Sex‐specific metabolomics‐derived blood biomarkers of Alzheimer’s disease.

Abstract

AbstractBackgroundReadily accessible diagnostic tools are crucial for early detection of Alzheimer’s disease (AD). Here, we sought to identify peripheral metabolism biomarkers predicting the presence of AD pathology.MethodUntargeted liquid chromatography‐mass spectrometry was used to quantify 2286 serum metabolites in participants on a longitudinal memory clinic study. Unbiased between‐group analysis using Orthogonal Partial Least Squares Discriminant Analysis, Linear Discriminant analysis and Principal Component Analysis were performed to build a classifier for AD as indicated by CSF biomarkers. MetaboAnalyst was subsequently used for selection of the most relevant metabolites. Pathway enrichment was used to determine biological pathway alterations related to AD.ResultNo biomarker signature of AD was found in the whole cohort. Stratification according to sex allowed building a classifier for AD using 14 serum metabolites in males and 9 in females. Thirteen enriched pathways were identified, including arachidonic acid and tryptophan metabolism (Figure 1). The selected metabolites significantly improved the prediction of cognitive decline in females compared to a reference model (Figure 2, AUC 0.874 vs. 0.719).ConclusionSex specific peripheral metabolism biomarker profiles are useful to predict cerebral AD pathology and cognitive decline, and detect related metabolic alterations. This highlights the need for personalised diagnostic and therapeutic approaches in AD.