Identification of potential non-invasive biomarkers for diagnosing patients with methamphetamine use disorder
To date, diagnosis of methamphetamine use disorder (MUD) is based primarily on the patient's self-reports of drug-seeking behaviour and interviews with psychiatrists in the absence of objective biomarkers. As an effective clinical method for diagnosis of MUD is still not available, the development of potential biomarkers for more accurate diagnosis is imperative. Transcription profiling and discovery of biomarkers in the treatment and recovery periods of MUD patients can be used as scientific basis to provide a greater understanding of the disease and to facilitate decisions on whether to continue or not. In this study, RNA sequencing analysis was performed to profile transcripts from hair follicle cells of healthy controls and patients with MUD, and biomarkers were discovered at each transition states to be used to diagnose MUD. This study will present an important information to diagnose MUD using non-invasive biomarkers for human addicts and it will help to develop better pharmacological treatment of MUD in the future. Overall design: RNA samples were extracted from hair follicles for 33 current patients with methamphetamine use disorders (CPs), 22 former patients with methamphetamine use disorders (FPs) and 30 healthy controls (HCs).