Diabetic Nephropathy (DN) is the most common cause of end stage renal disease in the United States. Among patients with type 2 diabetes (T2DM), microalbuminuria is not a strong risk factor for developing DN, and thus early identification of those at risk for DN has been challenging. Pro-inflammatory cytokines are biologically linked to DN, and cytokines acting locally in the kidney and evident in the urine may identify those with T2DM at risk for DN. Although cross-sectional studies suggest urine and not serum cytokines are altered at the time of DN, prospective studies are limited. Furthermore, prior studies examined single urine cytokine alterations, which may not best characterize this complex disorder. In fact, a specific combination of cytokines ('cytokine signatures') may better identify those at risk for DN. A study of subjects at high risk for DN with urine samples collected prospectively and tested with novel multiplexed profiling techniques overcomes these previous limitations. Pima Indians have a high rate of developing T2DM and DN. Since 1965, a cohort of Pima Indians has been followed biennially by the NIDDK. Utilizing a comprehensive database in conjunction with urine samples collected at each biennial visit, we will test two hypotheses: 1) Specific urine cytokines (TNF-alpha, TGF-beta, MCP-1, IL-6, IL-8, and IL-18) are altered 10 years before the onset of macroalbuminuria, when subjects display normoalbuminuria; and 2) A disease specific cytokine microarray identifying those at risk for DN can be developed. In collaboration with NIDDK, we have identified a nested group of cases and matched (to minimize confounding) controls with urine samples collected at baseline and 10 years thereafter. To test our hypotheses, we have assembled a multidisciplinary team with expertise in diabetes and diabetic nephropathy, nested case-control studies, protein array technology, and bioinfromatics. This R21 proposal may provide insight into the pathogenesis of DN, provide useful biomarkers to predict DN, and suggest early targets for intervention for this devastating disorder.
| Knickerbocker, Tanya; MacBeath, Gavin (2011) Detecting and quantifying multiple proteins in clinical samples in high-throughput using antibody microarrays. Methods Mol Biol 723:3-13 |
| Otu, Hasan H; Can, Handan; Spentzos, Dimitrios et al. (2007) Prediction of diabetic nephropathy using urine proteomic profiling 10 years prior to development of nephropathy. Diabetes Care 30:638-43 |
| Knickerbocker, Tanya; Chen, Jiunn R; Thadhani, Ravi et al. (2007) An integrated approach to prognosis using protein microarrays and nonparametric methods. Mol Syst Biol 3:123 |
