Integrative Omics Approach to Identifying Genes Associated with Atrial Fibrillation

Research output: Contribution to journalArticle

Authors

External Institution(s)

  • Boston University
  • Mayo Clinic Rochester, MN

Details

Original languageEnglish (US)
Pages (from-to)350-360
Number of pages11
JournalCirculation research
StatusPublished - Jan 31 2020
Peer-reviewedYes

Abstract

Rationale: GWAS (Genome-Wide Association Studies) have identified hundreds of genetic loci associated with atrial fibrillation (AF). However, these loci explain only a small proportion of AF heritability. Objective: To develop an approach to identify additional AF-related genes by integrating multiple omics data. Methods and Results: Three types of omics data were integrated: (1) summary statistics from the AFGen 2017 GWAS; (2) a whole blood EWAS (Epigenome-Wide Association Study) of AF; and (3) a whole blood TWAS (Transcriptome-Wide Association Study) of AF. The variant-level GWAS results were collapsed into gene-level associations using fast set-based association analysis. The CpG-level EWAS results were also collapsed into gene-level associations by an adapted SNP-set Kernel Association Test approach. Both GWAS and EWAS gene-based associations were then meta-analyzed with TWAS using a fixed-effects model weighted by the sample size of each data set. A tissue-specific network was subsequently constructed using the NetWAS (Network-Wide Association Study). The identified genes were then compared with the AFGen 2018 GWAS that contained more than triple the number of AF cases compared with AFGen 2017 GWAS. We observed that the multiomics approach identified many more relevant AF-related genes than using AFGen 2018 GWAS alone (1931 versus 206 genes). Many of these genes are involved in the development and regulation of heart- and muscle-related biological processes. Moreover, the gene set identified by multiomics approach explained much more AF variance than those identified by GWAS alone (10.4% versus 3.5%). Conclusions: We developed a strategy to integrate multiple omics data to identify AF-related genes. Our integrative approach may be useful to improve the power of traditional GWAS, which might be particularly useful for rare traits and diseases with limited sample size. Visual Overview: An online visual overview is available for this article.

    Research areas

  • atrial fibrillation, cutoff, genes, genomics, statistics

Citation formats

APA

Wang, B., Lunetta, K. L., Dupuis, J., Lubitz, S. A., Trinquart, L., Yao, L., ... Lin, H. (2020). Integrative Omics Approach to Identifying Genes Associated with Atrial Fibrillation. Circulation research, 350-360. https://doi.org/10.1161/CIRCRESAHA.119.315179

Harvard