Genetic and environmental contributions to phenotypic components of metabolic syndrome: a population-based twin study

Abstract

The increasing prevalence of metabolic syndrome (MS) poses a serious public-health problem worldwide. Effective prevention and intervention require improved understanding of the factors that contribute to MS. We analyzed data on a large twin cohort to estimate genetic and environmental contributions to MS and to major MS components and their intercorrelations: waist circumference (WC), systolic (SBP) and diastolic blood pressure (DBP), fasting plasma glucose (FPG), triglycerides (TGs), and high-density lipoprotein-cholesterol (HDL-C). We applied structural equation modeling to determine genetic and environmental structure of MS and its major components, using 1,617 adult female twin pairs recruited from rural China. The heritability estimate for MS was 0.42 (95% confidence interval (CI): 0.00-0.83) in this sample with low MS prevalence (4.4%). For MS components, heritability estimates were statistically significant and ranged from 0.13 to 0.64 highest for WC, followed by TG, SBP, DBP, HDL-C, and FPG. HDL-C was mainly influenced by common environmental factors (0.62, 95% CI: 0.58-0.62), whereas the other five MS components were largely influenced by unique environmental factors (0.32-0.44). Bivariate Cholesky decomposition analysis indicated that the clinical clustering of MS components may be explained by shared genetic and/or environmental factors. Our study underscores the importance of examining MS components as intercorrelated traits, and to carefully consider environmental and genetic factors in studying MS etiology.

Figure. 1

Genetic and environmental contributions to the phenotypic correlations of SBP and DBP in 1617 female Chinese twin pairs adjusted with age; r_G, r_C and r_E, genetic, common, and unique environmental correlation; a², c², and e², percentage of total phenotypic variance accounted for by genetic factors, common environmental factors, and unique environmental factors; r_TP, total phenotypic correlation; C_GCP, Genetic contribution to total phenotypic correlation; C_CCP, common environmental contribution to total phenotypic correlation; C_UCP, unique environmental contribution to total phenotypic correlation.