Ran Ding, Fan Qi, Qianqian Dai, Kangfan Li, Yuan Zhang
Alcohol-related liver disease (ALD) is a major cause of liver-related morbidity and mortality worldwide, yet the associations linking alcohol-induced gut microbial alterations to metabolic remodeling and hepatocyte dysfunction remain incompletely understood. Here, we applied an integrative multi-omics strategy combining untargeted fecal metabolomics, shotgun metagenomics, mouse liver bulk RNA sequencing, and reanalysis of publicly available human hepatic single-cell and bulk transcriptomic datasets to characterize alcohol exposure-associated gut-liver immunometabolic features. In a mouse model of acute ethanol-induced liver injury, fecal metabolomic and metagenomic profiling revealed marked alterations in microbial functional potential and fecal metabolic composition, identifying six convergent metabolic pathways across fecal multi-omics layers, including nucleotide metabolism, the pentose phosphate pathway, histidine metabolism, glycerophospholipid metabolism, glycine/serine/threonine metabolism, and the phosphotransferase system. Reanalysis of human ALD single-cell transcriptomes showed hepatocyte-enriched activity patterns for several corresponding pathways, suggesting potential pathway-level associations between fecal metabolic alterations and hepatic transcriptional responses. Integrative transcriptomic analysis further identified a ten-gene hepatocyte-associated signature, comprising LRG1, ORM1, ORM2, TAT, HP, FGB, FGG, ITIH3, NNMT, and AGT, which was associated with pathway activity and showed consistent upregulation across acute ethanol-induced liver injury and human ALD/AH transcriptomic datasets. In an external human cohort, this signature stratified patients into exploratory molecular subgroups with distinct metabolic pathway activities and clinical outcome distributions. Collectively, these findings provide a hypothesis-generating multi-omics framework for investigating alcohol-related liver injury and support further validation in chronic ethanol exposure models and functional studies.