Integrative analysis of mitochondrial and immune pathways in diabetic kidney disease: identification of AASS and CASP3 as key predictors and therapeutic targets.

IF 3 3区 医学 Q1 UROLOGY & NEPHROLOGY Renal Failure Pub Date : 2025-12-01 Epub Date: 2025-02-23 DOI:10.1080/0886022X.2025.2465811
Xinxin Yu, Yongzheng Hu, Wei Jiang
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Abstract

Objectives: Diabetic kidney disease (DKD) is driven by mitochondrial dysfunction and immune dysregulation, yet the mechanistic interplay remains poorly defined. This study aimed to identify key molecular networks linking mitochondrial and immune pathways to DKD progression, with a focus on uncovering biomarkers and therapeutic targets.

Methods: We conducted an integrative analysis of human DKD cohorts (GSE30122, GSE96804) using weighted gene co-expression network analysis (WGCNA) to identify gene modules enriched for immune response genes and mitochondrial pathways (from MitoCarta3.0). Machine learning algorithms were employed to prioritize key biomarkers for further investigation. Experimental validation was performed using a DKD rat model.

Results: WGCNA revealed significant gene modules associated with immune responses and mitochondrial functions. Machine learning analysis highlighted two central biomarkers: aminoadipate-semialdehyde synthase (AASS) and caspase-3 (CASP3). In the DKD rat model, elevated levels of AASS and CASP3 were found to correlate with increased oxidative stress. Mechanistically, AASS was shown to drive mitochondrial damage via lysine metabolism, while CASP3 amplified inflammatory apoptosis pathways.

Conclusions: Our findings establish AASS and CASP3 as dual biomarkers and therapeutic targets, bridging mitochondrial-immune crosstalk to DKD pathogenesis. This multi-omics framework provides actionable insights for targeting kidney damage in diabetes.

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糖尿病肾病的线粒体和免疫途径的综合分析:AASS和CASP3作为关键预测因子和治疗靶点的鉴定
目的:糖尿病肾病(DKD)是由线粒体功能障碍和免疫失调驱动的,但其机制相互作用仍不明确。本研究旨在确定连接线粒体和免疫途径与DKD进展的关键分子网络,重点是发现生物标志物和治疗靶点。方法:我们使用加权基因共表达网络分析(WGCNA)对人类DKD队列(GSE30122, GSE96804)进行了综合分析,以鉴定免疫应答基因和线粒体途径富集的基因模块(来自MitoCarta3.0)。采用机器学习算法对关键生物标志物进行优先排序,以供进一步研究。采用DKD大鼠模型进行实验验证。结果:WGCNA揭示了与免疫反应和线粒体功能相关的重要基因模块。机器学习分析突出了两个核心生物标志物:氨基己二酸半醛合成酶(AASS)和半胱天冬酶-3 (CASP3)。在DKD大鼠模型中,AASS和CASP3水平升高与氧化应激增加有关。机制上,AASS通过赖氨酸代谢驱动线粒体损伤,而CASP3放大炎症凋亡途径。结论:我们的研究结果确立了AASS和CASP3作为双重生物标志物和治疗靶点,将线粒体-免疫串扰与DKD发病机制联系起来。这种多组学框架为针对糖尿病肾损伤提供了可行的见解。
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来源期刊
Renal Failure
Renal Failure 医学-泌尿学与肾脏学
CiteScore
3.90
自引率
13.30%
发文量
374
审稿时长
1 months
期刊介绍: Renal Failure primarily concentrates on acute renal injury and its consequence, but also addresses advances in the fields of chronic renal failure, hypertension, and renal transplantation. Bringing together both clinical and experimental aspects of renal failure, this publication presents timely, practical information on pathology and pathophysiology of acute renal failure; nephrotoxicity of drugs and other substances; prevention, treatment, and therapy of renal failure; renal failure in association with transplantation, hypertension, and diabetes mellitus.
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