The causal relationship between triglycerides and myocardial infarction: A two-sample Mendelian randomization

The causal relationship between triglycerides and myocardial infarction (MI) was investigated using Mendelian randomization (MR) studies. Triglycerides were the exposure factor, and MI served as the outcome variable. Inverse variance weighting was used as the main analysis method, MR-Egger, and weight median as other analysis methods for MR analysis. In addition, heterogeneity test, level multivariate analysis, and sensitivity analysis were carried out. Inverse variance weighting results showed that the increase in triglyceride level affected the incidence of MI (OR = 1.287; 95% CI = 1.185-1.398; P = 1.988 × 10-9). Consistently, the results from all 3 methods indicated a statistically significant increase in the risk of MI with higher triglyceride levels (P < .05). The results showed that patients with high triglyceride levels had a higher incidence of MI, suggesting that MI should be prevented in the high triglyceride population.

Authors

Institutions

Publication Details

Journal
Medicine
Published
2024-09-13
DOI
https://doi.org/10.1097/md.0000000000039595
Primary Topic
Genetic Associations and Epidemiology
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The causal relationship between triglycerides and myocardial infarction: A two-sample Mendelian randomization

Zhong-Bin Yang, Xiehui Chen, Xiao‐Qing Quan, Ai-Ping Qiu et al.
Medicine
Genetic Associations and Epidemiology
article

The causal relationship between triglycerides and myocardial infarction: A two-sample Mendelian randomization

Zhong-Bin Yang, Xiehui Chen, Xiao‐Qing Quan, Ai-Ping Qiu, Hongtao Liu, Lu Kong
article en

Abstract

The causal relationship between triglycerides and myocardial infarction (MI) was investigated using Mendelian randomization (MR) studies. Triglycerides were the exposure factor, and MI served as the outcome variable. Inverse variance weighting was used as the main analysis method, MR-Egger, and weight median as other analysis methods for MR analysis. In addition, heterogeneity test, level multivariate analysis, and sensitivity analysis were carried out. Inverse variance weighting results showed that the increase in triglyceride level affected the incidence of MI (OR = 1.287; 95% CI = 1.185-1.398; P = 1.988 × 10-9). Consistently, the results from all 3 methods indicated a statistically significant increase in the risk of MI with higher triglyceride levels (P < .05). The results showed that patients with high triglyceride levels had a higher incidence of MI, suggesting that MI should be prevented in the high triglyceride population.

MedicineVol. 103(37)
Hubei University of Medicine (CN), Longgang Central Hospital (CN)
Good health and well-being
Openalex Percentile: Top 83%
Genetic Associations and Epidemiology
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.