Literature DB >> 25072359

Screening and identification of potential biomarkers and establishment of the diagnostic serum proteomic model for the Traditional Chinese Medicine Syndromes of tuberculosis.

Jiyan Liu1, Yanyuan Li2, Liliang Wei3, Xiuyun Yang4, Zhensheng Xie5, Tingting Jiang6, Chong Wang7, Xing Zhang8, Dandan Xu9, Zhongliang Chen10, Fuquan Yang11, Ji-Cheng Li12.   

Abstract

ETHNOPHARMACOLOGICAL RELEVANCE: Chemotherapy is the mainstay of modern tuberculosis (TB) control. Traditional Chinese Medicine (TCM) can enhance the effect of anti-TB drug, promote the absorption of the foci in the lung and reduce drug toxicity. In TCM, the determination of treatment is based on ZHENG (also called TCM syndrome). To establish a diagnostic model by using proteomics technology in order to identify potential biomarkers for TCM syndromes of TB.
MATERIALS AND METHODS: The surface-enhanced laser desorption ionization time of flight mass spectrometer (SELDI-TOF MS) combined with weak cation exchange (WCX) magnetic beads was used to screen serum samples from 71 cases of deficiency of lung yin syndrome (DLYS), 64 cases of fire (yang) excess yin deficiency syndrome (FEYDS) and 45 cases of deficiency of both qi and yin syndrome (DQYS). A classification model was established by Biomarker Pattern Software (BPS). Candidate protein biomarkers were purified by reverse phase-high performance liquid chromatograph (RP-HPLC), identified by MALDI-TOF MS, LC-MS/MS and validated by ProteinChip Immunoassays.
RESULTS: A total of 74 discriminating m/z peaks (P<0.001) among three TCM syndromes of TB were detected. A diagnostic model for the TCM syndrome of TB based on the five biomarkers (3961.7, 4679.7, 5646.4, 8891.2 and 9416.7 m/z) was established which could discriminate DLYS, FEYDS and DQYS patients with an accuracy of 74.0%, 72.5%, and 96.7%, respectively. The candidate biomarker with m/z of 9416.7 was identified as a fragment of apolipoprotein C-III (apoC-III) by MALDI-TOF-MS and LC-MS/MS.
CONCLUSION: The TCM syndrome diagnostic model of TB could successfully distinguish the three TCM syndromes of TB patients. This provided a biological basis for the determination of treatment based on different TCM syndromes of TB. ApoC-III was identified as a potential biomarker for TCM syndromes of TB and revealed the biochemical basis and pathogenesis of TCM syndromes in TB.
Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Apolipoprotein C-III; Proteomics; TCM syndrome; Traditional Chinese Medicine; Tuberculosis

Mesh:

Substances:

Year:  2014        PMID: 25072359     DOI: 10.1016/j.jep.2014.07.025

Source DB:  PubMed          Journal:  J Ethnopharmacol        ISSN: 0378-8741            Impact factor:   4.360


  11 in total

1.  Comparative proteomic analysis of serum diagnosis patterns of sputum smear-positive pulmonary tuberculosis based on magnetic bead separation and mass spectrometry analysis.

Authors:  Jiyan Liu; Tingting Jiang; Feng Jiang; Dandan Xu; Liliang Wei; Chong Wang; Zhongliang Chen; Xing Zhang; Jicheng Li
Journal:  Int J Clin Exp Med       Date:  2015-02-15

2.  Serum protein gamma-glutamyl hydrolase, Ig gamma-3 chain C region, and haptoglobin are associated with the syndromes of pulmonary tuberculosis in traditional Chinese medicine.

Authors:  Ting-Ting Jiang; Chong Wang; Li-Liang Wei; Xiao-Mei Yu; Li-Ying Shi; Dan-Dan Xu; Zhong-Liang Chen; Ze-Peng Ping; Ji-Cheng Li
Journal:  BMC Complement Altern Med       Date:  2015-07-22       Impact factor: 3.659

3.  Identification of potential serum proteomic biomarkers for clear cell renal cell carcinoma.

Authors:  Juan Yang; Jin Yang; Yan Gao; Lingyu Zhao; Liying Liu; Yannan Qin; Xiaofei Wang; Tusheng Song; Chen Huang
Journal:  PLoS One       Date:  2014-11-04       Impact factor: 3.240

4.  Microarray expression profile analysis of mRNAs and long non-coding RNAs in pulmonary tuberculosis with different traditional Chinese medicine syndromes.

Authors:  Ting-Ting Jiang; Li-Liang Wei; Li-Ying Shi; Zhong-Liang Chen; Chong Wang; Chang-Ming Liu; Zhong-Jie Li; Ji-Cheng Li
Journal:  BMC Complement Altern Med       Date:  2016-11-17       Impact factor: 3.659

5.  Comparative Proteomic Profiling and Biomarker Identification of Traditional Chinese Medicine-Based HIV/AIDS Syndromes.

Authors:  Li Wen; Ye-Fang Liu; Cen Jiang; Shao-Qian Zeng; Yue Su; Wen-Jun Wu; Xi-Yang Liu; Jian Wang; Ying Liu; Chen Su; Bai-Xue Li; Quan-Sheng Feng
Journal:  Sci Rep       Date:  2018-03-08       Impact factor: 4.379

6.  Label-Free Quantitative Proteomics Identifies Novel Plasma Biomarkers for Distinguishing Pulmonary Tuberculosis and Latent Infection.

Authors:  Huishan Sun; Liping Pan; Hongyan Jia; Zhiguo Zhang; Mengqiu Gao; Mailing Huang; Jinghui Wang; Qi Sun; Rongrong Wei; Boping Du; Aiying Xing; Zongde Zhang
Journal:  Front Microbiol       Date:  2018-06-13       Impact factor: 5.640

7.  The Common Prescription Patterns Based on the Hierarchical Clustering of Herb-Pairs Efficacies.

Authors:  Jia Cao
Journal:  Evid Based Complement Alternat Med       Date:  2016-04-10       Impact factor: 2.629

8.  A Group of Novel Serum Diagnostic Biomarkers for Multidrug-Resistant Tuberculosis by iTRAQ-2D LC-MS/MS and Solexa Sequencing.

Authors:  Chong Wang; Chang-Ming Liu; Li-Liang Wei; Li-Ying Shi; Zhi-Fen Pan; Lian-Gen Mao; Xiao-Chen Wan; Ze-Peng Ping; Ting-Ting Jiang; Zhong-Liang Chen; Zhong-Jie Li; Ji-Cheng Li
Journal:  Int J Biol Sci       Date:  2016-01-01       Impact factor: 6.580

9.  Screening and identification of five serum proteins as novel potential biomarkers for cured pulmonary tuberculosis.

Authors:  Chong Wang; Li-Liang Wei; Li-Ying Shi; Zhi-Fen Pan; Xiao-Mei Yu; Tian-Yu Li; Chang-Ming Liu; Ze-Peng Ping; Ting-Ting Jiang; Zhong-Liang Chen; Lian-Gen Mao; Zhong-Jie Li; Ji-Cheng Li
Journal:  Sci Rep       Date:  2015-10-26       Impact factor: 4.379

Review 10.  Recent Advance in Applications of Proteomics Technologies on Traditional Chinese Medicine Research.

Authors:  Qing Ji; Fangshi Zhu; Xuan Liu; Qi Li; Shi-Bing Su
Journal:  Evid Based Complement Alternat Med       Date:  2015-10-19       Impact factor: 2.629

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.