Inflammatory proteins and depression: bidirectional analyses using UK Biobank and MR

Abstract Background Inflammatory processes have been implicated in depression, but whether inflammation precedes or follows the onset of depression remains unclear. We investigated the directionality and underlying mechanisms of this association using longitudinal epidemiological approaches, proteomic analyses and Mendelian randomization (MR). Methods In this prospective cohort study, we analysed plasma protein data from the UK Biobank and incorporated publicly available results from GWASs on plasma proteins and depression. For the plasma protein analyses, participants were classified into two groups: those who developed depression after the baseline assessments (n = 8,085), when plasma proteins were measured using the Olink assay, and those with a depression diagnosis before or at baseline (n = 6,076). Results Adjusted logistic and linear regression analyses identified proteins associated with future and prior depression. Of 762 inflammatory proteins, 270 were associated with future and 157 with prior depression after FDR correction. These were further analysed using MR. Two proteins had a potential causal association with depression, both passing MR sensitivity analyses. Conversely, depression was potentially causally associated with 42 proteins, of which 9 passed sensitivity analyses. Pathway enrichment analyses indicated that proteins linked to future depression were enriched in immune and leukocyte activation and leukocyte migration pathways, whereas those linked to prior depression were enriched in cytokine signalling, T-cell activation and interleukin-10 regulation. Conclusions These findings identify immune system-related proteins associated with both the development and presence of depression, suggesting that different inflammatory pathways may be activated depending on the direction of the association. This evidence may contribute to the identification of depression subtypes with inflammatory components and inform future therapeutic targets. Key messages • Inflammatory proteins show distinct biological signatures in future versus prior depression, suggesting direction-specific pathways linking inflammation and depression onset. • This study identifies immune system-related proteins that may contribute to the development of novel drug targets for depression prevention and treatment of its inflammatory components.

Institutions

Publication Details

Journal
European Journal of Public Health
Published
2025-10-01
DOI
https://doi.org/10.1093/eurpub/ckaf161.1791
Primary Topic
Tryptophan and brain disorders
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Inflammatory proteins and depression: bidirectional analyses using UK Biobank and MR

European Journal of Public Health
Tryptophan and brain disorders
article

Inflammatory proteins and depression: bidirectional analyses using UK Biobank and MR

article en

Abstract

Abstract Background Inflammatory processes have been implicated in depression, but whether inflammation precedes or follows the onset of depression remains unclear. We investigated the directionality and underlying mechanisms of this association using longitudinal epidemiological approaches, proteomic analyses and Mendelian randomization (MR). Methods In this prospective cohort study, we analysed plasma protein data from the UK Biobank and incorporated publicly available results from GWASs on plasma proteins and depression. For the plasma protein analyses, participants were classified into two groups: those who developed depression after the baseline assessments (n = 8,085), when plasma proteins were measured using the Olink assay, and those with a depression diagnosis before or at baseline (n = 6,076). Results Adjusted logistic and linear regression analyses identified proteins associated with future and prior depression. Of 762 inflammatory proteins, 270 were associated with future and 157 with prior depression after FDR correction. These were further analysed using MR. Two proteins had a potential causal association with depression, both passing MR sensitivity analyses. Conversely, depression was potentially causally associated with 42 proteins, of which 9 passed sensitivity analyses. Pathway enrichment analyses indicated that proteins linked to future depression were enriched in immune and leukocyte activation and leukocyte migration pathways, whereas those linked to prior depression were enriched in cytokine signalling, T-cell activation and interleukin-10 regulation. Conclusions These findings identify immune system-related proteins associated with both the development and presence of depression, suggesting that different inflammatory pathways may be activated depending on the direction of the association. This evidence may contribute to the identification of depression subtypes with inflammatory components and inform future therapeutic targets. Key messages • Inflammatory proteins show distinct biological signatures in future versus prior depression, suggesting direction-specific pathways linking inflammation and depression onset. • This study identifies immune system-related proteins that may contribute to the development of novel drug targets for depression prevention and treatment of its inflammatory components.

European Journal of Public HealthVol. 35(Supplement_4)
Broad Institute (US), University of Helsinki (FI), Finland University (FI), Institute for Molecular Medicine Finland (FI), University College London (GB)
Good health and well-being
Openalex Percentile: Top 52%
Tryptophan and brain disorders
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.