Innate immune response analysis in COVID-19 and kawasaki disease reveals MIS-C predictors.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34193364", "kind": "science-record", "revision": 7, "content_hash": "sha256:be735685ef3ece62225e05b44e91def65843cd06864446ace3f2f507393b6a50", "created_at": "2026-11-01T15:41:41Z", "updated_at": "2026-11-01T21:25:38Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Innate immune response analysis in COVID-19 and kawasaki disease reveals MIS-C predictors.", "doi": "10.1016/j.jfma.2021.06.009", "pmid": "34193364", "authors": ["Chin-An Yang", "Ya-Ling Huang", "Bor-Luen Chiang"], "journal": "Journal of the Formosan Medical Association = Taiwan yi zhi", "year": 2022, "abstract": "BACKGROUND/PURPOSE: The association between dysregulated innate immune responses seen in Kawasaki disease (KD) with predisposition to Kawasaki-like multisystem inflammatory syndrome in children (MIS-C) remains unclear. We aimed to compare the innate immunity transcriptome signature between COVID-19 and KD, and to analyze the interactions of these molecules with genes known to predispose to KD.\nMETHODS: Transcriptome datasets of COVID-19 and KD cohorts (E-MTAB-9357, GSE-63881, GSE-68004) were downloaded from ArrayExpress for innate immune response analyses. Network analysis was used to determine enriched pathways of interactions.\nRESULTS: Upregulations of IRAK4, IFI16, STING, STAT3, PYCARD, CASP1, IFNAR1 and CD14 genes were observed in blood cells of acute SARS-CoV-2 infections with moderate severity. In the same patient group, increased expressions of TLR2, TLR7, IRF3, and CD36 were also noted in blood drawn a few days after COVID-19 diagnosis. Elevated blood PYCARD level was associated with severe COVID-19 in adults. Similar gene expression signature except differences in TLR8, NLRP3, STING and IRF3 levels was detected in KD samples. Network analysis on innate immune genes and genes associated with KD susceptibility identified enriched pathways of interactions. Furthermore, higher expression levels of KD susceptibility genes HLA-DOB, PELI1 and FCGR2A correlated with COVID-19 of different severities.\nCONCLUSION: Our findings suggest that most enriched innate immune response pathways were shared between transcriptomes of KD and COVID-19 with moderate severity. Genetic polymorphisms associated with innate immune dysregulation and KD susceptibility, together with variants in STING and STAT3, might predict COVID-19 severity and potentially susceptibility to COVID-19 related MIS-C.", "claims": [{"id": "claim-method", "statement": "Unpaired t tests were performed to calculate the differences of gene expressions between two groups.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34193364", "locator": "sections[3] \"COVID-19 and KD transcriptome dataset analysis\" paragraph 2", "quote": "Unpaired t tests were performed to calculate the differences of gene expressions between two groups."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The transcriptome dataset of whole blood derived from COVID-19 cases (E-MTAB-9357) was downloaded from ArrayExpress Archive of Functional Genomic Data (ebi.ac.uk/arrayexpress/experiments/E-MTAB-9357),", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34193364", "locator": "sections[3] \"COVID-19 and KD transcriptome dataset analysis\" paragraph 2", "quote": "The transcriptome dataset of whole blood derived from COVID-19 cases (E-MTAB-9357) was downloaded from ArrayExpress Archive of Functional Genomic Data (ebi.ac.uk/arrayexpress/experiments/E-MTAB-9357),"}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "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:34193364"], "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:E-MTAB-9357"], "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:E-MTAB-9357"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:34193364", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1016/j.jfma.2021.06.009", "sha256": "sha256:0553bb054c42ddf49dcd89555c281ea9c1b5705517d1745b0ef6cd31e8261456", "bytes": 44272, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1016/j.jfma.2021.06.009", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC8214167", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:E-MTAB-9357", "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=E-MTAB-9357", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "E-MTAB-9357", "version": null, "note": "The transcriptome dataset of whole blood derived from COVID-19 cases (E-MTAB-9357) was downloaded from ArrayExpress Archive of Functional Genomic Data (ebi.ac.uk/arrayexpress/experiments/E-MTAB-9357),", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The transcriptome dataset of whole blood derived from COVID-19 cases (E-MTAB-9357) was downloaded from ArrayExpress Archive of Functional Genomic Data (ebi.ac.uk/arrayexpress/experiments/E-MTAB-9357),", "access_statement_kind": "repository_route_statement", "sample_accessions": [], "sample_count": null, "group_sizes": null, "group_sizes_basis": null, "platform": null, "taxon": null, "title": null, "resolution_checked_at": "2026-10-31T18:35:08Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:E-MTAB-9357 not downloaded", "asset:data:geo:E-MTAB-9357 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "genetic_association", "specific": "gwas", "label": "Genetic association (GWAS / linkage / MR)", "dsl_operations": ["gwas_locus_scan"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["genotype_phenotype_table"], "evidence": {"score": 0.8, "band": "high", "quote": "GWAS"}}, {"id": "method-2", "family": null, "specific": null, "label": "Unpaired t tests", "dsl_operations": [], "missing_operations": [], "expressible": null, "parameters": {}, "data_shapes": [], "evidence": {"score": 1.0, "band": "verbatim", "quote": "Unpaired t tests were performed to calculate the differences of gene expressions between two groups."}}], "targets": [], "gaps": ["method.reader_named_unmapped"]}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["gwas_locus_scan"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: gwas."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. 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