Discovery of biomarkers in the psoriasis through machine learning and dynamic immune infiltration in three types of skin lesions.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38803495", "kind": "science-record", "revision": 5, "content_hash": "sha256:41367a0f8c334f55025cb2e105aa3c7f105416850548e11903b978efe17c1e5b", "created_at": "2026-11-01T19:20:45Z", "updated_at": "2026-11-01T22:54:23Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Discovery of biomarkers in the psoriasis through machine learning and dynamic immune infiltration in three types of skin lesions.", "doi": "10.3389/fimmu.2024.1388690", "pmid": "38803495", "authors": ["Xiao Zhou", "Han Zhou", "Xin Luo", "Rui-Fang Wu"], "journal": "Frontiers in immunology", "year": 2024, "abstract": "Introduction: Psoriasis is a chronic skin disease characterized by unique scaling plaques. However, during the acute phase, psoriatic lesions exhibit eczematous changes, making them difficult to distinguish from atopic dermatitis, which poses challenges for the selection of biological agents. This study aimed to identify potential diagnostic genes in psoriatic lesions and investigate their clinical significance.\nMethods: GSE182740 datasets from the GEO database were analyzed for differential analysis; machine learning algorithms (SVM-RFE and LASSO regression models) are used to screen for diagnostic markers; CIBERSORTx is used to determine the dynamic changes of 22 different immune cell components in normal skin lesions, psoriatic non-lesional skin, and psoriatic lesional skin, as well as the expression of the diagnostic genes in 10 major immune cells, and real-time quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry are used to validate results.\nResults: We obtained 580 differentially expressed genes (DEGs) in the skin lesion and non-lesion of psoriasis patients, 813 DEGs in mixed patients between non-lesions and lesions, and 96 DEGs in the skin lesion and non-lesion of atopic dermatitis, respectively. Then 144 specific DEGs in psoriasis via a Veen diagram were identified. Ultimately, UGGT1, CCNE1, MMP9 and ARHGEF28 are identified for potential diagnostic genes from these 144 specific DEGs. The value of the selected diagnostic genes was verified by receiver operating characteristic (ROC) curves with expanded samples. The the area under the ROC curve (AUC) exceeded 0.7 for the four diagnosis genes. RT-qPCR results showed that compared to normal human epidermis, the expression of UGGT1, CCNE1, and MMP9 was significantly increased in patients with psoriasis, while ARHGEF28 expression was significantly decreased. Notably, the results of CIBERSORTx showed that CCNE1 was highly expressed in CD4+ T cells and neutrophils, ARHGEF28 was also expressed in mast cells. Additionally, CCNE1 was strongly correlated with IL-17/CXCL8/9/10 and CCL20. Immunohistochemical results showed increased nuclear expression of CCNE1 in psoriatic epidermal cells relative to normal.\nConclusion: Based on the performance of the four genes in ROC curves and their expression in immune cells from patients with psoriasis, we suggest that CCNE1 possess higher diagnostic value.", "claims": [{"id": "claim-method", "statement": "GEO2R is an interactive R-based online analysis tool that utilizes limma R packages to analyze the original data with the moderated t-statistic for significance analysis, and Benjamini & Hochberg false discovery rate method for applying P-value adjustment for multiple testing correction.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38803495", "locator": "sections[3] \"Datasets information\" paragraph 2", "quote": "GEO2R is an interactive R-based online analysis tool that utilizes limma R packages to analyze the original data with the moderated t-statistic for significance analysis, and Benjamini & Hochberg false discovery rate method for applying P-value adjustment for multiple testing correction."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material .", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38803495", "locator": "sections[22] \"Data availability statement\" paragraph 2", "quote": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material ."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "", "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:38803495"], "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:GSE182740"], "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": {"fdr_threshold": "nd Benjamini & Hochberg false discovery rate adjustment"}, "inputs": ["data:geo:GSE182740"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:38803495", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fimmu.2024.1388690", "sha256": "sha256:86490d18cb5312962aa1636e6b325bcd71212a1a9b8a0819a709f2c3b57f50d2", "bytes": 35552, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fimmu.2024.1388690", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11128609", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE182740", "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=GSE182740", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE182740", "version": null, "note": "The datasets presented in this study can be found in online repositories. 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No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "assets": ["source:pmid:38803495", "data:geo:GSE182740"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE182740"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T19:19:45Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 10010, "completion_tokens": 1461, "cached_tokens": 264}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:38803495", "type": "paper", "label": "pmid:38803495"}, {"id": "source:pmid:38803495", "type": "manuscript", "label": "PMID 38803495 full text"}, {"id": "data:geo:GSE182740", "type": "dataset", "label": "GEO GSE182740"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:38803495", "type": "paper", "label": "pmid:38803495"}, {"id": "source:pmid:38803495", "type": "manuscript", "label": "PMID 38803495 full text"}, {"id": "data:geo:GSE182740", "type": "dataset", "label": "GEO GSE182740"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-38803495", "type": "extraction", "used": ["source:pmid:38803495"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE182740", "type": "accession_resolution", "used": ["data:geo:GSE182740"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}, {"id": "agent:minimax-reader", "type": "software", "label": "MiniMax literature reader"}], "source_run_id": "reading-sci-2026-11-01", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:38803495", "parent_hash": "sha256:81019f76b5371afad65fcb4efd7533658f9f3d423234f5d55d4778293be65193", "fork_of": null, "generation": 4}, "gaps": ["asset:data:geo:GSE182740 licence not read", "asset:data:geo:GSE182740 not downloaded", "asset:data:geo:GSE78097 licence not read", "asset:data:geo:GSE78097 not downloaded", "execution.not_run", "method.reader_differs_from_extractor", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "qpcr", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["time quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry are used to valida", ") exceeded 0.7 for the four diagnosis genes. RT-qPCR results showed that compared to normal human", "e quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry are used to valida", "xceeded 0.7 for the four diagnosis genes. RT-qPCR results showed that compared to normal human"], "order_basis": "paper_text_order:1004", "id": "assay:1"}, {"role": "data_generation", "definition_id": "ihc", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["tive polymerase chain reaction (RT-qPCR) and immunohistochemistry are used to validate results. Results: We ob", "correlated with IL-17/CXCL8/9/10 and CCL20. Immunohistochemical results showed increased nuclear expression"], "order_basis": "paper_text_order:1017", "id": "assay:2"}, {"role": "analysis", "definition_id": "differential_expression", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["GEO2R is an interactive R-based online analysis tool that utilizes limma R packages to analyze the original data with the moderated t-statistic for significance analysis, and Benjamini & Hochberg false discovery rate method for applying P-value adjustment for multiple testing correction."], "order_basis": "consumes_earlier_output", "id": "assay:3"}]}