Patent Application
20180143207
This application claims priority to Taiwan Patent Application No. 105138384 filed on 23 Nov. 2016, all disclosures of which are incorporated herein by reference in its entirety.
The present invention relates generally to a urinary biomarker, and more particularly to a method for screening out a subject having a high risk of developing a diabetic nephropathy by the urinary biomarker.
Although the medical science is highly developed in the twenty-first century, the prevalence of diabetes or early-stage of diabetes in the world is continuously raising. In 2013, the global diabetic patients were about 382 million, and it was estimated to about 592 million by 2035, equivalent to 10.1% population of 20 to 79-year-old adult of the world. One of the most common risk factors for chronic kidney disease (CKD) is diabetes, and the major complication of diabetes, diabetic nephropathy (DN), would often lead to the serious end-stage renal disease (ESRD). The patients suffering from the ESRD require hemodialysis or renal transplantation therapy, and are always facing the death threats. According to the United States The Third National Health and Nutrition Examination survey (NHANES III), the 10-year cumulative all-cause mortality of the diabetic adults, more than 20 yeas old, increased by 3.4 times, while CKD patients increased by 9 times; however, when a diabetic patient having CKD, the all-cause mortality increased significantly to 23.4 times. Apparently, diabetic nephropathy has become the most serious threat to diabetic patients.
Even aware of the trend described above, the need of renal transplantation for the patients with end-stage of the kidney disease has still been increasing. Up to now there has no effective strategy to prevent diabetic renal complications; and the knowledge of pathogenic mechanisms of DN remains insufficient so that the method for effectively screening or predicting patients having a high risk of developing ESRD is also deficient. There are some conventional clinical screening methods for diabetic nephropathy, such as detection of albumin-creatinine ratio (ACR) or protein-creatinine ratio (PCR) in urine of patients with abnormal blood glucose. As the value of ACR or PCR is much higher, the patient's renal function may be decreased more significantly in the future. Furthermore, detection of microalbuminuria has been the standard method for diagnosis of early stages of DN. However, some patients detected with microalbuminuria have appeared advanced renal pathological changes, which indicates that microalbuminuria is not an appropriate marker for early detection or prediction of DN. In addition, some patients with type 2 diabetes have found no microalbumin appeared after renal biopsy; that is, the pathology of part of diabetic patients is atypical diabetic nephropathy, and particularly some of them exhibit both non-diabetic nephropathy and diabetic nephropathy. As such, detection of microalbuminuria is therefore limited. Moreover, the prevalence or incidence of microalbuminuria in Asia patients with diabetes is higher than that of Caucasians, and so is the rate of deterioration of nephropathy. Therefore, it is urgently needed to find a suitable biomarker for precise detection of early diabetic nephropathy such that the diabetic patients having high risk of developing DN can be screened and treated earlier.
As mentioned above, the pathogenesis of diabetic nephropathy is unclear, but a variety of studies have shown that blood glucose abnormalities play an important role. In the case of patients with type 1 diabetes, strict glycemic control can reduce the probability of albuminuria and deterioration thereof. In addition to abnormal blood glucose, the most relevant factor regarding diabetic nephropathy is advanced glycation end products (AGEs). The advanced glycation end products are formed through a series of Maillard reactions, reducing sugars, such as glucose, react with amino groups in proteins, lipids, and nucleic acids forming Schiff bases and Amadori products to produce AGEs. In general, AGEs are produced continuously in the human body, even with euglycemia, but in diabetes patients AGEs are accelerated produced. The resultant AGEs are finally removed or metabolized by the kidney in normal subjects. However, AGEs are markedly accumulated in the serum and tissues of patients with ESRD. Compared with diabetic patients without renal disease, diabetic patients with ESRD had two times of AGE levels in tissues.
Uromodulin (UMOD), also known as Tamm-Horsfall protein, is the most abundant urinary protein in healthy individuals and normally expressed by epithelia of the TALH and the early distal tubule. UMOD exhibits diverse functions including the prevention of ascending urinary tract infections by binding type I-fimbriated Escherichia coli, up-regulation inflammatory response and tubular transport function. UMOD, normal and genetically determined variants, may also actively participate in the pathogenesis of CKD. As loss of protective UMOD activities, gain of damaging functions or dislocation, UMOD might impair tubular recovery after injury and promote chronic interstitial fibrosis and irreversible nephron loss due to abnormal intracellular trafficking, leading to stress within the endoplasmic reticulum (ER), tubular malfunction and eventual death. Many studies have confirmed the findings that there was association between UMOD with eGFR and diabetic nephropathy.
A primary objective of the present invention is to provide a urinary biomarker for early detection or prediction of a patient having a high risk of developing a diabetic nephropathy so as to diagnose and treat diabetic nephropathy earlier to decrease the probability of serious complications and the mortality resulting from ESRD.
In order to achieve the foregoing objective, the present invention provides a urinary biomarker, which can be used to screen the patients having high risks of developing a diabetic nephropathy. The urinary biomarker can include glycated uromodulin (glcUMOD).
Furthermore, in order to achieve the foregoing objective, the present invention also provides a method for evaluating a subject having a high risk of developing a diabetic nephropathy, comprising the steps of: providing a urine sample from the subject; and detecting the presence of glycated uromodulin in the urine sample. When glycated uromodulin is present in the urine sample, the subject is diagnosed to have a high risk of developing a diabetic nephropathy.
According to an embodiment of the present invention, the subject for evaluating is a diabetic patient. According to an embodiment of the present invention, the age of the subject can be less than 65 years old.
According to an embodiment of the present invention, the subject can be patients of stages 1 to 3a of CKD.
According to an embodiment of the present invention, the urine sample can be obtained from the supernatant fraction of the urine sample centrifugation.
According to an embodiment of the present invention, the urine sample can be centrifuged at about 16,000 xg to about 20,000 xg, preferably at about 18,000 xg, and then the supernatant is recovered. The supernatant recovered can further be centrifuged at about 100,000 xg to about 120,000 xg, preferably at 110,000 xg, and the resultant supernatant is further recovered.
According to an embodiment of the present invention, the level of glycated uromodulin can be determined by, including but not limited to, Western blot, mass spectrometry, immunoassay, or chromatography.
According to an embodiment of the present invention, the level of glycated uromodulin in the urine sample can be 8,000 a.u. (arbitrary unit) or more, preferably 9,000 a.u. or more.
Accordingly, the biomarker and the detection method provided by the present invention, compared to detection of microalbuminuria, PCR or ACR, can earlier and precisely screen out the diabetic patients having high risks of developing a diabetic nephropathy so that these patients can be treated in advance to prevent the progression of ESRD and decrease the subsequent pain of hemodialysis or probable death.
Furthermore, according to an embodiment of the present invention, when the subject is detected to have the glycated uromodulin in the urine sample, especially the level of glycated uromodulin is more than 8,000 a.u., preferably 9,000 a.u., An albumin-creatinine ratio (ACR) or a protein-creatinine ratio (PCR) of the urine sample can be furthered detected so as to increase the accuracy the prediction of DN.
The present invention will be apparent to those skilled in the art by reading the following detailed description of a preferred embodiment thereof, with reference to the attached drawings, in which:
The accompanying drawings are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification. The drawings illustrate embodiments of the invention and, together with the description, serve to explain the principles of the invention.
In order to isolate and determine the glycated uromodulin, the AGEs isolated from urine of non-diabetic CKD patients (non-DM) and diabetic CKD patients (DM) were immunoprecipitated and then the immunoprecipitates were subjected to LC-MS-MS, and further confirmed by Western blot analysis. Finally, glycated uromodulin was mainly present in the urine of DM subjects, especially in the supernatant fraction of urine thereof.
Firstly, 84 patients, 35 DM and 49 non-DM, were recruited from the nephrology clinic at Changhua Christian Hospital, Taiwan, between September 2013 and January 2015. The duration of follow-up was less than 3 years in all patients. Those with fever, infection, hepatic, cardiac, history of other endocrinopathies, surgery, trauma and admission for any causes in recent 3 months were excluded. The study protocol was approved by the Ethics Research Committee at Changhua Christian Hospital, Taiwan). Written informed consent was obtained from all participants. Next, these patients were fast overnight for 8 hours. Then, venous blood samples thereof were obtained and the first morning urine samples were also collected from each individual. After that, aliquots of urine were immediately frozen at −80° C. until further analysis.
In order to isolate glycated uromodulin, the urine samples were thawed and then isolated by differential centrifugation at 4° C., 18,000 xg for 3 hours. The supernatant collected therefrom was further centrifuged at 4° C., 111,000 xg for 3 hours. After that, the resultant supernatant and pellet (including exosome), and the pellet (including microvescile) obtained by the first centrifugation were immunoprecipitated with anti-uromodulin antibodies (IP: uromodulin) and subjected to LC-MS-MS. Next, the immunoprecipitates were further confirmed respectively by Western blot analysis with anti-AGEs and anti-uromodulin antibodies (WB: anti-AGEs and WB: anti-uromodulin). As the results shown in
Referring to
In addition to glycated uromodulin determination, microalbuminuria was established when two out of three ACR determinations were found to be within the range 30-300 mg/g in a six-month period. Creatinine concentration in urine and serum was measured by a kinetic method based on Jaffe reaction. The tests were run in duplicates. Intra-assay variation coefficient was <5%. The urinary concentration of albumin was assessed by an immunoturbidimetric method (Roche Diagnostics GmbH) and ACR was expressed as mg/g creatinine. Serum creatinine values were used to calculate an estimated glomerular filtration rate (eGFR), by means of the abbreviated Modification of Diet in Renal Disease formula.
Results from above tests were presented as the median (interquartile range) or percentage N (%). Statistical analyses were performed using Chi-Square test or Fisher's Exact test for comparing the proportion of categories variables of serum glcUMOD levels between patients with and without DM. As for nonparametric Wilcoxon rank-sum test was employed to compare the continuous variable of serum glcUMOD levels between patients with or without DM. The predicted probability of DM at various glcUMOD levels was calculated from a logistic regression model. Statistical analyses were performed with SPSS Statistics software version 19.0.0 (IBM Corporation, Somers, N.Y., USA). P<0.05 was considered to be statistically significant.
Referring to TABLE 1 below, it summarizes some clinical features of the study subjects, and also the glcUMOD levels and eGFR of patients. CKD patients can be classified into five stages by values of eGFR as follows: (1) Stage 1: Slightly diminished function; kidney damage with normal or relatively high eGFR (>90 ml/min/1.73 m2) and persistent albuminuria. Kidney damage is defined as pathological abnormalities or markers of damage, including abnormalities in blood or urine tests or imaging studies; (2) Stage 2: Mild reduction in eGFR (60-89 ml/min/1.73 m2) with kidney damage; (3) Stage 3: Moderate reduction in eGFR (30-59 ml/min/1.73 m2; it can further be divided into stage 3a having eGFR of 45-59 ml/min/1.73 m2 and stage 3b having eGFR of 30-44 ml/min/1.73 m2); (4) Stage 4: Severe reduction in eGFR (15-29 ml/min/1.73 m2). Preparation for renal replacement therapy; and (5) Stage 5: Established kidney failure (eGFR <15 ml/min/1.73 m2), permanent renal replacement therapy, or end-stage renal disease.
As shown in TABLE 1, the relationship via Person correlation analysis between glcUMOD and age (Sig.=0.773; 2-tailed) or body mass index (BMI) and glcUMOD (Sig.=0.059; 2-tailed) is statistic insignificancy. Referring also to
Referring to both
Further referring to TABLE 3 below, it shows the levels of urine glycated uromodulin expression in diabetic patients having age less or more than 65 years old. As shown in TABLE 3, patients' age has a significant correlation with the diabetic patient; particularly, the correlation is more obvious when the age is younger than 65 years old.
In order to determine the prediction accuracy of the biomarker of glycated uromodulin, the other well-known biomarkers, such as protein-creatinine ratio (PCR) and albumin-creatinine ratio (ACR) were performed at the same time to analyze patients who was and was not with diabetic nephropathy. Referring to
A risk prediction model was assessed using multivariable logistic regression and predictive ability was using c-statistics, category-free net reclassification improvement (cfNRI), integrated discrimination improvement (IDI) for the urine biomarkers model. The models were shown in TABLE 4 below.
Following ACR (Model 1a) or ACR and glcUMOD (Model 1b) adjustment, the glcUMOD is predictive for diabetic patients with CKD (odds ratio 1.14 (95% CI: 1.01-1.29), P=0.028); as PCR (Model 2a) or PCR and glcUMOD (Model 2b) adjustment, the glcUMOD is well predictive for diabetic patients with CKD (odds ratio 1.23 (95% CI: 1.11-1.38), P<0.0001). Variance inflation factors (vif) of the logistic regression were 1.105 and 1.022 respectively, indicating there are absent the collinearity between ACR and glcUMOD, PCR and glcUMOD.
To further describe the ability of these markers to risk-stratify diabetic patients beyond our clinical classic risk prediction model, c-statistics, NRI, IDI values were calculated and the results are shown in TABLE 5.
The IDI provides information on both the direction and magnitude of mean change in predicted probabilities for events and nonevents when additional variables or biomarkers are added. Referring to TABLE 5, as urine glcUMOD combing ACR, the IDI was 0.046 (95% CI: 0.002-0.09), P=0.048; namely the prediction probability increases for 4.6%. Whereas glcUMOD combing PCR, the IDI was 0.19 (95% CI: 0.103-0.277), P<0.0001). That is, the prediction probability increases for 19%.
In contrast, cfNRI provides a measure of the direction of change in estimated risk that a biomarker adds to the clinical model without considering cut-point exist, with results reported as proportions. Because it is possible for 100% of both events and nonevents to increase the risk, the maximum value of the total cfNRI (events+ nonevents) is 200%. As seen from TABLE 5, as urine glcUMOD combing ACR, the cfNRI increases 75.92% (95% CI: 36.96-114.88), P<0.0001). Whereas glcUMOD combing PCR, the cfNRI increases also 75.92% (95% CI: 36.96-114.88), P<0.0001). Therefore, combing the detection results of glcUMOD according to an embodiment of the present invention with the results of conventional ACR or PCR would further increase the prediction accuracy of DN.
By means of using glycosylated uromodulin as a biomarker, patients with high risks of developing diabetic nephropathy can be predicted accurately and earlier more than general detection methods of PCR or ACR tests in diabetic patient population. Thereby the patient being screened can be treated earlier and thus prevent deterioration of the progression of chronic kidney disease, and therefore dramatically decrease the risk of death.
Although the present invention has been described with reference to the preferred embodiments thereof, it is apparent to those skilled in the art that a variety of modifications and changes may be made without departing from the scope of the present invention which is intended to be defined by the appended claims.
| Number | Date | Country | Kind |
|---|---|---|---|
| 105138384 | Nov 2016 | TW | national |
