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Inflammation-Related Gene Biomarker For Personalized Diabetic Foot Ulcer Therapy: Optimization and Validation
Abstract   Peer reviewed

Inflammation-Related Gene Biomarker For Personalized Diabetic Foot Ulcer Therapy: Optimization and Validation

Juan Francisco Cortes Troncoso, Karen Marcela Jimenez Rodriguez, Yveeka Marcellus, Aliyah Stephens, Alisha Oropallo, David S Margolis and Kara Spiller
Wound repair and regeneration, v 34(2), pp 25-25
01 Mar 2026
DOI: https://doi.org/10.1111/wrr.70145
PMID: 41889223

Abstract

A particularly frustrating challenge in chronic wound care is that some wounds respond well to treatment while others do not, and there is often no clear reason for this heterogeneity inpatient response. New biomarkers may enable personalized medicine, in which different patients or wounds may be treated differently based on their cellular or molecular profile. Chronic inflammation is strongly associated with impaired wound healing in DFUs, suggesting that markers of inflammation may be useful as biomarkers with the potential to provide actionable information to guide treatment decisions. Previous pilot studies suggested that the Inflammation Index, a measure of gene expression from 4 early-stage pro-inflammatory markers (IL1b,CD80, CCR7, VEGFA) to 3 late-stage inflammation-resolution markers (MRC1, TIMP3, PDGFB) over time, was predictive of the healing trajectory. To support future clinical applications, we chose to use debrided wound tissue, which is routinely collected and discarded during routine wound care, and to measure the Inflammation Index via qRT-PCR. Given the potential degradation of debrided wound tissue, we first investigated the reliability and reproducibility of gene expression measurement as a function of sample degradation and purity using lab-prepared samples generated with primary human macrophages cultured on collagen scaffolds. We found that some genes were more affected by sample quality than others, but by processing the gene expression values into composite ratios, as in the novel Inflammation Index, reliable and reproducible measurements could be obtained from samples with high levels of degradation(RIN 1.9) and contamination (260/280nm ratio 1.4). Additionally, we characterized the reliability of the Inflammation Index in lab-prepared samples exposed to relevant storage and ship-ping conditions, finding that samples could be collected and shipped at room temperature for at least 7 days without compromising biomarker measurement. Next, we measured the Inflammation Index in DFU tissues collected from 44 subjects collected across 5 independent studies, including 14 subjects enrolled in the recently established national Diabetic Foot Consortium (DFC). The Inflammation Index from samples taken at weeks 0 and 4 predicts healing outcomes at 12 weeks. The model achieved a cross-validation accuracy of 89%, with an area under the ROC curve (AUC) of 0.87 (95% CI: 0.7552 - 0.9926,p < 0.0001). These results show that the Inflammation Index can be reliably detected even in samples that are highly degraded or contaminated with nucleic acids and proteins. The Inflammation Index may serve as an effective prognostic bio-marker, providing high accuracy and user-friendliness in wound care clinics. With further validation, it could help identify non-healing patients sooner, enabling personalized care and better selection criteria for clinical trials of new treatments.

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