Abstract
To dissect the genetic architecture of sexual dimorphism in obesity-related traits, we evaluated the sex-genotype interaction, sex-specific heritability and genome-wide linkages for seven measurements related to obesity. A total of 1,365 non-diabetic Chinese subjects from the family study of the Stanford Asia-Pacific Program of Hypertension and Insulin Resistance were used to search for quantitative trait loci (QTLs) responsible for the obesity-related traits. Pleiotropy and co-incidence effects from the QTLs were also examined using the bivariate linkage approach. We found that sex-specific differences in heritability and the genotype-sex interaction effects were substantially significant for most of these traits. Several QTLs with strong linkage evidence were identified after incorporating genotype by sex (G × S) interactions into the linkage mapping, including one QTL for hip circumference [maximum LOD score (MLS) = 4.22, empirical p = 0.000033] and two QTLs: for BMI on chromosome 12q with MLS 3.37 (empirical p = 0.0043) and 3.10 (empirical p = 0.0054). Sex-specific analyses demonstrated that these linkage signals all resulted from females rather than males. Most of these QTLs for obesity-related traits replicated the findings in other ethnic groups. Bivariate linkage analyses showed several obesity traits were influenced by a common set of QTLs. All regions with linkage signals were observed in one gender, but not in the whole sample, suggesting the genetic architecture of obesity-related traits does differ by gender. These findings are useful for further identification of the liability genes for these phenotypes through candidate genes or genome-wide association analysis.
Original language | English |
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Pages (from-to) | 501-513 |
Number of pages | 13 |
Journal | Human Genetics |
Volume | 128 |
Issue number | 5 |
DOIs | |
State | Published - Nov 2010 |
Externally published | Yes |
Bibliographical note
Funding Information:Acknowledgments We thank patients and their families for participating in this study. We also thank the members of the SAPPHIRe project for their help. We thank Dr. David Hinds and Ms. Guan-Yi Hung for assistance with data. We thank the reviewers for their constructive and insightful comments, which have greatly improved the quality of this manuscript. This work was supported in part by the Grant from the National Science Council (NSC 96-3112-B002-002 to L.M.C) and by the Grants BS-097-PP-03 (C.A.H) and BS-097-PP-04 (Y.F.C) from the National Health Research Institutes.