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

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...

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Autores principales: Lu, Yiyu, Fang, Zhaoyuan, Zeng, Tao, Li, Meiyi, Chen, Qilong, Zhang, Hui, Zhou, Qianmei, Hu, Yiyang, Chen, Luonan, Su, Shibing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6873721/
https://www.ncbi.nlm.nih.gov/pubmed/31768187
http://dx.doi.org/10.1186/s13020-019-0275-4
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author Lu, Yiyu
Fang, Zhaoyuan
Zeng, Tao
Li, Meiyi
Chen, Qilong
Zhang, Hui
Zhou, Qianmei
Hu, Yiyang
Chen, Luonan
Su, Shibing
author_facet Lu, Yiyu
Fang, Zhaoyuan
Zeng, Tao
Li, Meiyi
Chen, Qilong
Zhang, Hui
Zhou, Qianmei
Hu, Yiyang
Chen, Luonan
Su, Shibing
author_sort Lu, Yiyu
collection PubMed
description 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)
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spelling pubmed-68737212019-11-25 Chronic hepatitis B: dynamic change in Traditional Chinese Medicine syndrome by dynamic network biomarkers Lu, Yiyu Fang, Zhaoyuan Zeng, Tao Li, Meiyi Chen, Qilong Zhang, Hui Zhou, Qianmei Hu, Yiyang Chen, Luonan Su, Shibing Chin Med Research 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) BioMed Central 2019-11-21 /pmc/articles/PMC6873721/ /pubmed/31768187 http://dx.doi.org/10.1186/s13020-019-0275-4 Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Lu, Yiyu
Fang, Zhaoyuan
Zeng, Tao
Li, Meiyi
Chen, Qilong
Zhang, Hui
Zhou, Qianmei
Hu, Yiyang
Chen, Luonan
Su, Shibing
Chronic hepatitis B: dynamic change in Traditional Chinese Medicine syndrome by dynamic network biomarkers
title Chronic hepatitis B: dynamic change in Traditional Chinese Medicine syndrome by dynamic network biomarkers
title_full Chronic hepatitis B: dynamic change in Traditional Chinese Medicine syndrome by dynamic network biomarkers
title_fullStr Chronic hepatitis B: dynamic change in Traditional Chinese Medicine syndrome by dynamic network biomarkers
title_full_unstemmed Chronic hepatitis B: dynamic change in Traditional Chinese Medicine syndrome by dynamic network biomarkers
title_short Chronic hepatitis B: dynamic change in Traditional Chinese Medicine syndrome by dynamic network biomarkers
title_sort chronic hepatitis b: dynamic change in traditional chinese medicine syndrome by dynamic network biomarkers
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6873721/
https://www.ncbi.nlm.nih.gov/pubmed/31768187
http://dx.doi.org/10.1186/s13020-019-0275-4
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