Evidence map›Paper›PMID 34150004›Full record

ArticleAmerican journal of translational research2021

Identification of candidate targets for the diagnosis and treatment of atherosclerosis by bioinformatics analysis.

Yan Gu, Xiao Ma, Jing Li, Yuhong Ma, Yun Zhang

Open access · greenAbstract read
In one paragraph

Article in American journal of translational research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.1field-weighted citation impact, top 23% 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

15 citing papers in PubMed, 16 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

5 authors at 2 institutions in 1 country.

Yan GuAffiliated Hospital of Inner Mongolia Medical University Hohhot 010050, The Inner Mongolia Autonomous Region, P. R. China.
Xiao MaChinese People's Liberation Army No. 969 Hospital Hohhot 010051, The Inner Mongolia Autonomous Region, P. R. China.
Jing LiAffiliated Hospital of Inner Mongolia Medical University Hohhot 010050, The Inner Mongolia Autonomous Region, P. R. China.
Yuhong MaAffiliated Hospital of Inner Mongolia Medical University Hohhot 010050, The Inner Mongolia Autonomous Region, P. R. China.
Yun ZhangAffiliated Hospital of Inner Mongolia Medical University Hohhot 010050, The Inner Mongolia Autonomous Region, P. R. China.
Inner Mongolia Medical University · CNInner Mongolia People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Atherosclerosis, a chronic inflammatory disease, is the primary cause of most cardiovascular diseases. Circular RNAs (circRNAs) were reported to serve as post-transcriptional regulators and diagnostic markers in various diseases, but the underlying correlation between circRNAs and atherosclerosis remains elusive. In this study, we downloaded the microarray dataset GSE107522 from the Gene Expression Omnibus (GEO) and identified nine differentially expressed circRNAs (DECs). DECs expression in exosomes were investigated, and hsa_circ_0005699 was selected for subsequent analysis. We then identified 14 RNA-binding proteins (RBPs) and 71 possible hsa_circ_0005699-interacting microRNAs. Subsequently, target gene prediction and enrichment analyses were performed. The enriched pathways of RBP eIF4AIII include spliceosome, cell cycle, and pathways in cancer. We constructed a protein-protein interaction network, and 20 hub genes were identified using Search Tool for the Retrieval of Interacting Genes/Proteins and Cytoscape. Hub gene analysis revealed significant enrichment in mRNA splicing via the spliceosome, RNA splicing, protein binding, neurotrophin signaling pathway, and Ras signaling pathway. Using DrugMatrix of the Enrichr database, we identified 16 most significant small-molecule compounds that interacted with hub genes. Finally, seven hub genes (NEDD4L, FBXO44, FBXO27, WSB1, FBXW8, UBE2F, and ASB1) in cluster 1 were considered key targets associated with atherosclerosis according to MCODE analysis and the intersection between the module and hub genes. Thus, hsa_circ_0005699, RBP eIF4AIII, and the seven identified hub genes (NEDD4L, FBXO44, FBXO27, WSB1, FBXW8, UBE2F, and ASB1) could help to elucidate the pathogenesis and progression of atherosclerosis. This work may contribute to providing candidate targets for the diagnosis and treatment of atherosclerosis.

Indexed as

AtherosclerosisbiomarkercircRNAdiagnosistreatment

Identifiers

PMID34150004
PMCPMC8205787
OpenAlexW3173238276

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.