Atrial Fibrillation (AF), the most common sustained arrhythmia, has a strong genetic component, but the mechanism by which common genetic variants lead to increased AF susceptibility is unknown. Genome-wide association studies (GWAS) have identified that the single nucleotide polymorphisms (SNPs) most strongly associated with AF are located on chromosome 4q25 in an intergenic region distal to the PITX2 gene. Our objective was to determine whether the AF-associated SNPs on chromosome 4q25 were associated with PITX2c expression in adult human left atrial appendages. Analysis of a lone AF GWAS identified four independent AF risk SNPs at chromosome 4q25. Human adult left atrial appendage tissue was obtained from 239 subjects of European Ancestry and used for SNP analysis of genomic DNA and determination of PITX2c RNA expression levels by quantitative PCR. Subjects were divided into three groups based on their history of AF and pre-operative rhythm. AF rhythm subjects had higher PITX2c expression than those with history of AF but in sinus rhythm. PITX2c expression was not associated with the AF risk SNPs in human adult left atrial appendages in all subjects combined or in each of the three subgroups. However, we identified seven SNPs modestly associated with PITX2c expression located in the introns of the ENPEP gene, ∼54 kb proximal to PITX2. PITX2c expression in human adult left atrial appendages is not associated with the chromosome 4q25 AF risk SNPs; thus, the mechanism by which these SNPs are associated with AF remains enigmatic.

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Introduction: Over 135 genetic loci have been linked to atrial fibrillation (AF), yet the biological pathways of AF pathophysiology remain elusive. Weighted gene coexpression network analysis (WGCNA) constructs gene modules within a network based on correlations in gene expression, and identifies mechanisms related to AF risk. Objective: To identify biological pathways of candidate AF risk genes that will advance our understanding of AF mechanisms. Methods: RNA-sequencing was performed on left atrial appendage tissue from 265 patients. RNA-seq data were adjusted for differences in AF rhythm state and other known AF risk factors. Correlations from adjusted data were further adjusted for latent factors then spatial quantile normalized to correct for mean-variance bias. WGCNA was applied to the resulting adjusted and normalized gene-gene correlations to identify gene modules. Ingenuity Pathway Analysis and gene set over representation analysis (GSOR) were applied to each module. Results: WGCNA identified 63 modules from 17,434 genes; 47 of these contained at least one candidate AF risk gene. AF risk genes were overrepresented in 7 modules (Table 1). Notable top pathways of AF overrepresented modules include apelin signaling, heme metabolism, intracellular ion homeostasis, and the unfolded protein response. These are known to be involved in calcium signaling, iron homeostasis, glucose regulation, heat shock response, and protein ubiquitination during states of high energy demand and stress. These pathways coincide with larger cellular processes of myocyte remodeling, apoptosis, and cell survival, which were also prominent. Conclusions: Biological pathways identified through WGCNA and GSOR suggest that sustained increases in energy demand during AF promotes stress-induced cellular remodeling. Changes in calcium signaling, iron homeostasis, the unfolded protein response and glucose regulation are likely primary mechanisms of AF pathophysiology.