Patent Application
20150369820
All patent and non-patent references cited in the application are hereby incorporated by reference in their entirety.
The present invention relates to the use of soluble CD206 as a general health/disease marker, and a specific marker for liver disorders, sepsis, and pneumonia.
The mannose receptor is a C-type lectin carbohydrate binding protein primarily present on the surface of macrophages and dendritic cells. It helps recognize pathogens that have mannose on their surface, and triggers one pathway of the complement system.
The function of this receptor is to recognize complex carbohydrates that are located on glycoproteins that are a part of many different biological processes. Some of those processes include cell—cell recognition, serum glycoprotein turnover, and neutralization of pathogens. The protein also functions as a type 1 membrane immune receptor that mediates the endocytosis of glycoproteins by macrophages. The structure of these proteins allows them to bind to high mannose structures on the surface of potentially pathogenic viruses, bacteria, and fungi so that they can be engulfed by the cell.
Humans have two different mannose receptors, MRC1 and MRC2. MRC1 is also known as CD206.
Arce-Mendoza et al, “Expression of CD64, CD206 and RAGE in adherent cells of diabetic patients infected with Mycobacterium tuberculosis” Arch Med Res 2008; 39(3): 306-11 discloses a study of the expression of CD64, CD206 and RAGE on mononuclear cells isolated and cultured to obtain adherent cells using flow cytometry. Four groups of patients were examined; a group with type 2 diabetes, a group with pulmonary tuberculosis, a group with type 2 diabetes and pulmonary tuberculosis and a control group. The group with type 2 diabetes and the group with type 2 diabetes and pulmonary tuberculosis expressed greater mean fluorescense intensity of CD206 than the control group. The measurements are done on mononuclear cells isolated and cultured to obtain adherent cells and then stimulated with M. tuberculosis H37Rv lipids.
Porcheray et al., “Macrophage activation switching: an asset for the resolution of inflammation” Clin Exp Immunol, 2005; 142(3): 481-9 discloses that macrophage activation leads to differential phenotypes. It is disclosed that CD163 and CD206 exhibits mutually exclusive induction patterns after stimulation by a panel of anti-inflammatory molecules.
Linehan, S A, “The mannose receptor is expressed by subsets of APC in non-lymphoid organs” BMC Immunol, 2005; 6:4 discloses a study identifying the mannose receptor (MR) positive APC's and their distribution in different organs. It is concluded that MR positive APC are present in several peripheral organs like skin, liver, cardiac and skeletal muscle and tongue.
Nguyen and Hildreth, “Involvement of macrophage mannose receptor in the binding and transmission of HIV by macrophages” Eur J Immunol, 2003; 33(2): 483-93 discloses the ability of macrophages to bind HIV and facilitate its transmission to T cells. The initial association of HIV with macrophages is macrophage mannose receptor (MMR) mediated.
Allavena et al. “Engagement of the mannose receptor by tumoral mucins activates an immune suppressive phenotype in human tumor-associated macrophages” Clin Dev Immunol, 2010; Epub 2011 Feb. 9 discloses that Tumor-associated macrophages (TAMs) isolated from human ovarian carcinoma most abundantly expresses the mannose Receptor (MR). It is contemplating that this association may contribute to the immune suppressive phenotype of the TAMs.
Wollenberg et al “Expression and function of the mannose receptor CD206 on epidermal dendritic cells in inflammatory skin diseases” J Invest Dermatol, 2002; 118(2): 327-34 discloses that some epidermal dendritic cells may express CD206 under inflammatory skin conditions. It is contemplated that the inflammatory dendritic epidermal cells use CD206 for receptor-mediated endocytosis.
Martinez-Pomares et al “A functional soluble form of the murine mannose receptor is produced by macrophages in vitro and is present in mouse serum”, J Biol Chem 1998, 273:23376-80 discloses that the extracellular domain of the murine mannose receptor is shed from macrophages and can be detected in mouse serum. According to the reference sMR levels in mouse serum were not affected by Mycobacterium bovis bacillus, Calmette-Guérin or C. albicans infection or by intraperitoneal treatment with LPS, zymosan or heat-killed C. albicans.
The prior art provides no demonstration that soluble CD206 can be detected in human serum. Further, the prior art provides no indication that soluble CD206 can be used as a diagnostic marker. In contrast, according to Martinez-Pomares et al 1998, serum levels of murine CD206 is not affected by bacterial and fungal infections.
The present invention relates to the novel use of the CD206 protein as a sensitive biomarker for predicting the risk of a subject having a disorder and/or disease and is based on the surprising finding that human serum contains substantial amounts of soluble CD206 and that the level of soluble CD206 surprisingly correlates with the subject's health condition. Specifically, the inventors have observed that the amount of soluble CD206 in serum from healthy subjects is relatively low and that the level is significantly increased in subjects in intensive care units, especially in severely ill patients with sepsis, in patients with liver disease and in pneumonia patients.
The level of sCD206 can be used for several purposes. In apparently healthy subjects an increased level of sCD206 is indicative of the presence of a latent or developing disease. Early identification of subjects with latent or early stage disease can be used to improve diagnosis or treatment. If a subject is feeling unwell, an increased level of sCD206 is indicative of the presence of a disease that could be severe and may require further investigation and subsequent treatment.
As the level of sCD206 also correlates with disease severity and with fatal outcome, the marker can be used to predict disease severity in subjects that are sick and optionally have been diagnosed with a disorder. In subjects diagnosed with a disease the level of sCD206 can be used to diagnose or prognose disease progression and to follow the efficacy of any treatment.
In sick subjects, in particular in severely sick subjects, the level of sCD206 can be used to predict fatal outcome of the disease.
The level of sCD206 can therefore be used to distinguish between subjects that require further diagnostic assessment and/or intensified treatment (in particular subjects suspected of having sepsis, a hepatological disorder, or a pneumococcal disorder) and those that do not. As demonstrated in Example 4, the level of sCD206 is increased in invasive pneumococcal disease (IPD) and the level is indicative of fatal outcome.
The inventors have demonstrated that serum sCD206 is significantly increased in subjects with acute alcoholic hepatitis. The level of soluble CD206 in human serum has also been found to correlate at least to some extent with the serum level of CD163. Consequently, the serum level of CD206 may be used as a biomarker to the same extent as soluble CD163.
One preferred embodiment relates to the use of CD206 to predict the risk of having a liver disorder, preferably hepatitis, more preferably hepatitis C cirrhosis or fibrosis, or acute alcoholic hepatitis. In other embodiments, the liver disorder may be fatty liver disease, more specifically hepatitic steatosis.
Another preferred embodiment relates to the use of CD206 to identify patients with sepsis or septic shock among severely ill patients, and to predict the risk of contracting complications, including mortality, in patients with sepsis. In other embodiments, the severe disorder may be SIRS (systemic inflammatory Response Syndrome).
In a further aspect the invention relates to a method of treatment of a disease or disorder comprising treating subjects having an increased level of sCD206. Continued measurements of sCD206 can be used to follow the efficacy of the treatment.
In yet another preferred aspect, the present invention relates to the use of sCD206 in a method of assessing the efficacy of a therapy given to a patient by assessing the level of sCD206 in serum from a patient, subjecting said patient to therapy and subsequently assessing the level of sCD206 again to evaluate whether said therapy is efficious.
In yet another aspect, the present invention relates to the use in a method of assessing the safety of a potential therapy and/or drug candidate by determining the level of sCD206 in a subject, subjecting said subject to said therapy and/or drug candidate and determining the level of sCD206, wherein the absence of a significant increase in sCD206 indicates that the therapy and/or drug candidate is safe.
In yet another aspect, the present invention relates to the use of sCD206 in a method of screening donor blood, wherein the donor blood is evaluated for the content of sCD206 and said contents is compared to a cut-off value indicating whether the subject donating the blood is healthy or not. Thus the method may be used to determine whether the blood is safe enough to be used for transfusion or for preparation of blood-derived products.
In further aspects, the application relates to the use of the CD206 protein as a sensitive biomarker for predicting whether a subject is suffering from a fungal infection and is based on the surprising finding that human serum contains substantial amounts of soluble CD206. The level of sCD206 can therefore be used to distinguish between subjects that suffer from a fungal infection and those that do not.
In a further aspect the invention relates to a method of treatment of a fungal infection comprising treating subjects having an increased level of sCD206. Continued measurements of sCD206 can be used to follow the efficacy of the treatment.
In a further aspect the invention relates to a method of diagnosing and treatment of complications to a fungal infection comprising treating subjects having an increased level of sCD206. Continued measurements of sCD206 can be used to follow the efficacy of the treatment.
In yet another preferred aspect, the present invention relates to the use of sCD206 in a method of assessing the efficacy of a therapy given to a patient suffering from a fungal infection by assessing the level of sCD206 in serum from a patient, subjecting said patient to therapy and subsequently assessing the level of sCD206 again to evaluate whether said therapy is efficacious.
In an aspect, the application relates to a method for diagnosing or prognosing a disease, or the risk thereof, in a subject in need thereof, comprising: (a) determining an amount of soluble CD206 in a biological sample including a biological fluid or a biological tissue from the subject; and (b) comparing the amount of the soluble CD206 in the sample with a control level, wherein if the amount determined in (a) is higher the control level, the subject is diagnosed as having, or at an increased risk of developing, a disease. The disease may be any of the diseases as herein described. The control level may be a level representative of healthy subjects, optionally age or sex corrected or a cutoff level as herein described.
In other aspects the application relates to assessing the severity of a disease, or the risk of fatal outcome, in a subject in need thereof, comprising: (a) determining an amount of soluble CD206 in a biological sample including a biological fluid or a biological tissue from the subject; and (b) comparing the amount of the soluble CD206 in the sample with a control level, wherein if the amount determined in (a) is higher the control level, the severity of the disease is predicted to be higher or even fatal. In these cases the control level may be a level representative of healthy subjects, a level representative of sick subjects with non-severe disease, a cutoff level as herein described, or a level of sCD206 determined in the same subject prior to disease or in an earlier (less severe) stage of the disease.
(A) Immunoblotting of different human plasma samples (lanes 1-4), human macrophage lysate (positive control, lane 5), and bladder cancer cell lysate (negative control, lane 6) with monoclonal mouse anti human sMR. Enhanced chemiluminescence was used as detection system. The concentration of sMR as measured by the sandwich enzyme-linked immunosorbent assay (ELISA) is indicated for each sample.
(B) Coomassie Brilliant Blue staining of purified sMR from human plasma separated by SDS-PAGE. Lanes 1-4 were purified using mannose affinity chromatography, lane 5 by immune-affinity chromatography. Bands corresponding to approximately 170 kDa were cut and analysed by MALDI MS/MS.
A) Linearity. Serum (twofold diluted 1:20-1:10,240) was measured in quadruplicates.
(B) Comparability of serum vs. plasma. Paired serum, EDTA-plasma, and heparin-plasma was collected from 30 patients and sMR determined in duplicates.
(C) Stability over time. Three pools of fresh plasma were prepared, and aliquots of 50 μl were taken from each pool and kept at RT, +6° C., −20° C. and −80° C. Samples were analyzed during a period of 270 days.
(D) Freeze-thaw stability. Seven aliquots were taken from each of three pools of plasma and frozen (−80° C.) and thawed (+20° C.) one to seven times, frozen at −80° C. and subsequently analyzed in the same run.
The concentration of sMR in serum from 217 healthy individuals was measured by ELISA. Reference intervals for intervals<50 years (0.09-0.37 mg/l) and 50 years (0.12-0.46 mg/l) are indicated.
Comparison of sMR concentrations in 218 hospitalized patients with CRP (A) and sCD163 (B). Dotted lines indicate upper and lower limits of the reference intervals. sMR and sCD163 were measured by ELISA.
Serum concentrations of sMR in healthy compared to hospitalized patients as measured by ELISA. The mean concentrations are indicated. Med: Mainly endocrinological and haematological patients (n=153). The patients in this group have been hospitalized for different durations. Consequently this group covers a rather diverse section of patients, some of which have been cured or have been almost cured.
Hepatol: Hepatological patients (n=37). ICU: patient from intensive care unit (n=28). AAH: Patients with acute alcoholic hepatitis (n=50).
Sequence alignment of amino acid sequences of CD206 from humans (SEQ ID NO:1), pig (SEQ ID NO:4), mouse (SEQ ID NO:2), rat (SEQ ID NO:3), and Rhesus macaque (SEQ ID NO:5). The alignment prepared in Clustal W illustrates the degree of conservation and provides a consensus sequence for the group of sequences.
Panel A+B: The x-axis represents time (day 1, 2, 3, and 4 of ICU admission), and the y-axis represents the median fluorescence intensity or concentration of sCD163 (mg/L). Dots represent median, bars represent interquartil range. During the four-day observation period, monocyte expression of CD206 (panel A) and soluble CD206 (panel B) was significantly higher in patients with severe sepsis or septic shock compared with severely ill non-septic patients (p<0.001 for both comparisons). At ICU admission, monocyte expression of CD206 and levels of sCD206 were significantly higher in patients with severe sepsis and septic shock compared to severely ill non-septic patients and healthy controls (p<0.001 for all comparison). Levels of sCD206 were higher in the non-septic patients compared to controls (p=0.002). With regards to monocyte expression of CD206, we observed no difference between severely ill non-septic patients and controls.
Panel C: Monocyte expression of CD206 did not correlate with sCD206.
At ICU admission sCD206 had the highest AUROC (1; 95% CI 1 to 1), followed by sCD163 (0.95; 95% CI 0.788 to 1), CD206 (0.86; 95% CI 0.73 to 0.98), and CD163 (0.73; 95% CI 0.56 to 0.90).
Panel C: Monocyte expression of CD206 (p=0.02) and panel D: levels of sCD206 (p<0.001) was significantly higher in the septic patients compared to the non-septic patients.
During the 4-day observation period monocyte expression of CD163 (p<0.001) and levels of sCD163 (p=0.004) were significantly higher in the septic patients compared to the non-septic patients (Panel A+B). Monocyte expression of CD206 (p=0.02) and levels of sCD206 (p<0.001) was also observed to besignificantly higher in the septic patients compared to the non-septic patients (Panel C+D).
At ICU admission, monocyte expression of CD163 (p=0.006) and sCD163 (p=0.02) was higher in in-hospital non-survivors than survivors. Likewise, monocyte expression of CD206 (p=0.003) and sCD206 (p=0.001) was also higher in in-hospital non-survivors than survivors.
At ICU admission sCD206 had the highest AUROC (0.87; 95% CI 0.74 to 0.99), followed by CD206 (0.79; 95% CI 0.64 to 0.95), sCD163 (0.78; 95% CI 0.60 to 0.95), and CD163 (0.77; 95% CI 0.60 to 0.95). There were no differences between variables (Panel E).
A. all patients, B Patients below 75 yrs, C. Patients above 75 yrs.
A. all patients, B Patients below 75 yrs, C. Patients above 75 yrs.
The term CD206 used herein refers to both soluble and membrane-bound forms. CD206 is also known as Mannose receptor, MRC1, Macrophage mannose receptor 1, MMR, C-type lectin domain family 13 member D, C-type lectin domain family 13 member D-like, Macrophage mannose receptor 1-like protein, 1 CD_antigen=CD206,
The term “sCD206”=soluble CD206=shed CD206=plasma CD206=serum CD206=circulating CD206=sMR
The term ‘soluble’ used herein refers to the property of a solid, liquid, or gaseous chemical substance to dissolve in a liquid solvent to form a homogeneous solution. Further it refers to a compound, such as a protein, being in liquid solution as not being attached to a membrane or other anchoring or attaching moieties.
The term ‘disorder’ used herein refers to a medical problem, and is an abnormal condition of an organism that impairs bodily functions, associated with specific symptoms and signs. It may be caused by external factors, such as invading organisms, or it may be caused by internal dysfunctions.
The term ‘disease’ as used herein refers to an abnormal condition of the body or mind that causes discomfort or dysfunction; it is distinct from injury insofar as the latter is usually instantaneously acquired.
The term ‘protein’ used herein refers to an organic compound, also known as a polypeptide, which is a peptide having at least, and preferably more than two amino acids. The generic term amino acid comprises both natural and non-natural amino acids any of which may be in the ‘D’ or ‘L’ isomeric form.
The term ‘biological sample’ used herein refers to any sample selected from the group, but not limited to, serum, plasma, whole blood, saliva, urine, lymph, a biopsy, semen, faeces, tears, sweat, milk, cerebrospinal fluid, ascites fluid, synovial fluid.
The term ‘binding assay’ used herein refers to any biological or chemical assay in which any two or more molecules bind, covalently or non-covalently, to each other thereby enabling measuring the concentration of one of the molecules.
The term ‘chromatographic method’ used herein refers to a collective term for the process of separating mixtures. It involves passing a mixture dissolved in a “mobile phase” through a stationary phase, which separates the analyte to be measured from other molecules in the mixture and allows it to be isolated.
The term ‘risk factor’ used herein refers to a variable associated with an increased risk of disease or infection. Risk factors are correlational and not necessarily causal, because correlation does not imply causation.
The term ‘detection moiety’ used herein refers to a specific part of a molecule, preferably but not limited to be a protein, able to bind and detect another molecule.
The term “subject” used herein refers to a mammal, such as a dog, a cat, a horse, cattle, a camel or a human. In a preferred embodiment the subject is a human.
The term “Sequence identity” used herein refers to the determination of percent identity between two amino acid sequences can be accomplished using a mathematical algorithm. A preferred, non-limiting example of a mathematical algorithm utilized for the comparison of two sequences is the algorithm of Karlin and Altschul (1990) Proc. Natl. Acad. Sci. USA 87:2264-2268, modified as in Karlin and Altschul (1993) Proc. Natl. Acad. Sci. USA 90:5873-5877. Such an algorithm is incorporated into the BLASTP program of Altschul, et al. (1990) J. Mol. Biol. 215:403-410.
Another preferred, non-limiting example of a mathematical algorithm utilized for the comparison of sequences is the CLUSTAL W (1.7) alignment algorithm (Thompson, J. D., Higgins, D. G. and Gibson, T. J. (1994) CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, positions-specific gap penalties and weight matrix choice. Nucleic Acids Research, 22:4673-4680). CLUSTAL W can be used for multiple sequence alignment preferably using BLOSUM 62 as scoring matrix. When calculating sequence identities, CLUSTAL W includes any gaps made by the alignment in the length of the reference sequence. Sequence identities are calculated by dividing the number of matches by the length of the aligned sequences with gaps.
Hepatology is the branch of medicine that incorporates the study of liver, gallbladder, biliary tree, and pancreas as well as management of their disorders. Diseases and complications related to viral hepatitis and alcohol are the main reason for seeking specialist advice. More than 2 billion people have been infected with Hepatitis B virus at some point in their life, and approximately 350 million have become persistent carriers. Up to 80% of liver cancers can be attributed to either Hepatitis B or Hepatitis C virus. In terms of mortality, the former is second only to smoking among known agents causing cancer. With more widespread implementation of vaccination and strict screening before blood transfusion, lower infection rates are expected in the future. In many countries, though, overall alcohol consumption is increasing, and consequently the number of people with cirrhosis and other related complications is commensurately increasing.
According to the present invention liver diseases include the following ICD10 classified liver diseases:
K70 Alcoholic liver disease
Alcoholic fatty liver
Alcoholic hepatitis
Alcoholic fibrosis and sclerosis of liver
Alcoholic cirrhosis of liver
Alcoholic hepatic failure
Alcoholic liver disease, unspecified
K71 Toxic liver disease
Toxic liver disease with cholestasis
Toxic liver disease with hepatic necrosis
Toxic liver disease with acute hepatitis
Toxic liver disease with chronic persistent hepatitis
Toxic liver disease with chronic lobular hepatitis
Toxic liver disease with chronic active hepatitis
Toxic liver disease with hepatitis, not elsewhere classified
Toxic liver disease with fibrosis and cirrhosis of liver
Toxic liver disease with other disorders of liver
Toxic liver disease, unspecified
K72 Hepatic failure, not elsewhere classified
hepatic:
hepatitis:
liver (cell) necrosis with hepatic failure
yellow liver atrophy or dystrophy
Acute and subacute hepatic failure
Chronic hepatic failure
Hepatic failure, unspecified
K73 Chronic hepatitis, not elsewhere classified
Chronic persistent hepatitis, not elsewhere classified
Chronic lobular hepatitis, not elsewhere classified
Chronic active hepatitis, not elsewhere classified
Other chronic hepatitis, not elsewhere classified
Chronic hepatitis, unspecified
K74 Fibrosis and cirrhosis of liver
Hepatic fibrosis
Hepatic sclerosis
Hepatic fibrosis with hepatic sclerosis
Primary biliary cirrhosis
Secondary biliary cirrhosis
Biliary cirrhosis, unspecified
Other and unspecified cirrhosis of liver
K76 Other diseases of liver
Fatty (change of) liver, not elsewhere classified
Chronic passive congestion of liver
Central haemorrhagic necrosis of liver
Infarction of liver
Peliosis hepatis
Hepatic veno-occlusive disease
Portal hypertension
Hepatorenal syndrome
Other specified diseases of liver
Liver disease, unspecified
Intensive-care medicine (critical-care medicine) is a branch of medicine concerned with the diagnosis and management of life threatening conditions requiring sophisticated organ support and invasive monitoring. Sepsis affects approximately 3 in 1000 people a year, and is the second-leading cause of death in intensive care units. Approximately 20-35% of people with severe sepsis and 30-70% of people with septic shock die.
According to the present invention sepsis include the following ICD10 classified sepsis associated diseases:
A40 streptococcal sepsis
A41 other sepsis
CD206
CD206 is also known as MRC1, Macrophage mannose receptor 1, MR, sMR, MMR, C-type lectin domain family 13 member D, C-type lectin domain family 13 member D-like, Macrophage mannose receptor 1-like protein, and 1 CD_antigen=CD206.
CD206/MRC1 exists in humans as a 1456 amino acid long precursor. It consists of an N-terminal signal peptide and contains three domains: an extracellular domain, a transmembrane domain, and a cytoplasmic domain.
MRC1 is expressed as an unprocessed precursor of 1456 amino acids. The molecular weight of the unprocessed precursor is 166 KDa. The protein encoded by the MRC1 gene is classified as a type I transmembrane receptor since the protein C terminus is located on the cytoplasmic side of the membrane.
MRC1 is a membrane receptor containing:
The fourth of these domains, CTLD4, is the only functional domain. In cooperation with CTLD5, CTLD4 is central to ligand binding by the receptor,
Probably the MRC1 receptor acts with an alternation between bent and extended conformations, that might serve as a “conformational switch” to regulate ligand binding and receptor activity.
MRC1 interacts with CHEK2 (CHK2 checkpoint homolog—S. pombe) protein.
MRC1 is commonly expressed on macrophages and endothelial cells.
The protein is located in the Plasma membrane and functions by mediating the endocytosis of glycoproteins by macrophages binding both sulfated and non-sulfated polysaccharide chains.
MRC1 acts as a phagocytic receptor binding a range of pathogens, such as bacteria, viruses and fungi, through high-mannose structures that are in their surface.
Human MRC1 is an ortholog to murine Mrc1, rat Mrc1, cow LOC787578, chimpanzee MLR1L1, and canine LOC487114. It is a paralog to MRC1L1, CD302, PLA2R1, MRC2.
The extracellular domain of CD206 can be cleaved by metalloproteases (Martinez-Pomares, 2012, J Leukocyte Biol, vol 92 (E-pub doi:10.1189/jlb.0512231); Gazi et al, 2011, J Biol Chem, vol 286:7822-29; Martinez-Pomares et al 1998; Jordens et al 1999, Int Immunol 11,11:1775-1780) to create a soluble CD206 receptor. The soluble CD206 consists of the extracellular domain. The soluble CD206 is capable of binding mannosylated sugars and not sulphated sugars, as multimerisation is required for binding to sulphated sugars (Martinez-Pomares 2012).
Shedding of CD206 by cultured macrophages can be stimulated in vitro by fungal pathogens (Gazi et al, 2011). In vivo, no such stimulation has been reported in the prior art. In contrast, Martinez-Pomares et al 1998 found that the level of soluble CD206 in mouse serum was unaffected by Mycobacterium bovis bacillus, Calmette-Guérin or C. albicans infection or by intraperitoneal treatment with LPS, zymosan or heat-killed C albicans.
CD206 Variants
The present invention involves determining the level of CD206 in a sample from a subject. CD206 is found in a variety of organisms as demonstrated in the sequence alignment of
Variants can differ from naturally occurring CD206 in amino acid sequence or in ways that do not involve sequence, or in both ways. Variants in amino acid sequence (“sequence variants”) are produced when one or more amino acids in naturally occurring CD206 are substituted with a different natural amino acid, an amino acid derivative or non-native amino acid. Particularly preferred variants include naturally occurring CD206, or biologically active fragments of naturally occurring CD206, whose sequences differ from the wild type sequence by one or more conservative and/or semi-conservative amino acid substitutions, which typically have minimal influence on the secondary and tertiary structure and hydrophobic nature of the protein or peptide. Variants may also have sequences, which differ by one or more non-conservative amino acid substitutions, deletions or insertions, which do not abolish the CD206 biological activity. The alignment in
Substitutions within the following groups (Clustal W, ‘strong’ conservation group) are to be regarded as conservative substitutions within the meaning of the present invention
Substitutions within the following groups (Clustal W, ‘weak’ conservation group) are to be regarded as semi-conservative substitutions within the meaning of the present invention
Variants to be detected in one embodiment include proteins and peptides with amino acid sequences having at least 60 percent identity with the soluble part of human, murine, pig, rat or rhesus macaque CD206 (SEQ ID NO: 1, 2, 3, 4 and 5). More preferably the sequence identity is at least 65%, more preferably at least 70%, more preferably at least 75%, more preferably at least 80%, more preferably at least 85%, more preferably at least 90%, more preferably at least 95%, more preferably at least 98
In a preferred embodiment the sequence identity of the variant CD206 is determined with reference to the soluble part of a human CD206 polypeptide (SEQ ID 1).
All aspects of CD206 measurements herein and all detection methods refer to any form of soluble CD206. In a preferred embodiment, the measured CD206 is sCD206.
Associations with Disease States
In one embodiment, sCD206 is used as a sensitive biomarker for liver diseases. In a preferred embodiment, physicians may be enabled to discriminate between high and low risk groups throughout the entire age of a population by obtaining a biological sample from an individual.
Sepsis is a leading cause of death in hospitalized patients, and even though large efforts have been implemented, mortality rates of patients with severe sepsis or septic shock are still unacceptably high.
In another embodiment, sCD206 is used as a sensitive biomarker for sepsis in critically ill patients. In another preferred embodiment, physicians may diagnose risk of sepsis in severe illness by obtaining a biological sample from an individual and assessing the sCD206 level. In another preferred embodiment, physicians may diagnose risk of complications to sepsis (e.g. cardiovascular, or renal, for example, but not restricted to pulmonary complications), by obtaining a biological sample from an individual and assessing the sCD206 level.
In another embodiment, sCD206 is used as a sensitive biomarker for pneumonia and for prognosis of pneumonia patients. In another preferred embodiment, physicians may diagnose disease prognosis in pneumonia by obtaining a biological sample from an individual and assessing the sCD206 level. In another preferred embodiment, physicians may diagnose risk of complications to pneumonia, by obtaining a biological sample from an individual and assessing the sCD206 level.
The present invention relates to the use of sCD206 as a sensitive biomarker for fungal infections. In a preferred embodiment, physicians may discriminate between high and low risk groups throughout the entire age of a population by obtaining a biological sample from an individual and assessing the level of sCD206.
One embodiment relates to the use of sCD206 as a biomarker for fungal infections in critically ill patients. In another preferred embodiment, physicians may diagnose risk of fungal infections in severe illness by obtaining a biological sample from an individual.
Medical Conditions Associated with CD206
The present invention relates to the finding that sCD206 may be used as a biomarker for the presence of an unspecific disease or disorder, as sCD206 is elevated in hospitalised patients and in patients undergoing treatment. Preferably, the disease or disorder is a liver disorder and/or disease. In a more preferred embodiment, the liver disorder is alcoholic liver disease, such as alcoholic fatty liver, for example alcoholic hepatitis, such as alcoholic fibrosis and sclerosis of liver, for example alcoholic cirrhosis of liver, such as alcoholic hepatic failure (acute, chronic, subacute, with or without hepatic coma).
In another preferred embodiment, the liver disorder is toxic liver disease, such as toxic liver disease with cholestatsis (cholestasis with hepatocyte injury, pure cholestasis), for example toxic liver disease with hepatic necrosis (acute hepatic failure, chronic hepatic failure due to drug abuse), such as toxic liver disease with acute or chronic persistent hepatitis, for example toxic liver disease with chronic lobular hepatitis, such as toxic liver disease with chronic active hepatitis, for example toxic liver disease with lupoid hepatitis, such as toxic liver disease with hepatitis, for example toxic liver disease with fibrosis and cirrhosis of liver, such as toxic liver disease with other disorders of liver (focal nodular hyperplasia, hepatic granulomas, peliosis hepatis, veno-occlusive disease of liver).
In yet another preferred embodiment, the liver disorder is hepatic failure (coma NOS, encephalopathy NOS, acute hepatitis, fulminant hepatitis, malignant hepatitis, liver cell necrosis with hepatic failure), such as acute and subacute hepatic failure, for example chronic hepatic failure.
In yet another preferred embodiment, the liver disorder is chronic hepatitis, not elsewhere classified (NEC), such as chronic persistent hepatitis NEC, for example chronic lobular hepatitis NEC, such as chronic active hepatitis (lupoid hepatitis) NEC, for example other chronic hepatitis NEC.
In yet another preferred embodiment, the liver disorder is fibrosis and cirrhosis of liver, such as hepatic fibrosis, for example hepatic sclerosis, such as hepatic fibrosis with hepatic sclerosis, for example primary biliary cirrhosis (chronic nonsuppurative destructive cholangitis), such as secondary biliary cirrhosis, for example unspecified biliary cirrhosis, such as other and unspecified cirrhosis of liver, for example cryptogenic, macronodular, mixed type, portal or postnecrotic cirrhosis of liver. In yet another preferred embodiment, the liver disorder is specified as other inflammatory liver diseases such as abscess of liver (cholangitic, haematogenic, lymphogenic or pylephlebtic hepatic abscess), for example phlebitis (pylephlebitis) of portal vein, such as nonspecific reactive hepatitis, for example granulomatus hepatitis NEC, such as autoimmune hepatitis. As demonstrated in Example 5, sCD206 is elevated in fibrotic or cirrhotic HCV patients compared to non-fibrotic HCV patients.
In yet another preferred embodiment, the liver disorder is specified as other diseases of liver, such as fatty liver NEC, chronic passive congestion of liver (cirrhosis and sclerosis of liver), for example central haemorrhagic necrosis of liver, such as infarction of liver, for example peliosis hepatitis (hepatic angiomatosis), such as hepatic veno-occlusive disease, for example portal hypertension, such as hepatorenal syndrome, for example other specified diseases of liver, including focal nodular hyperplasia of liver and hepatoptosis.
In yet another preferred embodiment, the liver disorder is classified as liver disorders in other diseases, such as cytomegaloviral, herpesviral or toxoplasma hepatitis, for example hepatosplenic schistosomiasis, such as portal hypertension in schistosomiasis, for example syphilitic liver disease, such as hepatic granulomas in berylliosis and sarcoidosis.
sCD206 may be used as a biomarker for the presence of infection. Infection may be caused by bacteria or virus or both.
sCD206 may be used as a biomarker for the presence and severity of pneumonia.
sCD206 may be used as a biomarker for the presence of sepsis. Sepsis is a caused by an overwhelming immune response to infections. The term sepsis is often used interchangeable with septicemia, an infection that gets worse very quickly and is often fatal. Bacterial infections are the most common cause of sepsis. However, sepsis can also be caused by other infections. In a more preferred embodiment, the sepsis is caused by a Gram-positive bacteria, such as Streptococcus pneumonia and Streptococcus pyogenes.
The present invention relates to the finding that sCD206 may be used as a biomarker for the presence of a fungal infection. Fungal infections may be caused by a variety of different fungal species.
In one embodiment, sCD206 may be used as a biomarker for the presence of a number of fungal associated diseases.
In one embodiment the fungal associated diseases are selected from the group consisting of: Candidal endocartis, Candical sepsis, Coccidioidomycosis, Acute pulmonary coccidioidomycosis, Chronic pulmonary coccidioidomycosis, Pulmonary coccidioidomycosis, Cutaneous coccidioidomycosis, Coccidioidomycosis meningitis, Disseminated coccidioidomycosis, Generalized coccidioidomycosis, Other forms of coccidioidomycosis, Histoplasmosis, Acute pulmonary histoplasmosis capsulati, Chronic pulmonary histoplasmosis capsulati, Pulmonary histoplasmosis capsulati, Disseminated histoplasmosis capsulati, Generalized histoplasmosis capsulati, Histoplasmosis capsulati, American histoplasmosis, Histoplasmosis duboisii, African histoplasmosis, Histoplasmosis, Blastomycosis, Acute pulmonary blastomycosis, Chronic pulmonary blastomycosis, Pulmonary blastomycosis, Cutaneous blastomycosis, Disseminated blastomycosis, Generalized blastomycosis, Other forms of blastomycosis, Paracoccidioidomycosis, Pulmonary paracoccidioidomycosis, Disseminated paracoccidioidomycosis, Generalized paracoccidioidomycosis, Other forms of paracoccidioidomycosis, Sporotrichosis, Pulmonary sporotrichosis, Lymphocutaneous sporotrichosis, Disseminated sporotrichosis, Generalized sporotrichosis, Other forms of sporotrichosis, Chromomycosis and phaeomycotic abscess, Cutaneous chromomycosis, Dermatitis verrucosa, Phaeomycotic brain abscess, Cerebral chromomycosis, Subcutaneous phaeomycotic abscess and cyst, Other forms of chromomycosis, Aspergillosis, Invasive pulmonary aspergillosis, Other pulmonary aspergillosis, Tonsillar aspergillosis, Disseminated aspergillosis, Generalized aspergillosis, Other forms of aspergillosis, Cryptococcosis, Pulmonary cryptococcosis, Cerebral cryptococcosis, Cryptococcal meningitis, Cryptococcosis meningocerebralis, Cutaneous cryptococcosis, Osseous cryptococcosis, Disseminated cryptococcosis, Generalized cryptococcosis, Other forms of cryptococcosis, Zygomycosis, Pulmonary mucormycosis, Rhinocerebral mucormycosis, Gastrointestinal mucormycosis, Cutaneous mucormycosis, Subcutaneous mucormycosis, Disseminated mucormycosis, Generalized mucormycosis, Mucormycosis unspecified, Other zygomycoses, Entomophthoromycosis, Zygomycosis unspecified, Phycomycosis NOS, Mycetoma, Eumycetoma, Madura foot mycotic, Maduromycosis, Actinomycetoma, Mycetoma unspecified, Madura foot NOS, Lobomycosis, Keloidal blastomycosis, Lobo disease, Rhinosporidiosis, Allescheriasis, Infection due to Pseudallescheria boydii, Geotrichosis, Geotrichum stomatitis, Penicillosis, Opportunistic mycoses, Other specified mycoses, and Adiaspiromycosis.
Sampling of CD206
In a preferred embodiment, the level of CD206 will be obtained from a biological sample, such as serum, for example plasma, such as whole blood, for example saliva, such as urine, for example lymph, such as a biopsy, for example semen, such as faeces, for example tears, such as sweat, for example milk, such as cerebrospinal fluid, for example ascites fluid, such as for example synovial fluid. Preferably the sample is blood, plasma or serum. More preferably the sample is plasma or serum.
Methods for Determining CD206
Point of Care test preferably relies on a lateral flow test based on an immunological principle. Lateral flow tests are also known as lateral flow immunochromatographic assays and are simple devices intended to detect the presence (or absence) of a target analyte in a sample. Often produced in a dipstick format, a lateral flow test is a form of immunoassay in which the test sample flows along a solid substrate, preferably via capillary action. After the sample is applied to the test it preferably encounters a coloured reagent which mixes with the sample and transits the substrate encountering lines or zones which have been pretreated with an antibody or antigen. Depending upon the analytes present in the sample the coloured reagent can become bound at the test line or zone. Semi-quantitative lateral flow tests can operate as either competitive or sandwich assays.
In a preferred embodiment, the sample is mixed with CD206 antibody-coated microparticles with a resulting change in the turbidity of the sample. The turbidity change may then be correlated with the amount of CD206 in the sample when compared with a reference sample.
In another preferred embodiment, the level of CD206 is detected by nephelometry where an antibody and the antigen are mixed in concentrations such that only small aggregates are formed. These aggregates will scatter light (usually a laser) passed through it rather than simply absorbing it. The fraction of scattered light is determined by collecting the light at an angle where it is measured and compared to the fraction of scattered light from known mixtures. Scattered light from the sample is determined by using a standard curve.
In another preferred embodiment, the sample moves from the application site where it, for example, is mixed with antibody-coated nanoparticles in lateral flow/diffusion through a (e.g. nitrocellulose-) membrane. At one point on the way another CD206 antibody is fixed in the membrane making the CD206-primary antibody complex to halt. The nano-particle (preferably colloidal gold/dyed latex) will give a visual line. In another embodiment, the sample is applied through a (e.g. nitrocellulose-) membrane coated with a primary CD206 antibody. The sample CD206 is then recognised and bound by the primary CD206 antibody. The immobilised CD206 on the membrane may then be recognised by (preferably colloidal gold/dyed latex) particles conjugated with another CD206 antibody, and the complex will develop a colour reaction, which intensity corresponds to the amount of CD206 in the sample.
For large-scale detection and more precise quantitative measurement of CD206 in a sample, several methods may be applied.
In another preferred embodiment, the level of CD206 is detected by radioimmunoassay (RIA). RIA is a very sensitive technique used to measure concentrations of antigens without the need to use a bioassay. To perform a radioimmunoassay, a known quantity of an antigen is made radioactive, frequently by labeling it with gamma-radioactive isotopes of iodine attached to tyrosine. This radio labeled antigen is then mixed with a known amount of antibody for that antigen, and as a result, the two chemically bind to one another. Then, a sample of serum from a patient containing an unknown quantity of that same antigen is added. This causes the unlabeled (or “cold”) antigen from the serum to compete with the radio labeled antigen for antibody binding sites. As the concentration of “cold” antigen is increased, more of it binds to the antibody, displacing the radio labeled variant, and reducing the ratio of antibody-bound radio labeled antigen to free radio labeled antigen. The bound antigens are then separated from the unbound ones, and the radioactivity of the free antigen remaining in the supernatant is measured. Using known standards, a binding curve can then be generated which allows the amount of antigen in the patient's serum to be derived. In this assay, the binding between antibody and antigen may be substituted by any protein-protein or protein-peptide interaction, such as ligand-receptor interaction, for example CD206-haemoglobin or CD206-haemoglobin/haptoglobin binding.
In a preferred embodiment, the level of CD206 is detected by enzyme-linked immunosorbent assay (ELISA). ELISA is a quantitative technique used to detect the presence of protein, or any other antigen, in a sample. In ELISA an unknown amount of antigen is affixed to a surface, and then a specific antibody is washed over the surface so that it can bind to the antigen. This antibody is linked to an enzyme, and in the final step a substance is added that the enzyme can convert to some detectable signal. Several types of ELISA exist:
Indirect ELISA
Sandwich ELISA
Competitive ELISA
Reverse ELISA
Other immuno-based assays may also be used to detect CD206 in a sample, such as chemiluminescent immunometric assays and Dissociation-Enhanced Lanthinide Immunoassays.
In a preferred embodiment, the level of CD206 is detected by chromatography-based methods, more specifically liquid chromatography. Therefore, in a more preferred embodiment, the level of CD206 is detected by affinity chromatography which is based on selective non-covalent interaction between an analyte and specific molecules. In another preferred embodiment, the level of CD206 is detected by ion exchange chromatography which uses ion exchange mechanisms to separate analytes. Ion exchange chromatography uses a charged stationary phase to separate charged compounds. In conventional methods the stationary phase is an ion exchange resin that carries charged functional groups which interact with oppositely charged groups of the compound to be retained.
In yet another preferred embodiment, the level of CD206 is detected by size exclusion chromatography (SEC) which is also known as gel permeation chromatography (GPC) or gel filtration chromatography. SEC is used to separate molecules according to their size (or more accurately according to their hydrodynamic diameter or hydrodynamic volume). Smaller molecules are able to enter the pores of the media and, therefore, take longer to elute, whereas larger molecules are excluded from the pores and elute faster.
In yet another preferred embodiment, the level of CD206 is detected by reversed-phase chromatography which is an elution procedure in which the mobile phase is significantly more polar than the stationary phase. Hence, polar compounds are eluted first while non-polar compounds are retained.
In a preferred embodiment, the level of CD206 is detected by electrophoresis. Electrophoresis utilizes the motion of dispersed particles relative to a fluid under the influence of an electric field. Particles then move with a speed according to their relative charge. More specifically, the following electrophoretic methods may be used for detection of CD206:
Sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE).
Rocket immunoelectrophoresis.
Affinity immunoelectrophoresis.
Isoelectric focusing.
In a preferred embodiment, the level of CD206 is detected by flow cytometry. In flow cytometry a beam of light of a single wavelength is directed onto a hydrodynamically-focused stream of fluid. A number of detectors (some fluorescent) are aimed at the point where the stream passes through the light beam: one in line with the light beam and several detectors perpendicular to it. Each suspended particle from 0.2 to 150 micrometers passing through the beam scatters the light in some way, and fluorescent chemicals found in the particle or attached to the particle may be excited into emitting light at a longer wavelength than the light source. This combination of scattered and fluorescent light is picked up by the detectors, and, by analysing fluctuations in brightness at each detector, it is then possible to derive various types of information about the physical and chemical structure of each individual particle.
In a preferred embodiment, the level of CD206 is detected by Luminex technology, which is based on a technique where microspheres are coated with reagents specific to capture a specific antigen from a sample.
In a preferred embodiment, the level of CD206 is detected by mass spectrometry (MS). MS is an analytical technique for the determination of the elemental composition of a sample or molecule. It is also used for elucidating the chemical structures of molecules, such as proteins and other chemical compounds. The MS principle consists of ionizing chemical compounds to generate charged molecules or molecule fragments and measurement of their mass-to-charge ratios.
Determination of Cut-Off Value
In order to evaluate the level of CD206 as measured by any of the methods mentioned herein above, the establishment of a cut-off value may be beneficial.
The cut-off level as herein defined may also be regarded a control level to which the sCD206 level of a sample can be compared.
In one embodiment a cut-off value may be determined by measuring the level of CD206 in a given healthy subject several times over an extended period of time. In that way it is possible to determine the average normal level of CD206 in said subject.
In another embodiment a cut-off value may be determined for a given sick subject by measuring the level of CD206 in a sample from said given subject, provided that said sample has been taken prior to the onset of disease. The level measured in the sample taken when the subject was healthy is then used as the cut-off value for when the subject may be categorized as being healthy again after the disease has been treated.
In yet another embodiment a cut-off value may be determined by a mathematical value based on an average of measurement made in a large group of subjects. Said subjects may be grouped according to their age, gender, race and population group. Preferably said subjects are healthy subjects, i.e. without any known medical condition.
The skilled person will know that in biological systems some variation around an average should be expected and will still be accepted as a normal value. In one embodiment a value will be accepted as normal if it does not deviate significantly from the average value determined to be the cut-off value.
A low level of CD206 is indicative of a subject being healthy. Accordingly it is expected that the measured CD206 level in a subject suffering from a disorder and/or disease should fall after the subject has received treatment for the disorder and/or disease. Treatment may continue until the CD206 level is below the determined cut-off value. Once the CD206 level is below the determined cut-off value the subject will be evaluated as being healthy again.
A cut-off value according is preferably a cut-off value where the biomarker is both sensitive and specific. It is desired that the correlation between sensitivity and specificity is maximized.
One way of determining whether a given cut-off value is sensitive and specific is by plotting the data obtained in a Receiver Operating Characteristic (ROC) curve (see
Said curve is created by plotting the fraction of true positives out of the positives (TPR=true positive rate) vs. the fraction of false positives out of the negatives (FPR=false positive rate), at various threshold settings. TPR is also known as sensitivity, and FPR is one minus the specificity or true negative rate.
An ideal cut-off value would discriminate faultlessly between patient with or without a disease or disorder, such as with and without liver disorder and/or sepsis. Where the given cut-off value identifies only the true positives, it will have a sensitivity of 100% or 1.00. Where the test identifies only the true negatives, it will have a specificity of 100% or 1.00.
When determining where to set the cut-off value, the skilled person would have to make a balance between the need to identify all the patients suffering from the disease or disorder, such as from sepsis and/or a liver disorder, from the patients not suffering from said diseases. The effect of raising or lowering the cut-off value will have well-defined and predictable impact on the sensitivity and specificity. The skilled person will know that there is some overlap between “disease absent” and “disease present” patient populations.
The level of sCD206 may be measured on a variety of samples as described herein above.
A cutoff level may be an average of measurement made in a large group of healthy subjects, optionally grouped according to age, gender, race, or population group. In absolute numbers, a general cutoff level may be at least 0.25 mg/L sCD206, such as at least 0.3 mg/L, for example at least 0.35 mg/L, such as at least 0.4 mg/L, for example at least 0.43 mg/L, such as at least 0.5 mg/L. These absolute values have been determined using the ELISA-assay described in the examples. Using this assay, the level of sMR in NFKK reference-serum X has been found to be 0.243 mg/L (SD=0.030). NFKK-reference serum X, which is commercially available from NOBIDA, Nordic Reference Interval Project Bio-bank and Database (Scand J Clin Lab Invest. 2004; 64(4):431-8. Nordic Reference Interval Project Bio-bank and Database (NOBIDA): a source for future estimation and retrospective evaluation of reference intervals. Rustad P, Simonsson P, Felding P, Pedersen M.).
It is conceivable that other analytical methods will yield different concentrations in absolute numbers. The cutoff values provided in the present application can be converted to cutoff values for other analytical methods. If the concentration of sMR in NFKK-X using a different analytical method is found to be “C mg/L”, then all reported cut-off values for sMR using the methods herein described should be multiplied by the constant “C/0.243”.
In general the distinction between healthy and unhealthy individuals may involve comparing a value to a cutoff value, wherein said cutoff level is at least 1.5×a median level of sCD206 for healthy individuals, such as 1.75, for example 2.0, such as 2.25, for example 2.5, such as 2.75, for example 3.0, such as 3.25, for example 3.5.
In one embodiment the cut-off value when determining whether or not a patient is suffering from sepsis or not is 0.7 mg/L of sCD206, for example the cut-off value is 0.68 mg/L of sCD206, for example the cut-off value is 0.65 mg/L of sCD206, for example the cut-off value is 0.63 mg/L of sCD206, for example the cut-off value is 0.61 mg/L of sCD206.
In another embodiment the cut-off value when determining whether or not a patient is suffering from sepsis or not is 0.58 mg/L of sCD206, for example the cut-off value is 0.56 mg/L of sCD206, for example the cut-off value is 0.54 mg/L of sCD206, for example the cut-off value is 0.52 mg/L of sCD206, for example the cut-off value is 0.5 mg/L of sCD206, for example the cut-off value is 0.48 mg/L of sCD206, for example the cut-off value is 0.45 mg/l of sCD206, for example the cut-off value is 0.43 mg/L of sCD206.
In another embodiment the cut-off value when determining whether or not a patient is suffering from sepsis or not is at least 0.4 mg/L, for example at least 0.43 mg/L, such as at least 0.5 mg/L, for example at least 0.6 mg/L.
In one embodiment, the cut-off value when determining the likelihood of survival of a patient admitted to the ICU is 0.4 mg/L of sCD206, for example the cut-off value is 0.45 mg/L of sCD206, for example the cut-off value is 0.5 mg/L of sCD206, for example the cut-off value is 0.55 mg/L of sCD206, for example the cut-off value is 0.6 mg/L of sCD206, for example the cut-off value is 0.65 mg/L of sCD206, for example the cut-off value is 0.7 mg/L of sCD206, for example the cut-off value is 0.75 mg/L of sCD206, for example the cut-off value is 0.8 mg/L of sCD206, for example the cut-off value is 0.85 mg/L of sCD206, for example the cut-off value is 0.9 mg/L of sCD206, for example the cut-off value is 0.95 mg/L of sCD206, for example the cut-off value is 1.0 mg/L of sCD206. These cut-off values may also be used to discriminate between survivors and non-survivors among pneumonia patients.
In another embodiment the cut-off value when determining the likelihood of survival of a patient admitted to the ICU is at least 0.4 mg/L, for example at least 0.5 mg/L, such as at least 0.6 mg/L, for example at least 0.7 mg/L, such as at least 0.8 mg/L, for example at least 0.9 mg/L, such as at least 1.0 mg/L.
In one embodiment the cut-off value may be related to either the 97.5th percentile or the median value of a group of healthy individuals. The advantage of not using absolute values is that absolute values may vary depending on the method used to determine soluble CD206.
In one embodiment the cut-off value is related to the percentile groups described herein below and is defined as a value multiplied by (herein below “multiplied by” is denoted with an x) the value determined for the 97.5th percentile of healthy individuals. In such an embodiment the cut-off value when determining whether or not a patient is suffering from sepsis is 1.3×the 97.5th percentile value of healthy individuals, for example the cut-off value is 1.35×the 97.5th percentile value of healthy individuals, for example the cut-off value is 1.4×the 97.5th percentile value of healthy individuals, for example the cut-off value is 1.45×the 97.5th percentile value of healthy individuals, for example the cut-off value is 1.5×the 97.5th percentile value of healthy individuals.
In another embodiment the cut-off value when determining the likelihood of survival of a patient admitted to the ICU is 0.9×97.5th percentile value of healthy individuals, for example the cut-off value is 1.0×97.5th percentile value of healthy individuals, for example the cut-off value is 1.1×97.5th percentile value of healthy individuals, for example the cut-off value is 1.2×97.5th percentile value of healthy individuals, for example the cut-off value is 1.3×97.5th percentile value of healthy individuals, for example the cut-off value is 1.4×97.5th percentile value of healthy individuals, for example the cut-off value is 1.5×97.5th percentile value of healthy individuals, for example the cut-off value is 1.6×97.5th percentile value of healthy individuals, for example the cut-off value is 1.7×97.5th percentile value of healthy individuals, for example the cut-off value is 1.8×97.5th percentile value of healthy individuals, for example the cut-off value is 1.9×97.5th percentile value of healthy individuals, for example the cut-off value is 2.0×97.5th percentile value of healthy individuals, for example the cut-off value is 2.1×97.5th percentile value of healthy individuals, for example the cut-off value is 2.2×97.5th percentile value of healthy individuals, for example the cut-off value is 2.3×97.5th percentile value of healthy individuals.
In one embodiment the cut-off value is related to the median value determined for healthy individuals and is defined as a value multiplied by (herein below “multiplied by” is denoted with an x) the median value determined for healthy individuals.
In such an embodiment the cut-off value when determining whether or not a patient is suffering from sepsis is 2.0×the median value of healthy individuals, for example the cut-off value is 2.05×the median value for healthy individuals, for example the cut-off value is 2.1×the median value of healthy individuals, for example the cut-off value is 2.15×the median value of healthy individuals, for example the cut-off value is 2.2×the median value of healthy individuals, for example the cut-off value is 2.25×the median value for healthy individuals, for example the cut-off value is 2.3×the median value for healthy individuals.
In another embodiment the cut-off value when determining the likelihood of survival of a patient admitted to the ICU is 1.40×the median value of healthy individuals, for example the cut-off value is 1.50×the median value for healthy individuals, for example the cut-off value is 1.60×the median value for healthy individuals, for example the cut-off value is 1.70×the median value for healthy individuals, for example the cut-off value is 1.80×the median value for healthy individuals, for example the cut-off value is 1.90×the median value for healthy individuals, for example the cut-off value is 2.00×the median value for healthy individuals, for example the cut-off value is 2.10×the median value for healthy individuals, for example the cut-off value is 2.20×the median value for healthy individuals, for example the cut-off value is 2.30×the median value for healthy individuals, for example the cut-off value is 2.40×the median value for healthy individuals, for example the cut-off value is 2.50×the median value for healthy individuals, for example the cut-off value is 2.60×the median value for healthy individuals, for example the cut-off value is 2.70×the median value for healthy individuals, for example the cut-off value is 2.80×the median value for healthy individuals, for example the cut-off value is 2.90×the median value for healthy individuals, for example the cut-off value is 3.00×the median value for healthy individuals, for example the cut-off value is 3.10×the median value for healthy individuals, for example the cut-off value is 3.20×the median value for healthy individuals, for example the cut-off value is 3.30×the median value for healthy individuals, for example the cut-off value is 3.40×the median value for healthy individuals, for example the cut-off value is 3.50×the median value for healthy individuals, for example the cut-off value is 3.60×the median value for healthy individuals.
Alternatively the average value for healthy individuals may be used instead of the median value.
Percentile Groups
In another embodiment percentiles of sCD206 value are determined in a larger population over an extended period of time. The level of sCD206 found in a larger population can then be divided into percentiles. E.g. the 20th percentile is the value (or score) below which 20 percent of the observations are found. The percentiles can be used to determine a reference level of sCD206 (percentiles from e.g. 0-33%) and to determine “high level” of sCD206 (e.g. 90th percentile or lower as described herein below).
Therefore, in one embodiment a high level of sCD206 comprises a value higher than the 60th percentile, for example higher than the 65th percentile, such as higher than the 67th percentile, for example higher than the 70th percentile, such as higher than the 75th percentile, for example higher than the 80th percentile, such as higher than the 85th percentile, for example higher than the 90th percentile, such as higher than the 95th percentile, for example higher than the 97th percentile.
A high value may also be determined with relatively to a percentile. According to such methods, a high level of sCD206 comprises a value higher than 0.9×97.5th percentile, such as higher than 1.0×97.5th percentile, for example 1.1×97.5th percentile, such as 1.2×97.5th percentile, for example 1.3×97.5th percentile, such as 1.4×97.5th percentile, for example 1.5×97.5th percentile, such as 1.6×97.5th percentile, for example 1.7×97.5th percentile, such as 1.8×97.5th percentile, for example 1.9×97.5th percentile, such as 2.0×97.5th percentile, for example 2.1×97.5th percentile, such as 2.2×97.5th percentile, for example 2.3×97.5th percentile, such as 2.4×97.5th percentile, for example 2.5×97.5th percentile.
Percentiles and percentiles multiplied by a factor may also be regarded as cutoff values.
In another preferred embodiment, said percentiles are determined for a subset of individuals, said individuals having the same gender or race, or belonging to a group based on age, BMI, smoking habit, occupation, physical inactivity, hip circumference, waist circumference, systolic and/or diastolic blood pressure, alcohol consumption, a combination of any subset of these, or other risk factor. In a more preferred embodiment, said percentiles are determined for a subset of individuals, said individuals having the same gender and belonging to the same age interval, said interval being 5 years, 10 years, 15 years, 20 years or said interval being 25 years.
Said percentiles are based on multiple factors, among those CD206 levels, gender and age. When classified into 10-year age intervals, it is possible to derive absolute cut-off values, above which an individual is at risk of contracting said disorders.
The risk of suffering from liver disease or sepsis among said individuals may be determined from which percentile an individual belongs to. The risk of suffering from said disease may be calculated by comparing to a reference group.
Divided into percentiles based on CD206 levels, age and gender, a preferred reference group is the group with the lowest risk of suffering from a disease or disorder.
Additional Assessments
Several biochemical parameters are known to be associated with liver disease or sepsis. A normal procedure in the clinical laboratory may be to confirm positive and negative findings obtained by assessing one biochemical marker (of for example a disorder) by assessing the presence of other, independent biochemical markers with similar clinical indications.
In another preferred embodiment the use of CD206 as a biomarker for said diseases may be supported by assessing measures such as Apache-II score, Model for End-Stage Liver Disease (MELD score), Sequential Organ Failure Assessment score (SOFA score), or the Ostrosky-Zeichner prediction rule, or other, related biochemical markers obtained from a group of, but not limited to, Creatinine, Lactate, blood glucose, CRP, Fibrinogen, alpha1-antitrypsin, ALAT, ASAT, gammaGT, alkaline phosphatise, coagulation factors, Thrombocyte counts, lactate dehydrogenase, homocysteine, and bilirubine.
Treatment of Subjects with Increased CD206
One great asset of a biomarker is that it paves the way for an individual to take actions aimed at treating a certain disease at an early time point before overt signs of said disease develop. Said actions may include (in the ICU) an intensified monitoring, antibiotic treatment, organ-support (pressors, ventilation, dialysis) and in the case of liver disease in the search for viral disease, and altered daily routines, such as increased physical activity and a healthier diet, such as reduced consumption of fat, sugar and alcohol. Moreover, a number of compounds are undergoing clinical trials to investigate their effect on lowering low-grade systemic inflammation or subclinical inflammation. Examples of such drugs include but are not limited to:
Coffee, Glucose-dependent insulinotropic polypeptide (GIP), nicotinic acid, pioglitazone, ramipril, curcumin, fructanes, acarbose, vitamin D, butyrate, thiazolidinediones, mesalazine, salsalate, advair, flovent, atenolol, ramipril, metformin Glucagon-like peptide-1 agonists, and resveratrol.
Resveratrol (3,5,4′-trihydroxystilbene) is a polyphenolic phytoalexin. It is a stilbenoid, a derivate of stilbene, and is produced in plants with the help of the enzyme stilbene synthase. It exists as two structural isomers: cis-(Z) and trans-(E), with the trans-isomer shown in the top image. The trans-form can undergo isomerisation to the cis-form when heated or exposed to ultraviolet irradiation. Resveratrol is a polyphenol found in red wine.
The level of CD206 may be measured several times during treatment in order to evaluate the treatment regime. The level of CD206 will then inform the physician of whether or not a certain treatment is useful and providing an improvement in the general health of the subject or whether the treatment should be altered. If the level of sCD206 increases during treatment the physician will know that the treatment eventually should be stopped. A new treatment with another pharmaceutical compound may be administered subsequently.
Alterations in treatment could in one embodiment be a change in dosage of a given pharmaceutical compound or it may be a partial or complete change in medicament.
SEQ ID No. 1, CD206, Uniprot acc no. P22897
Signal peptide: 1-19
Extracellular domain: 19-1389
Transmembrane: 1390-1410
Cytoplasmic: 1411-1456
Materials and Methods
Western Blotting
Serum (diluted 1:10) and cell lysate controls (human monocyte derived macrophages 7.8 μg protein/μl and T24 human bladder carcinoma cell line 6.7 μg/μl) was analyzed by Sodium dodecyl sulfate-polyacrylamide gel electrophoresis (4-12% Novex® NuPAGE® SDS-page Gel System). Proteins were blotted onto PDVF membranes, blocked for 1 h and incubated o/n at 4° C. with mouse anti MR (Acris Antibodies, Clone 7-450, catalogue number AM05589PU-S) based on the protocol provided by Novex®. The membrane was subsequently incubated for 1 h at RT with goat anti-mouse-HRP (DAKO P0447, diluted 1:4000) and developed using enhanced chemiluminescence.
Affinity Purification of sMR from Human Plasma
MR was then purified from a pool of human EDTA-stabilized plasma by affinity chromatography. For mannose affinity chromatography, plasma was diluted 1:1 with 60 mM Tris pH 7.7, 100 mM NaCl, 20 mM Calcium (Buffer A), centrifuged at 10,000 rpm at RT for 30 min, and the supernatant filtered twice (Millipore Membrane filters 3.0 μM cat no. SSWP04700 and 0.8 μM cat no. AAWP04700) before loading on to a 5 mL Mannan-agarose column (Sigma-Aldrich cat no. MFCD00213010). The column had been initially washed in 60 mM Tris pH 7.7, 100 mM NaCl and 60 mM Tris pH 7.7, 100 mM NaCl, 20 mM Calcium, equilibrated with 60 mM Tris pH 7.7, 100 mM NaCl, 200 mM Mannose, 20 mM EDTA, and hence pre-equilibrated with sixty mL 60 mM Tris pH 7.7, 100 mM NaCl, 20 mM Calcium. After loading of the plasma, the column was washed with fifty mL 60 mM Tris pH 7.7, 100 mM NaCl, 20 mM Calcium, and hence, the bound protein was eluted with 60 mM Tris pH 7.7, 100 mM NaCl, 20 mM EDTA and collected in 1 mL fractions. Fractions with the highest concentrations of MR (as determined by ELISA) were pooled, dialyzed against 5 mM Tris pH 7.7, 10 mM NaCl for 24 h at 4° C., and concentrated on Amicon centrifugal filter device (MWCO 50,000, 4,000 rpm, Millepore). For antibody affinity chromatography 1 mg of anti-MR antibody was conjugated on a 1 ml HiTrap NHS-activated column (Product no: 17-0716-01, GE Healthcare, Brøndby, Denmark) according to manufacturer's instructions. Briefly, 1 mg of anti-MR antibody (catalog No: AM05589PU-N, Acris Antibodies GmbH, Herford, Germany) was dialyzed against 0.2 M NaHCO3, 0.5 M NaCl, pH 8.3 and concentrated to 1 mg/ml. The antibody coupling was performed in this buffer for 1 h at 25° C. Deactivation of excess active groups and washing out of uncoupled ligand was done by alternating washes with 2×6 ml 0.5 M ethanolamine, 0.5 M NaCl, pH 8.3 and 0.1 M acetate, 0.5 M NaCl, pH 4 and finally equilibrating the column by washing with 10 ml PBS. Plasma was prepared by centrifugation and sterile filtration. Purifications were made on the antibody affinity column with a flow rate of approximately 1 ml/min. 2 ml of plasma was loaded on the column. The column was washed with 5 ml PBS and eluted in 1 ml fractions with 100 mM Citrate pH 3 into tubes containing 100 μl 1 M Tris pH 8. The purification was repeated with additionally 2×2 ml plasma. Fractions containing MR (as determined by ELISA) were pooled and concentrated on Amicon centrifugal filter device (MWCO 50,000, 4,000 rpm, Millepore).
The purified MR was subjected to 4-12% SDS-PAGE and the gel stained by Coomassie Brilliant Blue. Bands of approximately 170 kDa were cut from the gel and subjected to protein identification by mass spectrometry MALDI MS/MS at Alphalyse A/S (Odense, Denmark).
Briefly, reduced and alkylated protein samples were digested with trypsin and peptides purified on a ZipTip micropurification column before they were analyzed on a Bruker Autoflex Speed MALDI TOF/TOF instrument. Spectra were combined and used for protein database searching using Mascot software (MS/MS ion search, 1 miscleavage, Peptide Tolerance: 60 ppm, Mascot version 2.2.03). Furthermore, data was searched against NCBI and NRDB protein databases and also searched against specific Macrophage Mannose Receptor 1 precursor sequence.
Enzyme Linked Immuno-Sorbent Assay (ELISA) for sMR
Polyclonal Anti-human MMR Antibody (0.2 mg/ml R&D systems, cataloguenumber AF2534 diluted 1:225 in 20 mM Carbonat-bicarbonatbuffer pH 9.6 to 0.7 mg/ml) 100 μl was coated onto microtitre wells (Nunc Maxisorp) and incubated at 4° C. for >17 h. The wells were washed three times in PBS, and subsequently 100 μl of sample (diluted 1:50 in PBS-albumin (10 mM, 0.5 M NaCl, 0.1% (V/V) Tween20, 0.2% (W/V) bovine serum albumin (Sigma no. A-4503), pH 7.2) was added and incubated for 1 h. The wells were washed, and 100 μl of inhouse biotinylated monoclonal anti MR (Acris Antibodies, Clone 7-450, catalogue number AM05589PU-S) diluted to 0.1 mg/l in PBS/albumin was added and incubated for one h. After washing, 100 μl of avidin-lysosym mixture (12 ml POD 10/400 ph 7.4+120 μl Lysosym (Sigma Cat. Nr. 6876 dilution 20 mg/l)+12μ Avidin (Dako Cat. Nr. P 0364)) was added and incubated for one h. The wells were washed and 100 μl TMB One (KEM-EN-TEC, Cat. Nr. 4380 A) was added. After incubating for 30 min 50 μl 1 M phosphorous acid was added and the plates were read at 450/620 nm in a microtitre plate reader (Thermo, Multiscan Acsent)
Validation of ELISA
To study linearity, twofold dilutions (1:5-1:10,240) of serum from a patient with high sMR was made and samples analyzed in quadruplicates. Estimates of within run imprecision was obtained by analyzing two samples 40 and 34 times respectively in the same run. Total variation was determined by control samples included in each run (n=32). No reference method or reference material was accessible and instead, recombinant Human MR (R&D Systems Catalog Number: 2534MR) was used for calibration. Calibrators with concentrations ranging from 1 to 256 μg/l were included on each plate. The level of sMR was also determined in serum based reference standards obtained from the Danish Institute for External Quality Assurance for Laboratories in Health Care reference sera (DEKS) (REF 1). Recovery was estimated by adding 100 μl of 400 μg/l recombinant MR diluted in PBS to 10 patient samples (diluted 1:10 in PBS). Furthermore paired serum, EDTA-plasma, and heparin-plasma (Terumo Cooporation, Japan) was collected from 30 patients and sCD163 determined in duplicates. The limit of detection (LOD) was determined by the mean of the zero standard plus 5 times the SD of the zero standard. The intra-assay variation of a serum sample diluted to 1.31 μg/L and measured in quadruplicate was 11.2% CV with a 4.2% bias.
To estimate the stability of sMR, 3 pools of fresh plasma were prepared, and aliquots of 50 μl were taken from each pool and kept at RT, +6° C., −20° C. and −80° C. Samples were analyzed during a period of 270 days and to reduce influence of day-to-day variation, 4 control samples included in each run were used to calibrate the results. Seven aliquots were also taken from each of the three pools of plasma and frozen (−80° C.) and thawed (+20° C.) one to seven times, frozen at −80° C. and subsequently analyzed in the same run.
Blood Samples
Serum samples from 240 healthy Scandinavians were obtained from the NOBIDA biobank, established as part of the Nordic Reference Interval Project (NORIP) (REF2). Values of common biochemical analytes was obtainable on 219 of the samples from the NORIP project and used for studies of covariation with sMR. These values were measured by the participating laboratories and harmonized from measured reference samples. All measurements were performed on thawed serum. Data on age, sex, height, weight, alcohol consumption (0, 1−21, >21 units/wk), medication, and physical activity (strenuous exercise within last week) was also obtained from the NORIP project.
EDTA-stabilized surplus plasma samples from 218 patients at Aarhus University Hospital were collected after routine testing at the Department of Clinical Biochemistry. These samples were collected over a period of two months and frozen at −80° until they were analyzed. Clinical data and routine lab results were obtained from the medical files of the patients. Soluble CD163 was measured essentially as previously described (REF3). Furthermore, 51 patients with acute alcoholic hepatitis were prospectively enrolled at the department of Gastroenterology and Hepatology, Aarhus Denmark. Peripheral venous blood samples were collected upon diagnosis and before initiation of treatment. After centrifugation, plasma was stored at −80° C. for up to 20 months until analysis. Fifty samples were available for sMR measurements.
Ethics
The local Ethical Committee of Central Denmark Region approved the study of patients with hepatitis (M-20080203) and informed consent was obtained from all participants. According to Danish law, the collection of surplus patient samples did not need to be approved by the Regional Scientific Ethical Committee. The reviewing of patient records was approved the Danish National Board of Health (Journal number 7-604-04-2/300) and by the Danish Data Protection agency (Journal number 2007-58-0010).
Statistical Analyses
Probability plots showed that all data were normally distributed either as raw data or after log transformation. The following data was log transformed in the reference group: BMI, Cholesterol, HDL Cholesterol, LDL Cholesterol, Triglycerides, Glucose, Uric acid, ALT, AST, GGT, ALP, Bilirubin. The following data was log transformed in the patient group: ALT, ALP, LDH, CRP, sCD163, Albumin, Hemoglobin, Leukocytes, Lymfocytes, Monocytes, Neutrofils, Imature granulocytes. Differences within unpaired data were evaluated with a two-sided t-test and paired data were evaluated with a paired student's t-test. The 95% reference interval was determined by calculating mean+/−1,96*σ. P-values less than 0.05 were considered statistically significant. Statistical analysis was performed using GraphPad Prism 4 and Analyse-it for Microsoft Excel.
Results
The Mannose Receptor is Present as a Soluble Protein in Human Plasma
We examined human sera and cell-extracts by SDS-gel electrophoresis followed by immunoblotting and identified a soluble form of MR in serum (
Establishment and Validation of an ELISA for Measurement of sMR in Human Serum
We explored commercially available antibodies against sMR and established and optimized an ELISA using a polyclonal coating-antibody and a monoclonal biotinylated secondary antibody. The assay was linear in serum dilutions ranging from 1:20-1:2560 (slope 1.003 (95% CI 0.978-1.027), intercept 0.171 (−1.35-1.69), R2=0.99 covering a concentration range of 1.3-168 μg/l (
In pools of EDTA-plasma sMR was stable for more than two days at RT, for 2 weeks at 6° C., and for at least 9 months at −20° C. and −80° C. respectively (
Serum Concentration of sMR in Healthy Individuals
We measured sMR in sera from 219 healthy Scandinavian individuals. Two samples with very high concentrations (2.6 and 4.8 mg/l respectively) were considered to be outliers and excluded from further analyses. The remaining 217 samples had levels between 0.06-0.53 mg/l and showed a Gaussian distribution (evaluated by histogram and QQ-plot). The mean concentration (n=217) was 0.28 mg/l (SD 0.085) and a parametric 95% reference interval was established to 0.10 mg/l (90% CI 0.08-0.11) to 0.43 mg/l (90% CI 0.41-0.45). There was a weak but significant, positive correlation between sMR and age (R2=0.13, p<0.0001). When stratifying for age under/over 50 years, the reference intervals were significantly different, <50 years: 0.09-0.37 mg/l 50 years: 0.12-0.46 mg/l (
Serum Concentration of sMR in Hospitalized Patients
In order to get a first impression as to the concentrations of sMR in relation to pathological conditions we examined serum from 218 unselected hospitalized patients. Of these, 110 (50.5%) had concentrations above the upper reference range (>0.43 mg/l). There was a significant correlation between sMR and biochemical markers of liver disease and inflammation (Table 2). The correlation to the general inflammatory marker CRP was moderate (R2=0.11, P<0.0001), and it seemed that patients with increased sMR constituted a fraction of patients with increased CRP (
REF1. Danish Institute for External Quality Assurance for Laboratories in Health Care, DEKS. Accessed at http://www.deks.dk/index.html
Oct. 1, 2012.
REF2. Nordic Reference Interval Project. Accessed at http://pweb.furst.no/norip/
Oct. 1, 2012.
REF3. Møller H J, Hald K, Moestrup S K. Characterization of an enzyme-linked immunosorbent assay for soluble CD163. Scand J Clin Lab Invest 2002; 62:293-299.
Materials and Methods
Study design & patients
Prospective observational study carried out at one mixed Intensive Care Unit (ICU) and one neurosurgical ICU at Aarhus University Hospital and at one mixed ICU at Randers regional Hospital, Denmark. Informed consent was obtained from the subjects if possible, alternatively from the closest relative and the patients' general practitioner prior to the study. The study was approved by the local ethics committee. 30 ICU patients were included in the study between January 2010 and January 2012. 15 patients with severe sepsis or septic shock by Bones's definition [Ref 4] later modified by Levy and collegeaus [Ref 5] were included. The diagnosis of sepsis was applied when the patient as a response to a documented or clinical suspected infection fulfilled 2 or more of the following systemic inflammatory response syndrome (SIRS) criteria: 1) temperature above 38° C. or below 36° C., 2) heart rate above 90 beats per minute, 3) respiratory rate above 20 breaths per minute or PaCO2 below 32 mmHg, and 4) white blood cell count above 12,000 cells/μl or below 4,000 cells/μl, or more than 10% immature forms. The term severe sepsis was used when sepsis was associated with organ dysfunction, hypoperfusion, or hypotension. Criteria for organ dysfunction was obtained from Marshall and colleagues [Ref 6]. Septic shock was defined as severe sepsis with hypotension (systolic blood pressure below 90 mmHg) despite adequate fluid resucitation. In addition 15 severely ill non-septic patients were included. Severely ill was defined as an Acute Physiology And Chronic Health Evaluation (APACHE II) score above 13 at ICU admission. 15 healthy volunteers matched on age and gender served as a control group.
Exclusion criteria were age below 18, pregnant or lactating, hematocrit below 0.30, immunemodulating therapy except for low dose steroid, chemotherapy or radiationtherapy within one year of inclusion, lifethreathning bleeding, inclusion in medical intervention research, brain-dead at time of inclusion, expected survival shorter than 4 days or expected ICU admission shorter than 4 days, and lack of informed consent or withdrawal of informed consent.
The sequential organ failure assessment (SOFA) score [Ref 7] was calculated daily to determine the extent of organ failure. The SOFA score is based on scores from six organ systems (cardiovascular, coagulation, hepatic, neurological, renal, and respiratory) and gives an estimate of organ dysfunction.
The acute physiology and chronic health evaluation II (APACHE II) score [Ref 8] was calculated on ICU admission. The APACHE II score is based on 12 routine physiologic measurements, age, and previous health status. The score gives an estimate of severity of disease and a predicted death rate.
Blood Sampling
Blood samples were drawn from an arterial cannula on day 1, 2, 3, and 4 of ICU admission. The samples were drawn between 8 am and 12 am to avoid circadian variation in the measured parameters. Routine blood samples were analysed immediately by the local biochemical department.
Results
Patient Characteristics
Important patient characteristics at baseline are shown in tables 3 and 4. All three groups were similar with regard to age, sex, alcohol consumption, blood sample time, and temperature.
The septic group had higher respiratory rate (RR) and heart rate (HR) than the non-septic group and control. The latter two did not differ with regard to RR and HR.
There was no difference between the Septic and non-septic group with regards to APACHE II score, SOFA score at ICU admission, and white blood cell (WBC) count. As expected these variables were found to be lower in the control group. Mean arterial pressure (MAP) was lower in the septic group compared to controls and the non-septic group, which again had lower MAP than controls.
Patients in the septic group smoked as much as patients in the non-septic group, but more than the healthy controls. There was no difference between non-septic patients and healthy controls.
The septic and non-septic groups were similar with regards to PaCO2, type of ventilation, and need of dialysis. The septic group was more likely to receive inotropic agents, antibiotics, glucocorticoids, and to be on a euglycemic clamp, than the non-septic group
sCD206 in Septic, Severely Ill Non-Septic ICU Patients, and Healthy Controls
At ICU admission, levels of sCD206 were significantly higher in patients with severe sepsis and septic shock compared to severely ill non-septic patients and healthy controls (p<0.001 for all comparison). Levels of sCD206 were higher in the non-septic patients compared to controls (p=0.002). During the four-day observation period, levels of sCD206 were significantly higher in the septic patients compared with the severely ill non-septic patients (p<0.001 for both comparisons) (
To examine if the monocyte expression of CD163 and levels of sCD163 and sMR could be used to discriminate between septic patients and non-septic patients, we performed AUROC curve analysis. At ICU admission, sMR had the highest AUROC (1; 95% CI 1 to 1), followed by sCD163 (0.95; 95% CI 0.88 to 1) and monocyte-bound CD163 expression (0.75; 95% CI 0.58 to 0.91) (
sMR at a cut-off value of 0.61 mg/ml were able to discriminate between septic and non-septic patients with 100% sensitivity and 100% specificity. sCD163 at a cut-off value of 1.74 mg/ml had 93% sensitivity and 93% specificity. CD163 at a MFI cut-off value of 646.5 had 67% sensitivity and 80% specificity. CRP at a cut-off value of 91.8 mg/l had 80% sensitivity and 86% specificity.
At ICU admission, sCD206 (p=0.001) was higher in in-hospital non-survivors than survivors (
Streptococcus pneumoniae (S. pneumoniae) is one of the most frequent causative agents of death from infections in both Europe and the US. It is estimated that 1.6 million people world-wide die of pneumococcal disease every year. When S. pneumonia is cultured from blood or other sterile sites, the infection is defined as invasive pneumococcal disease (IPD), which has a mortality of 10-25% even when the correct antibiotic treatment is administered.
Materials and Methods
The patients were enrolled from 5 university hospitals in Denmark between October 1999 and June 2001. Results from the study have been published previously [Møller et al (2006). Crit Care Med 34(10):2561-6; Kronborg et al (2002). J Infect Dis 15; 185(10):1517-20; Kronborg et al (2002). Scand J Infect Dis 34(5):323-6; Wittenhagen et al (2004). Clin Microbiol Infect. 2004 May; 10(5):409-15; Kronborg G (2004). Ugeskr Laeger 24; 166(22):2132]. The present example is based on measurements of the soluble form of the mannose receptor in human serum.
Study Design and Patients
The initial inclusion criteria were adults (>17 years old) with fever (>38° C.) or infection suspected by the clinical presentation of the patient. If blood cultures were positive for S. pneumoniae within 12-36 hours, then blood samples were drawn within the next 24 hours for later analysis of macrophage biomarkers. Serum was stored at −20° C. until biochemical analyses were performed.
Biochemical Analyses
Serum sMR was analyzed in duplicate samples of frozen serum as described in example 1. CD163 and CRP were measured as described in a previous publication [Møller et al 2006 op cit].
Ethics
The study was approved by the local ethical committees.
Statistics
sMR values were normally distributed after log-transformation. sCD163 was normally distributed without transformation. CRP values did not follow a normal distribution neither with nor without log-transformation.
Spearman's test was used for correlation analysis of non-parametric data, and
Pearson's correlation analysis was used for parametric data.
Students T-test was used for analysis of between groups difference.
Receiver operator characteristic analyses (ROC curves) were applied for analysis of the prognostic performance of the biomarkers.
Results
In total, 141 patients with culture results positive for S. pneumoniae were included. Serum was accessible for sCD163 analysis from 133 of the patients, but corresponding serum samples for sMR analysis were only available from 128 patients. The median age of the 133 patients was 66 years, with a range of 23-99 yrs. 95 patients were under 75 years of age (48 men and 47 women with median ages of 58 and 62 years, respectively). 11 men and 27 women were 75 years or above (median age 84 and 83 years, respectively).
Pneumonia was the most common focus on infection (n=110). Twenty-three patients died in the hospital (case fatality rate, 17%). An underlying chronic illness was present in 65% of the patients. All patients received adequate antibiotic treatment (e.g., penicillin or cephalosporin) within a few hours of admission and before the result of the positive blood culture was available.
Correlations between sMR serum concentrations and sCD163, and routine biochemical markers are shown in table 6.
The median sMR concentration in the entire group of patients (n=128) was 0.77 mg/L (CI: 0.70-0.90 mg/L), which is significantly above the upper reference range for sMR in healthy individuals (0.1-0.43 mg/L). In patients under the age of 75 (n=92) the median sMR concentration was 0.82 mg/L (CI: 0.71-0.97 mg/L). In patients 75 years or older (n=36) the median sMR concentration was 0.73 mg/L (CI: 0.56-0.86).
For the entire group (n=128) there was a significant difference in the sMR concentration between survivors (n=107) and non-survivors (n=21), (p<0.001) (
In ROC curve analysis for the prediction of survival in the entire group of patients (n=128) sMR had the highest (sMR AUC=0.79, sCD163 AUC=0.70, CRP AUC=0.73) (
The present study shows that for IPD patients under the age of 75, serum sMR within 24 hours after the time of positive blood culture is significantly higher in patients who subsequently die from the disease compared to those who survive. Furthermore, sMR is superior to both sCD163 and CRP for the prognosis of a fatal outcome in IPD patients.
Methods
Patients and Samples Collection
Patients chronically infected with HCV [HCV-RNA detectable by polymerase chain reaction (PCR) in blood≧6 months], genotype 1, were included in the study if they had either no/mild fibrosis or cirrhosis, as determined from a successful examination with transient elastography (TE). Patients were included between January 2009 and March 2010 from two Danish hospital clinics specialised in hepatitis, Department of Infectious
Diseases, Copenhagen University Hospital, Hvidovre, and Department of Infectious Diseases, Odense University Hospital. At the day of examination with TE, blood samples were drawn for HCV-RNA detection, platelet counts and analysis of alanine amino-transferase (ALT), alkaline phosphatase, bilirubin levels, albumin concentration and clotting factors II, VII and X. Creatinine concentrations for the calculation of Model for End-Stage Liver Disease (MELD) scores were measured on the day of examination with TE for most of the patients, but for 11 patients, measurements were taken up to one year before or after the date of examination. Furthermore, at the day of examination with TE, a plasma sample was centrifuged and stored at −20° C. for later analysis for sCD163, sMR and other potential markers. The results from the measurements of 12 fibrosis markers including TNF-α and suPAR have previously been published [Andersen et al (2011). Eur J Clin Microbiol Infect Dis 30:761-766]. Based on power considerations for expected differences between the two groups, we planned to include 40 participants.
Inclusion Criteria
Patients older than 18 years of age, chronically infected with HCV, genotype 1, and with no/mild liver fibrosis (liver stiffness measurement<7.7 kPa) or cirrhosis (liver stiffness measurement≧13.0 kPa) were offered participation in the study.
Exclusion Criteria
Patients infected with HCV non-genotype 1, with hepatitis B virus or with human immunodeficiency virus (HIV) were not included in the study. Furthermore, patients were excluded if they had been administered interferon or ribavirin up to one year before examination. Patients with hepatocellular carcinoma, previous liver transplantation or liver metastases were not included in the study. Patients with a self-reported daily alcohol consumption of >36 g for females and >60 g for males were not included.
Transient Elastography
We used FibroScan® (Echosens, Paris, France) with a medium probe and software version 1.30 for the liver stiffness measurements. The examination was performed by two physicians certified in the use of FibroScan® and with experience of more than 300 examinations. Liver stiffness measurements were considered successful if ten valid measurements were obtained (success rate of valid measurements>60%). The interquartile range of the measurements should be less than 25% of the median value. Patients were considered as having no/mild fibrosis when the liver stiffness was below 7.7 kPa and as having cirrhosis when the liver stiffness was equal to or above 13.0 kPa. These cut-off values had been selected prior to the study and are based on a large meta-analysis including 50 studies of correlation between fibrosis determined by liver biopsy and TE [Friedrich-Rust et al (2008). Gastroenterology 134:960-974]. For diagnosing cirrhosis with a cut-off value of 13.0 kPa using liver biopsies as the reference, a mean area under the receiver operating characteristic curve (AUC) of 0.94 has been found and for diagnosing significant fibrosis (F2 in the METAVIR classification) with liver stiffness above 7.7 kPa, the mean AUC was 0.84 [Friedrich-Rust et al 2008 op cit].
Biochemical Analysis
Blood samples were drawn from patients on the same day that the liver stiffness measurements were carried out. Blood from one 9-ml EDTA-coated tube was separated by centrifugation and plasma was stored at −20° C. Serum sCD163 and sMR were analysed as in example 1.
Statistics
Plasma concentrations of sCD163 and sMR for patients with no/mild fibrosis and cirrhosis were compared using non-parametric tests. The diagnostic performance of the plasma proteins was assessed using receiver operating characteristic (ROC) curve analysis and compared in accordance with the method suggested by Hanley and McNeil [1983, Radiol 148:839-843]. The software R Statistics, version 2.9.0 (R Development Core Team, Vienna, Austria) and SPSS version 17.0 (SPSS Inc., Chicago, Ill., USA) were used for the analyses. Correlation analyses (Pearson r) were performed using GraphPad Prism version 4.00 for Windows (GraphPad Software, San Diego, Calif., USA). p-values<0.05 were considered significant.
Ethics
The Danish National Committee on Biomedical Research Ethics (H-D-2007-0087) approved the study in accordance with the Helsinki Declaration. All patients gave written consent to participate in the study.
Results
The characteristics of the 40 patients with hepatitis C, genotype 1, and either no/mild fibrosis (19 patients) or cirrhosis (21 patients) are shown in Table 7. We had information on the presence of ascites for 37 of the 40 patients included. Only one of the patients (in the cirrhosis group) had ascites. All of the patients were followed in out-patient clinics and had no signs of encephalopathy. The Child-Pugh class and MELD scores (available for 37 patients) are presented in Table 7.
The plasma concentrations of sCD163 and sMR were compared between patients with no/mild fibrosis and cirrhosis. Both sCD163 and sMR were significantly higher in cirrhotic patients than in patients with no/mild fibrosis (Table 8,
The correlations between sCD163 and sMR and other immunological markers are shown in Table 9. Generally, sCD163 and sMR show the same pattern of positive and negative associations.
aNumber of patients (%)
bMedian with 25th and 75th percentiles in parentheses
cAlkaline phosphatase
dClotting factors II, VII and X
eAlanine aminotransferase
fModel for End-Stage Liver Disease
gNot applicable
hMann-Whitney test for equality
aMann-Whitney test for equality
bArea under the receiver operating characteristic curve (95% confidence interval, CI)
aTumour necrosis factor-α
bInterleukin 1-β
cInterleukin 6
dInterleukin 8
eMonocyte chemotactic protein-1
fSoluble urokinase-type plasminogen activator
gMonokine induced by γ-interferon
hAlanine aminotransferase
iAlkaline phosphatase
jClotting factors II, VII, and X
kModel for End-Stage Liver Disease
| Number | Date | Country | Kind |
|---|---|---|---|
| PA 2013 70043 | Jan 2013 | DK | national |
| PA 2013 70044 | Jan 2013 | DK | national |
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/DK2014/050014 | 1/24/2014 | WO | 00 |
