{"title":"Does COVID-19 impact the QT interval prolongation? Answers from genetic causal inference.","authors":"Yongfei Song, Zequn Zheng","doi":"10.1042/BSR20241281","DOIUrl":null,"url":null,"abstract":"<p><p>During the COVID-19 pandemic, there has been heightened interest in the QT interval, a crucial indicator of ventricular electrical activity. Mendelian randomization (MR) is used here to investigate the genetic causation between QT interval alterations and COVID-19. Genetic proxies representing three COVID-19 phenotypes-severe, hospitalized, and COVID-19-were identified in over 1,000,000 individuals of European ancestry. Univariate two-sample MR (TSMR) and multi-exposure-adjusted multivariate MR (MVMR) were used to assess genetic causal associations between COVID-19 and QT intervals in 84,630 UK Biobank participants. The MR-robust adjusted profile score (MR-RAPS) method and radial MR frame were utilized for effective robustness and outlier variant detection, with sensitivity analyses conducted to identify horizontal pleiotropy. For every COVID-19 phenotype, univariate TSMR analysis revealed non-significant causal estimates between COVID-19 and the QT interval [COVID-19: βIVW (95% CI): -0.44 (-1.72, 0.84), P = 0.50; hospitalization: βIVW: 0.12 (-0.57, 0.80), P = 0.74; severe case: βIVW: 0.11 (-0.29, 0.51), P = 0.58]. MR-RAPS and outlier-corrected radial MR analyses further supported this null causal estimation. In confounder-adjusted MVMR analysis, this nonsignificant causality was independent of body mass index (BMI), smoking, and alcohol consumption [βBMI+Alcohol+Smoking (95% CI): -0.77 (-2.44, 0.91), P = 0.37]. Sensitivity analyses did not detect any evidence of bias from horizontal pleiotropy, abnormal data distribution, or weak instruments. These findings suggest that COVID-19 does not directly causally prolong the QT interval. Inconsistent findings in observational research may be attributed to residual confounding.</p>","PeriodicalId":8926,"journal":{"name":"Bioscience Reports","volume":" ","pages":"1-14"},"PeriodicalIF":3.8000,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bioscience Reports","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1042/BSR20241281","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
During the COVID-19 pandemic, there has been heightened interest in the QT interval, a crucial indicator of ventricular electrical activity. Mendelian randomization (MR) is used here to investigate the genetic causation between QT interval alterations and COVID-19. Genetic proxies representing three COVID-19 phenotypes-severe, hospitalized, and COVID-19-were identified in over 1,000,000 individuals of European ancestry. Univariate two-sample MR (TSMR) and multi-exposure-adjusted multivariate MR (MVMR) were used to assess genetic causal associations between COVID-19 and QT intervals in 84,630 UK Biobank participants. The MR-robust adjusted profile score (MR-RAPS) method and radial MR frame were utilized for effective robustness and outlier variant detection, with sensitivity analyses conducted to identify horizontal pleiotropy. For every COVID-19 phenotype, univariate TSMR analysis revealed non-significant causal estimates between COVID-19 and the QT interval [COVID-19: βIVW (95% CI): -0.44 (-1.72, 0.84), P = 0.50; hospitalization: βIVW: 0.12 (-0.57, 0.80), P = 0.74; severe case: βIVW: 0.11 (-0.29, 0.51), P = 0.58]. MR-RAPS and outlier-corrected radial MR analyses further supported this null causal estimation. In confounder-adjusted MVMR analysis, this nonsignificant causality was independent of body mass index (BMI), smoking, and alcohol consumption [βBMI+Alcohol+Smoking (95% CI): -0.77 (-2.44, 0.91), P = 0.37]. Sensitivity analyses did not detect any evidence of bias from horizontal pleiotropy, abnormal data distribution, or weak instruments. These findings suggest that COVID-19 does not directly causally prolong the QT interval. Inconsistent findings in observational research may be attributed to residual confounding.
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