Mass spectrometry-based metabolomics in hair from current and former patients with methamphetamine use disorder.

Drug use disorder, a chronic and relapsing mental disorder, is primarily diagnosed via self-reports of drug-seeking behavioral and psychological conditions, accompanied by psychiatric assessment. Therefore, the identification of peripheral biomarkers that reflect pathological changes caused by such disorders is essential for improving treatment monitoring. Hair possesses great potential as a metabolomic sample for monitoring chronic diseases. This study aimed to investigate metabolic alterations in hair to elucidate a suitable treatment modality for methamphetamine (MA) use disorder. Consequently, both targeted and untargeted metabolomics analyses were performed via mass spectrometry on hair samples obtained from current and former patients with MA use disorder. Healthy subjects (HS), current (CP), and former (FP) patients with this disorder were selected based on psychiatric diagnosis and screening the concentrations of MA in hair. The drug abuse screening questionnaire scores did not differentiate between CP and FP. Moreover, according to both targeted and untargeted metabolomics, clustering was not observed among all three groups. Nevertheless, a model of partial least squares-discriminant analysis was established between HS and CP based on seven metabolites derived from the targeted metabolomics results. Thus, this study demonstrates the promising potential of hair metabolomes for monitoring recovery from drug use disorders in clinical practice.