Life sciences · Journal article
Frontiers in Nutrition · October 14, 2026
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Obesity is a metabolically heterogeneous condition with distinct metabolic phenotypes, ranging from metabolically healthy obesity (MHO) to metabolically unhealthy obesity (MUO). Although individuals with MHO initially lack cardiometabolic dysfunction, many transition to MUO over time, exponentially increasing their risk for type 2 diabetes and cardiovascular disease. In this mini-review, we synthesize recent evidence from multi-omic cohort studies evaluating gut microbiome composition and gut-derived metabolites as functional biomarkers of obesity heterogeneity and drivers of metabolic decline. While microbial diversity yields inconsistent signatures across cohorts, MHO is generally characterized by higher relative abundance of Ruminococcaceae, Oscillospira, Akkermansia, and Bifidobacterium and enrichment of other taxa predicted to be short-chain fatty acid-producers. Conversely, circulating gut-derived metabolomic signatures including altered secondary bile acid pools, elevated branched-chain amino acids, and trimethylamine N-oxide more reliably discriminate MUO from MHO than traditional measures, and correlate strongly with visceral adiposity, insulin resistance, and systemic inflammation. Furthermore, new systems biology approaches, such as integrating high-dimensional metagenomics and metabolomics via machine learning models, offer a potentially superior early indicators tool in precision medicine for identifying obesity phenotypes compared with traditional metrics (e.g., body mass index, fasting glucose). Overall, current evidence remains predominantly cross-sectional and based on secondary analyses of large cohort studies, underscoring the need for prospective longitudinal studies to validate these multi-omic biomarkers for precise phenotype identification and clinical risk assessment.