Identification of necroptosis-related gene TRAF5 as potential target of diagnosing atherosclerosis and assessing its stability.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37330462", "kind": "science-record", "revision": 4, "content_hash": "sha256:258e33aae28259c2700e730a761fc135c083472788b958753c2e3b16357d1619", "created_at": "2026-11-01T19:02:04Z", "updated_at": "2026-11-01T22:52:08Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of necroptosis-related gene TRAF5 as potential target of diagnosing atherosclerosis and assessing its stability.", "doi": "10.1186/s12920-023-01573-0", "pmid": "37330462", "authors": ["Zhanli Peng", "Kangjie Wang", "Shenming Wang", "Ridong Wu", "Chen Yao"], "journal": "BMC medical genomics", "year": 2023, "abstract": "BACKGROUND: Atherosclerosis (AS) is a leading cause of morbidity and mortality in older patients and features progressive formation of plaques in vascular tissues. With the progression of atherosclerosis, plaque rupture may occur and cause stroke, myocardial infarction, etc. Different forms of cell death promote the formation of a necrotic core of the plaque, leading to rupture. Necroptosis is a type of programmed cell death that contributes to the development of cardiovascular disease. However, the role of necroptosis in AS has not yet been investigated.\nMETHODS: The Gene Expression Omnibus (GEO) database was used to obtain gene expression profiles. Differentially expressed genes (DEGs) and necroptosis gene sets were used to identify necroptosis-related differentially expressed genes (NRDEGs). The NRDEGs were used to construct a diagnostic model and were further screened using least absolute shrinkage selection operator (LASSO) regression and random forest (RF) analysis. The discriminatory capacity of the NRDEGs was evaluated using receiver operating characteristic (ROC) curves. Immune infiltration levels were estimated based on CIBERSORTx analysis. The GSE21545 dataset, containing survival information, was used to determine prognosis-associated genes. Univariate and multivariate Cox regression analyses combined with survival analysis determined gene prognostic values. RNA and protein levels were detected by RT-qPCR and western blotting in arteriosclerosis obliterans(ASO) and normal vascular tissues. Vascular smooth muscle cells (VSMCs) were treated with oxidized low-density lipoprotein (ox-LDL) to develop cell models of advanced AS. The effects of protein knockdown on necroptosis were assessed by western blotting and flow cytometry. EdU and Cell Counting Kit-8 assays were used to examine cell proliferation.\nRESULTS: TNF Receptor Associated Factor 5 (TRAF5) was identified as a diagnostic marker for AS based on the AUC value in both the GSE20129 and GSE43292 datasets. According to differential expression analysis, LASSO regression analysis, RF analysis, univariate analysis, multivariate analysis, and gene-level survival analysis, TRAF5 was markedly associated with necroptosis in AS. Silencing TRAF5 promotes necroptosis and attenuates the proliferation of ox-LDL-induced cell models of advanced AS.\nCONCLUSIONS: This study identified a diagnostic marker of necroptosis-related atherosclerosis, TRAF5, which can also be used to diagnose and assess atherosclerotic plaque stability. This novel finding has important implications in the diagnosis and assessment of plaque stability in atherosclerosis.", "claims": [{"id": "claim-method", "statement": "Receiver operating characteristic (ROC) curves were generated to verify the predictive significance of the identified NRG signature [26]. To determine diagnostic accuracy, the area under the ROC curve (AUC) was calculated.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37330462", "locator": "sections[7] \"Screening and construction of necroptosis-related gene signatures for AS diagnosis\" paragraph 2", "quote": "Receiver operating characteristic (ROC) curves were generated to verify the predictive significance of the identified NRG signature [26]. To determine diagnostic accuracy, the area under the ROC curve (AUC) was calculated."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/Supplementary Material; further inquiries can be directed to the corresponding authors.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37330462", "locator": "sections[34] \"Availability of data and materials\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/Supplementary Material; further inquiries can be directed to the corresponding authors."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The 13-gene LASSO diagnostic model showed strong discrimination of atherosclerosis in the training and validation datasets, with AUC values of 0.8665 and 0.876, respectively.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37330462", "locator": "sections[21] \"Screening and creation of AS diagnostic NRG signatures\" paragraph 2", "quote": "The AUC scores in the GSE20129 and GSE43292 datasets were 0.8665 and 0.876 (Fig. 3E, F)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The 13-gene LASSO diagnostic model showed strong discrimination of atherosclerosis in the training and validation datasets, with AUC values of 0.8665 and 0.876, respectively.", "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:37330462"], "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:GSE100927"], "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:GSE100927"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:37330462", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12920-023-01573-0", "sha256": "sha256:c353f0d9c8a8825b886f15855644c190b519560424e3c5e4a41915cc1831afa0", "bytes": 48751, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1186/s12920-023-01573-0", "version": null, "note": "Full article fetched from PMC; 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