Abstract
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.
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Data availability
The datasets generated and analyzed during the current study are available in the ArrayExpress repository under accession number E-MTAB-16559.
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Acknowledgements
We thank Kanehisa Laboratories for providing permission (Ref: 254385) to use KEGG pathway images in this study.
Funding
This study was supported in part by Gansu Provincial People’s Hospital In-hospital Fund Program, Number: 25GSSYC-4; this study also was supported by grants from Gansu Provincial People’s Hospital In-hospital Fund Program, Number: 20GSSY4-19.
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LZ conceived and designed the study, managed project operations, and reviewed the final version of the manuscript, contributed significantly to manuscript writing, and implemented machine learning algorithms for data analysis. LH primarily responsible for the collection and analysis of specimens and patient data. YW conducted the literature review, provided experimental materials and technical support, and participated in discussions and revisions of the manuscript. YS participated in data analysis, reviewed and revised the manuscript, and contributed to figure preparation. WW interpreted patient data. All authors read and approved the final manuscript.
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The experimental protocol was established, according to the ethical guidelines of the Helsinki Declaration and was approved by the Human Ethics Committee of the People’s Hospital of Gansu Province, the number was 2023 − 299.Written informed consent was obtained from each participant before data collection.
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Zhang, L., Hao, L., Wang, Y. et al. Identification and validation of NETs-associated biomarkers in osteoporosis with diabetes. Sci Rep (2026). https://doi.org/10.1038/s41598-026-44721-z
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DOI: https://doi.org/10.1038/s41598-026-44721-z
