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Heritability and genetic correlations explained by common SNPs for metabolic syndrome traits.

ABSTRACT: We used a bivariate (multivariate) linear mixed-effects model to estimate the narrow-sense heritability (h(2)) and heritability explained by the common SNPs (h(g)(2)) for several metabolic syndrome (MetS) traits and the genetic correlation between pairs of traits for the Atherosclerosis Risk in Communities (ARIC) genome-wide association study (GWAS) population. MetS traits included body-mass index (BMI), waist-to-hip ratio (WHR), systolic blood pressure (SBP), fasting glucose (GLU), fasting insulin (INS), fasting trigylcerides (TG), and fasting high-density lipoprotein (HDL). We found the percentage of h(2) accounted for by common SNPs to be 58% of h(2) for height, 41% for BMI, 46% for WHR, 30% for GLU, 39% for INS, 34% for TG, 25% for HDL, and 80% for SBP. We confirmed prior reports for height and BMI using the ARIC population and independently in the Framingham Heart Study (FHS) population. We demonstrated that the multivariate model supported large genetic correlations between BMI and WHR and between TG and HDL. We also showed that the genetic correlations between the MetS traits are directly proportional to the phenotypic correlations.

SUBMITTER: Vattikuti S

PROVIDER: S-EPMC3315484 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Heritability and genetic correlations explained by common SNPs for metabolic syndrome traits.

Vattikuti Shashaank S Guo Juen J Chow Carson C CC

PLoS genetics 20120329 3

We used a bivariate (multivariate) linear mixed-effects model to estimate the narrow-sense heritability (h(2)) and heritability explained by the common SNPs (h(g)(2)) for several metabolic syndrome (MetS) traits and the genetic correlation between pairs of traits for the Atherosclerosis Risk in Communities (ARIC) genome-wide association study (GWAS) population. MetS traits included body-mass index (BMI), waist-to-hip ratio (WHR), systolic blood pressure (SBP), fasting glucose (GLU), fasting insu ...[more]

PMID: 22479213

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Project description:BACKGROUND AND OBJECTIVES:Metabolic syndrome is a cluster of risk factors associated with CKD. By studying the genetic and environmental influences on how traits of metabolic syndrome correlate with CKD, the understanding of the etiological relationships can be improved. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS:From the population-based TwinGene project within the Swedish Twin Registry, 4721 complete twin pairs (9442 European ancestry participants) were included in this cross-sectional twin study. Metabolic syndrome-related continuous traits were measured, and the binary components as well as the status of metabolic syndrome were defined according to the National Cholesterol Education Program-Adult Treatment Panel III. The eGFR was calculated by cystatin C-based equations from the CKD epidemiology collaboration group, and CKD was defined by eGFR<60 ml/min per 1.73 m2. Genetic and environmental contributions to the correlations between traits of metabolic syndrome and CKD were estimated by using twin-based bivariate structural equation models. RESULTS:The correlation between metabolic syndrome and eGFR-defined CKD was 0.16 (95% confidence interval [95% CI], 0.12 to 0.20), out of which 51% (95% CI, 12% to 90%) was explained by genes, whereas 15% (95% CI, 0% to 42%) and 34% (95% CI, 16% to 52%) was explained by the shared and nonshared environment, respectively. The genetic and environmental correlations between metabolic syndrome and CKD were 0.29 (95% CI, 0.07 to 0.51) and 0.27 (95% CI, 0.13 to 0.41), respectively. For the correlation between abdominal obesity and eGFR, 69% (95% CI, 10% to 100%) was explained by genes and 23% (95% CI, 5% to 41%) was explained by environment. The genetic correlation between abdominal obesity and eGFR was -0.30 (95% CI, -0.54 to -0.06), whereas the environmental correlation was -0.14 (95% CI, -0.22 to -0.06). CONCLUSIONS:Both genes and environment contribute to the correlation between metabolic syndrome and eGFR-defined CKD. The genetic contribution is particularly important to the correlation between abdominal obesity and eGFR.

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Heritability and genetic correlations explained by common SNPs for metabolic syndrome traits.

Publications

Heritability and genetic correlations explained by common SNPs for metabolic syndrome traits.

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