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ORIGINAL RESEARCH article

Front. Chem.

Sec. Theoretical and Computational Chemistry

Volume 13 - 2025 | doi: 10.3389/fchem.2025.1666651

Integrated analysis of stem cell-related genes shared between type 2 diabetes mellitus and sepsis

Provisionally accepted
Yubo  WangYubo Wang1Xinhai  JiangXinhai Jiang2Xiaohan  SongXiaohan Song3Zhijie  MaZhijie Ma4*Yan  WangYan Wang5*
  • 1Department of Pharmacy, Beijing Ditan Hospital, Capital Medical University, Beijing, China
  • 2Phase I Clinical Trial Unit, Capital Medical University Beijing Ditan Hospital, Beijing, China
  • 3Tasly Pharmaceutical Group Co., Ltd., Tianjin, China
  • 4Department of Pharmacy, Capital Medical University Beijing Ditan Hospital, Beijing, China
  • 5College of Agroforestry and Medicine, Open University of China, Beijing, China

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

Background: Diabetes-induced immune impairment and insulin resistance increase infection risk, which may progress to sepsis that further deteriorates diabetic status. Stem cell-based interventions show therapeutic potential for both diseases. This study sought to uncover common stem cell-related genes (SCRGs) between T2DM and sepsis. Methods: The GSE15932 dataset for T2DM and GSE65682 dataset for sepsis from the Gene Expression Omnibus (GEO) were utilized to locate common differentially expressed genes (DEGs), which were then intersected with SCRGs to derive shared differentially expressed SCRGs (DE-SCRGs). The stem-cell-related biomarkers were discovered through combining functional similarity analysis, machine learning algorithms, and receiver operating characteristic (ROC) curves. Subsequently, functional enrichment analysis, immune infiltration, and single-cell analyses were conducted to investigate the potential pathways by which biomarkers regulate T2DM and sepsis. Finally, the expression of biomarkers was further verified at both transcriptional and protein levels through the establishment of an in vitro model of T2DM-sepsis. Results: Through a comprehensive analysis, CAPG and DDAH2 were found and those were significantly highly expressed in both T2DM and sepsis. Analysis of functional enrichment demonstrated they were implicated in “FC gamma R-mediated phagocytosis” and “Ribosome”. Immune infiltration indicated a considerable disparity in the quantity of CD8 T cells and monocytes when comparing T2DM versus control groups, as well as sepsis versus control groups. At the cellular level, notable differences in CARG expression among alpha cells, beta cells, delta cells, and pancreatic stellate cells (PSCs) were observed in the two groups being compared. At transcription and protein levels, CAPG and DDAH2 were significantly more highly expressed in the T2DM-sepsis model than in the controls. The results corroborated the bioinformatics analysis conclusions, reinforcing the study's validity. Conclusion: Two common stem cell-related biomarkers (CAPG and DDAH2) and their common pathways between T2DM and sepsis were discovered, providing new insights for further molecular mechanism studies.

Keywords: type 2 diabetes mellitus, Sepsis, Stem Cells, biomarkers, machine learning

Received: 21 Jul 2025; Accepted: 02 Sep 2025.

Copyright: © 2025 Wang, Jiang, Song, Ma 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:
Zhijie Ma, Department of Pharmacy, Capital Medical University Beijing Ditan Hospital, Beijing, China
Yan Wang, College of Agroforestry and Medicine, Open University of China, Beijing, China

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