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.