Abstract

The prevalence of diabetes is rapidly increasing worldwide, thus leading to an increasing risk of diabetic microangiopathy, caused by prolonged hyperglycemia, as well as an increase in atherosclerotic diseases (macroangiopathy), of which diabetes is one of the risk factors. Complex gene-environment interactions make it difficult to investigate the molecular basis of diabetic etiology from clinical samples obtained from diabetic patients with wide-ranging backgrounds. In contrast, risk factors for diabetic complications such as micro- and macroangiopathies are common among patients with a variety of diabetic pathogeneses, thus enabling the proteomic search for biomarkers of diabetic complications from clinical samples feasible. In an attempt to identify diabetic biomarkers, we analyzed sera from more than 100 diabetic patients and approximately 40 control subjects, using cleavable isotope-coded affinity tag, followed by tandem mass spectrometry for protein sequencing and identification. These proteins, which were differentially expressed in the sera from diabetic patients, may be potential biomarkers of various pathological conditions related to diabetes. In another study, we developed a 2-dimensional gel-based method that enabled the analysis of approximately 2,000 protein spots by combining ultrafiltration, immunoaffinity depletion of major urinary proteins, and 2-dimensional difference gel electrophoresis. Using this experimental system, we analyzed urine samples collected from diabetic patients with or without microalbuminuria and healthy controls to search for early diagnostic markers of diabetic nephropathy. We identified 33 unique proteins (24 upregulated and 9 downregulated) that were differentially expressed in diabetic patients with microalbuminuria as compared to those in the healthy controls. Proteomic analyses of clinical samples from diabetic patients, animal models of diabetes, and cultured cells may help to elucidate the molecular mechanisms responsible for the development of various forms of diabetes and to identify diagnostic biomarkers of diabetic complications.

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