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Updated: Jan 31, 2026

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
Published on: November 15, 2017
Plasma proteome profiling of high-altitude polycythemia using TMT-based quantitative proteomics approach
Zongkui Wang1, Fengjuan Liu1, Shengliang Ye1
1Institute of Blood Transfusion, Chinese Academy of Medical Sciences & Peking Union Medical College, Chengdu 610052, China.
Abstract:
High-altitude polycythemia (HAPC) is one of the classic chronic mountain sicknesses and has been a serious public health problem in high-altitude regions. Despite numerous studies on HAPC via genomics or transcriptomics approaches, the pathogenesis of HAPC is still unclear. Here, we performed a TMT- based comparative quantitative proteomics analysis to reveal the changes of plasma proteomics profiles between HAPC subjects and healthy controls. Of identified 818 proteins, 7 and 12 proteins were up-regulated and down-accumulated, respectively, compared HAPC patients with healthy controls. GO and KEGG pathway analyses revealed the dysregulated proteins were primarily involved in complement and coagulation cascades, inflammation and immune response. ELISA validation demonstrated that C4A, C6 and CALR were down-regulated, and MASP1 and CNDP1 were up-regulated in HAPC patients. By ROC analysis, combinations of these five proteins (i.e., C4A, C6, CALR, MASP1 and CNDP1) resulted in a high AUC value (0.919; 95% CI, 0.817-961; p < .0001) to diagnose HAPC patients. Moreover, CNDP1 seems to be a robust biomarker for HAPC. This study not only provided a comprehensive dataset on overall proteomics changes in HAPC patients compared with healthy controls, but also indicated that CNDP1 can serve as a strong plasma biomarker of HAPC for the diagnostic and therapeutic potential. SIGNIFICANCE: HAPC, one of the classic chronic mountain sicknesses, has been a serious public health problem in high-altitude regions. Despite numerous studies on HAPC via genomics or transcriptomics approaches, the pathogenesis of HAPC is still largely unknown to date. In this study, we addressed this issue by performing TMT-based quantitative analyses of the plasma proteome profiles of HAPC patients and healthy controls. We identified 818 proteins, of which 19 were differentially expressed. Bioinformatics analysis revealed the differentially expressed proteins were mainly involved in complement and coagulation cascades, inflammation and immune response. By ROC analysis, combinations of C4A, C6, CALR, MASP1 and CNDP1 resulted in a high AUC value (0.919, p < .0001) to distinguish HAPC patients from healthy controls. Collectively, the current study provided a comprehensive dataset on overall proteomic changes in HAPC patients for the first time, and it also revealed C4A, C6, CALR, MASP1 and CNDP1 can be served as candidate plasma biomarkers of HAPC for their diagnostic and therapeutic potential.
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