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Background: Alzheimer’s disease (AD) is a common and progressive neurodegenerative disorder related to cognitive impairments that generally include deficits in short-term memory. Hair may be a potential biospecimen for AD biomarker discovery since it reflects the integral metabolic profiles of body burden over several months. Here, we discovered hair biomarkers in hair that differentiate AD patients from cognitively healthy controls using a high-resolution mass spectrometry (HRMS)-based untargeted metabolomics approach.Methods: An HRMS-based untargeted metabolomics approach was used to discover the potential AD biomarker candidates in hair samples from 24 AD patients (including n = 14, 7, and 3, with CDR scores of 0.5, 1, and 2, respectively) and 24 age- and sex-matched cognitively healthy controls. 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 hours. We assessed metabolic biomarker to distinguish between AD and controls with Student’s t test, hierarchical cluster analysis (HCA), and receiver operating characteristic (ROC) curve analysis.Results: Statistically significant changes in 61 peak features in hair between the patients with AD and cognitively healthy controls were discovered, of which 25 were identified to have chemical structures. The levels of nine metabolites, including acetyl-L-carnitine, propionylcarnitine, butyrylcarnitine, O-valeroyl-L-carnitine, PC (16:0/0:0), LPC 18:1, piperine, hydroxyprolyl-leucine, and 6-O-methylnorlaudanosoline, were significantly lower in patients with questionable AD (CDR score of 0.5) than in cognitively healthy controls (p < 0.01). ROC curves were constructed to evaluate the performance of the nine metabolites combined into a metabolic marker panel for distinguishing patients with questionable AD from cognitively healthy controls, in which the sensitivity and specificity were 86% and 71%, respectively, and the AUC value was 0.85 (95% CI: 0.72~0.97), indicating high potential for the initiation of AD dementia.Conclusions: Nine metabolites may be used as biomarkers for the early detection of AD dementia or therapeutic development after validation in a larger cohort. The present study suggested that the hair metabolome can be used to reveal metabolic perturbations for biomarker discovery and may lead to the development of a sensitive diagnostic tool for AD. |
