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Polygenic liability to depression is associated with multiple medical conditions in the electronic health record: Phenome-wide association study of 46,782 individuals

  • Yu Fang
    Correspondence
    Corresponding author: Yu Fang, 205 Zina Pitcher Place, Ann Arbor, MI, 48109, USA.
    Affiliations
    Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI, USA
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  • Lars G. Fritsche
    Affiliations
    Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA

    Rogel Cancer Center, University of Michigan Medicine, Ann Arbor, MI, USA

    Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
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  • Bhramar Mukherjee
    Affiliations
    Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA

    Rogel Cancer Center, University of Michigan Medicine, Ann Arbor, MI, USA

    Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA

    Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA
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  • Srijan Sen
    Affiliations
    Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI, USA

    Department of Psychiatry, University of Michigan Medicine, Ann Arbor, MI, USA
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  • Leah S. Richmond-Rakerd
    Affiliations
    Department of Psychology, University of Michigan, Ann Arbor, MI, USA
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      Abstract

      Background

      Major depressive disorder (MDD) is a leading cause of disease-associated disability, with much of the increased burden due to psychiatric and medical comorbidity. This comorbidity partly reflects common genetic influences across conditions. Integrating molecular-genetic tools with health records enables tests of association with the broad range of physiological and clinical phenotypes. However, standard phenome-wide association studies (PheWAS) analyze associations with individual genetic variants. For polygenic traits like MDD, aggregate measures of genetic risk may yield greater insight into associations across the clinical phenome.

      Methods

      We tested for associations between a genome-wide polygenic risk score (PRS) for MDD and medical and psychiatric traits in a PheWAS of 46,782 unrelated, European-ancestry participants from the Michigan Genomics Initiative.

      Results

      The MDD-PRS was associated with 211 traits from 15 medical and psychiatric disease categories at the phenome-wide significance threshold. After excluding patients with depression, continued associations were observed with respiratory, digestive, neurological, and genitourinary conditions; neoplasms; and mental disorders. Associations with tobacco use disorder, respiratory conditions, and genitourinary conditions persisted after accounting for genetic overlap between depression and other psychiatric traits. Temporal analyses of time-at-first-diagnosis indicated that depression disproportionately preceded chronic pain and substance-related disorders, while asthma disproportionately preceded depression.

      Conclusions

      The present results can inform the biological links between depression and both mental and systemic diseases. Although MDD-PRS cannot currently forecast health outcomes with precision at the individual level, as molecular-genetic discoveries for depression increase, these tools may augment risk prediction for medical and psychiatric conditions.

      Keywords

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