Metabolites correlate with plasma biomarkers and clinical diagnosis of Alzheimer's Disease.

Background: Energy, amino acid, and lipid metabolism are dysregulated in Alzheimer's Disease. We investigated circulating plasma metabolites to capture systemic biochemical changes associated with Alzheimer's disease (AD) using the clinical diagnosis and followed by the addition of plasma‐based biomarkers. Method: Exogenous and endogenous metabolites in plasma were measured in 300 individuals with a clinical diagnosis of AD and 430 healthy individuals without dementia of Caribbean Hispanic ancestry using untargeted liquid‐chromatography, performed on HILIC (+ ionization) and C18 (‐ ionization) columns, coupled to a Thermo Orbitrap HF‐X mass spectrometer. Genome‐wide SNP data and plasma biomarkers including pTau181, Aβ40, Aβ42, neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) were obtained on all participants. Metabolite association with the clinical diagnosis of AD and for the AD biomarker, pTau‐181, levels were assessed after adjustment for age and sex. Result: More than 6000 metabolic features were measured with high accuracy in the sample. 270 metabolic features were associated with pTau‐181 levels and 66 metabolic features were associated with clinical AD status, after correction for multiple testing. Valyl‐Serine (p = 1.1e‐7) and creatinine (p = 9.6e‐7) were strongly associated pTau‐181 levels. When using a diagnostic cutoff of pTau181 levels for AD as the outcome (biological AD), we also observed significant associations with a lysophospholipid (p = 9.5e‐5). Malic acid (p = 4.2e‐4) and tryptophan (p = 3.9e‐4) were significantly associated with clinical AD status. Metabolites associated with pTau‐181 levels were enriched in glycan biosynthesis, energy, amino acid, urea cycle/amino group and carbohydrate metabolism pathways. Patients with both clinical and biological AD showed altered tyrosine and tryptophan metabolism. Conclusion: Metabolites, specifically amino acids and lipids, were associated with AD status and pTau181 levels. Metabolite profiling can identify perturbed pathways in clinical and pre‐clinical AD and integration with genome‐wide SNP data will identify mechanisms underlying genetic association with disease. [ABSTRACT FROM AUTHOR]