Development and validation of a new diagnostic prediction model of ENHO and NOX4 for early diagnosis of systemic sclerosis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38348042", "kind": "science-record", "revision": 4, "content_hash": "sha256:6c31e38a629ec8ea84b433fb1bd199f1e569c7a52396b0471b6e0cdcb80951ac", "created_at": "2026-11-01T19:20:17Z", "updated_at": "2026-11-01T22:53:40Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Development and validation of a new diagnostic prediction model of ENHO and NOX4 for early diagnosis of systemic sclerosis.", "doi": "10.3389/fimmu.2024.1273559", "pmid": "38348042", "authors": ["Leting Zheng", "Qiulin Wu", "Shuyuan Chen", "Jing Wen", "Fei Dong", "Ningqin Meng", "Wen Zeng", "Cheng Zhao", "Xiaoning Zhong"], "journal": "Frontiers in immunology", "year": 2024, "abstract": "Objective: Systemic sclerosis (SSc) is a chronic autoimmune disease characterized by fibrosis. The challenge of early diagnosis, along with the lack of effective treatments for fibrosis, contribute to poor therapeutic outcomes and high mortality of SSc. Therefore, there is an urgent need to identify suitable biomarkers for early diagnosis of SSc.\nMethods: Three skin gene expression datasets of SSc patients and healthy controls were downloaded from Gene Expression Omnibus (GEO) database (GSE130955, GSE58095, and GSE181549). GSE130955 (48 early diffuse cutaneous SSc and 33 controls) were utilized to screen differentially expressed genes (DEGs) between SSc and normal skin samples. Least absolute shrinkage and selection operator (LASSO) regression and support vector machine recursive feature elimination (SVM-RFE) were performed to identify diagnostic genes and construct a diagnostic prediction model. The results were further validated in GSE58095 (61 SSc and 36 controls) and GSE181549 (113 SSc and 44 controls) datasets. Receiver operating characteristic (ROC) curves were applied for assessing the level of diagnostic ability. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used to verify the diagnostic genes in skin tissues of out cohort (10 SSc and 5 controls). Immune infiltration analysis were performed using CIBERSORT algorithm.\nResults: A total of 200 DEGs were identified between SSc and normal skin samples. Functional enrichment analysis revealed that these DEGs may be involved in the pathogenesis of SSc, such as extracellular matrix remodeling, cell-cell interactions, and metabolism. Subsequently, two critical genes (ENHO and NOX4) were identified by LASSO and SVM-RFE. ENHO was found down-regulated while NOX4 was up-regulated in skin of SSc patients and their expression levels were validated by above three datasets and our cohort. Notably, these differential expressions were more pronounced in patients with diffuse cutaneous SSc than in those with limited cutaneous SSc. Next, we developed a novel diagnostic model for SSc using ENHO and NOX4, which demonstrated strong predictive power in above three cohorts and in our own cohort. Furthermore, immune infiltration analysis revealed dysregulated levels of various immune cell subtypes within early SSc skin specimens, and a negative correlation was observed between the levels of ENHO and Macrophages M1 and M2, while a positive correlation was observed between the levels of NOX4 and Macrophages M1 and M2.\nConclusion: This study identified ENHO and NOX4 as novel biomarkers that can be serve as a diagnostic prediction model for early detection of SSc and play a potential role in the pathogenesis of the disease.", "claims": [{"id": "claim-method", "statement": "Data processing and screening for DEGs were conducted using the limma package in the R programming language.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38348042", "locator": "sections[4] \"Data processing and differentially expressed genes screening\" paragraph 2", "quote": "Data processing and screening for DEGs were conducted using the limma package in the R programming language."}], "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.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38348042", "locator": "sections[18] \"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."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Following LASSO and SVM analysis, we have successfully identified two pivotal genes, ENHO and NOX4, that play a crucial role in the pathogenesis and progression of SSc.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38348042", "locator": "sections[17] \"Conclusion\" paragraph 2", "quote": "Following LASSO and SVM analysis, we have successfully identified two pivotal genes, ENHO and NOX4, that play a crucial role in the pathogenesis and progression of SSc."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Following LASSO and SVM analysis, we have successfully identified two pivotal genes, ENHO and NOX4, that play a crucial role in the pathogenesis and progression of SSc.", "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:38348042"], "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:GSE130955"], "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:GSE130955"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:38348042", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fimmu.2024.1273559", "sha256": "sha256:e3070fa493840f3230be154f9c5a1616605a03fcef23391619e1ff082e245cfa", "bytes": 39673, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fimmu.2024.1273559", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC10859860", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE130955", "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=GSE130955", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE130955", "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:38348042", "data:geo:GSE130955"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE130955"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T19:08:23Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 10198, "completion_tokens": 1383, "cached_tokens": 128}}, "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:38348042", "type": "paper", "label": "pmid:38348042"}, {"id": "source:pmid:38348042", "type": "manuscript", "label": "PMID 38348042 full text"}, {"id": "data:geo:GSE130955", "type": "dataset", "label": "GEO GSE130955"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:38348042", "type": "paper", "label": "pmid:38348042"}, {"id": "source:pmid:38348042", "type": "manuscript", "label": "PMID 38348042 full text"}, {"id": "data:geo:GSE130955", "type": "dataset", "label": "GEO GSE130955"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-38348042", "type": "extraction", "used": ["source:pmid:38348042"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE130955", "type": "accession_resolution", "used": ["data:geo:GSE130955"], "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:38348042", "parent_hash": "sha256:c4fd634420c3efe83945a7058deec1fc050b3d8a5eb89d340493d0daf7754edb", "fork_of": null, "generation": 3}, "gaps": ["asset:data:geo:GSE130955 licence not read", "asset:data:geo:GSE130955 not downloaded", "asset:data:geo:GSE181549 licence not read", "asset:data:geo:GSE181549 not downloaded", "asset:data:geo:GSE58095 licence not read", "asset:data:geo:GSE58095 not downloaded", "execution.not_run", "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": ["tion-quantitative polymerase chain reaction (RT-qPCR) was used to verify the diagnostic genes in", "n-quantitative polymerase chain reaction (RT-qPCR) was used to verify the diagnostic genes in"], "order_basis": "paper_text_order:1280", "id": "assay:1"}, {"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": ["Data processing and screening for DEGs were conducted using the limma package in the R programming language."], "order_basis": "consumes_earlier_output", "id": "assay:2"}]}