Citation

Zhang Y, Sun Y, Yu Z, Sun Y, Chang X, Lu L, Chang S, Shi J. Addict. Biol. 2019; ePub(ePub): ePub.

Affiliation

Beijing Key Laboratory on Drug Dependence Research, Beijing, China.

Copyright

(Copyright © 2019, John Wiley and Sons)

DOI

10.1111/adb.12709

PMID

30821087

Abstract

Methamphetamine (MA)-related psychiatric symptoms (MAP) are serious comorbidities of MA use and result in many social problems such as violence and suicide. We investigated the sociodemographic and genetic risk factors for persistent MAP of MA users (MUs) and constructed an early MAP prediction model. Derivation and replication samples had 1734 and 905 MUs, respectively. Symptom Checklist 90, Childhood Trauma Questionnaire, Attention-Deficit Hyperactivity Disorder (ADHD) Rating Scale-IV, and Social Support Rating Scale were used to assess the past-year prevalence of general MAP and life events retrospectively. Genome-wide association study (GWAS) was used to analyze MAP-related genetic factors. The prediction model was constructed by integrating the risk life events and clinical and genetic features using logistic regression. Of the 2639 MUs, 1293 (48.83%) had past-year MAP. The severity of MA addiction (SMA), childhood trauma, childhood ADHD symptoms, and social support were reliable risk factors for persistent MAP. By integrating these risk factors and the polygenic risk score from GWAS from derivation samples, the area under the curve (AUC) of the predictive model for MAP was 0.754 (95% CI 0.717~0.771). The risk factors and prediction model were also verified in replication samples. In addition, SMA, ADHD, and social support were mediators for the effect of the risk genetic factor on persistent MAP. Our study identified several risk factors for persistent MAP and will be helpful for developing scalable tools for the prevention of persistent and general MAP.

© 2019 Society for the Study of Addiction.

Language: en

Keywords

attention-deficit hyperactivity disorder (ADHD); genome-wide association study (GWAS); methamphetamine use; methamphetamine-related persistent psychiatric symptoms; predictive model; risk factors