Minimal phenotyping yields genome-wide association signals of low specificity for major depression
Open accessAbstract
Minimal phenotyping refers to the reliance on the use of a small number of self-reported items for disease case identification, increasingly used in genome-wide association studies (GWAS). Here we report differences in genetic architecture between depression defined by minimal phenotyping and strictly defined major depressive disorder (MDD): the former has a lower genotype-derived heritability that cannot be explained by inclusion of milder cases and a higher proportion of the genome contributing to this shared genetic liability with other conditions than for strictly defined MDD. GWAS based on minimal phenotyping definitions preferentially identifies loci that are not specific to MDD, and, although it generates highly predictive polygenic risk scores, the predictive power can be explained entirely by large sample sizes rather than by specificity for MDD. Our results show that reliance on results from minimal phenotyping may bias views of the genetic architecture of MDD and impede the ability to identify pathways specific to MDD. Genetic analyses of depression based on minimal phenotyping identify nonspecific genetic risk factors shared between major depressive disorder (MDD) and other psychiatric conditions, suggesting that this approach may have limited ability to identify pathways specific to MDD.
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Maximizing power in this analysis required accepting broader biobank phenotyping, which may reduce specificity for the core depression phenotype.
“Maximizing the power available for this analysis comes at the cost of accepting broader biobank phenotyping approaches, which may reduce specificity of findings for the core depression phenotype.11”
From Bi-ancestral depression GWAS in the Million Veteran Program and meta-analysis in >1.2 million individuals highlight new therapeutic directions (2021) · cites this paper as [11]
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References 89 · Cited by 344
Research works printed but not linked: 1
- [41]Northern Ireland Statistics and Research Agency: 2011 Census aggregate data. UK Data Service 10.5257/census/aggregate-2011-1 (2016). · DOI
- Authors
- MDD Working Group of the Psychiatric Genomics Consortium, Cai, N., Revez, J. A., Adams, M. J., Andlauer, T. F. M., Breen, G., Byrne, E. M., Clarke, T.-K., Forstner, A. J., Grabe, H. J., Hamilton, S. P., Levinson, D. F., Lewis, C. M., Lewis, G., Martin, N. G., Milaneschi, Y., Mors, O., Müller-Myhsok, B., Penninx, B. W. J. H., Perlis, R. H., Pistis, G., Potash, J. B., Preisig, M., Shi, J., Smoller, J. W., Streit, F., Tiemeier, H., Uher, R., Van der Auwera, S., Viktorin, A., Weissman, M. M., Kendler, K. S., & Flint, J.
- Affiliations
- European Bioinformatics Institute (GB)
- The University of Queensland (AU)
- University of Edinburgh (GB)
- TUM Klinikum (DE)
- King's College London (GB)
- University of Bonn (DE)
- Universitätsmedizin Greifswald (DE)
- Kaiser Permanente Northern California (US)
- Stanford University (US)
- University College London (GB)
- QIMR Berghofer Medical Research Institute (AU)
- Amsterdam University Medical Centers (NL)
- Aarhus University Hospital (DK)
- Harvard University (US)
- Centre Hospitalier Universitaire Vaudois (CH)
- Johns Hopkins University (US)
- National Cancer Institute (US)
- Broad Institute (US)
- Heidelberg University (DE)
- Dalhousie University (CA)
- Karolinska Institutet (SE)
- New York State Psychiatric Institute (US)
- Virginia Commonwealth University (US)
- Corresponding author
- Cai, Na
- ORCID
- Cai, Na
- Revez, Joana A.
- Adams, Mark J.
- Andlauer, Till F. M.
- Breen, Gerome
- Byrne, Enda M.
- Clarke, Toni-Kim
- Forstner, Andreas J.
- Grabe, Hans J.
- Hamilton, Steven P.
- Levinson, Douglas F.
- Lewis, Cathryn M.
- Lewis, Glyn
- Martin, Nicholas G.
- Milaneschi, Yuri
- Mors, Ole
- Penninx, Brenda W. J. H.
- Perlis, Roy H.
- Pistis, Giorgio
- Potash, James B.
- Preisig, Martin
- Shi, Jianxin
- Smoller, Jordan W.
- Streit, Fabien
- Tiemeier, Henning
- Uher, Rudolf
- Viktorin, Alexander
- Weissman, Myrna M.
- Kendler, Kenneth S.
- Venue
- Nature Genetics
- Published
- 2020-03-30
- Volume
- 52
- Issue
- 4
- Pages
- 437-447
- ISSN
- 1061-4036 (ISSN-L)
- 1546-1718
- PMC
- PMC7906795
- OpenAlex
- W3013660197
- Cited by
- 344
- References
- 89
- Citations by year
- 2026: 44 · 2025: 61 · 2024: 55 · 2023: 51 · 2022: 53 · 2021: 56 · 2020: 20 · 2019: 3 · 2017: 1
- FWCI
- 26.54
- Type
- journal article
- Language
- en
- Open access
- green
- pure.amsterdamumc.nl
- Licence
- Locations
- Nature Genetics (publishedVersion)
- PubMed (publishedVersion)
- Pure Amsterdam UMC (publishedVersion, other-oa)
- EUR Research Repository (Erasmus University Rotterdam) (publishedVersion)
- PubMed Central (acceptedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (acceptedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (submittedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Open access LMU (Ludwid Maxmilian's Universitat Munchen) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- IRIS (submittedVersion)
- Research Portal (King's College London) (submittedVersion)
- Site cant be reached (submittedVersion, other-oa)
- Amsterdam UMC (VU Amsterdam) - Institutional Repository (submittedVersion)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, other-oa)
- PuSH - Publication Server of Helmholtz Zentrum München (submittedVersion)
- SERVAL (Université de Lausanne) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Funders
- ESPOD Fellowship from the European Bioinformatics (EMBL-EBI) and Wellcome Sanger Institute
- National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre at South London Maudsley Foundation Trust and King’s College London
- The CoLaus|PsyCoLaus study was and is supported by research grants from GlaxoSmithKline, the Faculty of Biology and Medicine of Lausanne, and the Swiss National Science Foundation
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Health Sciences › Medicine › Pharmacology › Treatment of Major Depression
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Keywords
- major depressive disorder, case definition, genetic architecture, heritability, polygenic risk score, shared genetic risk, psychiatric comorbidity, genetic specificity, self-reported symptoms
- MeSH terms
- Adult, Aged, Bipolar Disorder, Major Depressive Disorder, Female, Genotype, Humans, Male, Middle Aged, Phenotype, Risk Factors, Sensitivity and Specificity, Genetic Predisposition to Disease, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Genome-Wide Association Study
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