Identification of key genes and pathways revealing the central regulatory mechanism of brain-derived glucagon-like peptide-1 on obesity using bioinformatics analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35992905", "kind": "science-record", "revision": 5, "content_hash": "sha256:1fbd7d6bffff38a8f551108b7d4f4332b5c8210507233f04e13c6dd9267c2999", "created_at": "2026-11-01T18:15:09Z", "updated_at": "2026-11-01T22:49:51Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of key genes and pathways revealing the central regulatory mechanism of brain-derived glucagon-like peptide-1 on obesity using bioinformatics analysis.", "doi": "10.3389/fnins.2022.931161", "pmid": "35992905", "authors": ["Yuwei Shao", "Jun Tian", "Yanan Yang", "Yan Hu", "Ye Zhu", "Qing Shu"], "journal": "Frontiers in neuroscience", "year": 2022, "abstract": "Objective: Central glucagon-like peptide-1 (GLP-1) is a target in treating obesity due to its effect on suppressing appetite, but the possible downstream key genes that GLP-1 regulated have not been studied in depth. This study intends to screen out the downstream feeding regulation genes of central GLP-1 neurons through bioinformatics analysis and verify them by chemical genetics, which may provide insights for future research.\nMaterials and methods: GSE135862 genetic expression profiles were extracted from the Gene Expression Omnibus (GEO) database. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were carried out. STRING database and Cytoscape software were used to map the protein-protein interaction (PPI) network of the differentially expressed genes (DEGs). After bioinformatics analysis, we applied chemogenetic methods to modulate the activities of GLP-1 neurons in the nucleus tractus solitarius (NTS) and observed the alterations of screened differential genes and their protein expressions in the hypothalamus under different excitatory conditions of GLP-1 neurons.\nResults: A total of 49 DEGs were discovered, including 38 downregulated genes and 11 upregulated genes. The two genes with the highest expression scores were biglycan (Bgn) and mitogen-activated protein kinase activated protein kinase 3 (Mapkapk3). The results of GO analysis showed that there were 10 molecular functions of differential genes. Differential genes were mainly localized in seven regions around the cells, and enriched in 10 biology processes. The results of the KEGG signaling pathway enrichment analysis showed that differential genes played an important role in seven pathways. The top 15 genes selected according to the Cytoscape software included Bgn and Mapkapk3. Chemogenetic activation of GLP-1 in NTS induced a decrease in food intake and body mass, while chemogenetic inhibition induced the opposite effect. The gene and protein expression of GLP-1 were upregulated in NTS when activated by chemogenetics. In addition, the expression of Bgn was upregulated and that of Mapkapk3 was downregulated in the hypothalamus.\nConclusion: Our data showed that GLP-1 could modulate the protein expression of Bgn and Mapkapk3. Our findings elucidated the regulatory network in GLP-1 to obesity and might provide a novel diagnostic and therapeutic target for obesity.", "claims": [{"id": "claim-method", "statement": "The GSE135862 dataset was analyzed by the R language DESeq2 package to screen differentially expressed genes between different groups of the dataset and find out differentially expressed genes that may be involved in the regulation of appetite by GLP-1R.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35992905", "locator": "sections[4] \"Screening of differentially expressed genes\" paragraph 2", "quote": "The GSE135862 dataset was analyzed by the R language DESeq2 package to screen differentially expressed genes between different groups of the dataset and find out differentially expressed genes that may be involved in the regulation of appetite by GLP-1R."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35992905", "locator": "sections[23] \"Data availability statement\" paragraph 2", "quote": "The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A total of 49 DEGs were discovered, including 38 downregulated genes and 11 upregulated genes.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35992905", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "A total of 49 DEGs were discovered, including 38 downregulated genes and 11 upregulated genes."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A total of 49 DEGs were discovered, including 38 downregulated genes and 11 upregulated genes.", "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:35992905"], "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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