Multi-biofluid metabolomics coupled with gene network reveals stage-specific alterations in mild cognitive impairment and Alzheimer's disease in an ethnically mixed cohort.

Alzheimer's disease (AD) is the most prevalent age-related neurodegenerative disorder worldwide. A prodromal stage, often manifested as Mild Cognitive Impairment (MCI), can precede dementia onset. Metabolomics provides a powerful approach to detect metabolic alterations capturing combined genetic, epigenetic, dietary, gut microbiota, and environmental influences on AD pathogenesis and progression from MCI to AD. In this study, we analysed plasma, urine, and saliva metabolomes of 94 ethnically diverse Brazilian individuals (30 AD, 16 MCI and 48 healthy controls), all comorbidity-free, using Nuclear Magnetic Resonance (NMR)-based metabolomics. Cross-sectional analysis employed multivariate modelling (PLS-DA) and univariate Mann-Whitney U tests. We identified distinct group-specific metabolic signatures involving amino acids (phenylalanine, glutamine, asparagine, valine, alanine), energy-related metabolites (pyruvate, citrate, glucose), compounds linked to lipid/redox pathways (acetate, glutamate, aspartate), epigenetic regulation (betaine), neuroinflammation, immune fitness, and gut microbiome-influenced metabolites (scyllo-inositol). Valine increased progressively (controls < MCI < AD), while alanine showed a biphasic pattern (reduced in MCI, elevated in AD). These consistent, biofluid-spanning alterations highlight their potential as minimally invasive biomarkers for diagnosis and monitoring. Integration of metabolite data with AD-associated genes from genome-wide association studies (GWAS) revealed six genes (CYCS, NFAT5, GRIN2B, SLC43A2, MAPT, and SLC38A1) common to all biofluids, reinforcing convergent systemic pathways. Collectively, these findings underscore the importance of integrating metabolomics with genetic networks to enhance understanding of AD pathophysiology, identify potential therapeutic targets, and guide future clinical validation and precision medicine strategies for dementia in ethnically mixed populations.