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 g2) 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. © 2012 This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.
CITATION STYLE
Vattikuti, S., Guo, J., & Chow, C. C. (2012). Heritability and genetic correlations explained by common SNPS for metabolic syndrome traits. PLoS Genetics, 8(3). https://doi.org/10.1371/journal.pgen.1002637
Mendeley helps you to discover research relevant for your work.