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ORIGINAL RESEARCH article

Front. Endocrinol.
Sec. Diabetes: Molecular Mechanisms
Volume 15 - 2024 | doi: 10.3389/fendo.2024.1405726
This article is part of the Research Topic Novel Insights into the Pathophysiology of Diabetes-related Complications: Implications for Improved Therapeutic Strategies, Volume II View all 36 articles

Exploring the pathogenesis, biomarkers, and potential drugs for type 2 diabetes mellitus and acute pancreatitis through a comprehensive bioinformatic analysis

Provisionally accepted
Lei Zhong Lei Zhong Yao Yang Yao Yang *Li Junchen Li Junchen Shuo Liu Shuo Liu Yunshu Zhang Yunshu Zhang *Jifeng Liu Jifeng Liu *Xingchi Jiang Xingchi Jiang *
  • First Affiliated Hospital, Dalian Medical University, Dalian, China

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

    Background: Type 2 diabetes mellitus (T2DM) is a chronic metabolic disease that accounts for > 90% of all diabetes cases. Acute pancreatitis (AP) can be triggered by various factors and is a potentially life-threatening condition. Although T2DM has been shown to have a close relationship with AP, the common mechanisms underlying the two conditions remain unclear. Methods: We identified common differentially expressed genes (DEGs) in T2DM and AP and used functional enrichment analysis and Mendelian randomization to understand the underlying mechanisms. Subsequently, we used several machine learning algorithms to identify candidate biomarkers and construct a diagnostic nomogram for T2DM and AP. The diagnostic performance of the model was evaluated using ROC, calibration, and DCA curves. Furthermore, we investigated the potential roles of core genes in T2DM and AP using GSEA, xCell, and single-cell atlas and by constructing a ceRNA network. Finally, we identified potential small-molecule compounds with therapeutic effects on T2DM and AP using the CMap database and molecular docking.Results: A total of 26 DEGs, with 14 upregulated and 12 downregulated genes, were common between T2DM and AP. According to functional and DisGeNET enrichment analysis, these DEGs were mainly enriched in immune effector processes, blood vessel development, dyslipidemia, and hyperlipidemia. Mendelian randomization analyses further suggested that lipids may be a potential link between AP and T2DM.Machine learning algorithms revealed ARHGEF9 and SLPI as common genes associated with the two diseases. ROC, calibration, and DCA curves showed that the two-gene model had good diagnostic efficacy. Additionally, the two genes were found to be closely associated with immune cell infiltration. Finally, imatinib was identified as a potential compound for the treatment of T2DM and AP.Conclusion: This study suggests that abnormal lipid metabolism is a potential crosstalk mechanism between T2DM and AP. In addition, we established a two-gene 3 model for the clinical diagnosis of T2DM and AP and identified imatinib as a potential therapeutic agent for both diseases.

    Keywords: acute pancreatitis, type 2 diabetes mellitus, molecular docking, machine learning, biomarker

    Received: 23 Mar 2024; Accepted: 04 Nov 2024.

    Copyright: © 2024 Zhong, Yang, Junchen, Liu, Zhang, Liu and Jiang. 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:
    Yao Yang, First Affiliated Hospital, Dalian Medical University, Dalian, China
    Yunshu Zhang, First Affiliated Hospital, Dalian Medical University, Dalian, China
    Jifeng Liu, First Affiliated Hospital, Dalian Medical University, Dalian, China
    Xingchi Jiang, First Affiliated Hospital, Dalian Medical University, Dalian, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.