Causal relationship between particulate matter and COVID-19 risk: A mendelian randomization study

Jiayi Zhu; Yong Zhou; Qiuzhen Lin; Keke Wu; Yingxu Ma; Chan Liu; Na Liu; Tao Tu; Qiming Liu

doi:10.1016/j.heliyon.2024.e27083

Causal relationship between particulate matter and COVID-19 risk: A mendelian randomization study

Heliyon. 2024 Feb 24;10(5):e27083. doi: 10.1016/j.heliyon.2024.e27083. eCollection 2024 Mar 15.

Authors

Jiayi Zhu¹, Yong Zhou¹, Qiuzhen Lin¹, Keke Wu¹, Yingxu Ma¹, Chan Liu², Na Liu¹, Tao Tu¹, Qiming Liu¹

Affiliations

¹ Department of Cardiovascular Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, PR China.
² International Medical Department, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, PR China.

Abstract

Background: Observational studies have linked exposure to fine (PM2.5) and coarse (PM10) particulate matter air pollution with adverse COVID-19 outcomes, including higher incidence and mortality. However, some studies questioned the effect of air pollution on COVID-19 susceptibility, raising questions about the causal nature of these associations. To address this, a less biased method like Mendelian randomization (MR) is utilized, which employs genetic variants as instrumental variables to infer causal relationships in observational data.

Method: We performed two-sample MR analysis using public genome-wide association studies data. Instrumental variables correlated with PM2.5 concentration, PM2.5 absorbance, PM2.5-10 concentration and PM10 concentration were identified. The inverse variance weighted (IVW), robust adjusted profile score (RAPS) and generalized summary data-based Mendelian randomization (GSMR) methods were used for analysis.

Results: IVW MR analysis showed PM2.5 concentration [odd ratio (OR) = 3.29, 95% confidence interval (CI) 1.48-7.35, P-value = 0.0036], PM2.5 absorbance (OR = 5.62, 95%CI 1.98-15.94, P-value = 0.0012), and PM10 concentration (OR = 3.74, 95%CI 1.52-9.20, P-value = 0.0041) increased the risk of COVID-19 severity after Bonferroni correction. Further validation confirmed PM2.5 absorbance was associated with heightened COVID-19 severity (OR = 6.05, 95%CI 1.99-18.38, P-value = 0.0015 for RAPS method; OR = 4.91, 95%CI 1.65-14.59, P-value = 0.0042 for GSMR method) and hospitalization (OR = 3.15, 95%CI 1.54-6.47, P-value = 0.0018 for RAPS method). No causal links were observed between particulate matter exposure and COVID-19 susceptibility.

Conclusions: Our study established a causal relationship between smaller particle pollution, specifically PM2.5, and increased risk of COVID-19 severity and hospitalization. These findings highlight the importance of improving air quality to mitigate respiratory disease progression.

Keywords: Air pollution; COVID-19; Mendelian randomization; PM2.5; Particulate matter.