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Genetic Control of Left Atrial Gene Expression Yields Insights into the Genetic Susceptibility for Atrial Fibrillation.

ABSTRACT: BACKGROUND:Genome-wide association studies have identified 23 loci for atrial fibrillation (AF), but the mechanisms responsible for these associations, as well as the causal genes and genetic variants, remain undefined. METHODS:To identify the effect of common genetic variants on gene expression that might explain the mechanisms linking genome-wide association loci with AF risk, we performed RNA sequencing of left atrial appendages from a biracial cohort of 265 subjects. RESULTS:Combining gene expression data with genome-wide single nucleotide polymorphism data, we found that approximately two-thirds of the expressed genes were regulated in cis by common genetic variants at a false discovery rate of <0.05, defined as cis-expression quantitative trait loci. Twelve of 23 reported AF genome-wide association loci displayed genome-wide significant cis-expression quantitative trait loci, at PRRX1 (chromosome 1q24), SNRNP27 (1q24), CEP68 (2p14), FKBP7 (2q31), KCNN2 (5q22), FAM13B (5q31), CAV1 (7q31), ASAH1 (8p22), MYOZ1 (10q22), C11ORF45 (11q24), TBX5 (12q24), and SYNE2 (14q23), suggesting that altered expression of these genes plays a role in AF susceptibility. Allelic expression imbalance was used as an independent method to characterize the cis-control of gene expression. One thousand two hundred forty-eight of 5153 queried genes had cis-single nucleotide polymorphisms that significantly regulated allelic expression at a false discovery rate of <0.05. CONCLUSIONS:We provide a genome-wide catalog of the genetic control of gene expression in human left atrial appendage. These data can be used to confirm the relevance of genome-wide association loci and to direct future functional studies to identify the genes and genetic variants responsible for complex diseases such as AF.

SUBMITTER: Hsu J

PROVIDER: S-EPMC5858469 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

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Genetic Control of Left Atrial Gene Expression Yields Insights into the Genetic Susceptibility for Atrial Fibrillation.

Hsu Jeffrey J Gore-Panter Shamone S Tchou Gregory G Castel Laurie L Lovano Beth B Moravec Christine S CS Pettersson Gosta B GB Roselli Eric E EE Gillinov A Marc AM McCurry Kenneth R KR Smedira Nicholas G NG Barnard John J Van Wagoner David R DR Chung Mina K MK Smith Jonathan D JD

Circulation. Genomic and precision medicine 20180301 3

<h4>Background</h4>Genome-wide association studies have identified 23 loci for atrial fibrillation (AF), but the mechanisms responsible for these associations, as well as the causal genes and genetic variants, remain undefined.<h4>Methods</h4>To identify the effect of common genetic variants on gene expression that might explain the mechanisms linking genome-wide association loci with AF risk, we performed RNA sequencing of left atrial appendages from a biracial cohort of 265 subjects.<h4>Result ...[more]

PMID: 29545482

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Project description:BACKGROUND:Ablation is a widely used therapy for atrial fibrillation (AF); however, arrhythmia recurrence and repeat procedures are common. Studies examining surrogate markers of genetic susceptibility to AF, such as family history and individual AF susceptibility alleles, suggest these may be associated with recurrence outcomes. Accordingly, the aim of this study was to test the association between AF genetic susceptibility and recurrence after ablation using a comprehensive polygenic risk score for AF. METHODS:Ten centers from the AF Genetics Consortium identified patients who had undergone de novo AF ablation. AF genetic susceptibility was measured using a previously described polygenic risk score (N=929 single-nucleotide polymorphisms) and tested for an association with clinical characteristics and time-to-recurrence with a 3 month blanking period. Recurrence was defined as >30 seconds of AF, atrial flutter, or atrial tachycardia. Multivariable analysis adjusted for age, sex, height, body mass index, persistent AF, hypertension, coronary disease, left atrial size, left ventricular ejection fraction, and year of ablation. RESULTS:Four thousand two hundred seventy-six patients were eligible for analysis of baseline characteristics and 3259 for recurrence outcomes. The overall arrhythmia recurrence rate between 3 and 12 months was 44% (1443/3259). Patients with higher AF genetic susceptibility were younger (P<0.001) and had fewer clinical risk factors for AF (P=0.001). Persistent AF (hazard ratio [HR], 1.39 [95% CI, 1.22-1.58]; P<0.001), left atrial size (per cm: HR, 1.32 [95% CI, 1.19-1.46]; P<0.001), and left ventricular ejection fraction (per 10%: HR, 0.88 [95% CI, 0.80-0.97]; P=0.008) were associated with increased risk of recurrence. In univariate analysis, higher AF genetic susceptibility trended towards a higher risk of recurrence (HR, 1.08 [95% CI, 0.99-1.18]; P=0.07), which became less significant in multivariable analysis (HR, 1.06 [95% CI, 0.98-1.15]; P=0.13). CONCLUSIONS:Higher AF genetic susceptibility was associated with younger age and fewer clinical risk factors but not recurrence. Arrhythmia recurrence after AF ablation may represent a genetically different phenotype compared to AF susceptibility.

Project description:BackgroundAtrial fibrillation (AF) often arises from structural abnormalities in the left atria (LA). Annotation of the noncoding genome in human LA is limited, as are effects on gene expression and chromatin architecture. Many AF-associated genetic variants reside in noncoding regions; this knowledge gap impairs efforts to understand the molecular mechanisms of AF and cardiac conduction phenotypes.MethodsWe generated a model of the LA noncoding genome by profiling 7 histone post-translational modifications (active: H3K4me3, H3K4me2, H3K4me1, H3K27ac, H3K36me3; repressive: H3K27me3, H3K9me3), CTCF binding, and gene expression in samples from 5 individuals without structural heart disease or AF. We used MACS2 to identify peak regions (P<0.01), applied a Markov model to classify regulatory elements, and annotated this model with matched gene expression data. We intersected chromatin states with expression quantitative trait locus, DNA methylation, and HiC chromatin interaction data from LA and left ventricle. Finally, we integrated genome-wide association data for AF and electrocardiographic traits to link disease-related variants to genes.ResultsOur model identified 21 epigenetic states, encompassing regulatory motifs, such as promoters, enhancers, and repressed regions. Genes were regulated by proximal chromatin states; repressive states were associated with a significant reduction in gene expression (P<2×10-16). Chromatin states were differentially methylated, promoters were less methylated than repressed regions (P<2×10-16). We identified over 15 000 LA-specific enhancers, defined by homeobox family motifs, and annotated several cardiovascular disease susceptibility loci. Intersecting AF and PR genome-wide association studies loci with long-range chromatin conformation data identified a gene interaction network dominated by NKX2-5, TBX3, ZFHX3, and SYNPO2L.ConclusionsProfiling the noncoding genome provides new insights into the gene expression and chromatin regulation in human LA tissue. These findings enabled identification of a gene network underlying AF; our experimental and analytic approach can be extended to identify molecular mechanisms for other cardiac diseases and traits.

Dataset Information

Genetic Control of Left Atrial Gene Expression Yields Insights into the Genetic Susceptibility for Atrial Fibrillation.

Publications

Genetic Control of Left Atrial Gene Expression Yields Insights into the Genetic Susceptibility for Atrial Fibrillation.

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