Prediction of Metabolic Syndrome Based on Genetic Risk Score of HDL and TG Using the Reference-Free GBLUP Model; Tehran Cardiometabolic and Genetic Study (TCGS)

Background and aim: Metabolic syndrome (MetS) is a complex disorder defined by a cluster of interconnected factors that increase the risk of cardiovascular atherosclerotic diseases and diabetes mellitus type ۲. Recent genome-wide association studies (GWAS) on MetS identified several loci located mostly near genes regulating lipid metabolism. Also, elevated triglycerides (TG) and low high-density lipoproteins (HDL) are two of MetS main components. Therefore, detection of the susceptibility of dyslipidemia at an early age becomes a critical step to human health care. In this regard, the genomic risk score that aggregates the proportion of phenotypic variation that can be explained by genetic variants can play a critical role. In the following study, we estimate the genetic risk prediction of TG and HDL for individuals and evaluate their predictory power on MetS in the Tehranian population.Material and Methods: We considered adult participants (age>۱۸) from Tehran Cardiometabolic Genetic Study (TCGS) for whom MetS information are available, which contains ۸۸۸۷ people (۳۹۶۳ males and ۴۹۲۴ females) with ۵۴۶۳۳۹ single nucleotide variants after data cleaning (using Plink, SAGE, SNP۱۱۰۱, Beagle software). To estimate the genetic risk score (GRS) of TG and HDL, we have applied the entire genetic variants performing the genomic best linear unbiased prediction (GBLUP) model using a reference-free approach presented in GCTA software. The performance of TG and HDL generic risk score to detect MetS has been evaluated using the receiver operating characteristic (ROC) curve.Results: The average estimated standardized GRS of TG and HDL in the Tehranian participants obtained -۰.۰۱۳۵ for MetS and ۰.۰۱۵۵ for non-MetS and ۰.۲۵۵۰ for MetS and -۰.۳۸۲۲ for non-MetS respectively, which the difference between two groups was statistically significant in both phenotypes (p-value < ۲.۲e-۱۶). Moreover, the predictive GRS of TG and HDL adjusted on age, sex, and body mass index (BMI) revealed a powerful performance to predict MetS with the area under the curve (AUC) of ۰.۸۴۲.Conclusion: Our findings on adult Tehranian participants coming from the TCGS project showed genetic factors are likely to play important roles in the pathogenesis of the MetS. The genetic risk score of TG and HDL estimating based on entire genetic variants showed a reliable performance on prediction MetS, though still further research is needed to clarify the role of genetic variation and epigenetic mechanisms in the development of the MetS.

کلیدواژه ها:

Genetic risk score ، MetS ، high-density lipoprotein ، triglyceride ، Genetic Prediction ، GBLUP ، TCGS