4.6 Article

Heritability and Genetic Correlations Explained by Common SNPs for Metabolic Syndrome Traits

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PLOS GENETICS
卷 8, 期 3, 页码 -

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PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pgen.1002637

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资金

  1. NIH/NIDDK
  2. National Heart, Lung, and Blood Institute [N01-HC-55015, N01-HC-55016, N01-HC-55018, N01-HC-55019, N01-HC-55020, N01-HC-55021, N01-HC-55022, R01HL087641, R01HL59367, R01HL086694]
  3. National Human Genome Research Institute [U01HG004402]
  4. National Institutes of Health [HHSN268200625226C]
  5. National Institutes of Health and NIH Roadmap for Medical Research [UL1RR025005]
  6. National Heart, Lung, and Blood Institute (NHLBI) in collaboration with Boston University [N01-HC-25195, N02-HL-64278]

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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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