A Network and Pathway Analysis of Genes Associated With Atrial Fibrillation

IF 3.4 4区医学 Q2 CARDIAC & CARDIOVASCULAR SYSTEMS Cardiovascular Therapeutics Pub Date : 2024-10-04 DOI:10.1155/2024/7054039

Mengying Zeng, Xian Yang, Yunhao Chen, Jinqi Fan, Li Cao, Menghao Wang, Peilin Xiao, Zhiyu Ling, Yuehui Yin, Yunlin Chen

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Abstract

Background: Atrial fibrillation (AF) is affected by both environmental and genetic factors. Previous genetic association studies, especially genome-wide association studies, revealed a large group of AF-associated genes. However, little is known about the functions and interactions of these genes. Moreover, established genetic variants of AF contribute modestly to AF variance, implying that numerous additional AF-associated genetic variations need to be identified. Hence, a systematic network and pathway analysis is needed.

Methods: We retrieved all AF-associated genes from genetic association studies in various databases and performed integrative analyses including pathway enrichment analysis, pathway crosstalk analysis, network analysis, and microarray meta-analysis.

Results: We collected 254 AF-associated genes from genetic association studies in various databases. Pathway enrichment analysis revealed the top biological pathways that were enriched in the AF-associated genes related to cardiac electromechanical activity. Pathway crosstalk analysis showed that numerous neuro-endocrine-immune pathways connected AF with various diseases including cancers, inflammatory diseases, and cardiovascular diseases. Furthermore, an AF-specific subnetwork was constructed with the prize-collecting Steiner forest algorithm based on the AF-associated genes, and 24 novel genes that were potentially associated with AF were inferred by the subnetwork. In the microarray meta-analysis, six of the 24 novel genes (APLP1, CREB1, CREBBP, PRMT1, IRAK1, and PLXND1) were expressed differentially in patients with AF and sinus rhythm.

Conclusions: AF is not only an isolated disease with abnormal electrophysiological activity but might also share a common genetic basis and biological process with tumors and inflammatory diseases as well as cardiovascular diseases. Moreover, the six novel genes inferred from network analysis might help detect the missing AF risk loci.

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心房颤动相关基因的网络和通路分析

背景：心房颤动（房颤）受环境和遗传因素的双重影响。以往的遗传关联研究，尤其是全基因组关联研究，发现了一大批心房颤动相关基因。然而，人们对这些基因的功能和相互作用知之甚少。此外，已确定的心房颤动基因变异对心房颤动变异的影响不大，这意味着还需要确定更多与心房颤动相关的基因变异。因此，需要进行系统的网络和通路分析：方法：我们从各种数据库的遗传关联研究中检索了所有心房颤动相关基因，并进行了综合分析，包括通路富集分析、通路串联分析、网络分析和芯片荟萃分析：我们从各种数据库的遗传关联研究中收集了 254 个房颤相关基因。通路富集分析揭示了房颤相关基因中与心脏机电活动相关的顶级生物通路。通路串联分析表明，许多神经-内分泌-免疫通路将心房颤动与癌症、炎症性疾病和心血管疾病等多种疾病联系在一起。此外，基于心房颤动相关基因，利用有奖收集的斯坦纳森林算法构建了心房颤动特异性子网络，并通过该子网络推断出 24 个可能与心房颤动相关的新基因。在微阵列荟萃分析中，24个新基因中有6个（APLP1、CREB1、CREBBP、PRMT1、IRAK1和PLXND1）在房颤患者和窦性心律患者中表达不同：结论：房颤不仅是一种电生理活动异常的独立疾病，而且可能与肿瘤、炎症性疾病以及心血管疾病有着共同的遗传基础和生物学过程。此外，通过网络分析推断出的六个新基因可能有助于发现缺失的房颤风险位点。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Cardiovascular Therapeutics 医学-心血管系统

CiteScore

5.60

自引率

0.00%

发文量

审稿时长

6 months

期刊介绍： Cardiovascular Therapeutics (formerly Cardiovascular Drug Reviews) is a peer-reviewed, Open Access journal that publishes original research and review articles focusing on cardiovascular and clinical pharmacology, as well as clinical trials of new cardiovascular therapies. Articles on translational research, pharmacogenomics and personalized medicine, device, gene and cell therapies, and pharmacoepidemiology are also encouraged. Subject areas include (but are by no means limited to): Acute coronary syndrome Arrhythmias Atherosclerosis Basic cardiac electrophysiology Cardiac catheterization Cardiac remodeling Coagulation and thrombosis Diabetic cardiovascular disease Heart failure (systolic HF, HFrEF, diastolic HF, HFpEF) Hyperlipidemia Hypertension Ischemic heart disease Vascular biology Ventricular assist devices Molecular cardio-biology Myocardial regeneration Lipoprotein metabolism Radial artery access Percutaneous coronary intervention Transcatheter aortic and mitral valve replacement.