Human genomics · 2025
Genetic insights into cardiac conduction disorders from genome-wide association studies.
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Li Bingxun, Xu Hongxuan, Wu Lin
Аннотация
BACKGROUND: Substantial data support a heritable basis for cardiac conduction disorders (CCDs), but the genetic determinants and molecular mechanisms of these arrhythmias are poorly understood, therefore, we sought to identify genetic loci associated with CCDs.
METHODS: We performed meta-analyses of genome-wide association studies to identify genetic loci for atrioventricular block (AVB), left bundle branch block (LBBB), and right bundle branch block (RBBB) from public data from the UK Biobank and FinnGen consortium. We assessed evidence supporting the potential causal effects of candidate genes by analyzing relations between associated variants and cardiac gene expression, performing transcriptome-wide analyses, and ECG-wide phenome-wide associations for each indexed SNP.
RESULTS: Analysis comprised over 700,000 individuals for each trait. We identified 10, 4 and 0 significant loci for AVB (PLEKHA3, TTN, FNDC3B, SENP2, SCN10A, RRH, PPARGC1A, PKD2L2, NKX2-5 and TBX20), LBBB (PPARGC1A, HAND1, TBX5, and ADAMTS5) and RBBB, respectively. Transcriptome-wide association analysis supported an association between reduced predicted cardiac expression of SCN10A and AVB. Phenome-wide associations identified traits with both cardiovascular and non- cardiovascular traits with indexed SNPs.
CONCLUSIONS: Our analysis highlight gene regions associated with channel function, cardiac development, sarcomere function and energy modulation as important potential effectors of CCDs susceptibility.
METHODS: We performed meta-analyses of genome-wide association studies to identify genetic loci for atrioventricular block (AVB), left bundle branch block (LBBB), and right bundle branch block (RBBB) from public data from the UK Biobank and FinnGen consortium. We assessed evidence supporting the potential causal effects of candidate genes by analyzing relations between associated variants and cardiac gene expression, performing transcriptome-wide analyses, and ECG-wide phenome-wide associations for each indexed SNP.
RESULTS: Analysis comprised over 700,000 individuals for each trait. We identified 10, 4 and 0 significant loci for AVB (PLEKHA3, TTN, FNDC3B, SENP2, SCN10A, RRH, PPARGC1A, PKD2L2, NKX2-5 and TBX20), LBBB (PPARGC1A, HAND1, TBX5, and ADAMTS5) and RBBB, respectively. Transcriptome-wide association analysis supported an association between reduced predicted cardiac expression of SCN10A and AVB. Phenome-wide associations identified traits with both cardiovascular and non- cardiovascular traits with indexed SNPs.
CONCLUSIONS: Our analysis highlight gene regions associated with channel function, cardiac development, sarcomere function and energy modulation as important potential effectors of CCDs susceptibility.