In-depth serum proteomics reveals biomarkers of psoriasis severity and response to traditional Chinese medicine
Xu, Meng; Deng, Jingwen; Xu, Kaikun; Zhu, Tiansheng; Han, Ling; Yan, Yuhong; Yao, Danni; Deng, Hao; Wang, Dan; Sun, Yaoting; Chang, Cheng; Zhang, Xiaomei; Dai, Jiayu; Yue, Liang; Zhang, Qiushi; Cai, Xue; Zhu, Yi; Duan, Hu; Liu, Yuan; Li, Dong; Zhu, Yunping; Radstake, Timothy R.D.J.; Balak, Deepak M.W.; Xu, Danke; Guo, Tiannan; Lu, Chuanjian; Yu, Xiaobo
(2019) Theranostics, volume 9, issue 9, pp. 2475 - 2488
(Article)
Abstract
Serum and plasma contain abundant biological information that reflect the body’s physiological and pathological conditions and are therefore a valuable sample type for disease biomarkers. However, comprehensive profiling of the serological proteome is challenging due to the wide range of protein concentrations in serum. Methods: To address this challenge, we
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developed a novel in-depth serum proteomics platform capable of analyzing the serum proteome across ~10 orders or magnitude by combining data obtained from Data Independent Acquisition Mass Spectrometry (DIA-MS) and customizable antibody microarrays. Results: Using psoriasis as a proof-of-concept disease model, we screened 50 serum proteomes from healthy controls and psoriasis patients before and after treatment with traditional Chinese medicine (YinXieLing) on our in-depth serum proteomics platform. We identified 106 differentially-expressed proteins in psoriasis patients involved in psoriasis-relevant biological processes, such as blood coagulation, inflammation, apoptosis and angiogenesis signaling pathways. In addition, unbiased clustering and principle component analysis revealed 58 proteins discriminating healthy volunteers from psoriasis patients and 12 proteins distinguishing responders from non-responders to YinXieLing. To further demonstrate the clinical utility of our platform, we performed correlation analyses between serum proteomes and psoriasis activity and found a positive association between the psoriasis area and severity index (PASI) score with three serum proteins (PI3, CCL22, IL-12B). Conclusion: Taken together, these results demonstrate the clinical utility of our in-depth serum proteomics platform to identify specific diagnostic and predictive biomarkers of psoriasis and other immune-mediated diseases.
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Keywords: Antibody microarray, Biomarker, Data-independent acquisition mass spectrometry, Proteomics, Psoriasis, Medicine (miscellaneous), Pharmacology, Toxicology and Pharmaceutics (miscellaneous)
ISSN: 1838-7640
Publisher: Ivyspring International Publisher
Note: Funding Information: This project was financially supported by the National Key Basic Research Project (2018ZX0 9733003, 2017YFC0906703 and 2018YFA0507503), the National Natural Science Foundation of China (81673040 and 31870823), the Program on the Joint Proteomics Center for Chinese Medicine between PHOENIX Center and Guangdong Provincial Academy of Chinese Medical Sciences, the State Key Laboratory of Proteomics (SKLP-O201504, SKLP-O201703 and SKLP-K201505) and Capital’s Funds for Health Improvement and Research (2018-2-4034) to X.Y. We also thank Dr. Brianne Petritis for her critical review and editing of this manuscript. Funding Information: This project was financially supported by the National Key Basic Research Project (2018ZX09733003, 2017YFC0906703 and 2018YFA0507503), the National Natural Science Foundation of China (81673040 and 31870823), the Program on the Joint Proteomics Center for Chinese Medicine between PHOENIX Center and Guangdong Provincial Academy of Chinese Medical Sciences, the State Key Laboratory of Proteomics (SKLP-O201504, SKLP-O201703 and SKLP-K201505) and Capital’s Funds for Health Improvement and Research (2018-2-4034) to X.Y. We also thank Dr. Brianne Petritis for her critical review and editing of this manuscript. Publisher Copyright: © Ivyspring International Publisher.
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