Abstract
Genetic factors are strongly implicated in the susceptibility to develop externalizing syndromes such as attention-deficit/hyperactivity disorder (ADHD), oppositional defiant disorder, conduct disorder, and substance use disorder (SUD). Variants in the ADGRL3 (LPHN3) gene predispose to ADHD and predict ADHD severity, disruptive behaviors comorbidity, long-term outcome, and response to treatment. In this study, we investigated whether variants within ADGRL3 are associated with SUD, a disorder that is frequently co-morbid with ADHD. Using family-based, case-control, and longitudinal samples from disparate regions of the world (n = 2698), recruited either for clinical, genetic epidemiological or pharmacogenomic studies of ADHD, we assembled recursive-partitioning frameworks (classification tree analyses) with clinical, demographic, and ADGRL3 genetic information to predict SUD susceptibility. Our results indicate that SUD can be efficiently and robustly predicted in ADHD participants. The genetic models used remained highly efficient in predicting SUD in a large sample of individuals with severe SUD from a psychiatric institution that were not ascertained on the basis of ADHD diagnosis, thus identifying ADGRL3 as a risk gene for SUD. Recursive-partitioning analyses revealed that rs4860437 was the predominant predictive variant. This new methodological approach offers novel insights into higher order predictive interactions and offers a unique opportunity for translational application in the clinical assessment of patients at high risk for SUD.
Highlights
Substance use disorders (SUD) and addiction represent a global public health problem of substantial socioeconomic implications[1,2]
The prevalence of Attention-deficit/hyperactivity disorder (ADHD) co-morbid with disruptive behaviors is variable across populations, we found a higher frequency of conduct disorder (CD), oppositional defiant disorder (ODD), and SUD in ADHD individuals than in unaffected relatives[6,22,24]
The importance of these variables was corroborated, and their potential over fitting discarded by the TreeNet analyses that revealed a set of predictors for SUD containing those derived by Classification and Regression Trees (CART) (Fig. 1b)
Summary
Substance use disorders (SUD) and addiction represent a global public health problem of substantial socioeconomic implications[1,2]. In 2010, 147.5 million cases of Attention-deficit/hyperactivity disorder (ADHD), the most common neurodevelopmental behavioral disorder[4,5], is frequently co-morbid with disruptive behaviors. Arcos-Burgos et al Translational Psychiatry (2019)9:42 such as oppositional defiant disorder (ODD), conduct disorder (CD), and SUD6,7. ADHD and disruptive behaviors is summarized by longitudinal observations in ADHD cohorts[6,8,9]. Children diagnosed with ADHD monitored during the transition into adolescence exhibit higher rates of alcohol, tobacco, and psychoactive drug use than control groups of children without ADHD10,11. It has been estimated that the lifetime risk for SUD is ~50% in subjects with childhood ADHD persisting into adulthood[12,13]. The prevalence of ADHD is high in adolescents with SUD9,14,15 and the presence of an ADHD diagnosis affects
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
