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ORIGINAL RESEARCH article

Front. Endocrinol.

Sec. Renal Endocrinology

Volume 16 - 2025 | doi: 10.3389/fendo.2025.1652402

This article is part of the Research TopicPathophysiology of Diabetic Kidney DiseaseView all 12 articles

Immune regulatory mechanisms of M2 macrophage polarization and efferocytosis in diabetic kidney disease: an integrated screening study with therapeutic implications

Provisionally accepted
Yi  KangYi Kang1Qian  JinQian Jin2Mengqi  ZhouMengqi Zhou3Huijuan  ZhengHuijuan Zheng4Danwen  LiDanwen Li1Xuezhe  WangXuezhe Wang1Jingwei  ZhouJingwei Zhou4Jie  LvJie Lv4Yaoxian  WangYaoxian Wang4*
  • 1Beijing University of Chinese Medicine, Beijing, China
  • 2Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, China
  • 3Beijing Puren Hospital, Beijing, China
  • 4Beijing University of Chinese Medicine Affiliated Dongzhimen Hospital, Beijing, China

The final, formatted version of the article will be published soon.

Background The imbalance in macrophage phenotype transition is a central mechanism driving chronic inflammation in diabetic kidney disease (DKD). Macrophages can polarize toward the M2 phenotype via efferocytosis, exerting anti-inflammatory and pro-resolving effects. However, the identification and functional validation of regulatory genes governing M2 macrophage and efferocytosis in DKD remain to be thoroughly explored. Methods Differentially expressed genes were obtained based on GSE96804 and GSE30122 data sets. Based on efferocytosis-related genes (ERGs) and M2 polarization-related genes (MRGs), ERG and MRG scores were computed in the GSE96804 dataset. Weighted gene co-expression network analysis (WGCNA) was carried out to identify critical module genes. Finally, macrophage-efferocytosis-related DEGs (MEDEGs) were identified. Further, machine learning (ML)—support vector machine (SVM), BORUTA, and lasso regression—were employed to identify hub genes and build Nomogram predictive model. Additionally, hub genes were confirmed through animal experiments. Results A total of 35 MEDEGs were identified. ML recognized 3 hub genes—MCUR1, CYP27B1, and G6PC. Hub genes were notably downregulated in DKD group and exhibited high predictive ability. Furthermore, the Nomogram model based on key genes has shown potential in predicting DKD. The findings were further validated through transcriptome sequencing of DKD model. Conclusion This study uncovered 3 hub genes—MCUR1, CYP27B1, and G6PC—linked to M2 polarization, efferocytosis, and DKD. These genes may contribute to DKD pathogenesis, providing novel targets for early diagnosis and therapeutic interventions in DKD.

Keywords: Diabetic kidney disease, M2 macrophage, Efferocytosis, bioinformatics, Immune regulatory

Received: 23 Jun 2025; Accepted: 15 Sep 2025.

Copyright: © 2025 Kang, Jin, Zhou, Zheng, Li, Wang, Zhou, Lv and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Yaoxian Wang, jinqianqian0620@163.com

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