Development of novel lysosome-related signatures and their potential target drugs based on bulk RNA-seq and scRNA-seq for diabetic foot ulcers.

BACKGROUND: Diabetic foot ulcers (DFU) is the most serious complication of diabetes mellitus, which has become a global health problem due to its high morbidity and disability rates and the poor efficacy of conventional treatments. Thus, it is urgent to identify novel molecular targets to improve the prognosis and reduce disability rate in DFU patients. RESULTS: In the present study, bulk RNA-seq and scRNA-seq associated with DFU were downloaded from the GEO database. We identified 1393 DFU-related DEGs by differential analysis and WGCNA analysis together, and GO/KEGG analysis showed that these genes were associated with lysosomal and immune/inflammatory responses. Immediately thereafter, we identified CLU, RABGEF1 and ENPEP as DLGs for DFU using three machine learning algorithms (Randomforest, SVM-RFE and LASSO) and validated their diagnostic performance in a validation cohort independent of this study. Subsequently, we constructed a novel artificial neural network model for molecular diagnosis of DFU based on DLGs, and the diagnostic performance in the training and validation cohorts was sound. In single-cell sequencing, the heterogeneous expression of DLGs also provided favorable evidence for them to be potential diagnostic targets. In addition, the results of immune infiltration analysis showed that the abundance of mainstream immune cells, including B/T cells, was down-regulated in DFUs and significantly correlated with the expression of DLGs. Finally, we found latamoxef, parthenolide, meclofenoxate, and lomustine to be promising anti-DFU drugs by targeting DLGs. CONCLUSIONS: CLU, RABGEF1 and ENPEP can be used as novel lysosomal molecular signatures of DFU, and by targeting them, latamoxef, parthenolide, meclofenoxate and lomustine were identified as promising anti-DFU drugs. The present study provides new perspectives for the diagnosis and treatment of DFU and for improving the prognosis of DFU patients.

PROS1 is a crucial gene in the macrophage efferocytosis of diabetic foot ulcers: a concerted analytical approach through the prisms of computer analysis.

BACKGROUND: Diabetic foot ulcers (DFUs) pose a serious long-term threat because of elevated mortality and disability risks. Research on its biomarkers is still, however, very limited. In this paper, we have effectively identified biomarkers linked with macrophage excretion in diabetic foot ulcers through the application of bioinformatics and machine learning methodologies. These findings were subsequently validated using external datasets and animal experiments. Such discoveries are anticipated to offer novel insights and approaches for the early diagnosis and treatment of DFU. METHODS: In this work, we used the Gene Expression Omnibus (GEO) database's datasets GSE68183 and GSE80178 as the training dataset to build a gene model using machine learning methods. After that, we used the training and validation sets to validate the model (GSE134431). On the model genes, we performed enrichment analysis using both gene set variant analysis (GSVA) and gene set enrichment analysis (GSEA). Additionally, the model genes were subjected to immunological association and immune function analyses. RESULTS: In this study, PROS1 was identified as a potential key target associated with macrophage efflux in DFU by machine learning and bioinformatics approaches. Subsequently, the key biomarker status of PROS1 in DFU was also confirmed by external datasets. In addition, PROS1 also plays a key role in macrophage exudation in DFU. This gene may be associated with macrophage M1, CD4 memory T cells, naïve B cells, and macrophage M2, and affects IL-17, Rap1, hedgehog, and JAK-STAT signaling pathways. CONCLUSIONS: PROS1 was identified and validated as a biomarker for DFU. This finding has the potential to provide a target for macrophage clearance of DFU.

Endothelial ELABELA improves post-ischemic angiogenesis by upregulating VEGFR2 expression.

BACKGROUND: Post-ischemic angiogenesis is critical for perfusion recovery and tissue repair. ELABELA (ELA) plays an essential role in embryonic heart development and vasculogenesis. However, the mechanism of ELA on post-ischemic angiogenesis is poorly characterized. METHODS: We first assessed ELA expression after hind limb ischemia (HLI) in mice. We then established a HLI model in tamoxifen-inducible endothelial-ELA-specific knockout mice (ELAECKO) and assessed the rate of perfusion recovery, capillary density, and VEGFR2 pathway. Knockdown of ELA with lentivirus or siRNA and exogenous addition of ELA peptides were employed to analyze the effects of ELA on angiogenic capacity and VEGFR2 pathway in endothelial cells in vitro. The serum levels of ELA in healthy people and patients with type 2 diabetes mellitus (T2DM) and diabetic foot ulcer (DFU) were detected by a commercial ELISA kit. RESULTS: In murine HLI models, ELA was significantly up-regulated in the ischemic hindlimb. Endothelial-specific deletion of ELA impaired perfusion recovery and angiogenesis. In physiologic conditions, no significant difference in VEGFR2 expression was found between ELAECKO mice and ELAWT mice. After ischemia, the expression of VEGFR2, p-VEGFR2, and p-AKT was significantly lower in ELAECKO mice than in ELAWT mice. In cellular experiments, the knockdown of ELA inhibited endothelial cell proliferation and tube formation, and the addition of ELA peptides promoted proliferation and tube formation. Mechanistically, ELA upregulated the expression of VEGFR2, p-VEGFR2, and p-AKT in endothelial cells under hypoxic conditions. In clinical investigations, DFU patients had significantly lower serum levels of ELA compared to T2DM patients. CONCLUSION: Our results indicated that endothelial ELA is a positive regulator of post-ischemic angiogenesis via upregulating VEGFR2 expression. Targeting ELA may be a potential therapeutic option for peripheral arterial diseases.

Correlational analysis of PLIN1 with inflammation in diabetic foot ulcer wounds.

BACKGROUND: The persistent presence of inflammation is a recognized pathogenic mechanisms of diabetic foot ulcers (DFUs). We aimed to investigate the expression of PLIN1 in tissues from DFU patients and assess its potential association with inflammation-induced damage. METHODS: We performed transcriptome sequencing and correlation analysis of the foot skin from patients with or without DFUs. Additionally, we examined the correlation between PLIN1 and related inflammatory indicators by analyzing PLIN1 expression in tissue and serum samples and through high-glucose stimulation of keratinocytes (HaCaT cells). RESULTS: PLIN1 is upregulated in the tissue and serum from DFU patients. Additionally, PLIN1 shows a positive correlation with leukocytes, neutrophils, monocytes, C-reactive protein, and procalcitonin in the serum, as well as IL-1ß and TNF-α in the tissues. Experiments with Cells demonstrated that reduced expression of PLIN1 leads to significantly decreased expression of iNOS, IL-1ß, IL-6, IL-18, and TNF-α. PLIN1 may mediate wound inflammatory damage through the NF-κB signaling pathway. CONCLUSION: Our findings suggest that PLIN1 mediates the inflammatory damage in DFU, offering new prospects for the treatment of DFU.

Identification and clinical validation of the role of anoikis-related genes in diabetic foot.

This study aims to investigate the role of anoikis-related genes in diabetic foot (DF) by utilizing bioinformatics analysis to identify key genes associated with anoikis in DF. We selected the GEO datasets GSE7014, GSE80178 and GSE68183 for the extraction and analysis of differentially expressed anoikis-related genes (DE-ARGs). GO analysis and KEGG analysis indicated that DE-ARGs in DF were primarily enriched in apoptosis, positive regulation of MAPK cascade, anoikis, focal adhesion and the PI3K-Akt signalling pathway. Based on the LASSO and SVM-RFE algorithms, we identified six characteristic genes. ROC curve analysis revealed that these six characteristic genes had an area under the curve (AUC) greater than 0.7, indicating good diagnostic efficacy. Expression analysis in the validation set revealed downregulation of CALR in DF, consistent with the training set results. GSEA results demonstrated that CALR was mainly enriched in blood vessel morphogenesis, endothelial cell migration, ECM-receptor interaction and focal adhesion. The HPA database revealed that CALR was moderately enriched in endothelial cells, and CALR was found to interact with 63 protein-coding genes. Functional analysis with DAVID suggested that CALR and associated genes were enriched in the phagosome component. CALR shows promise as a potential marker for the development and treatment of DF.

HMOX1 as a therapeutic target associated with diabetic foot ulcers based on single-cell analysis and machine learning.

Diabetic foot ulcers (DFUs) are a serious chronic complication of diabetes mellitus and a leading cause of disability and death in diabetic patients. However, current treatments remain unsatisfactory. Although macrophages are associated with DFU, their exact role in this disease remains uncertain. This study sought to detect macrophage-related genes in DFU and identify possible therapeutic targets. Single-cell datasets (GSE223964) and RNA-seq datasets (GSM68183, GSE80178, GSE134431 and GSE147890) associated with DFU were retrieved from the gene expression omnibus (GEO) database for this study. Analysis of the provided single-cell data revealed the distribution of macrophage subpopulations in the DFU. Four independent RNA-seq datasets were merged into a single DFU cohort and further analysed using bioinformatics. This included differential expression (DEG) analysis, multiple machine learning algorithms to identify biomarkers and enrichment analysis. Finally, key results were validated using reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and Western bolt. Finally, the findings were validated using RT-qPCR and western blot. We obtained 802 macrophage-related genes in single-cell analysis. Differential expression analysis yielded 743 DEGs. Thirty-seven macrophage-associated DEGs were identified by cross-analysis of marker genes with macrophage-associated DEGs. Thirty-seven intersections were screened and cross-analysed using four machine learning algorithms. Finally, HMOX1 was identified as a potentially valuable biomarker. HMOX1 was significantly associated with biological pathways such as the insulin signalling pathway. The results showed that HMOX1 was significantly overexpressed in DFU samples. In conclusion, the analytical results of this study identified HMOX1 as a potentially valuable biomarker associated with macrophages in DFU. The results of our analysis improve our understanding of the mechanism of macrophage action in this disease and may be useful in developing targeted therapies for DFU.

MicroRNA-221-3p inhibits the inflammatory response of keratinocytes by regulating the DYRK1A/STAT3 signaling pathway to promote wound healing in diabetes.

Diabetic foot ulcer (DFU), a serious complication of diabetes, remains a clinical challenge. MicroRNAs affect inflammation and may have therapeutic value in DFU. Here, we find that an miR-221-3p mimic reduces the inflammatory response and increases skin wound healing rates in a mouse model of diabetes, whereas miR-221-3p knockout produced the opposite result. In human keratinocytes cells, miR-221-3p suppresses the inflammatory response induced by high glucose. The gene encoding DYRK1A is a target of miR-221-3p. High glucose increases the expression of DYRK1A, but silencing DYRK1A expression decreases high glucose-induced inflammatory cytokine release via dephosphorylation of STAT3, a substrate of DYRK1A. Application of miR-221-3p mimic to human keratinocytes cells not only decreases DYRK1A expression but also inhibits high glucose-induced production of inflammatory cytokines to promote wound healing. This molecular mechanism whereby miR-221-3p regulates inflammation through the DYRK1A/STAT3 signaling pathway suggests targets and therapeutic approaches for treating DFU.

GLI family zinc finger protein 2 promotes skin fibroblast proliferation and DNA damage repair by targeting the miR-200/ataxia telangiectasia mutated axis in diabetic wound healing.

Diabetic foot ulcer (DFU) is a serious complication of diabetic patients which negatively affects their foot health. This study aimed to estimate the role and mechanism of the miR-200 family in DNA damage of diabetic wound healing. Human foreskin fibroblasts (HFF-1 cells) were stimulated with high glucose (HG). Db/db mice were utilized to conduct the DFU in vivo model. Cell viability was evaluated using 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide assays. Superoxide dismutase activity was determined using detection kits. Reactive oxygen species determination was conducted via dichlorodihydrofluorescein-diacetate assays. Enzyme-linked immunosorbent assay was used to evaluate 8-oxo-7,8-dihydro-2'deoxyguanosine levels. Genes and protein expression were analyzed by quantitative real-time polymerase chain reaction, western blotting, or immunohistochemical analyses. Luciferase reporter gene and RNA immunoprecipitation assays determined the interaction with miR-200a/b/c-3p and GLI family zinc finger protein 2 (GLI2) or ataxia telangiectasia mutated (ATM) kinase. HG repressed cell proliferation and DNA damage repair, promoted miR-200a/b/c-3p expression, and suppressed ATM and GLI2. MiR-200a/b/c-3p inhibition ameliorated HG-induced cell proliferation and DNA damage repair repression. MiR-200a/b/c-3p targeted ATM. Then, the silenced ATM reversed the miR-200a/b/c-3p inhibition-mediated alleviative effects under HG. Next, GLI2 overexpression alleviated the HG-induced cell proliferation and DNA damage repair inhibition via miR-200a/b/c-3p. MiR-200a/b/c-3p inhibition significantly promoted DNA damage repair and wound healing in DFU mice. GLI2 promoted cell proliferation and DNA damage repair by regulating the miR-200/ATM axis to enhance diabetic wound healing in DFU.

Curcumin Promotes Diabetic Foot Ulcer Wound Healing by Inhibiting miR-152-3p and Activating the FBN1/TGF-ß Pathway.

The objective of this study was to investigate the mechanism of curcumin in diabetic foot ulcer (DFU) wound healing. A DFU rat model was established, and fibroblasts were cultured in a high-glucose (HG) environment to create a cell model. Various techniques, including Western blot, RT‒qPCR, flow cytometry, Transwell, cell scratch test and H&E staining, were employed to measure the levels of relevant genes and proteins, as well as to assess cell proliferation, apoptosis, migration, and pathological changes. The results showed that miR-152-3p was overexpressed in DFU patients, while FBN1 was underexpressed. Curcumin was found to inhibit fibroblast apoptosis, promote proliferation, migration, and angiogenesis in DFU rats, and accelerate wound healing in DFU rats. In addition, overexpression of miR-152-3p weakened the therapeutic effect of curcumin, while overexpression of FBN1 reversed the effects of the miR-152-3p mimic. Further investigations into the underlying mechanisms revealed that curcumin expedited wound healing in DFU rats by restoring the FBN1/TGF-ß pathway through the inhibition of miR-152-3p. In conclusion, curcumin can suppress the activity of miR-152-3p, which, in turn, leads to the rejuvenation of the FBN1/TGF-ß pathway and accelerates DFU wound healing.

An Improved Clinical and Genetics-Based Prediction Model for Diabetic Foot Ulcer Healing.

Objective: The goal of this investigation was to use comprehensive prediction modeling tools and available genetic information to try to improve upon the performance of simple clinical models in predicting whether a diabetic foot ulcer (DFU) will heal. Approach: We utilized a cohort study (n = 206) that included clinical factors, measurements of circulating endothelial precursor cells (CEPCs), and fine sequencing of the NOS1AP gene. We derived and selected relevant predictive features from this patient-level information using statistical and machine learning techniques. We then developed prognostic models using machine learning approaches and assessed predictive performance. The presentation is consistent with TRIPOD requirements. Results: Models using baseline clinical and CEPC data had an area under the receiver operating characteristic curve (AUC) of 0.73 (0.66-0.80). Models using only single nucleotide polymorphisms (SNPs) of the NOS1AP gene had an AUC of 0.67 (95% confidence interval, CI: [0.59-0.75]). However, models incorporating baseline and SNP information resulted in improved AUC (0.80, 95% CI [0.73-0.87]). Innovation: We provide a rigorous analysis demonstrating the predictive potential of genetic information in DFU healing. In this process, we present a framework for using advanced statistical and bioinformatics techniques for creating superior prognostic models and identify potentially predictive SNPs for future research. Conclusion: We have developed a new benchmark for which future predictive models can be compared against. Such models will enable wound care experts to more accurately predict whether a patient will heal and aid clinical trialists in designing studies to evaluate therapies for subjects likely or unlikely to heal.

A novel diabetic foot ulcer diagnostic model: identification and analysis of genes related to glutamine metabolism and immune infiltration.

BACKGROUND: Diabetic foot ulcer (DFU) is one of the most common and severe complications of diabetes, with vascular changes, neuropathy, and infections being the primary pathological mechanisms. Glutamine (Gln) metabolism has been found to play a crucial role in diabetes complications. This study aims to identify and validate potential Gln metabolism biomarkers associated with DFU through bioinformatics and machine learning analysis. METHODS: We downloaded two microarray datasets related to DFU patients from the Gene Expression Omnibus (GEO) database, namely GSE134431, GSE68183, and GSE80178. From the GSE134431 dataset, we obtained differentially expressed Gln-metabolism related genes (deGlnMRGs) between DFU and normal controls. We analyzed the correlation between deGlnMRGs and immune cell infiltration status. We also explored the relationship between GlnMRGs molecular clusters and immune cell infiltration status. Notably, WGCNA to identify differentially expressed genes (DEGs) within specific clusters. Additionally, we conducted GSVA to annotate enriched genes. Subsequently, we constructed and screened the best machine learning model. Finally, we validated the predictions' accuracy using a nomogram, calibration curves, decision curve analysis (DCA), and the GSE134431, GSE68183, and GSE80178 dataset. RESULTS: In both the DFU and normal control groups, we confirmed the presence of deGlnMRGs and an activated immune response. From the GSE134431 dataset, we obtained 20 deGlnMRGs, including CTPS1, NAGS, SLC7A11, GGT1, GCLM, RIMKLA, ARG2, ASL, ASNS, ASNSD1, PPAT, GLS2, GLUD1, MECP2, ASS1, PRODH, CTPS2, ALDH5A1, DGLUCY, and SLC25A12. Furthermore, two clusters were identified in DFU. Immune infiltration analysis indicated the presence of immune heterogeneity in these two clusters. Additionally, we established a Support Vector Machine (SVM) model based on 5 genes (R3HCC1, ZNF562, MFN1, DRAM1, and PTGDS), which exhibited excellent performance on the external validation datasetGSE134431, GSE68183, and GSE80178 (AUC = 0.929). CONCLUSION: This study has identified five Gln metabolism genes associated with DFU, revealing potential novel biomarkers and therapeutic targets for DFU. Additionally, the infiltration of immune-inflammatory cells plays a crucial role in the progression of DFU.

Understanding molecular mechanisms and miRNA-based targets in diabetes foot ulcers.

In today's culture, obesity and overweight are serious issues that have an impact on how quickly diabetes develops and how it causes complications. For the development of more effective therapies, it is crucial to understand the molecular mechanisms underlying the chronic problems of diabetes. The most prominent effects of diabetes are microvascular abnormalities such as retinopathy, nephropathy, and neuropathy, especially diabetes foot ulcers, as well as macrovascular abnormalities such as heart disease and atherosclerosis. MicroRNAs (miRNAs), which are highly conserved endogenous short non-coding RNA molecules, have been implicated in several physiological functions recently, including the earliest stages of the disease. By binding to particular messenger RNAs (mRNAs), which cause mRNA degradation, translation inhibition, or even gene activation, it primarily regulates posttranscriptional gene expression. These molecules exhibit considerable potential as diagnostic biomarkers for disease and are interesting treatment targets. This review will provide an overview of the latest findings on the key functions that miRNAs role in diabetes and its complications, with an emphasis on the various stages of diabetic wound healing.

Exploring shared therapeutic targets in diabetic cardiomyopathy and diabetic foot ulcers through bioinformatics analysis.

Advanced diabetic cardiomyopathy (DCM) patients are often accompanied by severe peripheral artery disease. For patients with DCM combined with diabetic foot ulcer (DFU), there are currently no good therapeutic targets and drugs. Here, we investigated the underlying network of molecular actions associated with the occurrence of these two complications. The datasets were downloaded from the Gene Expression Omnibus (GEO) database. We performed enrichment and protein-protein interaction analyses, and screened for hub genes. Construct transcription factors (TFs) and microRNAs regulatory networks for validated hub genes. Finally, drug prediction and molecular docking verification were performed. We identified 299 common differentially expressed genes (DEGs), many of which were involved in inflammation and lipid metabolism. 6 DEGs were identified as hub genes (PPARG, JUN, SLC2A1, CD4, SCARB1 and SERPINE1). These 6 hub genes were associated with inflammation and immune response. We identified 31 common TFs and 2 key miRNAs closely related to hub genes. Interestingly, our study suggested that fenofibrate, a lipid-lowering medication, holds promise as a potential treatment for DCM combined with DFU due to its stable binding to the identified hub genes. Here, we revealed a network involves a common target for DCM and DFU. Understanding these networks and hub genes is pivotal for advancing our comprehension of the multifaceted complications of diabetes and facilitating the development of future therapeutic interventions.

Mapping cellular senescence networks in human diabetic foot ulcers.

Cellular senescence, a cell fate defined by irreversible cell cycle arrest, has been observed to contribute to chronic age-related conditions including non-healing wounds, such as diabetic foot ulcers. However, the role of cellular senescence in the pathogenesis of diabetic foot ulcers remains unclear. To examine the contribution of senescent phenotypes to these chronic wounds, differential gene and network analyses were performed on publicly available bulk RNA sequencing of whole skin biopsies of wound edge diabetic foot ulcers and uninvolved diabetic foot skin. Wald tests with Benjamini-Hochberg correction were used to evaluate differential gene expression. Results showed that cellular senescence markers, CDKN1A, CXCL8, IGFBP2, IL1A, MMP10, SERPINE1, and TGFA, were upregulated, while TP53 was downregulated in diabetic foot ulcers compared to uninvolved diabetic foot skin. NetDecoder was then used to identify and compare context-specific protein-protein interaction networks using known cellular senescence markers as pathway sources. The diabetic foot ulcer protein-protein interaction network demonstrated significant perturbations with decreased inhibitory interactions and increased senescence markers compared to uninvolved diabetic foot skin. Indeed, TP53 (p53) and CDKN1A (p21) appeared to be key regulators in diabetic foot ulcer formation. These findings suggest that cellular senescence is an important mediator of diabetic foot ulcer pathogenesis.

Non-coding RNAs in diabetic foot ulcer- a focus on infected wounds.

Diabetes mellitus is associated with a wide range of neuropathies, vasculopathies, and immunopathies, resulting in many complications. More than 30% of diabetic patients risk developing diabetic foot ulcers (DFUs). Non-coding RNAs (ncRNAs), including microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), play essential roles in various biological functions in the hyperglycaemic environment that determines the development of DFU. Ulceration results in tissue breakdown and skin barrier scavenging, thereby facilitating bacterial infection and biofilm formation. Many bacteria contribute to diabetic foot infection (DFI), including Staphylococcus aureus (S. aureus) et al. A heterogeneous group of "ncRNAs," termed small RNAs (sRNAs), powerfully regulates biofilm formation and DFI healing. Multidisciplinary foot care interventions have been identified for nonhealing ulcers. With an appreciation of the link between disease processes and ncRNAs, a novel therapeutic model of bioactive materials loaded with ncRNAs has been developed to prevent and manage diabetic foot complications.

Stem cell therapy with CRISPR/Cas9-mediated MALAT1 delivery modulates miR-142 and rescues wound healing in rats with age-associated diabetic foot ulcers.

BACKGROUND: Diabetic foot ulcer (DFU) is a serious diabetes complication, significantly impacting the quality of life, particularly in the elderly. Age-associated DFUs pose additional challenges due to impaired healing mechanisms. Our study aims to explore the role of metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) as a miR-142 sponge in repairing diabetic rat foot ulcer tissue under age-associated diabetes, offering a new theoretical basis and therapeutic target for preventing and treating diabetic vascular disease in the elderly. METHODS: Using qPCR, we analyzed MALAT1 and miR-142 expression in EPCs and hUC-MSCs. Targetscan predicted potential interaction targets for MALAT1 and miR-142, confirmed by dual luciferase reporter gene assay. An age-associated diabetic rat model was established using Streptozotocin (STZ) injection. Hypoxia, apoptosis, and angiogenesis-related proteins were assessed through Western Blot. In vitro, miR-142 inhibition and MALAT1 overexpression promoted foot ulcer healing in diabetic rats. RESULTS: MALAT1 acted as a miR-142 sponge, downregulated in hUC-MSCs under high glucose, relevant to age-associated diabetic foot ulcers. MiR-142 negatively regulated SIRT1 and Nrf2. In vitro experiments demonstrated potential significance for age-related DFU treatment. CONCLUSIONS: MALAT1 in human umbilical cord mesenchymal stem cells expedited foot ulcer healing in diabetic rats, particularly in age-associated diabetes, through miR-142 sponge activity. These findings offer insights for novel therapeutic strategies targeting elderly diabetic foot ulcers, emphasizing exogenous stem cell transplantation's potential in effective DFU treatment for the elderly.

Identifying potential pathogenesis and immune infiltration in diabetic foot ulcers using bioinformatics and in vitro analyses.

BACKGROUND: Diabetic foot ulcers (DFU) are among the fastest-growing diseases worldwide. Recent evidence has emphasized the critical role of microRNA (miRNA)-mRNA networks in various chronic wounds, including DFU. In this study, we aimed to clarify the miRNA-mRNA axes associated with the occurrence of DFU. METHODS: Expression profiles of miRNAs and mRNAs were extracted from the Gene Expression Omnibus. Differentially expressed genes and differentially expressed miRNAs were identified, and miRNA-mRNA regulatory axes were constructed through integrated bioinformatics analyses. We validated the miRNA-mRNA axes using quantitative real-time PCR (qPCR) and dual-luciferase reporter assays. We conducted an immune infiltration analysis and confirmed the bioinformatics results using immunofluorescence staining. Single-sample gene set enrichment analysis (ssGSEA) was used to analyze the metabolic mechanisms. RESULTS: miR-182-5p-CHL1/MITF and miR-338-3p-NOVA1 interactions were identified using in silico analysis. The qPCR results showed apparent dysregulation of these miRNA-mRNA axes in DFU. The dual-luciferase reporter assay confirmed that miR-182-5p targeted CHL1 and MITF, and miR-338-3p targeted NOVA1. We conducted an immune infiltration analysis and observed that key genes correlated with decreased infiltration of M1 macrophages and resting mast cells in DFU. Immunofluorescence staining verified the co-localization of CHL1 and tryptase, while MITF and CD68 showed weak positive correlations. Metabolic pathways related to these three genes were identified using ssGSEA. CONCLUSIONS: In summary, the miR-182-5p-CHL1/MITF and miR-338-3p-NOVA1 pathway interactions and decreased infiltration of M1 macrophages and resting mast cells may provide novel clues to the pathogenesis of DFU. TRIAL REGISTRATION: The clinical trial included in this study was registered in the Chinese Clinical Trial Registry ( ChiCTR2200066660 ) on December 13, 2022.

Identification of potential diagnostic biomarkers and immune infiltration features in diabetic foot ulcer by bioinformatics analysis and validation.

Diabetic foot ulcer (DFU) is the most serious and costly chronic complication that may lead to disability and even death in patients suffering from diabetes mellitus (DM). However, the clinical diagnosis and prognosis of DFU is inadequate. There is still a lack of effective biomarkers for its early diagnosis. We obtained the circRNA expression dataset GSE114248 and mRNA expression dataset GSE80178 from the GEO. R software was used to identify the differentially expressed circRNAs (DECs). The mRNAs associated with DFU were identified by a random forest algorithm and intersected with mRNAs predicted by circRNAs. Then, the circRNA-miRNA-mRNA network was established and the hub genes were screened using GO semantic similarity and were validated by the GSE199939 dataset. Meanwhile, the expression level of the biomarkers was verified by RT-PCR assays and immunohistochemistry. Finally, GSEA was conducted to determine differential immune cell infiltration and the immunological cells' relationships with hub genes. We identified three hub genes including KIAA1109, ENPP5, and NRP1 that might play an important role in DFU. ROC curve results also showed a good performance of these three genes in the validation dataset. Furthermore, RT-PCR assays and immunohistochemistry confirmed the results above. Immune infiltration analysis indicated that DFU had a significant increase in Neutrophils. Moreover, three hub genes were closely correlated with a variety of inflammatory cells. KIAA1109, ENPP5, and NRP1 are key hub genes of DFU. They might play an important role in the development of DFU and could be potential biomarkers in DFU.

Unraveling shared risk factors for diabetic foot ulcer: a comprehensive Mendelian randomization analysis.

INTRODUCTION: Diabetic foot ulcer (DFU) stands as a severe diabetic lower extremity complication, characterized by high amputation rates, mortality, and economic burden. We propose using Mendelian randomization studies to explore shared and distinct risk factors for diabetic lower extremity complications. RESEARCH DESIGN AND METHODS: We selected uncorrelated genetic variants associated with 85 phenotypes in five categories at the genome-wide significance level as instrumental variables. Genetic associations with DFU, diabetic polyneuropathy (DPN), and diabetic peripheral artery disease (DPAD) were obtained from the FinnGen and UK Biobank studies. RESULTS: Body mass index (BMI) emerged as the only significant risk factor for DPAD, DPN, and DFU, independent of type 2 diabetes, fasting glucose, fasting insulin, and HbA1c. Educational attainment stood out as the sole significant protective factor against DPAD, DPN, and DFU. Glycemic traits below the type 2 diabetes diagnosis threshold showed associations with DPAD and DPN. While smoking history exhibited suggestive associations with DFU, indicators of poor nutrition, particularly total protein, mean corpuscular hemoglobin, and mean corpuscular volume, may also signal potential DFU occurrence. CONCLUSIONS: Enhanced glycemic control and foot care are essential for the diabetic population with high BMI, limited education, smoking history, and indicators of poor nutrition. By focusing on these specific risk factors, healthcare interventions can be better tailored to prevent and manage DFU effectively.

Exploring the pathogenesis of osteomyelitis accompanied by diabetic foot ulcers using microarray data analysis.

Although numerous studies have shown distinctive similarities between osteomyelitis and diabetic foot ulcers (DFU), the common pathogenesis of both is not fully understood. The current research focuses on an in-depth study of the molecular and pathway mechanisms involved in the complication of these 2 diseases. We downloaded clinical information on osteomyelitis (GSE30119) and DFU (GSE29221) from the GEO database, along with gene expression matrices. Differentially expressed genes (DEGs) among normal individuals and patients with osteomyelitis; normal individuals and patients with DFU were identified by R software, and thus common DEGs were confirmed. We then analyzed these differential genes, including the functional pathway analysis, protein-protein interaction (PPI), modules and hub genes establishment, and transcription factor regulatory networks. We identified 109 common DEGs (46 up-regulated and 63 down-regulated genes) for subsequent analysis. The results of PPI network and the functional pathway analysis revealed the importance of immune response and inflammatory response in both diseases. Among them, chemokines and cytokines were found to be closely related to both osteomyelitis and DFU. In addition, the tumor necrosis factor (TNF) pathway and Staphylococcus aureus infection were found to have more significant roles too. The 12 most essential key genes were later screened by cytoHubba, including matrix metalloproteinases (MMP) 1, MMP3, MMP9, IL8, C-X-C chemokine receptor (CXCR) 2, C-X-C motif chemokine ligand (CXCL) 9, CXCL10, CXCL13, FCGR3B, IL1B, LCN2, S100A12. CXCL10, and MMP1 were validated using the least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE) algorithms. Osteomyelitis and DFU share similar molecular and pathway mechanisms. These common key genes and pathways may provide new directions toward the future study of osteomyelitis and DFU.