In this validation study using ELISA, we were able to confirm the value of several proteins previously identified through the label-free protein expression as potential predictors of early diabetic nephropathy and that added to the model fit above and beyond previously identified risk markers. Discovery-based quantitative proteomics provide a powerful technique for identification and quantification in large-scale protein profiling for biomarker discovery, and multiple proteomic techniques are available (21
). To date, most proteomic approaches have used two-dimensional gel electrophoresis or capillary electrophoresis–mass spectrometry to classify type 1 diabetes and its complications (24
Label-free protein expression is a peptide-based proteomic technique that capitalizes on the highly reproducible chromatography and accurate mass accuracy available in current LC/MS systems. This platform quantifies a peptide by its intensity and groups each peptide across individual samples on the basis of its accurate mass and retention time (27
). These intensities associated with specific mass and retention time values are organized into peptide array tables that may be further processed using statistical techniques. The label-free protein expression analysis in the current study provided a comprehensive view of proteomic changes during the development of microalbuminuria from which predictive models could be derived. The models highlight a number of clinically relevant proteins, as well as novel indicators of disease.
THP, which is produced in the thick ascending limb and the early distal convoluted tubule of the kidney, is the most abundant protein in normal urine. THP is the protein product encoded by the uromodulin gene (UMOD
), which has been identified in genome-wide association scans with chronic kidney disease and GFR estimated from serum creatinine (29
). Urinary THP has been suggested as a useful marker of renal damage and has been reported to be decreased in patients with type 1 diabetes (30
) and in patients with kidney damage with and without diabetes (33
). In the current study, we found that levels of THP were significantly increased in patients who developed both ERFD and albuminuria. Köttgen et al. (34
) also found that higher levels of THP were associated with chronic kidney disease in a case-control study, with an odds ratio for chronic kidney disease of 1.72 per 1 SD increase in THP.
AGP has previously been reported as increasing in patients with diabetic nephropathy (35
) and may serve as both an early marker of diabetic nephropathy as well as a marker of diabetic nephropathy progression. Prostaglandin D synthase, which was not predictive of renal outcomes in the current study, was previously reported to be increased in patients with type 2 diabetes who had increased permeability of glomerular capillary walls, and higher levels of prostaglandin D synthase predicted albuminuria (37
Other proteins included in the model (clusterin and progranulin), while not directly associated with diabetic nephropathy, were observed to be associated with renal toxicity and/or renal damage. Clusterin is a glycoprotein that may have a role in repairing kidney damage, since low levels of clusterin have been found to predict worse recovery from renal ischemia-reperfusion injury in mice (38
). Clusterin may have a role in protecting organisms from apoptosis because of oxidative stress (39
) and may prevent glomerulopathy associated with aging (40
). Progranulin is a growth factor involved in wound healing and is known to have an anti-inflammatory effect (41
). On the other hand, when progranulin is degraded into peptides by proteases, it has been shown to have a proinflammatory effect (42
The current study provided important preliminary data on a panel of proteins that could be used to predict the early signs of diabetic nephropathy, including the development of micro- and macroalbuminuria as well as significant renal function decline. Further validation of this protein panel is needed in other populations to verify their predictive ability for the development of both renal function decline and urinary albumin and to determine whether these could be used as biomarkers of disease progression and response to treatment.