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Metabolic profiling of urinary exosomes for systemic lupus erythematosus discrimination based on HPL-SEC/MALDI-TOF MS.
Yan, Shaohan; Huang, Zhongzhou; Chen, Xiaofei; Chen, Haolin; Yang, Xue; Gao, Mingxia; Zhang, Xiangmin.
Afiliação
  • Yan S; Department of Chemistry and Institutes of Biomedical Sciences, Fudan University, Shanghai, 200438, China.
  • Huang Z; Department of Rheumatology, Huashan Hospital, Fudan University, Shanghai, China.
  • Chen X; Department of Chemistry and Institutes of Biomedical Sciences, Fudan University, Shanghai, 200438, China.
  • Chen H; Department of Chemistry and Institutes of Biomedical Sciences, Fudan University, Shanghai, 200438, China.
  • Yang X; Department of Rheumatology, Huashan Hospital, Fudan University, Shanghai, China. yangxue21@yeah.net.
  • Gao M; Department of Chemistry and Institutes of Biomedical Sciences, Fudan University, Shanghai, 200438, China. mxgao@fudan.edu.cn.
  • Zhang X; Department of Chemistry and Institutes of Biomedical Sciences, Fudan University, Shanghai, 200438, China.
Anal Bioanal Chem ; 415(26): 6411-6420, 2023 Nov.
Article em En | MEDLINE | ID: mdl-37644324
ABSTRACT
Systemic lupus erythematosus (SLE) is a chronic autoimmune disease which leads to the formation of immune complex deposits in multiple organs and has heterogeneous clinical manifestations. Currently, exosomes for liquid biopsy have been applied in diagnosis and monitoring of diseases, whereas SLE discrimination based on exosomes at the metabolic level is rarely reported. Herein, we constructed a protocol for metabolomic study of urinary exosomes from SLE patients and healthy controls (HCs) with high efficiency and throughput. Exosomes were first obtained by high-performance liquid size-exclusion chromatography (HPL-SEC), and then metabolic fingerprints of urinary exosomes were extracted by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) with high throughput and high efficency. With the statistical analysis by orthogonal partial least-squares discriminant analysis (OPLS-DA) model, SLE patients were efficiently distinguished from HCs, the area under the curve (AUC) of the receiver characteristic curve (ROC) was 1.00, and the accuracy of the unsupervised clustering heatmap was 90.32%. In addition, potential biomarkers and related metabolic pathways were analyzed. This method, with the characteristics of high throughput, high efficiency, and high accuracy, will provide the broad prospect of exosome-driven precision medicine and large-scale screening in clinical applications.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Guideline / Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Guideline / Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article