ArticleFrontiers in immunology2022
Proteomic Profiling of Cryoglobulinemia.
Article in Frontiers in immunology, 2022. 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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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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0 citing papers in PubMed, 3 citations in OpenAlex.
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: We aimed to explore and identify candidate protein biomarkers of cryoglobulinemia (CGE) in disease control patients with negative cryoglobulin (DC) or healthy controls (HCs). Methods: The 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). Results: A 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). Conclusion: This 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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