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Meta-Analysis of Genome-Wide Linkage Studies of Quantitative Lipid Traits in Families Ascertained for Type 2 Diabetes

¹ Diabetes and Obesity Research Unit, Translational Genomics Research Institute, Phoenix, Arizona
² Endocrinology Section, University of Arkansas, Little Rock, Arkansas
³ Department of Medicine and Therapeutics, Chinese University of Hong Kong, Shatin, Hong Kong
⁴ Department of Genetics, Southwest Foundation for Biomedical Research, San Antonio, Texas
⁵ Division of Clinical Epidemiology, University of Texas Health Sciences Center, San Antonio, Texas
⁶ Division of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, Georgia
⁷ National Human Genome Center, Howard University, Washington, DC
⁸ Division of Endocrinology, Diabetes, and Nutrition, University of Maryland, Baltimore, Maryland
⁹ Department of Medicine, University of California San Francisco, San Francisco, California
¹⁰ Diabetes and Arthritis Epidemiology Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, Arizona
¹¹ Human Genetics Department, University of Utah, Salt Lake City, Utah

Address correspondence and reprint requests to Alka Malhotra, Diabetes and Obesity Research Unit, Genetic Basis of Human Disease, Translational Genomics Research Institute, 445 N. 5th St., Phoenix, AZ 85004. E-mail: amalhotra{at}tgen.org

Abbreviations: AADM, Africa-America Diabetes Mellitus; AFDS, Amish Family Diabetes Study; CHD, coronary heart disease; GENNID, Genetics of NIDDM; GSMA, Genome Scan Meta-Analysis; HKFDS, Hong Kong Family Diabetes Study; LOD, logarithm of odds; SAFADS, San Antonio Family Diabetes Study

Dyslipidemia is a major risk factor for coronary heart disease, which is the predominant cause of mortality in individuals with type 2 diabetes. To date, nine linkage studies for quantitative lipid traits have been performed in families ascertained for type 2 diabetes, individually yielding linkage results that were largely nonoverlapping. Discrepancies in linkage findings are not uncommon and are typically due to limited sample size and heterogeneity. To address these issues and increase the power to detect linkage, we performed a meta-analysis of all published genome scans for quantitative lipid traits conducted in families ascertained for type 2 diabetes. Statistically significant evidence (i.e., P < 0.00043) for linkage was observed for total cholesterol on 7q32.3-q36.3 (152.43–182 cM; P = 0.00004), 19p13.3-p12 (6.57–38.05 cM; P = 0.00026), 19p12-q13.13 (38.05–69.53 cM; P = 0.00001), and 19q13.13-q13.43 (69.53–101.1 cM; P = 0.00033), as well as LDL on 19p13.3-p12 (P = 0.00041). Suggestive evidence (i.e., P < 0.00860) for linkage was also observed for LDL on 19p12-q13.13, triglycerides on 7p11-q21.11 (63.72–93.29 cM), triglyceride/HDL on 7p11-q21.11 and 19p12-q13.13, and LDL/HDL on 16q11.2-q24.3 (65.2–130.4 cM) and 19p12-q13.13. Linkage for lipid traits has been previously observed on both chromosomes 7 and 19 in several unrelated studies and, together with the results of this meta-analysis, provide compelling evidence that these regions harbor important determinants of lipid levels in individuals with type 2 diabetes.

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