Exploring the gut-brain-microbiome axis in Alzheimer's disease: Integrating metagenomics, metabolomics, and artificial intelligence for next-generation biomarker discovery.

Alzheimer's disease (AD), a progressive neurodegenerative disorder, is increasingly understood as a multifactorial condition influenced by systemic and environmental factors beyond the central nervous system. A growing body of evidence shows that the gut-brain-microbiome axis (GBMA), a complex bidirectional communication network, is involved in neural, endocrine, immune, and metabolic pathways in AD pathogenesis. This narrative review synthesizes emerging insights into the role of gut microbiota dysbiosis in promoting neuroinflammation, amyloid-β aggregation, blood-brain barrier disruption, and cognitive decline. We explored recent advancements in metagenomics and metabolomics for profiling microbial communities and their functional metabolites linked to AD. Alterations in microbe-derived compounds, such as short-chain fatty acids and tryptophan metabolites, influence neurodevelopment, glial activation, and mitochondrial dysfunction. Multi-omics integration, enhanced by artificial intelligence (AI), enables precise biomarker discovery, patient stratification, and the development of personalized therapeutic strategies. Translational opportunities include microbiome-based diagnostics, probiotic therapy, and stratified interventions. However, clinical translation faces challenges such as methodological heterogeneity, inter-individual microbiome variation, data governance issues, and algorithmic bias. We emphasize the need for diverse reference panels, longitudinal multimodal cohorts, and shared AI-ready datasets to enhance the reproducibility and global equity of research. Strategic investment in integrative, ethically governed, and interdisciplinary approaches is essential to unlock the full therapeutic and diagnostic potential of GBMA in AD.