Meta-Analysis of Genome-Wide Linkage Studies of Quantitative Lipid Traits in Families Ascertained for Type 2 Diabetes
Meta-Analysis of Genome-Wide Linkage Studies of Quantitative Lipid Traits in Families Ascertained for Type 2 Diabetes Alka Malhotra 1 , Steven C. Elbein 2 , Maggie C.Y. Ng 3 , Ravindranath Duggirala 4 , Rector Arya 5 , Giuseppina Imperatore 6 , Adebowale Adeyemo 7 , Toni I. Pollin 8 , Wen-Chi Hsueh...
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Published in | Diabetes (New York, N.Y.) Vol. 56; no. 3; pp. 890 - 896 |
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Main Authors | , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
American Diabetes Association
01.03.2007
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Subjects | |
Online Access | Get full text |
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Summary: | Meta-Analysis of Genome-Wide Linkage Studies of Quantitative Lipid Traits in Families Ascertained for Type 2 Diabetes
Alka Malhotra 1 ,
Steven C. Elbein 2 ,
Maggie C.Y. Ng 3 ,
Ravindranath Duggirala 4 ,
Rector Arya 5 ,
Giuseppina Imperatore 6 ,
Adebowale Adeyemo 7 ,
Toni I. Pollin 8 ,
Wen-Chi Hsueh 9 ,
Juliana C.N. Chan 3 ,
Charles Rotimi 7 ,
Robert L. Hanson 10 ,
Sandra J. Hasstedt 11 ,
Johanna K. Wolford 1 and
and the American Diabetes Association GENNID Study Group *
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
Abstract
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.
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
Footnotes
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* A complete list of the American Diabetes Association GENNID Study Group members can be found in the acknowledgments .
The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore
be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
Accepted December 12, 2006.
Received July 28, 2006.
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 ObjectType-Article-2 ObjectType-Feature-1 |
ISSN: | 0012-1797 1939-327X |
DOI: | 10.2337/db06-1057 |