Shared genetic associations and aetiology between obstructive sleep apnoea and cardiovascular diseases: a genome-wide cross-trait analysis and bidirectional Mendelian randomization analysis.

IF 7.5 2区 医学 Q1 CARDIAC & CARDIOVASCULAR SYSTEMS European journal of preventive cardiology Pub Date : 2025-10-28 DOI:10.1093/eurjpc/zwae347
Kun Feng, Jinyue Yang, Kai Liu
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Abstract

Aims: Study aimed to investigate the genetic correlations and potential causal relationships between obstructive sleep apnoea (OSA) and various cardiovascular diseases (CVDs), aiming to enhance understanding of shared genetic mechanisms and improve recognition and treatment of OSA in patients with CVDs.

Methods and results: Utilizing genome-wide association study (GWAS) data, we analysed shared genetics between OSA and CVDs using linkage disequilibrium score regression, multi-trait analysis of GWAS (MTAG), and genotype-tissue expression analysis. We further investigated causal relationships using Bayesian co-localization tests, bidirectional Mendelian randomization, and latent causal variable analysis. We found strong associations between OSA and multiple CVDs: coronary artery disease (CAD), heart failure (HF), myocardial infarction (MI), stroke, and atrial fibrillation (AF). Novel single-nucleotide polymorphisms related to CVDs were identified during single-trait MTAG analysis. By applying cross-trait MTAG, we identified 15 shared loci between OSA and CAD, 25 shared loci between OSA and MI, and 7 shared loci between OSA and HF. Shared genes are primarily expressed in the blood, heart, kidney, liver, muscle, and pancreas. Mendelian randomization analysis indicated a significant causal effect of OSA on HF and AF as a causal factor for OSA. Latent causal variable analysis suggested that AF was causally associated with OSA, while HF showed partial causality.

Conclusion: Our study suggests strong genetic correlations between OSA and several CVDs. Further research is needed on the associations between OSA and CVDs, as well as the mechanisms of the identified loci.

Lay summary: This study explores the genetic links between obstructive sleep apnoea (OSA) and cardiovascular diseases (CVDs).Key findings are as follows:Strong genetic correlations were found between OSA and five CVDs: coronary artery disease, heart failure (HF), myocardial infarction, stroke, and atrial fibrillation. Novel correlated and causal loci were identified.Atrial fibrillation was identified as a causal factor for OSA, while OSA was a causal factor for HF.Future research is needed to explore these genetic mechanisms further and improve understanding of the connections between OSA and CVDs.

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阻塞性睡眠呼吸暂停与心血管疾病之间的共同遗传关联和病因:全基因组跨性状分析和双向孟德尔随机分析。
目的:研究阻塞性睡眠呼吸暂停(OSA)与各种心血管疾病(CVDs)之间的遗传相关性和潜在因果关系,旨在加深对共同遗传机制的理解,改善对心血管疾病患者OSA的识别和治疗:利用全基因组关联研究(GWAS)数据,我们使用关联不平衡评分回归(LDSC)、GWAS 多性状分析(MTAG)和基因型-组织表达分析(GTEx TSEA)分析了 OSA 和心血管疾病之间的共同遗传学机制。我们还使用贝叶斯共定位检验、双向孟德尔随机化(MR)和潜在因果变量(LCV)分析进一步研究了因果关系:结果:我们发现 OSA 与多种心血管疾病(冠状动脉疾病(CAD)、心力衰竭(HF)、心肌梗死(MI)、中风和心房颤动(AF))之间存在密切联系。在单性状 MTAG 分析中发现了与心血管疾病相关的新 SNPs。通过跨性状 MTAG 分析,我们在 OSA 和 CAD 之间发现了 15 个共享基因位点,在 OSA 和 MI 之间发现了 25 个共享基因位点,在 OSA 和 HF 之间发现了 7 个共享基因位点。共享基因主要在血液、心脏、肾脏、肝脏、肌肉和胰腺中表达。MR分析表明,OSA对HF有明显的因果效应,而房颤是OSA的一个因果因素。LCV分析表明,房颤与OSA存在因果关系,而高频则显示出部分因果关系:我们的研究表明,OSA 与多种心血管疾病之间存在密切的遗传相关性。结论:我们的研究表明,OSA 与几种心血管疾病之间存在很强的遗传相关性。对于 OSA 与心血管疾病之间的关联以及已确定基因位点的机制,还需要进一步研究。
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来源期刊
European journal of preventive cardiology
European journal of preventive cardiology CARDIAC & CARDIOVASCULAR SYSTEMS-
CiteScore
12.50
自引率
12.00%
发文量
601
审稿时长
3-8 weeks
期刊介绍: European Journal of Preventive Cardiology (EJPC) is an official journal of the European Society of Cardiology (ESC) and the European Association of Preventive Cardiology (EAPC). The journal covers a wide range of scientific, clinical, and public health disciplines related to cardiovascular disease prevention, risk factor management, cardiovascular rehabilitation, population science and public health, and exercise physiology. The categories covered by the journal include classical risk factors and treatment, lifestyle risk factors, non-modifiable cardiovascular risk factors, cardiovascular conditions, concomitant pathological conditions, sport cardiology, diagnostic tests, care settings, epidemiology, pharmacology and pharmacotherapy, machine learning, and artificial intelligence.
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