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Bioinformatic gene analysis for potential biomarkers and therapeutic targets of atrial fibrillation-related stroke
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, an...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6375208/ https://www.ncbi.nlm.nih.gov/pubmed/30760287 http://dx.doi.org/10.1186/s12967-019-1790-x |
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author | Zou, Rongjun Zhang, Dingwen Lv, Lei Shi, Wanting Song, Zijiao Yi, Bin Lai, Bingjia Chen, Qian Yang, Songran Hua, Ping |
author_facet | Zou, Rongjun Zhang, Dingwen Lv, Lei Shi, Wanting Song, Zijiao Yi, Bin Lai, Bingjia Chen, Qian Yang, Songran Hua, Ping |
author_sort | Zou, Rongjun |
collection | PubMed |
description | 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12967-019-1790-x) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6375208 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-63752082019-02-26 Bioinformatic gene analysis for potential biomarkers and therapeutic targets of atrial fibrillation-related stroke Zou, Rongjun Zhang, Dingwen Lv, Lei Shi, Wanting Song, Zijiao Yi, Bin Lai, Bingjia Chen, Qian Yang, Songran Hua, Ping J Transl Med Research 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12967-019-1790-x) contains supplementary material, which is available to authorized users. BioMed Central 2019-02-13 /pmc/articles/PMC6375208/ /pubmed/30760287 http://dx.doi.org/10.1186/s12967-019-1790-x Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Zou, Rongjun Zhang, Dingwen Lv, Lei Shi, Wanting Song, Zijiao Yi, Bin Lai, Bingjia Chen, Qian Yang, Songran Hua, Ping Bioinformatic gene analysis for potential biomarkers and therapeutic targets of atrial fibrillation-related stroke |
title | Bioinformatic gene analysis for potential biomarkers and therapeutic targets of atrial fibrillation-related stroke |
title_full | Bioinformatic gene analysis for potential biomarkers and therapeutic targets of atrial fibrillation-related stroke |
title_fullStr | Bioinformatic gene analysis for potential biomarkers and therapeutic targets of atrial fibrillation-related stroke |
title_full_unstemmed | Bioinformatic gene analysis for potential biomarkers and therapeutic targets of atrial fibrillation-related stroke |
title_short | Bioinformatic gene analysis for potential biomarkers and therapeutic targets of atrial fibrillation-related stroke |
title_sort | bioinformatic gene analysis for potential biomarkers and therapeutic targets of atrial fibrillation-related stroke |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6375208/ https://www.ncbi.nlm.nih.gov/pubmed/30760287 http://dx.doi.org/10.1186/s12967-019-1790-x |
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