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

Atrial fibrillation (AF) is one of the most prevalent sustained arrhythmias, having an age-adjusted hospitalization incidence of 1–4% of the general population and an prevalence rising of > 13% for those older than 80-years-of-age [1, 2]. However, epidemiological data may understate its actual prevalence, because 40% of patients are asymptomatic and remain undiagnosed with subclinical AF [3]. There is also evidence that patients with AF have significantly increased cardiovascular-related morbidity, given its association with atrial and ventricular mechanical or electrical failure, structural and hemodynamic alterations, and thromboembolic events [3].

Stroke is the leading cause of disability and death and has an estimated incidence of 3.73 (95% CI 3.51–3.96) per 1000 person-years among black- and white- adults in an atherosclerosis risk in communities (ARIC) cohort [4]. Furthermore, global increases in stroke prevalence plus stroke-related disability and mortality associated with aging will increase [5, 6]. Thus, we may not now know the actual true burden of stroke due to limits in brain imaging identification in < 10 mm small hypointense areas and silent infarctions for 28% of those patients older than 65-years-of-age [7]. AF is commonly classified as paroxysmal, persistent or permanent, or new onset arrhythmia basing on the present continuous time, which mainly included that paroxysmal AF was self-terminates within 7 days, while persistent AF was lasts longer than 7 days or needs cardioversion, and usually has lasted for 3 months [8]. As we all kwon, AF is considering to be a major cause of ischemic strokes due to irregular heart-rhythm, coexisting chronic vascular inflammation, and renal insufficiency, and blood stasis. According to Rivaroxaban Once Daily Oral Direct Factor Xa Inhibition Compared With Vitamin K Antagonism for Prevention of Stroke and Embolism Trial in Atrial Fibrillation (ROCKET-AF) trial study, Steinberg et al. [9] suggested that the paroxysmal AF patients carrying a lower adjusted rate of stroke or systemic embolism (adjusted HR: 0.78, 95% CI 0.61–0.99, P = 0.045), all-cause mortality (adjusted HR: 0.79, 95% CI 0.67–0.94, P = 0.006), and the composite of stroke or systemic embolism or death (adjusted HR: 0.82, 95% CI 0.71–0.94, P = 0.005) than persistent AF patients after adjusted efficacy and safety outcomes. According to the Oxford vascular study (OXVASC), nearly 43.9% of ischemic strokes were associated with AF among patients 80 years-of-age or older who had a threefold increase in AF in the past 3 decades [10]. However, this assumption has been challenged by the atrial fibrillation reduction atrial pacing trial (ASSERT) which identified a temporal association between subclinical AF and stroke risk among patients with implantable pacemakers and defibrillators. They reported that only 8% and 16% of patients had an association between pre-detected and post-detected AF within months of stroke or systemic embolism, respectively [11]. Of note, AF is often intermittent and asymptomatic, and presents as an electromechanical disassociation of atrial fibrillation. Clinically, current stroke risk scores and traditional diagnosis with an electrocardiogram are practical, while the limitation of predict stroke risk accurately in individual AF patients was significantly identified, especially in persistent AF which carrying a higher risk of stroke or systemic embolism and all-cause mortality [12]. In this study, we identified co-expressed differentially expressed genes (co-DEGs) of persistent AF and stroke and elucidated molecular mechanisms and pathology of AF-related DEGs (AF-DEGs) and stroke-related DEGs (stroke-DEGs). Finally, we provide a bioinformatic analysis of DEGs and predicted microRNAs (miRNAs) for AF patients prone to stroke.

Predicting AF is needed for stroke prevention but 30% of patients have no signs of AF despite months of continuous cardiac rhythm monitoring. Thus, cardiovascular malignant events may be correlated with irregular and infrequent cardiovascular incidents as well as limitations in electromechanical indices that should predict problems with atrial contractility [7, 11, 12]. Estimating markers and associations between atrial dysfunction and embolic stroke are thus of interest and may be novel therapeutic targets for primary care. The inflammatory and immune response, and ion channel and transportation are significantly associated with AF recurrence and maintenance, as well as the stroke occurrence. Several hub-genes involved directly or indirectly that regulate the nervous system were found among AF-DEGs. Visanji’s group compared resting electrocardiograms of LRRK2-associated Parkinson’s disease (PD) patients, nonmanifesting carriers, noncarriers, and idiopathic PD patients to investigate heart rate variability in LRRK2-associated PD [24]. There is evidence that LRRK2 may act as a biofunctional mediator to correlate heart rate variability and PD [24]. In a molecular mechanistic study, the neural protective role for regulating mitochondrial complex I function and oxidative stress in ischemia/reperfusion was identified [25, 26]. According gene–gene interaction analysis, Timasheva’s group illustrated that the loci of CXCR2 is significantly associated with stroke development in patients with hypertension [26]. In addition, CXCR2 antagonism attenuated neurological deficits and infarct volumes via decreased cerebral neutrophil infiltration and peripheral neutrophilia in a hyperlipidemic ApoE^−/− mice stroke model [27]. CALM1 is recognized as a major regulator of cardiac ion-current expression and calcium handling, and a key determinant of cardiac electrical function [28]. Also, specific risk alleles for CALM1 were identified as being associated with increased risk of stroke in studies of coronary heart disease [29]. Thus, there may be a relationship between cardiovascular and nervous system disease and they may arise from loci mutations or gene variants.

Additionally, PITX2, of the pituitary homeobox (Pitx) family, has a critical role in organ morphogenesis and AF maintenance which is related to short stature homeobox 2 (Shox2) [30]. Pitx2 is expressed in the LA and the pulmonary vein, which is considered a substrate and trigger for AF maintenance respectively. However, several experimental data indicate a trend that PITX2 gene expression is silenced during aging in LA samples, suggesting genetic evidence for gene silencing for increased AF susceptibility [30, 31]. Then, miRNAs function analysis and a genomic approach showed that miR-17-92 and miR-106b-25 were associated with Pitx2 expression regulation and are implicated in human AF susceptibility [31]. To reveal relationships between genetic variants and the risk of ischemic stroke, Malik’s group studied PITX2 and ZFHX3 genes and found a significant association with cardioembolic stroke (CE) in a meta-analysis [31, 32]. Similarly, in a genome-wide association study using clinical samples from paroxysmal or persistent AF patients, ZFHX3 was significantly associated with LA enlargement and persistent AF and subsequently with ablation outcomes [33]. Correspondingly, Choi’s group found a significant association between top susceptibility loci (chromosomes 4q25 [PITX2], 16q22 [ZFHX3]) and AF recurrence after ablation in a Korean population, despite no top single nucleotide polymorphisms (SNPs) that predicted clinical recurrence after catheter ablation [34]. A regulatory role for PDZK1IP1 (MAP17) in reactive oxygen species production has been confirmed and is considered as a marker for increased oxidative stress and may be a new therapeutic target [35]. and recent research suggests a potential role for ions channels regulation, linked to the Na⁺/H⁺ exchanger 3 and A-kinase anchor protein 2/protein kinase A pathway [36]. However, ZNF566 plays a central role in heart regeneration and repair, and endocardial and epicardial epithelial to mesenchymal transitions [37, 38].

Research suggests potential beneficial effects of miRNA transformation therapy vectored by adenovirus, plasmid, and lentivirus for AF therapy [39]. We found that miR-27a-3p, miR-27b-3p, and miR-494-3p were co-DEGs and may be potential biomarkers of AF-related stroke. Interestingly, Vegter’s group compared heart failure-specific circulating miRNAs in 114 heart failure patients with/without different manifestations of atherosclerotic disease, and reported that miR-18a-5p, miR-27a-3p, miR-199a-3p, miR-223-3p and miR-652-3p abundance were associated with atherosclerosis and cardiovascular-related rehospitalizations [40]. Similarly, Marques and colleagues found that several miRNAs involved in let-7b-5p, let-7c-5p, let-7e-5p, miR-122-5p, and miR-21-5p, and absorbed miR-16-5p, miR-17-5p, miR-27a-3p, and miR-27b-3p are target pathways related to heart failure and considered to be potential biomarkers [41]. In contrast, expression of miR-27b-3p is significantly related to embryonic myogenesis and protein synthesis but miR-494-3p expression is associated with cerebral blood supply and functional recovery in a rat stroke model according to cerebral cortical miRNA profile changes [42, 43].

The hub-genes of LRRK2, CALM1, CXCR4, TLR4, CTNNB1, CXCR2, KIT, and IL1B may be associated with AF recurrence and maintenance and CD19, FGF9, SOX9, GNGT1, and NOG may be associated with stroke. Additionally, co-DEGs of ZNF566, PDZK1IP1, ZFHX3, and PITX2 link AF and stroke. Finally, the top 5 miRNAs for each co-DEGs may be potential biomarkers or therapeutic targets for AF-stroke, especially miR-27a-3p, miR-27b-3p, and miR-494-3p. Thus, there is an association between AF and stroke, and expression of ZNF566, PDZK1IP1, ZFHX3, and PITX2 genes favor AF-related stroke.

Several limitations still detected in our study. First, this study is a microarray analysis that all the results based on gene expression value. However, owing to gene expression may be not directly equivalent to protein expression, the biomarkers of this study should consider as gene, not in protein. In application, assay of PCR and microarray chip may be better for accessing the risk of AF-related stroke. Second, validation should be carried out both in vitro, in vivo and clinical trials. However, as of now the techniques of in vivo or in vitro models for AF and stroke was immature. And the larger, prospective clinical studies may be better to validate our results to some extent.