Causal relationship between particulate matter 2.5 (PM2.5), PM2.5 absorbance, and COVID-19 risk: A two-sample Mendelian randomisation study

Background Several observational studies reported on the association between par-ticulate matter & LE;2.5 & mu;m (PM2.5) and its absorbance with coronavirus (COVID-19), but none use Mendelian randomisation (MR). To strengthen the knowledge on causal-ity, we examined the association of PM2.5 and its absorbance with COVID-19 risk using MR.Methods We selected genome-wide association study (GWAS) integration data from the UK Biobank and IEU Open GWAS Project for two-sample MR analysis. We used inverse variance weighted (IVW) and its multiple random effects and fixed effects alternatives to generally predict the association of PM2.5 and its absorbance with COVID-19, and six methods (MR Egger, weighted median, simple mode, weighted mode, maximum-likelihood and MR-PRESSO) as complementary analyses.Results MR results suggested that PM2.5 absorbance was associated with COVID-19 infection (odds ratio (OR) = 2.64; 95% confidence interval (CI) = 1.32-5.27, P = 0.006), hospitalisation (OR = 3.52; 95% CI = 1.05-11.75, P = 0.041) and severe respiratory symptoms (OR = 28.74; 95% CI = 4.00-206.32, P = 0.001) in IVW methods. We ob-served no association between PM2.5 and COVID-19.Conclusions We found a potential causal association of PM2.5 absorbance with COVID-19 infection, hospitalisation, and severe respiratory symptoms using MR analysis. Prevention and control of air pollution could help delay and halt the neg-ative progression of COVID-19.

Automated summary

Using Mendelian randomisation (MR) analysis, a potential causal association was found between PM2.5 absorbance and COVID-19 infection, hospitalisation, and severe respiratory symptoms. Prevention and control of air pollution could help delay and halt the negative progression of COVID-19.