Evidence map›Paper›PMID 30115125›Full record

ArticleJournal of biomedical science2018

Identification of target genes in cardiomyopathy with fibrosis and cardiac remodeling.

Jianquan Zhao, Tiewei Lv, Junjun Quan, Weian Zhao, Jing Song, Zhuolin Li, Han Lei, Wei Huang, Longke Ran

Open access · diamondAbstract read
In one paragraph

Article in Journal of biomedical science, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed, 1 pooled it
4.5field-weighted citation impact, top 5% 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

38 citing papers in PubMed, 1 synthesis or guideline pooled it, 61 citations in OpenAlex.

  1. Pooled it
  2. Trial
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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

9 authors at 3 institutions in 1 country.

Jianquan ZhaoDepartment of Cardiology, Bayannaoer City Hospital, 35 Xinhua District, Bayannaoer, 015000, Inner Mongolia, China. jqzhaocqmu@163.com.
Tiewei LvDepartment of Cardiology, Children's hospital, Chongqing Medical University, Chongqing, China.
Junjun QuanDepartment of Cardiology, Children's hospital, Chongqing Medical University, Chongqing, China.
Weian ZhaoDepartment of Cardiology, Children's hospital, Chongqing Medical University, Chongqing, China.
Jing SongDepartment of Bioinformatics, Chongqing Medical University, 1 Yixueyuan Road, Yuzhong District, Chongqing, 400016, China.
Zhuolin LiDepartment of Vascular Cardiology, the First Affiliated Hospital of Chongqing, Medical University, Chongqing, China.
Han LeiDepartment of Vascular Cardiology, the First Affiliated Hospital of Chongqing, Medical University, Chongqing, China.
Wei HuangDepartment of Vascular Cardiology, the First Affiliated Hospital of Chongqing, Medical University, Chongqing, China.
Longke RanDepartment of Bioinformatics, Chongqing Medical University, 1 Yixueyuan Road, Yuzhong District, Chongqing, 400016, China. longkeran@aliyun.com.
Chongqing Medical University · CNChildren's Hospital of Chongqing Medical University · CNFirst Affiliated Hospital of Chongqing Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIdentify genes probably associated with chronic heart failure and predict potential target genes for dilated cardiomyopathy using bioinformatics analyses.

methodsGene expression profiles (series number GSE3585 and GSE42955) of cardiomyopathy patients and healthy controls were downloaded from the Expression Omnibus Gene (GEO) database. Differential expression of genes (DEGS) between the two groups of total 14 cardiomyopathy patients and 10 healthy controls were subsequently identified by limma package of R. Database for Annotation, Visualization, and Integrated Discovery (DAVID Tool), which is an analysis of enriched biological processes. Search Tool for the Retrieval Interacting Genes (STRING) was used as well for the analysis of protein-protein interaction network (PPI). Prediction of the potential drugs was suggested based on the preliminarily identified genes using Connectivity Map (CMap).

resultsEighty-nine DEGs were identified (57 up-regulated and 32 down-regulated). The most enrichment Gene Ontology (GO) terms (P < 0.05) contain genes involved in extracellular matrix (ECM) and biological adhesion signal pathways (P < 0.05, ES > 1.5) such as ECM-receptors, focal adhesion and transforming growth factor beta (TGF-β), etc. Fifty-one differentially expressed genes were found to encode interacting proteins. Eleven key genes along with related transcription factors were identified including CTGF, POSTN, CORIN, FIGF, etc.

conclusionBioinformatics-based analyses reveal the targeted genes probably associated with cardiomyopathy, which provide clues for pharmacological therapies aiming at the targets.

Indexed as

TranscriptomeCardiomyopathy, DilatedComputational BiologyGene Expression ProfilingHumansBioinformaticsDilated cardiomyopathyHeart failureMicroarray

Identifiers

PMID30115125
PMCPMC6094872
OpenAlexW2886216714

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.