Methods and devices for detecting diabetic nephropathy and associated disorders

Abstract

Methods and devices for diagnosing, monitoring, or determining diabetic nephropathy or an associated disorder in a mammal are described. In particular, methods and devices for diagnosing, monitoring, or determining diabetic nephropathy or an associated disorder using measured concentrations of a combination of three or more analytes in a test sample taken from the mammal are described.

1 .- 8 . (canceled) 
     
     
         9 . A method for generating a dataset for use in detecting diabetic nephropathy or an associated disorder in a human, the method comprising:
 a. performing a multiplexed immunoassay on analytes of a sample of bodily fluid selected from blood, plasma, or serum taken from a human, wherein the analytes are selected from alpha-1 microglobulin, beta-2 microglobulin, calbindin, clusterin, Connective tissue growth factor (CTGF), creatinine, cystatin C, Glutathione S-transferase alpha (GST-alpha), Kidney injury molecule-1 (KIM-1), microalbumin, Neutrophil gelatinase-associated lipocalin (NGAL), osteopontin, Tamm-Horsfall protein (THP), Tissue inhibitor of metalloproteinase-1 (TIMP-1), Trefoil factor 3 (TFF3), and Vascular endothelial growth factor (VEGF);   b. determining the concentration for each analyte in a combination of three or more analytes in the sample to provide a sample combination dataset;   c. providing a diagnostic dataset comprising a combination of three or more minimum diagnostic concentrations of the analytes indicative of a particular renal disorder;   d. comparing the entries of the sample combination dataset to the entries of the diagnostic dataset; and   e. generating a dataset for use in detecting diabetic nephropathy or an associated disorder in a human by selecting the diagnostic dataset entries that are less than the corresponding entries in the sample combination dataset thereby providing a matched dataset.   
     
     
         10 . The method of  claim 9 , wherein the minimum diagnostic concentration in human plasma of alpha-1 microglobulin is about 16 μg/ml, beta-2 microglobulin is about 2.2 μg/ml, calbindin is greater than about 5 ng/ml, clusterin is about 134 μg/ml, CTGF is about 16 μg/ml, cystatin C is about 1170 ng/ml, GST-alpha is about 62 ng/ml, KIM-1 is about 0.57 ng/ml, NGAL is about 375 ng/ml, osteopontin is about 25 ng/ml, THP is about 0.052 μg/ml, TIMP-1 is about 131 ng/ml, TFF-3 is about 0.49 μg/ml, and VEGF is about 855 μg/ml. 
     
     
         11 . The method of  claim 9 , wherein a combination of sample concentrations for six or more sample analytes in the test sample are determined. 
     
     
         12 . The method of  claim 11 , wherein sample concentrations are determined for the analytes selected from the group consisting of alpha-1 microglobulin, beta-2 microglobulin, cystatin C, KIM-1, THP, and TIMP-1. 
     
     
         13 . The method of  claim 9 , wherein a combination of sample concentrations for sixteen sample analytes in the test sample are determined. 
     
     
         14 . The method of  claim 9  further comprising identifying a diabetic nephropathy or an associated disorder based on the matched dataset. 
     
     
         15 . A method for generating a dataset for use in detecting diabetic nephropathy or an associated disorder in a human, the method comprising:
 a. performing a multiplexed immunoassay on analytes of a sample of bodily fluid selected from blood, plasma, or serum taken from a human, wherein the analytes are selected from alpha-1 microglobulin, beta-2 microglobulin, calbindin, clusterin, Connective tissue growth factor (CTGF), creatinine, cystatin C, Glutathione S-transferase alpha (GST-alpha), Kidney injury molecule-1 (KIM-1), microalbumin, Neutrophil gelatinase-associated lipocalin (NGAL), osteopontin, Tamm-Horsfall protein (THP), Tissue inhibitor of metalloproteinase-1 (TIMP-1), Trefoil factor 3 (TFF3), and Vascular endothelial growth factor (VEGF);   b. determining the concentration for each analyte in a combination of three or more analytes in the sample to provide a sample combination dataset;   c. providing a diagnostic dataset comprising a combination of three or more maximum diagnostic concentrations of the analytes indicative of a particular renal disorder;   d. comparing the entries of the sample combination dataset to the entries of the diagnostic dataset; and   e. generating a dataset for use in detecting diabetic nephropathy or an associated disorder in a human by selecting the diagnostic dataset entries that are less than the corresponding entries in the sample combination dataset thereby providing a matched dataset.   
     
     
         16 . A method for generating a dataset for use in detecting diabetic nephropathy or an associated disorder in a human, the method comprising:
 a. performing a multiplexed immunoassay on analytes of a sample of bodily fluid selected from blood, plasma, or serum taken from a human, wherein the analytes are selected from alpha-1 microglobulin, beta-2 microglobulin, calbindin, clusterin, Connective tissue growth factor (CTGF), creatinine, cystatin C, Glutathione S-transferase alpha (GST-alpha), Kidney injury molecule-1 (KIM-1), microalbumin, Neutrophil gelatinase-associated lipocalin (NGAL), osteopontin, Tamm-Horsfall protein (THP), Tissue inhibitor of metalloproteinase-1 (TIMP-1), Trefoil factor 3 (TFF3), and Vascular endothelial growth factor (VEGF);   b. determining the concentration for each analyte in a combination of three or more analytes in the sample to provide a sample combination dataset;   c. providing a diagnostic dataset comprising a combination of three or more diagnostic concentrations for each of the analytes indicative of a particular renal disorder;   d. comparing the entries of the sample combination dataset to the entries of the diagnostic dataset; and   e. generating a dataset for use in detecting diabetic nephropathy or an associated disorder in a human by selecting the diagnostic dataset entries that are altered relative to the corresponding entries in the sample combination dataset thereby providing a matched dataset.   
     
     
         17 . The method of  claim 16 , wherein the combined analyte concentration may be compared to a diagnostic criterion in which the corresponding minimum or maximum diagnostic concentrations are combined using the same algebraic operations used to determine the combined analyte concentration.