Abstract

Hair is considered a novel biospecimen for investigating long-term alterations of endogenous metabolites and for reflecting circulating chemicals in the bloodstream over the past months. Although hair is an emerging biospecimen, characterizing hair metabolome in Alzheimer’s disease (AD) remains limited. Here, an analytical approach integrating untargeted and targeted metabolomic approaches was employed to discover hair biomarker candidates and identify the critical metabolic pathways associated with AD in the 5xFAD mice, a widely used AD mouse model. Furthermore, the discovered biomarker candidates were applied to human subjects. The hair samples collected from 6-month-old 5xFAD mice, a stage marked by widespread accumulation of amyloid plaques in the brain, underwent sample preparation and were subsequently analyzed by high-resolution mass spectrometry. Forty-five biomarker candidates were discovered in the hair of 6-month-old 5xFAD mice compared to wild-type mice. Enrichment analysis revealed arachidonic acid metabolism, sphingolipid metabolism, alanine, aspartate, and glutamate metabolism related to AD. Among these pathways, the levels of six metabolites in the hair of 2-month-old 5xFAD mice, a stage before the onset of amyloid plaque deposition, demonstrated significant differences, suggesting that they might be involved in the early stages of AD pathogenesis. When assessing 45 biomarker candidates for differentiating patients with AD from cognitively healthy subjects, a metabolic panel combining L-valine and arachidonic acid achieved a 0.88 area under the curve. This suggests that this panel can distinguish AD patients from controls. Therefore, the findings highlight the potential use of the hair metabolome to identify biomarker candidates associated with AD.