Global analysis links ambient fine particulate matter to bacterial antimicrobial resistance based on 110,000 + genomes

Abstract

Antimicrobial resistance (AMR) is a global health challenge. Recently, overwhelming evidence suggests a possible association between fine particulate matter (PM_2.5) and bacterial AMR. However, the PM_2.5-AMR association was poorly understood. In this global analysis, we aim to provide an in-depth and comprehensive insight into the PM_2.5-AMR association. Based on multiple global databases, two Bayesian multivariable models (negative binomial regression model and logistic regression model) with different lag time were used to estimate the association, quantify the lag-response effects, and identify potential effect modifiers. A total of 114,488 isolates with genome data, collected between 2000 and 2022 from 139 countries and regions, were examined. For every 10 μg/m³ increase in PM_2.5 exposure over the past 12 months, there was a corresponding 11.2 % increase (95 % CI: 10.6 %, 11.7 %) in the percentage of total resistance genes per isolate and an odds ratio of 1.18 (95 % CI: 1.17, 1.20) for carrying at least one resistance gene. There was a dose–response relationship between PM_2.5 level and AMR. The PM_2.5-AMR association might be highest at cumulative exposure during the past 12 months, and modified by bacterial species, sample sources, environmental factors, and other national-level economic, medical, and social factors. To summarize, we found significant associations between PM_2.5 exposure and AMR. Further studies are needed in phenotypic resistance data and possible intervention experiments in animals or humans to confirm these findings.