[Shared Therapeutic Targets of Obesity and Type 2 Diabetes Mellitus and the Intervention Mechanisms of Chinese Herbal Components].

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:41113402", "kind": "science-record", "revision": 3, "content_hash": "sha256:7aabcb6a8695cbf9c48244f649f303b5771d5a4637a4e6a992a7903c6b6a86b6", "created_at": "2026-11-01T20:31:09Z", "updated_at": "2026-11-01T22:14:51Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "[Shared Therapeutic Targets of Obesity and Type 2 Diabetes Mellitus and the Intervention Mechanisms of Chinese Herbal Components].", "doi": "10.12182/20250760104", "pmid": "41113402", "authors": ["Ruli Li", "Rongrong Wang", "Lianxin Li", "Chuchu Wang", "Tianlan Liao", "Boxun Zhang", "Rensong Yue"], "journal": "Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition", "year": 2025, "abstract": "Objective: To explore the shared potential targets and molecular mechanisms of obesity and type 2 diabetes mellitus (T2DM) using bioinformatics methods, to validate the expression of core targets through animal experiments, and to analyze the intervention potential of active components of traditional Chinese medicine (TCM).\nMethods: The obese population datasets (GSE151839 and GSE162653) were obtained from the Gene Expression Omnibus (GEO) database to screen for differentially expressed genes, which were then intersected with T2DM-related targets from the GeneCards database to identify shared targets. A protein-protein interaction (PPI) network was constructed using the STRING database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to identify enriched biological processes and signaling pathways. The expression of core targets in adipose tissue from patients with obesity and T2DM was validated using the GEO database. A total of 12 specific-pathogen-free (SPF) male Sprague-Dawley (SD) rats, aged 8 weeks and weighing between 180 and 200 g, were randomly assigned to a control group and a model group (n = 6 each). A T2DM rat model was established, and the mRNA and protein expression levels of core targets in adipose tissue were measured. Molecular docking and molecular dynamics simulations were performed to assess the binding ability of TCM active components to core targets.\nResults: A total of 460 and 796 obesity-related differentially expressed genes were identified in the GSE151839 and GSE162653 datasets, respectively, and 109 shared targets were obtained by intersection with T2DM-related targets. According to PPI network analysis, PTPRC, MMP9, ITGB2, CD86, CCR5, and CCR2 were identified as the core targets. GO and KEGG analysis showed that these targets are mainly enriched in biological processes such as inflammatory response, immune regulation, and cell adhesion. Animal experiments confirmed that the mRNA and protein expression of core targets, including PTPRC, ITGAX, MMP9, ITGB2, CCR2, and CXCL1, were significantly upregulated in the adipose tissue of T2DM rats (P < 0.05). Molecular docking and molecular dynamics simulations revealed that berberine and puerarin had good binding ability with PTPRC, MMP9, and ITGB2.\nConclusion: This study reveals the shared molecular mechanisms between obesity and T2DM and shows that core targets, such as PTPRC and MMP9, may promote disease progression by regulating the inflammation-immune network. These findings provide a theoretical basis for the development of targeted therapeutic strategies based on TCM active ingredients.", "claims": [{"id": "claim-method", "statement": "变量首先通过F检验评估方差齐性，正态分布数据以\\begin{document}$\\bar x\\pm s $\\end{document}表示，两组数据采用非配对t检验（two-tailed）进行组间比较，P<0.05为差异有统计学意义。", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:41113402", "locator": "sections[19] \"统计学方法\" paragraph 2", "quote": "变量首先通过F检验评估方差齐性，正态分布数据以\\begin{document}$\\bar x\\pm s $\\end{document}表示，两组数据采用非配对t检验（two-tailed）进行组间比较，P<0.05为差异有统计学意义。"}], "state": "complete"}, {"id": "claim-data-access", "statement": "从GSE151839数据集获得10名肥胖〔体质量指数（body mass index, BMI）35～50 kg/m2〕和10名健康正常体质量（BMI 18.5～26.9 kg/m2）女性（按年龄和种族配对）脂肪中的基因表达情况。", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:41113402", "locator": "sections[5] \"肥胖差异基因及T2DM疾病靶点的获取\" paragraph 2", "quote": "从GSE151839数据集获得10名肥胖〔体质量指数（body mass index, BMI）35～50 kg/m2〕和10名健康正常体质量（BMI 18.5～26.9 kg/m2）女性（按年龄和种族配对）脂肪中的基因表达情况。"}], "state": "complete"}, {"id": "claim-target-result", "statement": "本研究揭示了肥胖与T2DM的共同分子机制，发现PTPRC、MMP9等核心靶点可能通过调控炎症-免疫网络促进疾病进展，为开发基于中药活性成分的靶向治疗策略提供了理论依据。", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:41113402", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "本研究揭示了肥胖与T2DM的共同分子机制，发现PTPRC、MMP9等核心靶点可能通过调控炎症-免疫网络促进疾病进展，为开发基于中药活性成分的靶向治疗策略提供了理论依据。"}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "本研究揭示了肥胖与T2DM的共同分子机制，发现PTPRC、MMP9等核心靶点可能通过调控炎症-免疫网络促进疾病进展，为开发基于中药活性成分的靶向治疗策略提供了理论依据。", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:41113402"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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A T2DM rat model was established, and the mRNA and prot", "ly upregulated in the adipose tissue of T2DM rats (P < 0.05). Molecular docking and molecular"], "order_basis": "paper_text_order:1133", "id": "assay:1"}, {"role": "analysis", "definition_id": "network_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["build_graph", "centrality_scores", "pathway_enrich"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 0.7, "evidence": ["protein-protein interaction"], "order_basis": "consumes_earlier_output", "id": "assay:2"}]}