Evidence map›Paper›PMID 36818726›Full record

ArticleFrontiers in neurology2022

Comprehensive analysis of cuproptosis-related genes in immune infiltration in ischemic stroke.

Xuehui Fan, Hongping Chen, Fangchao Jiang, Chen Xu, Yingju Wang, Haining Wang, Meng Li, Wan Wei, Jihe Song, Di Zhong and 1 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in neurology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 1 pooled it
8.0field-weighted citation impact, top 2% of its field
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

29 citing papers in PubMed, 1 synthesis or guideline pooled it, 31 citations in OpenAlex.

  1. Pooled it
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  3. Review
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  5. Review
  6. Article
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  18. Current neuropharmacology · 2025
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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

11 authors at 2 institutions in 1 country.

Xuehui FanDepartment of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China.
Hongping ChenDepartment of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China.
Fangchao JiangDepartment of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China.
Chen XuDepartment of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China.
Yingju WangDepartment of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China.
Haining WangDepartment of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China.
Meng LiDepartment of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China.
Wan WeiDepartment of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China.
Jihe SongDepartment of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China.
Di ZhongDepartment of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China.
Guozhong LiDepartment of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China.
Harbin Medical University · CNFirst Affiliated Hospital of Harbin Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Immune infiltration plays an important role in the course of ischemic stroke (IS) progression. Cuproptosis is a newly discovered form of programmed cell death. To date, no studies on the mechanisms by which cuproptosis-related genes regulate immune infiltration in IS have been reported. Methods: IS-related microarray datasets were retrieved from the Gene Expression Omnibus (GEO) database and standardized. Immune infiltration was extracted and quantified based on the processed gene expression matrix. The differences between the IS group and the normal group as well as the correlation between the infiltrating immune cells and their functions were analyzed. The cuproptosis-related DEGs most related to immunity were screened out, and the risk model was constructed. Finally, Gene Ontology (GO) function, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses and drug target were performed using the Enrichr website database. miRNAs were predicted using FunRich software. Finally, cuproptosis-related differentially expressed genes (DEGs) in IS samples were typed, and Gene Set Variation Analysis (GSVA) was used to analyze the differences in biological functions among the different types. Results: Seven Cuproptosis-related DEGs were obtained by merging the GSE16561 and GSE37587 datasets. Correlation analysis of the immune cells showed that NLRP3, NFE2L2, ATP7A, LIPT1, GLS, and MTF1 were significantly correlated with immune cells. Subsequently, these six genes were included in the risk study, and the risk prediction model was constructed to calculate the total score to analyze the risk probability of the IS group. KEGG analysis showed that the genes were mainly enriched in the following two pathways: D-glutamine and D-glutamate metabolism; and lipids and atherosclerosis. Drug target prediction found that DMBA CTD 00007046 and Lithocholate TTD 00009000 were predicted to have potential therapeutic effects of candidate molecules. GSVA showed that the TGF-β signaling pathway and autophagy regulation pathways were upregulated in the subgroup with high expression of cuproptosis-related DEGs. Conclusions: NLRP3, NFE2L2, ATP7A, LIPT1, GLS and MTF1 may serve as predictors of cuproptosis and play an important role in the pathogenesis of immune infiltration in IS.

Indexed as

cuproptosisimmune infiltrationischemic strokepredictorsrisk model construction

Identifiers

PMID36818726
PMCPMC9933552
OpenAlexW4318980488

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.