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

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 Comm...

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Bibliographic Details
Published in:PLoS genetics 2012-03, Vol.8 (3), p.e1002637-e1002637
Main Authors: Vattikuti, Shashaank, Guo, Juen, Chow, Carson C
Format: Article
Language:English
Subjects:
Atherosclerosis
Atherosclerosis - genetics
Atherosclerosis - metabolism
Biology
Blood Glucose
Blood Pressure
Body Mass Index
Development and progression
Diabetes Mellitus, Type 2 - complications
Diabetes Mellitus, Type 2 - genetics
Estimates
Fasting
Genetic aspects
Genetics
Genome-Wide Association Study
Genomes
Heart
Heritability
Humans
Insulin - blood
Lipoproteins, HDL - blood
Metabolic diseases
Metabolic syndrome
Metabolic Syndrome - complications
Metabolic Syndrome - genetics
Obesity
Phenotype
Physiological aspects
Polymorphism, Single Nucleotide - genetics
Population
Risk Factors
Statistics as Topic
Triglycerides - blood
Waist-Hip Ratio
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Summary: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.
ISSN:1553-7404
1553-7390
1553-7404
DOI:10.1371/journal.pgen.1002637