Evidence map›Paper›PMID 36304068›Full record

ArticleJournal of immunology research2022

Identifying Hub Genes and Immune Cell Infiltration for the Progression of Carotid Atherosclerotic Plaques in the Context of Predictive and Preventive Using Integrative Bioinformatics Approaches and Machine-Learning Strategies.

Han Zhang, Yinde Huang, Xin Li, Wenbin Chen, Yu Lun, Jian Zhang

Open access · goldAbstract read
In one paragraph

Article in Journal of immunology research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.6field-weighted citation impact, top 36% 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

8 citing papers in PubMed, 7 citations in OpenAlex.

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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

6 authors at 1 institution in 1 country.

Han ZhangDepartment of Vascular and Thyroid Surgery, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning 110001, China.ORCID https://orcid.org/0000-0002-5333-3322
Yinde HuangDepartment of Vascular and Thyroid Surgery, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning 110001, China.ORCID https://orcid.org/0000-0002-6063-9549
Xin LiDepartment of Vascular and Thyroid Surgery, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning 110001, China.ORCID https://orcid.org/0000-0003-0315-7321
Wenbin ChenDepartment of Vascular and Thyroid Surgery, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning 110001, China.ORCID https://orcid.org/0000-0003-3037-4356
Yu LunDepartment of Vascular and Thyroid Surgery, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning 110001, China.ORCID https://orcid.org/0000-0001-5165-247X
Jian ZhangDepartment of Vascular and Thyroid Surgery, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning 110001, China.ORCID https://orcid.org/0000-0003-4448-0774
First Hospital of China Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Emerging evidence shows that carotid atherosclerosis is related to the activation of immune-related pathways and inflammatory cell infiltration. However, the immune-linked pathways that helped in the advancement of the carotid atherosclerotic plaque and the association of such plaques with the infiltration status of the body's immune cells still unclear. Here, the expression profiles of the genes expressed during the progression of the carotid atherosclerotic plaques were retrieved from the Gene Expression Omnibus database and 178 differentially expressed genes were examined. The Weighted Gene Coexpression Network Analysis technique identified one of the brown modules showed the greatest correlation with carotid atherosclerotic plaques. In total, 66 intersecting genes could be detected after combining the DEGs. LASSO regression analysis was subsequently performed to obtain five hub genes as potential biomarkers for carotid atherosclerotic plaques. The functional analysis emphasized the vital roles played by the inflammation- and immune system-related pathways in this disease. The immune cell infiltration results highlighted the significant correlation among the CD4+ T cells, B cells, macrophages, and CD8+ T cells. Thereafter, the gene expression levels and the diagnostic values related to every hub gene were further validated. The above results indicated that macrophages, B cells, CD4+ T cells, and CD8 + T cells were closely related to the formation of the advanced-stage carotid atherosclerotic plaques. Based on the results, it could be hypothesized that the expression of hub genes (C3AR1, SLAMF8, TMEM176A, FERMT3, and GIMAP4) assisted in the advancement of the early-stage to advanced-stage carotid atherosclerotic plaque through immune-related signaling pathways. This may help to provide novel strategies for the treatment of carotid plaque in the context of predictive, preventive, and personalized medicine.

Indexed as

Plaque, AtheroscleroticComputational BiologyGene Regulatory NetworksGTP-Binding ProteinsHumansMachine LearningMacrophagesMembrane ProteinsSignaling Lymphocytic Activation Molecule FamilyGIMAP4 protein, humanGTP-Binding ProteinsMembrane ProteinsSignaling Lymphocytic Activation Molecule FamilySLAMF8 protein, humanTMEM176A protein, human

Identifiers

PMID36304068
PMCPMC9596267
OpenAlexW4306724243

What OpenQuestion holds

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Registered trials

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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.