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May 1, 2026Immunobiology0 citationsOpen Access

Low-abundance plasma proteomics reveals NET-associated molecular signatures in rheumatoid arthritis

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FZFeng ZhuWZWei Emma ZhangXZXuejia Zheng

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Abstract

BACKGROUND: Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by systemic inflammation and multi-organ involvement, yet its molecular mechanisms remain incompletely understood. While plasma proteomics provides valuable insights into disease-associated alterations, most studies focus on high-abundance proteins. Low-abundance plasma proteins, which often serve as critical regulators of immune signaling and inflammatory pathways, remain insufficiently characterized in RA. METHODS: Plasma samples from 27 RA patients and 10 healthy controls (HCs) were analyzed using the SomaScan P11K platform. Differential expression analysis, pathway enrichment, protein-protein interaction network construction, and drug repurposing analyses were performed. Enzyme-linked immunosorbent assay (ELISA) validation was conducted in independent cohorts. RESULTS: A total of 218 differentially expressed low-abundance proteins were identified. Neutrophil extracellular trap (NET) formation was the most significantly enriched KEGG pathway (p = 0.0057), with seven NET-associated proteins showing differential expression. Protein-protein interaction (PPI) analysis revealed functional integration with mitogen-activated protein kinase (MAPK) and chemokine signaling pathways. ELISA validation confirmed differential expression of NCF1, PPIF, and HDAC3. Drug repurposing analysis identified several candidate compounds, among which Delsemidine emerged as one of the top-ranked compounds in the exploratory analysis. CONCLUSIONS: This study systematically characterizes NET-associated molecular signatures in the low-abundance plasma proteome of RA and provides a hypothesis-generating basis for future validation of candidate biomarkers and related pathways.

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Zhu et al. (2026) studied this question.

synapsesocial.com/papers/6a0d7df3cb02dac523a4daa3https://doi.org/10.1016/j.imbio.2026.153188
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