ADGRL3 (LPHN3) variants predict substance use disorder
Arcos-Burgos, Mauricio (Universidad de Antioquia. Instituto de Investigaciones Médicas (IIM), Facultad de Medicina)
Vélez, Jorge I. (Universidad del Norte)
Martinez, Ariel F. (National Institutes of Health. Medical Genetics Branch, National Human Genome Research Institute)
Ribasés Haro, Marta (Hospital Universitari Vall d'Hebron)
Ramos-Quiroga, Josep Antoni (Universitat Autònoma de Barcelona. Departament de Psiquiatria i de Medicina Legal)
Sánchez-Mora, Cristina (Hospital Universitari Vall d'Hebron)
Richarte, Vanesa (Universitat Autònoma de Barcelona. Departament de Psiquiatria i de Medicina Legal)
Roncero, Carlos (Universitat Autònoma de Barcelona. Departament de Psiquiatria i de Medicina Legal)
Cormand, Bru (Institut de Recerca Sant Joan de Déu)
Fernández-Castillo, Noelia (Institut de Recerca Sant Joan de Déu)
Casas Brugué, Miquel (Universitat Autònoma de Barcelona. Departament de Psiquiatria i de Medicina Legal)
Lopera, Francisco (Universidad de Antioquia)
Pineda, David A. (Universidad de Antioquia)
Palacio, Juan D. (Universidad de Antioquia)
Acosta-López, Johan E. (Universidad Simón Bolívar. Grupo de Neurociencias del Caribe, Unidad de Neurociencias Cognitivas)
Cervantes-Henriquez, Martha L. (Universidad Simón Bolívar. Grupo de Neurociencias del Caribe, Unidad de Neurociencias Cognitivas)
Sánchez-Rojas, Manuel G. (Universidad Simón Bolívar. Grupo de Neurociencias del Caribe, Unidad de Neurociencias Cognitivas)
Puentes-Rozo, Pedro J. (Universidad del Atlántico. Grupo de Neurociencias del Caribe)
Molina, Brooke S. G. (University of Pittsburg. Departments of Psychiatry and Psychology)
Boden, Margaret T. (University of Kentucky Mental Health Research Center at Eastern State Hospital)
Wallis, Deeann (Texas A&M University. Department of Biochemistry and Biophysics)
Lidbury, Brett (The Australian National University. National Center for Indigenous Genomics, Genome Biology Department, John Curtin School of Medical Research, ANU College of Medicine, Biology and Environment)
Newman, Saul (The Australian National University. National Center for Indigenous Genomics, Genome Biology Department, John Curtin School of Medical Research, ANU College of Medicine, Biology and Environment)
Easteal, Simon (The Australian National University. National Center for Indigenous Genomics, Genome Biology Department, John Curtin School of Medical Research, ANU College of Medicine, Biology and Environment)
Swanson, James (University of California at Irvine. Child Development Center)
Patel, Hardip (The Australian National University. Genome Discovery Unit, Genome Biology Department, John Curtin School of Medical Research, ANU College of Medicine, Biology and Environment)
Volkow, Nora (National Institute on Drug Abuse (Rockville, Estats Units d'Amèrica))
Acosta, Maria T. (National Institutes of Health. Medical Genetics Branch, National Human Genome Research Institute)
Castellanos, Francisco X. (Nathan Kline Institute for Psychiatric Research)
de Leon, Jose (University of Kentucky Mental Health Research Center at Eastern State Hospital)
Mastronardi, Claudio A. (Universidad del Rosario. Center for Research in Genetics and Genomics, Institute of Translational Medicine, School of Medicine and Health Sciences)
Muenke, Maximilian (National Institutes of Health. Medical Genetics Branch, National Human Genome Research Institute)

Data:	2019
Resum:	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.
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Publicat a:	Translational psychiatry, Vol. 9 (january 2019) , ISSN 2158-3188

DOI: 10.1038/s41398-019-0396-7
PMID: 30696812

15 p, 2.4 MB

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