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Phenome-wide association analysis of substance use disorders in a deeply-phenotyped sample

  • Author Footnotes
    ∗ These authors contributed equally
    Rachel L. Kember
    Correspondence
    Corresponding author: Rachel L. Kember, 3535 Market Street Suite 551, Philadelphia, PA 19104,
    Footnotes
    ∗ These authors contributed equally
    Affiliations
    Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA

    Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA
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  • Author Footnotes
    ∗ These authors contributed equally
    Emily E. Hartwell
    Footnotes
    ∗ These authors contributed equally
    Affiliations
    Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA

    Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA
    Search for articles by this author
  • Heng Xu
    Affiliations
    Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
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  • James Rotenberg
    Affiliations
    Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA
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  • Laura Almasy
    Affiliations
    Department of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, PA

    Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
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  • Hang Zhou
    Affiliations
    Department of Psychiatry, Yale University School of Medicine, New Haven, CT

    Department of Psychiatry, VA Connecticut Healthcare System, West Haven, CT
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  • Joel Gelernter
    Affiliations
    Department of Psychiatry, Yale University School of Medicine, New Haven, CT

    Department of Psychiatry, VA Connecticut Healthcare System, West Haven, CT

    Departments of Genetics and Neuroscience, Yale University School of Medicine
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  • Henry R. Kranzler
    Affiliations
    Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA

    Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA
    Search for articles by this author
  • Author Footnotes
    ∗ These authors contributed equally

      Abstract

      Background

      Substance use disorders (SUDs) are associated with a variety of co-occurring psychiatric disorders and other SUDs, which partly reflects genetic pleiotropy. Polygenic risk scores (PRS) and phenome-wide association studies (PheWAS) are useful in evaluating pleiotropic effects. However, the comparatively low prevalence of SUDs in population samples and the lack of detailed information available in electronic health records limits these data sets’ informativeness for such analyses.

      Methods

      We used the deeply phenotyped Yale-Penn sample [(N=10,610 with genetic data; 46.3% African ancestry (AFR), 53.7% European ancestry (EUR)] to examine pleiotropy for 4 major substance-related traits: alcohol use disorder (AUD), opioid use disorder (OUD), smoking initiation (SMK), and lifetime cannabis use (CAN). The sample includes both affected and control subjects interviewed using the Semi-Structured Assessment for Drug Dependence and Alcoholism, a comprehensive psychiatric interview.

      Results

      In AFR individuals PRS for AUD, and in EUR individuals PRS for AUD, OUD, and SMK, were associated with their respective primary DSM diagnoses. These PRS were also associated with additional phenotypes involving the same substance. PheWAS analyses of PRS in EUR individuals identified associations across multiple phenotypic domains, including phenotypes not commonly assessed in PheWAS analyses, such as family environment and early childhood experiences.

      Conclusions

      Smaller, deeply-phenotyped samples can complement large biobank genetic studies with limited phenotyping by providing greater phenotypic granularity. These efforts allow associations to be identified between specific features of disorders and genetic liability for SUDs, which help to inform our understanding of the pleiotropic pathways underlying them.

      Keywords

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