Literature DB >> 34514752

Bioinformatic analysis for potential biological processes and key targets of heart failure-related stroke.

Chiyu Liu1,2,3, Sixu Chen1,2,3, Haifeng Zhang1,2, Yangxin Chen1,2, Qingyuan Gao1,2, Zhiteng Chen1,2, Zhaoyu Liu4, Jingfeng Wang5,6.   

Abstract

This study aimed to uncover underlying mechanisms and promising intervention targets of heart failure (HF)-related stroke. HF-related dataset GSE42955 and stroke-related dataset GSE58294 were obtained from the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was conducted to identify key modules and hub genes. Gene Ontology (GO) and pathway enrichment analyses were performed on genes in the key modules. Genes in HF- and stroke-related key modules were intersected to obtain common genes for HF-related stroke, which were further intersected with hub genes of stroke-related key modules to obtain key genes in HF-related stroke. Key genes were functionally annotated through GO in the Reactome and Cytoscape databases. Finally, key genes were validated in these two datasets and other datasets. HF- and stroke-related datasets each identified two key modules. Functional enrichment analysis indicated that protein ubiquitination, Wnt signaling, and exosomes were involved in both HF- and stroke-related key modules. Additionally, ten hub genes were identified in stroke-related key modules and 155 genes were identified as common genes in HF-related stroke. OTU deubiquitinase with linear linkage specificity(OTULIN) and nuclear factor interleukin 3-regulated(NFIL3) were determined to be the key genes in HF-related stroke. Through functional annotation, OTULIN was involved in protein ubiquitination and Wnt signaling, and NFIL3 was involved in DNA binding and transcription. Importantly, OTULIN and NFIL3 were also validated to be differentially expressed in all HF and stroke groups. Protein ubiquitination, Wnt signaling, and exosomes were involved in HF-related stroke. OTULIN and NFIL3 may play a key role in HF-related stroke through regulating these processes, and thus serve as promising intervention targets.

Entities:  

Keywords:  Bioinformatics; Cardioembolic stroke; Heart failure; Weighted gene co-expression network analysis (WGCNA)

Mesh:

Substances:

Year:  2021        PMID: 34514752      PMCID: PMC8435344          DOI: 10.1631/jzus.B2000544

Source DB:  PubMed          Journal:  J Zhejiang Univ Sci B        ISSN: 1673-1581            Impact factor:   3.066


  64 in total

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4.  Increased stroke risk in atrial fibrillation patients with heart failure: does ejection fraction matter?

Authors:  Dipak Kotecha; Amitava Banerjee; Gregory Y H Lip
Journal:  Stroke       Date:  2015-01-27       Impact factor: 7.914

5.  Secular trends in ischemic stroke subtypes and stroke risk factors.

Authors:  Chrysi Bogiatzi; Daniel G Hackam; A Ian McLeod; J David Spence
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Review 6.  Oral anticoagulants versus antiplatelet therapy for preventing stroke in patients with non-valvular atrial fibrillation and no history of stroke or transient ischemic attacks.

Authors:  M I Aguilar; R Hart; L A Pearce
Journal:  Cochrane Database Syst Rev       Date:  2007-07-18

7.  Bioinformatics Analysis of Gene Expression Profiles of Sex Differences in Ischemic Stroke.

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Journal:  Biomed Res Int       Date:  2019-04-30       Impact factor: 3.411

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Journal:  PLoS Comput Biol       Date:  2014-07-24       Impact factor: 4.475

9.  The linear ubiquitin-specific deubiquitinase gumby regulates angiogenesis.

Authors:  Elena Rivkin; Stephanie M Almeida; Derek F Ceccarelli; Yu-Chi Juang; Teresa A MacLean; Tharan Srikumar; Hao Huang; Wade H Dunham; Ryutaro Fukumura; Gang Xie; Yoichi Gondo; Brian Raught; Anne-Claude Gingras; Frank Sicheri; Sabine P Cordes
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10.  Potential biomarkers of acute myocardial infarction based on weighted gene co-expression network analysis.

Authors:  Zhihua Liu; Chenguang Ma; Junhua Gu; Ming Yu
Journal:  Biomed Eng Online       Date:  2019-01-25       Impact factor: 2.819

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  2 in total

Review 1.  Research and application advances in rehabilitation assessment of stroke.

Authors:  Kezhou Liu; Mengjie Yin; Zhengting Cai
Journal:  J Zhejiang Univ Sci B       Date:  2022-08-15       Impact factor: 5.552

2.  Exosomes released by melanocytes modulate fibroblasts to promote keloid formation: a pilot study.

Authors:  Zeren Shen; Jinjin Shao; Jiaqi Sun; Jinghong Xu
Journal:  J Zhejiang Univ Sci B       Date:  2022-08-15       Impact factor: 5.552

  2 in total

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