Multiple anthropometric measures and proarrhythmic 12-lead ECG indices: A mendelian randomization study.
<h4>Background</h4>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 mendel...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2023-08-01
|
| Series: | PLoS Medicine |
| Online Access: | https://doi.org/10.1371/journal.pmed.1004275 |
| _version_ | 1797733751748296704 |
|---|---|
| author | Maddalena Ardissino Kiran Haresh Kumar Patel Bilal Rayes Rohin K Reddy Greg J Mellor Fu Siong Ng |
| author_facet | Maddalena Ardissino Kiran Haresh Kumar Patel Bilal Rayes Rohin K Reddy Greg J Mellor Fu Siong Ng |
| author_sort | Maddalena Ardissino |
| collection | DOAJ |
| description | <h4>Background</h4>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).<h4>Methods and findings</h4>Uncorrelated (r2 < 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.<h4>Conclusions</h4>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. |
| first_indexed | 2024-03-12T12:33:55Z |
| format | Article |
| id | doaj.art-4d0228fb270446908a3136714b79a605 |
| institution | Directory Open Access Journal |
| issn | 1549-1277 1549-1676 |
| language | English |
| last_indexed | 2024-03-12T12:33:55Z |
| publishDate | 2023-08-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Medicine |
| spelling | doaj.art-4d0228fb270446908a3136714b79a6052023-08-29T05:30:38ZengPublic Library of Science (PLoS)PLoS Medicine1549-12771549-16762023-08-01208e100427510.1371/journal.pmed.1004275Multiple anthropometric measures and proarrhythmic 12-lead ECG indices: A mendelian randomization study.Maddalena ArdissinoKiran Haresh Kumar PatelBilal RayesRohin K ReddyGreg J MellorFu Siong Ng<h4>Background</h4>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).<h4>Methods and findings</h4>Uncorrelated (r2 < 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.<h4>Conclusions</h4>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.https://doi.org/10.1371/journal.pmed.1004275 |
| spellingShingle | Maddalena Ardissino Kiran Haresh Kumar Patel Bilal Rayes Rohin K Reddy Greg J Mellor Fu Siong Ng Multiple anthropometric measures and proarrhythmic 12-lead ECG indices: A mendelian randomization study. PLoS Medicine |
| 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 |
| url | https://doi.org/10.1371/journal.pmed.1004275 |
| work_keys_str_mv | AT maddalenaardissino multipleanthropometricmeasuresandproarrhythmic12leadecgindicesamendelianrandomizationstudy AT kiranhareshkumarpatel multipleanthropometricmeasuresandproarrhythmic12leadecgindicesamendelianrandomizationstudy AT bilalrayes multipleanthropometricmeasuresandproarrhythmic12leadecgindicesamendelianrandomizationstudy AT rohinkreddy multipleanthropometricmeasuresandproarrhythmic12leadecgindicesamendelianrandomizationstudy AT gregjmellor multipleanthropometricmeasuresandproarrhythmic12leadecgindicesamendelianrandomizationstudy AT fusiongng multipleanthropometricmeasuresandproarrhythmic12leadecgindicesamendelianrandomizationstudy |