Causal effects and immune cell mediators between prescription analgesic use and risk of infectious diseases: a Mendelian randomization study

Yi Jin; Xinghao Yu; Jun Li; Mingzhu Su; Xiaomin Li

doi:10.3389/fimmu.2023.1319127

Causal effects and immune cell mediators between prescription analgesic use and risk of infectious diseases: a Mendelian randomization study

Front Immunol. 2023 Dec 21:14:1319127. doi: 10.3389/fimmu.2023.1319127. eCollection 2023.

Authors

Yi Jin^#^{1

2

3}, Xinghao Yu^#^{4

5

6}, Jun Li^{1

2

3}, Mingzhu Su^{1

3}, Xiaomin Li^{1

2

3}

Affiliations

¹ The Wujin Clinical College of Xuzhou Medical University, Changzhou, Jiangsu, China.
² Jiangsu Province Key Laboratory of Anesthesiology, Xuzhou Medical University, Xuzhou, Jiangsu, China.
³ Department of Pharmacy, Wujin Hospital Affiliated with Jiangsu University, Changzhou, Jiangsu, China.
⁴ National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.
⁵ Institute of Blood and Marrow Transplantation, Collaborative Innovation Center of Hematology, Soochow University, Suzhou, Jiangsu, China.
⁶ Center for Genetic Epidemiology and Genomics, School of Public Health, Medical College of Soochow University, Suzhou, Jiangsu, China.

^# Contributed equally.

Abstract

Introduction: Clinical observations have found that prolonged use of analgesics increases the incidence of infection. However, the direct causal relationship between prescription analgesic use (PAU) and risk of infection (ROI) remains unclear.

Methods: This study used Mendelian randomization (MR) design to estimate the causal effect of PAU on ROI, as well as their mediating factors. Genetic data on prescription analgesics use and immune cells were obtained from published GWAS. Additionally, data on ROI were extracted from the FinnGen database. Two-sample MR analysis and multivariate MR (MVMR) analysis were performed using inverse variance weighting (IVW) to ascertain the causal association between PAU and ROI. Finally, 731 immune cell phenotypes were analyzed for their mediating role between analgesics and infection.

Results: Using two-sample MR, IVW modeling showed that genetically predicted opioid use was associated with increased risk of pulmonary infection (PI) (OR = 1.13, 95% CI: 1.05-1.21, p< 0.001) and upper respiratory infection (URI) (OR = 1.18, 95% CI: 1.08-1.30, p< 0.001); non-steroidal anti-inflammatory drugs (NSAIDs) were related to increased risk of skin and subcutaneous tissue infection (OR = 1.21, 95% CI: 1.05-1.39, p = 0.007), and antimigraine preparations were linked to a reduced risk of virus hepatitis (OR = 0.79, 95% CI: 0.69-0.91, p< 0.001). In MVMR, the association of opioids with URI and PI remained after accounting for cancer conditions. Even with a stricter threshold (p< 0.05/30), we found a significant causal association between opioids and respiratory infections (URI/PI). Finally, mediation analyses found that analgesics influence the ROI through different phenotypes of immune cells as mediators.

Conclusion: This MR study provides new genetic evidence for the causal relationship between PAU and ROI, and the mediating role of immune cells was demonstrated.

Keywords: Analgesics; Mendelian randomization; immune cell; infection disease; opioids.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Analgesics / adverse effects
Analgesics, Opioid / adverse effects
Communicable Diseases*
Humans
Immunologic Factors
Mendelian Randomization Analysis
Prescriptions
Respiratory Tract Infections*

Substances

Analgesics
Analgesics, Opioid
Immunologic Factors

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by the Key Laboratory of Anesthesiology of Jiangsu Province through an open research project (Project ID: XZSYSKF2023011).