ORIGINAL RESEARCH article
Front. Endocrinol.
Sec. Diabetes: Molecular Mechanisms
Volume 16 - 2025 | doi: 10.3389/fendo.2025.1574858
Integrated Transcriptomic, Proteomic, and Metabolomic Analysis Unveils Key Roles of Protein and Nucleic Acid Interactions in Diabetic Ulcer Pathogenesis
Provisionally accepted
- 1The Affiliated Hospital of Qingdao University, Qingdao, Shandong Province, China
- 2Nanjing Hospital of Chinese Medicine Affiliated to Nanjing University of Chinese Medicine, Nanjing, Jiangsu Province, China
- 3Beijing Tiantan Hospital, Capital Medical University, Beijing, Beijing Municipality, China
- 4Qilu Hospital, Shandong University, Jinan, Shandong Province, China
- 5Sun Yat-sen Memorial Hospital, Guangzhou, China
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Background: Diabetes mellitus significantly increases the risk of complications, particularly diabetic foot ulcers (DFUs). However, the underlying mechanism remains unclear. This study aimed to assess the overall therapeutic approach in diabetic ulcers.Methods: Using integrated high-throughput multi-omics approaches, including transcriptomics, proteomics, and metabolomics, we constructed a compound-reactionenzyme-gene network to identify the key molecular mechanisms involved in the pathogenesis of DFUs. Major findings were further validated in mouse models of diabetic and control ulcers.Results: Transcriptomics identified 653 differentially expressed genes (DEGs) between diabetic ulcers and control groups. Pathway analysis indicated that these genes were mostly related to inflammation, including the cytokine-cytokine receptor interaction, TNF signaling pathway, and NF-κB signaling pathway. Proteomics revealed 464 upregulated and 419 downregulated proteins, indicating many differentially expressed proteins (DEPs). The pathways with the highest representation of DEPs included diabetic cardiomyopathy, PPAR signaling pathway, and HIF-1 signaling pathway.Metabolomics identified 1,304 metabolites, predominantly lipids (32.1%) and organic acids (20.2%). Principal component analysis and partial least squares discriminant analysis confirmed the model's effectiveness in distinguishing sample groups, whereas bioinformatics analysis revealed significant metabolic pathways, particularly amino acid biosynthesis.Our findings identified critical molecular signatures associated with DFUs and lay the groundwork for developing innovative therapeutic strategies to improve clinical outcomes in patients with this challenging condition.
Keywords: Diabetic foot ulcers, Transcriptomics, Proteomics, Metabolomics, multiomics
Received: 11 Feb 2025; Accepted: 30 May 2025.
Copyright: © 2025 Lu, Gao, Wang, Xu, Chen, Zhang and Gu. 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:
Yixin Zhang, Sun Yat-sen Memorial Hospital, Guangzhou, China
Yunfei Gu, Nanjing Hospital of Chinese Medicine Affiliated to Nanjing University of Chinese Medicine, Nanjing, 210023, Jiangsu Province, 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.