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Utility of Candidate Genes From an Algorithm Designed to Predict Genetic Risk for Opioid Use Disorder.

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Title: Utility of Candidate Genes From an Algorithm Designed to Predict Genetic Risk for Opioid Use Disorder.
Authors: Davis CN; Mental Illness Research, Education and Clinical Center, Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania.; Center for Studies of Addiction, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia., Jinwala Z; Mental Illness Research, Education and Clinical Center, Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania.; Center for Studies of Addiction, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia., Hatoum AS; Department of Psychological and Brain Sciences, Washington University School of Medicine, St Louis, Missouri., Toikumo S; Mental Illness Research, Education and Clinical Center, Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania.; Center for Studies of Addiction, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia., Agrawal A; Department of Psychiatry, Washington University, St Louis, Missouri., Rentsch CT; Veterans Affairs Connecticut Healthcare System, West Haven.; Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut.; Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, United Kingdom., Edenberg HJ; Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis., Baurley JW; BioRealm LLC, Walnut, California., Hartwell EE; Mental Illness Research, Education and Clinical Center, Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania.; Center for Studies of Addiction, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia., Crist RC; Mental Illness Research, Education and Clinical Center, Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania.; Center for Studies of Addiction, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia., Gray JC; Department of Medical and Clinical Psychology, Uniformed Services University, Bethesda, Maryland., Justice AC; Veterans Affairs Connecticut Healthcare System, West Haven.; Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut., Gelernter J; Veterans Affairs Connecticut Healthcare System, West Haven.; Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut.; Departments of Genetics and Neuroscience, Yale University School of Medicine, New Haven, Connecticut., Kember RL; Mental Illness Research, Education and Clinical Center, Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania.; Center for Studies of Addiction, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia., Kranzler HR; Mental Illness Research, Education and Clinical Center, Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania.; Center for Studies of Addiction, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia.
Corporate Authors: VA Million Veteran Program
Source: JAMA network open [JAMA Netw Open] 2025 Jan 02; Vol. 8 (1), pp. e2453913. Date of Electronic Publication: 2025 Jan 02.
Publication Type: Journal Article; Research Support, U.S. Gov't, Non-P.H.S.; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't
Journal Info: Publisher: American Medical Association Country of Publication: United States NLM ID: 101729235 Publication Model: Electronic Cited Medium: Internet ISSN: 2574-3805 (Electronic) Linking ISSN: 25743805 NLM ISO Abbreviation: JAMA Netw Open Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: Utility of Candidate Genes From an Algorithm Designed to Predict Genetic Risk for Opioid Use Disorder.
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