Bioinformatics analysis of genomic and immune infiltration patterns in autism spectrum disorder.

{"sci_version": "1.0", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36267781", "kind": "science-record", "revision": 3, "content_hash": "sha256:4f427e701bebd8fcbe1ce8ae7f0d42777b9d15dcd59cc5ddaf7292c02cedebab", "created_at": "2026-11-01T18:15:40Z", "updated_at": "2026-11-01T21:29:16Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Bioinformatics analysis of genomic and immune infiltration patterns in autism spectrum disorder.", "doi": "10.21037/atm-22-4108", "pmid": "36267781", "authors": ["Ru-Qiong Wei", "Wen-Liang Guo", "Yin-Teng Wu", "Raquel Alarcòn Rodrìguez", "Marìa Del Mar Requena Mullor", "Yu-Chang Gui", "Jian-Wen Xu"], "journal": "Annals of translational medicine", "year": 2022, "abstract": "Background: Autism spectrum disorder (ASD) is a specific type of pervasive developmental disorder, and most studies suggest that the onset of autism may be related to genetic and immune factors. The etiology of autism and the underlying molecular events need to be further addressed.\nMethods: The ASD-related dataset GSE18123 was downloaded from the Gene Expression Omnibus (GEO) database. Gene set enrichment analysis (GSEA) was used to screen for Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways that may be associated with autism. The top 5,000 genes with an absolute median difference were obtained, and a co-expression network was constructed using weighted correlation network analysis (WGCNA). In addition, GO and KEGG enrichment analyses were performed for genes in the modules most closely related to ASD. Hub genes were found in the significant modules, and the expression values and receiver operating characteristic (ROC) curves of the hub genes were analyzed and validated. Immune cell infiltration in ASD was calculated using the CIBERSORT algorithm, and the relationship between hub genes and immune cells was analyzed. Finally, GSEA was used to explore the potential pathways of hub genes affecting ASD.\nResults: The 5,000 DEGs were divided into eight significant modules by WGCNA. The green module was most significantly associated with ASD, and two hub genes [fatty acid-binding protein 2 (FABP2) and Janus kinase 2 (JAK2)] were found. Immune cell infiltration showed that resting dendritic cells and monocytes differed significantly in ASD and healthy individuals. FABP2 was significantly associated with memory B cells and CD8 T cells. JAK2 was significantly associated with monocytes, CD4 activated memory T cells, CD4 resting memory T cells, activated dendritic cells, gamma delta T cells, regulatory T cells (Tregs), CD8 T cells, and naïve CD4 T cells. FABP2 and JAK2 were found to affect multiple pathways of immunity.\nConclusions: FABP2 and JAK2 may influence the immune microenvironment of ASD by regulating immune cells and immune-related pathways and are candidate molecular markers for the development of ASD.", "claims": [{"id": "claim-method", "statement": "The co-expression network of DEGs was constructed based on the microarray dataset of the GPL570 platform using the “WGCNA” R package.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36267781", "locator": "sections[5] \"Screening of differentially expressed genes (DEGs) and the construction of co-expression networks\" paragraph 2", "quote": "The co-expression network of DEGs was constructed based on the microarray dataset of the GPL570 platform using the “WGCNA” R package."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The GSE18123 dataset contains 285 human peripheral blood cell samples, including 170 ASD patients and 115 healthy controls. The dataset includes the GPL570 and GPL6244 platforms.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36267781", "locator": "sections[3] \"Data collection and pre-processing\" paragraph 2", "quote": "The GSE18123 dataset contains 285 human peripheral blood cell samples, including 170 ASD patients and 115 healthy controls. The dataset includes the GPL570 and GPL6244 platforms."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The 5,000 DEGs were divided into eight significant modules by WGCNA.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36267781", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "The 5,000 DEGs were divided into eight significant modules by WGCNA."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The 5,000 DEGs were divided into eight significant modules by WGCNA.", "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:36267781"], "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. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE18123"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE18123"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36267781", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.21037/atm-22-4108", "sha256": "sha256:982f64f461ad77b308acfeee1e2050cd16acd1f23be9884aae13addf40342ab8", "bytes": 57564, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.21037/atm-22-4108", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9577768", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE18123", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE18123", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE18123", "version": null, "note": "The GSE18123 dataset contains 285 human peripheral blood cell samples, including 170 ASD patients and 115 healthy controls. 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