| Title: | Insomnia, proteomic characteristics, and mortality risk in depression: a UK Biobank study |
| Journal: | BMC Psychiatry |
| Published: | 13 Jun 2026 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/42288794/ |
| DOI: | https://doi.org/10.1186/s12888-026-08270-z |
Publication 20642
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Abstract
BackgroundAlthough insomnia is associated with increased mortality in patients with depression, the underlying biological pathways remain unclear. As functional gene products, proteins are well suited to bridge behavioural risk factors and clinical outcomes.ObjectiveTo explore the associations between insomnia, proteomic characteristics, and mortality risk in depressed individuals.MethodsWe included 4,498 patients with depression from the UK Biobank. Insomnia was self-reported; all-cause mortality was the primary outcome. Cox models, LASSO regression, single- and multi-mediator joint mediation analyses, subgroup analyses, competing-risk analyses, and incremental predictive value assessments were performed.Results"Usually insomnia" was an independent predictor of increased mortality (HR = 1.38, 95% CI: 1.05-1.81) and was associated with a 2.3-year shorter life expectancy at age 45. Twenty insomnia-related proteins were identified via LASSO regression and used to construct a proteomic signature, which was significantly associated with mortality (T3 vs. T1: HR = 2.54, 95% CI: 1.95-3.32). Multi-mediator joint analysis revealed that these 20 proteins collectively accounted for 37.2% of the total effect of insomnia on mortality, among which TNFRSF6B, CSTB, and LGALS4 retained statistically significant independent mediating contributions. The proteomic signature demonstrated significant incremental predictive value beyond conventional clinical risk factors.ConclusionInsomnia is associated with increased mortality risk in depressed patients. Multi-mediator analysis identified three proteins (TNFRSF6B, CSTB, and LGALS4) as independent mediators of this association. The insomnia-related proteomic signature may serve as a biomarker for mortality risk stratification.Clinical trial numberNot applicable.</p>
6 Authors
- Xuesong Liu
- Hongli Xu
- Xiaoqian Zhu
- Jiabin Tu
- Kaiyang Lin
- Yansong Guo
1 Application
| Application ID | Title |
|---|---|
| 105322 | Multi-angle exploration of chronic diseases in the elderly |
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