Dataset Information

Imbalanced network biomarkers for traditional Chinese medicine Syndrome in gastritis patients.

ABSTRACT: Cold Syndrome and Hot Syndrome are thousand-year-old key therapeutic concepts in traditional Chinese medicine (TCM), which depict the loss of body homeostasis. However, the scientific basis of TCM Syndrome remains unclear due to limitations of current reductionist approaches. Here, we established a network balance model to evaluate the imbalanced network underlying TCM Syndrome and find potential biomarkers. By implementing this approach and investigating a group of chronic superficial gastritis (CSG) and chronic atrophic gastritis (CAG) patients, we found that with leptin as a biomarker, Cold Syndrome patients experience low levels of energy metabolism, while the CCL2/MCP1 biomarker indicated that immune regulation is intensified in Hot Syndrome patients. Such a metabolism-immune imbalanced network is consistent during the course from CSG to CAG. This work provides a new way to understand TCM Syndrome scientifically, which in turn benefits the personalized medicine in terms of the ancient medicine and complex biological systems.

SUBMITTER: Li R

PROVIDER: S-EPMC3607832 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Imbalanced network biomarkers for traditional Chinese medicine Syndrome in gastritis patients.

Li Rui R Ma Tao T Gu Jin J Liang Xujun X Li Shao S

Scientific reports 20130101

Cold Syndrome and Hot Syndrome are thousand-year-old key therapeutic concepts in traditional Chinese medicine (TCM), which depict the loss of body homeostasis. However, the scientific basis of TCM Syndrome remains unclear due to limitations of current reductionist approaches. Here, we established a network balance model to evaluate the imbalanced network underlying TCM Syndrome and find potential biomarkers. By implementing this approach and investigating a group of chronic superficial gastritis ...[more]

PMID: 23529020

Similar Datasets

Project description:BackgroundIn 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.MethodsTo 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.ResultsOur 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.ConclusionsThis 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).

Project description:Objective It is not clear which Traditional Chinese Medicine- (TCM-) related elements affect primary IgA nephropathy (IgAN) progression. Here, we explored the risk factors, based on TCM syndrome elements, related to the prognosis of primary IgAN patients. Methods We analyzed patients with newly diagnosed, biopsy-proven IgAN at a single institution from December 2013 to September 2021. Basic clinical and pathological characteristics were assessed at the time of renal biopsy. The study endpoint was end-stage renal disease (ESRD: eGFR <15 ml/min per 1.73 m2, dialysis, or kidney transplantation) and/or eGFR decreased by >30% from baseline. Kaplan‒Meier survival analysis was used to explore the role of TCM syndrome elements in IgAN progression. Multivariate Cox regression analysis with adjustment for traditional risk factors was performed to explore TCM syndrome elements that may influence patient prognosis. The factors correlated with TCM syndrome elements in IgAN patients were further evaluated by logistic regression analysis. Results During a median follow-up of 22.0 months, 53 (12.5%) of the 423 included IgAN patients reached the study endpoint. The main IgAN disease location elements were the kidney, liver, and spleen. The main IgAN disease nature elements were Yin-deficiency and Qi-deficiency, dampness, Yang-deficiency, phlegm, and Blood-deficiency. Kaplan‒Meier analysis identified three disease locations (liver, spleen, and kidney) and four disease natures (Qi-deficiency, Yang-deficiency, phlegm, and dampness) as elements associated with poor renal survival in IgAN patients. In multivariate Cox regression analysis, baseline Yang-deficiency was an independent risk predictor of poor prognosis in primary IgAN patients (hazard ratio 2.338; 95% confidence interval [CI]: 1.208–4.525; P=0.012) after adjustment for traditional risk factors. Furthermore, logistic regression analysis identified being female (odds ratio [OR] 2.518; 95% CI: 1.538–4.122; P < 0.001), older age (OR 1.043; 95% CI: 1.022–1.065; P < 0.001), low hemoglobin levels (OR 0.984; 95% CI: 0.971–0.996; P=0.013), and cellular/fibrocellular crescents (OR 1.706; 95% CI: 1.068–2.728; P=0.026) as factors affecting Yang-deficiency in IgAN patients. Conclusions Yang-deficiency independently predicts the risk of poor prognosis in primary IgAN patients. Being female, older age, low hemoglobin levels, and cellular/fibrocellular crescents were independently associated with Yang-deficiency in IgAN patients.

Dataset Information

Imbalanced network biomarkers for traditional Chinese medicine Syndrome in gastritis patients.

Publications

Imbalanced network biomarkers for traditional Chinese medicine Syndrome in gastritis patients.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets