Multi-omics integration reveals functional signatures of gut microbiome in atherosclerosis.

Atherosclerosis (AS), a predominant contributor to global cardiovascular disease burden, exhibits complex interplay with gut microbiota dysbiosis. While the associations between microbial imbalance and AS pathogenesis are well-documented, the pathophysiological mechanisms governing microbe-host crosstalk remain incompletely characterized. Current research limitations stem from methodological heterogeneity across studies and the absence of consensus regarding disease-specific microbial signatures. In this study, we conducted an integrated multi-omics analysis to characterize the functional signatures of gut microbiome in AS. We collected all public AS-related 6 microbiome datasets and 8 peripheral blood host transcriptomic datasets from across the world, comprising 456 metagenomic samples and 111 16S rRNA gene sequencing samples for microbial profiling, alongside 118 RNA-Seq samples and 302 microarray samples. We systematically characterized AS microbial taxa and computationally inferred the metabolic potential for the gut microbiome using metabolomic-related data. Metabolite-host gene interactions were further predicted based on the synergistic effects between microbiome and host transcriptome in AS. Five "microbe-metabolite-host gene" tripartite associations related to AS were identified involving 5 microbial genera (, , , , and ), 2 metabolites (Ethanol and HO), and 2 host genes (FANCD2 and GPX2), and the reliability of these associations was validated. Five microbial genera demonstrated robust diagnostic potential as noninvasive biomarkers, with 5-fold cross-validation, study-to-study transfer validation, and leave-one-study-out (LOSO) validation confirming good diagnostic performance. Additionally, the specificity of the biomarkers was validated against hypertension, inflammatory bowel disease (IBD), diabetes, and obesity cohorts. Our study unveiled the functional characteristics of gut microbiota interacting with AS host genes and highlighted the potential of gut microbiota as both diagnostic biomarkers and therapeutic targets for AS. However, the findings should be interpreted considering the inherent heterogeneity of the integrated datasets and the preliminary diagnostic value of the biomarkers.