C1QC, VSIG4, and CFD as Potential Peripheral Blood Biomarkers in Atrial Fibrillation-Related Cardioembolic Stroke

Abstract

Atrial fibrillation (AF) is a major risk factor for ischemic stroke. We aimed to identify novel potential biomarkers with diagnostic value in patients with atrial fibrillation-related cardioembolic stroke (AF-CE).Publicly available gene expression profiles related to AF, cardioembolic stroke (CE), and large artery atherosclerosis (LAA) were downloaded from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were identified and then functionally annotated. The support vector machine recursive feature elimination (SVM-RFE) and least absolute shrinkage and selection operator (LASSO) regression analysis were conducted to identify potential diagnostic AF-CE biomarkers. Furthermore, the results were validated by using external data sets, and discriminability was measured by the area under the ROC curve (AUC). In order to verify the predictive results, the blood samples of 13 healthy controls, 20 patients with CE, and 20 patients with LAA stroke were acquired for RT-qPCR, and the correlation between biomarkers and clinical features was further explored. Lastly, a nomogram and the companion website were developed to predict the CE-risk rate. Three feature genes (C1QC, VSIG4, and CFD) were selected and validated in the training and the external datasets. The qRT-PCR evaluation showed that the levels of blood biomarkers (C1QC, VSIG4, and CFD) in patients with AF-CE can be used to differentiate patients with AF-CE from normal controls ( P < 0.05 ) and can effectively discriminate AF-CE from LAA stroke ( P < 0.05 ). Immune cell infiltration analysis revealed that three feature genes were correlated with immune system such as neutrophils. Clinical impact curve, calibration curves, ROC, and DCAs of the nomogram indicate that the nomogram had good performance. Our findings showed that C1QC, VSIG4, and CFD can potentially serve as diagnostic blood biomarkers of AF-CE; novel nomogram and the companion website can help clinicians to identify high-risk individuals, thus helping to guide treatment decisions for stroke patients.

Screening and Analysis of Aortic Dissection Based on Bioinformatics Methods Related Key Genes and Early Prevention and Treatment

“…The Benjamini and Hochberg false discovery rate methods were used to correct for false positives. Set the statistically significant difference threshold to |log2FC|>1 and p<0.01 as the statistical significance threshold level for the DEGs sample [18,19] .…”

Comparison of left atrial and left atrial appendage mechanics in the recurrence of atrial fibrillation after radiofrequency catheter ablation

“…1 AF is not only closely related to the poor prognosis of diseases such as heart failure or acute myocardial infarction, but also an important risk factor for thromboembolic stroke. [2][3][4][5] The main purpose of the treatment of AF is to achieve long-term maintenance of sinus rhythm. 6 At present, radiofrequency catheter ablation (RFCA) has become the main treatment method for patients with paroxysmal and persistent AF.…”

“…According to statistics, the number of patients with atrial fibrillation (AF) worldwide has increased significantly in the past 20 years, with a growth rate of up to 33%, accounting for .51% of the global population, and its incidence rate and prevalence rate continue to rise, which will bring huge burden to social economy and health 1 . AF is not only closely related to the poor prognosis of diseases such as heart failure or acute myocardial infarction, but also an important risk factor for thromboembolic stroke 2–5 . The main purpose of the treatment of AF is to achieve long‐term maintenance of sinus rhythm 6 .…”