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Integrated genetic analysis of diabetic complications: Bioinformatics insights into foot ulcers, neuropathy and peripheral artery disease.
Liang, Jiaru; Gong, Xiaoyang; Hu, Xuyang; You, Chong; Zhou, Jiaqi; Gao, Yuling; Zong, Junwei; Liu, Yong.
Afiliación
  • Liang J; Department of Rehabilitation Medicine, The First Affiliated Hospital of Dalian Medical University, Dalian, China.
  • Gong X; Institute (College) of Integrative Medicine, Dalian Medical University, Dalian, China.
  • Hu X; Department of Rehabilitation Medicine, The First Affiliated Hospital of Dalian Medical University, Dalian, China.
  • You C; Institute (College) of Integrative Medicine, Dalian Medical University, Dalian, China.
  • Zhou J; Institute (College) of Integrative Medicine, Dalian Medical University, Dalian, China.
  • Gao Y; Department of Rehabilitation Medicine, The First Affiliated Hospital of Dalian Medical University, Dalian, China.
  • Zong J; Department of Rehabilitation Medicine, The First Affiliated Hospital of Dalian Medical University, Dalian, China.
  • Liu Y; Department of Orthopaedic Surgery, The First Affiliated Hospital of Dalian Medical University, Dalian, China.
Int Wound J ; 21(2): e14748, 2024 Feb.
Article en En | MEDLINE | ID: mdl-38358067
ABSTRACT
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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Úlcera del Pie / Pie Diabético / Diabetes Mellitus Tipo 2 / Neuropatías Diabéticas / Enfermedad Arterial Periférica Tipo de estudio: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Int Wound J Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Úlcera del Pie / Pie Diabético / Diabetes Mellitus Tipo 2 / Neuropatías Diabéticas / Enfermedad Arterial Periférica Tipo de estudio: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Int Wound J Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido