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PMID: 41851246 已发表 · epublish 英语

Identification and validation of NETs-associated biomarkers in osteoporosis with diabetes.

Scientific reports ·第 16 卷 ·第 1 期 ·2026-03-18

Zhang L, Hao L, Wang Y, Shi Y, Wei W

摘要

Osteoporosis and diabetes represent major global public health challenges. Neutrophil extracellular traps (NETs) serve as key components of the innate immune system by capturing and eliminating pathogens. This exploratory study aimed to preliminarily identify biomarkers associated with NETs in osteoporosis with diabetes and to provide initial insights into underlying molecular mechanisms. A transcriptomic sequencing dataset was integrated to analyze the molecular profiles of comorbid osteoporosis and diabetes (OP-DM). The NETs-related genes (NETs-RGs) were curated from previous literature. As a pilot investigation, biomarkers were identified through differential analysis, machine learning, and receiver operating characteristic (ROC). These candidate biomarkers were further evaluated by qRT-PCR and ELISA. Subsequently, molecular regulatory network construction, immune infiltration analysis, enrichment analysis, and drug prediction were conducted to generate hypotheses. S100A12 and SLC25A37 were identified as potential biomarkers. Their significant upregulation at the protein level (S100A12 and SLC25A37) was observed in an independent cohort. Enrichment analysis suggested that S100A12 was significantly enriched in 68 pathways, including "ECM-receptor interaction" and "maturity onset diabetes of the young". SLC25A37 was significantly enriched in 54 pathways, primarily including "ribosome" and "Toll-like receptor signaling pathway". A total of 7 immune cell types exhibited differences between the two groups. Furthermore, the XIST-hsa-miR-146a-5p-S100A12 and XIST-hsa-miR-7-5-SLC25A37 axes were suggested to have potential regulatory roles. Drugs such as rimegepant and eptinezumab were associated with biomarkers. This preliminary study suggests that S100A12 and SLC25A37 may serve as candidate biomarkers associated with NETs in osteoporosis with diabetes, providing a preliminary theoretical foundation for future larger-scale studies.

关键词
Biomarkers Machine learning Neutrophil extracellular traps Osteoporosis with diabetes
文献信息
期刊
Scientific reports
期刊简称
Sci Rep
ISSN
2045-2322
发表日期
2026-03-18
语言
英语
国家/地区
England
NLM ID
101563288
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