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Novel functional atrial fibrillation risk genes and pathways identified from coexpression analyses in human left atria

候选基因 生物 基因 遗传学 生物途径 基因调控网络 全基因组关联研究 计算生物学 单核苷酸多态性 生物信息学 基因表达 基因型
作者
Sojin Youn Wass,Erik Offerman,Han Sun,Jeffrey Hsu,Julie H. Rennison,Catherine Cantlay,Meghan McHale,A. Marc Gillinov,Christine S. Moravec,Jonathan Smith,David R. Van Wagoner,John Barnard,Mina K. Chung
出处
期刊:Heart Rhythm [Elsevier BV]
卷期号:20 (9): 1219-1226 被引量:1
标识
DOI:10.1016/j.hrthm.2023.05.035
摘要

BackgroundGenomewide association studies have associated >100 genetic loci with atrial fibrillation (AF), but establishing causal genes contributing to AF remains challenging.ObjectiveThe purpose of this study was to determine candidate novel causal genes and mechanistic pathways associated with AF risk loci by incorporating gene expression and coexpression analyses and to provide a resource for functional studies and targeting of AF-associated genes.MethodsCis-expression quantitative trait loci were identified for candidate genes near AF risk variants in human left atrial tissues. Coexpression partners were identified for each candidate gene. Weighted gene coexpression network analysis (WGCNA) identified modules and modules with overrepresentation of candidate AF genes. Ingenuity pathway analysis (IPA) was applied to the coexpression partners of each candidate gene. IPA and gene set over representation analysis were applied to each WGCNA module.ResultsOne hundred sixty-six AF-risk single nucleotide polymorphisms were located in 135 loci. Eighty-one novel genes not previously annotated as putative AF risk genes were identified. IPA identified mitochondrial dysfunction, oxidative stress, epithelial adherens junction signaling, and sirtuin signaling as the most frequent significant pathways. WGCNA characterized 64 modules (candidate AF genes overrepresented in 8), represented by cell injury, death, stress, developmental, metabolic/mitochondrial, transcription/translation, and immune activation/inflammation regulatory pathways.ConclusionCandidate gene coexpression analyses suggest significant roles for cellular stress and remodeling in AF, supporting a dual risk model for AF: Genetic susceptibility to AF may not manifest until later in life, when cellular stressors overwhelm adaptive responses. These analyses also provide a novel resource to guide functional studies on potential causal AF genes. Genomewide association studies have associated >100 genetic loci with atrial fibrillation (AF), but establishing causal genes contributing to AF remains challenging. The purpose of this study was to determine candidate novel causal genes and mechanistic pathways associated with AF risk loci by incorporating gene expression and coexpression analyses and to provide a resource for functional studies and targeting of AF-associated genes. Cis-expression quantitative trait loci were identified for candidate genes near AF risk variants in human left atrial tissues. Coexpression partners were identified for each candidate gene. Weighted gene coexpression network analysis (WGCNA) identified modules and modules with overrepresentation of candidate AF genes. Ingenuity pathway analysis (IPA) was applied to the coexpression partners of each candidate gene. IPA and gene set over representation analysis were applied to each WGCNA module. One hundred sixty-six AF-risk single nucleotide polymorphisms were located in 135 loci. Eighty-one novel genes not previously annotated as putative AF risk genes were identified. IPA identified mitochondrial dysfunction, oxidative stress, epithelial adherens junction signaling, and sirtuin signaling as the most frequent significant pathways. WGCNA characterized 64 modules (candidate AF genes overrepresented in 8), represented by cell injury, death, stress, developmental, metabolic/mitochondrial, transcription/translation, and immune activation/inflammation regulatory pathways. Candidate gene coexpression analyses suggest significant roles for cellular stress and remodeling in AF, supporting a dual risk model for AF: Genetic susceptibility to AF may not manifest until later in life, when cellular stressors overwhelm adaptive responses. These analyses also provide a novel resource to guide functional studies on potential causal AF genes.
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