{"title":"心房颤动相关基因的网络和通路分析","authors":"Mengying Zeng, Xian Yang, Yunhao Chen, Jinqi Fan, Li Cao, Menghao Wang, Peilin Xiao, Zhiyu Ling, Yuehui Yin, Yunlin Chen","doi":"10.1155/2024/7054039","DOIUrl":null,"url":null,"abstract":"<p><b>Background:</b> 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.</p><p><b>Methods:</b> 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.</p><p><b>Results:</b> 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 (<i>APLP1</i>, <i>CREB1</i>, <i>CREBBP</i>, <i>PRMT1</i>, <i>IRAK1</i>, and <i>PLXND1</i>) were expressed differentially in patients with AF and sinus rhythm.</p><p><b>Conclusions:</b> 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.</p>","PeriodicalId":9582,"journal":{"name":"Cardiovascular Therapeutics","volume":"2024 1","pages":""},"PeriodicalIF":3.4000,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/7054039","citationCount":"0","resultStr":"{\"title\":\"A Network and Pathway Analysis of Genes Associated With Atrial Fibrillation\",\"authors\":\"Mengying Zeng, Xian Yang, Yunhao Chen, Jinqi Fan, Li Cao, Menghao Wang, Peilin Xiao, Zhiyu Ling, Yuehui Yin, Yunlin Chen\",\"doi\":\"10.1155/2024/7054039\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><b>Background:</b> 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.</p><p><b>Methods:</b> 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.</p><p><b>Results:</b> 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 (<i>APLP1</i>, <i>CREB1</i>, <i>CREBBP</i>, <i>PRMT1</i>, <i>IRAK1</i>, and <i>PLXND1</i>) were expressed differentially in patients with AF and sinus rhythm.</p><p><b>Conclusions:</b> 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.</p>\",\"PeriodicalId\":9582,\"journal\":{\"name\":\"Cardiovascular Therapeutics\",\"volume\":\"2024 1\",\"pages\":\"\"},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2024-10-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/7054039\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cardiovascular Therapeutics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1155/2024/7054039\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CARDIAC & CARDIOVASCULAR SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cardiovascular Therapeutics","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1155/2024/7054039","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
A Network and Pathway Analysis of Genes Associated With Atrial Fibrillation
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.
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.