| Title: | Exploring the genetic heterogeneity in major depression across diagnostic criteria |
| Journal: | Molecular Psychiatry |
| Published: | 21 Jul 2021 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/34290369/ |
| DOI: | https://doi.org/10.1038/s41380-021-01231-w |
| URL: | https://www.nature.com/articles/s41380-021-01231-w.pdf |
Publication 9774
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Abstract
Major depressive disorder (MDD) is defined differently across genetic research studies and this may be a key source of heterogeneity. While previous literature highlights differences between minimal and strict phenotypes, the components contributing to this heterogeneity have not been identified. Using the cardinal symptoms (depressed mood/anhedonia) as a baseline, we build MDD phenotypes using five components - (1) five or more symptoms, (2) episode duration, (3) functional impairment, (4) episode persistence, and (5) episode recurrence - to determine the contributors to such heterogeneity. Thirty-two depression phenotypes which systematically incorporate different combinations of MDD components were created using the mental health questionnaire data within the UK Biobank. SNP-based heritabilities and genetic correlations with three previously defined major depression phenotypes were calculated (Psychiatric Genomics Consortium (PGC) defined depression, 23andMe self-reported depression and broad depression) and differences between estimates analysed. All phenotypes were heritable (h2SNP range: 0.102-0.162) and showed substantial genetic correlations with other major depression phenotypes (Rg range: 0.651-0.895 (PGC); 0.652-0.837 (23andMe); 0.699-0.900 (broad depression)). The strongest effect on SNP-based heritability was from the requirement for five or more symptoms (1.4% average increase) and for a long episode duration (2.7% average decrease). No significant differences were noted between genetic correlations. While there is some variation, the two cardinal symptoms largely reflect the genetic aetiology of phenotypes incorporating more MDD components. These components may index severity, however, their impact on heterogeneity in genetic results is likely to be limited.</p>
5 Authors
- Bradley S. Jermy
- Kylie P. Glanville
- Jonathan R. I. Coleman
- Cathryn M. Lewis
- Evangelos Vassos
1 Application
| Application ID | Title |
|---|---|
| 18177 | Multi-trait GWAS analyses in the UK Biobank |
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