Cheating on forensic hair testing? Detection of potential biomarkers for cosmetically altered hair samples using untargeted hair metabolomics

Characterization of Hair Metabolome in 5xFAD Mice and Patients with Alzheimer's Disease Using Mass Spectrometry-Based Metabolomics

Hair emerged as a biospecimen for long-term investigation of endogenous metabolic perturbations, reflecting the chemical composition circulating in the blood over the past months. Despite its potential, the use of human hair for metabolomics in Alzheimer's disease (AD) research remains limited. Here, we performed both untargeted and targeted metabolomic approaches to profile the key metabolic pathways in the hair of 5xFAD mice, a widely used AD mouse model. Furthermore, we applied the discovered metabolites to human subjects. Hair samples were collected from 6-month-old 5xFAD mice, a stage marked by widespread accumulation of amyloid plaques in the brain, followed by sample preparation and high-resolution mass spectrometry analysis. Forty-five discriminatory metabolites were discovered in the hair of 6-month-old 5xFAD mice compared to wild-type control mice. Enrichment analysis revealed three key metabolic pathways: arachidonic acid metabolism, sphingolipid metabolism, and alanine, aspartate, and glutamate metabolism. Among these pathways, six metabolites demonstrated significant differences in the hair of 2-month-old 5xFAD mice, a stage prior to the onset of amyloid plaque deposition. These findings suggest their potential involvement in the early stages of AD pathogenesis. When evaluating 45 discriminatory metabolites for distinguishing patients with AD from nondemented controls, a combination of l-valine and arachidonic acid significantly differentiated these two groups, achieving a 0.88 area under the curve. Taken together, these findings highlight the potential of hair metabolomics in identifying disease-specific metabolic alterations and developing biomarkers for improving disease detection and monitoring.

MARS: A Multipurpose Software for Untargeted LC-MS-Based Metabolomics and Exposomics

Untargeted metabolomics is a growing field, in which recent advances in high-resolution mass spectrometry coupled with liquid chromatography (LC-MS) have facilitated untargeted approaches as a result of improvements in sensitivity, mass accuracy, and resolving power. However, a very large amount of data are generated. Consequently, using computational tools is now mandatory for the in-depth analysis of untargeted metabolomics data. This article describes MetAbolomics ReSearch (MARS), an all-in-one vendor-agnostic graphical user interface-based software applying LC-MS analysis to untargeted metabolomics. All of the analytical steps are described (from instrument data conversion and processing to statistical analysis, annotation/identification, quantification, and preliminary biological interpretation), and tools developed to improve annotation accuracy (e.g., multiple adducts and in-source fragmentation detection, trends across samples, and the MS/MS validator) are highlighted. In addition, MARS allows in-house building of reference databases, to bypass the limits of freely available MS/MS spectra collections. Focusing on the flexibility of the software and its user-friendliness, which are two important features in multipurpose software, MARS could provide new perspectives in untargeted metabolomics data analysis.

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

This review article compiles critical pre-analytical factors for sample collection and extraction of eight uncommon or underexplored biological specimens (human breast milk, ocular fluids, sebum, seminal plasma, sweat, hair, saliva, and cerebrospinal fluid) under the perspective of clinical metabolomics. These samples are interesting for metabolomics studies as they reflect the status of living organisms and can be applied for diagnostic purposes and biomarker discovery. Pre-collection and collection procedures are critical, requiring protocols to be standardized to avoid contamination and bias. Such procedures must consider cleaning the collection area, sample stimulation, diet, and food and drug intake, among other factors that impact the lack of homogeneity of the sample group. Precipitation of proteins and removal of salts and cell debris are the most used sample preparation procedures. This review intends to provide a global view of the practical aspects that most impact results, serving as a starting point for the designing of metabolomic experiments.

Recent omics advances in hair aging biology and hair biomarkers analysis

Aging is a complex natural process that leads to a decline in physiological functions, which is visible in signs such as hair graying, thinning, and loss. Although hair graying is characterized by a loss of pigment in the hair shaft, the underlying mechanism of age-associated hair graying is not fully understood. Hair graying and loss can have a significant impact on an individual's self-esteem and self-confidence, potentially leading to mental health problems such as depression and anxiety. Omics technologies, which have applications beyond clinical medicine, have led to the discovery of candidate hair biomarkers and may provide insight into the complex biology of hair aging and identify targets for effective therapies. This review provides an up-to-date overview of recent omics discoveries, including age-associated alterations of proteins and metabolites in the hair shaft and follicle, and highlights the significance of hair aging and graying biomarker discoveries. The decline in hair follicle stem cell activity with aging decreased the regeneration capacity of hair follicles. Cellular senescence, oxidative damage and altered extracellular matrix of hair follicle constituents characterized hair follicle and hair shaft aging and graying. The review attempts to correlate the impact of endogenous and exogenous factors on hair aging. We close by discussing the main challenges and limitations of the field, defining major open questions and offering an outlook for future research.

Advances in testing for sample manipulation in clinical and forensic toxicology-part B: hair samples

As a continuation of part A, focusing on advances in testing for sample manipulation of urine samples in clinical and forensic toxicology, part B of the review article relates to hair, another commonly used matrix for abstinence control testing. Similar to urine manipulation, relevant strategies to manipulate a hair test are lowering drug concentrations in hair to undercut the limits of detection/cut-offs, for instance, by forced washout effects or adulteration. However, distinguishing between usual, common cosmetic hair treatment and deliberate manipulation to circumvent a positive drug test is often impossible. Nevertheless, the identification of cosmetic hair treatment is very relevant in the context of hair testing and interpretation of hair analysis results. Newly evaluated techniques or elucidation of specific biomarkers to unravel adulteration or cosmetic treatment often focused on specific structures of the hair matrix with promising strategies recently proposed for daily routine work. Identification of other approaches, e.g., forced hair-washing procedures, still remains a challenge in clinical and forensic toxicology.

Hair analysis: Assessment of homemade hair treatment effects on drug concentrations in the keratin matrix

Hair is the matrix of choice for investigating a subject's drug history over time, usually with specific forensic applications (license renewal, workplace drug testing, toxicological evaluation), and it is generally considered difficult to be tampered with. Nevertheless, some treatments promising to lower drug concentrations in hair are described online as how to "pass" a drug test. We selected three of these practices, claiming to be effective in decreasing drug concentrations-Treatment 1: (A) baking soda, (B) salicylic acid, (C) bleach; Treatment 2: (A) bleaching and (B) dyeing; Treatment 3: (A) white vinegar, (B) salicylic acid moisturizer, (C) liquid cleanser, and (D) dyeing. Quantitative results were compared with those of untreated hair strands, used as reference. We evaluated the efficacy of the treatment on drugs of abuse and benzodiazepines. Treatment 1 proved to be the most effective, since drug concentrations in treated hair were significantly lower than in untreated ones, although methadone and tetrahydrocannabinol (THC) seemed to be less affected than cocaine and 6-monoacetylmorphine (MAM). The mean percentage values of treatment-induced decrease were up to 90% for cocaine, 81% for benzoylecgonine, 77% for morphine, 89% for MAM, 37% for methadone, 67% for ketamine, 80% for MDMA, 76% for methamphetamine, and 60% for THC, compared with the reference samples. There was no noticeable damage or discoloration of the keratin matrix, making it difficult for the technicians to determine if there was a treatment. This could be an issue for the application of cutoffs or when low concentrations of drugs are incorporated into the keratinic matrix.

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

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.

Identifying contamination versus ingestion in hair testing, with cocaine as example

When developing a procedure to identify external contamination of hair as opposed to drug that is in hair from ingestion, there are components of the process that must be considered in the final method. A method that does not achieve the objective may be missing one or more of these elements: choice of solvent, a drug-binding agent, ratio of solvent to hair, temperature, time, intactness of the hair, and establishing, for the chosen method, a criterion based on the drug contents of the wash and hair that indicates the hair may be contaminated.

Metabolomics in clinical and forensic toxicology, sports anti-doping and veterinary residues

Metabolomics is a multidisciplinary field providing workflows for complementary approaches to conventional analytical determinations. It allows for the study of metabolically related groups of compounds or even the study of novel pathways within the biological system. The procedural stages of metabolomics; experimental design, sample preparation, analytical determinations, data processing and statistical analysis, compound identification and validation strategies are explored in this review. The selected approach will depend on the type of study being conducted. Experimental design influences the whole metabolomics workflow and thus needs to be properly assessed to ensure sufficient sample size, minimal introduced and biological variation and appropriate statistical power. Sample preparation needs to be simple, yet potentially global in order to detect as many compounds as possible. Analytical determinations need to be optimised either for the list of targeted compounds or a universal approach. Data processing and statistical analysis approaches vary widely and need to be better harmonised for review and interpretation. This includes validation strategies that are currently deficient in many presented workflows. Common compound identification approaches have been explored in this review. Metabolomics applications are discussed for clinical and forensic toxicology, human and equine sports anti-doping and veterinary residues.

Development and validation of a method for simultaneous analysis of hair underivatized amino acids and damage biomarkers, using liquid chromatography-tandem mass spectrometry

The forensic and medical fields are seeing growing interest in the amino acid and damage biomarker composition of hair, in order to identify adulteration of drug hair testing and for diagnostic purposes. Therefore, there is an increased demand for quick and accurate analytical methods. This study presents the first liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay for the simultaneous quantification of hair amino acids and four damage biomarkers, which also implements an isotopic dilution strategy to improve recovery and precision of the acid hydrolysis-sensitive analytes. The applied strategy enabled a recovery of the hydrolysis-sensitive amino acids between 83 and 120% (vs. 33-77%, without isotopic dilution) for two different protein standards, and a precision with a relative standard deviation (RSD) between 1.3 and 7.5% (vs. 9.0-29.4%, without isotopic dilution). All 21 analytes could be measured without interferences by matrix and sample components, thus demonstrating satisfactory selectivity of the method. For spiked samples of hair hydrolyzate, recovery was between 88 and 120%, whereas precision and intermediate precision were below 10.1%. The high sensitivity of the method made it possible to reduce sample preparation to a 10000-fold dilution of the raw hydrolyzate. The wide linear range displayed by the method allowed the simultaneous quantification of minor (0.3 μmol/g of hair) and major (up to 1000 μmol/g of hair) components of the biological fiber. This method was successfully applied to the analysis of real hair samples submitted to six different treatments. Statistical data analysis by means of t-test and principal component analysis (PCA) showed a clear discrimination of the treated from the untreated hair samples and of the different treatments. Since these hair treatments can interfere with hair drug testing, the method possesses the ability of identifying hair samples with potential for attempted drug test evasion. In addition, lanthionine emerged as a new biomarker for heat damaged hair.

Hyphenated high-resolution mass spectrometry-the "all-in-one" device in analytical toxicology?

This trend article reviews papers with hyphenated high-resolution mass spectrometry (HRMS) approaches applied in analytical toxicology, particularly in clinical and forensic toxicology published since 2016 and referenced in PubMed. The article focuses on the question of whether HRMS has or will become the all-in-one device in these fields as supposed by the increasing number of HRMS presentations at scientific meetings, corresponding original papers, and review articles. Typical examples for the different application fields are discussed such as targeted or untargeted drug screening, quantification, drug metabolism studies, and metabolomics approaches. Considering the reviewed papers, HRMS is currently the only technique that fulfills the criteria of an all-in-one device for the various applications needed in analytical toxicology.

Graphical abstract

Towards Best Practice in Hair Metabolomic Studies: Systematic Investigation on the Impact of Hair Length and Color

Untargeted metabolomic studies are used for large-scale analysis of endogenous compounds. Due to exceptional long detection windows of incorporated substances in hair, analysis of hair samples for retrospective monitoring of metabolome changes has recently been introduced. However, information on the general behavior of metabolites in hair samples is scarce, hampering correct data interpretation so far. The presented study aimed to investigate endogenous metabolites depending on hair color and along the hair strand and to propose recommendations for best practice in hair metabolomic studies. A metabolite selection was analyzed using untargeted data acquisition in genuine hair samples from different hair colors and after segmentation in 3 cm segments. Significant differences in metabolites among hair colors and segments were found. In conclusion, consideration of hair color and hair segments is necessary for hair metabolomic studies and, subsequently, recommendations for best practice in hair metabolomic studies were proposed.