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Risk Assessment for Heroin Use and Craving Score Using Polygenic Risk Score

Authors: Chieh-Liang Huang; Ping-Ho Chen; Hsien-Yuan Lane; Ing-Kang Ho; Chia-Min Chung;

Risk Assessment for Heroin Use and Craving Score Using Polygenic Risk Score

Abstract

Addiction is characterized by drug-craving, compulsive drug-taking, and relapse, and results from the interaction between multiple genetic and environmental factors. Reward pathways play an important role in mediating drug-seeking and drug-taking behaviors, and relapse. The objective of this study was to identify heroin addicts who carry specific genetic variants in their dopaminergic reward systems. A total of 326 heroin-dependent patients undergoing methadone maintenance therapy (MMT) were recruited from the Addiction Center of the China Medical University Hospital. A heroin-use and craving questionnaire was used to evaluate the urge for heroin, the daily or weekly frequency of heroin usage, daily life disturbance, anxiety, and the ability to overcome heroin use. A general linear regression model was used to assess the associations of genetic polymorphisms in one’s dopaminergic reward system with heroin-use and craving scores. Results: The most significant results were obtained for rs2240158 in GRIN3B (p = 0.021), rs3983721 in GRIN3A (p = 0.00326), rs2129575 in TPH2 (p = 0.033), rs6583954 in CYP2C19 (p = 0.033), and rs174699 in COMT (p = 0.036). These were all associated with heroin-using and craving scores with and without adjustments for age, sex, and body mass index. We combined five variants, and the ensuing dose-response effect indicated that heroin-craving scores increased with the numbers of risk alleles (p for trend = 0.0008). These findings will likely help us to understand the genetic mechanism of craving, which will help in predicting the risk of relapse in clinical practice and the potential for therapies to target craving in heroin addiction.

Keywords

craving, genetic biomarker, addiction, heroin, Article

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Top 10%
Average
Top 10%
Green
gold