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

• Published in: Journal of translational medicine Vol. 17; no. 1; p. 45
• Main Authors: Zou, Rongjun, Zhang, Dingwen, Lv, Lei, Shi, Wanting, Song, Zijiao, Yi, Bin, Lai, Bingjia, Chen, Qian, Yang, Songran, Hua, Ping
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 13.02.2019; BioMed Central; BMC
• Subjects: Age; Atrial fibrillation; Atrial Fibrillation - complications; Atrial Fibrillation - genetics; Atrial Fibrillation - therapy; Atrial fibrillation-related stroke; Biochemistry; Biological markers; Biomarkers; Biomarkers - metabolism; Blood; Cardiac arrhythmia; CD19 antigen; Cluster Analysis; Computational biology; Computational Biology - methods; CXCR2 protein; CXCR4 protein; Diagnosis; Embolisms; Epidemiology; Fibrillation; Fibroblast growth factor receptor 9; Fibroblast growth factors; Gene analysis; Gene expression; Gene Expression Profiling; Gene Ontology; Gene Regulatory Networks; Genes; Genetic aspects; Genomes; Health aspects; Heart; Humans; Inflammation; Ischemia; Kidney failure; LRRK2 protein; MicroRNA; MicroRNAs; MicroRNAs - genetics; MicroRNAs - metabolism; Molecular Targeted Therapy; Mortality; Novels; Protein Interaction Maps - genetics; Protein-protein interactions; Proteins; Renal insufficiency; Risk factors; Rivaroxaban; Signal Transduction - genetics; Sox9 protein; Stroke; Stroke - genetics; Stroke - therapy; Therapeutic applications; TLR4 protein; Toll-like receptors; Biomarkers; Atrial fibrillation-related stroke; Gene analysis
• ISSN: 1479-5876; 1479-5876
• DOI: 10.1186/s12967-019-1790-x

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. 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. 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. AF and stroke are related and ZNF566, PDZK1IP1, ZFHX3, and PITX2 genes are significantly associated with novel biomarkers involved in AF-related stroke.