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

Erfan Aref-Eshghi,
Oliver Hurley,
Guang Sun,
Alvin Simms,
Marshall Godwin,
Pauline Duke,
Mehdee Araee,
Masoud Mahdavian and
Shabnam AsghariEmail author View ORCID ID profile

BMC Medical Genetics201819:205

https://doi.org/10.1186/s12881-018-0719-1

Received: 16 July 2018
Accepted: 14 November 2018
Published: 29 November 2018

Open Peer Review reports

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.