Identification of target hub genes and construction of a novel miRNA regulatory network in autism spectrum disorder by integrated analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37478258", "kind": "science-record", "revision": 4, "content_hash": "sha256:052c49eabd42487d73ce6d0cbf3ad506ce942976cb2ba233ac48628a25fcbe5c", "created_at": "2026-11-01T19:02:14Z", "updated_at": "2026-11-01T22:52:21Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of target hub genes and construction of a novel miRNA regulatory network in autism spectrum disorder by integrated analysis.", "doi": "10.1097/MD.0000000000034420", "pmid": "37478258", "authors": ["Jinyi Zhu", "Haoran Meng", "Yan Li"], "journal": "Medicine", "year": 2023, "abstract": "The incidence of autism spectrum disorder (ASD) is increasing year by year in children. The aim of the study was to find possible biomarkers for ASD diagnosis as well as examine MicroRNA (miRNA) signatures and crucial pathways. We conducted a two-stage study to explore potential target genes and functional miRNAs. Peripheral blood samples of children with ASD were enrolled and performed RNA sequencing analysis. The overlapped candidate genes were further screened in combination with differentially expressed genes (DEGs) of GSE77103 datasets. STRING established a protein-protein interaction network comprising DEGs. The hub genes were filtered out using the CytoHubba. Then, we set up a miRNA-mRNA regulatory network. Correlational analyses between hub genes and immune cells associated with ASD were carried out using the CIBERSORT software to assess the diversity of immune cell types in ASD. RNA-sequencing analysis was used to confirm the differential expression of 3 hub genes. Briefly, after blood samples were sequenced interrogating 867 differential genes in our internal screening dataset. After screening GEO databases, 551 DEGs obtained from GSE77103. Fourteen common genes were overlapped through DEGs of GEO datasets and internal screening dataset. Among protein-protein interaction network, 10 hub genes with high degree algorithm were screened out and 3 hub genes of them - ADIPOR1, LGALS3, and GZMB - that were thought to be most associated with the emergence of ASD. Then, we developed a network of miRNA-mRNA regulatory interactions by screening miRNAs (such as hsa-miR-20b-5p, hsa-miR-17-5p, and hsa-miR-216b-5p) that were closely associated to 3 hub genes. Additionally, we discovered 18 different immune cell types associated with ASD using the CIBERSORT algorithm, and we discovered that mononuclear macrophages differed considerably between the 2 groups. Overall, 3 hub genes (ADIPOR1, LGALS3, and GZMB) and 15 candidates miRNAs-target 3 genes regulatory pathways representing potentially novel biomarkers of ASD diseases were revealed. These findings could enhance our knowledge of ASD and offer possible therapeutic targets of ASD patients in the future.", "claims": [{"id": "claim-method", "statement": "Finally, edgeR (Robinson et al, 2010) was used for gene differential expression analysis. The selection criteria were | log2 Fold change | ≥ 1 and FDR (corrected P value) < .05. We obtained 867 DEGs by using DESeq2 (Anders et al, 2014) (type: biological duplication) and edgeR (Robinson et al, 2010) (type: no biological duplication) from 3 sets of peripheral blood samples from children with autism and normal children. Using the “limma” package of R language software, 551 DEGs were screened from GSE77103 in accordance with the criteria of P values <.05, | logFC | > 1.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37478258", "locator": "sections[4] \"2.2. Library preparation and sequencing\" paragraph 2", "quote": "Finally, edgeR (Robinson et al, 2010) was used for gene differential expression analysis."}, {"asset": "source:pmid:37478258", "locator": "sections[4] \"2.2. Library preparation and sequencing\" paragraph 2", "quote": "The selection criteria were | log2 Fold change | ≥ 1 and FDR (corrected P value) < .05."}, {"asset": "source:pmid:37478258", "locator": "sections[4] \"2.2. Library preparation and sequencing\" paragraph 3", "quote": "We obtained 867 DEGs by using DESeq2 (Anders et al, 2014) (type: biological duplication) and edgeR (Robinson et al, 2010) (type: no biological duplication) from 3 sets of peripheral blood samples from children with autism and normal children."}, {"asset": "source:pmid:37478258", "locator": "sections[5] \"2.3. 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Identification of candidate genes\" paragraph 2", "quote": "In our sequencing dataset, a total of 867 differentially expressed mRNAs were explored and identified based on the hypothesis testing probability (P value), and multiple hypothesis testing was performed to obtain the FDR value."}, {"asset": "source:pmid:37478258", "locator": "sections[14] \"3.2. Identification of candidate genes\" paragraph 2", "quote": "Briefly, 551 DEGs were detected in ASD samples from 4 ASD and 4 control."}, {"asset": "source:pmid:37478258", "locator": "sections[14] \"3.2. Identification of candidate genes\" paragraph 2", "quote": "Finally, the intersection of 867 DEGs and 551 DEGs in GSE77103 was selected. We selected 19 genes in common, as shown in Figure 2D. Among them, 14 DEGs expressed the same trend"}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The study identified 867 differentially expressed genes by RNA sequencing, screened 551 DEGs from GSE77103, and found 14 common genes with the same expression trend across the two datasets.", "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:37478258"], "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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