Samuel Harwood , M. Benjamin Shoemaker , John Barnard , David R. Van Wagoner , Daniel P. Morin , Mina K. Chung
{"title":"房颤基因组学:用遗传学预测房颤治疗后的复发。","authors":"Samuel Harwood , M. Benjamin Shoemaker , John Barnard , David R. Van Wagoner , Daniel P. Morin , Mina K. Chung","doi":"10.1016/j.pcad.2025.06.008","DOIUrl":null,"url":null,"abstract":"<div><div>With the demonstration that AF is highly hereditable and strongly associated with over 100 genetic loci, one step towards personalized treatment of AF is the potential use of genetic testing to predict response to therapy. Although various clinical models have been developed to predict recurrence, none have shown a consistent ability to predict treatment outcomes. This highlights a need for additional patient information to increase predictive value. Here, we review the use of genetic data for prediction of AF recurrence after interventions such as ablation, cardioversion, or drug therapy. We explore the use of other downstream predictors, such as mRNA and protein, as other possible predictive tools. Finally, we assess how this genetic data can further our mechanistc understanding of AF pathogenesis and recurrence.</div></div>","PeriodicalId":21156,"journal":{"name":"Progress in cardiovascular diseases","volume":"91 ","pages":"Pages 62-66"},"PeriodicalIF":7.6000,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Genomics in atrial fibrillation: Predicting recurrence of AF after treatment using genetics\",\"authors\":\"Samuel Harwood , M. Benjamin Shoemaker , John Barnard , David R. Van Wagoner , Daniel P. Morin , Mina K. Chung\",\"doi\":\"10.1016/j.pcad.2025.06.008\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>With the demonstration that AF is highly hereditable and strongly associated with over 100 genetic loci, one step towards personalized treatment of AF is the potential use of genetic testing to predict response to therapy. Although various clinical models have been developed to predict recurrence, none have shown a consistent ability to predict treatment outcomes. This highlights a need for additional patient information to increase predictive value. Here, we review the use of genetic data for prediction of AF recurrence after interventions such as ablation, cardioversion, or drug therapy. We explore the use of other downstream predictors, such as mRNA and protein, as other possible predictive tools. Finally, we assess how this genetic data can further our mechanistc understanding of AF pathogenesis and recurrence.</div></div>\",\"PeriodicalId\":21156,\"journal\":{\"name\":\"Progress in cardiovascular diseases\",\"volume\":\"91 \",\"pages\":\"Pages 62-66\"},\"PeriodicalIF\":7.6000,\"publicationDate\":\"2025-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Progress in cardiovascular diseases\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0033062025000866\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CARDIAC & CARDIOVASCULAR SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Progress in cardiovascular diseases","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0033062025000866","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
Genomics in atrial fibrillation: Predicting recurrence of AF after treatment using genetics
With the demonstration that AF is highly hereditable and strongly associated with over 100 genetic loci, one step towards personalized treatment of AF is the potential use of genetic testing to predict response to therapy. Although various clinical models have been developed to predict recurrence, none have shown a consistent ability to predict treatment outcomes. This highlights a need for additional patient information to increase predictive value. Here, we review the use of genetic data for prediction of AF recurrence after interventions such as ablation, cardioversion, or drug therapy. We explore the use of other downstream predictors, such as mRNA and protein, as other possible predictive tools. Finally, we assess how this genetic data can further our mechanistc understanding of AF pathogenesis and recurrence.
期刊介绍:
Progress in Cardiovascular Diseases provides comprehensive coverage of a single topic related to heart and circulatory disorders in each issue. Some issues include special articles, definitive reviews that capture the state of the art in the management of particular clinical problems in cardiology.