Multi-variant study of obesity risk genes in African Americans: The Jackson Heart Study

Shijian Liu, James G. Wilson, Fan Jiang, Michael Griswold, Adolfo Correa, Hao Mei

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Objective Genome-wide association study (GWAS) has been successful in identifying obesity risk genes by single-variant association analysis. For this study, we designed steps of analysis strategy and aimed to identify multi-variant effects on obesity risk among candidate genes. Methods Our analyses were focused on 2137 African American participants with body mass index measured in the Jackson Heart Study and 657 common single nucleotide polymorphisms (SNPs) genotyped at 8 GWAS-identified obesity risk genes. Results Single-variant association test showed that no SNPs reached significance after multiple testing adjustment. The following gene-gene interaction analysis, which was focused on SNPs with unadjusted p-value < 0.10, identified 6 significant multi-variant associations. Logistic regression showed that SNPs in these associations did not have significant linear interactions; examination of genetic risk score evidenced that 4 multi-variant associations had significant additive effects of risk SNPs; and haplotype association test presented that all multi-variant associations contained one or several combinations of particular alleles or haplotypes, associated with increased obesity risk. Conclusions Our study evidenced that obesity risk genes generated multi-variant effects, which can be additive or non-linear interactions, and multi-variant study is an important supplement to existing GWAS for understanding genetic effects of obesity risk genes.

Original languageEnglish (US)
Pages (from-to)315-321
Number of pages7
JournalGene
Volume593
Issue number2
DOIs
StatePublished - Nov 30 2016
Externally publishedYes

Keywords

  • Gene-gene interaction
  • Genetic risk score
  • Haplotype
  • Obesity
  • SNP association

ASJC Scopus subject areas

  • Medicine(all)
  • Genetics

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