A 6-CpG Validated Methylation Risk Score Model for Metabolic Syndrome: The HyperGEN and GOLDN Studies

Abstract

There has been great interest in genetic risk prediction using risk scores in recent years, however, the utility of scores developed in European populations and later applied to non-European populations has not been successful. In this study, we used cross-sectional data from the Hypertension Genetic Epidemiology Network (HyperGEN, N=614 African Americans (AA)) and the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN, N=995 European Americans (EA)), to create a methylation risk score (MRS) for metabolic syndrome (MetS), demonstrating the utility of MRS across race groups. To demonstrate this, we first selected cytosine-guanine dinucleotides (CpG) sites measured on Illumina Methyl450 arrays previously reported to be significantly associated with MetS and/or component conditions (CPT1A cg00574958, PHOSPHO1 cg02650017, ABCG1 cg06500161, SREBF1 cg11024682, SOCS3 cg18181703, TXNIP cg19693031). Second, we calculated the parameter estimates for the 6 CpGs in the HyperGEN data and used the beta estimates as weights to construct a MRS in HyperGEN, which was validated in GOLDN. We performed association analyses using a logistic mixed model to test the association between the MRS and MetS adjusting for covariates. Results showed the MRS was significantly associated with MetS in both populations. In summary, a MRS for MetS was a strong predictor for the condition across two ethnic groups suggesting MRS may be useful to examine metabolic disease risk or related complications across ethnic groups.