Antimicrobial resistance (AMR) surveillance is primarily based on clinical isolates, providing limited insight into population-level resistance dynamics. Metagenomic sequencing enables large-scale profiling of antibiotic resistance genes (ARGs), but integrating such data with heterogeneous socio-economic and ecological variables requires robust statistical and computational frameworks.
We analysed over 58,000 publicly available human gut metagenomes from NCBI and ENA, spanning more than 60 countries. ARG profiles were quantified by mapping reads to the ResFinder database, and microbiome composition was derived from marker-gene-based taxonomic annotation. These data were integrated with country-level indicators, including antibiotic consumption, socioeconomic indicators, and global connectivity.
We combined generalized additive models and Bayesian multilevel models to capture non-linear associations and region-specific variability while accounting for hierarchical structure. To explicitly model relationships between countries, we constructed dissimilarity matrices and apply dyadic regression to quantify how resistome differences correlate with geographic, socioeconomic, and microbiome distances and similarity.
ARG load and diversity are higher in low- and middle-income countries, with several predictors showing context-dependent or reversed associations across income groups. At the country level, resistome dissimilarity is strongly associated with microbiome composition and socio-economic similarity. Adjustment for microbiome structure reduces the strength of associations between socioeconomic distance and resistome variation, which suggests that microbiome composition partly accounts for the association between socio-economic factors and resistance patterns
These results show that global AMR patterns are structured by interacting socioeconomic and ecological factors, and demonstrate the value of combining hierarchical and dyadic modelling for analysing population-scale metagenomic data.

Co-authors: Shivang Bhanushali, Eetu Tammi, Peter Collingon, John J. Beggs, Johan Bengtsson-Palme, Leo Lahti, Katariina Pärnänen