Bidirectional causal relationship between glucose-lipid metabolism, obesity indicators, and myocardial infarction: a bidirectional Mendelian randomization analysis study
10.3760/cma.j.cn112148-20240605-00314
- VernacularTitle:基于双向孟德尔随机化分析糖脂代谢及肥胖指标、心肌梗死间的双向因果关联研究
- Author:
Linghuan WANG
1
;
Tingting LU
;
Yingjie ZHANG
;
Tianhu WANG
;
Naiyuan SUN
;
Sijia CHEN
;
Feng CAO
Author Information
1. 南开大学医学院，天津 300071
- Keywords:
Myocardial infarction;
Mendelian randomization;
Glucose and lipid metabolism disorder
- From:
Chinese Journal of Cardiology
2024;52(10):1162-1169
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the causal association of glucose-lipid metabolism and obesity indicators with myocardial infarction by a two-sample Mendelian randomization analysis.Methods:Single nucleotide polymorphisms (SNPs) related to phenotypes were obtained from genome-wide association study databases. The body mass index (BMI) and glycated hemoglobin dataset includes 99 998 samples and 8 126 035 SNPs; the waist-to-hip ratio dataset includes 224 459 samples and 2 562 516 SNPs; the waist circumference and hip circumference dataset includes 462 166 samples and 9 851 867 SNPs; the fasting glucose dataset includes approximately 12 million SNPs; the low-density lipoprotein cholesterol (LDL-C) dataset includes 201 678 samples and 12 321 875 SNPs; the high-density lipoprotein cholesterol (HDL-C), and triglycerides dataset includes 156 109 samples and 15 784 414 SNPs; and the body fat percentage, whole-body fat mass, trunk fat percentage, and trunk fat mass dataset includes 454 588 samples and 9 851 867 SNPs. This study primarily used inverse-variance weighted method to analyze the associations between various exposure factors and outcomes. Heterogeneity among SNPs was assessed using Cochran′s Q test, and horizontal pleiotropy of SNPs was examined using the MR-Egger method. Additionally, a multivariable MR approach was used to adjust for BMI, further validating associations between exposure factors and the risk of myocardial infarction. Results:Higher BMI ( OR=1.070, 95% CI: 1.041-1.100), waist-to-hip ratio ( OR=1.366, 95% CI: 1.113-1.677), LDL-C ( OR=1.638, 95% CI: 1.488-1.803), triglycerides ( OR=1.445, 95% CI: 1.300-1.606), waist circumference ( OR=1.841, 95% CI: 1.650-2.055), hip circumference ( OR=1.247, 95% CI: 1.132-1.372), body fat percentage ( OR=1.795, 95% CI: 1.568-2.055), whole-body fat mass ( OR=1.519, 95% CI: 1.381-1.670), trunk fat percentage ( OR=1.538, 95% CI: 1.374-1.723), and trunk fat mass ( OR=1.421, 95% CI: 1.294-1.561), as well as lower HDL-C ( OR=0.799, 95% CI: 0.729-0.875), have causal effects on myocardial infarction (all P<0.05). After adjusting for BMI, hip circumference, trunk fat percentage, and trunk fat mass were no longer associated with myocardial infarction. However, waist-to-hip ratio ( OR=1.457, 95% CI: 1.132-1.877), fasting glucose ( OR=1.191, 95% CI: 1.024-1.383), glycated hemoglobin ( OR=1.129, 95% CI: 1.034-1.233), LDL-C ( OR=1.592, 95% CI: 1.314-1.929), triglycerides ( OR=1.410, 95% CI: 1.279-1.553), waist circumference ( OR=1.922, 95% CI: 1.448-2.551), body fat percentage ( OR=1.421, 95% CI: 1.072-1.884), and whole-body fat mass ( OR=1.295, 95% CI: 1.031-1.626) remained positively associated with myocardial infarction, while HDL-C ( OR=0.809, 95% CI: 0.729-0.897) remained negatively associated. Conclusions:Abdominal obesity and dysregulation of glucose-lipid metabolism are risk factors for myocardial infarction. Screening for glucose-lipid metabolism (fasting glucose, HDL-C, LDL-C, triglycerides) and obesity-related indicators (waist circumference, waist-to-hip ratio, body fat percentage, and whole-body fat mass) is of great importance for the primary prevention of myocardial infarction.
