ArticleDrug design, development and therapy2021
Study on Hepatotoxicity of Rhubarb Based on Metabolomics and Network Pharmacology.
Article in Drug design, development and therapy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed, 37 citations in OpenAlex.
- Hepatotoxicity prediction for traditional Chinese medicine: a two-step in silico framework integrating network and machine learning approaches.BMC complementary medicine and therapies · 2026Article
- Analysis of risk factors for herb-induced liver injury: a retrospective study from China.Frontiers in pharmacology · 2026Article
- Mechanistic insights into the multi-target anti-atherosclerotic actions of rhubarb: a traditional remedy revisited.Chinese medicine · 2025Review
- Integrated analyses to explore the mechanism of Gancao Renshen Zhixue Decoction in treating liver cirrhosis.Scientific reports · 2025Article
- Rhubarb: Traditional Uses, Phytochemistry, Multiomics-Based Novel Pharmacological and Toxicological Mechanisms.Drug design, development and therapy · 2025Review
- Regulation of transient receptor potential ankyrin 1 by traditional Chinese medicine drugs and their active ingredients.Frontiers in pharmacology · 2025Review
- Exploration of compatibility rules and discovery of active ingredients in TCM formulas by network pharmacology.Chinese herbal medicines · 2024Review
- Study on the mechanism of hepatotoxicity of Aucklandiae radix through liver metabolomics and network pharmacology.Toxicology research · 2024Article
- A novel bioinformatics strategy to uncover the active ingredients and molecular mechanisms of Bai Shao in the treatment of non-alcoholic fatty liver disease.Frontiers in pharmacology · 2024Article
- Mechanism of the Effect of CompoundDrug design, development and therapy · 2023Article
- Integrated Metabolomics and Network Pharmacology to Reveal the Mechanisms of Gandouling Tablets Against Copper-Overload-Induced Neuronal Injury in Rats with Wilson's Disease.Drug design, development and therapy · 2023Article
- Ameliorative effect of Aconite aqueous extract on diarrhea is associated with modulation of the gut microbiota and bile acid metabolism.Frontiers in pharmacology · 2023Article
- Integrating systematic pharmacology-based strategy and experimental validation to explore mechanism ofChinese herbal medicines · 2022Article
- Effects of Anthraquinones on Immune Responses and Inflammatory Diseases.Molecules (Basel, Switzerland) · 2022Review
- The effect and mechanism of cypermethrin-induced hippocampal neurotoxicity as determined by network pharmacology analysis and experimental validation.Bioengineered · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRhubarb, as a traditional Chinese medicine, is the preferred drug for the treatment of stagnation and constipation in clinical practice. It has been reported that rhubarb possesses hepatotoxicity, but its mechanism in vivo is still unclear.
methodsIn this study, the chemical components in rhubarb were identified based on UPLC-Q-TOF/MS combined with data postprocessing technology. The metabolic biomarkers obtained through metabolomics technology were related to rhubarb-induced hepatotoxicity. Furthermore, the potential targets of rhubarb-induced hepatotoxicity were obtained by network pharmacology involving the above components and metabolites. Meanwhile, GO gene enrichment analysis and KEGG pathway analysis were performed on the common targets.
resultsTwenty-eight components in rhubarb were identified based on UPLC-Q-TOF/MS, and 242 targets related to rhubarb ingredients were predicted. Nine metabolic biomarkers obtained through metabolomics technology were closely related to rhubarb-induced hepatotoxicity, and 282 targets of metabolites were predicted. Among them, the levels of 4 metabolites, namely dynorphin B (10-13), cervonoyl ethanolamide, lysoPE (18:2), and 3-hydroxyphenyl 2-hydroxybenzoate, significantly increased, while the levels of 5 metabolites, namely dopamine, biopterin, choline, coenzyme Q9 and P1, P4-bis (5'-uridyl) tetraphosphate significantly decreased. In addition, 166 potential targets of rhubarb-induced hepatotoxicity were obtained by network pharmacology. The KEGG pathway analysis was performed on the common targets to obtain 46 associated signaling pathways.
conclusionThese data suggested that rhubarb may cause liver toxicity due to its action on dopamine D1 receptor (DRD1), dopamine D2 receptor (DRD2), phosphodiesterase 4B (PDE4B), vanilloid receptor (TRPV1); transient receptor potential cation channel subfamily M member 8 (TRPM8), prostanoid EP2 receptor (PTGER2), acetylcholinesterase (ACHE), muscarinic acetylcholine receptor M3 (CHRM3) through the cAMP signaling pathway, cholinergic synapses, and inflammatory mediators to regulate TRP channels. Metabolomics technology and network pharmacology were integrated to explore rhubarb hepatotoxicity to promote the reasonable clinical application of rhubarb.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.