通过基于多组学汇总数据的孟德尔随机化分析鉴定抑郁症中潜在的致病性氧化应激相关基因。

Identifying potential pathogenic oxidative stress-related genes in depression through multi-omics summary-data-based Mendelian randomization analysis.

作者信息

Cheng Junxiang, Liu Zhifen, Zhu Ruifang, Liu Qia, Han Hong, Liu Na, Shi Juan, Han Shifan, Ma Ning

机构信息

Department of Psychiatry, the First Hospital of Shanxi Medical University, Taiyuan 030001, China; School of Nursing, Shanxi Medical University, Taiyuan 030001, China.

Department of Psychiatry, the First Hospital of Shanxi Medical University, Taiyuan 030001, China.

出版信息

J Affect Disord. 2025 Nov 1;388:119734. doi: 10.1016/j.jad.2025.119734. Epub 2025 Jun 20.

DOI:10.1016/j.jad.2025.119734

PMID:40544884

Abstract

PURPOSE

The relationship between oxidative stress-related genes (OSGs) and depression remains unclear. This study investigates causal associations between OSGs and depression susceptibility to elucidate their roles in this mental health condition.

METHODS

This study employed a Summary-data-based Mendelian randomization (SMR) approach to investigate the associations between oxidative stress-related genes (OSGs) and depression risk. Differentially expressed genes (DEGs) associated with depression were identified from merged Gene Expression Omnibus transcriptome data and intersected with OSGs from GeneCards to define depression-related OSGs (DeOSGs). SMR analyses using methylation quantitative trait loci (mQTL), expression quantitative trait loci (eQTL), and protein quantitative trait loci (pQTL) data from large-scale consortia and cohorts evaluated associations between DeOSG methylation, expression, and protein levels with depression risk. Colocalization analysis identified shared causal variants between traits. Functional enrichment and validation using FinnGen cohorts further supported findings.

RESULTS

We identified 488 DeOSGs in depression patients. SMR analyses across mQTL, eQTL, and pQTL levels identified 130 methylation sites, 28 genes, and three proteins linked to depression risk. Ten CpG sites and three DeOSGs showed strong colocalization evidence. Integrative analysis identified four genes (BRAF, CUTA, SLC27A3, and SMARCA4) as potential candidates influencing depression risk through methylation and expression changes. External validation in the FinnGen cohort confirmed a negative association for CUTA expression in blood eQTL data.

CONCLUSIONS

This study identified BRAF, CUTA, SLC27A3, and SMARCA4 as influencing depression risk through methylation and expression changes. These findings provide potential targets for future therapeutic exploration and biomarker development.

摘要

目的

氧化应激相关基因（OSGs）与抑郁症之间的关系尚不清楚。本研究调查OSGs与抑郁症易感性之间的因果关联，以阐明它们在这种心理健康状况中的作用。

方法

本研究采用基于汇总数据的孟德尔随机化（SMR）方法来研究氧化应激相关基因（OSGs）与抑郁症风险之间的关联。从合并的基因表达综合数据库转录组数据中鉴定出与抑郁症相关的差异表达基因（DEGs），并与来自基因卡片的OSGs进行交叉分析，以定义抑郁症相关的OSGs（DeOSGs）。使用来自大规模联盟和队列的甲基化数量性状位点（mQTL）、表达数量性状位点（eQTL）和蛋白质数量性状位点（pQTL）数据进行SMR分析，评估DeOSG甲基化、表达和蛋白质水平与抑郁症风险之间的关联。共定位分析确定了性状之间共享的因果变异。使用芬兰基因队列进行功能富集和验证进一步支持了研究结果。

结果

我们在抑郁症患者中鉴定出488个DeOSGs。跨mQTL、eQTL和pQTL水平的SMR分析确定了130个甲基化位点、28个基因和三种与抑郁症风险相关的蛋白质。十个CpG位点和三个DeOSGs显示出强烈的共定位证据。综合分析确定了四个基因（BRAF、CUTA、SLC27A3和SMARCA4）作为通过甲基化和表达变化影响抑郁症风险的潜在候选基因。芬兰基因队列中的外部验证证实了血液eQTL数据中CUTA表达的负相关。