Abstract The human gut microbiome is increasingly viewed as an active regulator of host physiology, extending beyond earlier taxonomy‐centered descriptions of a complex microbial community. Accumulating evidence supports an organ‐like conceptual framework in which the gut microbiome exhibits spatially structured organization, extensive metabolic capacity, and continuous bidirectional communication with host systems. Through the production of bioactive metabolites with endocrine‐like, immunomodulatory, and neuromodulatory properties, the microbiome contributes to metabolic, immune, and neuroendocrine regulation, thereby influencing systemic homeostasis and disease susceptibility. Recent advances in multi‐omics, spatial biology, and computational modeling are moving the field from taxonomic association toward functional interpretation, mechanistic insight, and causal inference. These approaches are beginning to reveal microbiome‐derived functional modules and host–microbe signaling networks that are shaped by host genetics, diet, medications, feeding patterns, circadian rhythms, and environmental exposures. In this review, we synthesize current mechanistic and translational evidence to conceptualize the gut microbiome as an organ‐like functional system, delineate its structural and functional organization, and propose a framework for mapping, modeling, and therapeutically targeting microbiome‐derived circuits to support precision medicine in metabolic, inflammatory, and selected gut–brain axis‐related disorders.
Yang Bi, Wei-Bin Song, Maria Glymenaki et al.· iMeta· 0 citations
Autism spectrum disorder (ASD) has been associated with gut microbiome and metabolic alterations, but reported biomarkers are inconsistent and often inadequately account for family and shared environment. We analysed 620 children, including 334 with ASD and 286 neurotypical siblings, with a median age of 6.0 years (IQR 4.0–8.0). Faecal and urine samples were collected monthly up to eight times. After quality control, 869 microbiome, 754 faecal metabolome and 787 urine metabolome samples were analysed using 16S rRNA sequencing, NMR and LC–MS metabolomics. Mixed models accounted for family, repeated sampling and biological sex. Family membership explained 46.1% of variation across microbiome and metabolome profiles, compared with 8.0% attributable to ASD. After family adjustment, ASD explained only 0.1% to 0.3% of microbiome beta diversity. No stable taxonomic biomarkers were identified, and microbial classification was poor (AUROC <0.75). Urinary metabolomics identified elevated 5-hydroxy-L-tryptophan and altered phenylalanine metabolism. Structural equation modelling found no direct associations between selected taxa and metabolites. These findings argue against a universal ASD microbiome and indicate that family context contributes more strongly than diagnosis to microbial and metabolic variation.
Ashley G. Bell, Kiana A. West, Gary Frost et al.· bioRxiv· 0 citations
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