Evidence for bivariate linkage of obesity and HDL-C levels in the Framingham Heart Study

被引:23
作者
Arya, R [1 ]
Lehman, D
Hunt, KJ
Schneider, J
Almasy, L
Blangero, J
Stern, MP
Duggirala, R
机构
[1] Univ Texas, Hlth Sci Ctr, Dept Med, Div Clin Epidemiol, San Antonio, TX 78284 USA
[2] SW Fdn Biomed Res, Dept Genet, San Antonio, TX USA
关键词
D O I
10.1186/1471-2156-4-S1-S52
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
Background: Epidemiological studies have indicated that obesity and low high-density lipoprotein (HDL) levels are strong cardiovascular risk factors, and that these traits are inversely correlated. Despite the belief that these traits are correlated in part due to pleiotropy, knowledge on specific genes commonly affecting obesity and dyslipidemia is very limited. To address this issue, we first conducted univariate multipoint linkage analysis for body mass index (BMI) and HDL-C to identify loci influencing variation in these phenotypes using Framingham Heart Study data relating to 1702 subjects distributed across 330 pedigrees. Subsequently, we performed bivariate multipoint linkage analysis to detect common loci influencing covariation between these two traits. Results: We scanned the genome and identified a major locus near marker D6S1009 influencing variation in BMI (LOD = 3.9) using the program SOLAR. We also identified a major locus for HDL-C near marker D2S1334 on chromosome 2 ( LOD = 3.5) and another region near marker D6S1009 on chromosome 6 with suggestive evidence for linkage ( LOD = 2.7). Since these two phenotypes have been independently mapped to the same region on chromosome 6q, we used the bivariate multipoint linkage approach using SOLAR. The bivariate linkage analysis of BMI and HDL-C implicated the genetic region near marker D6S1009 as harboring a major gene commonly influencing these phenotypes (bivariate LOD = 6.2; LODeq = 5.5) and appears to improve power to map the correlated traits to a region, precisely. Conclusions: We found substantial evidence for a quantitative trait locus with pleiotropic effects, which appears to influence both BMI and HDL-C phenotypes in the Framingham data.
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