Chronic hepatitis B: dynamic change in Traditional Chinese Medicine syndrome by dynamic network biomarkers

Yiyu Lu; Zhaoyuan Fang; Tao Zeng; Meiyi Li; Qilong Chen; Hui Zhang; Qianmei Zhou; Yiyang Hu; Luonan Chen; Shibing Su

doi:10.1186/s13020-019-0275-4

Chronic hepatitis B: dynamic change in Traditional Chinese Medicine syndrome by dynamic network biomarkers

Chin Med. 2019 Nov 21:14:52. doi: 10.1186/s13020-019-0275-4. eCollection 2019.

Authors

Yiyu Lu¹, Zhaoyuan Fang², Tao Zeng², Meiyi Li³, Qilong Chen¹, Hui Zhang¹, Qianmei Zhou¹, Yiyang Hu⁴, Luonan Chen^{2

5}, Shibing Su¹

Affiliations

¹ 1Institute of Interdisciplinary Integrative Medicine Research, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203 China.
² 2Key Laboratory of Systems Biology, CAS Center for Excellence in Molecular Cell Science, Institute of Biochemistry and Cell Biology, Shanghai Institute of Biological Sciences, Chinese Academy of Sciences, Shanghai, 200031 China.
³ 5Minhang Branch, Zhongshan Hospital, Fudan University/Institute of Fudan-Minhang Academic Health System, Minhang Hospital, Fudan University, Shanghai, 201199 China.
⁴ 4Institute of Liver Disease, Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203 China.
⁵ 3CAS Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223 China.

Abstract

Background: In traditional Chinese medicine (TCM) clinical practice, TCM syndromes help to understand human homeostasis and guide individualized treatment. However, the TCM syndrome changes with disease progression, of which the scientific basis and mechanism remain unclear.

Methods: To demonstrate the underlying mechanism of dynamic changes in the TCM syndrome, we applied a dynamic network biomarker (DNB) algorithm to obtain the DNBs of changes in the TCM syndrome, based on the transcriptomic data of patients with chronic hepatitis B and typical TCM syndromes, including healthy controls and patients with liver-gallbladder dampness-heat syndrome (LGDHS), liver-depression spleen-deficiency syndrome (LDSDS), and liver-kidney yin-deficiency syndrome (LKYDS). The DNB model exploits collective fluctuations and correlations of the observed genes, then diagnoses the critical state.

Results: Our results showed that the DNBs of TCM syndromes were comprised of 52 genes and the tipping point occurred at the LDSDS stage. Meanwhile, there were numerous differentially expressed genes between LGDHS and LKYDS, which highlighted the drastic changes before and after the tipping point, implying the 52 DNBs could serve as early-warning signals of the upcoming change in the TCM syndrome. Next, we validated DNBs by cytokine profiling and isobaric tags for relative and absolute quantitation (iTRAQ). The results showed that PLG (plasminogen) and coagulation factor XII (F12) were significantly expressed during the progression of TCM syndrome from LGDHS to LKYDS.

Conclusions: This study provides a scientific understanding of changes in the TCM syndrome. During this process, the cytokine system was involved all the time. The DNBs PLG and F12 were confirmed to significantly change during TCM-syndrome progression and indicated a potential value of DNBs in auxiliary diagnosis of TCM syndrome in CHB.Trial registration Identifier: NCT03189992. Registered on June 4, 2017. Retrospectively registered (http://www.clinicaltrials.gov).

Keywords: Chronic hepatitis B; Disease progression; Dynamic network biomarkers; Systems biology; Traditional Chinese Medicine syndrome.

Associated data

ClinicalTrials.gov/NCT03189992