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Symptom-level modelling unravels the shared genetic architecture of anxiety and depression

Author

Listed:
  • Jackson G. Thorp

    (QIMR Berghofer Medical Research Institute
    University of Queensland)

  • Adrian I. Campos

    (University of Queensland
    QIMR Berghofer Medical Research Institute)

  • Andrew D. Grotzinger

    (University of Texas at Austin)

  • Zachary F. Gerring

    (QIMR Berghofer Medical Research Institute)

  • Jiyuan An

    (QIMR Berghofer Medical Research Institute)

  • Jue-Sheng Ong

    (QIMR Berghofer Medical Research Institute)

  • Wei Wang

    (23andMe)

  • Suyash Shringarpure

    (23andMe)

  • Enda M. Byrne

    (University of Queensland)

  • Stuart MacGregor

    (QIMR Berghofer Medical Research Institute)

  • Nicholas G. Martin

    (QIMR Berghofer Medical Research Institute)

  • Sarah E. Medland

    (QIMR Berghofer Medical Research Institute)

  • Christel M. Middeldorp

    (University of Queensland
    Children’s Health Queensland Hospital and Health Service
    VU University Amsterdam)

  • Eske M. Derks

    (QIMR Berghofer Medical Research Institute)

Abstract

Depression and anxiety are highly prevalent and comorbid psychiatric traits that cause considerable burden worldwide. Here we use factor analysis and genomic structural equation modelling to investigate the genetic factor structure underlying 28 items assessing depression, anxiety and neuroticism, a closely related personality trait. Symptoms of depression and anxiety loaded on two distinct, although highly genetically correlated factors, and neuroticism items were partitioned between them. We used this factor structure to conduct genome-wide association analyses on latent factors of depressive symptoms (89 independent variants, 61 genomic loci) and anxiety symptoms (102 variants, 73 loci) in the UK Biobank. Of these associated variants, 72% and 78%, respectively, replicated in an independent cohort of approximately 1.9 million individuals with self-reported diagnosis of depression and anxiety. We use these results to characterize shared and trait-specific genetic associations. Our findings provide insight into the genetic architecture of depression and anxiety and comorbidity between them.

Suggested Citation

  • Jackson G. Thorp & Adrian I. Campos & Andrew D. Grotzinger & Zachary F. Gerring & Jiyuan An & Jue-Sheng Ong & Wei Wang & Suyash Shringarpure & Enda M. Byrne & Stuart MacGregor & Nicholas G. Martin & S, 2021. "Symptom-level modelling unravels the shared genetic architecture of anxiety and depression," Nature Human Behaviour, Nature, vol. 5(10), pages 1432-1442, October.
  • Handle: RePEc:nat:nathum:v:5:y:2021:i:10:d:10.1038_s41562-021-01094-9
    DOI: 10.1038/s41562-021-01094-9
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    Cited by:

    1. Ya Cui & Frederick J. Arnold & Fanglue Peng & Dan Wang & Jason Sheng Li & Sebastian Michels & Eric J. Wagner & Albert R. Spada & Wei Li, 2023. "Alternative polyadenylation transcriptome-wide association study identifies APA-linked susceptibility genes in brain disorders," Nature Communications, Nature, vol. 14(1), pages 1-15, December.

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