Evidence map›Paper›PMID 42384338›Full record

ArticleAnalytical sciences : the international journal of the Japan Society for Analytical Chemistry2026

Isolation of synovial fluid exosomes using phospholipid molecular imprinting technology and discovery of early diagnostic markers for osteoarthritis.

Hualong Deng, Chaoyong Jiang, Huaxin Deng, Yaohua Li, Baoliang Zhang

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Article in Analytical sciences : the international journal of the Japan Society for Analytical Chemistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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5 authors.

Hualong DengDepartment of Spine Surgery, The Central Hospital of Yongzhou, Yongzhoum, 425000, Hunan, China.
Chaoyong JiangDepartment of Spine Surgery, The Central Hospital of Yongzhou, Yongzhoum, 425000, Hunan, China.
Huaxin DengDepartment of Spine Surgery, The Central Hospital of Yongzhou, Yongzhoum, 425000, Hunan, China.
Yaohua LiCollege of Life Sciences and Technology, China Pharmaceutical University, Nanjing, 211198, China.
Baoliang ZhangDepartment of Spine Surgery, The Central Hospital of Yongzhou, Yongzhoum, 425000, Hunan, China. b18674604575@163.com.

Funding

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6 · The paper itself

Abstract

Osteoarthritis (OA) is a leading cause of chronic pain and disability in the elderly. The lack of sensitive diagnostic methods for early OA remains a major clinical challenge. Synovial fluid contains exosomes (SF-exosomes) that carry disease-specific biomolecules, making them promising targets for early diagnosis. However, efficient isolation of SF-exosomes with high purity is technically demanding. This study aimed to develop phosphatidylserine-based molecularly imprinted polymers (P-MIPs) for the efficient enrichment of SF-exosomes and to discover potential protein biomarkers for early OA diagnosis using proteomic analysis. P-MIPs can specifically recognize phosphatidylserine on the extracellular vesicle membrane, thereby achieving highly selective enrichment of extracellular vesicles. P-MIPs were synthesized via a reverse microemulsion system. The binding capacity, specificity, and enrichment efficiency of P-MIPs were characterized. SF-exosomes from 6 OA patients and 6 healthy controls were enriched using P-MIPs and analyzed by LC-MS/MS proteomics. Differentially expressed proteins (DEPs) were subjected to bioinformatics analysis. The diagnostic value of hub genes was validated by ROC analysis in an independent cohort. The results showed that the binding capacity (Qmax) of P-MIPs was 129.71 µmol/g, and the cross-reactivity with sphingomyelin (SM), phenylphosphonic acid (PYP), and tyrosine phosphopeptides was less than 3.5%. The purity of enriched SF-exosomes was 82.6%. A total of 40 DEPs were identified, of which 28 were upregulated and 12 were downregulated in OA. PPI network analyses identified 10 hub genes: IL6, IL1B, MYC, CD4, MMP9, PTPRC, CXCL8, PPARG, ICAM1, and STAT3. ROC analysis showed that among the top five hub genes ranked by degree, MYC (AUC = 0.741) and IL6 (AUC = 0.735) exhibited good diagnostic performance. A combined biomarker panel comprising the top five hub genes achieved an even higher diagnostic accuracy, with an AUC of 0.899. The P-MIPs-based SF-exosome enrichment strategy is efficient and selective. MYC and IL6 are potential diagnostic biomarkers for early OA, and the identified DEPs provide insights into OA pathogenesis. Furthermore, this strategy can be extended for the recognition and enrichment of exosomes in other biological fluid matrices, facilitating the discovery of novel disease biomarkers and therapeutic targets.

Indexed as

ExosomesMolecular ImprintingOsteoarthritisPhospholipidsSynovial FluidBiomarkersEarly DiagnosisHumansProteomicsBiomarkersPhospholipidsExosomeLiquid chromatography-tandem mass spectrometry (LC–MS/MS)Molecularly imprinted polymersOsteoarthritisPhosphatidylserineProteomicsSynovial fluid

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.