Receptor-interacting protein 2 (RIP2) gene polymorphisms are associated with increased risk of subclinical atherosclerosis and clinical and metabolic parameters. The Genetics of Atherosclerotic Disease (GEA) Mexican study

The receptor-interacting protein 2 (Rip2) is a serine/threonine kinase involved in multiple nuclear factor-KB (NFKB) activation pathways and is a key regulator of cellular lipid metabolism and cardiovascular disease. The aim of the present study was to evaluate the role of RIP2 gene polymorphisms as susceptibility markers for sub clinical atherosclerosis (SA). Using an informatics analysis, four RIP2 gene polymorphisms with predicted functional effects (rs2293808, rs43133, rs431264, and rs16900627) were selected. The polymorphisms were genotyped in 405 individuals with SA (calcium score > 0 assessed by computed tomography) and 1099 controls (calcium score = 0). Clinical, anthropometric, tomographic and biochemical traits were measured. The association between the RIP2 polymorphisms and SA was evaluated using logistic regression analyses. Pair wise linkage disequilibrium (LD, D') estimations between polymorphisms and haplotype reconstruction were performed with Haploview version 4:1. Under different models adjusted by age, gender, body mass index, hypertension, diabetes mellitus, smoking habit, total cholesterol, HDL-cholesterol, LDL-cholesterol and triglyceride levels, rs43133 (OR = 1.43,95% Cl: 1.05-1.94, P = 0.022), and rs16900627 (OR = 1.59, 95% Cl: 1.00-2.54, P-dom = 0.048 and OR = 1.60,95% Cl: 1.05-2.54, P-add = 0.028) were associated with increased risk of developing SA. Moreover, rs2293808, and rs431264 were associated with clinical or metabolic parameters in SA individuals and in healthy controls. The four polymorphisms were in high linkage disequilibrium and the GAAG haplotype was associated with increased risk of developing SA (OR = 1.47, P = 0.027). This study shows for the first time, that RIP2 polymorphisms are associated with increased risk of SA and with some clinical and metabolic parameters. (C) 2017 Elsevier Inc. All rights reserved.