| Title: | Plasma proteomics identifies proteins and pathways associated with incident depression in 46,165 adults |
| Journal: | Science Bulletin |
| Published: | 27 Sep 2024 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/39424455/ |
| DOI: | https://doi.org/10.1016/j.scib.2024.09.041 |
Publication 13363
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
Abstract
Proteomic alterations preceding the onset of depression offer valuable insights into its development and potential interventions. Leveraging data from 46,165 UK Biobank participants and 2920 plasma proteins profiled at baseline, we conducted a longitudinal analysis with a median follow-up of 14.5 years to explore the relationship between plasma proteins and incident depression. Linear regression was then used to assess associations between depression-related proteins and brain structures, genetic factors, and stress-related events. Our analysis identified 157 proteins associated with incident depression (P <1.71 × 10-5), including novel associations with proteins such as GAST, PLAUR, LRRN1, BCAN, and ITGA11. Notably, higher expression levels of GDF15 (P = 6.18 × 10-26) and PLAUR (P = 2.88 × 10-14) were linked to an increased risk of depression, whereas higher levels of LRRN1 (P = 4.28 × 10-11) and ITGA11 (P = 3.68 × 10-9) were associated with a decreased risk. Dysregulation of the 157 proteins is correlated with brain regions implicated in depression, including the hippocampus and middle temporal gyrus. Additionally, these protein alterations were strongly correlated with stress-related events, including self-harm events, adult, and childhood trauma. Biological pathway enrichment analysis highlighted the critical roles of the immune response. EGFR and TNF emerged as key proteins in the protein-protein interaction network. BTN3A2, newly linked to incident depression (P = 4.35 × 10-10), was confirmed as a causal factor through Mendelian randomization analysis. In summary, our research identified the proteomic signatures associated with the onset of depression, highlighting its potential for early intervention and tailored therapeutic avenues.</p>
19 Authors
- Jujiao Kang
- Liu Yang
- Tianye Jia
- Wei Zhang
- Lin-Bo Wang
- Yu-Jie Zhao
- Jia You
- Yue-Ting Deng
- Yi-Jun Ge
- Wei-Shi Liu
- Yi Zhang
- Yi-Lin Chen
- Xiao-Yu He
- Barbara J Sahakian
- Yucheng T Yang
- Xing-Ming Zhao
- Jin-Tai Yu
- Jianfeng Feng
- Wei Cheng
1 Application
| Application ID | Title |
|---|---|
| 19542 | Identifying multi-level biomarkers and disease mechanisms for major mental disorders |
Enabling scientific discoveries that improve human health