Polygenic Analyses Show Important Differences Between Major Depressive Disorder Symptoms Measured Using Various Instruments
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Symptoms of major depressive disorder (MDD) are commonly assessed using self-rating instruments like the Patient Health Questionnaire-9 (PHQ-9) (current symptoms) and the Composite International Diagnostic Interview Short-Form (CIDI-SF) (worst-episode symptoms). We performed a systematic comparison between them for their genetic architecture and utility in investigating MDD heterogeneity.
Methods
Using data from the UK Biobank (n = 41,948–109,417), we assessed the single nucleotide polymorphism heritability and genetic correlation (rg) of both sets of MDD symptoms. We further compared their rg with non-MDD traits and used Mendelian randomization to assess whether either set of symptoms has more genetic sharing with non-MDD traits. We also assessed how specific each set of symptoms is to MDD using the metric polygenic risk score pleiotropy. Finally, we used genomic structural equation modeling to identify factors that explain the genetic covariance between each set of symptoms.
Results
Corresponding symptoms reported through the PHQ-9 and CIDI-SF have low to moderate genetic correlations (rg = 0.43–0.87), and this cannot be fully attributed to different severity thresholds or the use of a skip structure in the CIDI-SF. Both Mendelian randomization and polygenic risk score pleiotropy analyses showed that PHQ-9 symptoms are more associated with traits that reflect general dysphoria, whereas the skip structure in the CIDI-SF allows for the identification of heterogeneity among likely MDD cases. Finally, the 2 sets of symptoms showed different factor structures in genomic structural equation modeling, reflective of their genetic differences.
Conclusions
MDD symptoms assessed using the PHQ-9 and CIDI-SF are not interchangeable; the former better indexes general dysphoria, while the latter is more informative about within-MDD heterogeneity.
Keywords
DepressionFactor analysisGeneticsGWASHeterogeneitySymptoms
| Originalsprog | Engelsk |
|---|---|
| Tidsskrift | Biological Psychiatry |
| Antal sider | 12 |
| ISSN | 0006-3223 |
| DOI | |
| Status | Accepteret/In press - 2024 |
Bibliografisk note
Funding Information:
LH, ST, VZ, and NC are supported by the Technical University of MunichGlobal Incentive Fund. The iPSYCH team is supported by Lundbeck Foundation (Grants Nos. R102-A9118, R155-2014-1724, and R248-2017-2003); the National Institute of Mental Health (Grant No. 1R01MH124851-01); and the Universities and University Hospitals of Aarhus and Copenhagen. The Danish National Biobank resource is supported by the Novo Nordisk Foundation. High-performance computer capacity for handling and statistical analysis of iPSYCH data on the GenomeDK high-performance computing facility is provided by the Center for Genomics and Personalised Medicine and the Centre for Integrative Sequencing, iSEQ, Aarhus University, Denmark. AJS is supported by Lundbeckfonden (Fellowship No. R335-2019-2318). VA is supported by Lundbeck Foundation postdoctoral (Grant No. R380-2021-1465). ST is supported by a Medical Research Council UK Ph.D. Studentship. We thank Jonathan Flint, Noah Zaitlen, Joel Mefford, Andrew Dahl, Richard Border, and Eiko Fried for constructive discussions and feedback on the paper. A previous version of this article was published as a preprint on medRxiv: https://www.medrxiv.org/content/10.1101/2023.02.27.23286527v1. LH and NC wrote the paper. VZ, KK, and NC designed the study. ST supported the Mendelian randomization analyses. MK, VA, TW, and AJS supported the iPSYCH analyses. LH and NC performed all analyses. All authors reviewed the paper. This research was conducted under ethical approval from the UK Biobank Resource under application No. 28709. The use of iPSYCH data follows the standards of the Danish Scientific Ethics Committee, the Danish Health Data Authority, the Danish Data Protection Agency, and the Danish Neonatal Screening Biobank Steering Committee. Data access was via secure portals in accordance with Danish data protection guidelines set by the Danish Data Protection Agency, the Danish Health Data Authority, and Statistics Denmark. UK Biobank genotype and phenotype data used in this study are from the full release of the UK Biobank Resource obtained under application No. 28709. We used publicly available summary statistics from PGC29 (https://www.med.unc.edu/pgc/results-and-downloads). The individual-level data from the iPSYCH cohort are not publicly available due to institutional restrictions on data sharing and privacy concerns. Summary statistics for all PHQ-9 and worst-episode symptoms presented in this paper are available on https://doi.org/10.6084/m9.figshare.22041212. Publicly available tools that are used in data analyses are described wherever relevant in the Methods and Materials and Key Resource Table. Custom code is available at https://github.com/caina89/MDDSymptoms. The authors report no biomedical financial interests or potential conflicts of interest.
Funding Information:
LH, ST, VZ, and NC are supported by the Technical University of Munich Global Incentive Fund. The iPSYCH team is supported by Lundbeck Foundation (Grants Nos. R102-A9118 , R155-2014-1724 , and R248-2017-2003 ); the National Institute of Mental Health (Grant No. 1R01MH124851-01 ); and the Universities and University Hospitals of Aarhus and Copenhagen . The Danish National Biobank resource is supported by the Novo Nordisk Foundation . High-performance computer capacity for handling and statistical analysis of iPSYCH data on the GenomeDK high-performance computing facility is provided by the Center for Genomics and Personalised Medicine and the Centre for Integrative Sequencing, iSEQ, Aarhus University, Denmark. AJS is supported by Lundbeckfonden (Fellowship No. R335-2019-2318 ). VA is supported by Lundbeck Foundation postdoctoral (Grant No. R380-2021-1465 ). ST is supported by a Medical Research Council UK Ph.D. Studentship .
Publisher Copyright:
© 2023 Society of Biological Psychiatry
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