4.7 Article

ADGRL3 (LPHN3) variants predict substance use disorder

Journal

TRANSLATIONAL PSYCHIATRY
Volume 9, Issue -, Pages -

Publisher

NATURE PUBLISHING GROUP
DOI: 10.1038/s41398-019-0396-7

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Funding

  1. National Human Genome Research Institute
  2. Eli Lilly Research Foundation
  3. National Alliance for Research on Schizophrenia and Depression (NARSAD) Independent Award
  4. University of Kentucky
  5. Roche Molecular Systems, Inc.
  6. Universidad del Norte, Barranquilla, Colombia [FOFICO 32101-511035-PE0031]
  7. National Institute on Drug Abuse (NIDA) [DA039881]
  8. Instituto de Salud Carlos III, Spain [PI12/01139, PI14/01700, PI15/01789, PI16/01505]
  9. European Regional Development Fund (ERDF)
  10. Agencia de Gestio d'Ajuts Universitaris i de Recerca-AGAUR, Generalitat de Catalunya [2014SGR1357, 2014SGR0932]
  11. Departament de Salut, Generalitat de Catalunya
  12. Ministerio de Economia, Industria y Competitividad, Spain [SAF2015-68341-R]
  13. European College of Neuropsychopharmacology (ECNP network: 'ADHD across the lifespan')
  14. NARSAD Young Investigator Grant from the Brain & Behavior Research Foundation
  15. European Union's Horizon 2020 research and innovation programme (CoCA) [667302]
  16. Instituto de Salud Carlos III, Ministerio de Economia, Industria y Competitividad, Spain [CD15/00199]
  17. Miguel de Servet contract from the Instituto de Salud Carlos III, Ministerio de Economia, Industria y Competitividad, Spain [CP09/00119, CPII15/00023]
  18. Centro de Investigacion Biomedica en Red de Enfermedades Raras (CIBERER)
  19. NATIONAL HUMAN GENOME RESEARCH INSTITUTE [ZIAHG000175] Funding Source: NIH RePORTER
  20. NATIONAL INSTITUTE ON DRUG ABUSE
  21. NATIONAL INSTITUTE ON ALCOHOL ABUSE AND ALCOHOLISM [ZIAAA000550] Funding Source: NIH RePORTER

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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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