Integrated genetic analysis of diabetic complications: Bioinformatics insights into foot ulcers, neuropathy and peripheral artery disease

• Published in: International wound journal 2024-02, Vol.21 (2), p.e14748-n/a
• Main Authors: Liang, Jiaru, Gong, Xiaoyang, Hu, Xuyang, You, Chong, Zhou, Jiaqi, Gao, Yuling, Zong, Junwei, Liu, Yong
• Format: Article
• Language: English
• Subjects: Amputation; Atherosclerosis; Basic-Leucine Zipper Transcription Factors; Bioinformatics; biomarker; Biomarkers; Datasets; Diabetes; Diabetes Mellitus, Type 2 - complications; Diabetic Foot - diagnosis; diabetic foot ulcer; Diabetic Neuropathies - complications; Diabetic Neuropathies - genetics; diabetic peripheral neuropathy; Disease; Fibrinogen; Foot diseases; Foot Ulcer; Gene expression; GTPase-Activating Proteins; Humans; Immune system; Leg ulcers; Original; Peripheral Arterial Disease - complications; Peripheral Arterial Disease - genetics; peripheral artery disease; Peripheral neuropathy; Skin
• ISSN: 1742-4801; 1742-481X; 1742-481X
• DOI: 10.1111/iwj.14748

Diabetic foot ulcers (DFU), diabetic peripheral neuropathy (DPN) and peripheral arterial disease (PAD) are common complications of diabetes mellitus, while diabetic peripheral neuropathy and peripheral arterial disease contribute to the pathogenesis of diabetic foot ulcers, and the pathogenic mechanisms between these three diseases still need further investigation. The keywords ‘diabetic foot ulcer’, ‘diabetic peripheral neuropathy’ and ‘atherosclerosis’ were used to search for related gene sets in the GEO database. Differentially expressed genes (DEGs) were screened and analysed for GO, KEGG and enrichR functional enrichment. Potential three disease biomarkers were identified by SVM‐SVM‐RFE and LASSO regression analysis. The results were also validated using external datasets and discriminability was measured by area under the ROC curve (AUC). Finally, biomarkers and co‐upregulated genes were analysed through the GSEA and Attie Laboratories diabetes databases. A total of 11 shared genes (KRT16, CD24, SAMD9L, SRGAP2, FGL2, GPR34, DDIT4, NFE2L3, FBLN5, ANXA3 and CPA3), two biomarkers (SAMD9L and FGL2) and one co‐upregulated gene (CD24) were screened. GO and KEGG pathway analysis of DEGs, enrichr enrichment analysis of shared differential genes and GSEA analysis of biomarkers showed that these significant genes were mainly focused on vasoregulatory, inflammatory‐oxidative stress and immunomodulatory pathways. In this study, we used bioinformatics to investigate the intrinsic relationship and potential mechanisms of three common lower extremity complications of diabetes and identified two pivotal genes using the LASSO model and the SVM‐RFE algorithm, which will further help clinicians to understand the relationship between diabetic complications, improve the diagnosis and treatment of diabetic foot problems and help doctors to identify the potential risk factors of diabetic foot.