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Published in: Journal of Translational Medicine 1/2019

Open Access 01-12-2019 | Stroke | Research

Bioinformatic gene analysis for potential biomarkers and therapeutic targets of atrial fibrillation-related stroke

Authors: Rongjun Zou, Dingwen Zhang, Lei Lv, Wanting Shi, Zijiao Song, Bin Yi, Bingjia Lai, Qian Chen, Songran Yang, Ping Hua

Published in: Journal of Translational Medicine | Issue 1/2019

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Abstract

Background

Atrial fibrillation (AF) is one of the most prevalent sustained arrhythmias, however, epidemiological data may understate its actual prevalence. Meanwhile, AF is considered to be a major cause of ischemic strokes due to irregular heart-rhythm, coexisting chronic vascular inflammation, and renal insufficiency, and blood stasis. We studied co-expressed genes to understand relationships between atrial fibrillation (AF) and stroke and reveal potential biomarkers and therapeutic targets of AF-related stroke.

Methods

AF-and stroke-related differentially expressed genes (DEGs) were identified via bioinformatic analysis Gene Expression Omnibus (GEO) datasets GSE79768 and GSE58294, respectively. Subsequently, extensive target prediction and network analyses methods were used to assess protein–protein interaction (PPI) networks, Gene Ontology (GO) terms and pathway enrichment for DEGs, and co-expressed DEGs coupled with corresponding predicted miRNAs involved in AF and stroke were assessed as well.

Results

We identified 489, 265, 518, and 592 DEGs in left atrial specimens and cardioembolic stroke blood samples at < 3, 5, and 24 h, respectively. LRRK2, CALM1, CXCR4, TLR4, CTNNB1, and CXCR2 may be implicated in AF and the hub-genes of CD19, FGF9, SOX9, GNGT1, and NOG may be associated with stroke. Finally, co-expressed DEGs of ZNF566, PDZK1IP1, ZFHX3, and PITX2 coupled with corresponding predicted miRNAs, especially miR-27a-3p, miR-27b-3p, and miR-494-3p may be significantly associated with AF-related stroke.

Conclusion

AF and stroke are related and ZNF566, PDZK1IP1, ZFHX3, and PITX2 genes are significantly associated with novel biomarkers involved in AF-related stroke.
Appendix
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Metadata
Title
Bioinformatic gene analysis for potential biomarkers and therapeutic targets of atrial fibrillation-related stroke
Authors
Rongjun Zou
Dingwen Zhang
Lei Lv
Wanting Shi
Zijiao Song
Bin Yi
Bingjia Lai
Qian Chen
Songran Yang
Ping Hua
Publication date
01-12-2019
Publisher
BioMed Central
Published in
Journal of Translational Medicine / Issue 1/2019
Electronic ISSN: 1479-5876
DOI
https://doi.org/10.1186/s12967-019-1790-x

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