Genetic evidence for T-wave area from 12-lead electrocardiograms to monitor cardiovascular diseases in patients taking diabetes medications
Qi, Mengling ; Zhang, Haoyang LU
; Xiu, Xuehao
; He, Dan
; Cooper, David N
; Yang, Yuanhao
and Zhao, Huiying
(2024)
In Human Genetics
- Abstract
Aims Many studies indicated use of diabetes medications can influence the electrocardiogram (ECG), which remains the simplest and fastest tool for assessing cardiac functions. However, few studies have explored the role of genetic factors in determining the relationship between the use of diabetes medications and ECG trace characteristics (ETC). Methods Genome-wide association studies (GWAS) were performed for 168 ETCs extracted from the 12-lead ECGs of 42,340 Europeans in the UK Biobank. The genetic correlations, causal relationships, and phenotypic relationships of these ETCs with medication usage, as well as the risk of cardiovascular diseases (CVDs), were estimated by linkage disequilibrium score regression (LDSC), Mendelian... (More)
Aims Many studies indicated use of diabetes medications can influence the electrocardiogram (ECG), which remains the simplest and fastest tool for assessing cardiac functions. However, few studies have explored the role of genetic factors in determining the relationship between the use of diabetes medications and ECG trace characteristics (ETC). Methods Genome-wide association studies (GWAS) were performed for 168 ETCs extracted from the 12-lead ECGs of 42,340 Europeans in the UK Biobank. The genetic correlations, causal relationships, and phenotypic relationships of these ETCs with medication usage, as well as the risk of cardiovascular diseases (CVDs), were estimated by linkage disequilibrium score regression (LDSC), Mendelian randomization (MR), and regression model, respectively. Results The GWAS identified 124 independent single nucleotide polymorphisms (SNPs) that were study-wise and genome-wide significantly associated with at least one ETC. Regression model and LDSC identified significant phenotypic and genetic correlations of T-wave area in lead aVR (aVR_T-area) with usage of diabetes medications (ATC code: A10 drugs, and metformin), and the risks of ischemic heart disease (IHD) and coronary atherosclerosis (CA). MR analyses support a putative causal effect of the use of diabetes medications on decreasing aVR_T-area, and on increasing risk of IHD and CA. ConclusionPatients taking diabetes medications are prone to have decreased aVR_T-area and an increased risk of IHD and CA. The aVR_T-area is therefore a potential ECG marker for pre-clinical prediction of IHD and CA in patients taking diabetes medications.
(Less)
- author
- Qi, Mengling
; Zhang, Haoyang
LU
; Xiu, Xuehao
; He, Dan
; Cooper, David N
; Yang, Yuanhao
and Zhao, Huiying
- publishing date
- 2024-03-20
- type
- Contribution to journal
- publication status
- epub
- subject
- in
- Human Genetics
- pages
- 14 pages
- publisher
- Springer
- external identifiers
-
- pmid:38507016
- ISSN
- 1432-1203
- DOI
- 10.1007/s00439-024-02661-6
- language
- English
- LU publication?
- no
- additional info
- © 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
- id
- 86ee2cef-9983-40bd-b256-823003603234
- date added to LUP
- 2024-03-21 10:58:21
- date last changed
- 2024-03-21 11:31:44
@article{86ee2cef-9983-40bd-b256-823003603234,
abstract = {{<p>Aims Many studies indicated use of diabetes medications can influence the electrocardiogram (ECG), which remains the simplest and fastest tool for assessing cardiac functions. However, few studies have explored the role of genetic factors in determining the relationship between the use of diabetes medications and ECG trace characteristics (ETC). Methods Genome-wide association studies (GWAS) were performed for 168 ETCs extracted from the 12-lead ECGs of 42,340 Europeans in the UK Biobank. The genetic correlations, causal relationships, and phenotypic relationships of these ETCs with medication usage, as well as the risk of cardiovascular diseases (CVDs), were estimated by linkage disequilibrium score regression (LDSC), Mendelian randomization (MR), and regression model, respectively. Results The GWAS identified 124 independent single nucleotide polymorphisms (SNPs) that were study-wise and genome-wide significantly associated with at least one ETC. Regression model and LDSC identified significant phenotypic and genetic correlations of T-wave area in lead aVR (aVR_T-area) with usage of diabetes medications (ATC code: A10 drugs, and metformin), and the risks of ischemic heart disease (IHD) and coronary atherosclerosis (CA). MR analyses support a putative causal effect of the use of diabetes medications on decreasing aVR_T-area, and on increasing risk of IHD and CA. ConclusionPatients taking diabetes medications are prone to have decreased aVR_T-area and an increased risk of IHD and CA. The aVR_T-area is therefore a potential ECG marker for pre-clinical prediction of IHD and CA in patients taking diabetes medications.</p>}},
author = {{Qi, Mengling and Zhang, Haoyang and Xiu, Xuehao and He, Dan and Cooper, David N and Yang, Yuanhao and Zhao, Huiying}},
issn = {{1432-1203}},
language = {{eng}},
month = {{03}},
publisher = {{Springer}},
series = {{Human Genetics}},
title = {{Genetic evidence for T-wave area from 12-lead electrocardiograms to monitor cardiovascular diseases in patients taking diabetes medications}},
url = {{http://dx.doi.org/10.1007/s00439-024-02661-6}},
doi = {{10.1007/s00439-024-02661-6}},
year = {{2024}},
}