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Research Paper|Volume 16, Issue 11|pp 9944—9958

Causal effects for neurodegenerative diseases on the risk of myocardial infarction: a two-sample Mendelian randomization study

Jianing Chi1,2,3,4, Jiaman Hu1,2,3,5, Ningxia Wu1,2,3,6, Hua Cai1,2,3,6, Cailong Lin1,2,3,5, Yingying Lai1,2,3,5, Jianyu Huang1,2,3, Weihua Li1, Peng Su1, Min Li1,2,3, Lin Xu1,2,3,4
  • 1Department of Geriatric Cardiology, General Hospital of Southern Theater Command, Guangzhou, China
  • 2Branch of National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Guangzhou, China
  • 3Guangzhou Key Laboratory of Cardiac Rehabilitation, Guangzhou, China
  • 4The First School of Clinical Medicine, Southern Medical University, Guangzhou, China
  • 5School of Public Health, Guangdong Pharmaceutical University, Guangzhou, China
  • 6Graduate School, Guangzhou University of Chinese Medicine, Guangzhou, China
Received: November 22, 2023Accepted: May 3, 2024Published: June 7, 2024

Copyright: © 2024 Chi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Several studies have demonstrated a correlation between neurodegenerative diseases (NDDs) and myocardial infarction (MI), yet the precise causal relationship between these remains elusive. This study aimed to investigate the potential causal associations of genetically predicted Alzheimer’s disease (AD), dementia with Lewy bodies (DLB), Parkinson’s disease (PD), and multiple sclerosis (MS) with MI using two-sample Mendelian randomization (TSMR). Various methods, including inverse variance weighted (IVW), weighted median (WM), MR-Egger regression, weighted mode, and simple mode, were employed to estimate the effects of genetically predicted NDDs on MI. To validate the analysis, we assessed pleiotropic effects, heterogeneity, and conducted leave-one-out sensitivity analysis. We identified that genetic predisposition to NDDs was suggestively associated with higher odds of MI (OR_IVW=1.07, OR_MR–Egger=1.08, OR_WM=1.07, OR_weighted mode=1.07, OR_simple mode=1.10, all P<0.05). Furthermore, we observed significant associations of genetically predicted DLB with MI (OR_IVW=1.07, OR_MR–Egger=1.11, OR_WM=1.09, OR_weighted mode=1.09, all P<0.05). However, there was no significant causal evidence of genetically predicted PD and MS in MI. Across all MR analyses, no horizontal pleiotropy or statistical heterogeneity was observed (all P>0.05). Additionally, results from MRPRESSO and leave-one-out sensitivity analysis confirmed the robustness of the causal effect estimations for genetically predicted AD, DLB, PD, and MS on MI. This study provides further support for the causal effects of AD on MI and, for the first time, establishes robust causal evidence for the detrimental effect of DLB on the risk of MI. Our findings emphasize the importance of monitoring the cardiovascular function of the elderly experiencing neurodegenerative changes.