Transcriptomics-based exploration of shared M1-type macrophage-related biomarker in acute kidney injury after kidney transplantation and acute rejection after kidney transplantation

IF 1.6 4区医学 Q4 IMMUNOLOGY Transplant immunology Pub Date : 2024-05-28 DOI:10.1016/j.trim.2024.102066

Jun Pei , Jie Zhang , Chengjun Yu , Jin Luo , Sheng Wen , Yi Hua , Guanghui Wei

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Abstract

Background

Macrophage type 1 (M1) cells are associated with both acute kidney injury (AKI) during kidney transplantation and acute rejection (AR) after kidney transplantation. Our study explored M1-related biomarkers involved in both AKI and AR and their potential biological functions.

Methods

Based on the Gene Expression Omnibus (GEO) database, the immune cell infiltration levels and differentially expressed genes were examined in AKI and AR in the kidney transplantation; M1-related genes shared in AKI and AR were identified using weighted gene co-expression analysis (WGCNA) system. Subsequently, protein-protein interaction (PPI) networks and machine learning methods to identify Hub genes and construct diagnostic models. Both AKI model and AR rat models were built to validate the expressions of Hub genes and test the injury phenotype, oxidative stress markers, and inflammatory factors. Finally, the transcription factor (TF)-Hub gene and micro-RNA (miRNA)-Hub gene regulatory networks were constructed based on identified Hub genes.

Results

Out of 2167 differential expression genes (DEGs) in AKI and 2100 DEGs in AR, four M1-related Hub genes were obtained by PPI networks and machine learning methods, namely GBP2, TYROBP, CCR5, and TLR8. The calibration curves in the nomogram diagnostic model for these four Hub genes suggested the same predictive probability as an ideal model for AKI and AR after kidney transplantation (AUC values of the area under the ROC curve were all >0.7). The same observations were confirmed in ischemia reperfusion injury (IRI) and AR rat models by identifying common four Hub genes (GBP2, TYROBP, TLR8, and CCR5). Western blots showed that these four Hub genes were significantly different in rat models of IRI and AR (all p<0.05). Compared with the control group, IRI and AR groups showed aggravated histopathological damage and increased secretion of oxidative stress markers and inflammatory factors in rat kidneys (all p<0.05). Finally, TF-Hub and miRNA-Hub gene regulatory networks were constructed to provide a theoretical basis for the regulation of Hub genes.

Conclusion

We identified four macrophage M1-related Hub genes shared among AKI and AR after kidney transplantation. These genes may be considered for diagnosis of AKI and AR after kidney transplantation.

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基于转录组学的肾移植后急性肾损伤和肾移植后急性排斥反应中共同的 M1 型巨噬细胞相关生物标志物的探索

背景：1型巨噬细胞（M1）与肾移植过程中的急性肾损伤（AKI）和肾移植后的急性排斥反应（AR）有关。我们的研究探讨了参与急性肾损伤和急性排斥反应的M1相关生物标志物及其潜在的生物学功能：方法：基于基因表达总库（Gene Expression Omnibus，GEO）数据库，研究了肾移植AKI和AR中的免疫细胞浸润水平和差异表达基因；使用加权基因共表达分析（WGCNA）系统鉴定了AKI和AR中共有的M1相关基因。随后，利用蛋白质-蛋白质相互作用（PPI）网络和机器学习方法识别枢纽基因并构建诊断模型。建立了 AKI 模型和 AR 大鼠模型，以验证 Hub 基因的表达，并检测损伤表型、氧化应激标志物和炎症因子。最后，根据已识别的Hub基因构建了转录因子（TF）-Hub基因和微RNA（miRNA）-Hub基因调控网络：结果：在2167个AKI差异表达基因（DEGs）和2100个AR差异表达基因（DEGs）中，通过PPI网络和机器学习方法获得了4个与M1相关的Hub基因，即GBP2、TYROBP、CCR5和TLR8。这四个Hub基因的提名图诊断模型的校准曲线表明，它们对肾移植后AKI和AR的预测概率与理想模型相同（ROC曲线下面积的AUC值均大于0.7）。在缺血再灌注损伤（IRI）和AR大鼠模型中，通过识别共同的四个Hub基因（GBP2、TYROBP、TLR8和CCR5），证实了同样的观察结果。Western 印迹显示，这四个 Hub 基因在 IRI 和 AR 大鼠模型中存在显著差异（所有 pConclusion）：我们发现了肾移植后 AKI 和 AR 中共有的四个巨噬细胞 M1 相关 Hub 基因。这些基因可用于肾移植后 AKI 和 AR 的诊断。

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来源期刊

Transplant immunology 医学-免疫学

CiteScore

2.10

自引率

13.30%

发文量

198

审稿时长

48 days

期刊介绍： Transplant Immunology will publish up-to-date information on all aspects of the broad field it encompasses. The journal will be directed at (basic) scientists, tissue typers, transplant physicians and surgeons, and research and data on all immunological aspects of organ-, tissue- and (haematopoietic) stem cell transplantation are of potential interest to the readers of Transplant Immunology. Original papers, Review articles and Hypotheses will be considered for publication and submitted manuscripts will be rapidly peer-reviewed and published. They will be judged on the basis of scientific merit, originality, timeliness and quality.