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PLoS Genet. 2012;8(3):e1002637. doi: 10.1371/journal.pgen.1002637. Epub 2012 Mar 29.

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

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Laboratory of Biological Modeling, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health (NIH), Bethesda, Maryland, United States of America.

Erratum in

  • PLoS Genet. 2012 Jun;8(6). doi: 10.1371/annotation/8f3f1f56-6731-486e-8d55-5fa09b476cad.
  • PLoS Genet. 2012 Jun;8(6). doi:10.1371/annotation/61bb5924-6688-4ee5-a37f-d48aa09ad66a.


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.

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Conflict of interest statement

The authors have declared that no competing interests exist.

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