| Title: | Antidepressant Switching as a Proxy Phenotype for Drug Nonresponse: Investigating Clinical, Demographic, and Genetic Characteristics |
| Journal: | Biological Psychiatry Global Open Science |
| Published: | 10 Apr 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/40510220/ |
| DOI: | https://doi.org/10.1016/j.bpsgos.2025.100502 |
Publication 14845
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Abstract
Background: Selective serotonin reuptake inhibitors (SSRIs) are a first-line pharmacological therapy in major depressive disorder (MDD), but treatment response rates are low. Clinical trials lack the power to study the genetic contribution to SSRI response. Real-world evidence from electronic health records provides larger sample sizes, but novel response definitions are needed to accurately define SSRI nonresponders.</p>
Methods: In the UK Biobank (UKB) (N = 38,813) and Generation Scotland (N = 1777) datasets, SSRI switching was defined using ≤90-day gap between prescriptions for an SSRI and another antidepressant in primary care. Nonswitchers were participants with ≥3 consecutive prescriptions for an SSRI. In the UKB, clinical, demographic, and polygenic score (PGS) associations with switching were determined, and the common-variant heritability was estimated.</p>
Results: In the UKB, 5133 (13.2%) SSRI switchers and 33,680 nonswitchers were defined. The mean time to switch was 28 days (interquartile range, 17-49). Switching patterns were consistent across the UKB and Generation Scotland (n = 498 switchers). Higher annual income and educational levels (odds ratio [OR] [95% CI] for a university degree, 0.73 [0.67-0.79] compared with no qualifications) were associated with lower levels of switching. PGSs for nonremission, based on clinical studies, were associated with increased risk of switching (OR, 1.07 [1.02-1.12], p = .007). MDD PGSs and family history of depression were not significantly associated with switching. Using genome-wide complex trait Bayesian, the single nucleotide polymorphism-based heritability was approximately 4% (SE 0.016) on the observed scale.</p>
Conclusions: This study identified SSRI switching as a proxy for nonresponse, scalable across biobanks with electronic health records, capturing demographics and genetics of treatment nonresponse, and independent of MDD genetics.</p>
15 Authors
- Chris Wai Hang Lo
- Alexandra C. Gillett
- Matthew H. Iveson
- Michelle Kamp
- Chiara Fabbri
- Win Lee Edwin Wong
- Dale Handley
- Oliver Pain
- Evangelos Vassos
- Naomi R. Wray
- Heather C. Whalley
- Danyang Li
- Allan H. Young
- Andrew M. McIntosh
- Cathryn M. Lewis
1 Application
| Application ID | Title |
|---|---|
| 82087 | Genetics and genetic epidemiology of brain-related traits and disorders, and their interplay with physical health |
Enabling scientific discoveries that improve human health