PRRs-related genes and immune landscape in heart failure and COPD.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:41491714", "kind": "science-record", "revision": 4, "content_hash": "sha256:c59f438ec4d0016da65284d1fb370546767681fba305cf7c459aabd009d0f193", "created_at": "2026-11-01T20:31:28Z", "updated_at": "2026-11-01T22:57:42Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "PRRs-related genes and immune landscape in heart failure and COPD.", "doi": "10.1038/s41598-025-34671-3", "pmid": "41491714", "authors": ["Heqing Yang", "Tingting Mei"], "journal": "Scientific reports", "year": 2026, "abstract": "Heart failure (HF) and chronic obstructive pulmonary disease (COPD) are major health issues causing high hospitalization and mortality rates. Pattern recognition receptor-related differentially expressed genes (PRDEGs) play a crucial role in disease progression, as their altered expression patterns are closely linked to immune responses, inflammatory processes, and tissue remodeling. Understanding PRDEGs is vital for effective diagnostics and therapies. This study incorporated four GEO datasets (GSE57338, GSE16499, GSE76925, and GSE57148). Among them, GSE57338 and GSE76925 served as the primary analysis sets for HF and COPD, respectively, where differential expression, functional enrichment, and immune infiltration analyses were performed. GSE16499 and GSE57148 were used as independent validation sets to confirm the key findings. Seven PRDEGs, including PTX3, UCHL1, IL1R1, PLA2G2A, CXCL12, SPP1, and CD24, which exhibited significant expression differences in both HF and COPD. Enrichment analysis revealed that these genes were primarily associated primarily with biological processes such as the regulation of cellular extravasation and leukocyte migration, as well as the NF-kappa B signaling pathway. Immune infiltration analysis indicated significant differences in the abundances of various immune cells in HF and COPD samples. This study identified 7 PRDEGs as biomarkers, emphasizing the need to explore key genes and pathways in HF and COPD, along with 9 immune cell types and 2 signaling pathways, suggesting immune modulation's role in treatment.", "claims": [{"id": "claim-data-access", "statement": "Data availability the datasets used and/or analysed during the current study available from the corresponding author on reason able request. Data are available on reasonable request. All data relevant to the study are included in the article or uploaded as supplemental information. Gene expression data from the GEO repository (https://www.ncbi.nlm.nih.gov/geo/) include the following datasets: GSE57338, GSE16499, GSE76925 and GSE57148.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:41491714", "locator": "sections[26] \"Data availability\" paragraph 2", "quote": "Data availability the datasets used and/or analysed during the current study available from the corresponding author on reason able request. Data are available on reasonable request. All data relevant to the study are included in the article or uploaded as supplemental information. Gene expression data from the GEO repository (https://www.ncbi.nlm.nih.gov/geo/) include the following datasets: GSE57338, GSE16499, GSE76925 and GSE57148."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The study identified seven pattern recognition receptor-related differentially expressed genes as biomarkers for heart failure and chronic obstructive pulmonary disease.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:41491714", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "This study identified 7 PRDEGs as biomarkers, emphasizing the need to explore key genes and pathways in HF and COPD, along with 9 immune cell types and 2 signaling pathways, suggesting immune modulation’s role in treatment."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The study identified seven pattern recognition receptor-related differentially expressed genes as biomarkers for heart failure and chronic obstructive pulmonary disease.", "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:41491714"], "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:GSE16499"], "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:GSE16499"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:41491714", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1038/s41598-025-34671-3", "sha256": "sha256:0b2876087675674b6f9bb00f7f96603c0b4e6a3dad08ff0280795b00a20664eb", "bytes": 71660, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1038/s41598-025-34671-3", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC12868864", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE16499", "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=GSE16499", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE16499", "version": null, "note": "Data availability the datasets used and/or analysed during the current study available from the corresponding author on reason able request. Data are available on reasonable request. All data relevant to the study are included in the article or uploaded as supplemental information. Gene expression data from the GEO repository (https://www.ncbi.nlm.nih.gov/geo/) include the following datasets: GSE57338, GSE16499, GSE76925 and GSE57148.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Data availability the datasets used and/or analysed during the current study available from the corresponding author on reason able request. Data are available on reasonable request. All data relevant to the study are included in the article or uploaded as supplemental information. 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