Diversity and molecular network patterns of symptom phenotypes

Shu, Zixin; Wang, Jingjing; Sun, Haiyan; Xu, Ning; Lu, Chenxia; Zhang, Runshun; Li, Xiaodong; Liu, Baoyan; Zhou, Xuezhong

doi:10.1038/s41540-021-00206-5

Cited by 8 publications

(6 citation statements)

References 75 publications

(57 reference statements)

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“…We rely on a curated symptom-gene association dataset ( 28 ) (see Materials and Methods and data S1) to identify genes associated with each symptom, and then map these genes onto their corresponding proteins in the PPI (see Materials and Methods and data S2). We focus on 174 symptoms with at least 20 associated proteins.…”

Section: Resultsmentioning

confidence: 99%

Network medicine framework reveals generic herb-symptom effectiveness of traditional Chinese medicine

Gan,

Shu,

Wang

et al. 2023

Sci. Adv.

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Understanding natural and traditional medicine can lead to world-changing drug discoveries. Despite the therapeutic effectiveness of individual herbs, traditional Chinese medicine (TCM) lacks a scientific foundation and is often considered a myth. In this study, we establish a network medicine framework and reveal the general TCM treatment principle as the topological relationship between disease symptoms and TCM herb targets on the human protein interactome. We find that proteins associated with a symptom form a network module, and the network proximity of an herb’s targets to a symptom module is predictive of the herb’s effectiveness in treating the symptom. These findings are validated using patient data from a hospital. We highlight the translational value of our framework by predicting herb-symptom treatments with therapeutic potential. Our network medicine framework reveals the scientific foundation of TCM and establishes a paradigm for understanding the molecular basis of natural medicine and predicting disease treatments.

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Section: Resultsmentioning

confidence: 99%

Network medicine framework reveals generic herb-symptom effectiveness of traditional Chinese medicine

Gan,

Shu,

Wang

et al. 2023

Sci. Adv.

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“…In recent years, researchers have developed a series of systems or network pharmacological strategies to detect the molecular mechanisms of TCM (Schroen, et al, 2015). A study extracted symptom co-occurrences from clinical textbooks to construct phenotype network of symptoms with clinical co-occurrence and incorporated high-quality symptom-gene associations and protein–protein interactions to explore the molecular network patterns of symptom phenotypes ( Shu, et al, 2021 ). The work of Lu et al showed that the integrated network analysis method could be used for identifying robust symptom clusters (SCs) and investigate the molecular mechanisms of these SCs, which would be valuable for symptom science and precision health ( Lu, et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

Molecular mechanism of the treatment of lung adenocarcinoma by Hedyotis Diffusa: an integrative study with real-world clinical data and experimental validation

Wang,

Yin,

et al. 2024

Front. Pharmacol.

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BackgroundWith a variety of active ingredients, Hedyotis Diffusa (H. diffusa) can treat a variety of tumors. The purpose of our study is based on real-world data and experimental level, to double demonstrate the efficacy and possible molecular mechanism of H. diffusa in the treatment of lung adenocarcinom (LUAD).MethodsPhenotype-genotype and herbal-target associations were extracted from the SymMap database. Disease-gene associations were extracted from the MalaCards database. A molecular network-based correlation analysis was further conducted on the collection of genes associated with TCM and the collection of genes associated with diseases and symptoms. Then, the network separation SAB metrics were applied to evaluate the network proximity relationship between TCM and symptoms. Finally, cell apoptosis experiment, Western blot, and Real-time PCR were used for biological experimental level validation analysis.ResultsIncluded in the study were 85,437 electronic medical records (318 patients with LUAD). The proportion of prescriptions containing H. diffusa in the LUAD group was much higher than that in the non-LUAD group (p < 0.005). We counted the symptom relief of patients in the group and the group without the use of H. diffusa: except for symptoms such as fatigue, palpitations, and dizziness, the improvement rate of symptoms in the user group was higher than that in the non-use group. We selected the five most frequently occurring symptoms in the use group, namely, cough, expectoration, fatigue, chest tightness and wheezing. We combined the above five symptom genes into one group. The overlapping genes obtained were CTNNB1, STAT3, CASP8, and APC. The selection of CTNNB1 target for biological experiments showed that the proliferation rate of LUAD A549 cells in the drug intervention group was significantly lower than that in the control group, and it was concentration-dependent. H. diffusa can promote the apoptosis of A549 cells, and the apoptosis rate of the high-concentration drug group is significantly higher than that of the low-concentration drug group. The transcription and expression level of CTNNB1 gene in the drug intervention group were significantly decreased.ConclusionH. diffusa inhibits the proliferation and promotes apoptosis of LUAD A549 cells, which may be related to the fact that H. diffusa can regulate the expression of CTNNB1.

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“…Dong et al [13] constructed a mapping method for TCM prescription recommendations based on symptom term network. Shu et al [14] used network diversity to analyse protein-protein interactions in TCM symptom clusters to elucidate the potential molecular network mechanism of symptom phenotypes.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Real-World Application Laws for Zhengan Xifeng Decoction in the Treatment of Hypertension Based on Machine Learning

Huan

Cai

et al. 2023

Preprint

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Hypertension is a common cardiovascular disease. Zhengan Xifeng Decoction (ZGXFD), a classic prescription for adjuvant treatment of hypertension, but its clinical application characteristics and biological information have not been comprehensively analysed. This study is based on real-world data from 7571 electronic medical records of hypertension patients treated by ZGXFD. The Apriori algorithm was used to obtain the coupled herbs of ZGXFD. A convolutional neural network was designed to measure the dose characteristic information of herbs. The topological features of the protein‒protein interaction data were used to analyse the biological information of herbs. The K-nearest neighbour model integrates the above characteristics of herbs into the same framework to observe the composition adjustment laws and mechanism of ZGXFD from multiple dimensions. Eighty-seven coupled herbs with dose characteristics were obtained. The results revealed that ZXGFD regulates cytokines and reduces the inflammatory response and metabolic disorder to achieve the purpose of adjuvant therapy. Moreover, machine learning model is used to analyze real-world data that include clinical and molecular biological data with hierarchical characteristics, which provides a micro-biological explanation for the clinical application of herbs.

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Diversity and molecular network patterns of symptom phenotypes

Cited by 8 publications

References 75 publications

Network medicine framework reveals generic herb-symptom effectiveness of traditional Chinese medicine

Network medicine framework reveals generic herb-symptom effectiveness of traditional Chinese medicine

Molecular mechanism of the treatment of lung adenocarcinoma by Hedyotis Diffusa: an integrative study with real-world clinical data and experimental validation

Analysis of the Real-World Application Laws for Zhengan Xifeng Decoction in the Treatment of Hypertension Based on Machine Learning

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