Foot Ulcer

Macrophage polarization, encompassing classically activated (M1) and alternatively activated (M2) states, is a critical determinant of immune response in wound healing. In diabetic foot ulcers (DFUs), a persistent imbalance favoring pro-inflammatory M1 over anti-inflammatory M2 macrophages drives chronic inflammation and impedes tissue repair. This review delineates the central role of macrophage polarization in DFU pathogenesis and systematically summarizes the key signaling pathways that govern this process, including PI3K/AKT, PPARγ, Notch, and Toll-like receptors (TLRs). We further synthesize these cascades into a novel hierarchical network model, identifying NF-κB and JAK-STAT as the core regulatory hubs. Beyond mechanism, we discuss emerging therapeutic strategies-including pharmacological agents and biomaterial-based approaches-that target macrophage polarization, positioning them as promising adjuvants to standard wound care. By integrating mechanistic insights with therapeutic potential, this review provides an updated framework for developing targeted immunomodulatory therapies to break the cycle of non-healing in DFUs.

BackgroundThis study aimed to investigate the association between systemic inflammatory biomarkers-specifically the systemic inflammatory response index (SIRI), systemic immune inflammation index (SII), and aggregate index of systemic inflammation (AISI)-and the prevalence of diabetic foot ulcer (DFU).MethodWe conducted a cross-sectional analysis using data from three cycles of the National Health and Nutrition Examination Survey (NHANES), supplemented by a single-center retrospective clinical study. Initially, 31,126 participants were screened from NHANES. Binary logistic regression models (both unadjusted and adjusted for covariates) were employed to evaluate the associations between ln SIRI, ln SII, and ln AISI and DFU prevalence. Restricted cubic spline (RCS) analysis was applied to assess nonlinear relationships, and subgroup analyses were performed to examine the stability of associations across strata defined by age, gender, race, body mass index (BMI), smoking status, and hypertension. Additionally, a clinical validation study was conducted from January to December 2023, comprising 34 DFU patients and 68 diabetic controls. We performed multivariable binary logistic regression analyses to assess the independent associations between systemic inflammatory indices and the presence of DFU, adjusting for age, sex, diabetes duration, BMI, and albumin levels. Receiver operating characteristic (ROC) curve analysis was used to preliminarily assess the discriminatory ability of SII, SIRI, and AISI for DFU status.ResultsThe cross-sectional analysis included 135 participants with DFU and 1560 without DFU. Logistic regression revealed consistent positive associations between ln SIRI, ln SII, and ln AISI and DFU prevalence in both unadjusted and adjusted models. RCS analysis indicated linear dose-response relationships for all three biomarkers. Subgroup analyses confirmed that these associations remained stable across demographic and clinical subgroups. In the retrospective clinical study, ln SIRI, ln SII, and ln AISI were significantly associated with DFU prevalence, with odds ratios (ORs) as follows: ln SIRI: OR = 2.51 (95% CI: 1.39-4.54), ln SII: OR = 5.44 (95% CI: 2.48-11.91), and ln AISI: OR = 2.75 (95% CI: 1.59-4.74). After adjusting for key confounders, the associations between these biomarkers and DFU remained consistent in both direction and statistical significance. ROC analysis showed that SII was more reliable than the other two for predicting DFU.ConclusionBy integrating a cross-sectional NHANES-based analysis with a clinical retrospective study, this research demonstrates that elevated levels of SIRI, SII, and AISI are significantly associated with an increased prevalence of DFU. These systemic inflammatory biomarkers may serve as valuable tools for risk assessment in patients with DFU.

Background: Diabetic foot ulcers (DFUs) are chronic wounds with high morbidity and mortality. Secretory proteins coordinate intercellular communication and may regulate inflammation, tissue repair and regeneration, but their contributions to DFU pathogenesis remain unclear. Aim: To discover and validate secretory protein-linked biomarkers that distinguish non-healing DFUs and to explore their potential utility for diagnosis and therapy. Methods: We integrated bulk RNA-sequencing datasets (GSE199939 training set; GSE80178 and GSE143735 validation sets) and a single-cell RNA-sequencing dataset (GSE223964). Differentially expressed genes, secretory protein lists, and weighted gene co-expression networks were intersected to select candidates. Functional enrichment, protein interaction networks and support vector machine-recursive feature elimination identified key markers. We visualized their cell-type distribution at single-cell resolution and validated their expression in external cohorts. Pathway enrichment, gene co-expression networks, ceRNA regulatory analysis and qRT-PCR in patient samples were used for further characterization. Results: Among 4803 differentially expressed genes, 743 overlapped with known secretory proteins. WGCNA highlighted modules strongly associated with DFUs, yielding 386 candidates. SVM-RFE combined with protein interaction analysis pinpointed four secretory proteins-LYZ, MPO, SLCO2B1 and TREM2-as putative biomarkers. Single-cell analyses showed that MPO, LYZ, SLCO2B1 and TREM2 transcripts are detectable in multiple skin-resident and immune cell populations, and that the DFU-associated upregulation of MPO and LYZ is most pronounced within keratinocyte clusters, while MPO and TREM2 remained consistently dysregulated in independent bulk cohorts. MPO-associated genes were enriched for immune and inflammatory pathways, whereas TREM2-linked genes implicated cell cycle and cytoskeletal regulation. GeneMANIA and ceRNA analyses revealed extensive interaction networks. qRT-PCR confirmed differential expression of MPO and TREM2 in clinical DFU tissues. Conclusions: Integrated multi-modal analysis identifies secretory proteins, particularly MPO and TREM2, as central determinants of impaired healing in DFUs. These molecules and their regulatory networks represent promising biomarkers and therapeutic targets for precision management of diabetic wounds.