Investigation of Urinary Exosome Metabolic Patterns in Membranous Nephropathy by Titania‐Assisted Intact Exosome Mass Spectrometry
Exosomes are regarded as the emerging potential targets for liquid biopsy and bioprocess study owing to their abundant inclusive cargos that carry significant disease information. In addition, metabolites have been promising biomarkers for diagnosis. However, little metabolic research on exosomes is carried out by now. Herein, the mix‐crystal titania‐assisted laser desorption/ionization mass spectrometry (LDI‐MS) method is established, which features fast speed, high throughput, and efficiency, to directly extract urinary exosome metabolic patterns of healthy controls (HC) and membrane nephropathy (MN) patients. Besides, this method is also adopted to acquire the primitive urinary metabolic patterns from the same samples for comparison. By taking advantage of principal component analysis, unpaired parametric t‐test, and orthogonal partial least squares discriminant analysis on the exosome metabolic patterns, 27 significant m/z signals are filtrated, which possess more prominent differentiation capacity toward HC and MN patients (AUC = 0.942), and hold greater potential in MN diagnosis, compared to primitive urine (AUC = 0.801). The work reveals the important clinical value of exosome metabolic analysis, and paves a way to exosome‐based diagnosis at metabolomic level toward large‐scale clinical use.
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Erschienen in
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Investigation of Urinary Exosome Metabolic Patterns in Membranous Nephropathy by Titania‐Assisted Intact Exosome Mass Spectrometry ; day:09 ; month:02 ; year:2022 ; extent:8
Small science ; (09.02.2022) (gesamt 8)
- Urheber
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Chen, Haolin
Zhang, Ning
Wu, Yonglei
Yang, Chenjie
Xie, Qionghong
Deng, Chunhui
Sun, Nianrong
- DOI
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10.1002/smsc.202100118
- URN
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urn:nbn:de:101:1-2022021014000808592827
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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15.08.2025, 07:27 MESZ
Datenpartner
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Chen, Haolin
- Zhang, Ning
- Wu, Yonglei
- Yang, Chenjie
- Xie, Qionghong
- Deng, Chunhui
- Sun, Nianrong
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