Suppr超能文献

对人类慢性伤口拭子进行免疫标志物分析发现,IL-1β/IL-1RA和CXCL8/CXCL10的比值可作为伤口愈合、感染状态和再生阶段的潜在生物标志物。

Immunomarker profiling in human chronic wound swabs reveals IL-1 beta/IL-1RA and CXCL8/CXCL10 ratios as potential biomarkers for wound healing, infection status and regenerative stage.

作者信息

Rembe Julian-Dario, Garabet Waseem, Augustin Matthias, Dissemond Joachim, Ibing Wiebke, Schelzig Hubert, Stuermer Ewa K

机构信息

Department for Vascular and Endovascular Surgery, University Hospital Duesseldorf (UKD), Heinrich Heine University Duesseldorf, Moorenstrasse 5, 40225, Duesseldorf, Germany.

Institute for Health Services Research in Dermatology and Nursing Professions (IVDP), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany.

出版信息

J Transl Med. 2025 Apr 8;23(1):407. doi: 10.1186/s12967-025-06417-2.

Abstract

BACKGROUND

Chronic wounds, such as diabetic foot ulcers, venous leg ulcers, and post-surgical wound healing disorders pose a significant challenge due to prolonged healing, risk of infection, and impaired quality of life. Persistent inflammation and impaired tissue remodeling are common in these wounds. Traditional diagnostic methods, including visual inspection and microbiological cultures, offer limited insight into the wound micro-environment. Immunomarker profiling could provide a deeper understanding of the molecular mechanisms underpinning wound healing, offering potential biomarkers for infection status and healing progression.

METHODS

This observational, multi-center cohort study, part of the 'Wound-BIOME' project, analyzed 110 swab samples from patients with acute and chronic wounds using multiplex immunoassays. Clinical parameters such as wound type, healing status, regeneration stage, and microbial burden were recorded. Total protein concentration was assessed, and 35 key immunomarkers, including cytokines (e.g. IL- 1α, IL- 1β), chemokines (CCL2, CXCL8, CXCL10), growth factors (FGF- 2, VEGF) and matrix metalloproteinases (MMP- 7, MMP- 9, MMP- 13), were quantified. Statistical analyses were performed to correlate immunomarker levels with clinical outcomes.

RESULTS

Pro-inflammatory markers, such as IL- 1β, IL- 18 and chemokines like CCL2 and CXCL8, were significantly elevated in non-healing and infected wounds compared to healing wounds. The study identified two new immunomarker ratios - IL- 1β/IL- 1RA and CXCL8/CXCL10 - as potential predictors of wound healing status. The IL- 1β/IL- 1RA ratio showed the highest accuracy for distinguishing healing from non-healing wounds (AUC = 0.6837), while the CXCL8/CXCL10 ratio was most effective in identifying infection (AUC = 0.7669).

CONCLUSIONS

Immunomarker profiling via wound swabbing offers valuable insights into the wound healing process. Elevated levels of pro-inflammatory cytokines and MMPs are associated with chronic inflammation and impaired healing. The IL- 1β/IL- 1RA and CXCL8/CXCL10 ratios emerge as promising biomarkers to distinguish between infection and inflammation, with potential in targeted wound care. Further studies are needed to validate these findings and implement them in clinical practice.

摘要

背景

慢性伤口,如糖尿病足溃疡、下肢静脉溃疡和术后伤口愈合障碍,由于愈合时间延长、感染风险以及生活质量受损,构成了重大挑战。这些伤口中持续存在炎症和组织重塑受损的情况很常见。传统的诊断方法,包括目视检查和微生物培养,对伤口微环境的了解有限。免疫标志物分析可以更深入地了解伤口愈合的分子机制,为感染状态和愈合进程提供潜在的生物标志物。

方法

这项观察性、多中心队列研究是“伤口生物群落”项目的一部分,使用多重免疫测定法分析了110例急性和慢性伤口患者的拭子样本。记录了伤口类型、愈合状态、再生阶段和微生物负荷等临床参数。评估了总蛋白浓度,并对35种关键免疫标志物进行了定量,包括细胞因子(如IL-1α、IL-1β)、趋化因子(CCL2、CXCL8、CXCL10)、生长因子(FGF-2、VEGF)和基质金属蛋白酶(MMP-7、MMP-9、MMP-13)。进行了统计分析以关联免疫标志物水平与临床结果。

结果

与愈合伤口相比,非愈合和感染伤口中的促炎标志物,如IL-1β、IL-18以及趋化因子CCL2和CXCL8显著升高。该研究确定了两种新的免疫标志物比率——IL-1β/IL-1RA和CXCL8/CXCL10——作为伤口愈合状态的潜在预测指标。IL-1β/IL-1RA比率在区分愈合伤口和非愈合伤口方面显示出最高的准确性(AUC = 0.6837),而CXCL8/CXCL10比率在识别感染方面最有效(AUC = 0.7669)。

结论

通过伤口拭子进行免疫标志物分析为伤口愈合过程提供了有价值的见解。促炎细胞因子和基质金属蛋白酶水平升高与慢性炎症和愈合受损有关。IL-1β/IL-1RA和CXCL8/CXCL10比率有望成为区分感染和炎症的生物标志物,并在针对性伤口护理中具有潜力。需要进一步的研究来验证这些发现并将其应用于临床实践。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee15/11978031/3a9b74cc5a70/12967_2025_6417_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验