Identifying Hair Biomarker Candidates for Alzheimer’s Disease Using Three High Resolution Mass Spectrometry-Based Untargeted Metabolomics Strategies

Abstract

High-resolution mass spectrometry (HRMS)-based untargeted metabolomics strategies have emerged as an effective tool for discovering biomarkers of Alzheimer's disease (AD). There are various HRMS-based untargeted metabolomics strategies for biomarker discovery, including the data-dependent acquisition (DDA) method, the combination of full scan and target MS/MS, and the all ion fragmentation (AIF) method. Hair has emerged as a potential biospecimen for biomarker discovery in clinical research since it might reflect the circulating metabolic profiles over several months, while the analytical performances of the different data acquisition methods for hair biomarker discovery have been rarely investigated. Here, the analytical performances of three data acquisition methods in HRMS-based untargeted metabolomics for hair biomarker discovery were evaluated. The human hair samples from AD patients (N = 23) and cognitively normal individuals (N = 23) were used as an example. The most significant number of discriminatory features was acquired using the full scan (407), which is approximately 10-fold higher than that using the DDA strategy (41) and 11% higher than that using the AIF strategy (366). Only 66% of discriminatory chemicals discovered in the DDA strategy were discriminatory features in the full scan dataset. Moreover, compared to the deconvoluted MS/MS spectra with coeluted and background ions from the AIF method, the MS/MS spectrum obtained from the targeted MS/MS approach is cleaner and purer. Therefore, an untargeted metabolomics strategy combining the full scan with the targeted MS/MS method could obtain most discriminatory features along with a high quality MS/MS spectrum for discovering the AD biomarkers.

Critical Factors in Sample Collection and Preparation for Clinical Metabolomics of Underexplored Biological Specimens

“…Thus, in the last five years, hair samples have been widely used to study pregnancy complications, such as pre-eclampsia [ 127 ], fetal growth restriction [ 128 ], gestational T2DM [ 129 ], and diet restrictions [ 130 ]. Additional clinical investigations include the search for biomarkers in cervical cancer [ 131 ] and Alzheimer’s disease [ 132 , 133 ] and the monitoring of chronic conditions such as androgenetic alopecia [ 134 ] and baldness [ 135 ].…”

“…Metabolite extraction is performed with or without alkaline hydrolysis, using NaOH 4 mol L −1 [ 139 ] or, more frequently, KOH 1 mol L −1 , followed by neutralization with H 2 SO 4 (3 mol L −1 ) [ 127 , 128 , 131 ]. Proteins are usually precipitated by the addition of pure methanol [ 125 , 129 , 134 , 135 ], methanol/phosphate saline buffer (PBS) [ 132 , 133 , 140 ], or methanol/water/acetone (1:1:1, v / v / v ) [ 141 ]. In order to increase extraction performance, bench mills [ 142 , 143 ], ultrasound [ 132 , 133 ], and vortex [ 128 , 139 ] have been applied.…”

“…Proteins are usually precipitated by the addition of pure methanol [ 125 , 129 , 134 , 135 ], methanol/phosphate saline buffer (PBS) [ 132 , 133 , 140 ], or methanol/water/acetone (1:1:1, v / v / v ) [ 141 ]. In order to increase extraction performance, bench mills [ 142 , 143 ], ultrasound [ 132 , 133 ], and vortex [ 128 , 139 ] have been applied. The resulting supernatants can be directly analyzed through LC–MS, completely dried and resuspended in the respective mobile phases, or even derivatized for GC–MS analysis.…”