Novel therapeutic targets for major depressive disorder related to oxidative stress identified by integrative
Xiaojun Shao1, Yuan Wang2, Zhongli Geng1,3
1Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, 110001, China.
Abstract:
Oxidative stress (OS) is strongly implicated in the pathophysiology of major depressive disorder (MDD) but the molecular mechanisms remain largely unknown. The purpose of this study is to identify genes related to both OS and MDD, and further to evaluate the utility of these genes as diagnostic markers and potential treatment targets. We searched datasets related to MDD from the Gene Expression Omnibus (GEO) database for differentially expressed genes (DEGs) also related to OS according to GeneCards. Bioinformatics analyses and machine learning algorithms were used to identify hub genes mediating OS-MDD interactions. A summary data-based Mendelian randomization (SMR) approach was employed to identify possible causal genes for MDD from blood tissue eQLT data. These investigations identified 32 genes mediating OS-MDD interactions, while SMR analysis identified KCNE1 (OR = 1.057, 95%CI = 1.013-1.102, P value = 0.010), MAPK3 (OR = 1.023, 95%CI = 1.004-1.043, P value = 0.020), and STIP1 (OR = 0.792, 95%CI = 0.641-0.979, P value = 0.031) as OS-related causal genes for MDD. These genes may thus serve as useful diagnostic markers and potential therapeutic targets.
Insights
This study identifies 32 genes linking oxidative stress and major depressive disorder (MDD). Key causal genes like KCNE1, MAPK3, and STIP1 may offer new diagnostic and therapeutic strategies for MDD.
Area of Science:
- Biomedical research
- Genetics
- Neuroscience
Background:
- Oxidative stress (OS) plays a significant role in major depressive disorder (MDD) pathophysiology.
- The precise molecular mechanisms underlying this connection remain largely undetermined.
Purpose of the Study:
- To identify genes associated with both OS and MDD.
- To assess the potential of these genes as diagnostic markers and therapeutic targets for MDD.
Main Methods:
- Utilized Gene Expression Omnibus (GEO) datasets for MDD.
- Applied bioinformatics and machine learning to find OS-MDD interaction hub genes.
- Employed a summary data-based Mendelian randomization (SMR) approach using blood tissue eQTL data.
Main Results:
- Identified 32 genes mediating OS-MDD interactions.
- Discovered KCNE1, MAPK3, and STIP1 as OS-related causal genes for MDD.
- KCNE1 (OR=1.057), MAPK3 (OR=1.023), and STIP1 (OR=0.792) showed significant associations.
Conclusions:
- The identified genes, particularly KCNE1, MAPK3, and STIP1, show promise as diagnostic biomarkers for MDD.
- These genes represent potential novel therapeutic targets for managing MDD.
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