Identification of Potential Biomarkers for Diagnosis of Patients with Methamphetamine Use Disorder
May 2023
in “
International Journal of Molecular Sciences
”
Studysummary This study developed a two-step diagnostic model using transcriptome biomarkers from hair follicles to improve the accuracy of methamphetamine use disorder diagnosis, achieving high prediction accuracy in distinguishing non-recovered and almost-recovered patients from healthy controls. Our plain-language summary of this paper — not a Tressless recommendation.
This study identified potential biomarkers for diagnosing methamphetamine use disorder (MUD) using RNA sequencing of hair follicle samples from 85 participants (55 MUD patients and 30 healthy controls). Researchers found 6106 differentially expressed genes (DEGs) and developed a prediction model using 39 DEGs, achieving high accuracy (AUC = 1 for non-recovered vs. others, AUC = 0.891 for almost-recovered vs. healthy controls). Key genes involved in neurological functions and diseases were highlighted. The study suggests that gene expression patterns in hair follicles can serve as reliable biomarkers for MUD diagnosis, with further research needed for validation.
