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    Loneliness and depression: bidirectional mendelian randomization analyses using data from three large genome-wide association studies

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    Name:
    Sbarra et al_Loneliness_DepMR_ ...
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    Description:
    Final Accepted Manuscript
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    Author
    Sbarra, David A.
    Ramadan, Ferris A.
    Choi, Karmel W.
    Treur, Jorien L.
    Levey, Daniel F.
    Wootton, Robyn E.
    Stein, Murray B.
    Gelernter, Joel
    Klimentidis, Yann C.
    Affiliation
    Department of Psychology, University of Arizona
    Mel & Enid Zuckerman College of Public Health, University of Arizona
    BIO5 Institute, University of Arizona
    Issue Date
    2023-09-21
    Keywords
    Cellular and Molecular Neuroscience
    Psychiatry and Mental health
    molecular biology
    
    Metadata
    Show full item record
    Publisher
    Springer Science and Business Media LLC
    Citation
    Sbarra, D. A., Ramadan, F. A., Choi, K. W., Treur, J. L., Levey, D. F., Wootton, R. E., ... & Klimentidis, Y. C. (2023). Loneliness and depression: bidirectional mendelian randomization analyses using data from three large genome-wide association studies. Molecular psychiatry, 1-8.
    Journal
    Molecular Psychiatry
    Rights
    © 2023, The Author(s), under exclusive licence to Springer Nature Limited.
    Collection Information
    This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
    Abstract
    Major depression (MD) is a serious psychiatric illness afflicting nearly 5% of the world’s population. A large correlational literature suggests that loneliness is a prospective risk factor for MD; correlational assocations of this nature may be confounded for a variety of reasons. This report uses Mendelian Randomization (MR) to examine potentially causal associations between loneliness and MD. We report on analyses using summary statistics from three large genome wide association studies (GWAS). MR analyses were conducted using three independent sources of GWAS summary statistics. In the first set of analyses, we used available summary statistics from an extant GWAS of loneliness to predict MD risk. We used two sources of outcome data: the Psychiatric Genomics Consortium (PGC) meta-analysis of MD (PGC-MD; N = 142,646) and the Million Veteran Program (MVP-MD; N = 250,215). Finally, we reversed analyses using data from the MVP and PGC samples to identify risk variants for MD and used loneliness outcome data from UK Biobank. We find robust evidence for a bidirectional causal relationship between loneliness and MD, including between loneliness, depression cases status, and a continuous measure of depressive symptoms. The estimates remained significant across several sensitivity analyses, including models that account for horizontal pleiotropy. This paper provides the first genetically-informed evidence that reducing loneliness may play a causal role in decreasing risk for depressive illness, and these findings support efforts to reduce loneliness in order to prevent or ameliorate MD. Discussion focuses on the public health significance of these findings, especially in light of the SARS-CoV-2 pandemic.
    Note
    6 month embargo; first published: 21 September 2023
    ISSN
    1359-4184
    EISSN
    1476-5578
    PubMed ID
    37735503
    DOI
    10.1038/s41380-023-02259-w
    Version
    Final accepted manuscript
    Sponsors
    U.S. Department of Health & Human Services | NIH | National Institute on Aging
    ae974a485f413a2113503eed53cd6c53
    10.1038/s41380-023-02259-w
    Scopus Count
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