Cargando…

Multiple anthropometric measures and proarrhythmic 12-lead ECG indices: A mendelian randomization study

BACKGROUND: Observational studies suggest that electrocardiogram (ECG) indices might be influenced by obesity and other anthropometric measures, though it is difficult to infer causal relationships based on observational data due to risk of residual confounding. We utilized mendelian randomization (...

Descripción completa

Detalles Bibliográficos
Autores principales: Ardissino, Maddalena, Patel, Kiran Haresh Kumar, Rayes, Bilal, Reddy, Rohin K., Mellor, Greg J., Ng, Fu Siong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10443852/
https://www.ncbi.nlm.nih.gov/pubmed/37552661
http://dx.doi.org/10.1371/journal.pmed.1004275
_version_ 1785093926763364352
author Ardissino, Maddalena
Patel, Kiran Haresh Kumar
Rayes, Bilal
Reddy, Rohin K.
Mellor, Greg J.
Ng, Fu Siong
author_facet Ardissino, Maddalena
Patel, Kiran Haresh Kumar
Rayes, Bilal
Reddy, Rohin K.
Mellor, Greg J.
Ng, Fu Siong
author_sort Ardissino, Maddalena
collection PubMed
description BACKGROUND: Observational studies suggest that electrocardiogram (ECG) indices might be influenced by obesity and other anthropometric measures, though it is difficult to infer causal relationships based on observational data due to risk of residual confounding. We utilized mendelian randomization (MR) to explore causal relevance of multiple anthropometric measures on P-wave duration (PWD), PR interval, QRS duration, and corrected QT interval (QTc). METHODS AND FINDINGS: Uncorrelated (r(2) < 0.001) genome-wide significant (p < 5 × 10(−8)) single nucleotide polymorphisms (SNPs) were extracted from genome-wide association studies (GWAS) on body mass index (BMI, n = 806,834), waist:hip ratio adjusted for BMI (aWHR, n = 697,734), height (n = 709,594), weight (n = 360,116), fat mass (n = 354,224), and fat-free mass (n = 354,808). Genetic association estimates for the outcomes were extracted from GWAS on PR interval and QRS duration (n = 180,574), PWD (n = 44,456), and QTc (n = 84,630). Data source GWAS studies were performed between 2018 and 2022 in predominantly European ancestry individuals. Inverse-variance weighted MR was used for primary analysis; weighted median MR and MR-Egger were used as sensitivity analyses. Higher genetically predicted BMI was associated with longer PWD (β 5.58; 95%CI [3.66,7.50]; p = < 0.001), as was higher fat mass (β 6.62; 95%CI [4.63,8.62]; p < 0.001), fat-free mass (β 9.16; 95%CI [6.85,11.47]; p < 0.001) height (β 4.23; 95%CI [3.16, 5.31]; p < 0.001), and weight (β 8.08; 95%CI [6.19,9.96]; p < 0.001). Finally, genetically predicted BMI was associated with longer QTc (β 3.53; 95%CI [2.63,4.43]; p < 0.001), driven by both fat mass (β 3.65; 95%CI [2.73,4.57]; p < 0.001) and fat-free mass (β 2.08; 95%CI [0.85,3.31]; p = 0.001). Additionally, genetically predicted height (β 0.98; 95%CI [0.46,1.50]; p < 0.001), weight (β 3.45; 95%CI [2.54,4.36]; p < 0.001), and aWHR (β 1.92; 95%CI [0.87,2.97]; p = < 0.001) were all associated with longer QTc. The key limitation is that due to insufficient power, we were not able to explore whether a single anthropometric measure is the primary driver of the associations observed. CONCLUSIONS: The results of this study support a causal role of BMI on multiple ECG indices that have previously been associated with atrial and ventricular arrhythmic risk. Importantly, the results identify a role of both fat mass, fat-free mass, and height in this association.
format Online
Article
Text
id pubmed-10443852
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-104438522023-08-23 Multiple anthropometric measures and proarrhythmic 12-lead ECG indices: A mendelian randomization study Ardissino, Maddalena Patel, Kiran Haresh Kumar Rayes, Bilal Reddy, Rohin K. Mellor, Greg J. Ng, Fu Siong PLoS Med Research Article BACKGROUND: Observational studies suggest that electrocardiogram (ECG) indices might be influenced by obesity and other anthropometric measures, though it is difficult to infer causal relationships based on observational data due to risk of residual confounding. We utilized mendelian randomization (MR) to explore causal relevance of multiple anthropometric measures on P-wave duration (PWD), PR interval, QRS duration, and corrected QT interval (QTc). METHODS AND FINDINGS: Uncorrelated (r(2) < 0.001) genome-wide significant (p < 5 × 10(−8)) single nucleotide polymorphisms (SNPs) were extracted from genome-wide association studies (GWAS) on body mass index (BMI, n = 806,834), waist:hip ratio adjusted for BMI (aWHR, n = 697,734), height (n = 709,594), weight (n = 360,116), fat mass (n = 354,224), and fat-free mass (n = 354,808). Genetic association estimates for the outcomes were extracted from GWAS on PR interval and QRS duration (n = 180,574), PWD (n = 44,456), and QTc (n = 84,630). Data source GWAS studies were performed between 2018 and 2022 in predominantly European ancestry individuals. Inverse-variance weighted MR was used for primary analysis; weighted median MR and MR-Egger were used as sensitivity analyses. Higher genetically predicted BMI was associated with longer PWD (β 5.58; 95%CI [3.66,7.50]; p = < 0.001), as was higher fat mass (β 6.62; 95%CI [4.63,8.62]; p < 0.001), fat-free mass (β 9.16; 95%CI [6.85,11.47]; p < 0.001) height (β 4.23; 95%CI [3.16, 5.31]; p < 0.001), and weight (β 8.08; 95%CI [6.19,9.96]; p < 0.001). Finally, genetically predicted BMI was associated with longer QTc (β 3.53; 95%CI [2.63,4.43]; p < 0.001), driven by both fat mass (β 3.65; 95%CI [2.73,4.57]; p < 0.001) and fat-free mass (β 2.08; 95%CI [0.85,3.31]; p = 0.001). Additionally, genetically predicted height (β 0.98; 95%CI [0.46,1.50]; p < 0.001), weight (β 3.45; 95%CI [2.54,4.36]; p < 0.001), and aWHR (β 1.92; 95%CI [0.87,2.97]; p = < 0.001) were all associated with longer QTc. The key limitation is that due to insufficient power, we were not able to explore whether a single anthropometric measure is the primary driver of the associations observed. CONCLUSIONS: The results of this study support a causal role of BMI on multiple ECG indices that have previously been associated with atrial and ventricular arrhythmic risk. Importantly, the results identify a role of both fat mass, fat-free mass, and height in this association. Public Library of Science 2023-08-08 /pmc/articles/PMC10443852/ /pubmed/37552661 http://dx.doi.org/10.1371/journal.pmed.1004275 Text en © 2023 Ardissino et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Ardissino, Maddalena
Patel, Kiran Haresh Kumar
Rayes, Bilal
Reddy, Rohin K.
Mellor, Greg J.
Ng, Fu Siong
Multiple anthropometric measures and proarrhythmic 12-lead ECG indices: A mendelian randomization study
title Multiple anthropometric measures and proarrhythmic 12-lead ECG indices: A mendelian randomization study
title_full Multiple anthropometric measures and proarrhythmic 12-lead ECG indices: A mendelian randomization study
title_fullStr Multiple anthropometric measures and proarrhythmic 12-lead ECG indices: A mendelian randomization study
title_full_unstemmed Multiple anthropometric measures and proarrhythmic 12-lead ECG indices: A mendelian randomization study
title_short Multiple anthropometric measures and proarrhythmic 12-lead ECG indices: A mendelian randomization study
title_sort multiple anthropometric measures and proarrhythmic 12-lead ecg indices: a mendelian randomization study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10443852/
https://www.ncbi.nlm.nih.gov/pubmed/37552661
http://dx.doi.org/10.1371/journal.pmed.1004275
work_keys_str_mv AT ardissinomaddalena multipleanthropometricmeasuresandproarrhythmic12leadecgindicesamendelianrandomizationstudy
AT patelkiranhareshkumar multipleanthropometricmeasuresandproarrhythmic12leadecgindicesamendelianrandomizationstudy
AT rayesbilal multipleanthropometricmeasuresandproarrhythmic12leadecgindicesamendelianrandomizationstudy
AT reddyrohink multipleanthropometricmeasuresandproarrhythmic12leadecgindicesamendelianrandomizationstudy
AT mellorgregj multipleanthropometricmeasuresandproarrhythmic12leadecgindicesamendelianrandomizationstudy
AT ngfusiong multipleanthropometricmeasuresandproarrhythmic12leadecgindicesamendelianrandomizationstudy