Genetic liability for prescription opioid use and risk of cardiovascular diseases: a multivariable Mendelian randomization study.

Abstract

BACKGROUND AND AIMS:

Observational studies have yielded conflicting results on the association of prescription opioid use (POU) with the risk of cardiovascular diseases (CVD). Residual confounding and potential reverse causality are inevitable in such conventional observational studies. This study used Mendelian randomization (MR) design to estimate the causal effect of POU on the risk of CVD, including coronary heart disease (CHD), myocardial infarction (MI) and ischemic stroke (IS), as well as their common risk factors.

DESIGN:

We estimated the causal effect of genetic liability for POU on CVD in a two-sample MR framework. Complementary sensitivity analyses were conducted to test the robustness of our results.

SETTING:

Genome-wide association studies (GWAS) that were based on predominantly European ancestry.

PARTICIPANTS:

The sample sizes of the GWAS used in this study ranged from 69 033 to 757 601 participants.

MEASUREMENTS:

Genetic variants predictive of the POU and their corresponding summary-level information in the outcomes were retrieved and extracted from the respective GWAS.

FINDINGS:

Using univariable MR, we found evidence for a causal effect of genetic liability for POU on an increased risk of CHD [odds ratio (OR) = 1.09; 95% confidence interval (CI) = 1.02-1.16; P = 0.008] and MI (OR = 1.13; 95% CI = 1.04-1.22; P = 0.002). In multivariable MR, the association remained after accounting for comorbid pain conditions, but was attenuated with adjustment for potential mediators, including body mass index (BMI), waist circumference (WC) and type 2 diabetes (T2D).

CONCLUSION:

Mendelian randomization estimates provide robust evidence for the causal effects of genetic liability for prescription opioid use on an increased risk of coronary heart disease and myocardial infarction, which might be mediated by obesity-related traits.

• Authors: Jiahao Cai, Lei He, Hongxuan Wang, Xiaoming Rong, Ming Chen, Qingyu Shen, Xiangpen Li, Mei Li, Ying Peng
• Journal: Addiction (Abingdon, England) (Addiction) Vol. 117 Issue 5 Pg. 1382-1391 (05 2022) ISSN: 1360-0443 [Electronic] England
• PMID: 34859517 (Publication Type: Journal Article, Research Support, Non-U.S. Gov't)
• Copyright: © 2021 Society for the Study of Addiction.

Chemical References

• Analgesics, Opioid

Topics

• Analgesics, Opioid (adverse effects)
• Cardiovascular Diseases (epidemiology, genetics)
• Diabetes Mellitus, Type 2 (epidemiology, genetics)
• Genome-Wide Association Study
• Humans
• Mendelian Randomization Analysis
• Polymorphism, Single Nucleotide
• Prescriptions
• Risk Factors