PSMB4: a potential biomarker and therapeutic target for depression, perspective from integration analysis of depression GWAS data and human plasma proteome

Depression is a common and severe mental disorder that affects more than 300 million people worldwide. While it is known to have a moderate genetic component, identifying specific genes that contribute to the disorder has been challenging. Previous Genome-wide association studies (GWASs) have identified over 100 genomic loci that are significantly associated with depression. But finding useful therapeutic targets and diagnostic biomarkers from this information has proven difficult. To address this challenge, I conducted a plasma protein proteome-wide association study (PWAS) for depression, using human plasma protein QTL (pQTL) and depression GWAS data. I identified four proteins that were significantly associated with depression: BTN3A3 (P value = 6.41 × 10<sup>-06</sup>), PSMB4 (P value = 1.42 × 10<sup>-05</sup>), TIMP4 (P value = 3.77 × 10<sup>-05</sup>), and ITIH1 (P value = 7.86 × 10<sup>-05</sup>). Specifically, I found that BTN3A3 and PSMB4 play a causal role in depression, as confirmed by colocalization and Mendelian Randomization (MR) analysis. Interestingly, I also discovered that PSMB4 was significantly associated with depression in both the brain proteome studies and the plasma PWAS results, which suggests that it may be a particularly promising candidate for further study. Overall, this work has identified 4 new risk proteins for depression and highlights the potential of plasma proteome data for uncovering novel therapeutic targets and diagnostic biomarkers.

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Publication Details

Journal
Translational Psychiatry
Published
2025-02-20
DOI
https://doi.org/10.1038/s41398-025-03279-6
Citations
3
Primary Topic
Genetic Associations and Epidemiology
Type
article
Field-Weighted Citation Impact
5.45

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article

PSMB4: a potential biomarker and therapeutic target for depression, perspective from integration analysis of depression GWAS data and human plasma proteome

Jiewei Liu
3 citations
Translational Psychiatry
Genetic Associations and Epidemiology
5.45
article

PSMB4: a potential biomarker and therapeutic target for depression, perspective from integration analysis of depression GWAS data and human plasma proteome

Jiewei Liu
article en
3 citations

Abstract

Depression is a common and severe mental disorder that affects more than 300 million people worldwide. While it is known to have a moderate genetic component, identifying specific genes that contribute to the disorder has been challenging. Previous Genome-wide association studies (GWASs) have identified over 100 genomic loci that are significantly associated with depression. But finding useful therapeutic targets and diagnostic biomarkers from this information has proven difficult. To address this challenge, I conducted a plasma protein proteome-wide association study (PWAS) for depression, using human plasma protein QTL (pQTL) and depression GWAS data. I identified four proteins that were significantly associated with depression: BTN3A3 (P value = 6.41 × 10<sup>-06</sup>), PSMB4 (P value = 1.42 × 10<sup>-05</sup>), TIMP4 (P value = 3.77 × 10<sup>-05</sup>), and ITIH1 (P value = 7.86 × 10<sup>-05</sup>). Specifically, I found that BTN3A3 and PSMB4 play a causal role in depression, as confirmed by colocalization and Mendelian Randomization (MR) analysis. Interestingly, I also discovered that PSMB4 was significantly associated with depression in both the brain proteome studies and the plasma PWAS results, which suggests that it may be a particularly promising candidate for further study. Overall, this work has identified 4 new risk proteins for depression and highlights the potential of plasma proteome data for uncovering novel therapeutic targets and diagnostic biomarkers.

Translational PsychiatryVol. 15(1)
Wuhan No.1 Hospital (CN), Hubei University of Education (CN)
National Natural Science Foundation of China, Natural Science Foundation of Hubei Province
Openalex Percentile: Top 6%
Genetic Associations and Epidemiology
5.45
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