Abstract

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.

Highlights

  • IntroductionCascade, metabolomics directly reflects modified metabolic pathways provoked by systems disruption as a consequence of, e.g., diseases or exogenous causes [1]

  • In recent years, metabolomic studies have gained significant importance

  • Focus was applied to include a number of metabolites that were both from various chemical classes and unambiguously identifiable

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Summary

Introduction

Cascade, metabolomics directly reflects modified metabolic pathways provoked by systems disruption as a consequence of, e.g., diseases or exogenous causes [1]. This permits a deeper understanding of metabolic pathways in general and in particular a biomarker search for specific questions. Small or short-term changes of the metabolome as a consequence of a monitored effect might go unnoticed. Hair was introduced as a new matrix for metabolomic studies for long-term and retrospective analysis of metabolome changes [3,4,5,6].

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