4.8 Article

Proteomic Profiling of Cryoglobulinemia

期刊

FRONTIERS IN IMMUNOLOGY
卷 13, 期 -, 页码 -

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FRONTIERS MEDIA SA
DOI: 10.3389/fimmu.2022.855513

关键词

proteomics; serum; biomarker; cyroglobulinemia; metabolic pathway

资金

  1. CAMS Innovation Fund for Medical Sciences [CIFMS 2021-I2M-1-003]
  2. Basic Research Funds of Central Public Research Institutes, Chinese Academy of Medical Sciences [2020-RW330-004]

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This study aimed to identify and validate candidate protein biomarkers for cryoglobulinemia (CGE) using a TMT-PRM-ELISA workflow. APOA1 and PCSK9 were confirmed to be increased in CGE patients, indicating the involvement of proteins in cholesterol metabolism in the development of CGE. These findings provide valuable insights for pathogenesis research and biomarker discovery in CGE.
ObjectiveWe aimed to explore and identify candidate protein biomarkers of cryoglobulinemia (CGE) in disease control patients with negative cryoglobulin (DC) or healthy controls (HCs). MethodsThe tandem mass tag (TMT)-labeled serum quantitative proteomics approach was used to identify differentially expressed proteins between the CGE and DC groups. Ingenuity pathway analysis was used for functional annotation of differentially expressed proteins. Biomarker candidates were validated in another cohort using the parallel reaction monitoring (PRM) method. Apolipoprotein A1 (APOA1), apolipoprotein CIII (APOC3), adiponectin, and proprotein convertase subtilisin/kexin type-9 (PCSK9), which represent key proteins involved in the cholesterol metabolism pathway, were further verified in an increased number of samples by enzyme-linked immunosorbent assay (ELISA). ResultsA total of 1004 proteins were identified, of which 109 proteins were differentially expressed between the CGE and DC groups. These differentially expressed proteins were primarily involved in hepatic fibrosis/hepatic stellate cell activation and immune/inflammation-related pathways. In the disease and biofunction analysis, these proteins were mainly associated with the adhesion of blood cells, leukocyte migration, cholesterol transport, and transport of lipids. Twelve candidate biomarkers were validated by PRM-based proteomics, and proteins involved in the cholesterol metabolism pathway were further verified. APOA1, APOC3, adiponectin and PCSK9 concentrations were increased in CGE patients compared with healthy controls (P=0.0123, 0.1136, 0.5760, and 0.0019, respectively). ConclusionThis report describes the first application of a TMT-PRM-ELISA workflow to identify and validate CGE-specific biomarkers in serum. APOA1 and PCSK9 have been confirmed to be increased in CGE patients, demonstrating that proteins involved in cholesterol metabolism are also implicated in the development of CGE. These findings contribute to pathogenesis research and biomarker discovery in CGE.

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