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author Arcos-Burgos, Mauricio
Vélez, Jorge I.
Martinez, Ariel F.
Ribasés, Marta
Ramos-Quiroga, Josep A.
Sánchez-Mora, Cristina
Richarte, Vanesa
Roncero, Carlos
Cormand, Bru
Fernández-Castillo, Noelia
Casas, Miguel
Lopera, Francisco
Pineda, David A.
Palacio, Juan D.
Acosta-López, Johan E.
Cervantes-Henriquez, Martha L.
Sánchez-Rojas, Manuel G.
Puentes-Rozo, Pedro J.
Molina, Brooke S. G.
Boden, Margaret T.
Wallis, Deeann
Lidbury, Brett
Newman, Saul
Easteal, Simon
Swanson, James
Patel, Hardip
Volkow, Nora
Acosta, Maria T.
Castellanos, Francisco X.
de Leon, Jose
Mastronardi, Claudio A.
Muenke, Maximilian
author_facet Arcos-Burgos, Mauricio
Vélez, Jorge I.
Martinez, Ariel F.
Ribasés, Marta
Ramos-Quiroga, Josep A.
Sánchez-Mora, Cristina
Richarte, Vanesa
Roncero, Carlos
Cormand, Bru
Fernández-Castillo, Noelia
Casas, Miguel
Lopera, Francisco
Pineda, David A.
Palacio, Juan D.
Acosta-López, Johan E.
Cervantes-Henriquez, Martha L.
Sánchez-Rojas, Manuel G.
Puentes-Rozo, Pedro J.
Molina, Brooke S. G.
Boden, Margaret T.
Wallis, Deeann
Lidbury, Brett
Newman, Saul
Easteal, Simon
Swanson, James
Patel, Hardip
Volkow, Nora
Acosta, Maria T.
Castellanos, Francisco X.
de Leon, Jose
Mastronardi, Claudio A.
Muenke, Maximilian
author_sort Arcos-Burgos, Mauricio
collection PubMed
description 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.
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spelling pubmed-63515842019-01-30 ADGRL3 (LPHN3) variants predict substance use disorder Arcos-Burgos, Mauricio Vélez, Jorge I. Martinez, Ariel F. Ribasés, Marta Ramos-Quiroga, Josep A. Sánchez-Mora, Cristina Richarte, Vanesa Roncero, Carlos Cormand, Bru Fernández-Castillo, Noelia Casas, Miguel Lopera, Francisco Pineda, David A. Palacio, Juan D. Acosta-López, Johan E. Cervantes-Henriquez, Martha L. Sánchez-Rojas, Manuel G. Puentes-Rozo, Pedro J. Molina, Brooke S. G. Boden, Margaret T. Wallis, Deeann Lidbury, Brett Newman, Saul Easteal, Simon Swanson, James Patel, Hardip Volkow, Nora Acosta, Maria T. Castellanos, Francisco X. de Leon, Jose Mastronardi, Claudio A. Muenke, Maximilian Transl Psychiatry Article 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. Nature Publishing Group UK 2019-01-29 /pmc/articles/PMC6351584/ /pubmed/30696812 http://dx.doi.org/10.1038/s41398-019-0396-7 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Arcos-Burgos, Mauricio
Vélez, Jorge I.
Martinez, Ariel F.
Ribasés, Marta
Ramos-Quiroga, Josep A.
Sánchez-Mora, Cristina
Richarte, Vanesa
Roncero, Carlos
Cormand, Bru
Fernández-Castillo, Noelia
Casas, Miguel
Lopera, Francisco
Pineda, David A.
Palacio, Juan D.
Acosta-López, Johan E.
Cervantes-Henriquez, Martha L.
Sánchez-Rojas, Manuel G.
Puentes-Rozo, Pedro J.
Molina, Brooke S. G.
Boden, Margaret T.
Wallis, Deeann
Lidbury, Brett
Newman, Saul
Easteal, Simon
Swanson, James
Patel, Hardip
Volkow, Nora
Acosta, Maria T.
Castellanos, Francisco X.
de Leon, Jose
Mastronardi, Claudio A.
Muenke, Maximilian
ADGRL3 (LPHN3) variants predict substance use disorder
title ADGRL3 (LPHN3) variants predict substance use disorder
title_full ADGRL3 (LPHN3) variants predict substance use disorder
title_fullStr ADGRL3 (LPHN3) variants predict substance use disorder
title_full_unstemmed ADGRL3 (LPHN3) variants predict substance use disorder
title_short ADGRL3 (LPHN3) variants predict substance use disorder
title_sort adgrl3 (lphn3) variants predict substance use disorder
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6351584/
https://www.ncbi.nlm.nih.gov/pubmed/30696812
http://dx.doi.org/10.1038/s41398-019-0396-7
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