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Minimal phenotyping yields genome-wide association signals of low specificity for major depression

  • MDD Working Group of the Psychiatric Genomics Consortium
  • Wellcome Sanger Institute
  • European Molecular Biology Laboratory
  • Helmholtz Zentrum München - German Research Center for Environmental Health
  • University of Queensland
  • University of Edinburgh
  • Max Planck Institute of Psychiatry
  • Technical University of Munich
  • King's College London
  • University of Basel
  • University of Bonn
  • University of Marburg
  • University of Greifswald
  • Kaiser Permanente
  • Stanford University
  • University College London
  • Queensland Institute of Medical Research
  • Vrije Universiteit Amsterdam
  • Aarhus University
  • H. Lundbeck A/S
  • Munich Cluster for Systems Neurology (SyNergy)
  • University of Liverpool
  • Harvard University
  • University of Lausanne
  • Johns Hopkins University
  • National Institutes of Health
  • Broad Institute
  • Heidelberg University 
  • Erasmus University Rotterdam
  • Dalhousie University, Faculty of Medicine
  • Karolinska Institutet
  • Columbia University
  • Virginia Commonwealth University
  • University of California at Los Angeles

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

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.

Original languageEnglish
Pages (from-to)437-447
Number of pages11
JournalNature genetics
Volume52
Issue number4
DOIs
Publication statusPublished - 1 Apr 2020

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