ORIGINAL RESEARCH article
Front. Immunol.
Sec. Autoimmune and Autoinflammatory Disorders: Autoinflammatory Disorders
Volume 16 - 2025 | doi: 10.3389/fimmu.2025.1514243
This article is part of the Research TopicThe Innate Immune System as a Driver of Diabetes and its ComplicationsView all 3 articles
Targeting Macrophages and Ion Homeostasis in T2D: New Genes and Therapeutic Pathways Identified
Provisionally accepted
- 1Shenzhen Second People’s Hospital, Shenzhen, China
- 2Skidmore College, Saratoga Springs, New York, United States
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Introduction: Type 2 diabetes (T2D) is characterized by insulin resistance and chronic inflammation, with macrophages playing a crucial role in pancreatic islet dysfunction. This study explored the intersection of macrophage-specific gene expression and abnormal blood monovalent inorganic cation concentration-related genes (ABRGs) in T2D patients via singlecell RNA sequencing (scRNA-seq) and machine learning to identify key genes and potential therapeutic targets.Methods: ScRNA-seq data from the pancreatic islet cells of 27 nondiabetic (ND) patients and 17 T2D patients were analyzed to identify differentially expressed genes (DEGs) in macrophages. These DEGs were intersected with ABRGs to identify hub genes. Machine learning models were developed to predict T2D, and structural predictions of the hub proteins were performed. PPI networks and regulatory networks involving transcription factors (TFs) and miRNAs were also analyzed. Correlations between hub ABRGs and immune cell infiltration, as well as cytokine responses, were examined via ssGSEA and immune response enrichment analysis (IREA).Results: Sixteen overlapping hub ABRGs, including ATP1A1, CACNA1D, and CLDN10, were identified. The GBM model demonstrated high predictive accuracy, with an AUC of 0.988. Correlation analysis revealed significant relationships between the hub genes and the infiltration of immune cells, particularly macrophages. Cytokine enrichment analysis revealed that macrophages in T2D exhibit a distinct signature of cytokines, including IL15, IFNα1, IFNβ, and IL17F. PPI networks highlighted significant interactions among the hub genes.Regulatory network analysis revealed that STAT3 is a central TF and that miRNAs such as hsa-mir-1-3p are critical regulators.3 Discussion: This study highlights the central roles of macrophages and ABRGs in T2D, identifying novel genes and regulatory networks that contribute to disease progression. The integration of scRNA-seq and machine learning provides valuable insights and potential therapeutic targets for T2D.
Keywords: Type 2 diabetes (T2D), Macrophages, ion homeostasis, Immune infiltration, ScRNA-seq, machine learning, cytokine signatures, therapeutic targets
Received: 20 Oct 2024; Accepted: 10 Jul 2025.
Copyright: © 2025 Mou, Wang, Lu, Wu, Chen, Luo, Wang and Pu. 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: Lisha Mou, Shenzhen Second People’s Hospital, Shenzhen, China
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