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A Genome-Wide DNA Microsatellite Association Screen to Identify Chromosomal Regions Harboring Candidate Genes in Diabetic Nephropathy

Amy Jayne McKnight^*, A. Peter Maxwell^*, Stephen Sawcer, Alastair Compston, Efrosini Setakis, Chris C. Patterson, Hugh R. Brady^|| and David A. Savage^*

^* Nephrology Research Group; Department of Epidemiology & Public Health, Queen’s University Belfast, Belfast, Northern Ireland; Department of Neurology, University of Cambridge, Cambridge, United Kingdom; Department of Epidemiology and Public Health, Imperial College, London, United Kingdom; and ^|| Conway Institute, University College Dublin, Dublin, Ireland

Address correspondence to: Dr. David A. Savage, Nephrology Research Group, Queen’s University Belfast, c/o Medical Genetics, Floor A, Tower Block, Belfast City Hospital, Lisburn Road, Belfast BT9 7AB, Northern Ireland. Phone: +44-0-28-90329241 ext. 2149; Fax: +44-0-28-90236911; d.savage{at}qub.ac.uk

Received for publication May 12, 2005. Accepted for publication January 3, 2006.

In an effort to accelerate the identification of susceptibility genes in diabetic nephropathy, the first genome-wide fluorescence-based DNA microsatellite (n = 6000) association screen was performed, using pools of genomic DNA derived from Irish patients with (cases; n = 200) and without (controls; n = 200) type 1 diabetic nephropathy. Allele image profiles were generated for 5353 (89.2%) microsatellite markers for both case and control pools. Allele counts (estimated from allele image profiles) were compared in case versus control groups, and empirical P values were generated. Markers then were ranked on the basis of their empirical P values (lowest to highest). Repeat PCR amplification and electrophoresis of pooled samples were performed systematically on ranked markers until the 50 most associated markers with consistent results were identified. DNA samples that composed the pools then were genotyped individually for these markers. Two markers on chromosome 10, D10S558 (P_corrected = 0.005) and D10S1435 (P_corrected = 0.016), revealed statistically significant associations with diabetic nephropathy. An additional four markers (D6S281, D4S2937, D2S291, and D17S515) also are worthy of further investigation. Relevant functional candidate genes have been identified in the vicinity of these markers, demonstrating the feasibility of low-resolution genome-wide microsatellite association screening to identify possible candidate genes for diabetic nephropathy.

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