Evidence map›Paper›PMID 39553847›Full record

ArticleFrontiers in cardiovascular medicine2024

Identification of key genes for cuproptosis in carotid atherosclerosis.

Xize Wu, Jian Kang, Xue Pan, Chentian Xue, Jiaxiang Pan, Chao Quan, Lihong Ren, Lihong Gong, Yue Li

Abstract read
In one paragraph

Article in Frontiers in cardiovascular medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
  2. Distinct types of regulated cell death in atherosclerosis.Journal of pharmaceutical analysis · 2026
    Review
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Xize Wu *Department of Critical Care Medicine, Nantong Hospital of Traditional Chinese Medicine, Nantong Hospital Affiliated to Nanjing University of Chinese Medicine, Nantong, Jiangsu, China.
Jian Kang *Graduate School, Liaoning University of Traditional Chinese Medicine, Shenyang, Liaoning, China.
Xue Pan *Graduate School, Liaoning University of Traditional Chinese Medicine, Shenyang, Liaoning, China.
Chentian XueDepartment of Critical Care Medicine, Nantong Hospital of Traditional Chinese Medicine, Nantong Hospital Affiliated to Nanjing University of Chinese Medicine, Nantong, Jiangsu, China.
Jiaxiang PanDepartment of Cardiology, The Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang, Liaoning, China.
Chao QuanDepartment of Critical Care Medicine, Nantong Hospital of Traditional Chinese Medicine, Nantong Hospital Affiliated to Nanjing University of Chinese Medicine, Nantong, Jiangsu, China.
Lihong RenDepartment of Critical Care Medicine, Nantong Hospital of Traditional Chinese Medicine, Nantong Hospital Affiliated to Nanjing University of Chinese Medicine, Nantong, Jiangsu, China.
Lihong GongDepartment of Cardiology, The Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang, Liaoning, China.
Yue LiDepartment of Cardiology, The Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang, Liaoning, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Atherosclerosis is a leading cause of cardiovascular disease worldwide, while carotid atherosclerosis (CAS) is more likely to cause ischemic cerebrovascular events. Emerging evidence suggests that cuproptosis may be associated with an increased risk of atherosclerotic cardiovascular disease. This study aims to explore the potential mechanisms linking cuproptosis and CAS. Methods: The GSE100927 and GSE43292 datasets were merged to screen for CAS differentially expressed genes (DEGs) and intersected with cuproptosis-related genes to obtain CAS cuproptosis-related genes (CASCRGs). Unsupervised cluster analysis was performed on CAS samples to identify cuproptosis molecular clusters. Weighted gene co-expression network analysis was performed on all samples and cuproptosis molecule clusters to identify common module genes. CAS-specific DEGs were identified in the GSE100927 dataset and intersected with common module genes to obtain candidate hub genes. Finally, 83 machine learning models were constructed to screen hub genes and construct a nomogram to predict the incidence of CAS. Results: Four ASCRGs (NLRP3, SLC31A2, CDKN2A, and GLS) were identified as regulators of the immune infiltration microenvironment in CAS. CAS samples were identified with two cuproptosis-related molecular clusters with significant biological function differences based on ASCRGs. 220 common module hub genes and 1,518 CAS-specific DEGs were intersected to obtain 58 candidate hub genes, and the machine learning model showed that the Lasso + XGBoost model exhibited the best discriminative performance. Further external validation of single gene differential analysis and nomogram identified SGCE, PCDH7, RAB23, and RIMKLB as hub genes; SGCE and PCDH7 were also used as biomarkers to characterize CAS plaque stability. Finally, a nomogram was developed to assess the incidence of CAS and exhibited satisfactory predictive performance. Conclusions: Cuproptosis alters the CAS immune infiltration microenvironment and may regulate actin cytoskeleton formation.

Indexed as

atherosclerosiscuproptosismachine learning modelnomogramunsupervised clustering analysis

Identifiers

PMID39553847
PMCPMC11564188

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.