Effect of acute exercise on gene expression in peripheral blood mononuclear cells of puberty children.

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In this study, we identified differential gene expression associated with acute exercise and PBMC in puberty children through the GEO database. We utilized bioinformatics technology to analyze the impact of acute exercise on PBMC and identified key genes involving the puberty children. Combining two datasets of gene expression, we identified 197 shared differentially expressed genes (DEGs) in PBMC before and after exercise. We conducted pathway analysis of these DEGs and built a gene co-expression network. The identification of hub genes was achieved through the utilization of protein-protein interaction (PPI) networks. 268 shared DEGs were identified in the GSE11761 dataset in pre- and post-exercise groups, while 352 differential genes were identified between the pre- and post-exercise groups of females in the GSE14642 dataset. A total of 197 shared genes were identified between the two datasets. Seven core genes were identified by MCODE and CytoHubba, namely IL2RB, KLRD1, GZMB, TBX21, PRF1, HAVCR2, and GZMA. Bioinformatics techniques are effective in screening and analyzing PBMC-associated DEGs in children undergoing acute pre- and post-exercise puberty. Microarray analysis of PBMCs in children undergoing puberty can identify molecules that may predict acute exercise responses. This study provides insights for further exploration of the mechanisms and targets of acute exercise on the organism.", "claims": [{"id": "claim-method", "statement": "GEO2R (https://www.ncbi.nlm.nih.gov/geo/geo2r/), an online analysis tool, can be used to filter DEGs between the pre-exercise and post-exercise groups.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39543149", "locator": "sections[4] \"Data processing\" paragraph 2", "quote": "GEO2R (https://www.ncbi.nlm.nih.gov/geo/geo2r/), an online analysis tool, can be used to filter DEGs between the pre-exercise and post-exercise groups."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. 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All the data were acquired from the Gene Expression Omnibus (GEO) database.GSE11761_series_matrix.File(s): The GSE11761 series based on the GPL570 [HG-U133_Plus_2] Affymetrix Human Genome U133 Plus 2.0 Array.(https://www.ncbi.nlm.nih.gov/geo/).GSE14642_series_matrix.File(s): The GSE14642 series based on the GPL570 [HG-U133_Plus_2] Affymetrix Human Genome U133 Plus 2.0 Array.(https://www.ncbi.nlm.nih.gov/geo/)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Seven core genes were identified by MCODE and CytoHubba, namely IL2RB, KLRD1, GZMB, TBX21, PRF1, HAVCR2, and GZMA.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39543149", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Seven core genes were identified by MCODE and CytoHubba, namely IL2RB, KLRD1, GZMB, TBX21, PRF1, HAVCR2, and GZMA."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Seven core genes were identified by MCODE and CytoHubba, namely IL2RB, KLRD1, GZMB, TBX21, PRF1, HAVCR2, and GZMA.", "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:39543149"], "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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