Discovering Hair Biomarkers of Alzheimer’s Disease Using High Resolution Mass Spectrometry-Based Untargeted Metabolomics

Abstract

Hair may be a potential biospecimen to discover biomarkers for Alzheimer’s disease (AD) since it reflects the integral metabolic profiles of body burden over several months. Here, we described the AD biomarker discovery in the hair using a high-resolution mass spectrometry (HRMS)-based untargeted metabolomics approach. A total of 24 patients with AD and 24 age- and sex-matched cognitively healthy controls were recruited. The hair samples were collected 0.1-cm away from the scalp and further cut into 3-cm segments. Hair metabolites were extracted by ultrasonication with methanol/phosphate-buffered saline 50/50 (v/v) for 4 h. A total of 25 discriminatory chemicals in hair between the patients with AD and controls were discovered and identified. The AUC value achieved 0.85 (95% CI: 0.72~0.97) in patients with very mild AD compared to healthy controls using a composite panel of the 9 biomarker candidates, indicating high potential for the initiation or promotion phase of AD dementia in the early stage. A metabolic panel combined with the nine metabolites may be used as biomarkers for the early detection of AD. The hair metabolome can be used to reveal metabolic perturbations for biomarker discovery. Investigating perturbations of the metabolites will offer insight into the pathogenesis of AD.

Keywords

• Alzheimer’s disease
• untargeted metabolomics
• hair, biomarker discovery
• high-resolution mass spectrometry