Global-Scale Metabolomic Profiling of Human Hair for Simultaneous Monitoring of Endogenous Metabolome, Short- and Long-Term Exposome

Abstract

Hair is a unique biological matrix that adsorbs short-term exposures (e. g., environmental contaminants and personal care products) on its surface and also embeds endogenous metabolites and long-term exposures in its matrix. In this work, we developed an untargeted metabolomics workflow to profile both temporal exposure chemicals and endogenous metabolites in the same hair sample. This analytical workflow begins with the extraction of short-term exposures from hair surfaces through washing. Further development of mechanical homogenization extracts endogenous metabolites and long-term exposures from the cleaned hair. Both solutions of hair wash and hair extract were analyzed using ultra-high-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS)-based metabolomics for global-scale metabolic profiling. After analysis, raw data were processed using bioinformatic programs recently developed specifically for exposome research. Using optimized experimental conditions, we detected a total of 10,005 and 9,584 metabolic features from hair wash and extraction samples, respectively. Among them, 274 and 276 features can be definitively confirmed by MS2 spectral matching against spectral library, and an additional 3,356 and 3,079 features were tentatively confirmed as biotransformation metabolites. To demonstrate the performance of our hair metabolomics, we collected hair samples from three female volunteers and tested their hair metabolic changes before and after a 2-day exposure exercise. Our results show that 645 features from wash and 89 features from extract were significantly changed from the 2-day exposure. Altogether, this work provides a novel analytical approach to study the hair metabolome and exposome at a global scale, which can be implemented in a wide range of biological applications for a deeper understanding of the impact of environmental and genetic factors on human health.

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

“…The aligned features were removed according to their detection frequency within the QC sample of <80% 35 and the calculated RSD values of the corresponding peak area of ≥100%. After exclusion, we acquired 15,732, 23,196, and 20,902 aligned features using the DDA, full scan, and AIF methods, respectively, as shown in Figure S1B. Our results suggested that the most significant number of features in human hair samples were detected by the full scan mode compared to DDA and AIF, which agrees with previous reports.…”

“…Plasma, saliva, and urine have been commonly exploited to discover novel AD biomarkers in HRMS-based untargeted metabolomics studies. − For example, AD patients were differentiated from cognitively normal controls with the five metabolites in plasma, including cholic acid, chenodeoxycholic acid, allocholic acid, indolelactic acid, and tryptophan, with 76.7% sensitivity and 83.3% specificity . However, the chemical compositions of these biological samples are affected by circadian rhythms, daily activities, and even sleep patterns. − Hair has emerged as a potential alternative biospecimen for biomarker discovery in previous studies, as it might reflect the chemical composition in the circulatory system for the previous several months. − For instance, the hair samples have been used to investigate the alternations of metabolite profiles between women with pregnancies complicated by fetal growth restriction and healthy controls . A metabolic panel comprising 5 metabolites, including lactate, levulinate, 2-methyloctadecanate, tyrosine, and margarate, achieved an area under the receiver operating curve of 0.998 .…”

Evaluation of elements in hair samples of children with developmental language disorder (DLD)

“…Hair samples are collected in biobank cohorts [58] but some researchers have debated the utility of this sample type because the composition of hair can be altered by external exposure to materials such as bleaches, hair dyes, and shampoos [59,60].…”

Routine omics collection is a golden opportunity for European human research in space and analog environments

“… 99 Although several markers of hair growth were unsurprisingly dysregulated during flight, interestingly, hair PCDH8 was derived as a potential biomarker for astronaut neurochemical changes in the space environment. 99 Terrestrial studies of human hair also span other omic lines (e.g., proteomics and metabolomics), 100 , 101 highlighting the potential for multiomic profiling of astronaut hair samples. Nevertheless, the extent to which various physiological responses to spaceflight can be tracked by biomarkers in hair warrants a better understanding, before the true scientific potential of hair omics toward biomonitoring astronaut health can be established.…”