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Linkage Analysis of Albuminuria

Amy K. Mottl^*, Suma Vupputuri^*,, Shelley A. Cole, Laura Almasy, Harald H.H. Göring, Vincent P. Diego, Sandra Laston, Nawar Shara, Elisa T. Lee^||, Lyle G. Best^¶, Richard R. Fabsitz^**, Jean W. MacCluer, Jason G. Umans^, and Kari E. North^,

^* UNC Kidney Center, School of Medicine, Department of Epidemiology, School of Public Health, and Carolinas Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina; Department of Genetics, Southwest Foundation for Biomedical Research, San Antonio, Texas; MedStar Research Institute and ^** Epidemiology and Biometry Program, Heart, Lung, and Blood Institute, Bethesda, Maryland; ^|| Center for American Indian Health Research, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma; ^¶ Missouri Breaks Industries Research, Timber Lake, South Dakota; and Department of Medicine, Obstetrics and Gynecology, General Clinical Research Center, Georgetown University Medical Center, Washington, DC

Correspondence: Dr. Amy K. Mottl, UNC Kidney Center, CB# 7155, 6008 Burnett Womack Building, Chapel Hill, NC 27599-7155. Phone: 919-966-2561, ext. 304; Fax: 919-966-4251; E-mail: amy_mottl{at}med.unc.edu

Received for publication August 26, 2008. Accepted for publication January 13, 2009.

American Indians have a higher prevalence of albuminuria than the general population, likely resulting from a combination of environmental and genetic risk factors. To localize gene regions influencing variation in urinary albumin-to-creatinine ratio, we performed a linkage analysis and explored gene-by-diabetes, -hypertension, and -obesity interactions in a large cohort of American Indian families. We recruited >3600 individuals from 13 American Indian tribes from three centers (Arizona, North and South Dakota, and Oklahoma). We performed multipoint variance component linkage analysis in each center as well as in the entire cohort after controlling for center effects. We used two modeling strategies: Model 1 incorporated age, gender, and interaction terms; model 2 also controlled for diabetes, BP, body mass index, HDL, LDL, triglycerides, and smoking status. We evaluated interactions with diabetes, hypertension, and obesity using additive, interaction-specific linkage and stratified analyses. Loci suggestive for linkage to urinary albumin-to-creatinine ratio included 1q, 6p, 9q, 18q, and 20p. Gene-by-diabetes interaction was present with a quantitative trait locus specific to the diabetic stratum in the Dakotas isolated on 18q21.2 to 21.3 using model 1 (logarithm of odds = 3.3). Gene-by-hypertension interaction was present with quantitative trait loci specific to the hypertensive stratum in the Dakotas on 7q21.11 using model 1 (logarithm of odds = 3.4) and 10q25.1 using model 2 (logarithm of odds = 3.3). These loci replicate findings from multiple other genome scans of kidney disease phenotypes with distinct populations and are worthy of further study.

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Copyright © 2009 by the American Society of Nephrology. Online ISSN: 1533-3450 Print ISSN: 1046-6673