Evidence map›Paper›PMID 34163213›Full record

ArticlePharmacogenomics and personalized medicine2021

Identification of Independent and Communal Differentially Expressed Genes as Well as Potential Therapeutic Targets in Ischemic Heart Failure and Non-Ischemic Heart Failure.

Zuoxiang Wang, Mingyang Zhang, Yinan Xu, Yiyu Gu, Yumeng Song, Tingbo Jiang

Open access · goldAbstract read
In one paragraph

Article in Pharmacogenomics and personalized medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.1field-weighted citation impact, top 57% of its field
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Zuoxiang WangDepartment of Cardiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, People's Republic of China.
Mingyang ZhangDepartment of Cardiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, People's Republic of China.
Yinan XuDepartment of Cardiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, People's Republic of China.
Yiyu GuDepartment of Cardiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, People's Republic of China.
Yumeng SongDepartment of Cardiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, People's Republic of China.
Tingbo JiangDepartment of Cardiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, People's Republic of China.
Soochow University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHeart failure (HF) is a rapidly growing public health problem, and its two main etiological types are non-ischemic heart failure (NIHF) and ischemic heart failure (IHF). However, the independent and common mechanisms of NIHF and IHF have not been fully elucidated. Here, bioinformatic analysis was used to characterize the difference and independent pathways for IHF and NIHF, and more importantly, to unearth the common potential markers and therapeutic targets in IHF and NIHF.

methodsTwo data sets with accession numbers GSE26887 and GSE84796 were downloaded from the Gene Expression Omnibus (GEO) database. After identifying the independent and communal DEGs of NIHF and IHF, a functional annotation, protein-protein interaction (PPI) network analysis, co-expression and drug-gene interaction prediction analysis, and mRNA-miRNA regulatory network analysis were performed for DEGs.

resultsWe found 1146 independent DEGs (DEGs2) of NIHF mainly enriched in transcription-related and 2595 independent DEGs (DEGs3) of IHF mainly enriched in immune-related. Moreover, 185 communal DEGs (DEGs1) were found between NIHF and IHF, including 93 upregulated genes and 92 downregulated genes. Pathway enrichment analysis results showed that GPCR pathways and biological processes are closely related to the occurrence of HF. In addition, three hub genes were identified from PPI network, including CCL5, C5 and TLR3.

conclusionThe identification of DEGs and hub genes in this study contributes to a novel perception for potential functional mechanisms and biomarkers or therapeutic targets in NIHF and IHF.

Indexed as

bioinformatical analysisdifferentially expressed genesheart failurehub genesischemic heart failurenon-ischemic heart failure

Identifiers

PMID34163213
PMCPMC8214211
OpenAlexW3170039851

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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.