Identification of Macrophage Polarization-Related Genes as Biomarkers of Chronic Obstructive Pulmonary Disease Based on Bioinformatics Analyses.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34250093", "kind": "science-record", "revision": 5, "content_hash": "sha256:6fae8fa253aed46feacf95c504f7fe78a93ce851bf4e6adcbdec6043f44dd997", "created_at": "2026-11-01T15:41:42Z", "updated_at": "2026-11-01T22:04:11Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of Macrophage Polarization-Related Genes as Biomarkers of Chronic Obstructive Pulmonary Disease Based on Bioinformatics Analyses.", "doi": "10.1155/2021/9921012", "pmid": "34250093", "authors": ["Yalin Zhao", "Meihua Li", "Yanxia Yang", "Tao Wu", "Qingyuan Huang", "Qinghua Wu", "Chaofeng Ren"], "journal": "BioMed research international", "year": 2021, "abstract": "OBJECTIVES: Chronic obstructive pulmonary disease (COPD) is characterized by lung inflammation and remodeling. Macrophage polarization is associated with inflammation and tissue remodeling, as well as immunity. Therefore, this study attempts to investigate the diagnostic value and regulatory mechanism of macrophage polarization-related genes for COPD by bioinformatics analysis and to provide a new theoretical basis for experimental research.\nMETHODS: The raw gene expression profile dataset (GSE124180) was collected from the Gene Expression Omnibus (GEO) database. Next, a weighted gene coexpression network analysis (WGCNA) was conducted to screen macrophage polarization-related genes. The differentially expressed genes (DEGs) between the COPD and normal samples were generated using DESeq2 v3.11 and overlapped with the macrophage polarization-related genes. Moreover, functional annotations of overlapped genes were conducted by Database for Annotation, Visualization and Integrated Discovery (DAVID) Bioinformatics Resource. The immune-related genes were selected, and their correlation with the differential immune cells was analyzed by Pearson. Finally, receiver operating characteristic (ROC) curves were used to verify the diagnostic value of genes.\nRESULTS: A total of 4922 coexpressed genes related to macrophage polarization were overlapped with the 203 DEGs between the COPD and normal samples, obtaining 25 genes related to COPD and macrophage polarization. GEM, S100B, and GZMA of them participated in the immune response, which were considered the candidate biomarkers. GEM and S100B were significantly correlated with marker genes of B cells which had a significant difference between the COPD and normal samples. Moreover, GEM was highly associated with the genes in the PI3K/Akt/GSK3β signaling pathway, regulation of actin cytoskeleton, and calcium signaling pathway based on a Pearson correlation analysis of the candidate genes and the genes in the B cell receptor signaling pathway. PPI network analysis also indicated that GEM might participate in the regulation of the PI3K/Akt/GSK3β signaling pathway. The ROC curve showed that GEM possessed an excellent accuracy in distinguishing COPD from normal samples.\nCONCLUSIONS: The data provide a transcriptome-based evidence that GEM is related to COPD and macrophage polarization likely contributes to COPD diagnosis. At the same time, it is hoped that in-depth functional mining can provide new ideas for exploring the COPD pathogenesis.", "claims": [{"id": "claim-method", "statement": "Pearson analysis was used to investigate the correlation of the candidate genes and the differential immune cells between the COPD and normal samples, as well as marker genes and pathways of differential immune cells.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34250093", "locator": "sections[6] \"2.4. The Functional Annotations and Correlation Analysis of the Candidate Genes\" paragraph 2", "quote": "Pearson analysis was used to investigate the correlation of the candidate genes and the differential immune cells between the COPD and normal samples, as well as marker genes and pathways of differential immune cells."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The GSE124180 dataset analyzed in this study was available in the GEO database.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34250093", "locator": "sections[20] \"Data Availability\" paragraph 2", "quote": "The GSE124180 dataset analyzed in this study was available in the GEO database."}], "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:34250093"], "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:GSE124180"], "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:GSE124180"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:34250093", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1155/2021/9921012", "sha256": "sha256:dfb104fe7ed9687932e637ec013e24311f6797dc66709050b51e900f49549dc1", "bytes": 45799, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1155/2021/9921012", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC8238569", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE124180", "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=GSE124180", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE124180", "version": null, "note": "The GSE124180 dataset analyzed in this study was available in the GEO database.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The GSE124180 dataset analyzed in this study was available in the GEO database.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM3523461", "GSM3523462", "GSM3523463", "GSM3523464", "GSM3523465", "GSM3523466", "GSM3523467", "GSM3523468", "GSM3523469", "GSM3523470", "GSM3523471", "GSM3523472", "GSM3523473", "GSM3523474", "GSM3523475", "GSM3523476", "GSM3523477", "GSM3523478", "GSM3523479", "GSM3523480", "GSM3523481", "GSM3523482", "GSM3523483", "GSM3523484", "GSM3523485", "GSM3523486", "GSM3523487", "GSM3523488", "GSM3523489", "GSM3523490", "GSM3523491", "GSM3523492", "GSM3523493", "GSM3523494", "GSM3523495", "GSM3523496", "GSM3523497", "GSM3523498", "GSM3523499", "GSM3523500", "GSM3523501", "GSM3523502", "GSM3523503", "GSM3523504", "GSM3523505", "GSM3523506", "GSM3523507", "GSM3523508", "GSM3523509", "GSM3523510", "GSM3523511", "GSM3523512", "GSM3523513", "GSM3523514", "GSM3523515", "GSM3523516", "GSM3523517", "GSM3523518", "GSM3523519", "GSM3523520", "GSM3523521", "GSM3523522", "GSM3523523"], "sample_count": 63, "group_sizes": null, "group_sizes_basis": null, "platform": "16791", "taxon": "Homo sapiens", "title": "RNA-sequencing across three matched tissues highlights gene expression signatures in COPD", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "asset:table:pmid:34250093:1", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:d48ffd9dc17df6ee5934f52fac7853c517df871b32e399dd968c79fe3b60cf0a", "bytes": 8190, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[11]/table-wrap[1]#tab1", "version": null, "note": "The results of GO functional annotation and KEGG pathways for the 25 candidate genes.", "structure": {"pmcid": "PMC8238569", "section_index": 11, "section_title": "3.3. Functional Annotations of the Candidate Genes", "row_count": 19, "column_count": 3}, "table": {"label": "Table 1", "caption": "The results of GO functional annotation and KEGG pathways for the 25 candidate genes.", "rows": [["ID", "Biological process", "KEGG pathway"], ["CBR3", "GO:0042376 ~ phylloquinone catabolic process, GO:0050890 ~ cognition, GO:0055114 ~ oxidation-reduction process", "hsa00590: arachidonic acid metabolism, hsa00980: metabolism of xenobiotics by cytochrome P450, hsa01100: metabolic pathways"], ["FZD6", "GO:0001736 ~ establishment of planar polarity, GO:0001843 ~ neural tube closure, GO:0001942 ~ hair follicle development, GO:0007186 ~ G-protein coupled receptor signaling pathway, GO:0007223 ~ Wnt signaling pathway, calcium modulating pathway, GO:0007275 ~ multicellular organism development, GO:0030168 ~ platelet activation, GO:0033278 ~ cell proliferation in midbrain, GO:0035567 ~ non-canonical Wnt signaling pathway, GO:0035880 ~ embryonic nail plate morphogenesis, GO:0042472 ~ inner ear morphogenesis, GO:0043433 ~ negative regulation of sequence-specific DNA binding transcription factor activity, GO:0060071 ~ Wnt signaling pathway, planar cell polarity pathway, GO:0090090 ~ negative regulation of canonical Wnt signaling pathway, GO:1904693 ~ midbrain morphogenesis", "hsa04310: Wnt signaling pathway, hsa04390: Hippo signaling pathway, hsa04550: signaling pathways regulating pluripotency of stem cells, hsa04916: melanogenesis, hsa05166:HTLV-I infection, hsa05200: pathways in cancer, hsa05205: proteoglycans in cancer, hsa05217: basal cell carcinoma"], ["NEFL", "GO:0000165 ~ MAPK cascade, GO:0000226 ~ microtubule cytoskeleton organization, GO:0008089 ~ anterograde axonal transport, GO:0008090 ~ retrograde axonal transport, GO:0009636 ~ response to toxic substance, GO:0014012 ~ peripheral nervous system axon regeneration, GO:0019896 ~ axonal transport of mitochondrion, GO:0021510 ~ spinal cord development, GO:0021766 ~ hippocampus development, GO:0021987 ~ cerebral cortex development, GO:0031133 ~ regulation of axon diameter, GO:0033693 ~ neurofilament bundle assembly, GO:0040011 ~ locomotion, GO:0043434 ~ response to peptide hormone, GO:0043524 ~ negative regulation of neuron apoptotic process, GO:0043547 ~ positive regulation of GTPase activity, GO:0045105 ~ intermediate filament polymerization or depolymerization, GO:0045109 ~ intermediate filament organization, GO:0048812 ~ neuron projection morphogenesis, GO:0050772 ~ positive regulation of axonogenesis, GO:0050885 ~ neuromuscular process controlling balance, GO:0051258 ~ protein polymerization, GO:0051412 ~ response to corticosterone, GO:0061564 ~ axon development, GO:1903935 ~ response to sodium arsenite, GO:1903937 ~ response to acrylamide", "hsa05014: amyotrophic lateral sclerosis (ALS),"], ["ZNF676", "GO:0006351 ~ transcription, DNA-templated, GO:0006355 ~ regulation of transcription, DNA-templated", ""], ["PROX2", "GO:0000122 ~ negative regulation of transcription from RNA polymerase II promoter, GO:0006351 ~ transcription, DNA-templated, GO:0030182 ~ neuron differentiation, GO:0045944 ~ positive regulation of transcription from RNA polymerase II promoter, GO:0055007 ~ cardiac muscle cell differentiation", ""], ["HMMR", "GO:0000086 ~ G2/M transition of mitotic cell cycle, GO:0030214 ~ hyaluronan catabolic process", "hsa04512: ECM-receptor interaction"], ["GEM", "GO:0006955 ~ immune response, GO:0007067 ~ mitotic nuclear division, GO:0007165 ~ signal transduction, GO:0007166 ~ cell surface receptor signaling pathway, GO:0007264 ~ small GTPase mediated signal transduction, GO:0051276 ~ chromosome organization, GO:0051310 ~ metaphase plate congression", ""], ["HESX1", "GO:0006351 ~ transcription, DNA-templated, GO:0007420 ~ brain development,GO:0030916 ~ otic vesicle formation, GO:0043584 ~ nose development, GO:0045892 ~ negative regulation of transcription, DNA-templated, GO:0048853 ~ forebrain morphogenesis,", "hsa04550: signaling pathways regulating pluripotency of stem cells"], ["PRDM6", "GO:0006351 ~ transcription, DNA-templated, GO:0022008 ~ neurogenesis, GO:0034968 ~ histone lysine methylation, GO:0045892 ~ negative regulation of transcription, DNA-templated, GO:0051151 ~ negative regulation of smooth muscle cell differentiation", ""], ["RUNDC3B", "", ""], ["S100B", "GO:0007409 ~ axonogenesis, GO:0007417 ~ central nervous system development, GO:0007611 ~ learning or memory, GO:0007613 ~ memory, GO:0008283 ~ cell proliferation, GO:0008284 ~ positive regulation of cell proliferation, GO:0008360 ~ regulation of cell shape, GO:0043065 ~ positive regulation of apoptotic process, GO:0043123 ~ positive regulation of I-kappaB kinase/NF-kappaB signaling, GO:0045087 ~ innate immune response, GO:0048168 ~ regulation of neuronal synaptic plasticity, GO:0048708 ~ astrocyte differentiation, GO:0051384 ~ response to glucocorticoid, GO:0051597 ~ response to methylmercury, GO:0060291 ~ long-term synaptic potentiation, GO:0071456 ~ cellular response to hypoxia, GO:2001015 ~ negative regulation of skeletal muscle cell differentiation", ""], ["CENPS", "GO:0000712 ~ resolution of meiotic recombination intermediates, GO:0006281 ~ DNA repair, GO:0006312 ~ mitotic recombination, GO:0006974 ~ cellular response to DNA damage stimulus, GO:0007062 ~ sister chromatid cohesion, GO:0007067 ~ mitotic nuclear division, GO:0031297 ~ replication fork processing, GO:0031398 ~ positive regulation of protein ubiquitination, GO:0034080 ~ CENP-A containing nucleosome assembly, GO:0036297 ~ interstrand cross-link repair, GO:0051301 ~ cell division, GO:0051382 ~ kinetochore assembly", "hsa03460: Fanconi anemia pathway"], ["C10orf105", "", ""], ["GZMA", "GO:0006915 ~ apoptotic process, GO:0006955 ~ immune response, GO:0019835 ~ cytolysis, GO:0032078 ~ negative regulation of endodeoxyribonuclease activity, GO:0043065 ~ positive regulation of apoptotic process, GO:0043392 ~ negative regulation of DNA binding, GO:0051354 ~ negative regulation of oxidoreductase activity, GO:0051603 ~ proteolysis involved in cellular protein catabolic process", "hsa04080: neuroactive ligand-receptor interaction"], ["NEBL", "GO:0071691 ~ cardiac muscle thin filament assembly", ""], ["RNF43", "GO:0016055 ~ Wnt signaling pathway, GO:0016567 ~ protein ubiquitination, GO:0030178 ~ negative regulation of Wnt signaling pathway, GO:0038018 ~ Wnt receptor catabolic process, GO:0042787 ~ protein ubiquitination involved in ubiquitin-dependent protein catabolic process, GO:0072089 ~ stem cell proliferation,", ""], ["SPINK2", "GO:0002176 ~ male germ cell proliferation, GO:0007286 ~ spermatid development, GO:0009566 ~ fertilization, GO:0043065 ~ positive regulation of apoptotic process, GO:0060046 ~ regulation of acrosome reaction, GO:0072520 ~ seminiferous tubule development, GO:1900004 ~ negative regulation of serine-type endopeptidase activity", ""], ["UTS2", "GO:0001666 ~ response to hypoxia, GO:0003105 ~ negative regulation of glomerular filtration, GO:0006936 ~ muscle contraction, GO:0007204 ~ positive regulation of cytosolic calcium ion concentration, GO:0007268 ~ chemical synaptic transmission, GO:0008217 ~ regulation of blood pressure, GO:0010459 ~ negative regulation of heart rate, GO:0010460 ~ positive regulation of heart rate, GO:0010763 ~ positive regulation of fibroblast migration, GO:0010841 ~ positive regulation of circadian sleep/wake cycle, wakefulness, GO:0032224 ~ positive regulation of synaptic transmission, cholinergic, GO:0032967 ~ positive regulation of collagen biosynthetic process, GO:0033574 ~ response to testosterone, GO:0035811 ~ negative regulation of urine volume, GO:0035814 ~ negative regulation of renal sodium excretion, GO:0042312 ~ regulation of vasodilation, GO:0042493 ~ response to drug, GO:0045597 ~ positive regulation of cell differentiation, GO:0045766 ~ positive regulation of angiogenesis,GO:0045776 ~ negative regulation of blood pressure, GO:0045777 ~ positive regulation of blood pressure, GO:0045909 ~ positive regulation of vasodilation, GO:0046005 ~ positive regulation of circadian sleep/wake cycle, REM sleep,GO:0046676 ~ negative regulation of insulin secretion,GO:0048146 ~ positive regulation of fibroblast proliferation,", ""]], "row_count": 19, "column_count": 3, "numeric_cells": 27, "header_rows": 1, "locator": "section[11]/table-wrap[1]#tab1"}}], "gaps": ["asset:data:geo:GSE124180 not downloaded", "asset:data:geo:GSE124180 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "correlation_analysis", "specific": "pearson", "label": "Correlation analysis", "dsl_operations": ["pearson_r"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["paired_numeric_columns"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "Pearson analysis was used to investigate the correlation of the candidate genes and the differential immune cells between the COPD and normal samples, as well 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