Evidence map›Paper›PMID 32602534›Full record

ArticleBioscience reports2020

Weighted gene co-expression network analysis to define pivotal modules and genes in diabetic heart failure.

Weiwei Liang, FangFang Sun

Open access · goldAbstract read
In one paragraph

Article in Bioscience reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.4field-weighted citation impact, top 40% 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

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
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  3. Heliyon · 2023
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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

2 authors at 2 institutions in 1 country.

Weiwei Liang *Department of Endocrinology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, P. R. China.
FangFang Sun *Department of Colorectal Surgery and Oncology, Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, The Second Affiliated Hospital, Cancer Institute, Zhejiang University School of Medicine, Hangzhou, P. R. China.
Second Affiliated Hospital of Zhejiang University · CNZhejiang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This research was carried out to reveal specific hub genes involved in diabetic heart failure, as well as remarkable pathways that hub genes locate. The GSE26887 dataset from the GEO website was downloaded. The gene co-expression network was generated and central modules were analyzed to identify key genes using the WGCNA method. Functional analyses were conducted on genes of the clinical interest modules via Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene ontology (GO) enrichment, associated with protein-protein interaction (PPI) network construction in a sequence. Centrality parameters of the PPI network were determined using the CentiScape plugin in Cytoscape. Key genes, defined as genes in the ≥95% percentile of the degree distribution of significantly perturbed networks, were identified. Twenty gene co-expression modules were detected by WGCNA analysis. The module marked in light yellow exhibited the most significant association with diabetes (P=0.08). Genes involved in this module were primarily located in immune response, plasma membrane and receptor binding, as shown by the GO analysis. These genes were primarily assembled in endocytosis and phagosomes for KEGG pathway enrichment. Three key genes, STK39, HLA-DPB1 and RAB5C, which may be key genes for diabetic heart failure, were identified. To our knowledge, our study is the first to have constructed the co-expression network involved in diabetic heart failure using the WGCNA method. The results of the present study have provided better understanding the molecular mechanism of diabetic heart failure.

Indexed as

Gene Regulatory NetworksBiopsyComputational BiologyDatasets as TopicDiabetes ComplicationsGene Expression ProfilingHeart FailureHLA-DP beta-ChainsHumansMyocardiumProtein Interaction MapsProtein Serine-Threonine Kinasesrab5 GTP-Binding ProteinsHLA-DPB1 antigenHLA-DP beta-ChainsProtein Serine-Threonine KinasesRAB5C protein, humanrab5 GTP-Binding ProteinsSTK39 protein, humanDiabetesDiabetic Heart FailureWGCNA

Identifiers

PMID32602534
PMCPMC7340867
OpenAlexW3038852268

What OpenQuestion holds

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LicenceCC BY
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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.