.2






NP_060528.3






NM_018058.6


CTBS
Di--acetylchitobiase
DIAC_HUMAN
Q01459
NP_004379.1






NM_004388.2


DBH
Dopamine beta-
DOPO_HUMAN
P09172
NP_000778.3



hydroxylase


NM_000787.3


DBNL
Drebrin-like
DBNL_HUMAN
Q9UJU6
NP_001014436.1



protein


NM_001014436.2






NP_001116428.1






NM_001122956.1






NP_054782.2






NM_014063.6


DPEP2
Dipeptidase 2
DPEP2_HUMAN
Q9H4A9
NP_071750.1






NM_022355.3


ECM1
Extracellular matrix
ECM1_HUMAN
Q16610
NP_001189787.1



protein 1


NM_001202858.1






NP_004416.2






NM_004425.3






NP_073155.2






NM_022664.2


EFEMP1
EGF-containing
FBLN3_HUMAN
Q12805
NP_001034437.1



fibulin-like


NM_001039348.2



extracellular matrix


NP_001034438.1



protein 1


NM_001039349.2


ENPP2
Ectonucleotide
ENPP2_HUMAN
Q13822
NP_001035181.1



pyrophosphatase/


NM_001040092.2



phosphodiesterase


NP_001124335.1



family member 2


NM_001130863.2






NP_006200.3






NM_006209.4


ERP29
Endoplasmic
ERP29_HUMAN
P30040
NP_006808.1



reticulum resident


NM_006817.3



protein 29





F10
Coagulation factor
FA10_HUMAN
P00742
NP_000495.1



X


NM_000504.3


F11
Coagulation factor
FA11_HUMAN
P03951
NP_000119.1



XI


NM_000128.3


F12
Coagulation factor
FA12_HUMAN
P00748
NP_000496.2



XII


NM_000505.3


F13B
Coagulation factor
F13B_HUMAN
P05160
NP_001985.2



XIII B chain


NM_001994.2


F9
Coagulation factor
FA9_HUMAN
P00740
NP_000124.1



IX


NM_000133.3


FAM3B
Protein FAM3B
FAM3B_HUMAN
P58499
NP_478066.3






NM_058186.3






NP_996847.1






NM_206964.1


FBLN1
Fibulin-1
FBLN1_HUMAN
P23142
NP_001987.2






NM_001996.3






NP_006476.2






NM_006485.3






NP_006477.2






NM_006486.2






NP_006478.2






NM_006487.2


FCGBP
IgGFc-binding
FCGBP_HUMAN
Q9Y6R7
NP_003881.2



protein


NM_003890.2


FERMT3
Fermitin family
URP2_HUMAN
Q86UX7
NP_113659.3



homolog 3


NM_031471.5






NP_848537.1






NM_178443.2


FETUB
Fetuin-B
FETUB_HUMAN
Q9UGM5
NP_055190.2






NM_014375.2


FLNA
Filamin-A
FLNA_HUMAN
P21333
NP_001104026.1






NM_001110556.1






NP_001447.2






NM_001456.3


FN1
Fibronectin
FINC_HUMAN
P02751
NP_002017.1






NM_002026.2






NP_473375.2






NM_054034.2






NP_997639.1






NM_212474.1






NP_997641.1






NM_212476.1






NP_997643.1






NM_212478.1






NP_997647.1






NM_212482.1


FTH1
Ferritin heavy chain
FRIH_HUMAN
P02794
NP_002023.2






NM_002032.2


FTL
Ferritin light chain
FRIL_HUMAN
P02792
NP_000137.2






NM_000146.3


GAPDH
Glyceraldehyde-3-
G3P_HUMAN
P04406
NP_001243728.1



phosphate


NM_001256799.1



dehydrogenase


NP_002037.2






NM_002046.4


GPLD1
Phosphatidylinositol-
PHLD_HUMAN
P80108
NP_001494.2



glycan-specific


NM_001503.3



phospholipase D





GPX3
Glutathione
GPX3_HUMAN
P22352
NP_002075.2



peroxidase 3


NM_002084.3


GSN
Gelsolin
GELS_HUMAN
P06396
NP_000168.1






NM_000177.4






NP_001121134.1






NM_001127662.1






NP_001121135.2






NM_001127663.1






NP_001121136.1






NM_001127664.1






NP_001121137.1






NM_001127665.1






NP_001121138.1






NM_001127666.1






NP_001121139.1






NM_001127667.1






NP_001244958.1






NM_001258029.1






NP_937895.1






NM_198252.2


GSTP1
Glutathione S-
GSTP1_HUMAN
P09211
NP_000843.1



transferase P


NM_000852.3


HABP2
Hyaluronan-
HABP2_HUMAN
Q14520
NP_001171131.1



binding protein 2


NM_001177660.1






NP_004123.1






NM_004132.3


HBA1
Hemoglobin
HBA_HUMAN
P69905
NP_000508.1


and
subunit alpha


NM_000517.4


HBA2



NP_000549.1






NM_000558.3


HBD
Hemoglobin
HBD_HUMAN
P02042
NP_000510.1



subunit delta


NM_000519.3


HGFAC
Hepatocyte growth
HGFA_HUMAN
Q04756
NP_001519.1



factor activator


NM_001528.2


HPR
Haptoglobin-
HPTR_HUMAN
P00739
NP_066275.3



related protein


NM_020995.3


HSPA8
Heat shock cognate
HSP7C_HUMAN
P11142
NP_006588.1



71 kDa protein


NM_006597.4






NP_694881.1






NM_153201.2


HSPB1
Heat shock protein
HSPB1_HUMAN
P04792
NP_001531.1



beta-1


NM_001540.3


HSPG2
Basement
PGBM_HUMAN
P98160
NP_005520.4



membrane-specific


NM_005529.5



heparan sulfate






proteoglycan core






protein





IGF2
Insulin-like growth
IGF2_HUMAN
P01344
NP_000603.1



factor II


NM_000612.4






NP_001007140.2






NM_001007139.4


IGF2R
Cation-
MPRI_HUMAN
P11717
NP_000867.2



independent


NM_000876.2



mannose-6-






phosphate






receptor





IGFALS
Insulin-like growth
ALS_HUMAN
P35858
NP_004961.1



factor-binding


NM_004970.2



protein complex






acid labile subunit





IGFBP3
Insulin-like growth
IBP3_HUMAN
P17936
NP_000589.2



factor-binding


NM_000598.4



protein 3


NP_001013416.1






NM_001013398.1


IGFBP4
Insulin-like growth
P4_HUMAN
P22692
NP_001543.2



factor-binding


NM_001552.2



protein 4





IGLL5
Immunoglobulin
IGLL5_HUMAN
B9A064
NP_001171597.1



lambda-like


NM_001178126.1



polypeptide 5





IL18BP
lnterleukin-18-
I18BP_HUMAN
O95998
NP_001034748.1



binding protein


NM_001039659.1






NP_001034749.1






NM_001039660.1






NP_001138527.1






NM_001145055.1






NP_001138529.1






NM_001145057.1






NP_005690.2






NM_005699.3






NP_766630.2






NM_173042.2






NP_766632.2






NM_173044.2


IL1RAP
Interleukin-1
IL1AP_HUMAN
Q9NPH3
NP_001161400.1



receptor accessory


NM_001167928.1



protein


NP_001161401.1






NM_001167929.1






NP_001161402.1






NM_001167930.1






NP_001161403.1






NM_001167931.1






NP_002173.1






NM_002182.3






NP_608273.1






NM_134470.3


ILK
Integrin-linked
ILK_HUMAN
Q13418
NP_001014794.1.



protein kinase


NM_001014794.1.






NP_001014795.1.






NM_001014795.1.






NP_004508.1.






NM_004517.2.


ISLR
Immunoglobulin
ISLR_HUMAN
O14498
NP_005536.1



superfamily


NM_005545.3



containing leucine-


NP_958934.1



rich repeat protein


NM_201526.1


ITIH3
Inter-alpha-trypsin
ITIH3_HUMAN
Q06033
NP_002208.3



inhibitor heavy


NM_002217.3



chain H3





ITIH4
Inter-alpha-trypsin
ITIH3_HUMAN
Q14624
NP_002208.3



inhibitor heavy


NM_002217.3



chain H3





LBP
Lipopolysaccharide-
LBP_HUMAN
P18428
NP_004130.2



binding protein


NM_004139.3


LCAT
Phosphatidylcholine-
LCAT_HUMAN
P04180
NP_000220.1



sterol


NM_000229.1



acyltransferase





LRG1
Leucine-rich alpha-
A2GL_HUMAN
P02750
NP_443204.1



2-glycoprotein


NM_052972.2


LUM
Lumican
LUM_HUMAN
P51884
NP_002336.1






NM_002345.3


LYVE1
Lymphatic vessel
LYVE1_HUMAN
Q9Y5Y7
NP_006682.2



endothelial


NM_006691.3



hyaluronic acid






receptor 1





MASP1
Mannan-binding
MASP1_HUMAN
P48740
NP_001027019.1



lectin serine


NM_001031849.2



protease 1


NP_001870.3






NM_001879.5






NP_624302.1






NM_139125.3


MBL2
Mannose-binding
MBL2_HUMAN
P11226
NP_000233.1



protein C


NM_000242.2


MCAM
Cell surface
MUC18_HUMAN
P43121
NP_006491.2



glycoprotein


NM_006500.2



MUC18





MINPP1
Multiple inositol
MINP1_HUMAN
Q9UNW1
NP_001171588.1



polyphosphate


NM_001178117.1



phosphatase 1


NP_001171589.1






NM_001178118.1






NP_004888.2






NM_004897.4


MST1
Hepatocyte growth
HGFL_HUMAN
P26927
NP_066278.3



factor-like protein


NM_020998.3


NID1
Nidogen-1
NID1_HUMAN
P14543
NP_002499.2






NM_002508.2


ORM1
Alpha-1-acid
A1AG1_HUMAN
P02763
NP_000598.2



glycoprotein 1


NM_000607.2


ORM2
Alpha-1-acid
A1AG2_HUMAN
P19652
NP_000599.1



glycoprotein 2


NM_000608.2


PCOLCE
Procollagen C-
PCOC1_HUMAN
Q15113
NP_002584.2



endopeptidase


NM_002593.3



enhancer 1





PDIA3
Protein disulfide-
PDIA3_HUMAN
P30101
NP_005304.3



isomerase A3


NM_005313.4


PDIA6
Protein disulfide-
PDIA6_HUMAN
Q15084
NP_005733.1



isomerase A6


NM_005742.2


PDLIM1
PDZ and LIM
PDLI1_HUMAN
O00151
NP_066272.1



domain protein 1


NM_020992.3


PEPD
Xaa-Pro
PEPD_HUMAN
P12955
NP_000276.2



dipeptidase


NM_000285.3






NP_001159528.1






NM_001166056.1






NP_001159529.1






NM_001166057.1


PFN1
Profilin-1
PROF1_HUMAN
P07737
NP_005013.1






NM_005022.3


PGLYRP2
N-acetylmuramoyl-
PGRP2_HUMAN
Q96PD5
NP_443122.3



L-alanine amidase


NM_052890.3


PKM2
Pyruvate kinase
KPYM_HUMAN
P14618
NP_001193725.1



isozymes M1/M2


NM_001206796.1






NP_001193726.1






NM_001206797.1






NP_001193727.1






NM_001206798.1






NP_001193728.1






NM_001206799.1






NP_002645.3






NM_002654.4






NP_872270.1






NM_182470.2






NP_872271.1






NM_182471.2


PLEK
Pleckstrin
PLEK_HUMAN
P08567
NP_002655.2






NM_002664.2


PPIA
Peptidyl-prolyl cis-
PPIA_HUMAN
P62937
NP_066953.1



trans isomerase A


NM_021130.3


PRDX2
Peroxiredoxin-2
PRDX2_HUMAN
P32119
NP_005800.3






NM_005809.4






NP_859428.1






NM_181738.1


PROCR
Endothelial protein
EPCR_HUMAN
Q9UNN8
NP_006395.2



C receptor


NM_006404.3


PROS1
Vitamin K-
PROS_HUMAN
P07225
NP_000304.2



dependent protein S


NM_000313.3


PROZ
Vitamin K-
PROZ_HUMAN
P22891
NP_001243063.1



dependent protein Z


NM_001256134.1






NP_003882.1






NM_003891.2


QSOX1
Sulfhydryl oxidase 1
QSOX1_HUMAN
O00391
NP_001004128.1






NM_001004128.2






NP_002817.2






NM_002826.4


RNASE1
Ribonuclease
RNAS1_HUMAN
P07998
NP_002924.1



pancreatic


NM_002933.4






NP_937875.1






NM_198232.2






NP_937877.1






NM_198234.2






NP_937878.1






NM_198235.2


S100A9
Protein S100-A9
S10A9_HUMAN
P06702
NP_002956.1






NM_002965.3


SAA4
Serum amyloid A-4
SAA4_HUMAN
P35542
NP_006503.2



protein


NM_006512.3


SELL
L-selectin
LYAM1_HUMAN
P14151
NP_000646.2






NM_000655.4


SERPINA1
Alpha-1-antitrypsin
A1AT_HUMAN
P01009
NP_000286.3






NM_000295.4






NP_001002235.1






NM_001002235.2






NP_001002236.1






NM_001002236.2






NP_001121172.1






NM_001127700.1






NP_001121173.1






NM_001127701.1






NP_001121174.1






NM_001127702.1






NP_001121175.1






NM_001127703.1






NP_001121176.1






NM_001127704.1






NP_001121177.1






NM_001127705.1






NP_001121178.1






NM_001127706.1






NP_001121179.1






NM_001127707.1


SERPINA4
Kallistatin
KAIN_HUMAN
P29622
NP_006206.2






NM_006215.2


SERPINA6
Corticosteroid-
CBG_HUMAN
P08185
NP_001747.2



binding globulin


NM_001756.3


SERPINA7
Thyroxine-binding
THBG_HUMAN
P05543
NP_000345.2



globulin


NM_000354.5


SERPIND1
Heparin cofactor 2
HEP2_HUMAN
P05546
NP_000176.2






NM_000185.3


SLC3A2
4F2 cell-surface
4F2_HUMAN
P08195
NP_001012680.1



antigen heavy


NM_001012662.2



chain


NP_001012682.1






NM_001012664.2






NP_001013269.1






NM_001013251.2






NP_002385.3






NM_002394.5


SNCA
Alpha-synuclein
SYUA_HUMAN
P37840
NP_000336.1






NM_000345.3






NP_001139526.1






NM_001146054.1






NP_001139527.1






NM_001146055.1






NP_009292.1






NM_007308.2


SOD3
Extracellular
SODE_HUMAN
P08294
NP_003093.2



superoxide


NM_003102.2



dismutase [Cu—Zn]





SPP2
Secreted
SPP24_HUMAN
Q13103
NP_008875.1



phosphoprotein 24


NM_006944.2


TAGLN2
Transgelin-2
TAGL2_HUMAN
P37802
NP_003555.1






NM_003564.1


TF
Serotransferrin
TRFE_HUMAN
P02787
NP_001054.1






NM_001063.3


THBS1
Thrombospondin-1
TSP1_HUMAN
P07996
NP_003237.2






NM_003246.2


TLN1
Talin-1
TLN1_HUMAN
Q9Y490
NP_006280.3






NM_006289.3


TNC
Tenascin
TENA_HUMAN
P24821
NP_002151.2






NM_002160.3


TNXB
Tenascin-X
TENX_HUMAN
P22105
NP_061978.6






NM_019105.6






NP_115859.2






NM_032470.3


TPM1
Tropomyosin
TPM1_HUMAN
P09493
NP_000357.3



alpha-1 chain


NM_000366.5






NP_001018005.1






NM_001018005.1






NP_001018006.1






NM_001018006.1






NP_001018007.1






NM_001018007.1






NP_001018008.1






NM_001018008.1


TPM3
Tropomyosin
TPM3_HUMAN
P06753
NP_001036816.1



alpha-3 chain


NM_001043351.1






NP_001036817.1






NM_001043352.1






NP_689476.2






NM_152263.2






NP_705935.1






NM_153649.3


TPM4
Tropomyosin
TPM4_HUMAN
P67936
NP_001138632.1



alpha-4 chain


NM_001145160.1






NP_003281.1






NM_003290.2


TTR
Transthyretin
TTHY_HUMAN
P02766
NP_000362.1-






NM_000371.3


VCAM1
Vascular cell
VCAM1_HUMAN
P19320
NP_001069.1



adhesion protein 1


NM_001078.3






NP_001186763.1






NM_001199834.1






NP_542413.1






NM_080682.2


VCL
Vinculin
VINC_HUMAN
P18206
NP_003364.1






NM_003373.3






NP_054706.1






NM_014000.2


VWF
von Willebrand
VWF_HUMAN
P04275
NP_000543.2



factor


NM_000552.3


YWHAZ
14-3-3 protein
1433Z_HUMAN
P63104
NP_001129171.1



zeta/delta


NM_001135699.1






NP_001129172.1






NM_001135700.1






NP_001129173.1






NM_001135701.1






NP_001129174.1






NM_001135702.1






NP_003397.1






NM_003406.3






NP_663723.1






NM_145690.2


FGG
Fibrinogen gamma
FIBG_HUMAN
P02679
NP_000500.2



chain


NM_000509.4






NP_068656.2






NM_021870.2


NEO1
Neogenin
NEO1_HUMAN
Q92859
NP_001166094.1






NM_001172623.1






NP_002490.2






NM_002499.3


FAM20C
Extracellular
DMP4_HUMAN
Q8IXL6
NP_064608.2



serine/threonine


NM_020223.3



protein kinase






Fam20C





NCAM1
Neural cell
NCAM1_HUMAN
P13591
NP_000606.3



adhesion molecule


NM_000615.6



1


NP_001070150.1






NM_001076682.3






NP_001229537.1






NM_001242608.1






NP_851996.2






NM_181351.4


PTPRJ
Receptor-type
PTPRJ_HUMAN
Q12913
NP_001091973.1



tyrosine-protein


NM_001098503.1



phosphatase eta


NP_002834.3






NM_002843.3









In certain aspects of the invention, a single marker (e.g., any one of the markers listed in Tables 1-3) may be used in the methods and compositions of the invention. For example, in one embodiment, the marker for use in the methods and compositions of the invention is USP9X. In one embodiment, the marker is SEPT3. In one embodiment, the marker is DAG1. In one embodiment, the marker is PTPRJ. In one embodiment, the marker is CPM. In one embodiment, the marker is SERPINB13. In one embodiment, the marker is LDLR. In one embodiment, the marker is MMP7. In one embodiment, the marker is BTC. In one embodiment, the marker is PPY. In one embodiment, the marker is INS.


In some embodiments, the methods may further comprise determining the level of a marker selected from the group consisting of the markers listed in Table 1-3. In other embodiments, the methods may further comprise determining the level of a marker selected from the group consisting of CSTF3, NELL1, SLIT3, LAMTOR2, MGAT4B, TMPRSS11F, ATAD3B, PTPRN, WNT9B, FUT6, B4GALT1, FAM20C, CNTN1, MGAT1, STX1A, NMU, CD59, CASR, and CPE.


In other aspects of the invention, more than one marker, e.g., a plurality of markers, e.g., two, three, four, five, six, seven, eight, nine, ten, eleven, or more markers, may be used in the methods and compositions of the invention. For example, in one embodiment, the markers for use in the methods and compositions of the invention include USP9X and SEPT3. In one embodiment, the markers include USP9X and INS. In one embodiment, the markers include SEPT3 and INS. In one embodiment, the markers include, SERPINB13 and INS. In one embodiment, the markers include PPY and DAG1. In one embodiment, the markers include PPY and BTC. In one embodiment, the markers include USP9X, SEPT3, and DAG1. In one embodiment, the markers include USP9X, SEPT3, and PTPRJ. In one embodiment, the markers include USP9X, SEPT3, and CPM. In one embodiment, the markers include USP9X, SEPT3, and SERPINB13. In one embodiment, the markers include USP9X, SEPT3, and LDLR. In one embodiment, the markers include USP9X, SEPT3, and MMP7. In one embodiment, the markers include USP9X, SEPT3, and BTC. In one embodiment, the markers include USP9X, SEPT3, and PPY. In one embodiment, the markers include USP9X, SEPT3, and INS. In one embodiment, the markers include BTC, MMP7, and PPY. In one embodiment, the markers include PPY, SEPT3, and PTPRJ. In one embodiment, the markers include CPM, INS, MMP7, and LDLR.


In some embodiments, the methods may further comprise determining the level of a marker selected from the group consisting of the markers listed in Table 1-3. In other embodiments, the methods may further comprise determining the level of a marker selected from the group consisting of CSTF3, NELL1, SLIT3, LAMTOR2, MGAT4B, TMPRSS11F, ATAD3B, PTPRN, WNT9B, FUT6, B4GALT1, FAM20C, CNTN1, MGAT1, STX1A, NMU, CD59, CASR, and CPE. For example, in one embodiment, the markers for use in the methods and compositions of the invention include USP9X, SEPT3, and CSTF3. In one embodiment, the markers include USP9X, SEPT3, and NELL1. In one embodiment, the markers include USP9X, SEPT3, and SLIT3. In one embodiment, the markers include USP9X, SEPT3, and LAMTOR2. In one embodiment, the markers include USP9X, SEPT3, and MGAT4B. In one embodiment, the markers include USP9X, SEPT3, and TMPRSS11F. In one embodiment, the markers include USP9X, SEPT3, and, ATAD3B. In one embodiment, the markers include USP9X, SEPT3, and PTPRN. In one embodiment, the markers include USP9X, SEPT3, and WNT9B. In one embodiment, the markers include USP9X, SEPT3, and FUT6. In one embodiment, the markers include USP9X, SEPT3, and B4GALT1. In one embodiment, the markers include USP9X, SEPT3, and FAM20C. In one embodiment, the markers include USP9X, SEPT3, and CNTN1. In one embodiment, the markers include USP9X, SEPT3, and MGAT1. In one embodiment, the markers include USP9X, SEPT3, and STX1A. In one embodiment, the markers include USP9X, SEPT3, and NMU. In one embodiment, the markers include USP9X, SEPT3, and CD59. In one embodiment, the markers include USP9X, SEPT3, and CASR. In one embodiment, the markers include USP9X, SEPT3, and CPE. In one embodiment, the markers include USP9X, INS, and CSTF3. In one embodiment, the markers include USP9X, INS, and NELL1. In one embodiment, the markers include USP9X, INS, and SLIT3. In one embodiment, the markers include USP9X, INS, and LAMTOR2. In one embodiment, the markers include USP9X, INS, and MGAT4B. In one embodiment, the markers include USP9X, INS, and TMPRSS11F. In one embodiment, the markers include USP9X, INS, and, ATAD3B. In one embodiment, the markers include USP9X, INS, and PTPRN. In one embodiment, the markers include USP9X, INS, and WNT9B. In one embodiment, the markers include USP9X, INS, and FUT6. In one embodiment, the markers include USP9X, INS, and B4GALT1. In one embodiment, the markers include USP9X, INS, and FAM20C. In one embodiment, the markers include USP9X, INS, and CNTN1. In one embodiment, the markers include USP9X, INS, and MGAT1. In one embodiment, the markers include USP9X, INS, and STX1A. In one embodiment, the markers include USP9X, INS, and NMU. In one embodiment, the markers include USP9X, INS, and CD59. In one embodiment, the markers include USP9X, INS, and CASR. In one embodiment, the markers include USP9X, INS, and CPE. In one embodiment, the markers include SEPT3, INS, and CSTF3. In one embodiment, the markers include SEPT3, INS, and NELL1. In one embodiment, the markers include SEPT3, INS, and SLIT3. In one embodiment, the markers include SEPT3, INS, and LAMTOR2. In one embodiment, the markers include SEPT3, INS, and MGAT4B. In one embodiment, the markers include SEPT3, INS, and TMPRSS11F. In one embodiment, the markers include SEPT3, INS, and, ATAD3B. In one embodiment, the markers include SEPT3, INS, and PTPRN. In one embodiment, the markers include SEPT3, INS, and WNT9B. In one embodiment, the markers include SEPT3, INS, and FUT6. In one embodiment, the markers include SEPT3, INS, and B4GALT1. In one embodiment, the markers include SEPT3, INS, and FAM20C. In one embodiment, the markers include SEPT3, INS, and CNTN1. In one embodiment, the markers include SEPT3, INS, and MGAT1. In one embodiment, the markers include SEPT3, INS, and STX1A. In one embodiment, the markers include SEPT3, INS, and NMU. In one embodiment, the markers include SEPT3, INS, and CD59. In one embodiment, the markers include SEPT3, INS, and CASR. In one embodiment, the markers include SEPT3, INS, and CPE. In one embodiment, the markers include SERPINB13, INS, and CSTF3. In one embodiment, the markers include SERPINB13, INS, and NELL1. In one embodiment, the markers include SERPINB13, INS, and SLIT3. In one embodiment, the markers include SERPINB13, INS, and LAMTOR2. In one embodiment, the markers include SERPINB13, INS, and MGAT4B. In one embodiment, the markers include SERPINB13, INS, and TMPRSS11F. In one embodiment, the markers include SERPINB13, INS, and, ATAD3B. In one embodiment, the markers include SERPINB13, INS, and PTPRN. In one embodiment, the markers include SERPINB13, INS, and WNT9B. In one embodiment, the markers include SERPINB13, INS, and FUT6. In one embodiment, the markers include SERPINB13, INS, and B4GALT1. In one embodiment, the markers include SERPINB13, INS, and FAM20C. In one embodiment, the markers include SERPINB13, INS, and CNTN1. In one embodiment, the markers include SERPINB13, INS, and MGAT1. In one embodiment, the markers include SERPINB13, INS, and STX1A. In one embodiment, the markers include SERPINB13, INS, and NMU. In one embodiment, the markers include SERPINB13, INS, and CD59. In one embodiment, the markers include SERPINB13, INS, and CASR. In one embodiment, the markers include SERPINB13, INS, and CPE. In one embodiment, the markers include PPY, DAG1, and CSTF3. In one embodiment, the markers include PPY, DAG1, and NELL1. In one embodiment, the markers include PPY, DAG1, and SLIT3. In one embodiment, the markers include PPY, DAG1, and LAMTOR2. In one embodiment, the markers include PPY, DAG1, and MGAT4B. In one embodiment, the markers include PPY, DAG1, and TMPRSS11F. In one embodiment, the markers include PPY, DAG1, and, ATAD3B. In one embodiment, the markers include PPY, DAG1, and PTPRN. In one embodiment, the markers include PPY, DAG1, and WNT9B. In one embodiment, the markers include PPY, DAG1, and FUT6. In one embodiment, the markers include PPY, DAG1, and B4GALT1. In one embodiment, the markers include PPY, DAG1, and FAM20C. In one embodiment, the markers include PPY, DAG1, and CNTN1. In one embodiment, the markers include PPY, DAG1, and MGAT1. In one embodiment, the markers include PPY, DAG1, and STX1A. In one embodiment, the markers include PPY, DAG1, and NMU. In one embodiment, the markers include PPY, DAG1, and CD59. In one embodiment, the markers include PPY, DAG1, and CASR. In one embodiment, the markers include PPY, DAG1, and CPE. In one embodiment, the markers include PPY, BTC, and CSTF3. In one embodiment, the markers include PPY, BTC, and NELL1. In one embodiment, the markers include PPY, BTC, and SLIT3. In one embodiment, the markers include PPY, BTC, and LAMTOR2. In one embodiment, the markers include PPY, BTC, and MGAT4B. In one embodiment, the markers include PPY, BTC, and TMPRSS11F. In one embodiment, the markers include PPY, BTC, and, ATAD3B. In one embodiment, the markers include PPY, BTC, and PTPRN. In one embodiment, the markers include PPY, BTC, and WNT9B. In one embodiment, the markers include PPY, BTC, and FUT6. In one embodiment, the markers include PPY, BTC, and B4GALT1. In one embodiment, the markers include PPY, BTC, and FAM20C. In one embodiment, the markers include PPY, BTC, and CNTN1. In one embodiment, the markers include PPY, BTC, and MGAT1. In one embodiment, the markers include PPY, BTC, and STX1A. In one embodiment, the markers include PPY, BTC, and NMU. In one embodiment, the markers include PPY, BTC, and CD59. In one embodiment, the markers include PPY, BTC, and CASR. In one embodiment, the markers include PPY, BTC, and CPE. In one embodiment, the markers include USP9X, SEPT3, DAG1, and CSTF3. In one embodiment, the markers include USP9X, SEPT3, DAG1, and NELL1. In one embodiment, the markers include USP9X, SEPT3, DAG1, and SLIT3. In one embodiment, the markers include USP9X, SEPT3, DAG1, and LAMTOR2. In one embodiment, the markers include USP9X, SEPT3, DAG1, and MGAT4B. In one embodiment, the markers include USP9X, SEPT3, DAG1, and TMPRSS11F. In one embodiment, the markers include USP9X, SEPT3, DAG1, and, ATAD3B. In one embodiment, the markers include USP9X, SEPT3, DAG1, and PTPRN. In one embodiment, the markers include USP9X, SEPT3, DAG1, and WNT9B. In one embodiment, the markers include USP9X, SEPT3, DAG1, and FUT6. In one embodiment, the markers include USP9X, SEPT3, DAG1, and B4GALT1. In one embodiment, the markers include USP9X, SEPT3, DAG1, and FAM20C. In one embodiment, the markers include USP9X, SEPT3, DAG1, and CNTN1. In one embodiment, the markers include USP9X, SEPT3, DAG1, and MGAT1. In one embodiment, the markers include USP9X, SEPT3, DAG1, and STX1A. In one embodiment, the markers include USP9X, SEPT3, DAG1, and NMU. In one embodiment, the markers include USP9X, SEPT3, DAG1, and CD59. In one embodiment, the markers include USP9X, SEPT3, DAG1, and CASR. In one embodiment, the markers include USP9X, SEPT3, DAG1, and CPE. In one embodiment, the markers include USP9X, SEPT3, PTPRJ, and CSTF3. In one embodiment, the markers include USP9X, SEPT3, PTPRJ, and NELL1. In one embodiment, the markers include USP9X, SEPT3, PTPRJ, and SLIT3. In one embodiment, the markers include USP9X, SEPT3, PTPRJ, and LAMTOR2. In one embodiment, the markers include USP9X, SEPT3, PTPRJ, and MGAT4B. In one embodiment, the markers include USP9X, SEPT3, PTPRJ, and TMPRSS11F. In one embodiment, the markers include USP9X, SEPT3, PTPRJ, and, ATAD3B. In one embodiment, the markers include USP9X, SEPT3, PTPRJ, and PTPRN. In one embodiment, the markers include USP9X, SEPT3, PTPRJ, and WNT9B. In one embodiment, the markers include USP9X, SEPT3, PTPRJ, and FUT6. In one embodiment, the markers include USP9X, SEPT3, PTPRJ, and B4GALT1. In one embodiment, the markers include USP9X, SEPT3, PTPRJ, and FAM20C. In one embodiment, the markers include USP9X, SEPT3, PTPRJ, and CNTN1. In one embodiment, the markers include USP9X, SEPT3, PTPRJ, and MGAT1. In one embodiment, the markers include USP9X, SEPT3, PTPRJ, and STX1A. In one embodiment, the markers include USP9X, SEPT3, PTPRJ, and NMU. In one embodiment, the markers include USP9X, SEPT3, PTPRJ, and CD59. In one embodiment, the markers include USP9X, SEPT3, PTPRJ, and CASR. In one embodiment, the markers include USP9X, SEPT3, PTPRJ, and CPE. In one embodiment, the markers include USP9X, SEPT3, CPM, and CSTF3. In one embodiment, the markers include USP9X, SEPT3, CPM, and NELL1. In one embodiment, the markers include USP9X, SEPT3, CPM, and SLIT3. In one embodiment, the markers include USP9X, SEPT3, CPM, and LAMTOR2. In one embodiment, the markers include USP9X, SEPT3, CPM, and MGAT4B. In one embodiment, the markers include USP9X, SEPT3, CPM, and TMPRSS11F. In one embodiment, the markers include USP9X, SEPT3, CPM, and, ATAD3B. In one embodiment, the markers include USP9X, SEPT3, CPM, and PTPRN. In one embodiment, the markers include USP9X, SEPT3, CPM, and WNT9B. In one embodiment, the markers include USP9X, SEPT3, CPM, and FUT6. In one embodiment, the markers include USP9X, SEPT3, CPM, and B4GALT1. In one embodiment, the markers include USP9X, SEPT3, CPM, and FAM20C. In one embodiment, the markers include USP9X, SEPT3, CPM, and CNTN1. In one embodiment, the markers include USP9X, SEPT3, CPM, and MGAT1. In one embodiment, the markers include USP9X, SEPT3, CPM, and STX1A. In one embodiment, the markers include USP9X, SEPT3, CPM, and NMU. In one embodiment, the markers include USP9X, SEPT3, CPM, and CD59. In one embodiment, the markers include USP9X, SEPT3, CPM, and CASR. In one embodiment, the markers include USP9X, SEPT3, CPM, and CPE. In one embodiment, the markers include USP9X, SEPT3, SERPINB13, and CSTF3. In one embodiment, the markers include USP9X, SEPT3, SERPINB13, and NELL1. In one embodiment, the markers include USP9X, SEPT3, SERPINB13, and SLIT3. In one embodiment, the markers include USP9X, SEPT3, SERPINB13, and LAMTOR2. In one embodiment, the markers include USP9X, SEPT3, SERPINB13, and MGAT4B. In one embodiment, the markers include USP9X, SEPT3, SERPINB13, and TMPRSS11F. In one embodiment, the markers include USP9X, SEPT3, SERPINB13, and, ATAD3B. In one embodiment, the markers include USP9X, SEPT3, SERPINB13, and PTPRN. In one embodiment, the markers include USP9X, SEPT3, SERPINB13, and WNT9B. In one embodiment, the markers include USP9X, SEPT3, SERPINB13, and FUT6. In one embodiment, the markers include USP9X, SEPT3, SERPINB13, and B4GALT1. In one embodiment, the markers include USP9X, SEPT3, SERPINB13, and FAM20C. In one embodiment, the markers include USP9X, SEPT3, SERPINB13, and CNTN1. In one embodiment, the markers include USP9X, SEPT3, SERPINB13, and MGAT1. In one embodiment, the markers include USP9X, SEPT3, SERPINB13, and STX1A. In one embodiment, the markers include USP9X, SEPT3, SERPINB13, and NMU. In one embodiment, the markers include USP9X, SEPT3, SERPINB13, and CD59. In one embodiment, the markers include USP9X, SEPT3, SERPINB13, and CASR. In one embodiment, the markers include USP9X, SEPT3, SERPINB13, and CPE. In one embodiment, the markers include USP9X, SEPT3, LDLR, and CSTF3. In one embodiment, the markers include USP9X, SEPT3, LDLR, and NELL1. In one embodiment, the markers include USP9X, SEPT3, LDLR, and SLIT3. In one embodiment, the markers include USP9X, SEPT3, LDLR, and LAMTOR2. In one embodiment, the markers include USP9X, SEPT3, LDLR, and MGAT4B. In one embodiment, the markers include USP9X, SEPT3, LDLR, and TMPRSS11F. In one embodiment, the markers include USP9X, SEPT3, LDLR, and, ATAD3B. In one embodiment, the markers include USP9X, SEPT3, LDLR, and PTPRN. In one embodiment, the markers include USP9X, SEPT3, LDLR, and WNT9B. In one embodiment, the markers include USP9X, SEPT3, LDLR, and FUT6. In one embodiment, the markers include USP9X, SEPT3, LDLR, and B4GALT1. In one embodiment, the markers include USP9X, SEPT3, LDLR, and FAM20C. In one embodiment, the markers include USP9X, SEPT3, LDLR, and CNTN1. In one embodiment, the markers include USP9X, SEPT3, LDLR, and MGAT1. In one embodiment, the markers include USP9X, SEPT3, LDLR, and STX1A. In one embodiment, the markers include USP9X, SEPT3, LDLR, and NMU. In one embodiment, the markers include USP9X, SEPT3, LDLR, and CD59. In one embodiment, the markers include USP9X, SEPT3, LDLR, and CASR. In one embodiment, the markers include USP9X, SEPT3, LDLR, and CPE. In one embodiment, the markers include USP9X, SEPT3, MMP7, and CSTF3. In one embodiment, the markers include USP9X, SEPT3, MMP7, and NELL1. In one embodiment, the markers include USP9X, SEPT3, MMP7, and SLIT3. In one embodiment, the markers include USP9X, SEPT3, MMP7, and LAMTOR2. In one embodiment, the markers include USP9X, SEPT3, MMP7, and MGAT4B. In one embodiment, the markers include USP9X, SEPT3, MMP7, and TMPRSS11F. In one embodiment, the markers include USP9X, SEPT3, MMP7, and, ATAD3B. In one embodiment, the markers include USP9X, SEPT3, MMP7, and PTPRN. In one embodiment, the markers include USP9X, SEPT3, MMP7, and WNT9B. In one embodiment, the markers include USP9X, SEPT3, MMP7, and FUT6. In one embodiment, the markers include USP9X, SEPT3, MMP7, and B4GALT1. In one embodiment, the markers include USP9X, SEPT3, MMP7, and FAM20C. In one embodiment, the markers include USP9X, SEPT3, MMP7, and CNTN1. In one embodiment, the markers include USP9X, SEPT3, MMP7, and MGAT1. In one embodiment, the markers include USP9X, SEPT3, MMP7, and STX1A. In one embodiment, the markers include USP9X, SEPT3, MMP7, and NMU. In one embodiment, the markers include USP9X, SEPT3, MMP7, and CD59. In one embodiment, the markers include USP9X, SEPT3, MMP7, and CASR. In one embodiment, the markers include USP9X, SEPT3, MMP7, and CPE. In one embodiment, the markers include USP9X, SEPT3, BTC, and CSTF3. In one embodiment, the markers include USP9X, SEPT3, BTC, and NELL1. In one embodiment, the markers include USP9X, SEPT3, BTC, and SLIT3. In one embodiment, the markers include USP9X, SEPT3, BTC, and LAMTOR2. In one embodiment, the markers include USP9X, SEPT3, BTC, and MGAT4B. In one embodiment, the markers include USP9X, SEPT3, BTC, and TMPRSS11F. In one embodiment, the markers include USP9X, SEPT3, BTC, and, ATAD3B. In one embodiment, the markers include USP9X, SEPT3, BTC, and PTPRN. In one embodiment, the markers include USP9X, SEPT3, BTC, and WNT9B. In one embodiment, the markers include USP9X, SEPT3, BTC, and FUT6. In one embodiment, the markers include USP9X, SEPT3, BTC, and B4GALT1. In one embodiment, the markers include USP9X, SEPT3, BTC, and FAM20C. In one embodiment, the markers include USP9X, SEPT3, BTC, and CNTN1. In one embodiment, the markers include USP9X, SEPT3, BTC, and MGAT1. In one embodiment, the markers include USP9X, SEPT3, BTC, and STX1A. In one embodiment, the markers include USP9X, SEPT3, BTC, and NMU. In one embodiment, the markers include USP9X, SEPT3, BTC, and CD59. In one embodiment, the markers include USP9X, SEPT3, BTC, and CASR. In one embodiment, the markers include USP9X, SEPT3, BTC, and CPE. In one embodiment, the markers include USP9X, SEPT3, PPY, and CSTF3. In one embodiment, the markers include USP9X, SEPT3, PPY, and NELL1. In one embodiment, the markers include USP9X, SEPT3, PPY, and SLIT3. In one embodiment, the markers include USP9X, SEPT3, PPY, and LAMTOR2. In one embodiment, the markers include USP9X, SEPT3, PPY, and MGAT4B. In one embodiment, the markers include USP9X, SEPT3, PPY, and TMPRSS11F. In one embodiment, the markers include USP9X, SEPT3, PPY, and, ATAD3B. In one embodiment, the markers include USP9X, SEPT3, PPY, and PTPRN. In one embodiment, the markers include USP9X, SEPT3, PPY, and WNT9B. In one embodiment, the markers include USP9X, SEPT3, PPY, and FUT6. In one embodiment, the markers include USP9X, SEPT3, PPY, and B4GALT1. In one embodiment, the markers include USP9X, SEPT3, PPY, and FAM20C. In one embodiment, the markers include USP9X, SEPT3, PPY, and CNTN1. In one embodiment, the markers include USP9X, SEPT3, PPY, and MGAT1. In one embodiment, the markers include USP9X, SEPT3, PPY, and STX1A. In one embodiment, the markers include USP9X, SEPT3, PPY, and NMU. In one embodiment, the markers include USP9X, SEPT3, PPY, and CD59. In one embodiment, the markers include USP9X, SEPT3, PPY, and CASR. In one embodiment, the markers include USP9X, SEPT3, PPY, and CPE. In one embodiment, the markers include USP9X, SEPT3, INS, and CSTF3. In one embodiment, the markers include USP9X, SEPT3, INS, and NELL1. In one embodiment, the markers include USP9X, SEPT3, INS, and SLIT3. In one embodiment, the markers include USP9X, SEPT3, INS, and LAMTOR2. In one embodiment, the markers include USP9X, SEPT3, INS, and MGAT4B. In one embodiment, the markers include USP9X, SEPT3, INS, and TMPRSS11F. In one embodiment, the markers include USP9X, SEPT3, INS, and, ATAD3B. In one embodiment, the markers include USP9X, SEPT3, INS, and PTPRN. In one embodiment, the markers include USP9X, SEPT3, INS, and WNT9B. In one embodiment, the markers include USP9X, SEPT3, INS, and FUT6. In one embodiment, the markers include USP9X, SEPT3, INS, and B4GALT1. In one embodiment, the markers include USP9X, SEPT3, INS, and FAM20C. In one embodiment, the markers include USP9X, SEPT3, INS, and CNTN1. In one embodiment, the markers include USP9X, SEPT3, INS, and MGAT1. In one embodiment, the markers include USP9X, SEPT3, INS, and STX1A. In one embodiment, the markers include USP9X, SEPT3, INS, and NMU. In one embodiment, the markers include USP9X, SEPT3, INS, and CD59. In one embodiment, the markers include USP9X, SEPT3, INS, and CASR. In one embodiment, the markers include USP9X, SEPT3, INS, and CPE. In one embodiment, the markers include BTC, MMP7, PPY, and CSTF3. In one embodiment, the markers include BTC, MMP7, PPY, and NELL1. In one embodiment, the markers include BTC, MMP7, PPY, and SLIT3. In one embodiment, the markers include BTC, MMP7, PPY, and LAMTOR2. In one embodiment, the markers include BTC, MMP7, PPY, and MGAT4B. In one embodiment, the markers include BTC, MMP7, PPY, and TMPRSS11F. In one embodiment, the markers include BTC, MMP7, PPY, and, ATAD3B. In one embodiment, the markers include BTC, MMP7, PPY, and PTPRN. In one embodiment, the markers include BTC, MMP7, PPY, and WNT9B. In one embodiment, the markers include BTC, MMP7, PPY, and FUT6. In one embodiment, the markers include BTC, MMP7, PPY, and B4GALT1. In one embodiment, the markers include BTC, MMP7, PPY, and FAM20C. In one embodiment, the markers include BTC, MMP7, PPY, and CNTN1. In one embodiment, the markers include BTC, MMP7, PPY, and MGAT1. In one embodiment, the markers include BTC, MMP7, PPY, and STX1A. In one embodiment, the markers include BTC, MMP7, PPY, and NMU. In one embodiment, the markers include BTC, MMP7, PPY, and CD59. In one embodiment, the markers include BTC, MMP7, PPY, and CASR. In one embodiment, the markers include BTC, MMP7, PPY, and CPE. In one embodiment, the markers include PPY, SEPT3, PTPRJ, and CSTF3. In one embodiment, the markers include PPY, SEPT3, PTPRJ, and NELL1. In one embodiment, the markers include PPY, SEPT3, PTPRJ, and SLIT3. In one embodiment, the markers include PPY, SEPT3, PTPRJ, and LAMTOR2. In one embodiment, the markers include PPY, SEPT3, PTPRJ, and MGAT4B. In one embodiment, the markers include PPY, SEPT3, PTPRJ, and TMPRSS11F. In one embodiment, the markers include PPY, SEPT3, PTPRJ, and, ATAD3B. In one embodiment, the markers include PPY, SEPT3, PTPRJ, and PTPRN. In one embodiment, the markers include PPY, SEPT3, PTPRJ, and WNT9B. In one embodiment, the markers include PPY, SEPT3, PTPRJ, and FUT6. In one embodiment, the markers include PPY, SEPT3, PTPRJ, and B4GALT1. In one embodiment, the markers include PPY, SEPT3, PTPRJ, and FAM20C. In one embodiment, the markers include PPY, SEPT3, PTPRJ, and CNTN1. In one embodiment, the markers include PPY, SEPT3, PTPRJ, and MGAT1. In one embodiment, the markers include PPY, SEPT3, PTPRJ, and STX1A. In one embodiment, the markers include PPY, SEPT3, PTPRJ, and NMU. In one embodiment, the markers include PPY, SEPT3, PTPRJ, and CD59. In one embodiment, the markers include PPY, SEPT3, PTPRJ, and CASR. In one embodiment, the markers include PPY, SEPT3, PTPRJ, and CPE. In one embodiment, the markers include CPM, INS, MMP7, LDLR, and CSTF3. In one embodiment, the markers include CPM, INS, MMP7, LDLR, and NELL1. In one embodiment, the markers include CPM, INS, MMP7, LDLR, and SLIT3. In one embodiment, the markers include CPM, INS, MMP7, LDLR, and LAMTOR2. In one embodiment, the markers include CPM, INS, MMP7, LDLR, and MGAT4B. In one embodiment, the markers include CPM, INS, MMP7, LDLR, and TMPRSS11F. In one embodiment, the markers include CPM, INS, MMP7, LDLR, and, ATAD3B. In one embodiment, the markers include CPM, INS, MMP7, LDLR, and PTPRN. In one embodiment, the markers include CPM, INS, MMP7, LDLR, and WNT9B. In one embodiment, the markers include CPM, INS, MMP7, LDLR, and FUT6. In one embodiment, the markers include CPM, INS, MMP7, LDLR, and B4GALT1. In one embodiment, the markers include CPM, INS, MMP7, LDLR, and FAM20C. In one embodiment, the markers include CPM, INS, MMP7, LDLR, and CNTN1. In one embodiment, the markers include CPM, INS, MMP7, LDLR, and MGAT1. In one embodiment, the markers include CPM, INS, MMP7, LDLR, and STX1A. In one embodiment, the markers include CPM, INS, MMP7, LDLR, and NMU. In one embodiment, the markers include CPM, INS, MMP7, LDLR, and CD59. In one embodiment, the markers include CPM, INS, MMP7, LDLR, and CASR. In one embodiment, the markers include CPM, INS, MMP7, LDLR, and CPE.


II. Methods of the Invention

A. Diagnostic and Prognostic Methods


In certain aspects, the present invention provides diagnostic methods. For example, in one aspect, the present invention provides methods for determining whether a subject has impaired glucose tolerance. The methods include determining the level of one or more markers of the invention in a sample(s) from the subject with a level of the one or more markers in a control sample(s). A difference in the level (e.g., higher or lower) of the one or more markers in the sample(s) from the subject as compared to the level of the one or more markers in the control sample indicates that the subject has impaired glucose tolerance. In another aspect, the present invention provides methods for determining whether a subject has type 2 diabetes. The methods include determining the level of one or more markers of the invention in a sample(s) from the subject with a level of the one or more markers in a control sample(s). A difference in the level (e.g., higher or lower) of one or more markers in the sample(s) from the subject as compared to the level of the one or more markers in the control sample indicates that the subject has type 2 diabetes.


The present invention also provides prognostic methods. For example, in one aspect, the present invention provides methods for determining whether a subject will develop impaired glucose tolerance. The methods include determining the level of one or more markers of the invention in a sample(s) from the subject with a level of the one or more markers in a control sample(s). A difference in the level (e.g., higher or lower) of one or more markers in the sample(s) from the subject as compared to the level of the one or more markers in the control sample indicates that the subject will develop impaired glucose tolerance.


In another aspect, the present invention provides methods for determining whether a subject will develop type 2 diabetes. The methods include determining the level of one or more markers of the invention in a sample(s) from the subject with a level of the one or more markers in a control sample(s). A difference in the level (e.g., higher or lower) of the one or more markers in the sample(s) from the subject as compared to the level of the one or more markers in the control sample indicates that the subject will develop type 2 diabetes. Numerous complications have been associated with impaired glucose tolerance and/or type 2 diabetes, especially prolonged impaired glucose tolerance and/or type 2 diabetes. For example, such subjects have a two to four times the risk of cardiovascular disease, including ischemic heart disease and stroke, a 20-fold increase in lower limb amputations, and increased rates of hospitalizations. Type 2 diabetes is also the largest cause of non-traumatic blindness and nephropathy including kidney failure and has been associated with an increased risk of cognitive dysfunction and dementia through disease processes such as Alzheimer's disease and vascular dementia. Other complications include, for example, neuropathy, acanthosis nigricans, sexual dysfunction, and frequent infections.


As the markers of the present invention have been shown to be differentially expressed in subjects newly diagnosed with type 2 diabetes and those having established type 2 diabetes, e.g., those subjects having prolonged impaired glucose tolerance and/or type 2 diabetes, the present invention also provides methods for determining whether a subject will develop a type 2 diabetes-associated complication. The methods include determining the level of one or more markers of the invention in a sample(s) from the subject with a level of the one or more markers in a control sample(s). A difference in the level (e.g., higher or lower) of the one or more markers in the sample(s) from the subject as compared to the level of the one or more markers in the control sample indicates that the subject will respond to a diabetic therapy.


In another aspect the present invention provides methods for determining whether a subject having impaired glucose tolerance and/or type 2 diabetes will respond to a treatment regime. The methods include determining the level of one or more markers of the invention in a sample(s) from the subject with a level of the one or more markers in a control sample(s). A difference in the level (e.g., higher or lower) of the one or more markers in the sample(s) from the subject as compared to the level of the one or more markers in the control sample indicates that the subject will respond to a treatment.


Numerous diabetic therapies are known in the art and include, for example, insulin sensitizers, such as biguanides (e.g., metformin) and thiazolidinediones (e.g., rosiglitazone, pioglitazone, troglitazone); secretagogues, such as the sulfonylureas (e.g., glyburide, glipizide, glimepiride, tolbutamide, acetohexamide, tolazamide, chlorpropamide, gliclazide, glycopyamide, gliquidone), the nonsulfonylurea secretagogues, e.g., meglitinide derivatives (e.g., repaglinide, nateglinide); the dipeptidyl peptidase IV inhibitors (e.g., sitagliptin, saxagliptin, linagliptin, vildagliptin, allogliptin, septagliptin); alpha-glucosidase inhibitors (e.g., acarbose, miglitol, voglibose); amylinomimetics (e.g., pramlintide acetate); incretin mimetics (e.g., exenatide, liraglutide, taspoglutide); insulin and its analogues (e.g., rapid acting, slow acting, and intermediate acting); bile acid sequestrants (e.g., colesevelam); and dopamine agonists (e.g., bromocriptine), alone or in combinations.


In certain embodiments of the invention, the treatment comprises an insulin sensitizer. In another embodiment, the treatment comprises an insulin sensitizer and a secretagogue. In yet another embodiment, the treatment comprises an insulin sensitizer, a secretagogue, and insulin.


The methods of the present invention can be practiced in conjunction with any other method(s) used by the skilled practitioner to diagnose, prognose, and/or monitor impaired glucose tolerance and/or type 2 diabetes in a subject and/or a type 2 diabetes complication and/or response to trreatment. For example, the methods of the invention may be performed in conjunction with any clinical measurement of glucose tolerance, obesity, and/or diabetes known in the art including serological, cytological and/or detection (and quantification, if appropriate) of other molecular markers.


In any of the methods (and kits) of the invention, the level of a marker(s) of the invention in a sample obtained from a subject may be determined by any of a wide variety of well-known techniques and methods, which transform a marker of the invention within the sample into a moiety that can be detected and quantified. Non-limiting examples of such methods include analyzing the sample using immunological methods for detection of proteins, protein purification methods, protein function or activity assays, nucleic acid hybridization methods, nucleic acid reverse transcription methods, and nucleic acid amplification methods, immunoblotting, Western blotting, Northern blotting, electron microscopy, mass spectrometry, e.g., MALDI-TOF and SELDI-TOF, immunoprecipitations, immunofluorescence, immunohistochemistry, enzyme linked immunosorbent assays (ELISAs), e.g., amplified ELISA, quantitative blood based assays, e.g., serum ELISA, quantitative urine based assays, flow cytometry, Southern hybridizations, array analysis, and the like, and combinations or sub-combinations thereof.


For example, an mRNA sample may be obtained from the sample from the subject (e.g., bronchial lavage, mouth swab, biopsy, or peripheral blood mononuclear cells, by standard methods) and expression of mRNA(s) encoding a marker of the invention in the sample may be detected and/or determined using standard molecular biology techniques, such as PCR analysis. A preferred method of PCR analysis is reverse transcriptase-polymerase chain reaction (RT-PCR). Other suitable systems for mRNA sample analysis include microarray analysis (e.g., using Affymetrix's microarray system or Illumina's BeadArray Technology).


It will be readily understood by the ordinarily skilled artisan that essentially any technical means established in the art for detecting the level a marker of the invention at either the nucleic acid or protein level, can be used to determine the level a marker of the invention as discussed herein.


In one embodiment, the level of a marker of the invention in a sample is determined by detecting a transcribed polynucleotide, or portion thereof, e.g., mRNA, or cDNA, of a marker of the invention gene. RNA may be extracted from cells using RNA extraction techniques including, for example, using acid phenol/guanidine isothiocyanate extraction (RNAzol B; Biogenesis), RNeasy RNA preparation kits (Qiagen) or PAXgene (PreAnalytix, Switzerland). Typical assay formats utilizing ribonucleic acid hybridization include nuclear run-on assays, RT-PCR, RNase protection assays (Melton et al., Nuc. Acids Res. 12:7035), Northern blotting, in situ hybridization, and microarray analysis.


In one embodiment, the level of a marker of the invention is determined using a nucleic acid probe. The term “probe”, as used herein, refers to any molecule that is capable of selectively binding to a specific marker of the invention. Probes can be synthesized by one of skill in the art, or derived from appropriate biological preparations. Probes may be specifically designed to be labeled. Examples of molecules that can be utilized as probes include, but are not limited to, RNA, DNA, proteins, antibodies, and organic molecules.


Isolated mRNA can be used in hybridization or amplification assays that include, but are not limited to, Southern or Northern analyses, polymerase chain reaction (PCR) analyses and probe arrays. One method for the determination of mRNA levels involves contacting the isolated mRNA with a nucleic acid molecule (probe) that can hybridize to a marker mRNA. The nucleic acid probe can be, for example, a full-length cDNA, or a portion thereof, such as an oligonucleotide of at least about 7, 10, 15, 20, 25, 30, 35, 40, 45, 50, 100, 250 or about 500 nucleotides in length and sufficient to specifically hybridize under stringent conditions to marker genomic DNA.


In one embodiment, the mRNA is immobilized on a solid surface and contacted with a probe, for example by running the isolated mRNA on an agarose gel and transferring the mRNA from the gel to a membrane, such as nitrocellulose. In an alternative embodiment, the probe(s) are immobilized on a solid surface and the mRNA is contacted with the probe(s), for example, in an Affymetrix gene chip array. A skilled artisan can readily adapt known mRNA detection methods for use in determining the level of a marker of the invention mRNA.


An alternative method for determining the level of a marker of the invention in a sample involves the process of nucleic acid amplification and/or reverse transcriptase (to prepare cDNA) of for example mRNA in the sample, e.g., by RT-PCR (the experimental embodiment set forth in Mullis, 1987, U.S. Pat. No. 4,683,202), ligase chain reaction (Barany (1991) Proc. Natl. Acad. Sci. USA 88:189-193), self-sustained sequence replication (Guatelli et al. (1990) Proc. Natl. Acad. Sci. USA 87:1874-1878), transcriptional amplification system (Kwoh et al. (1989) Proc. Natl. Acad. Sci. USA 86:1173-1177), Q-Beta Replicase (Lizardi et al. (1988) Bio/Technology 6:1197), rolling circle replication (Lizardi et al., U.S. Pat. No. 5,854,033) or any other nucleic acid amplification method, followed by the detection of the amplified molecules using techniques well known to those of skill in the art. These detection schemes are especially useful for the detection of nucleic acid molecules if such molecules are present in very low numbers. In particular aspects of the invention, the level of expression of a marker of the invention is determined by quantitative fluorogenic RT-PCR (i.e., the TaqMan™ System). Such methods typically utilize pairs of oligonucleotide primers that are specific for a marker of the invention. Methods for designing oligonucleotide primers specific for a known sequence are well known in the art.


The level of a marker of the invention mRNA may be monitored using a membrane blot (such as used in hybridization analysis such as Northern, Southern, dot, and the like), or microwells, sample tubes, gels, beads or fibers (or any solid support comprising bound nucleic acids). See U.S. Pat. Nos. 5,770,722, 5,874,219, 5,744,305, 5,677,195 and 5,445,934, which are incorporated herein by reference. The determination of a level of a marker of the invention may also comprise using nucleic acid probes in solution.


In one embodiment of the invention, microarrays are used to detect the level of a marker of the invention. Microarrays are particularly well suited for this purpose because of the reproducibility between different experiments. DNA microarrays provide one method for the simultaneous measurement of the levels of large numbers of genes. Each array consists of a reproducible pattern of capture probes attached to a solid support. Labeled RNA or DNA is hybridized to complementary probes on the array and then detected by laser scanning. Hybridization intensities for each probe on the array are determined and converted to a quantitative value representing relative gene expression levels. See, e.g., U.S. Pat. Nos. 6,040,138, 5,800,992 and 6,020,135, 6,033,860, and 6,344,316, which are incorporated herein by reference. High-density oligonucleotide arrays are particularly useful for determining the gene expression profile for a large number of RNA's in a sample.


In certain situations it may be possible to assay for the level of a marker of the invention at the protein level, using a detection reagent that detects the protein product encoded by the mRNA of a marker of the invention. For example, if an antibody reagent is available that binds specifically to a marker of the invention protein product to be detected, and not to other proteins, then such an antibody reagent can be used to detect the expression of a marker of the invention in a cellular sample from the subject, or a preparation derived from the cellular sample, using standard antibody-based techniques known in the art, such as FACS analysis, and the like.


Other known methods for detecting a marker of the invention at the protein level include methods such as electrophoresis, capillary electrophoresis, high performance liquid chromatography (HPLC), thin layer chromatography (TLC), hyperdiffusion chromatography, and the like, or various immunological methods such as fluid or gel precipitin reactions, immunodiffusion (single or double), immunoelectrophoresis, radioimmunoassay (RIA), enzyme-linked immunosorbent assays (ELISAs), immunofluorescent assays, and Western blotting.


Proteins from samples can be isolated using techniques that are well known to those of skill in the art. The protein isolation methods employed can, for example, be those described in Harlow and Lane (Harlow and Lane, 1988, Antibodies: A Laboratory Manual, Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y.).


In one embodiment, antibodies, or antibody fragments, are used in methods such as Western blots or immunofluorescence techniques to detect the expressed proteins. Antibodies for determining the expression of a marker of the invention are commercially available and one of ordinary skill in the art can readily identify appropriate antibodies for use in the methods of the invention. Exemplary commercially available antibodies suitable for use in the claimed methods for determining the level of a marker of the invention are listed in the table below (Table 4).









TABLE 4







Commercially Available Antibodies









Marker




Name
Company Name
Catalog Number





USP9X
Fitzgerald Industries International
70R-9746



Abnova Corporation
H00008239-A01



LifeSpan BioSciences
LS-C143435



Bethyl Laboratories
A301-350A



Abgent
AT4497a


DAG1
antibodies-online
ABIN502745



GeneTex
GTX88089



Abnova Corporation
H00001605-M01



ProSci, Inc
48-780



Proteintech Group Inc
11017-1-AP


SEPT3
Atlas Antibodies
HPA003548



LifeSpan BioSciences
LS-C120158



Sigma-Aldrich
HPA003548-100UL



Abgent
AT3814a



USCN Life Science, Inc.
E95863Hu


PTPRJ
GeneTex
GTX82145



Thermo Scientific Pierce Antibodies
PA1-27625



Abnova Corporation
H00005795-B01P



LifeSpan BioSciences
LS-C40932



Novus Biologicals
H00005795-M01


CPM
MyBioSource.com
MBS855861



Santa Cruz Biotechnology, Inc.
sc-98698



Abnova Corporation
H00001368-B01P



Biorbyt
orb125616



USCN Life Science, Inc.
E92397Hu


SERPINB13
Fitzgerald Industries International
10R-5733



Proteintech Group Inc
18045-1-AP



Novus Biologicals
NBP2-01336



Sigma-Aldrich
SAB2104770-50UG



Abnova Corporation
PAB1049


LDLR
Atlas Antibodies
HPA009647



Santa Cruz Biotechnology, Inc.
sc-20744



Abgent
AP8960c



Abnova Corporation
H00003949-A01



Acris Antibodies GmbH
BP5013


MMP7
GeneTex
GTX17854



GenWay Biotech, Inc.
GWB-5EF98D



Abgent
AF1674a



LifeSpan BioSciences
LS-C88495-20



R&D Systems
DMP700


BTC
LifeSpan BioSciences
LS-C100871-100



Abgent
AP11669a



Sigma-Aldrich
B2430



R&D Systems
AF-261-NA



Creative Diagnostics
DEIA089


PPY
Abnova Corporation
H00005539-B01



LifeSpan BioSciences
LS-C38055-200



GenWay Biotech, Inc.
GWB-C1C3DC



R&D Systems
MAB6297



USCN Life Science, Inc.
E91265Hu


INS
Abgent
AM1985b



antibodies-online
ABIN237690



GeneTex
GTX81555



Atlas Antibodies
HPA004932



EMD Millipore Corp
EZHIASF-14K


CSTF3
Atlas Antibodies
HPA040168



Abnova Corporation
H00001479-A01



AbD Serotec
MCA3034Z



Fitzgerald Industries International
70R-4939



Abgent
AT1663a


NELL1
GeneTex
GTX103819



Abnova Corporation
H00004745-A01



LifeSpan BioSciences
LS-C139121-100



AbD Serotec
MCA5151Z



Abcam
ab55548


SLIT3
EMD Millipore
AB5703P



Abnova Corporation
H00006586-A01



R&D Systems
AF3629



Sigma-Aldrich
WH0006586M4



Creative Biomart
CAB-4683MH


LAMTOR2
Atlas Antibodies
HPA004126



Sigma-Aldrich
HPA004126



Cell Signaling Technology
8145S



Abgent
AP13338c



Novus Biologicals
NBP1-71687


MGAT4B
Abnova Corporation
H00011282-D01



Sigma-Aldrich
SAB1407130



Novus Biologicals
H00011282-B01P



Creative Biomart
CPBT-40309MH



Abcam
ab67394


TMPRSS11F
Atlas Antibodies
HPA026911



Sigma-Aldrich
HPA026911



Abcam
ab59857



Novus Biologicals
NBP1-94000



Abnova Corporation
PAB21857


ATAD3B
Abnova Corporation
H00083858-B01P



Thermo Scientific Pierce Antibodies
PA5-21160



Novus Biologicals
H00083858-B01



Sigma-Aldrich
SAB1400727



Abcam
ab112563


PTPRN
Atlas Antibodies
HPA007179



GeneTex
GTX82148



Thermo Scientific Pierce Antibodies
PA1-27627



Abnova Corporation
MAB2710



Novus Biologicals
H00005798-B02P


WNT9B
Abgent
AP16959c



Aviva Systems Biology
ARP41243_T100



LifeSpan BioSciences
LS-C108128-100



Fitzgerald Industries International
70R-7246



R&D Systems
AF3669


FUT6
Fitzgerald Industries International
70R-5379



Abgent
AP4925c



Thermo Scientific Pierce Antibodies
PA5-24850



Sigma-Aldrich
AV48467



Novus Biologicals
H00002528-B01P


B4GALT1
Atlas Antibodies
HPA010806



GeneTex
GTX80958



Abnova Corporation
PAB20512



LifeSpan BioSciences
LS-C36410-100



Biorbyt
orb126744


FAM20C
Atlas Antibodies
HPA019823



Santa Cruz Biotechnology, Inc.
sc-160322



Abnova Corporation
PAB21246



Fitzgerald Industries International
70R-6353



LifeSpan BioSciences
LS-C82574-50


CNTN1
Fitzgerald Industries International
70R-9772



Atlas Antibodies
HPA041060



antibodies-online
ABIN748823



LifeSpan BioSciences
LS-C116852-50



Abnova Corporation
PAB23744


MGAT1
Atlas Antibodies
HPA017432



antibodies-online
ABIN571229



Thermo Scientific Pierce Antibodies
PA5-12148



Abnova Corporation
PAB18956



LifeSpan BioSciences
LS-C99702-100


STX1A
Abgent
AP9813a



Fitzgerald Industries International
70R-10562



Acris Antibodies GmbH
AP15806PU-M



LifeSpan BioSciences
LS-C89914-100



Covance, Inc.
MMS-619R-500


NMU
Atlas Antibodies
HPA025926



GeneTex
GTX87991



antibodies-online
ABIN461275



LifeSpan BioSciences
LS-C9258-50



Biorbyt
orb126042


CD59
antibodies-online
ABIN94204



Antigenix America Inc.
M590020



GeneTex
GTX74620



AbD Serotec
MCA1927T



Thermo Scientific Pierce Antibodies
MA1-70058


CASR
Atlas Antibodies
HPA039686



antibodies-online
ABIN460094



Spring Bioscience
E10624



Abnova Corporation
PAB18311



Acris Antibodies GmbH
AP20293PU-N


CPE
Santa Cruz Biotechnology, Inc.
sc-34321



LifeSpan BioSciences
LS-C119819-100



Proteintech Group Inc
13710-1-AP



R&D Systems
AF3587



Biorbyt
orb127922









It is generally preferable to immobilize either the antibody or proteins on a solid support for Western blots and immunofluorescence techniques. Suitable solid phase supports or carriers include any support capable of binding an antigen or an antibody. Well-known supports or carriers include glass, polystyrene, polypropylene, polyethylene, dextran, nylon, amylases, natural and modified celluloses, polyacrylamides, gabbros, and magnetite.


One skilled in the art will know many other suitable carriers for binding antibody or antigen, and will be able to adapt such support for use with the present invention. For example, protein isolated from cells can be run on a polyacrylamide gel electrophoresis and immobilized onto a solid phase support such as nitrocellulose. The support can then be washed with suitable buffers followed by treatment with the detectably labeled antibody. The solid phase support can then be washed with the buffer a second time to remove unbound antibody. The amount of bound label on the solid support can then be detected by conventional means. Means of detecting proteins using electrophoretic techniques are well known to those of skill in the art (see generally, R. Scopes (1982) Protein Purification, Springer-Verlag, N.Y.; Deutscher, (1990) Methods in Enzymology Vol. 182: Guide to Protein Purification, Academic Press, Inc., N.Y.).


Other standard methods include immunoassay techniques which are well known to one of ordinary skill in the art and may be found in Principles And Practice Of Immunoassay, 2nd Edition, Price and Newman, eds., MacMillan (1997) and Antibodies, A Laboratory Manual, Harlow and Lane, eds., Cold Spring Harbor Laboratory, Ch. 9 (1988), each of which is incorporated herein by reference in its entirety.


Antibodies used in immunoassays to determine the level of a marker of the invention, may be labeled with a detectable label. The term “labeled”, with regard to the probe or antibody, is intended to encompass direct labeling of the probe or antibody by coupling (i.e., physically linking) a detectable substance to the probe or antibody, as well as indirect labeling of the probe or antibody by reactivity with another reagent that is directly labeled. Examples of indirect labeling include detection of a primary antibody using a fluorescently labeled secondary antibody and end-labeling of a DNA probe with biotin such that it can be detected with fluorescently labeled streptavidin.


In one embodiment, the antibody is labeled, e.g. a radio-labeled, chromophore-labeled, fluorophore-labeled, or enzyme-labeled antibody. In another embodiment, an antibody derivative (e.g. an antibody conjugated with a substrate or with the protein or ligand of a protein-ligand pair {e.g. biotin-streptavidin}), or an antibody fragment (e.g. a single-chain antibody, an isolated antibody hypervariable domain, etc.) which binds specifically with a marker of the invention.


In one embodiment of the invention, proteomic methods, e.g., mass spectrometry, are used. Mass spectrometry is an analytical technique that consists of ionizing chemical compounds to generate charged molecules (or fragments thereof) and measuring their mass-to-charge ratios. In a typical mass spectrometry procedure, a sample is obtained from a subject, loaded onto the mass spectrometry, and its components (e.g., a marker of the invention) are ionized by different methods (e.g., by impacting them with an electron beam), resulting in the formation of charged particles (ions). The mass-to-charge ratio of the particles is then calculated from the motion of the ions as they transit through electromagnetic fields.


For example, matrix-associated laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) or surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) which involves the application of a biological sample, such as serum, to a protein-binding chip (Wright, G. L., Jr., et al. (2002) Expert Rev Mol Diagn 2:549; Li, J., et al. (2002) Clin Chem 48:1296; Laronga, C., et al. (2003) Dis Markers 19:229; Petricoin, E. F., et al. (2002) 359:572; Adam, B. L., et al. (2002) Cancer Res 62:3609; Tolson, J., et al. (2004) Lab Invest 84:845; Xiao, Z., et al. (2001) Cancer Res 61:6029) can be used to determine the level of a marker of the invention.


Furthermore, in vivo techniques for determination of the level of a marker of the invention include introducing into a subject a labeled antibody directed against a marker of the invention, which binds to and transforms a marker of the invention into a detectable molecule. As discussed above, the presence, level, or even location of the detectable marker of the invention in a subject may be detected determined by standard imaging techniques.


In general, it is preferable that the difference between the level of a marker of the invention in a sample from a subject and the amount of a marker of the invention in a control sample, is as great as possible. Although this difference can be as small as the limit of detection of the method for determining the level of a marker it is preferred that the difference be at least greater than the standard error of the assessment method, and preferably a difference of at least 2-, 3-, 4-, 5-, 6-, 7-, 8-, 9-, 10-, 15-, 20-, 25-, 100-, 500-, 1000-fold or greater than the standard error of the assessment method.


B. Methods for Monitoring the Effectiveness of a Treatment


The present invention also provides methods for monitoring the effectiveness of a therapy or treatment regimen or any other therapeutic approach useful for inhibiting the development of impaired glucose tolerance and/or type 2 diabetes; reducing or slowing down the progression of normal glucose tolerance to impaired fasting glycaemia, to impaired glucose tolerance, and/or to diabetes; and/or reducing or inhibiting the development of complications associated with the disease in a subject. In these methods the level of one or more markers of the invention in a pair of samples (a first sample not subjected to the treatment regimen and a second sample subjected to at least a portion of the treatment regimen) is assessed. A modulation in the level of expression of the one or more markers in the first sample, relative to the second sample, is an indication that the therapy is effective for inhibiting the development of impaired glucose tolerance and/or type 2 diabetes; reduce or slow down the progression of normal glucose tolerance to impaired fasting glycaemia, to impaired glucose tolerance, and/or to diabetes; and/or reduce or inhibit the development of complications associated with the disease in a subject.


C. Screening Methods


Using the methods described herein, a variety of molecules, particularly molecules sufficiently small to be able to cross the cell membrane, may be screened in order to identify molecules which modulate, e.g., decrease or increase, the expression and/or activity of a marker(s) of the invention. Compounds so identified can be administered to a subject in order to inhibit the development of impaired glucose tolerance and/or type 2 diabetes; reduce or slow down the progression of normal glucose tolerance to impaired fasting glycaemia, to impaired glucose tolerance, and/or to diabetes; and/or reduce or inhibit the development of complications associated with the disease in a subject.


Accordingly, in one embodiment, the invention provides methods for identifying modulators, i.e., candidate or test compounds or agents (e.g., enzymes, peptides, peptidomimetics, small molecules, ribozymes, or marker antisense molecules) which bind to a marker polypeptide; have a stimulatory or inhibitory effect on a marker expression; marker processing; marker post-translational modification (e.g., glycosylation, ubiquitinization, or phosphorylation); marker activity; and/or have a stimulatory or inhibitory effect on the expression, processing or activity of a marker target molecule.


Methods for identifying a compound that can modulate the expression and/or activity of a marker in a cell (in vitro and/or in vivo), inhibit the development of impaired glucose tolerance and/or type 2 diabetes; reduce or slow down the progression of normal glucose tolerance to impaired fasting glycaemia, to impaired glucose tolerance, and/or to diabetes; and/or reduce or inhibit the development of complications associated with the disease in a subject (also referred to herein as screening assays) include separately contacting an aliquot of a sample (e.g., a sample from the subject) with each member of a library of compounds; determining the effect of a member of the library of compounds on the level of one or more marker(s) of the invention (or the activity of one or more marker(s) of the invention) in each of the aliquots; and selecting a member of the library of compounds which modulates the level of and/or the activity of the one or more marker(s) of the invention in an aliquot as compared to the level and/or activity of the one or more marker(s) of the invention in a control sample, thereby identifying a compound that can modulate the expression and/or activity of a marker in a cell, inhibit the development of impaired glucose tolerance and/or type 2 diabetes; reduce or slow down the progression of normal glucose tolerance to impaired fasting glycaemia, to impaired glucose tolerance, and/or to diabetes; and/or reduce or inhibit the development of complications associated with the disease in a subject.


As used interchangeably herein, the terms “marker activity” and “biological activity of a marker” include activities exerted by a marker(s) protein on marker responsive cell or tissue, or on marker(s) nucleic acid molecule or protein target molecule, as determined in vivo, and/or in vitro, according to standard techniques. A marker(s) activity can be a direct activity, such as an association with a marker-target molecule. Alternatively, marker(s) activity is an indirect activity, such as a downstream biological event mediated by interaction of the marker(s) protein with a marker-target molecule or other molecule in a signal-transduction pathway involving the marker(s). The biological activities of the markers of the invention are known in the art and can be found at, for example, the Uniprot database. The Uniprot Accession Numbers for each of the markers of the invention are provided in Tables 1-3. The entire contents of each of these Uniprot records is hereby incorporated by reference. Methods for determining the effect of a compound on the expression and/or activity of marker are known in the art and/or described herein.


A variety of test compounds can be evaluated using the screening assays described herein. The term “test compound” includes any reagent or test agent which is employed in the assays of the invention and assayed for its ability to influence the expression and/or activity of a marker. More than one compound, e.g., a plurality of compounds, can be tested at the same time for their ability to modulate the expression and/or activity of a marker in a screening assay. The term “screening assay” preferably refers to assays which test the ability of a plurality of compounds to influence the readout of choice rather than to tests which test the ability of one compound to influence a readout. Preferably, the subject assays identify compounds not previously known to have the effect that is being screened for. In one embodiment, high throughput screening can be used to assay for the activity of a compound.


Candidate/test compounds include, for example, 1) peptides such as soluble peptides, including Ig-tailed fusion peptides and members of random peptide libraries (see, e.g., Lam, K. S. et al. (1991) Nature 354:82-84; Houghten, R. et al. (1991) Nature 354:84-86) and combinatorial chemistry-derived molecular libraries made of D- and/or L-configuration amino acids; 2) phosphopeptides (e.g., members of random and partially degenerate, directed phosphopeptide libraries, see, e.g., Songyang, Z. et al. (1993) Cell 72:767-778); 3) antibodies (e.g., polyclonal, monoclonal, humanized, anti-idiotypic, chimeric, and single chain antibodies as well as Fab, F(ab′)2, Fab expression library fragments, and epitope-binding fragments of antibodies); 4) small organic and inorganic molecules (e.g., molecules obtained from combinatorial and natural product libraries); 5) enzymes (e.g., endoribonucleases, hydrolases, nucleases, proteases, synthatases, isomerases, polymerases, kinases, phosphatases, oxido-reductases and ATPases), 6) mutant forms of marker(s) molecules, e.g., dominant negative mutant forms of the molecules, 7) nucleic acids, 8) carbohydrates, and 9) natural product extract compounds.


Test compounds can be obtained using any of the numerous approaches in combinatorial library methods known in the art, including: biological libraries; spatially addressable parallel solid phase or solution phase libraries; synthetic library methods requiring deconvolution; the ‘one-bead one-compound’ library method; and synthetic library methods using affinity chromatography selection. The biological library approach is limited to peptide libraries, while the other four approaches are applicable to peptide, non-peptide oligomer or small molecule libraries of compounds (Lam, K. S. (1997) Anticancer Drug Des. 12:145).


Examples of methods for the synthesis of molecular libraries can be found in the art, for example in: DeWitt et al. (1993) Proc. Natl. Acad. Sci. U.S.A. 90:6909; Erb et al. (1994) Proc. Natl. Acad. Sci. USA 91:11422; Zuckermann et al. (1994) J. Med. Chem. 37:2678; Cho et al. (1993) Science 261:1303; Carrell et al. (1994) Angew. Chem. Int. Ed. Engl. 33:2059; Carell et al. (1994) Angew. Chem. Int. Ed. Engl. 33:2061; and Gallop et al. (1994) J. Med. Chem. 37:1233.


Libraries of compounds can be presented in solution (e.g., Houghten (1992) Biotechniques 13:412-421), or on beads (Lam (1991) Nature 354:82-84), chips (Fodor (1993) Nature 364:555-556), bacteria (Ladner U.S. Pat. No. 5,223,409), spores (Ladner USP '409), plasmids (Cull et al. (1992) Proc Natl Acad Sci USA 89:1865-1869) or phage (Scott and Smith (1990) Science 249:386-390; Devlin (1990) Science 249:404-406; Cwirla et al. (1990) Proc. Natl. Acad. Sci. 87:6378-6382; Felici (1991) J. Mol. Biol. 222:301-310; Ladner supra.).


Compounds identified in the screening assays can be used in methods of modulating one or more of the biological responses regulated by a marker, e.g., glucose tolerance. It will be understood that it may be desirable to formulate such compound(s) as pharmaceutical compositions prior to contacting them with cells.


Once a test compound is identified by one of the variety of methods described hereinbefore, the selected test compound (or “compound of interest”) can then be further evaluated for its effect on cells, for example by contacting the compound of interest with cells either in vivo (e.g., by administering the compound of interest to a subject or animal model) or ex vivo (e.g., by isolating cells from the subject or animal model and contacting the isolated cells with the compound of interest or, alternatively, by contacting the compound of interest with a cell line) and determining the effect of the compound of interest on the cells, as compared to an appropriate control (such as untreated cells or cells treated with a control compound, or carrier, that does not modulate the biological response).


Computer-based analysis of a marker with a known structure can also be used to identify molecules which will bind to a marker of the invention. Such methods rank molecules based on their shape complementary to a receptor site. For example, using a 3-D database, a program such as DOCK can be used to identify molecules which will bind to TLR9. See DesJarlias et al. (1988) J. Med. Chem. 31:722; Meng et al. (1992) J. Computer Chem. 13:505; Meng et al. (1993) Proteins 17:266; Shoichet et al. (1993) Science 259:1445. In addition, the electronic complementarity of a molecule to a marker can be analyzed to identify molecules which bind to the marker. This can be determined using, for example, a molecular mechanics force field as described in Meng et al. (1992) J. Computer Chem. 13:505 and Meng et al. (1993) Proteins 17:266. Other programs which can be used include CLIX which uses a GRID force field in docking of putative ligands. See Lawrence et al. (1992) Proteins 12:31; Goodford et al. (1985) J. Med. Chem. 28:849; Boobbyer et al. (1989) J. Med. Chem. 32:1083.


The instant invention also pertains to compounds identified using the foregoing screening assays.


D. Methods for Modulating the Expression and/or Activity of a Biomarker of the Invention


Yet another aspect of the invention pertains to methods of modulating expression and/or activity of a marker in a cell. The modulatory methods of the invention involve contacting the cell with an agent that modulates the expression and/or activity of a marker such that the expression and/or activity of a marker in the cell is modulated. In order for the expression and/or activity of a marker to be modulated in a cell, the cell is contacted with a modulatory agent in an amount sufficient to modulate the expression and/or activity of a marker.


A “modulator” or “modulatory agent” is a compound or molecule that modulates, and may be, e.g., an agonist, antagonist, activator, stimulator, suppressor, or inhibitor. As used herein, the term “modulator” refers to any moiety which modulates activity of a marker(s), including moieties which modulates marker(s) expression or modulates marker(s) function. The modulator may act by modulating the activity of a marker polypeptide in the cell, (e.g., by contacting a cell with an agent that, e.g., interferes with the binding of a marker(s) to a molecule with which it interacts, changes the binding specificity of a marker(s), or post-translationally modifies a marker(s) or the expression of a marker(s), (e.g., by modulating transcription of the marker gene or translation of the marker mRNA). Accordingly, the invention features methods for modulating one or more biological responses regulated by a marker(s) by contacting the cells with a modulator of the expression and/or activity the marker(s) such that the biological response is modulated.


Representative modulators are described below and include, but are not limited to, proteins, nucleic acid molecules, antibodies, nucleic acids (e.g., antisense molecules, such as ribozymes and RNA interfering agents), immunoconjugates (e.g., an antibody conjugated to a therapeutic agent), small molecules, fusion proteins, adnectins, aptamers, anticalins, lipocalins, and marker-derived peptidic compounds.


As used herein, the term “contacting” (e.g., contacting a cell with a modulator) is intended to include incubating the modulator and the cell together in vitro (e.g., adding the modulator to cells in culture) or administering the modulator to a subject such that the modulator and cells of the subject are contacted in vivo. The term “contacting” is not intended to include exposure of cells to an agent that may occur naturally in a subject (i.e., exposure that may occur as a result of a natural physiological process).


In one embodiment, the modulatory methods of the invention are performed in vitro. In another embodiment, the modulatory methods of the invention are performed in vivo, e.g., in a subject, e.g., having impaired glucose tolerance, type 2 diabetes, that would benefit from modulation of the expression and/or activity of a marker of the invention.


Accordingly, the present invention also provides methods for inhibiting the development of impaired glucose tolerance and/or type 2 diabetes; reducing or slowing down the progression of normal glucose tolerance to impaired fasting glycaemia, to impaired glucose tolerance, and/or to diabetes; and/or reducing or inhibiting the development of complications associated with the disease in a subject


The methods of “inhibiting”, “slowing”, and/or “treating” include administration of a marker modulator to a subject in order to cure or to prolong the health or survival of a subject beyond that expected in the absence of such treatment.


The terms “patient” or “subject” as used herein is intended to include human and veterinary patients. In a particular embodiment, the subject is a human. The term “non-human animal” includes all vertebrates, e.g., mammals and non-mammals, such as non-human primates, mice, rabbits, sheep, dog, cow, chickens, amphibians, and reptiles.


The methods of the invention also contemplate the use of marker(s) modulators in combination with other therapies, including life-style changes. Thus, in addition to the use of marker(s) modulators, the methods of the invention may also include administering to the subject one or more “standard” therapies. For example, the modulators can be administered in combination with (i.e., together with or linked to (i.e., an immunoconjugate)) cytotoxins, immunosuppressive agents, radiotoxic agents, and/or therapeutic antibodies. Particular co-therapeutics contemplated by the present invention include, but are not limited to, insulin sensitizers, secretagogues, dipeptidyl peptidase IV inhibitors, alpha-glucosidase inhibitors, amylinomimetics, incretin mimetics, insulin, bile acid sequestrants, dopamine agonists, statins.


Marker(s) modulators and the co-therapeutic agent or co-therapy can be administered in the same formulation or separately. In the case of separate administration, the marker(s) modulators can be administered before, after or concurrently with the co-therapeutic or co-therapy. One agent may precede or follow administration of the other agent by intervals ranging from minutes to weeks. In embodiments where two or more different kinds of therapeutic agents are applied separately to a subject, one would generally ensure that a significant period of time did not expire between the time of each delivery, such that these different kinds of agents would still be able to exert an advantageously combined effect on the target tissues or cells.


In one embodiment, the marker(s) modulators (e.g., an anti-marker(s) antibody) may be linked to a second binding molecule, such as an antibody (i.e., thereby forming a bispecific molecule) or other binding agent that, for example, binds to a different target or a different epitope on the marker(s).


The term “effective amount” as used herein, refers to that amount of marker(s) modulators, which is sufficient to inhibit the progression of fibrosis in a subject when administered to a subject. An effective amount will vary depending upon the subject and the severity of the disease and age of the subject, the manner of administration and the like, which can readily be determined by one of ordinary skill in the art. Marker(s) modulators dosages for administration can range from, for example, about 1 ng to about 10,000 mg, about 5 ng to about 9,500 mg, about 10 ng to about 9,000 mg, about 20 ng to about 8,500 mg, about 30 ng to about 7,500 mg, about 40 ng to about 7,000 mg, about 50 ng to about 6,500 mg, about 100 ng to about 6,000 mg, about 200 ng to about 5,500 mg, about 300 ng to about 5,000 mg, about 400 ng to about 4,500 mg, about 500 ng to about 4,000 mg, about 1 μg to about 3,500 mg, about 5 μg to about 3,000 mg, about 10 μg to about 2,600 mg, about 20 μg to about 2,575 mg, about 30 μg to about 2,550 mg, about 40 μg to about 2,500 mg, about 50 μg to about 2,475 mg, about 100 μg to about 2,450 mg, about 200 μg to about 2,425 mg, about 300 μg to about 2,000, about 400 μg to about 1,175 mg, about 500 μg to about 1,150 mg, about 0.5 mg to about 1,125 mg, about 1 mg to about 1,100 mg, about 1.25 mg to about 1,075 mg, about 1.5 mg to about 1,050 mg, about 2.0 mg to about 1,025 mg, about 2.5 mg to about 1,000 mg, about 3.0 mg to about 975 mg, about 3.5 mg to about 950 mg, about 4.0 mg to about 925 mg, about 4.5 mg to about 900 mg, about 5 mg to about 875 mg, about 10 mg to about 850 mg, about 20 mg to about 825 mg, about 30 mg to about 800 mg, about 40 mg to about 775 mg, about 50 mg to about 750 mg, about 100 mg to about 725 mg, about 200 mg to about 700 mg, about 300 mg to about 675 mg, about 400 mg to about 650 mg, about 500 mg, or about 525 mg to about 625 mg, of a marker(s) modulator. Dosage regimens may be adjusted to provide the optimum therapeutic response. An effective amount is also one in which any toxic or detrimental effects (i.e., side effects) of a marker(s) modulator are minimized and/or outweighed by the beneficial effects.


Actual dosage levels of the marker(s) modulators used in the methods of the present invention may be varied so as to obtain an amount of the active ingredient which is effective to achieve the desired response, e.g., inhibiting the progression of diabetes, for a particular patient, composition, and mode of administration, without being toxic to the patient. The selected dosage level will depend upon a variety of pharmacokinetic factors including the activity of the particular marker(s) modulator employed, or the ester, salt or amide thereof, the route of administration, the time of administration, the rate of excretion of the particular modulator being employed, the duration of the treatment, other drugs, compounds and/or materials used in combination with the particular modulator employed, the age, sex, weight, condition, general health and prior medical history of the patient being treated, and like factors well known in the medical arts. A physician or veterinarian having ordinary skill in the art can readily determine and prescribe the effective amount of the modulator required. For example, the physician or veterinarian could start doses of the modulator at levels lower than that required in order to achieve the desired therapeutic effect and gradually increase the dosage until the desired effect is achieved. In general, a suitable daily dose of a marker(s) modulator will be that amount which is the lowest dose effective to produce a therapeutic effect. Such an effective dose will generally depend upon the factors described above. It is preferred that administration be intravenous, intramuscular, intraperitoneal, or subcutaneous, preferably administered proximal to the site of the target. If desired, the effective daily dose of a marker(s) modulator may be administered as two, three, four, five, six or more sub-doses administered separately at appropriate intervals throughout the day, optionally, in unit dosage forms. While it is possible for a marker(s) modulator of the present invention to be administered alone, it is preferable to administer the modulator as a pharmaceutical formulation (composition).


Dosage regimens are adjusted to provide the optimum desired response (e.g., a therapeutic response). For example, a single bolus may be administered, several divided doses may be administered over time or the dose may be proportionally reduced or increased as indicated by the exigencies of the therapeutic situation. For example, the marker(s) modulators used in the methods of the present invention may be administered once or twice weekly by subcutaneous injection or once or twice monthly by subcutaneous injection.


To administer a marker(s) modulator used in the methods of the present invention by certain routes of administration, it may be necessary to include the modulator in a formulation suitable for preventing its inactivation. For example, the marker(s) modulator may be administered to a subject in an appropriate carrier, for example, liposomes, or a diluent. Pharmaceutically acceptable diluents include saline and aqueous buffer solutions. Liposomes include water-in-oil-in-water CGF emulsions, as well as conventional liposomes (Strejan et al. (1984) J. Neuroimmunol. 7:27).


Pharmaceutically acceptable carriers include sterile aqueous solutions or dispersions and sterile powders for the extemporaneous preparation of sterile injectable solutions or dispersion. The use of such media and agents for pharmaceutically active substances is known in the art. Except insofar as any conventional media or agent is incompatible with the active marker(s) modulator, use thereof in pharmaceutical compositions is contemplated. Supplementary active compounds can also be incorporated with the marker(s) modulator.


Marker(s) modulators used in the methods of the invention typically must be sterile and stable under the conditions of manufacture and storage. The modulator can be formulated as a solution, microemulsion, liposome, or other ordered structure suitable to high drug concentration. The carrier can be a solvent or dispersion medium containing, for example, water, ethanol, polyol (for example, glycerol, propylene glycol, and liquid polyethylene glycol, and the like), and suitable mixtures thereof. The proper fluidity can be maintained, for example, by the use of a coating such as lecithin, by the maintenance of the required particle size in the case of dispersion and by the use of surfactants. In many cases, it will be preferable to include isotonic agents, for example, sugars, polyalcohols such as mannitol, sorbitol, or sodium chloride in the composition. Prolonged absorption of the injectable compositions can be brought about by including an agent that delays absorption, for example, monostearate salts and gelatin.


Sterile injectable solutions can be prepared by incorporating the active modulator in the required amount in an appropriate solvent with one or a combination of ingredients enumerated above, as required, followed by sterilization microfiltration. Generally, dispersions are prepared by incorporating the active compound into a sterile vehicle that contains a basic dispersion medium and the required other ingredients from those enumerated above. In the case of sterile powders for the preparation of sterile injectable solutions, the preferred methods of preparation are vacuum drying and freeze-drying (lyophilization) that yield a powder of the active ingredient plus any additional desired ingredient from a previously sterile-filtered solution thereof.


Marker(s) modulators that can be used in the methods of the present invention include those suitable for oral, nasal, topical (including buccal and sublingual), rectal, vaginal and/or parenteral administration. The formulations may conveniently be presented in unit dosage form and may be prepared by any methods known in the art of pharmacy. The amount of active ingredient which can be combined with a carrier material to produce a single dosage form will vary depending upon the subject being treated, and the particular mode of administration. The amount of active ingredient which can be combined with a carrier material to produce a single dosage form will generally be that amount of the modulator which produces a therapeutic effect. Generally, out of one hundred percent, this amount will range from about 0.001% to about 90% of active ingredient, preferably from about 0.005% to about 70%, most preferably from about 0.01% to about 30%.


The phrases “parenteral administration” and “administered parenterally”, as used herein, means modes of administration other than enteral and topical administration, usually by injection, and includes, without limitation, intravenous, intramuscular, intraarterial, intrathecal, intracapsular, intraorbital, intracardiac, intradermal, intraperitoneal, transtracheal, subcutaneous, subcuticular, intraarticular, subcapsular, subarachnoid, intraspinal, epidural and intrasternal injection and infusion.


Examples of suitable aqueous and non-aqueous carriers which may be employed along with the marker(s) modulators utilized in the methods of the present invention include water, ethanol, polyols (such as glycerol, propylene glycol, polyethylene glycol, and the like), and suitable mixtures thereof, vegetable oils, such as olive oil, and injectable organic esters, such as ethyl oleate. Proper fluidity can be maintained, for example, by the use of coating materials, such as lecithin, by the maintenance of the required particle size in the case of dispersions, and by the use of surfactants.


Marker(s) modulatos may also be administered with adjuvants such as preservatives, wetting agents, emulsifying agents and dispersing agents. Prevention of presence of microorganisms may be ensured both by sterilization procedures and by the inclusion of various antibacterial and antifungal agents, for example, paraben, chlorobutanol, phenol sorbic acid, and the like. It may also be desirable to include isotonic agents, such as sugars, sodium chloride, and the like into the compositions. In addition, prolonged absorption of the injectable pharmaceutical form may be brought about by the inclusion of agents which delay absorption such as aluminum monostearate and gelatin.


When marker(s) modulators used in the methods of the present invention are administered to humans and animals, they can be given alone or as a pharmaceutical modulator containing, for example, 0.001 to 90% (more preferably, 0.005 to 70%, such as 0.01 to 30%) of active ingredient in combination with a pharmaceutically acceptable carrier.


Marker(s) modulators can be administered with medical devices known in the art. For example, in a preferred embodiment, a modulator can be administered with a needleless hypodermic injection device, such as the devices disclosed in U.S. Pat. Nos. 5,399,163, 5,383,851, 5,312,335, 5,064,413, 4,941,880, 4,790,824, or 4,596,556. Examples of well-known implants and modules useful in the present invention include: U.S. Pat. No. 4,487,603, which discloses an implantable micro-infusion pump for dispensing medication at a controlled rate; U.S. Pat. No. 4,486,194, which discloses a therapeutic device for administering medications through the skin; U.S. Pat. No. 4,447,233, which discloses a medication infusion pump for delivering medication at a precise infusion rate; U.S. Pat. No. 4,447,224, which discloses a variable flow implantable infusion apparatus for continuous drug delivery; U.S. Pat. No. 4,439,196, which discloses an osmotic drug delivery system having multi-chamber compartments; and U.S. Pat. No. 4,475,196, which discloses an osmotic drug delivery system. Many other such implants, delivery systems, and modules are known to those skilled in the art.


1. Inhibitory Agents


According to a modulatory method of the invention, the expression and/or activity of a marker(s) is inhibited in a cell or subject by contacting the cell with (or administering to a subject) an inhibitory agent. Inhibitory agents of the invention can be, for example, molecules that act to decrease or inhibit the expression and/or activity of the marker(s).


In one embodiment of the invention, the modulatory, e.g., therapeutic, and diagnostic methods described herein employ an antibody that binds, e.g., directly to or indirectly to, and inhibits marker(s) activity and/or down-modulates marker(s) expression.


The term “antibody” or “immunoglobulin,” as used interchangeably herein, includes whole antibodies and any antigen binding fragment (i.e., “antigen-binding portion”) or single chains thereof. An “antibody” comprises at least two heavy (H) chains and two light (L) chains inter-connected by disulfide bonds. Each heavy chain is comprised of a heavy chain variable region (abbreviated herein as VH) and a heavy chain constant region. The heavy chain constant region is comprised of three domains, CH1, CH2 and CH3. Each light chain is comprised of a light chain variable region (abbreviated herein as VL) and a light chain constant region. The light chain constant region is comprised of one domain, CL. The VH and VL regions can be further subdivided into regions of hypervariability, termed complementarity determining regions (CDR), interspersed with regions that are more conserved, termed framework regions (FR). Each VH and VL is composed of three CDRs and four FRs, arranged from amino-terminus to carboxy-terminus in the following order: FR1, CDR1, FR2, CDR2, FR3, CDR3, FR4. The variable regions of the heavy and light chains contain a binding domain that interacts with an antigen. The constant regions of the antibodies may mediate the binding of the immunoglobulin to host tissues or factors, including various cells of the immune system (e.g., effector cells) and the first component (Clq) of the classical complement system.


The term “antigen-binding portion” of an antibody (or simply “antibody portion”), as used herein, refers to one or more fragments of an antibody that retain the ability to specifically bind to an antigen (e.g., a marker). It has been shown that the antigen-binding function of an antibody can be performed by fragments of a full-length antibody. Examples of binding fragments encompassed within the term “antigen-binding portion” of an antibody include (i) a Fab fragment, a monovalent fragment consisting of the VL, VH, CL and CH1 domains; (ii) a F(ab′)2 fragment, a bivalent fragment comprising two Fab fragments linked by a disulfide bridge at the hinge region; (iii) a Fd fragment consisting of the VH and CH1 domains; (iv) a Fv fragment consisting of the VL and VH domains of a single arm of an antibody, (v) a dAb including VH and VL domains; (vi) a dAb fragment (Ward et al. (1989) Nature 341, 544-546), which consists of a VH domain; (vii) a dAb which consists of a VH or a VL domain; and (viii) an isolated complementarity determining region (CDR) or (ix) a combination of two or more isolated CDRs which may optionally be joined by a synthetic linker. Furthermore, although the two domains of the Fv fragment, VL and VH, are coded for by separate genes, they can be joined, using recombinant methods, by a synthetic linker that enables them to be made as a single protein chain in which the VL and VH regions pair to form monovalent molecules (known as single chain Fv (scFv); see e.g., Bird et al. (1988) Science 242, 423-426; and Huston et al. (1988) Proc. Natl. Acad. Sci. USA 85, 5879-5883). Such single chain antibodies are also intended to be encompassed within the term “antigen-binding portion” of an antibody. These antibody fragments are obtained using conventional techniques known to those with skill in the art, and the fragments are screened for utility in the same manner as are intact antibodies. Antigen-binding portions can be produced by recombinant DNA techniques, or by enzymatic or chemical cleavage of intact immunoglobulins.


The term “antibody”, as used herein, includes polyclonal antibodies, monoclonal antibodies, chimeric antibodies, humanized antibodies, and human antibodies, and those that occur naturally or are recombinantly produced according to methods well known in the art.


In one embodiment, an antibody for use in the methods of the invention is a bispecific antibody. A “bispecific” or “bifunctional antibody” is an artificial hybrid antibody having two different heavy/light chain pairs and two different binding sites. Bispecific antibodies can be produced by a variety of methods including fusion of hybridomas or linking of Fab′ fragments. See, e.g., Songsivilai & Lachmann, (1990) Clin. Exp. Immunol. 79, 315-321; Kostelny et al. (1992) J. Immunol. 148, 1547-1553.


In another embodiment, an antibody for use in the methods of the invention is a camelid antibody as described in, for example, PCT Publication WO 94/04678, the entire contents of which are incorporated herein by reference.


A region of the camelid antibody that is the small, single variable domain identified as VHH can be obtained by genetic engineering to yield a small protein having high affinity for a target, resulting in a low molecular weight, antibody-derived protein known as a “camelid nanobody”. See U.S. Pat. No. 5,759,808; see also Stijlemans et al., 2004 J. Biol. Chem. 279: 1256-1261; Dumoulin et al., 2003 Nature 424: 783-788; Pleschberger et al., 2003 Bioconjugate Chem. 14: 440-448; Cortez-Retamozo et al., 2002 Int. J. Cancer 89: 456-62; and Lauwereys, et al., 1998 EMBO J. 17: 3512-3520. Engineered libraries of camelid antibodies and antibody fragments are commercially available, for example, from Ablynx, Ghent, Belgium. Accordingly, a feature of the present invention is a camelid nanobody having high affinity for a marker.


In other embodiments of the invention, an antibody for use in the methods of the invention is a diabody, a single chain diabody, or a di-diabody.


Diabodies are bivalent, bispecific molecules in which VH and VL domains are expressed on a single polypeptide chain, connected by a linker that is too short to allow for pairing between the two domains on the same chain. The VH and VL domains pair with complementary domains of another chain, thereby creating two antigen binding sites (see e.g., Holliger et al., 1993 Proc. Natl. Acad. Sci. USA 90:6444-6448; Poljak et al., 1994 Structure 2:1121-1123). Diabodies can be produced by expressing two polypeptide chains with either the structure VHA-VLB and VHB-VLA (VH-VL configuration), or VLA-VHB and VLB-VHA (VL-VH configuration) within the same cell. Most of them can be expressed in soluble form in bacteria.


Single chain diabodies (scDb) are produced by connecting the two diabody-forming polypeptide chains with linker of approximately 15 amino acid residues (see Holliger and Winter, 1997 Cancer Immunol. Immunother., 45(3-4):128-30; Wu et al., 1996 Immunotechnology, 2(1):21-36). scDb can be expressed in bacteria in soluble, active monomeric form (see Holliger and Winter, 1997 Cancer Immunol. Immunother., 45(34): 128-30; Wu et al., 1996 Immunotechnology, 2(1):21-36; Pluckthun and Pack, 1997 Immunotechnology, 3(2): 83-105; Ridgway et al., 1996 Protein Eng., 9(7):617-21).


A diabody can be fused to Fc to generate a “di-diabody” (see Lu et al., 2004 J. Biol. Chem., 279(4):2856-65).


Marker binding molecules that exhibit functional properties of antibodies but derive their framework and antigen binding portions from other polypeptides (e.g., polypeptides other than those encoded by antibody genes or generated by the recombination of antibody genes in vivo) may also be used in the methods of the present invention. The antigen binding domains (e.g., marker binding domains) of these binding molecules are generated through a directed evolution process. See U.S. Pat. No. 7,115,396. Molecules that have an overall fold similar to that of a variable domain of an antibody (an “immunoglobulin-like” fold) are appropriate scaffold proteins. Scaffold proteins suitable for deriving antigen binding molecules include fibronectin or a fibronectin dimer, tenascin, N-cadherin, E-cadherin, ICAM, titin, GCSF-receptor, cytokine receptor, glycosidase inhibitor, antibiotic chromoprotein, myelin membrane adhesion molecule P0, CD8, CD4, CD2, class I MHC, T-cell antigen receptor, CD1, C2 and I-set domains of VCAM-1, I-set immunoglobulin domain of myosin-binding protein C, I-set immunoglobulin domain of myosin-binding protein H, I-set immunoglobulin domain of telokin, NCAM, twitchin, neuroglian, growth hormone receptor, erythropoietin receptor, prolactin receptor, interferon-gamma receptor, β-galactosidase/glucuronidase, β-glucuronidase, transglutaminase, T-cell antigen receptor, superoxide dismutase, tissue factor domain, cytochrome F, green fluorescent protein, GroEL, and thaumatin.


To generate non-antibody binding molecules, a library of clones is created in which sequences in regions of the scaffold protein that form antigen binding surfaces (e.g., regions analogous in position and structure to CDRs of an antibody variable domain immunoglobulin fold) are randomized Library clones are tested for specific binding to the antigen of interest (e.g., TLR9) and for other functions (e.g., inhibition of biological activity of TLR9). Selected clones can be used as the basis for further randomization and selection to produce derivatives of higher affinity for the antigen.


High affinity binding molecules are generated, for example, using the tenth module of fibronectin III (10Fn3) as the scaffold, described in U.S. Pat. Nos. 6,818,418 and 7,115,396; Roberts and Szostak, 1997 Proc. Natl. Acad. Sci USA 94:12297; U.S. Pat. Nos. 6,261,804; 6,258,558; and Szostak et al. WO98/31700, the entire contents of each of which are incorporated herein by reference.


Non-antibody binding molecules can be produced as dimers or multimers to increase avidity for the target antigen. For example, the antigen binding domain is expressed as a fusion with a constant region (Fc) of an antibody that forms Fc-Fc dimers. See, e.g., U.S. Pat. No. 7,115,396, the entire contents of which are incorporated herein by reference.


The therapeutic methods of the invention also may be practiced through the use of antibody fragments and antibody mimetics. As detailed below, a wide variety of antibody fragment and antibody mimetic technologies have now been developed and are widely known in the art. While a number of these technologies, such as domain antibodies, Nanobodies, and UniBodies make use of fragments of, or other modifications to, traditional antibody structures, there are also alternative technologies, such as Adnectins, Affibodies, DARPins, Anticalins, Avimers, and Versabodies that employ binding structures that, while they mimic traditional antibody binding, are generated from and function via distinct mechanisms. Some of these alternative structures are reviewed in Gill and Damle (2006) 17: 653-658.


Domain Antibodies (dAbs) are the smallest functional binding units of antibodies, corresponding to the variable regions of either the heavy (VH) or light (VL) chains of human antibodies. Domantis has developed a series of large and highly functional libraries of fully human VH and VL dAbs (more than ten billion different sequences in each library), and uses these libraries to select dAbs that are specific to therapeutic targets. In contrast to many conventional antibodies, domain antibodies are well expressed in bacterial, yeast, and mammalian cell systems. Further details of domain antibodies and methods of production thereof may be obtained by reference to U.S. Pat. Nos. 6,291,158; 6,582,915; 6,593,081; 6,172,197; 6,696,245; U.S. Serial No. 2004/0110941; European patent application No. 1433846 and European Patents 0368684 & 0616640; WO05/035572, WO04/101790, WO04/081026, WO04/058821, WO04/003019 and WO03/002609, the contents of each of which is herein incorporated by reference in its entirety.


Nanobodies are antibody-derived therapeutic proteins that contain the unique structural and functional properties of naturally-occurring heavy-chain antibodies. These heavy-chain antibodies contain a single variable domain (VHH) and two constant domains (CH2 and CH3). Importantly, the cloned and isolated VHH domain is a perfectly stable polypeptide harboring the full antigen-binding capacity of the original heavy-chain antibody. Nanobodies have a high homology with the VH domains of human antibodies and can be further humanized without any loss of activity.


Nanobodies are encoded by single genes and are efficiently produced in almost all prokaryotic and eukaryotic hosts, e.g., E. coli (see, e.g., U.S. Pat. No. 6,765,087, which is herein incorporated by reference in its entirety), molds (for example Aspergillus or Trichoderma) and yeast (for example Saccharomyces, Kluyveromyces, Hansenula or Pichia) (see, e.g., U.S. Pat. No. 6,838,254, which is herein incorporated by reference in its entirety). The production process is scalable and multi-kilogram quantities of Nanobodies have been produced. Because Nanobodies exhibit a superior stability compared with conventional antibodies, they can be formulated as a long shelf-life, ready-to-use solution.


The Nanoclone method (see, e.g., WO 06/079372, which is herein incorporated by reference in its entirety) is a proprietary method for generating Nanobodies against a desired target, based on automated high-throughout selection of B-cells and could be used in the context of the instant invention.


UniBodies are another antibody fragment technology, however this one is based upon the removal of the hinge region of IgG4 antibodies. The deletion of the hinge region results in a molecule that is essentially half the size of traditional IgG4 antibodies and has a univalent binding region rather than the bivalent binding region of IgG4 antibodies. It is also well known that IgG4 antibodies are inert and thus do not interact with the immune system, which may be advantageous for the treatment of diseases where an immune response is not desired, and this advantage is passed onto UniBodies. Further details of UniBodies may be obtained by reference to patent application WO2007/059782, which is herein incorporated by reference in its entirety.


Adnectin molecules are engineered binding proteins derived from one or more domains of the fibronectin protein. In one embodiment, adnectin molecules are derived from the fibronectin type 21 domain by altering the native protein which is composed of multiple beta strands distributed between two beta sheets. Depending on the originating tissue, fibronectin may contain multiple type 21 domains which may be denoted, e.g., 1Fn3, 2Fn3, 3Fn3, etc. Adnectin molecules may also be derived from polymers of 10Fn3 related molecules rather than a simple monomeric 10Fn3 structure.


Although the native 10Fn3 domain typically binds to integrin, 10Fn3 proteins adapted to become adnectin molecules are altered so to bind antigens of interest, e.g., a marker(s). In one embodiment, the alteration to the 10Fn3 molecule comprises at least one mutation to a beta strand. In a preferred embodiment, the loop regions which connect the beta strands of the 10Fn3 molecule are altered to bind to an antigen of interest, e.g., a marker(s).


The alterations in the 10Fn3 may be made by any method known in the art including, but not limited to, error prone PCR, site-directed mutagenesis, DNA shuffling, or other types of recombinational mutagenesis which have been referenced herein. In one example, variants of the DNA encoding the 10Fn3 sequence may be directly synthesized in vitro, and later transcribed and translated in vitro or in vivo. Alternatively, a natural 10Fn3 sequence may be isolated or cloned from the genome using standard methods (as performed, e.g., in U.S. Pat. Application No. 20070082365), and then mutated using mutagenesis methods known in the art.


An aptamer is another type of antibody-mimetic which may be used in the methods of the present invention. Aptamers are typically small nucleotide polymers that bind to specific molecular targets. Aptamers may be single or double stranded nucleic acid molecules (DNA or RNA), although DNA based aptamers are most commonly double stranded. There is no defined length for an aptamer nucleic acid; however, aptamer molecules are most commonly between 15 and 40 nucleotides long.


Aptamers may be generated using a variety of techniques, but were originally developed using in vitro selection (Ellington and Szostak. (1990) Nature. 346(6287):818-22) and the SELEX method (systematic evolution of ligands by exponential enrichment) (Schneider et al. 1992. J Mol Biol. 228(3):862-9) the contents of which are incorporated herein by reference. Other methods to make and uses of aptamers have been published including Klussmann. The Aptamer Handbook: Functional Oligonucleotides and Their Applications. ISBN: 978-3-527-31059-3; Ulrich et al. 2006. Comb Chem High Throughput Screen 9(8):619-32; Cerchia and de Franciscis. 2007. Methods Mol Biol. 361:187-200; Ireson and Kelland. 2006. Mol Cancer Ther. 2006 5(12):2957-62; U.S. Pat. Nos. 5,582,981; 5,840,867; 5,756,291; 6,261,783; 6,458,559; 5,792,613; 6,111,095; and U.S. patent application Ser. Nos. 11/482,671; 11/102,428; 11/291,610; and 10/627,543 which are all incorporated herein by reference.


Aptamer molecules made from peptides instead of nucleotides may also be used in the methods of the invention. Peptide aptamers share many properties with nucleotide aptamers (e.g., small size and ability to bind target molecules with high affinity) and they may be generated by selection methods that have similar principles to those used to generate nucleotide aptamers, for example Baines and Colas. 2006. Drug Discov Today. 11(7-8):334-41; and Bickle et al. 2006. Nat Protoc. 1(3):1066-91 which are incorporated herein by reference.


Affibody molecules represent a class of affinity proteins based on a 58-amino acid residue protein domain, derived from one of the IgG-binding domains of staphylococcal protein A. This three helix bundle domain has been used as a scaffold for the construction of combinatorial phagemid libraries, from which Affibody variants that target the desired molecules can be selected using phage display technology (Nord K, et al. Nat Biotechnol 1997; 15:772-7. Ronmark J, et al., Eur J Biochem 2002; 269:2647-55). Further details of Affibodies and methods of production thereof may be obtained by reference to U.S. Pat. No. 5,831,012 which is herein incorporated by reference in its entirety.


DARPins (Designed Ankyrin Repeat Proteins) are one example of an antibody mimetic DRP (Designed Repeat Protein) technology that has been developed to exploit the binding abilities of non-antibody polypeptides. Repeat proteins such as ankyrin or leucine-rich repeat proteins, are ubiquitous binding molecules, which occur, unlike antibodies, intra- and extracellularly. Their unique modular architecture features repeating structural units (repeats), which stack together to form elongated repeat domains displaying variable and modular target-binding surfaces. Based on this modularity, combinatorial libraries of polypeptides with highly diversified binding specificities can be generated. This strategy includes the consensus design of self-compatible repeats displaying variable surface residues and their random assembly into repeat domains.


Additional information regarding DARPins and other DRP technologies can be found in U.S. Patent Application Publication No. 2004/0132028 and International Patent Application Publication No. WO 02/20565, both of which are hereby incorporated by reference in their entirety.


Anticalins are an additional antibody mimetic technology, however in this case the binding specificity is derived from lipocalins, a family of low molecular weight proteins that are naturally and abundantly expressed in human tissues and body fluids. Lipocalins have evolved to perform a range of functions in vivo associated with the physiological transport and storage of chemically sensitive or insoluble compounds. Lipocalins have a robust intrinsic structure comprising a highly conserved ß-barrel which supports four loops at one terminus of the protein. These loops form the entrance to a binding pocket and conformational differences in this part of the molecule account for the variation in binding specificity between individual lipocalins.


Lipocalins are cloned and their loops are subjected to engineering in order to create Anticalins. Libraries of structurally diverse Anticalins have been generated and Anticalin display allows the selection and screening of binding function, followed by the expression and production of soluble protein for further analysis in prokaryotic or eukaryotic systems. Studies have successfully demonstrated that Anticalins can be developed that are specific for virtually any human target protein can be isolated and binding affinities in the nanomolar or higher range can be obtained.


Anticalins can also be formatted as dual targeting proteins, so-called Duocalins. A Duocalin binds two separate therapeutic targets in one easily produced monomeric protein using standard manufacturing processes while retaining target specificity and affinity regardless of the structural orientation of its two binding domains.


Additional information regarding Anticalins can be found in U.S. Pat. No. 7,250,297 and International Patent Application Publication No. WO 99/16873, both of which are hereby incorporated by reference in their entirety.


Another antibody mimetic technology useful in the context of the instant invention are Avimers. Avimers are evolved from a large family of human extracellular receptor domains by in vitro exon shuffling and phage display, generating multidomain proteins with binding and inhibitory properties. Linking multiple independent binding domains has been shown to create avidity and results in improved affinity and specificity compared with conventional single-epitope binding proteins. Other potential advantages include simple and efficient production of multitarget-specific molecules in Escherichia coli, improved thermostability and resistance to proteases. Avimers with sub-nanomolar affinities have been obtained against a variety of targets.


Additional information regarding Avimers can be found in U.S. Patent Application Publication Nos. 2006/0286603, 2006/0234299, 2006/0223114, 2006/0177831, 2006/0008844, 2005/0221384, 2005/0164301, 2005/0089932, 2005/0053973, 2005/0048512, 2004/0175756, all of which are hereby incorporated by reference in their entirety.


Versabodies are another antibody mimetic technology that could be used in the context of the instant invention. Versabodies are small proteins of 3-5 kDa with >15% cysteines, which form a high disulfide density scaffold, replacing the hydrophobic core that typical proteins have. The replacement of a large number of hydrophobic amino acids, comprising the hydrophobic core, with a small number of disulfides results in a protein that is smaller, more hydrophilic (less aggregation and non-specific binding), more resistant to proteases and heat, and has a lower density of T-cell epitopes, because the residues that contribute most to MHC presentation are hydrophobic. All four of these properties are well-known to affect immunogenicity, and together they are expected to cause a large decrease in immunogenicity.


Additional information regarding Versabodies can be found in U.S. Patent Application Publication No. 2007/0191272 which is hereby incorporated by reference in its entirety.


SMIPs™ (Small Modular ImmunoPharmaceuticals-Trubion Pharmaceuticals) engineered to maintain and optimize target binding, effector functions, in vivo half-life, and expression levels. SMIPS consist of three distinct modular domains. First they contain a binding domain which may consist of any protein which confers specificity (e.g., cell surface receptors, single chain antibodies, soluble proteins, etc). Secondly, they contain a hinge domain which serves as a flexible linker between the binding domain and the effector domain, and also helps control multimerization of the SMIP drug. Finally, SMIPS contain an effector domain which may be derived from a variety of molecules including Fc domains or other specially designed proteins. The modularity of the design, which allows the simple construction of SMIPs with a variety of different binding, hinge, and effector domains, provides for rapid and customizable drug design.


More information on SMIPs, including examples of how to design them, may be found in Zhao et al. (2007) Blood 110:2569-77 and the following U.S. Pat. App. Nos. 20050238646; 20050202534; 20050202028; 20050202023; 20050202012; 20050186216; 20050180970; and 20050175614.


In another aspect, the methods of the present invention employ immunoconjugate agents that target a marker(s) and which inhibit or down-modulate the marker(s). Agents that can be targeted to a marker(s) include, but are not limited to, cytotoxic agents, anti-inflammatory agents, e.g., a steroidal or nonsteroidal inflammatory agent, or a cytotoxin antimetabolites (e.g., methotrexate, 6-mercaptopurine, 6-thioguanine, cytarabine, 5-fluorouracil decarbazine), alkylating agents (e.g., mechlorethamine, thioepa chlorambucil, melphalan, carmustine (BSNU) and lomustine (CCNU), cyclothosphamide, busulfan, dibromomannitol, streptozotocin, mitomycin C, and cis-dichlorodiamine platinum (II) (DDP) cisplatin), anthracyclines (e.g., daunorubicin (formerly daunomycin) and doxorubicin), antibiotics (e.g., dactinomycin (formerly actinomycin), bleomycin, mithramycin, and anthramycin (AMC)), and anti-mitotic agents (e.g., vincristine and vinblastine).


In another embodiment, marker(s) modulator employed in the methods of the invention are small molecules. As used herein, the term “small molecule” is a term of the art and includes molecules that are less than about 7500, less than about 5000, less than about 1000 molecular weight or less than about 500 molecular weight, and inhibit marker(s) activity. Exemplary small molecules include, but are not limited to, small organic molecules (e.g., Cane et al. 1998. Science 282:63), and natural product extract libraries. In another embodiment, the compounds are small, organic non-peptidic compounds. Like antibodies, these small molecule inhibitors indirectly or directly inhibit the activity of a marker(s).


In another embodiment, the marker(s) modulator employed in the methods of the present invention is an antisense nucleic acid molecule that is complementary to a gene encoding a marker(s) or to a portion of that gene, or a recombinant expression vector encoding the antisense nucleic acid molecule. As used herein, an “antisense” nucleic acid comprises a nucleotide sequence which is complementary to a “sense” nucleic acid encoding a protein, e.g., complementary to the coding strand of a double-stranded cDNA molecule, complementary to an mRNA sequence or complementary to the coding strand of a gene. Accordingly, an antisense nucleic acid can hydrogen bond to a sense nucleic acid.


The use of antisense nucleic acids to down-modulate the expression of a particular protein in a cell is well known in the art (see e.g., Weintraub, H. et al., Antisense RNA as a molecular tool for genetic analysis, Reviews—Trends in Genetics, Vol. 1(1) 1986; Askari, F. K. and McDonnell, W. M. (1996) N. Eng. J. Med. 334:316-318; Bennett, M. R. and Schwartz, S. M. (1995) Circulation 92:1981-1993; Mercola, D. and Cohen, J. S. (1995) Cancer Gene Ther. 2:47-59; Rossi, J. J. (1995) Br. Med. Bull. 51:217-225; Wagner, R. W. (1994) Nature 372:333-335). An antisense nucleic acid molecule comprises a nucleotide sequence that is complementary to the coding strand of another nucleic acid molecule (e.g., an mRNA sequence) and accordingly is capable of hydrogen bonding to the coding strand of the other nucleic acid molecule. Antisense sequences complementary to a sequence of an mRNA can be complementary to a sequence found in the coding region of the mRNA, the 5′ or 3′ untranslated region of the mRNA or a region bridging the coding region and an untranslated region (e.g., at the junction of the 5′ untranslated region and the coding region). Furthermore, an antisense nucleic acid can be complementary in sequence to a regulatory region of the gene encoding the mRNA, for instance a transcription initiation sequence or regulatory element. Preferably, an antisense nucleic acid is designed so as to be complementary to a region preceding or spanning the initiation codon on the coding strand or in the 3′ untranslated region of an mRNA.


Antisense nucleic acids can be designed according to the rules of Watson and Crick base pairing. The antisense nucleic acid molecule can be complementary to the entire coding region of marker(s) mRNA, but more preferably is an oligonucleotide which is antisense to only a portion of the coding or noncoding region of marker(s) mRNA. For example, the antisense oligonucleotide can be complementary to the region surrounding the translation start site of marker(s) mRNA. An antisense oligonucleotide can be, for example, about 5, 10, 15, 20, 25, 30, 35, 40, 45 or 50 nucleotides in length.


An antisense nucleic acid can be constructed using chemical synthesis and enzymatic ligation reactions using procedures known in the art. For example, an antisense nucleic acid (e.g., an antisense oligonucleotide) can be chemically synthesized using naturally occurring nucleotides or variously modified nucleotides designed to increase the biological stability of the molecules or to increase the physical stability of the duplex formed between the antisense and sense nucleic acids, e.g., phosphorothioate derivatives and acridine substituted nucleotides can be used. Examples of modified nucleotides which can be used to generate the antisense nucleic acid include 5-fluorouracil, 5-bromouracil, 5-chlorouracil, 5-iodouracil, hypoxanthine, xantine, 4-acetylcytosine, 5-(carboxyhydroxylmethyl) uracil, 5-carboxymethylaminomethyl-2-thiouridine, 5-carboxymethylaminomethyluracil, dihydrouracil, beta-D-galactosylqueosine, inosine, N6-isopentenyladenine, 1-methylguanine, 1-methylinosine, 2,2-dimethylguanine, 2-methyladenine, 2-methylguanine, 3-methylcytosine, 5-methylcytosine, N6-adenine, 7-methylguanine, 5-methylaminomethyluracil, 5-methoxyaminomethyl-2-thiouracil, beta-D-mannosylqueosine, 5′-methoxycarboxymethyluracil, 5-methoxyuracil, 2-methylthio-N6-isopentenyladenine, uracil-5-oxyacetic acid (v), wybutoxosine, pseudouracil, queosine, 2-thiocytosine, 5-methyl-2-thiouracil, 2-thiouracil, 4-thiouracil, 5-methyluracil, uracil-5-oxyacetic acid methylester, uracil-5-oxyacetic acid (v), 5-methyl-2-thiouracil, 3-(3-amino-3-N-2-carboxypropyl) uracil, (acp3)w, and 2,6-diaminopurine. Alternatively, the antisense nucleic acid can be produced biologically using an expression vector into which a nucleic acid has been subcloned in an antisense orientation (i.e., RNA transcribed from the inserted nucleic acid will be of an antisense orientation to a target nucleic acid of interest, described further in the following subsection).


The antisense nucleic acid molecules that can be utilized in the methods of the present invention are typically administered to a subject or generated in situ such that they hybridize with or bind to cellular mRNA and/or genomic DNA encoding a marker(s) to thereby inhibit expression by inhibiting transcription and/or translation. The hybridization can be by conventional nucleotide complementarity to form a stable duplex, or, for example, in the case of an antisense nucleic acid molecule which binds to DNA duplexes, through specific interactions in the major groove of the double helix. An example of a route of administration of antisense nucleic acid molecules includes direct injection at a tissue site. Alternatively, antisense nucleic acid molecules can be modified to target selected cells and then administered systemically. For example, for systemic administration, antisense molecules can be modified such that they specifically bind to receptors or antigens expressed on a selected cell surface, e.g., by linking the antisense nucleic acid molecules to peptides or antibodies which bind to cell surface receptors or antigens. The antisense nucleic acid molecules can also be delivered to cells using vectors well known in the art and described in, for example, US20070111230 the entire contents of which are incorporated herein. To achieve sufficient intracellular concentrations of the antisense molecules, vector constructs in which the antisense nucleic acid molecule is placed under the control of a strong pol II or pol III promoter are preferred.


In yet another embodiment, the antisense nucleic acid molecule employed by the methods of the present invention can include an α-anomeric nucleic acid molecule. An α-anomeric nucleic acid molecule forms specific double-stranded hybrids with complementary RNA in which, contrary to the usual β-units, the strands run parallel to each other (Gaultier et al. (1987) Nucleic Acids. Res. 15:6625-6641). The antisense nucleic acid molecule can also comprise a 2′-o-methylribonucleotide (Inoue et al. (1987) Nucleic Acids Res. 15:6131-6148) or a chimeric RNA-DNA analogue (Inoue et al. (1987) FEBS Lett. 215:327-330).


In another embodiment, an antisense nucleic acid used in the methods of the present invention is a compound that mediates RNAi. RNA interfering agents include, but are not limited to, nucleic acid molecules including RNA molecules which are homologous to a marker(s) or a fragment thereof, “short interfering RNA” (siRNA), “short hairpin” or “small hairpin RNA” (shRNA), and small molecules which interfere with or inhibit expression of a target gene by RNA interference (RNAi). RNA interference is a post-transcriptional, targeted gene-silencing technique that uses double-stranded RNA (dsRNA) to degrade messenger RNA (mRNA) containing the same sequence as the dsRNA (Sharp, P. A. and Zamore, P. D. 287, 2431-2432 (2000); Zamore, P. D., et al. Cell 101, 25-33 (2000). Tuschl, T. et al. Genes Dev. 13, 3191-3197 (1999)). The process occurs when an endogenous ribonuclease cleaves the longer dsRNA into shorter, 21- or 22-nucleotide-long RNAs, termed small interfering RNAs or siRNAs. The smaller RNA segments then mediate the degradation of the target mRNA. Kits for synthesis of RNAi are commercially available from, e.g., New England Biolabs and Ambion. In one embodiment one or more of the chemistries described above for use in antisense RNA can be employed.


In still another embodiment, an antisense nucleic acid is a ribozyme. Ribozymes are catalytic RNA molecules with ribonuclease activity which are capable of cleaving a single-stranded nucleic acid, such as an mRNA, to which they have a complementary region. Thus, ribozymes (e.g., hammerhead ribozymes (described in Haselhoff and Gerlach, 1988, Nature 334:585-591) can be used to catalytically cleave marker(s) mRNA transcripts to thereby inhibit translation of the marker(s) mRNA.


Alternatively, gene expression can be inhibited by targeting nucleotide sequences complementary to the regulatory region of a marker(s) (e.g., the promoter and/or enhancers) to form triple helical structures that prevent transcription of the marker(s) gene. See generally, Helene, C., 1991, Anticancer Drug Des. 6(6):569-84; Helene, C. et al., 1992, Ann. N.Y. Acad. Sci. 660:27-36; and Maher, L. J., 1992, Bioassays 14(12):807-15.


In another embodiment, the marker(s) modulator used in the methods of the present invention is a fusion protein or peptidic compound derived from the marker(s) amino acid sequence. In particular, the inhibitory compound comprises a fusion protein or a portion of a marker(s) (or a mimetic thereof) that mediates interaction of the marker(s) with a target molecule such that contact of the marker(s) with this fusion protein or peptidic compound competitively inhibits the interaction of the marker(s) with the target molecule. Such fusion proteins and peptidic compounds can be made using standard techniques known in the art. For example, peptidic compounds can be made by chemical synthesis using standard peptide synthesis techniques and then introduced into cells by a variety of means known in the art for introducing peptides into cells (e.g., liposome and the like).


The in vivo half-life of the fusion protein or peptidic compounds of the invention can be improved by making peptide modifications, such as the addition of N-linked glycosylation sites into the marker(s) or conjugating the marker(s) to poly(ethylene glycol) (PEG; pegylation), e.g., via lysine-monopegylation. Such techniques have proven to be beneficial in prolonging the half-life of therapeutic protein drugs. It is expected that pegylation of marker(s) polypeptides of the invention may result in similar pharmaceutical advantages.


In addition, pegylation can be achieved in any part of a polypeptide of the invention by the introduction of a nonnatural amino acid. Certain nonnatural amino acids can be introduced by the technology described in Deiters et al., J Am Chem Soc 125:11782-11783, 2003; Wang and Schultz, Science 301:964-967, 2003; Wang et al., Science 292:498-500, 2001; Zhang et al., Science 303:371-373, 2004 or in U.S. Pat. No. 7,083,970. Briefly, some of these expression systems involve site-directed mutagenesis to introduce a nonsense codon, such as an amber TAG, into the open reading frame encoding a polypeptide of the invention. Such expression vectors are then introduced into a host that can utilize a tRNA specific for the introduced nonsense codon and charged with the nonnatural amino acid of choice. Particular nonnatural amino acids that are beneficial for purpose of conjugating moieties to the polypeptides of the invention include those with acetylene and azido side chains. Marker(s) polypeptides containing these novel amino acids can then be pegylated at these chosen sites in the protein.


2. Stimulatory Agents


According to a modulatory method of the invention, the expression and/or activity of a marker(s) is stimulated in a cell or subject by contacting the cell with (or administering to a subject) a stimulatory agent. Stimulatory agents of the invention can be, for example, molecules that act to stimulate or increase the expression and/or activity of the marker(s).


Examples of such stimulatory agents include active marker(s) polypeptide and nucleic acid molecules encoding the marker(s) that are introduced into the cell to increase expression and/or activity of the marker in the cell. A preferred stimulatory agent is a nucleic acid molecule encoding a marker(s) polypeptide, wherein the nucleic acid molecule is introduced into the cell in a form suitable for expression of the active marker(s) polypeptide in the cell. To express a marker(s) polypeptide in a cell, typically a marker(s)-encoding cDNA (full length or partial cDNA sequence) is first introduced into a recombinant expression vector using standard molecular biology techniques, and the vector may be transfected into cells using standard molecular biology techniques. A cDNA can be obtained, for example, by amplification using the polymerase chain reaction (PCR), using primers based on the marker(s) nucleotide sequence or by screening an appropriate cDNA library.


The nucleic acids for use in the methods of the invention can also be prepared, e.g., by standard recombinant DNA techniques. A nucleic acid of the invention can also be chemically synthesized using standard techniques. Various methods of chemically synthesizing polydeoxynucleotides are known, including solid-phase synthesis which has been automated in commercially available DNA synthesizers (See e.g., Itakura et al. U.S. Pat. No. 4,598,049; Caruthers et al. U.S. Pat. No. 4,458,066; and Itakura U.S. Pat. Nos. 4,401,796 and 4,373,071, incorporated by reference herein).


In one embodiment, a nucleic acid molecule encoding a marker(s) may be present in an inducible construct. In another embodiment, a nucleic acid molecule encoding marker(s) may be present in a construct which leads to constitutive expression. In one embodiment, a nucleic acid molecule encoding marker(s) may be delivered to cells, or to subjects, in the absence of a vector.


A nucleic acid molecule encoding marker(s) may be delivered to cells or to subjects using a viral vector, preferably one whose use for gene therapy is well known in the art. Techniques for the formation of vectors or virions are generally described in “Working Toward Human Gene Therapy,” Chapter 28 in Recombinant DNA, 2nd Ed., Watson, J. D. et al., eds., New York: Scientific American Books, pp. 567-581 (1992). An overview of suitable viral vectors or virions is provided in Wilson, J. M., Clin. Exp. Immunol. 107(Suppl. 1):31-32 (1997), as well as Nakanishi, M., Crit. Rev. Therapeu. Drug Carrier Systems 12:263-310 (1995); Robbins, P. D., et al., Trends Biotechnol. 16:35-40 (1998); Zhang, J., et al., Cancer Metastasis Rev. 15:385-401(1996); and Kramm, C. M., et al., Brain Pathology 5:345-381 (1995). Such vectors may be derived from viruses that contain RNA (Vile, R. G., et al., Br. Med Bull. 51:12-30 (1995)) or DNA (Ali M., et al., Gene Ther. 1:367-384 (1994)).


Examples of viral vector systems utilized in the gene therapy art and, thus, suitable for use in the present invention, include the following: retroviruses (Vile, R. G., supra; U.S. Pat. Nos. 5,741,486 and 5,763,242); adenoviruses (Brody, S. L., et al., Ann. N.Y. Acad. Sci. 716: 90-101 (1994); Heise, C. et al., Nat. Med. 3:639-645 (1997)); adenoviral/retroviral chimeras (Bilbao, G., et al., FASEB J. 11:624-634 (1997); Feng, M., et al., Nat. Biotechnol. 15:866-870 (1997)); adeno-associated viruses (Flotte, T. R. and Carter, B. J., Gene Ther. 2:357-362 (1995); U.S. Pat. No. 5,756,283); herpes simplex virus I or II (Latchman, D. S., Mol. Biotechnol. 2:179-195 (1994); U.S. Pat. No. 5,763,217; Chase, M., et al., Nature Biotechnol. 16:444-448 (1998)); parvovirus (Shaughnessy, E., et al., Semin Oncol. 23:159-171 (1996)); reticuloendotheliosis virus (Donburg, R., Gene Therap. 2:301-310 (1995)). Extrachromosomal replicating vectors may also be used in the gene therapy methods of the present invention. Such vectors are described in, for example, Calos, M. P. (1996) Trends Genet. 12:463-466, the entire contents of which are incorporated herein by reference. Other viruses that can be used as vectors for gene delivery include poliovirus, papillomavirus, vaccinia virus, lentivirus, as well as hybrid or chimeric vectors incorporating favorable aspects of two or more viruses (Nakanishi, M. (1995) Crit. Rev. Therapeu. Drug Carrier Systems 12:263-310; Zhang, J., et al. (1996) Cancer Metastasis Rev. 15:385-401; Jacoby, D. R., et al. (1997) Gene Therapy 4:1281-1283).


The term “AAV vector” refers to a vector derived from an adeno-associated virus serotype, including without limitation, AAV-1, AAV-2, AAV-3, AAV-4, AAV-5, or AAVX7. “rAAV vector” refers to a vector that includes AAV nucleotide sequences as well as heterologous nucleotide sequences. rAAV vectors require only the 145 base terminal repeats in cis to generate virus. All other viral sequences are dispensable and may be supplied in trans (Muzyczka (1992) Curr. Topics Microbiol. Immunol. 158:97). Typically, the rAAV vector genome will only retain the inverted terminal repeat (ITR) sequences so as to maximize the size of the transgene that can be efficiently packaged by the vector. The ITRs need not be the wild-type nucleotide sequences, and may be altered, e.g., by the insertion, deletion or substitution of nucleotides, as long as the sequences provide for functional rescue, replication and packaging. In particular embodiments, the AAV vector is an AAV2/5 or AAV2/8 vector. Suitable AAV vectors are described in, for example, U.S. Pat. No. 7,056,502 and Yan et al. (2002) J. Virology 76(5):2043-2053, the entire contents of which are incorporated herein by reference.


As used herein, the term “lentivirus” refers to a group (or genus) of retroviruses that give rise to slowly developing disease. Viruses included within this group include HIV (human immunodeficiency virus; including but not limited to HIV type 1 and HIV type 2), the etiologic agent of the human acquired immunodeficiency syndrome (AIDS); visna-maedi, which causes encephalitis (visna) or pneumonia (maedi) in sheep; the caprine arthritis-encephalitis virus, which causes immune deficiency, arthritis, and encephalopathy in goats; equine infectious anemia virus (EIAV), which causes autoimmune hemolytic anemia, and encephalopathy in horses; feline immunodeficiency virus (FIV), which causes immune deficiency in cats; bovine immune deficiency virus (BIV), which causes lymphadenopathy, lymphocytosis, and possibly central nervous system infection in cattle; and simian immunodeficiency virus (SIV), which cause immune deficiency and encephalopathy in sub-human primates. Diseases caused by these viruses are characterized by a long incubation period and protracted course. Usually, the viruses latently infect monocytes and macrophages, from which they spread to other cells. HIV, FIV, and SIV also readily infect T lymphocytes (i.e., T-cells). In one embodiment of the invention, the lentivirus is not HIV.


As used herein, the term “adenovirus” (“Ad”) refers to a group of double-stranded DNA viruses with a linear genome of about 36 kb. See, e.g., Berkner et al., Curr. Top. Microbiol. Immunol., 158: 39-61 (1992). In some embodiments, the adenovirus-based vector is an Ad-2 or Ad-5 based vector. See, e.g., Muzyczka, Curr. Top. Microbiol. Immunol., 158: 97-123, 1992; Ali et al., 1994 Gene Therapy 1: 367-384; U.S. Pat. Nos. 4,797,368, and 5,399,346. Suitable adenovirus vectors derived from the adenovirus strain Ad type 5 d1324 or other strains of adenovirus (e.g., Ad2, Ad3, Ad7 etc.) are well known to those skilled in the art. Recombinant adenoviruses are advantageous in that they do not require dividing cells to be effective gene delivery vehicles and can be used to infect a wide variety of cell types. Additionally, introduced adenovirus DNA (and foreign DNA contained therein) is not integrated into the genome of a host cell but remains episomal, thereby avoiding potential problems that can occur as a result of insertional mutagenesis in situations where introduced DNA becomes integrated into the host genome (e.g., retroviral DNA). Moreover, the carrying capacity of the adenovirus genome for foreign DNA is large (up to 8 kilobases) relative to other gene delivery vectors (Haj-Ahmand et al. J. Virol. 57, 267-273 [1986]).


In one embodiment, an adenovirus is a replication defective adenovirus. Most replication-defective adenoviral vectors currently in use have all or parts of the viral E1 and E3 genes deleted but retain as much as 80% of the adenovirus genetic material. Adenovirus vectors deleted for all viral coding regions are also described by Kochanek et al. and Chamberlain et al. (U.S. Pat. Nos. 5,985,846 and 6,083,750). Such viruses are unable to replicate as viruses in the absence of viral products provided by a second virus, referred to as a “helper” virus.


In one embodiment, an adenoviral vector is a “gutless” vector. Such vectors contain a minimal amount of adenovirus DNA and are incapable of expressing any adenovirus antigens (hence the term “gutless”). The gutless replication defective Ad vectors provide the significant advantage of accommodating large inserts of foreign DNA while completely eliminating the problem of expressing adenoviral genes that result in an immunological response to viral proteins when a gutless replication defective Ad vector is used in gene therapy. Methods for producing gutless replication defective Ad vectors have been described, for example, in U.S. Pat. No. 5,981,225 to Kochanek et al., and U.S. Pat. Nos. 6,063,622 and 6,451,596 to Chamberlain et al; Parks et al., PNAS 93:13565 (1996) and Lieber et al., J. Virol. 70:8944-8960 (1996).


In another embodiment, an adenoviral vector is a “conditionally replicative adenovirus” (“CRAds”). CRAds are genetically modified to preferentially replicate in specific cells by either (i) replacing viral promoters with tissue specific promoters or (ii) deletion of viral genes important for replication that are compensated for by the target cells only. The skilled artisan would be able to identify epithelial cell specific promoters.


Other art known adenoviral vectors may be used in the methods of the invention. Examples include Ad vectors with recombinant fiber proteins for modified tropism (as described in, e.g., van Beusechem et al., 2000 Gene Ther. 7: 1940-1946), protease pre-treated viral vectors (as described in, e.g., Kuriyama et al., 2000 Hum. Gene Ther. 11: 2219-2230), E2a temperature sensitive mutant Ad vectors (as described in, e.g., Engelhardt et al., 1994 Hum. Gene Ther. 5: 1217-1229), and “gutless” Ad vectors (as described in, e.g., Armentano et al., 1997 J. Virol. 71: 2408-2416; Chen et al., 1997 Proc. Nat. Acad. Sci. USA 94: 1645-1650; Schieder et al., 1998 Nature Genetics 18: 180-183).


The vector will include one or more promoters or enhancers, the selection of which will be known to those skilled in the art. Suitable promoters include, but are not limited to, the retroviral long terminal repeat (LTR), the SV40 promoter, the human cytomegalovirus (CMV) promoter, and other viral and eukaryotic cellular promoters known to the skilled artisan.


Guidance in the construction of gene therapy vectors and the introduction thereof into affected subjects for therapeutic purposes may be obtained in the above-referenced publications, as well as in U.S. Pat. Nos. 5,631,236, 5,688,773, 5,691,177, 5,670,488, 5,529,774, 5,601,818, and PCT Publication No. WO 95/06486, the entire contents of which are incorporated herein by reference.


Generally, methods are known in the art for viral infection of the cells of interest. The virus can be placed in contact with the cell of interest or alternatively, can be injected into a subject suffering from a retinal disorder, for example, as described in U.S. Provisional Patent Application No. 61/169,835 and PCT Application No. PCT/US09/053730, the contents of each of which are incorporated by reference.


Gene therapy vectors comprising a nucleic acid molecule encoding a marker(s) can be delivered to a subject or a cell by any suitable method in the art, for example, intravenous injection, local administration, e.g., application of the nucleic acid in a gel, oil, or cream, (see, e.g., U.S. Pat. No. 5,328,470), stereotactic injection (see, e.g., Chen et al. (1994) Proc. Natl. Acad. Sci. U.S.A. 91:3054), gene gun, or by electroporation (see, e.g., Matsuda and Cepko (2007) Proc. Natl. Acad. Sci. U.S.A. 104:1027), using lipid-based transfection reagents, or by any other suitable transfection method.


As used herein, the terms “transformation” and “transfection” are intended to refer to a variety of art-recognized techniques for introducing foreign nucleic acid (e.g., DNA) into a host cell, including calcium phosphate or calcium chloride co-precipitation, DEAE-dextran-mediated transfection, lipofection (e.g., using commercially available reagents such as, for example, LIPOFECTIN® (Invitrogen Corp., San Diego, Calif.), LIPOFECTAMINE® (Invitrogen), FUGENE® (Roche Applied Science, Basel, Switzerland), JETPEI™ (Polyplus-transfection Inc., New York, N.Y.), EFFECTENE® (Qiagen, Valencia, Calif.), DREAMFECT™ (OZ Biosciences, France) and the like), or electroporation (e.g., in vivo electroporation). Suitable methods for transforming or transfecting host cells can be found in Sambrook, et al. (Molecular Cloning: A Laboratory Manual. 2nd, ed., Cold Spring harbor Laboratory, Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y., 1989), and other laboratory manuals.


In one embodiment, a marker(s) is delivered to a subject or cells in the form of a peptide or protein. In order to produce such peptides or proteins, recombinant expression vectors of the invention can be designed for expression of one or more marker(s) proteins, and/or portion(s) thereof in prokaryotic or eukaryotic cells. For example, one or more glucose transporter proteins and/or portion(s) thereof can be expressed in bacterial cells such as E. coli, insect cells (using baculovirus expression vectors) yeast cells or mammalian cells. Suitable host cells are discussed further in Goeddel, Gene Expression Technology: Methods in Enzymology 185, Academic Press, San Diego, Calif. (1990). Alternatively, the recombinant expression vector can be transcribed and translated in vitro, for example using T7 promoter regulatory sequences and T7 polymerase.


In one embodiment, the recombinant mammalian expression vector is capable of directing expression of the nucleic acid preferentially in a particular cell type (e.g., tissue-specific regulatory elements are used to express the nucleic acid). Tissue-specific regulatory elements are known in the art. Non-limiting examples of suitable tissue-specific promoters include retinal cell-type-specific promoters (e.g., rhodopsin regulatory sequences, Cabp5, Cralbp, Nrl, Crx, Ndrg4, clusterin, Rax, Hest and the like (Matsuda and Cepko, supra)), the albumin promoter (liver-specific, Pinkert et al. (1987) Genes Dev. 1:268), neuron-specific promoters (e.g., the neurofilament promoter; Byrne and Ruddle (1989) Proc. Natl. Acad. Sci. U.S.A. 86:5473). Developmentally-regulated promoters are also encompassed, for example the α-fetoprotein promoter (Campes and Tilghman (1989) Genes Dev. 3:537).


Application of the methods of the invention for the treatment and/or prevention of a retinal disorder can result in curing the disorder, decreasing at least one symptom associated with the disorder, either in the long term or short term or simply a transient beneficial effect to the subject. Accordingly, as used herein, the terms “treat,” “treatment” and “treating” include the application or administration of agents, as described herein, to a subject who is suffering from a retinal disorder, or who is susceptible to such conditions with the purpose of curing, healing, alleviating, relieving, altering, remedying, ameliorating, improving or affecting such conditions or at least one symptom of such conditions. As used herein, the condition is also “treated” if recurrence of the condition is reduced, slowed, delayed or prevented.


A modulatory agent, such as a chemical compound, can be administered to a subject as a pharmaceutical composition. Such compositions typically comprise the modulatory agent and a pharmaceutically acceptable carrier. As used herein the term “pharmaceutically acceptable carrier” is intended to include any and all solvents, dispersion media, coatings, antibacterial and antifungal agents, isotonic and absorption delaying agents, and the like, compatible with pharmaceutical administration. The use of such media and agents for pharmaceutically active substances is well known in the art. Except insofar as any conventional media or agent is incompatible with the active compound, use thereof in the compositions is contemplated. Supplementary active compounds can also be incorporated into the compositions. Pharmaceutical compositions can be prepared as described above.


E. Methods of Identifying Type 2 Diabetes Biomarkers


The present invention further provides methods for identifying type 2 diabetes biomarkers useful as markers for, e.g., disease (prognostics and diagnostics), therapeutic effectiveness of a drug (theranostics) and of drug toxicity. For example, as described above, the markers described herein and the markers identified using the methods for biomarker discovery are useful for, e.g., determining whether a subject has or will develop impaired glucose tolerance; determining whether a subject has or will develop type 2 diabetes; determining whether a subject having type 2 diabetes will respond to a diabetic therapy; monitoring the effectiveness of a therapy for inhibiting the development of impaired glucose tolerance and/or type 2 diabetes, reducing or slowing down the progression of normal glucose tolerance to impaired fasting glycaemia, to impaired glucose tolerance, and/or to diabetes, and/or reducing or inhibiting the development of complications associated with the disease in a subject; in screening assays to identify molecules which modulate, e.g., decrease or increase, the expression and/or activity of a marker(s) of the invention for e.g., use as therapeutics.


Methods for identifying a type 2 diabetes marker are described in the working examples and include identifying proteins in the secretory vesicles of two or more organs from two or more species under steady state conditions, identifying proteins in the secretory vesicles of pancreatic β cells thereby generating a provisional list of steady state markers, identifying the markers in the provisional list of steady state markers from the two or more organs from the two or more species common to the markers in the secretory vesicles of pancreatic β cells and removing those markers from the provisional list of steady state markers, thereby generating a list of β cell mass markers; identifying proteins in the secretory vesicles of pancreatic β cells under dysfunctional conditions, identifying proteins in the secretory vesicles of pancreatic β cells under normal conditions, identifying the proteins that were differentially expressed under dysfunctional conditions and under normal conditions, thereby generating a provisional list of β cell function markers, determining the level of a β cell mass marker and/or a β cell function marker in a sample form a control subject, e.g., a having normal glucose tolerance, determining the level of the marker in a test sample from a subject having, e.g., impaired glucose tolerance and/or type 2 diabetes. A difference in the level of a marker in the control sample as compared to the level in the test sample, e.g., a statistically significant level, identifies the marker as a type 2 diabetes biomarker.


A type 2 diabetes marker may also be identified by determining the level of a protein in a first sample obtained from a subject having type 2 diabetes prior to providing at least a portion of a therapy to the subject, and determining the level of a protein in a second sample obtained from the subject following provision of at least a portion of the therapy. A difference in the level of expression of the protein in the second sample relative to the first sample, e.g., a statistically significant level, identifies the protein as a type 2 diabetes marker.


IV. Kits of the Invention

The invention also provides kits for determining whether a subject has or will develop impaired glucose tolerance and/or whether a subject has or will develop type 2 diabetes. Kits to determine whether a subject will develop type 2 diabetes complications, to determine whether a treatment will be efficacious for treating a subject having impaired glucose tolerance and/or type 2 diabetes and kits for monitoring the effectiveness of a treatment are also provided.


These kits include means for determining the level of one or more markers of the invention and instructions for use of the kit.


The kits of the invention may optionally comprise additional components useful for performing the methods of the invention. By way of example, the kits may comprise reagents for obtaining a biological sample from a subject, a control sample, one or more sample compartments, a diabetic therapeutic, an instructional material which describes performance of a method of the invention and tissue specific controls/standards.


The reagents for determining the level of one or more marker(s) can include, for example, buffers or other reagents for use in an assay for evaluating the level of one or more markers, e.g., expression level (e.g., at either the mRNA or protein level). The instructions can be, for example, printed instructions for performing the assay for evaluating the level of one or more marker(s) of the invention.


The reagents for isolating a biological sample from a subject can comprise one or more reagents that can be used to obtain a fluid or tissue from a subject, such as means for obtaining a saliva or blood.


The kits of the invention may further comprise reagents for culturing a sample obtained from a subject.


Preferably, the kits are designed for use with a human subject.


The present invention is further illustrated by the following examples which should not be construed as further limiting. The contents of all references, patents and published patent applications cited throughout this application, as well as the Figures, are expressly incorporated herein by reference in their entirety.


EXAMPLES
Example I. Biomarker Identification

Materials and Methods


Candidate biomarkers were identified by evaluating proteins known or suspected to be secreted by pancreatic beta islets.


Three in vitro systems were used to identify secretory protein candidate biomarkers, primary human islets and 2 pancreatic ß-cell lines. The primary human islets were obtained from donors lacking major medical problems. Table 5 lists the characteristics of the donors. The cell lines used were the rat INS832/13 and the mouse MIN6. The experimental systems were analyzed using two conditions, steady state, and during an experimental dysfunctional state designed to mimic the pancreatic beta cell dysfunction observed in type 2 diabetes.









TABLE 5







Pancreatic islet donor characteristics.















Donor
VP146
VP149
VP151
VP152
Paraskevas
VP157
VP166
VP167





Gender
F
F
M
F
M
F
M
F


Age
43
44
59
35
29
26
59
50


Ethnicity
Caucasian
African
Caucasian
Caucasian
Caucasian
African
Caucasian
African




American



American

American


Ht (cm)
172.5
149.9 cm
175
157.5

1.59
170
157.5


Wt (kg)
104 kg
66.8 kg
84.5
80.6

84
61.8
93


BMI
34.9
29.6
27
31.6
22.1
33
20.7
36.3


Cause
Anoxic
ICH
Head
Head
Anoxic
HT/BI
CVA/
CVA/


of
brain

trauma
trauma
brain
secondary to
ICH
ICH


death
injury



injury
MVA




Smoking
no
quit 13
Occasional
Yes
?
<1 ppd
Occasional
No




y ago
(cigar)
(1 ppd)


(cigar)



EtOH
2-3/wk
1 glass
Occasional
No
?
rare, <1
Occasional
No




wive/day



month




Serologies
Neg
Neg
CMV+
CMV+, EBV+
None
Neg
EBV+
Neg


Medicines
None
None
None
None
None
None
None
None


Disease
None
None
None
None
None
None
None
None





ICH; Intracerebral hemorrhage.,


HT/BI; Head Trauma/brain injury


MVA; Motor vehicle accident.,


EBV+; Epstein-Barr virus positive,


CMV; Cytomegalovirus positive






For identification of proteins secreted during steady state, the cell lines were cultivated in RPMI containing 5 mM glucose and the primary human islets were kept in saline at 4° C. until secretory vesicle sample preparation. For identification of proteins secreted during a dysfunctional state, the experimental systems were incubated with 20 mM glucose/0.4 mM palmitate or with 25 mM glucose/0.4 mM palmitate (El-Assaad et al. (2010) Endocrinology 151:3061-73) until insulin production was reduced by at least 30% and programmed cell death was induced, events that typically occurred between 16-24 hours for the cell lines and between 36-72 hours for the primary islets.


Secretory protein preparations from both steady state and dysfunctionalized islets and cell lines were made using the same process. At least 4 independent replicates were used per experimental system. The cultured cells were harvested by scraping, centrifuged for 5 minutes at 4° C. at 1400 rpm to remove debris and resuspended in homogenization buffer (250 mM sucrose/10 mM Tris pH 7.4/protease inhibitor EDTA-free cocktail). The islet or cell line suspensions were homogenized using a Dounce homogenizer. The homogenate was adjusted to 1.4M sucrose. A 14 ml SW40Ti ultra-clear centrifuge tube (Beckman Coulter #344060) was layered with homogenate followed by 4 ml of 1.2M sucrose and topped with 0.8M sucrose. The samples were centrifuged for 2 hours at 155,000 g at 4° C. and vesicles were harvested from the 0.8-1.2M interface. The vesicles were washed in 0.5M KCl followed by incubation in ammonium carbonate pH11. Vesicle content was separated from the vesicle membranes by centrifugation at 112,000 g. Protein yields were measured using the BCA Protein Assay (Pierce #23227). In instances where sample was limiting, the entire secretory vesicle was processed for mass spectrometry analysis. Western blot characterization of the starting cell line homogenates and secretory protein final products were done using antibodies against proteins expressed in specific subcellular compartments, such as the plasma membrane, endoplasmic reticulum (ER), Golgi apparatus, and mitochondria. Both membrane-bound and soluble proteins associated with these compartments were used, to assess the relative enrichment of potentially secreted proteins from the relevant subcellular compartments in the preparations. FIG. 1 depicts Western blots of starting materials (Hom), intermediate (SV) and final product (SC) preparations of secreted proteins from a rat cell line (A) and human primary islets (B).


An additional set of secretory protein samples were prepared from a selection of major organs or from organs known to become involved in diabetes disease progression and complications, using the process described above, substituting more robust mechanical tissue disruption for the more fibrous organs. To generate the human organ secretome dataset, secretory proteins from lung, breast, kidney, prostate, bladder, and colon were prepared. For the rat dataset, secretory proteins from heart, liver, kidney, skeletal muscle, subcutaneous fat, and whole pancreas were prepared. This experiment was done in order to identify the secretory proteins that can also be made by other tissues than the primary islets or the beta cell lines. Secretory proteins that can be made by multiple tissues would thus likely have relatively less tissue specificity, and would thus be de-prioritized as biomarker candidates.


Once the secretory protein samples were generated they were further processed for mass spectrometry data acquisition and peptide and protein identification. Briefly, the samples were digested with trypsin to generate peptides. The peptides were then separated by strong cation exchange chromatography (SCX) into three fractions. Each of the three fractions per sample was analyzed by reversed phase liquid chromatography, coupled by electrospray to a Waters QTOF mass spectrometer (LC-MS). Components were detected and matched across all samples and compared for relative peak intensity. Peak intensity was normalized to account for small differences in protein concentration between samples. ANOVA was then applied to identify peptides that were differentially expressed between the groups of interest in the samples derived from dysfunctionalized islets or cell lines. High stringency thresholds were used to ensure the statistical significance of the identified peptides. All intensity values were log (base e) transformed with values <0 replaced by 0. A subset of the samples was used to create an average sample (i.e., the Reference sample) against which all samples were then normalized. The normalization factors were chosen so that the median of log ratios between each sample and the Reference sample over all the peptides was adjusted to zero. Peptide identification was done with custom protein database using Mascot (Matrix Science) software. Candidate biomarker annotation was done using a combination of manual literature review and network and pathway analysis (Ingenuity).


Several thousand proteins were identified in the secretomes of the primary islets, cell lines, and organs in the steady state. The secretory proteins identified in the islets or cell lines that were also found in the organ secretomes were removed. The remaining proteins were ordered to identify which subset was expressed either in the primary human islets alone, or also in at least one of the cell lines. A total of 170 proteins met these criteria, and these proteins therefore constituted the initial steady state biomarker dataset.


A similar process was used to identify the initial dysfunctionalized biomarker dataset. An additional requirement to the two previously described criteria was that any of the candidate biomarkers also be differentially expressed by at least 1.5-fold in the dysfunctional state compared to control. A total of 245 proteins met the criteria and these proteins therefore constituted the initial dysfunctionalized biomarker dataset.


Subjects used for the plasma-based biomarker verification analyses are indicated in Tables 6 and 7. Plasma was processed using 3 different methods. First, common high abundance plasma proteins were removed using affinity chromatography methods. Removing the most abundant plasma proteins allowed less abundant plasma proteins to be more readily measured. Some of the biomarker candidates, however, were expected to be present beneath the current level of detection of the MRM-MS assays deployed. To measure candidates from this low abundance class of biomarkers commercially available ELISA kits were used. Lastly, plasma was processed to enrich for exosomes. Exosomes are small vesicles that are secreted whole by numerous cell types under normal and disease conditions. Originally described in immune and central nervous system interactions, exosomes have since been described to be produced by multiple tissue types, and are present in multiple different body fluids including plasma. Exosomes and are now understood to be part of a general, widely used secretion mechanism.


Sequential high speed centrifugation methods were used to enrich the exosomes present in blood (Graner M W et al. (2009) FASEB J. 23:1541), and this method was used to make exosome preparations from the majority of clinical samples obtained. Analysis of these preparations was expected to test the performance of biomarker that would not otherwise be detected, including low abundance proteins but also membrane associated proteins not expected to be readily solubilized in blood.









TABLE 6







Characteristics of subjects used for verification


of BCM/BCF candidate biomarkers










Cohort
Samples






Normoglycemic subject: NGT
47



Normoglycemic subject: IGT
17



Long term T1D (insulin > 5 yrs)
19



Long term T2D (insulin > 5 yrs)
28
















TABLE 7







Additional subjects used for verification of


BCM/BCF/TEM candidate biomarkers


ALL SUBJECTS













Number
Age
Age
BMI
BMI



of subjects
range
median
range
median





Controls
50
18-74
40
18-30
24


Diabetics High BMI
69
24-66
51
39-74
58


Pre-Diabetics High BMI
79
19-64
40
37-75
60


Diabetics Lower BMI
50
26-71
52
33-40
39


Pre-Diabetics Lower BMI
47
30-62
41
32-40
38










Results


A. Type 2 Diabetes Biomarker Identification


Three datasets were generated based on the methods described above. The first dataset was an extensive catalog of secretory vesicle content proteins prepared from 6 different human organs. The second dataset contained the corresponding list of secretory vesicle content proteins from 6 rat organs. The third dataset was a catalogue of the steady state secretory vesicle content proteins from each of the 3 experimental systems. The proteins common to the organ secretome database and to any one of the experimental systems were then removed from the experimental system datasets, leaving the secreted proteins more likely to be uniquely expressed by ß-cells or ß-islets. Over two thousand proteins were identified for each species, and on the order of one thousand proteins were identified from the secretory vesicle contents of the rodent ß-cell lines or primary human ß-islets. Between half and ⅔ of these proteins appeared to be also expressed by at least one of the organ secretomes. Removal of these commonly expressed proteins resulted in the ß-cell mass candidate biomarkers. These candidates were then examined in detail to prioritize them for further analysis.


The initial analysis indicated a modest overlap in the net secretome proteins identified from the 3 experimental systems, suggesting only a partial correspondence between the cell line systems and the primary islets. While that finding may not have been surprising, a similarly modest overlap observed between the two cell lines was not expected, and may indicate distinct physiological states for the cell lines.


The proteins identified were assessed for biological function and network and pathway connections through manual literature review and networking software analysis. Relatively stringent criteria were used to denote protein to protein relationships, such as a known direct link between any two proteins be already established, as well as statistical significance that the biological functions or pathways that appear to be over-represented be so by greater than chance alone. The dataset subset that met these criteria contained a considerable number of proteins (152).


Additional assessments for candidate biomarkers prioritization were to establish tissue specificity, which was done using histochemical assessment of the expression of the candidate biomarker proteins in the pancreas and in other organs. This analysis suggested that a significant proportion of the higher ranked candidate biomarkers identified had relatively restricted tissue expression, typically to pancreatic islets, or if they were also expressed in other tissues, they were found with typically lesser expression in the central nervous system. A subset of these markers had also been detected in human body fluids, indicating that these proteins were also secreted. At the end of the analysis, 200 proteins were prioritized and these candidate biomarkers are listed in Table 1 (β cell mass (BCM) markers).


Proteins secreted by the tissues of interest under steady state conditions may change under stress or under dysfunctional states. Secretion of particular proteins under these conditions may become upregulated or down regulated. Furthermore, proteins not normally secreted in steady state may become secreted under stress. Identification of these changes to define biomarker candidates associated with ß-cell and ß-islet function was also performed.


The ß-cell lines and primary human ß-islets were incubated with vehicle or with a glucolipotoxic treatment (described above) for defined periods till the dysfunction described earlier was obtained. Following the treatment, secretory vesicle content sample preparation and proteomic data acquisition and analysis was executed as above. Several hundred proteins that became differentially expressed after the glucolipotoxic treatment were identified. Subtraction of the proteins in common with the organ secretome left 326 non-redundant proteins that were differentially expressed in any of the three experimental systems. The three experimental systems continued to display minimal overlap, even though they were each treated with the same glucolipotoxic treatment and each developed a similar drop in insulin production and induction of apoptosis. After applying the prioritization strategy described above, 129 proteins were selected. The β-cell function (BCF) candidate biomarker proteins and their degree of change after treatment are listed in Table 2.


The pathway analysis supported the interpretation that the 3 experimental systems responded differently to the same stimulus. This indicated that the physiological relevance of the cell line systems might be insufficient to effectively model the human primary tissue. The response by the primary human islets to select the biomarker candidates associated with ß-cell dysfunction was therefore focused on.


A list of biomarker candidates in human plasma that were associated with response to treatment was also developed. All the subjects recruited for this part of the project had type 2 diabetes, and were about to initiate or switch treatment. Plasma was collected prior to the treatment initiation as well as 2 weeks after treatment was initiated. The subjects were then followed for at least 5 months to establish treatment response. A responder was defined as a subject who displayed by treatment's end glycated hemoglobin levels less than 7% without side effects, or had a 1.5% drop of glycated hemoglobin by treatment's end without side effects. Initially the objective was to assess metformin treatment only, which is the first line treatment for type 2 diabetes. The scope of the study was later expanded to allow subjects with other therapies to be included. The number of subjects and their treatment regimes at the time of recruitment are indicated in Table 8.









TABLE 8







Characteristics of subjects used for discovery


of treatment monitoring candidate biomarkers









Number of samples










Treatment option
Baseline
Week_2
Total













Metformin initiation
12
12
24


Metformin + Sulfonyurea
12
11
23


Metformin + Sulfonyurea + DPP4
5
5
10


inhibitor





Metformin + DPP4 inhibitor
4
4
8


Metformin + Sulfonyurea + Insulin
9
9
18


Total number of samples
42
41
83









The plasma samples from these subjects were depleted of high abundance proteins and analyzed. The differentially expressed proteins identified were then associated with the available clinical data to identify protein biomarker candidates associated with prediction of response (analysis using the pre-dose samples) or monitoring of response (analysis using the post-treatment initiation samples). The therapeutic efficacy biomarker (TEM) candidates are listed in Table 3.


Approximately 150 proteins were identified that were significantly differentially expressed in at least one treatment response comparison. Differences were observed in the pre-dose samples of the eventual responders versus the eventual non-responders. Furthermore, the differences between responders and non-responders appear to become magnified during the treatment, as more proteins become differentially expressed in the eventual responders compared to the eventual non-responders once treatment has begun.


These analyses indicated that the changes between responders and non-responders become augmented after treatment began, both in the number of proteins differentially expressed per pathway, but also in the introduction of related pathways not induced in the pre-treatment samples.


B. Biomarker Validation


The biomarkers identified as described above were assessed in blood. Human plasma was processed by the three methods described earlier. An aliquot of each subject's plasma sample was depleted of high abundance proteins by affinity chromatography. The remaining material was digested with trypsin and analyzed by a multiplex MRM-MS assay. Another plasma aliquot was used to prepare plasma exosomes by sequential high speed centrifugation. The recovered material was analyzed using the same multiplex MRM-MS assay used on the depleted plasma Finally, a third aliquot of the plasma was used to assess the performance of 23 biomarker candidates by ELISA.


The clinical cohorts selected were designed to describe the spectrum of diabetes disease progression. The early stages of disease progression were represented by normoglycemic controls, which represent non-diabetic healthy subjects, and by subjects with impaired glucose tolerance, which corresponds to pre-diabetic individuals not yet formally diagnosed with type 2 diabetes. Diabetes disease was represented by subjects that have been diagnosed with type 2 diabetes within the last 1.5 years or at least 5 years previously. These two groups represent the early stage and advanced stage diabetics, respectively. Long term (>5 years since diagnosis) type 1 diabetics have also been included in this study. Study plasma was tested for insulin using a commercial ELISA kit. All the subjects had blood draws performed in the AM, after an overnight fast, and thus the insulin reactivity detected most likely represented endogenous levels. An increase in resting insulin concentration was observed in the impaired glucose tolerant, early stage, and advanced diabetics compared to the controls, consistent with type 2 diabetes disease progression.


In order to validate the biomarkers, the level of the biomarkers was determined in samples from subjects. The samples for the analysis were described in Table 7. They comprised morbidly obese individuals with metabolic syndrome, and candidates for bariatric surgery. A subset of these subjects have been diagnosed with T2D and were undergoing therapy at the time of the blood sampling, whereas others appeared to be in a pre-diabetic state. Metabolic syndrome is an umbrella term used to describe what is likely a variety of conditions that all have in common metabolic imbalance that frequently leads to obesity and is often a precursor to T2D. An analysis of these subjects was conducted to evaluate the performance of the candidate biomarkers in a background of extreme metabolic syndrome. The same type of analysis for the non-morbidly obese subjects was conducted (see Table 7): plasma samples were depleted of abundant proteins by chromatography and analyzed using a multiplex MRM-MS assay. Plasma exosome preparations were also made to assess detection of biomarker candidates that may have been beneath the level of detection of the multiplex MRM-MS assay in depleted plasma, and a selection of ELISA assays were performed as well. The performance of the candidate biomarkers is presented in Tables 9-12 which provide the DI value for each marker comparison. If the DI value is above 1 the level of the protein is upregulated for that particular comparison. If the DI value is less than 1, the level of the marker is downregulated for that particular comparison.









TABLE 9







MRM ANALYSIS OF HUMAN PLASMA SAMPLES OF BCM/BCF CANDIDATE


BIOMARKERS *Differential expression (DE) thresholds: p-value < 0.05 | q-value < 0.05











Established T1D vs Control
Established T2D vs Control
New T2D vs Control
















PROTEIN
DI
p-Value
q-Value
DI
p-Value
q-Value
DI
p-Value
q-Value



















INS_HUMAN
0.96
0.638
0.000
1.37
0.001
0.000
1.22
0.032
0.000


USP9X_HUMAN
1.18
0.170
0.000
0.76
0.020
0.000
0.88
0.290
0.000


TRI42_HUMAN
1.27
0.008
0.000
1.61
0.000
0.000
1.20
0.035
0.000


B4GT1_HUMAN
0.97
0.495
0.000
1.52
0.000
0.000
1.09
0.068
0.000


MGAT1_HUMAN
0.86
0.096
0.000
1.35
0.001
0.000
1.15
0.115
0.000


ANAG_HUMAN
0.99
0.866
0.000
0.99
0.878
0.000
1.31
0.002
0.000


CHKA_HUMAN
1.26
0.019
0.000
1.56
0.000
0.000
1.27
0.013
0.000


CADM1_HUMAN
1.07
0.447
0.031
1.11
0.205
0.031
1.14
0.115
0.031


DAG1_HUMAN
1.11
0.272
0.000
1.72
0.000
0.000
1.07
0.469
0.000


CNTN1_HUMAN
1.05
0.523
0.010
1.16
0.035
0.010
1.06
0.449
0.010


SPRL1_HUMAN
1.09
0.083
0.000
1.15
0.004
0.000
1.02
0.714
0.000


NCAM1_HUMAN
0.96
0.484
0.076
1.01
0.889
0.076
0.95
0.367
0.076


ITM2B_HUMAN
1.06
0.224
0.007
1.12
0.024
0.007
1.07
0.188
0.007


DMP4_HUMAN
0.97
0.630
0.000
1.15
0.013
0.000
1.21
0.001
0.000


CD59_HUMAN
0.99
0.919
0.000
1.81
0.000
0.000
1.18
0.043
0.000


NEO1_HUMAN
0.99
0.802
0.000
1.16
0.008
0.000
1.04
0.484
0.000


PTPRJ_HUMAN
0.99
0.881
0.004
1.06
0.148
0.004
1.08
0.053
0.004


CBPM_HUMAN
0.97
0.732
0.000
1.33
0.000
0.000
1.26
0.002
0.000


SPIT1_HUMAN
1.02
0.750
0.006
1.12
0.038
0.006
1.07
0.175
0.006


PVR_HUMAN
0.94
0.268
0.000
1.15
0.012
0.000
1.06
0.286
0.000


QPCT_HUMAN
1.05
0.578
0.000
1.33
0.000
0.000
1.10
0.245
0.000


SDK1_HUMAN
1.04
0.544
0.002
1.15
0.018
0.002
0.99
0.928
0.002


NAAA_HUMAN
0.99
0.913
0.020
1.09
0.105
0.020
1.02
0.735
0.020


GALT2_HUMAN
0.96
0.529
0.000
1.29
0.000
0.000
1.12
0.073
0.000


LMAN2_HUMAN
1.00
0.958
0.000
1.37
0.000
0.000
1.11
0.123
0.000


A4_HUMAN
1.15
0.079
0.015
1.05
0.534
0.015
1.13
0.123
0.015
















TABLE 10





ELISA ANALYSIS OF HUMAN PLASMA SAMPLES OF BCM/BCF CANDIDATE


BIOMARKERS Significance Thresholds: p-value < 0.05 | q-value < 0.05




















IGT vs NGT
New T2D vs NGT
Est T2D vs NGT
New T2D vs IGT















PROTEIN
DI
p-Value
DI
p-Value
DI
p-Value
DI
p-Value





INS
1.82
0.005
2.55
0.000
2.82
0.002
1.40
0.043


PPY
0.89
0.627
2.05
0.000
1.78
0.000
2.29
0.000


FUT6
1.07
0.421
0.76
0.000
0.92
0.241
0.71
0.000


CPM
1.16
0.357
1.72
0.000
1.81
0.001
1.48
0.015


SERPINB13
1.04
0.820
0.38
0.000
0.87
0.696
0.37
0.000


WNT9B
0.99
0.979
2.30
0.004
1.61
0.050
2.31
0.019


STX1A
1.46
0.408
3.38
0.038
1.72
0.228
2.31
0.175


BTC
0.34
0.084
1.87
0.044
0.96
0.894
5.47
0.002


SNAP25
0.65
0.094
0.64
0.052
1.15
0.507
0.98
0.954


MMP7
1.09
0.576
1.22
0.074
3.07
0.006
1.12
0.396


CCL20
1.57
0.322
1.62
0.090
1.98
0.055
1.03
0.923


IGFBP7
1.16
0.583
0.62
0.087
1.34
0.238
0.54
0.021


SEPT3
1.82
0.163
0.69
0.115
0.59
0.018
0.38
0.031


SCG5
1.74
0.121
1.81
0.125
2.86
0.089
1.04
0.917


TNFSF11
4.23
0.132
2.66
0.140
1.81
0.522
0.63
0.489


REG3A
0.86
0.560
1.37
0.373
1.04
0.909
1.60
0.313


PTPRN
0.86
0.138
1.11
0.459
0.79
0.020
1.29
0.199


IAPP
2.90
0.158
1.40
0.682
2.07
0.258
0.48
0.349


CPE
1.62
0.063
0.97
0.853
0.87
0.275
0.60
0.044















Est T2D vs IGT
Est vs New T2D
T1D vs NGT
T1D vs IGT















PROTEIN
DI
p-Value
DI
p-Value
DI
p-Value
DI
p-Value





INS
1.55
0.181
1.11
0.598
0.19
0.000
0.10
0.000


PPY
1.99
0.000
0.87
0.123
1.64
0.017
1.83
0.022


FUT6
0.86
0.072
1.22
0.003
0.86
0.043
0.81
0.013


CPM
1.56
0.028
1.06
0.663
1.28
0.081
1.10
0.495


SERPINB13
0.83
0.676
2.25
0.112
1.56
0.435
1.50
0.576


WNT9B
1.63
0.108
0.70
0.094
2.25
0.011
2.26
0.043


STX1A
1.18
0.700
0.51
0.100
2.18
0.199
1.49
0.515


BTC
2.82
0.021
0.51
0.009
0.92
0.853
2.69
0.213


SNAP25
1.77
0.103
1.80
0.028
1.05
0.834
1.61
0.242


MMP7
2.81
0.041
2.51
0.006
1.03
0.850
0.95
0.806


CCL20
1.26
0.564
1.22
0.448
1.05
0.897
0.67
0.355


IGFBP7
1.15
0.598
2.15
0.004
2.19
0.004
1.88
0.037


SEPT3
0.33
0.012
0.85
0.447
0.79
0.405
0.43
0.084


SCG5
1.65
0.428
1.58
0.308
1.42
0.241
0.82
0.559


TNFSF11
0.43
0.306
0.68
0.550
2.90
0.129
0.68
0.594


REG3A
1.21
0.644
0.76
0.425
1.28
0.433
1.49
0.311


PTPRN
0.91
0.476
0.71
0.021
0.82
0.185
0.96
0.816


IAPP
0.71
0.583
1.47
0.540
1.59
0.520
0.55
0.408


CPE
0.54
0.012
0.89
0.429
0.92
0.455
0.57
0.029
















TABLE 11







MRM ANALYSIS OF HUMAN EXOSOME SAMPLES OF BCM/BCF CANDIDATE


BIOMARKERS *Differential expression (DE) thresholds: p-value < 0.05 | q-value < 0.05











T1D-Established vs
T2D-Established vs




Control
Control
T2D-New vs Control
















PROTEIN
DI
p-value
q-value
DI
p-value
q-value
DI
p-value
q-value



















EDF1_HUMAN
128.37
0.000
0.000
0.24
0.136
0.341
33.68
0.001
0.001


SNAPN_HUMAN
34.25
0.000
0.000
0.36
0.116
0.316
8.43
0.009
0.007


NXPH1_HUMAN
31.14
0.000
0.000
0.45
0.324
0.505
5.19
0.080
0.035


CDCP1_HUMAN
18.20
0.000
0.000
5.82
0.011
0.047
8.00
0.008
0.007


INGR1_HUMAN
5.94
0.002
0.001
1.03
0.957
0.738
0.71
0.621
0.196


BTC_HUMAN
4.60
0.007
0.003
0.75
0.617
0.662
2.49
0.131
0.052


NCAM1_HUMAN
4.13
0.001
0.001
1.07
0.886
0.733
2.20
0.102
0.044


RICBA_HUMAN
2.98
0.002
0.001
0.99
0.986
0.742
3.28
0.002
0.002


TM11F_HUMAN
2.93
0.000
0.000
1.07
0.588
0.662
2.71
0.000
0.000


MGT4B_HUMAN
2.89
0.000
0.000
0.91
0.534
0.662
2.75
0.000
0.000


ERO1B_HUMAN
2.75
0.000
0.000
0.99
0.923
0.733
2.06
0.000
0.000


PDYN_HUMAN
2.57
0.000
0.000
0.85
0.237
0.419
2.24
0.000
0.000


LTOR2_HUMAN
2.24
0.000
0.000
0.95
0.669
0.671
2.06
0.000
0.000


NELL1_HUMAN
2.03
0.000
0.000
0.97
0.781
0.733
1.71
0.000
0.000


TCO2_HUMAN
1.96
0.000
0.000
1.12
0.406
0.555
1.42
0.022
0.014


PTPRJ_HUMAN
1.84
0.003
0.001
1.26
0.203
0.408
1.98
0.000
0.000


CLLD6_HUMAN
1.78
0.009
0.003
1.11
0.669
0.671
1.34
0.309
0.110


ATD3B_HUMAN
1.77
0.000
0.000
0.87
0.204
0.408
2.15
0.000
0.000


NXPH2_HUMAN
1.60
0.036
0.011
1.04
0.843
0.733
1.65
0.030
0.017


VAV3_HUMAN
1.51
0.014
0.005
0.34
0.007
0.045
1.43
0.057
0.029


PLXC1_HUMAN
0.45
0.019
0.006
1.12
0.590
0.662
0.53
0.070
0.033


CSTF3_HUMAN
0.34
0.000
0.000
1.04
0.744
0.722
0.71
0.020
0.013


MCRS1_HUMAN
1.00
0.998
0.173
0.38
0.004
0.037
0.87
0.670
0.200


LDLR_HUMAN
0.96
0.825
0.151
0.56
0.001
0.037
1.12
0.542
0.181


GHRL_HUMAN
1.22
0.101
0.025
0.56
0.006
0.043
0.42
0.001
0.001


NMU_HUMAN
1.14
0.406
0.078
0.60
0.004
0.037
1.06
0.739
0.215


AMPD3_HUMAN
0.29
0.067
0.018
0.62
0.401
0.555
0.38
0.156
0.060


SLIT3_HUMAN
1.58
0.061
0.017
0.99
0.927
0.733
2.06
0.000
0.000


GP158_HUMAN
1.24
0.142
0.033
0.70
0.010
0.047
1.63
0.013
0.009


MGAT1_HUMAN
0.85
0.241
0.050
0.88
0.336
0.505
0.64
0.008
0.007


OLFM4_HUMAN
1.51
0.234
0.050
0.035
0.126
0.03
2.07
0.033
0.018


RENR_HUMAN
1.25
0.030
0.010
1.19
0.107
0.316
0.80
0.039
0.021


NAAA_HUMAN
0.82
0.180
0.040
0.80
0.268
0.447
0.80
0.116
0.048


MMP14_HUMAN
1.48
0.243
0.050
1.50
0.155
0.358
0.83
0.587
0.191


NCEH1_HUMAN
1.34
0.520
0.098
1.27
0.609
0.662
0.81
0.657
0.200


TTC37_HUMAN
3.66
0.056
0.016
1.11
0.870
0.733
0.96
0.959
0.265


MOGS_HUMAN
1.57
0.115
0.028
0.66
0.228
0.419
1.07
0.843
0.239


CD59_HUMAN
1.05
0.879
0.157
1.75
0.038
0.126
0.68
0.289
0.106


B4GT1_HUMAN
1.29
0.086
0.022
0.92
0.570
0.662
0.71
0.078
0.035


USP9X_HUMAN
1.35
0.369
0.073
0.93
0.823
0.733
0.69
0.351
0.121
















TABLE 12







BCM and BCF candidate biomarkers in morbidly obese subjects


*Differential expression (DE) thresholds: p-value < 0.05 | q-value < 0.05












High BMI Diabetics
Low BMI Diabetics



BCM | BCF
vs Pre-diabetics
vs Pre-diabetics












Gene
q-Value
DI
p-Value
DI
p-Value















TRIM42
0.000
1.57
0.000
1.44
0.000


CHKA
0.000
1.58
0.000
1.52
0.000


CNTN1
0.000
1.10
0.001
1.07
0.028


PVR
0.000
1.09
0.031
1.23
0.000


INS
0.000
2.13
0.009
2.98
0.002


LCN2
0.000
0.86
0.000
1.03
0.541


CD59
0.000
0.89
0.036
1.09
0.167


NGRN
0.000
0.59
0.035
1.03
0.922


TMEM132A
0.002
0.76
0.044
0.93
0.593


B4GALT1
0.000
1.04
0.396
1.12
0.046


CADM1
0.000
1.01
0.855
1.20
0.005


CYFIP1
0.000
1.37
0.067
0.60
0.003


CASC4
0.000
0.88
0.593
1.77
0.018


STX2
0.000
1.21
0.061
1.04
0.726


NCAM1
0.000
0.93
0.095
1.01
0.905


SPINT1
0.004
1.13
0.106
1.12
0.205


NEO1
0.000
1.06
0.119
1.07
0.105


VAV3
0.000
1.30
0.136
0.97
0.872


SV2A
0.000
1.04
0.146
0.99
0.661


USP9X
0.000
0.88
0.178
0.90
0.361


FAM20C
0.000
1.26
0.191
1.05
0.831


MICU1
0.004
0.83
0.214
0.92
0.636


LAMTOR3
0.000
1.06
0.237
1.03
0.597


IGFBP7
0.005
1.15
0.264
1.26
0.125


LMAN2
0.000
0.85
0.284
1.02
0.912


GALNT2
0.000
1.06
0.295
1.08
0.232


MGAT1
0.000
0.96
0.312
1.05
0.370


NAGLU
0.007
1.03
0.327
0.98
0.645


ERO1LB
0.000
1.14
0.365
1.10
0.599


MAP1B
0.000
0.95
0.428
0.93
0.412


MPP2
0.001
0.91
0.440
0.75
0.052


PTPRJ
0.000
0.98
0.448
1.04
0.304


SFT2D3
0.000
1.12
0.481
0.99
0.947


SHANK2
0.014
0.93
0.488
0.97
0.783


ITM2B
0.011
1.07
0.496
1.01
0.955


ENPP4
0.000
1.14
0.500
1.09
0.713


TLL2
0.000
0.95
0.600
0.91
0.443


CFDP1
0.000
1.09
0.613
1.47
0.056


NFASC
0.000
1.08
0.620
1.17
0.407


TMEM123
0.000
0.91
0.636
0.82
0.373


NGRN
0.001
0.94
0.642
0.84
0.293


APOL2
0.001
1.01
0.666
1.06
0.070


MGAT4B
0.013
1.04
0.762
0.95
0.681


FGF19
0.000
1.02
0.799
0.96
0.707


TCN2
0.001
1.04
0.809
1.14
0.463


PAM
0.000
1.00
0.951
1.09
0.162


SPARCL1
0.018
1.00
0.984
1.04
0.632


PAPPA2
0.005
1.00
0.987
1.01
0.928


MIA3
0.000
1.22
0.621
0.96
0.923


MGAT1
0.000
1.09
0.653
0.75
0.116


OLFM4
0.000
0.82
0.635
2.12
0.066


PLSCR3
0.000
1.15
0.588
1.23
0.418


CFDP1
0.000
1.09
0.722
0.80
0.347


SHANK2
0.000
1.07
0.867
0.63
0.246


CHGB
0.000
0.91
0.750
0.74
0.317


B4GALT1
0.000
1.35
0.077
1.14
0.437


MBP
0.000
0.84
0.575
0.62
0.133


PAPPA2
0.000
2.10
0.099
2.16
0.087


PAM
0.000
0.73
0.052
0.76
0.083


CD59
0.000
1.70
0.165
1.00
0.999


LCN2
0.002
0.92
0.670
1.21
0.307


SLC30A1
0.003
1.09
0.719
1.24
0.384


SCAMP3
0.035
0.97
0.851
1.02
0.921


CPE
0.028
1.38
0.199
0.95
0.846


GPRIN1
0.010
0.94
0.723
1.00
0.980


VAV3
0.038
0.88
0.663
1.20
0.528


NAGLU
0.038
1.12
0.601
1.06
0.784


USP9X
0.016
1.81
0.539
0.45
0.402


APP
0.012
1.28
0.295
0.90
0.638


PPY
0.000
0.86
0.188
1.06
0.651


CPM
0.000
1.09
0.397
1.13
0.291


BTC
0.001
1.20
0.560
1.09
0.816









A subset of the biomarkers was identified to be differentially expressed in both this group of obese subjects and the less obese subjects in the initial verification analysis. There were, however, many biomarkers candidates that were not shared between these two groups. The impact of the excessive obesity was substantial. There were many more biomarker candidates differentially expressed in the morbidly obese to lean comparisons than it the morbidly obese diabetic to morbidly obese pre-diabetic comparisons. The level of the candidate biomarkers was also determined in samples from subjects having type 2 diabetes and about to begin or switch treatments (see Table 8).


Responsiveness to therapy was assessed by A1c levels and blood glucose levels. The 3 largest treatment groups were the subjects on metformin, on metformin and glyburide, and on metformin, glyburide and insulin, and these groups were used to assess the performance of the candidate biomarkers. Changes were identified between responders and non-responders for each treatment (Table 13). It was observed that the number of differentially expressed biomarker candidates increased with each added treatment. Twelve proteins were identified to be differentially expressed between metformin responders and non-responders, 15 in the same comparison for metformin and glyburide, and 21 for metformin, glyburide and insulin.


Worth noting is that insulin family proteins were observed to be differentially expressed between responders and non-responders only for those subjects on metformin, and not for any on the subsequent combination therapies. This results are consistent with advancing disease progression.









TABLE 13







TEM biomarkers on plasma of in morbidly obese subjects


*Differential expression (DE) thresholds: p-value < 0.05 | q-value < 0.05














Met + Gly
Met + Gly + Insulin



TEM
Met (Responders vs
(Responders vs Non-responders)
(Responders vs Non-responders)
















q-
Non-responders)
Median


Median



















Gene
Value
AUC
DI
p-Value
AUC
DI
p-Value
AUC
DI
p-Value




















APOE
0.000
0.66
0.77
0.027
0.72
0.70
0.034
0.64
0.78
0.105


ACE
0.002
0.75
1.54
0.011
0.57
1.04
0.859
0.78
1.56
0.044


SAA4
0.000
0.64
0.69
0.019
0.52
0.76
0.215
0.73
0.64
0.029


B2M
0.000
0.70
1.20
0.032
0.63
1.10
0.424
0.77
1.39
0.002


CACNA2D1
0.000
0.62
0.81
0.034
0.67
0.85
0.233
0.70
0.76
0.033


DBH
0.010
0.64
0.55
0.008
0.65
0.69
0.253
0.52
1.24
0.462


CNN2
0.009
0.63
0.50
0.029
0.61
1.50
0.383
.057
1.23
0.614


LYVE1
0.020
0.65
1.42
0.012
0.57
1.12
0.588
0.55
0.92
0.650


IGF2
0.029
0.71
1.37
0.031
0.58
0.95
0.804
0.51
0.95
0.791


IGF2R
0.003
0.63
1.26
0.031
0.58
0.59
0.470
0.59
0.83
0.176


HGFAC
0.013
0.66
1.18
0.036
0.64
0.92
0.433
0.73
1.21
0.053


ITIH3
0.017
0.72
1.31
0.038
0.51
1.01
0.971
0.67
1.29
0.132


ALDOB
0.000
0.51
0.91
0.681
0.74
0.42
0.009
0.74
0.50
0.020


GPX3
0.000
0.61
1.14
0.276
0.88
0.68
0.023
0.69
0.48
0.000


F11
0.000
0.52
0.99
0.819
0.79
0.75
0.001
0.74
1.20
0.025


C9
0.000
0.62
1.32
0.051
0.84
1.80
0.003
0.73
1.42
0.053


TLN1
0.000
0.62
0.79
0.093
0.76
1.72
0.006
0.57
1.00
0.986


PROZ
0.004
0.68
1.19
0.217
0.86
0.64
0.028
0.52
0.92
0.667


FGG
0.000
0.56
1.13
0.468
0.86
2.54
0.000
0.57
0.90
0.624


CDH5
0.008
0.59
1.34
0.473
0.74
0.26
0.020
0.58
0.72
0.526


CNDP1
0.000
0.54
1.07
0.499
0.75
0.65
0.002
0.61
1.16
0.231


FAM20C
0.001
0.61
1.17
0.685
0.79
0.20
0.003
0.59
0.50
0.156


CA2
0.024
0.53
1.02
0.897
0.67
0.59
0.042
0.56
0.84
0.452


C4BPA
0.006
0.53
1.06
0.583
0.71
1.38
0.048
0.63
1.16
0.326


AFM
0.004
0.54
0.96
0.655
0.71
0.72
0.027
0.61
0.88
0.337


MASP1
0.008
0.51
0.98
0.687
0.70
0.83
0.030
0.56
0.95
0.474


ITIH4
0.000
0.63
1.25
0.050
0.69
1.32
0.094
0.72
1.52
0.004


APOB
0.001
0.56
0.88
0.376
0.52
0.86
0.476
0.83
0.58
0.003


SERPINA4
0.000
0.55
1.09
0.478
0.68
0.79
0.156
0.76
0.55
0.000


MBL2
0.005
0.54
0.90
0.665
0.63
0.66
0.231
0.64
0.54
0.048


PROCR
0.020
0.52
0.94
0.702
0.57
0.89
0.638
0.51
0.61
0.025


BTD
0.005
0.51
1.03
0.846
0.71
0.61
0.356
0.61
0.54
0.004


APOC4
0.000
0.56
0.96
0.862
0.63
0.58
0.132
0.82
0.23
0.000


F10
0.002
0.53
0.98
0.901
0.70
0.78
0.244
0.62
0.60
0.009


PGLYRP2
0.010
0.54
1.09
0.398
0.54
0.91
0.540
0.62
0.75
0.035


ATRN
0.008
0.54
1.07
0.484
0.52
0.98
0.893
0.57
0.75
0.021


EFEMP1
0.002
0.61
1.09
0.489
0.61
1.22
0.264
0.83
1.46
0.018


GPLD1
0.002
0.54
1.04
0.590
0.68
0.80
0.056
0.70
0.78
0.018


COL6A3
0.000
0.63
1.05
0.618
0.61
1.21
0.164
0.76
1.45
0.003


SERPINA7
0.008
0.53
1.02
0.861
0.60
1.15
0.331
0.58
0.76
0.034









Additional analyses of the markers identified 30 markers that have individual discrimination power, defined as being able to discriminate between two cohorts with an accuracy of 75% or greater. Specifically, and as described above, samples were obtained from control subjects (e.g., normal glucose tolerant (NGT) subjects, pre-diabetic subjects (e.g., subjects having impaired glucose tolerance), subjects diagnosed as having type 2 diabetes in the previous 18 months (nT2D) and subjects having type 2 diabetes and a complication associated with type 2 diabetes, such as diabetic neuropathy, retinopathy, nephropathy, cardiovascular disease (eT2D) and the level of each of the markers listed in Tables 1-3 was determined. Pairwise comparisons of the level of each marker in NGT subjects and; IGT subjects; nT2D subjects; eT2D; and a combination of nT2D and eT2D subjects (All T2D) were performed and the area under the curve for each marker was calculated. Similarly, pairwise comparisons of the level of each marker in IGT subjects and; nT2D subjects; eT2D; and a combination of nT2D and eT2D subjects (All T2D) were performed and the area under the curve for each marker was calculated. The results of these analyses are shown in Table 14. Therefore a substantial number of well performing candidates was identified. For most comparison, multiple biomarker candidates with good performance indicators were identified.









TABLE 14







Area Under the Curve (AUC) for Single Markers.










NGT vs
IGT vs














Marker
IGT
nT2D
eT2D
All T2D
nT2D
eT2D
All T2D





USP9X
0.718








DAG1


0.989


0.947



SEPT3


0.732
0.814

0.834
0.824


PTPRJ



0.774

0.774
0.923


CPM

0.876
0.785
0.814

0.742
0.746


SERPINB13

0.885


0.940




LDLR


0.802
0.835





MMP7


0.884
0.838

0.847



BTC

0.690


0.968
0.833
0.798


PPY

0.907
0.881
0.923
0.961
0.937
0.945


INS

0.983
0.802
0.818





CSTF3

0.766







NELL1

0.741







SLIT3

0.861


0.812




LAMTOR2

0.850


0.813




MGAT4B

0.826


0.786




TMPRSS11F

0.822


0.741




ATAD3B

0.765


0.751




PTPRN


0.730






WNT9B

0.794

0.513


0.705


FUT6

0.844

0.572
0.885

0.591


B4GALT1



0.945


0.885


FAM20C






0.878


CNTN1






0.758


MGAT1

0.915







STX1A

0.828







NMU


0.782
0.877





CD59



0.980


0.903


CASR



0.898





CPE
0.590




0.850
0.875









The ability of these individual biomarkers to act in combination, as a panel, was also assessed. This preliminary panel analysis focused on identifying combinations that improved discrimination accuracy, but also used the smallest possible number of biomarkers. As shown in Table 15, small panels of proteins that were able to accurately discriminate between each of the disease progression cohorts were successfully identified. The area under the curve (AUC) for various combinations of the markers listed in Tables 1-3 was also determined. The results of these analyses are shown in Table 15.









TABLE 15







Area Under the Curve (AUC) for Marker Combinations.












NGT vs
IGT vs















Markers
Proteins in panel
IGT
nT2D
eT2D
All T2D
nT2D
eT2D
All T2D





INS; USPX
2
0.774








INS; SERPINB13
2




0.998




BTC; MMP7; PPY
3





0.999



INS; SERPINB13
2

0.998







CPM; INS; MMP7;
4


0.948






LDLR










PPY; SEPT3; PTPRJ
3






0.952


PPY; DAG1
2



0.986












The biomarker candidates associated with pancreatic function and disease progression were also evaluated in plasma from morbidly obese type 2 diabetics or pre-diabetics. Fewer proteins overall (13 vs 30) compared to the initial, less obese, cohorts were found to have acceptable individual discrimination power. However, the list of candidate biomarkers from both cohorts overlapped, with only 2 of the 13 better biomarker candidates from the obese subject dataset were detected only in the obese subjects. This suggests that the bulk of the biomarker candidates identified with good discriminatory power had similar performance in both cohorts. While this suggests that these biomarker candidates could be relevant in multiple populations, there were also important differences. One of these appears to be that combinations containing more proteins were necessary to separate the diabetic from the pre-diabetic subjects from the obese cohorts. For example, a combination of 5 proteins was required to generate a panel able to discriminate morbidly obese diabetics from morbidly obese pre-diabetics with an accuracy of 0.826. By comparison, non-morbidly obese pre-diabetics could be distinguished from diabetics of comparable BMI with an accuracy of 0.998 using a combination of only 3 proteins. This suggests that it might be more difficult to separate the obese diabetics from the obese pre-diabetics, which is why more panel members were required and even then these additional panel members produced an overall less accurate combination. Variability among the cohort subjects may be a factor affecting panel performance, since the morbidly obese subjects included had widely varying BMI values, ranging from 35 to 70. Once the subjects were sorted into two groups, one containing subjects with BMI of up to 40, and the other subjects with BMI above 40, the best 5 protein panel composition became different for each of these groups, and the best panel performance rose from 0.826 to 0.843 and 0.889, respectively (Table 16).









TABLE 16







BCM|BCF|TEM High BMI [Diabetics vs Non Diabetics]









PANEL COMPOSITION
#PROTEINS
AUC












CD59 | CNTN1 | MGAT1 | TRIM42 | USP9X
5
0.889


CD59 | CHKA | CNTN1 | TRIM42 | USP9X
5
0.881


CD59 | CNTN1 | PTPRJ | TRIM42 | USP9X
5
0.879


B4GALT1 | CD59 | CNTN1 | TRIM42 | USP9X
5
0.874


CD59 | CNTN1 | TRIM42 | USP9X | BTC
5
0.872


CD59 | CNTN1 | TRIM42 | USP9X | CPM
5
0.872


CD59 | CNTN1 | TRIM42 | USP9X | PPY
5
0.871


CD59 | CNTN1 | FAM20C | TRIM42 | USP9X
5
0.871


CD59 | CNTN1 | TRIM42 | USP9X
4
0.871


CD59 | CNTN1 | TRIM42 | USP9X | INS
5
0.871


CNTN1 | MGAT1 | PTPRJ | TRIM42 | USP9X
5
0.868


CD59 | CHKA | CNTN1 | MGAT1 | USP9X
5
0.867


CHKA | CNTN1 | MGAT1 | TRIM42 | USP9X
5
0.867


B4GALT1 | CHKA | CNTN1 | TRIM42 | USP9X
5
0.867


B4GALT1 | CNTN1 | PTPRJ | TRIM42 | USP9X
5
0.867


CNTN1 | MGAT1 | TRIM42 | USP9X | INS
5
0.865


CHKA | CNTN1 | PTPRJ | TRIM42 | USP9X
5
0.865


B4GALT1 | CNTN1 | MGAT1 | TRIM42 | USP9X
5
0.863


CNTN1 | FAM20C | MGAT1 | TRIM42 | USP9X
5
0.863


CNTN1 | MGAT1 | TRIM42 | USP9X | BTC
5
0.861


CNTN1 | MGAT1 | TRIM42 | USP9X | CPM
5
0.860


CD59 | CHKA | CNTN1 | FAM20C | USP9X
5
0.860


CNTN1 | MGAT1 | TRIM42 | USP9X
4
0.860


CD59 | CNTN1 | PTPRJ | TRIM42 | INS
5
0.860


CD59 | CHKA | CNTN1 | PTPRJ | USP9X
5
0.859


CNTN1 | MGAT1 | TRIM42 | USP9X | PPY
5
0.859


CD59 | CNTN1 | MGAT1 | PTPRJ | TRIM42
5
0.859


B4GALT1 | CNTN1 | FAM20C | TRIM42 | USP9X
5
0.858


B4GALT1 | CNTN1 | TRIM42 | USP9X | INS
5
0.857


B4GALT1 | CNTN1 | TRIM42 | USP9X | PPY
5
0.857


CD59 | CHKA | CNTN1 | USP9X | PPY
5
0.856


B4GALT1 | CNTN1 | TRIM42 | USP9X
4
0.856


CHKA | CNTN1 | FAM20C | MGAT1 | USP9X
5
0.855


CD59 | CHKA | CNTN1 | USP9X | BTC
5
0.855


B4GALT1 | CNTN1 | TRIM42 | USP9X | CPM
5
0.855


CNTN1 | PTPRJ | TRIM42 | USP9X | INS
5
0.855


CD59 | CHKA | CNTN1 | USP9X | CPM
5
0.855


CD59 | CHKA | CNTN1 | USP9X | INS
5
0.854


B4GALT1 | CNTN1 | TRIM42 | USP9X | BTC
5
0.854


B4GALT1 | CD59 | CHKA | CNTN1 | USP9X
5
0.853


CD59 | CHKA | CNTN1 | USP9X
4
0.853


CNTN1 | PTPRJ | TRIM42 | USP9X | BTC
5
0.853


CNTN1 | PTPRJ | TRIM42 | USP9X | PPY
5
0.853


CD59 | CNTN1 | FAM20C | PTPRJ | TRIM42
5
0.853


CD59 | CHKA | CNTN1 | PTPRJ | TRIM42
5
0.853


B4GALT1 | CHKA | CNTN1 | MGAT1 | USP9X
5
0.852


CNTN1 | PTPRJ | TRIM42 | USP9X
4
0.852


CNTN1 | FAM20C | PTPRJ | TRIM42 | USP9X
5
0.852


CHKA | CNTN1 | MGAT1 | PTPRJ | USP9X
5
0.852


CD59 | CNTN1 | PTPRJ | TRIM42 | PPY
5
0.852


CNTN1 | PTPRJ | TRIM42 | USP9X | CPM
5
0.852


B4GALT1 | CHKA | CNTN1 | FAM20C | USP9X
5
0.851


CHKA | CNTN1 | MGAT1 | USP9X | INS
5
0.851


CD59 | CHKA | MGAT1 | TRIM42 | USP9X
5
0.851


CD59 | CNTN1 | PTPRJ | TRIM42 | BTC
5
0.850


B4GALT1 | CD59 | CNTN1 | PTPRJ | TRIM42
5
0.850


CD59 | CNTN1 | PTPRJ | TRIM42
4
0.850


CD59 | CNTN1 | PTPRJ | TRIM42 | CPM
5
0.850









Example II. Determination of the Level of One or More Biomarkers in a Subject Sample

A biological sample (e.g., serum, saliva) is obtained from a subject and the level of one or more of the markers listed in Tables 1-3 is determined by mass spectrometry to determine (e.g., whether a subject has or will develop type 2 diabetes, whether the subject has or will develop impaired glucose tolerance, whether the subject will develop a type 2 diabetes-associated complication, whether the subject having impaired glucose tolerance and/or type 2 diabetes will respond to a therapy). Briefly, the sample is digested with trypsin to generate peptides. The peptides are then separated by strong cation exchange chromatography (SCX) into three fractions. Each of the three fractions per sample is analyzed by reversed phase liquid chromatography, coupled by electrospray to a Waters QTOF mass spectrometer (LC-MS). Components are detected and matched across all samples and compared for relative peak intensity. Peak intensity is normalized. The level of the one or more markers in the sample is compared to a level of the one or more markers in a control sample and a difference in the level of the one or more markers in the subject sample as compared to the level of the one or more markers in the control sample indicates that the subject has or will develop impaired glucose tolerance.


EQUIVALENTS

In describing exemplary embodiments, specific terminology is used for the sake of clarity. For purposes of description, each specific term is intended to at least include all technical and functional equivalents that operate in a similar manner to accomplish a similar purpose. Additionally, in some instances where a particular exemplary embodiment includes a plurality of system elements or method steps, those elements or steps may be replaced with a single element or step. Likewise, a single element or step may be replaced with a plurality of elements or steps that serve the same purpose. Further, where parameters for various properties are specified herein for exemplary embodiments, those parameters may be adjusted up or down by 1/20th, 1/10th, ⅕th, ⅓rd, ½, etc., or by rounded-off approximations thereof, unless otherwise specified. Moreover, while exemplary embodiments have been shown and described with references to particular embodiments thereof, those of ordinary skill in the art will understand that various substitutions and alterations in form and details may be made therein without departing from the scope of the invention. Further still, other aspects, functions and advantages are also within the scope of the invention.


Exemplary flowcharts are provided herein for illustrative purposes and are non-limiting examples of methods. One of ordinary skill in the art will recognize that exemplary methods may include more or fewer steps than those illustrated in the exemplary flowcharts, and that the steps in the exemplary flowcharts may be performed in a different order than shown.


INCORPORATION BY REFERENCE

The contents of all references, including patents and patent applications, cited throughout this application are hereby incorporated herein by reference in their entirety. The appropriate components and methods of those references may be selected for the invention and embodiments thereof. Still further, the components and methods identified in the Background section are integral to this disclosure and can be used in conjunction with or substituted for components and methods described elsewhere in the disclosure within the scope of the invention.

Claims
  • 1. A method for monitoring the effectiveness of a diabetic treatment in a subject having type 2 diabetes, the method comprising determining the level of carboxypeptidase M (CPM), insulin-1 (INS), matrilysin (MMP7), and low-density lipoprotein receptor (LDLR) in a first fluid sample(s) obtained from the subject prior to the initiation of the treatment,wherein the determining of the level of CPM, INS, MMP7, and LDLR in the first fluid sample(s) is performed using mass spectrometry or immunoassay;determining the level of CPM, INS, MMP7, and LDLR in a second fluid sample(s) obtained from the subject after the treatment has been administered,wherein the determining of the level of CPM, INS, MMP7, and LDLR in the second fluid sample(s) is performed using mass spectrometry or immunoassay; andcomparing the level of CPM, INS, MMP7, and LDLR in the first sample(s) with a level of CPM, INS, MMP7, and LDLR in the second sample(s), wherein a lower level of CPM, INS, and MMP7, and a higher level of LDLR in the second sample(s) as compared to the level of CPM, INS, MMP7, and LDLR in the first sample(s) indicates that the subject is responding to the diabetic treatment, thereby monitoring the effectiveness of the treatment in the subject.
  • 2. The method of claim 1, further comprising determining one or more of the level of the hemoglobin A1c (HbA1c) level, and the fasting plasma glucose level in a sample(s) from the subject.
  • 3. The method of claim 1, further comprising determining the level of one or more markers selected from the group consisting of probable ubiquitin carboxyl-terminal hydrolase FAF-X (USP9X), similar to dystroglycan precursor (DAG1), neuronal-specific septin-3 (SEPT3), receptor-type tyrosine-protein phosphatase eta (PTPRJ), Serpin B13 (SERPINB13), probetacellulin (BTC), and pancreatic icosapeptide (PPY) in a sample(s) obtained from the subject.
  • 4. The method of claim 1, further comprising determining the level of one or more markers selected from the group consisting of cleavage stimulation factor subunit 3 (CSTF3), protein kinase C-binding protein NELL1 (NELL1), slit homolog 3 (SLIT3), regulator complex protein LAMTOR 2 (LAMTOR2), alpha-1,3-mannosyl-glycoprotein 4-beta-acetylglucosaminyl transferase B (MGAT4B), transmembrane protease serine 11F (TMPRSS11F), ATPase family AAA domain-containing protein 3B (ATAD3B), receptor-type tyrosine-protein phosphatase-like N (PTPRN), protein Wnt-9b (WNT9B), alpha-(1,3)-fucosyltransferase (FUT6), beta-1,4-galactosyltransferase 1 (B4GALT1), family with sequence similarity 20, member C (FAM20C), contactin-1 (CNTN1), alpha-1,3-mannosyl-glycoprotein 2-beta-acetylglucosaminyl transferase (MGAT1), syntaxin-1A (STXIA), neuromedin U (NMU), CD59 glycoprotein (CD59), peripheral plasma membrane protein CASK (CASR), and carboxypeptidase E (CPE) in a sample(s) obtained from the subject.
  • 5. The method of claim 1, wherein the fluid sample(s) is a blood sample(s).
  • 6. The method of claim 1, wherein the subject is a non-human mammal.
  • 7. The method of claim 1, wherein the subject is human.
  • 8. The method of claim 1, wherein the combination of CPM, INS, MMP7, and LDLR has an area under the curve (AUC) of greater than about 0.70.
RELATED APPLICATIONS

This application is a 35 U.S.C. 111(a) continuation application, which claims the benefit of priority to PCT/PCT/IB2014/000426, filed on Jan. 31, 2014 and U.S. Provisional Patent Application Ser. No. 61/758,987, filed on Jan. 31, 2013, the entire contents of each of which is incorporated herein by reference.

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Related Publications (1)
Number Date Country
20150330997 A1 Nov 2015 US
Provisional Applications (1)
Number Date Country
61758987 Jan 2013 US
Continuations (1)
Number Date Country
Parent PCT/IB2014/000426 Jan 2014 US
Child 14813344 US