Qiu Zhengqi, Nie Yu, Lin Xu, Du Jun, Kan Juntao, Huang Emma Yun Zhi
The Institute of Mental Psychology, School of Health Management, Guangzhou Medical University, Guangzhou, 510370, China.
School of Public Health, Sun Yat-sen University, No.74, 2nd Zhongshan Road, 510080, Guangzhou, China.
Sci Rep. 2025 Jul 1;15(1):21279. doi: 10.1038/s41598-025-04707-9.
Depression is a common psychiatric comorbidity in individuals with end-stage renal disease (ESRD). However, the underlying biological mechanisms and the precise relationship between depression and renal failure remain unclear. While interventions such as cognitive behavioral therapy and exercise have been shown to alleviate symptoms, the interplay between these conditions and their molecular pathways is poorly understood. An integrated analysis was conducted combining bioinformatics approaches and data from the UK Biobank (UKB) cohort. The UKB study revealed a significant association between renal failure and depression. Gene expression data from the Gene Expression Omnibus (GEO) database were analyzed to identify key co-expression modules using Weighted Gene Co-expression Network Analysis (WGCNA). Protein-protein interaction (PPI) networks were constructed using the STRING database, and immune cell infiltration was assessed with the CIBERSORT tool. UKB data confirmed a robust association between renal failure and depression. Bioinformatics analyses highlighted significant enrichment in pathways related to the acute inflammatory response, specific granule lumen, and immune receptor activity. PPI network analysis identified 23 hub genes, including CYP4F2, KCNA3, KISS1R, LILRA5, and ZC3H12D, as key players in the shared pathophysiology of ESRD and depression. Validation studies further emphasized the roles of LILRA5, CYP4F2, and KISS1R in these mechanisms. This study reveals novel insights into the molecular and immune interactions underlying the comorbidity of renal failure and depression. By combining cohort and bioinformatics analyses, we identify potential therapeutic targets and pathways that may inform innovative treatment strategies.
抑郁症是终末期肾病（ESRD）患者中常见的精神共病。然而，其潜在的生物学机制以及抑郁症与肾衰竭之间的确切关系仍不清楚。虽然认知行为疗法和运动等干预措施已被证明可以缓解症状，但这些病症及其分子途径之间的相互作用却知之甚少。我们结合生物信息学方法和来自英国生物银行（UKB）队列的数据进行了综合分析。UKB研究揭示了肾衰竭与抑郁症之间存在显著关联。我们分析了基因表达综合数据库（GEO）中的基因表达数据，使用加权基因共表达网络分析（WGCNA）来识别关键的共表达模块。利用STRING数据库构建蛋白质-蛋白质相互作用（PPI）网络，并使用CIBERSORT工具评估免疫细胞浸润情况。UKB数据证实了肾衰竭与抑郁症之间存在紧密关联。生物信息学分析突出了与急性炎症反应、特定颗粒腔和免疫受体活性相关的通路中的显著富集。PPI网络分析确定了23个枢纽基因，包括CYP4F2、KCNA3、KISS1R、LILRA5和ZC3H12D，它们是ESRD和抑郁症共同病理生理学中的关键因素。验证研究进一步强调了LILRA5、CYP4F2和KISS1R在这些机制中的作用。本研究揭示了肾衰竭和抑郁症共病背后分子和免疫相互作用的新见解。通过结合队列研究和生物信息学分析，我们确定了潜在的治疗靶点和途径，可为创新治疗策略提供参考。
