Circulatory dietary and gut-derived metabolites predict preclinical Alzheimer's disease.

A key component of disease prevention is the identification of at-risk individuals. Microbial dysbiosis and microbe-derived metabolites (MDM) can influence the central nervous system, but their role in disease progression and as prognostic indicators is unknown. To identify preclinical factors associated with Alzheimers disease (AD), we compared gut microbiome and metabolome profiles of cognitively healthy subjects, subjective cognitive impairment (SCI) participants and mild cognitive impairment (MCI) participants (n=50 per group, matched for age, BMI and sex), targeting metabolites previously associated with cognitive health (TMAO, bile acids, tryptophan, p-cresol and their derivatives). 16S rRNA bacterial microbiome sequencing and targeted LC-MS/MS were employed for faecal microbiome speciation and serum MDM quantification. Microbiome beta diversity differed between healthy controls and SCI participants. Multiple linear regression modelling highlighted five serum metabolites (indoxyl sulfate, choline, 5-hydroxyindole acetic acid, indole-3-propionic acid (IPA) and kynurenic acid) significantly altered in preclinical AD. Neuroprotective metabolites, including choline, 5-hydroxyindole acetic acid and IPA, exhibited lower concentrations in SCI and MCI in comparison to controls, while the cytotoxic metabolite indoxyl sulfate had higher levels. A Random Forest algorithm with multiclass classification confirmed and extended our results, identifying six metabolites (indoxyl sulfate, choline, 5-hydroxyindole acetic acid, IPA, kynurenic acid, kynurenine) as predictors of early cognitive decline, with an area under the curve of 0.74. In summary, a combined statistical and machine learning approach identified MDM as a novel composite risk factor for the early identification of future dementia risk.