Julia Ramírez, Stefan van Duijvenboden, William J Young, Michele Orini, Aled R Jones, Pier D Lambiase, Patricia B Munroe, Andrew Tinker
{"title":"Analysing electrocardiographic traits and predicting cardiac risk in UK biobank.","authors":"Julia Ramírez, Stefan van Duijvenboden, William J Young, Michele Orini, Aled R Jones, Pier D Lambiase, Patricia B Munroe, Andrew Tinker","doi":"10.1177/20480040211023664","DOIUrl":null,"url":null,"abstract":"<p><p>The electrocardiogram (ECG) is a commonly used clinical tool that reflects cardiac excitability and disease. Many parameters are can be measured and with the improvement of methodology can now be quantified in an automated fashion, with accuracy and at scale. Furthermore, these measurements can be heritable and thus genome wide association studies inform the underpinning biological mechanisms. In this review we describe how we have used the resources in UK Biobank to undertake such work. In particular, we focus on a substudy uniquely describing the response to exercise performed at scale with accompanying genetic information.</p>","PeriodicalId":30457,"journal":{"name":"JRSM Cardiovascular Disease","volume":"10 ","pages":"20480040211023664"},"PeriodicalIF":1.4000,"publicationDate":"2021-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/20480040211023664","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"JRSM Cardiovascular Disease","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/20480040211023664","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2021/1/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
引用次数: 2
Abstract
The electrocardiogram (ECG) is a commonly used clinical tool that reflects cardiac excitability and disease. Many parameters are can be measured and with the improvement of methodology can now be quantified in an automated fashion, with accuracy and at scale. Furthermore, these measurements can be heritable and thus genome wide association studies inform the underpinning biological mechanisms. In this review we describe how we have used the resources in UK Biobank to undertake such work. In particular, we focus on a substudy uniquely describing the response to exercise performed at scale with accompanying genetic information.