Genetic associations in community context: a mixed model approach identifies a functional variant in the RBP4 gene associated with HDL-C dyslipidemia

Abstract

Abstract Background The objective of this study was to examine individual and community factors that influence high-density lipoprotein cholesterol (HDL-C) dyslipidemia in Newfoundland and Labrador (NL), a genetically isolated population in Canada with a high prevalence of HDL-C dyslipidemia. Methods First, a group of single nucleotide polymorphisms from 10 metabolic trait candidate genes was tested using a multivariate logistic regression model. The significant SNPs were entered into the second phase, where a mixed logistic model incorporated the community disease risk factors together with the individual factors as the fixed part of the model and the geographic region as a random effect. Results Analysis of 1489 subjects (26.9% HDL-C dyslipidemia) identified rs3758539, a non-coding variant in the 5’UTR of RBP4, to be associated with HDL-C dyslipidemia (odds ratio = 1.45, 95% confidence interval = 1.08–1.97, p = 0.01). The association remained significant, and the effect size did not change after the incorporation of individual and community risk factors from 17 geographic regions (odds ratio: 1.41, 95% confidence interval = 1.03–1.93, p = 0.03) in NL. Besides this variant, sex, BMI, and smoking also showed significant associations with HDL-C dyslipidemia, whereas no role was identified for the community factors. Conclusions This study demonstrates the use of community-level data in a genetic association testing. It reports a functional variant in the promoter of RBP4, a gene directly involved in lipoprotein metabolism, to be associated with HDL-C dyslipidemia. These findings indicate that individual factors are the main reason for a higher prevalence of HDL-C dyslipidemia in the NL population.

Keywords

• HDL
• Dyslipidemia
• RBP4
• Mixed model
• Genetics
• Associations