Replicated gene expression changes in patients with atrial fibrillation

Abstract

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – EU funding. Main funding source(s): European Union Horizon 2020 CATCH ME; Cardiovascular Research Netherlands RACE V Background Little is known about changes in the atrial transcriptome associated with paroxysmal and persistent atrial fibrillation (AF). Purpose To identify major molecular mechanisms in AF, we determined consistent differential expression (DE) between atrial tissue samples from well-characterized patients with paroxysmal or persistent AF and patients without a history of AF (no AF) in two independent patient cohorts. Methods Poly-A tailed RNA from left and right atrial appendage tissue samples from independent discovery and replication cohorts CATCH ME (n=192) and RACE V (n=122) was sequenced and analyzed according to patient AF history. Analyses were performed stratified by atrial side, adjusting for age, sex, heart failure and a combination of clinical characteristics determined by principal component analysis. Transcripts were considered DE in CATCH ME if their fold change reached transcriptome-wide significance (false discovery rate (FDR) < 0.05). DE transcripts in each rhythm comparison were replicated in RACE V if we observed a concordant direction of effect and a within-set FDR < 0.05 in the same comparison. Results Persistent AF compared to no AF was associated with 184 left atrial DE transcripts in CATCH ME of which 85 (46%) were replicated in RACE V, and with 208 right atrial DE transcripts in CATCH ME of which 86 (41%) were replicated in RACE V. Overall, 26 transcripts were discovered and replicated in both atria. Discovered but non-replicated transcripts often did exhibit concordant direction of effect (left: 78%, right: 83%). Replicated transcripts consisted of protein coding genes, antisense and non-coding RNAs. Protein coding genes showed involvement in pathways linking persistent AF to cardiomyocyte structure, conduction properties, fibrosis, inflammation, molecule trafficking, and endothelial dysfunction. Interestingly, paroxysmal AF was not consistently associated with DE transcripts in any comparison. Principal component analysis of the expression of the 26 transcripts strongly associated with persistent AF did however reveal a distinct paroxysmal AF expression profile in-between no AF and persistent AF patients in the first principal component scores (Figure 1). Conclusion RNA sequencing of human atrial tissue samples identified many transcripts associated with persistent AF in left and/or right atria, discovered and replicated using two independent cohorts. These consistent findings of AF-induced changes provide a starting point for targeted proteomic analysis and single-nucleus sequencing to further unravel the molecular mechanisms underlying AF progression to persistent AF, and biomarker development to quantify AF progression and enable precision medicine in individual patients.