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January 30, 2019

Progressing Polygenic Medicine in Psychiatry Through Electronic Health Records

Author Affiliations
  • 1Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, England
  • 2Faculty of Life Sciences and Medicine, Department of Medical and Molecular Genetics, King’s College London, London, England
JAMA Psychiatry. 2019;76(5):470-472. doi:10.1001/jamapsychiatry.2018.3975

Depression was a late arrival at the genome-wide association study discovery party, with early meta-analyses showing no evidence for genetic variants associated with depression1 despite sample sizes that have led to success in most other physical and mental traits. With persistence and collaboration, 2 recent meta-analyses have been more successful: more than 100 independent loci are now associated with depression in studies from the Psychiatric Genomics Consortium, UK Biobank, and other cohorts. The depression phenotypes included in these studies range from major depressive disorder cases in clinical cohorts2 to self-reported depression in 23andMe3 and a question on help seeking for depression and anxiety in UK Biobank.4,5 For the discovery of genetic loci, using broad phenotypic definitions of major depression4 increases power, and high genetic correlations between cohorts with diverse recruitment support the validity of this strategy. However, these heterogeneous cohorts make it difficult to assess the relevance of genetic findings in a clinical setting. The article from the Danish iPSYCH study by Musliner and colleagues6 in this issue of JAMA Psychiatry begins to fill this information gap, asking the question of how risk for first-episode depression is conferred by genetic liabilities for major depression, bipolar disorder, and schizophrenia.

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