Atrial Fibrillation

Chung, Mina K.; Refaat, Marwan M.; Shen, Win‐Kuang; Kutyifa, Valentina; Cha, Yong‐Mei; Biase, Luigi Di; Baranchuk, Adrián; Lampert, Rachel; Natale, Andrea; Fisher, John D.; Lakkireddy, Dhanunjaya

doi:10.1016/j.jacc.2020.02.025

Cited by 172 publications

(60 citation statements)

References 146 publications

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“…Many of these changes corroborate the findings of previous clinical and electrophysiology studies of AF. On the one hand, inflammatory disease, cardiovascular comorbidities, and increased serum inflammatory biomarkers have been associated with an increased risk of AF (Chung et al, 2020 ; Li and Brundel, 2020 ), which supports the idea that inflammation and oxidative stress contribute to AF susceptibility. On the other hand, GWAS studies and gain and loss of function studies have identified various genes related to ion channel expression that are associated with AF persistence (Roselli et al, 2020 ).…”

Section: Introductionmentioning

confidence: 78%

“…The currently estimated global prevalence of AF is between 2 and 4% (Hindricks et al, 2020;Virani et al, 2020), and by the middle of the 21st century, AF will be diagnosed in an estimated 72 million individuals in Asia, 16 million in America, and 14 million in Europe (Kornej et al, 2020). Well-known risk factors contribute to AF susceptibility, including aging, male sex, alcohol consumption, obesity, and smoking as well as comorbidities such as heart failure, diabetes, obstructive sleep apnea, and inflammatory disease (Chung et al, 2020). AF is also heritable (Weng et al, 2017), and two large-scale genome-wide association studies (GWAS) identified more than 100 loci associated with AF (Nielsen et al, 2018;Roselli et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

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Identifying ceRNA Networks Associated With the Susceptibility and Persistence of Atrial Fibrillation Through Weighted Gene Co-Expression Network Analysis

Liu

Bai

et al. 2021

Front. Genet.

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Background: Atrial fibrillation (AF) is the most common arrhythmia. We aimed to construct competing endogenous RNA (ceRNA) networks associated with the susceptibility and persistence of AF by applying the weighted gene co-expression network analysis (WGCNA) and prioritize key genes using the random walk with restart on multiplex networks (RWR-M) algorithm.Methods: RNA sequencing results from 235 left atrial appendage samples were downloaded from the GEO database. The top 5,000 lncRNAs/mRNAs with the highest variance were used to construct a gene co-expression network using the WGCNA method. AF susceptibility- or persistence-associated modules were identified by correlating the module eigengene with the atrial rhythm phenotype. Using a module-specific manner, ceRNA pairs of lncRNA–mRNA were predicted. The RWR-M algorithm was applied to calculate the proximity between lncRNAs and known AF protein-coding genes. Random forest classifiers, based on the expression value of key lncRNA-associated ceRNA pairs, were constructed and validated against an independent data set.Results: From the 21 identified modules, magenta and tan modules were associated with AF susceptibility, whereas turquoise and yellow modules were associated with AF persistence. ceRNA networks in magenta and tan modules were primarily involved in the inflammatory process, whereas ceRNA networks in turquoise and yellow modules were primarily associated with electrical remodeling. A total of 106 previously identified AF-associated protein-coding genes were found in the ceRNA networks, including 16 that were previously implicated in the genome-wide association study. Myocardial infarction–associated transcript (MIAT) and LINC00964 were prioritized as key lncRNAs through RWR-M. The classifiers based on their associated ceRNA pairs were able to distinguish AF from sinus rhythm with respective AUC values of 0.810 and 0.940 in the training set and 0.870 and 0.922 in the independent test set. The AF-related single-nucleotide polymorphism rs35006907 was found in the intronic region of LINC00964 and negatively regulated the LINC00964 expression.Conclusion: Our study constructed AF susceptibility- and persistence-associated ceRNA networks, linked genetics with epigenetics, identified MIAT and LINC00964 as key lncRNAs, and constructed random forest classifiers based on their associated ceRNA pairs. These results will help us to better understand the mechanisms underlying AF from the ceRNA perspective and provide candidate therapeutic and diagnostic tools.

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Section: Introductionmentioning

confidence: 78%

Section: Introductionmentioning

confidence: 99%

Identifying ceRNA Networks Associated With the Susceptibility and Persistence of Atrial Fibrillation Through Weighted Gene Co-Expression Network Analysis

Liu

Bai

et al. 2021

Front. Genet.

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“…Atrial fibrillation (AF), on the other hand, is a major arrhythmia defined as fast and disorganized electrical excitation of the atria affecting cardiac function (8,9). AF is considered as a risk factor for stroke, as more than 15% of strokes in the US are due to AF (8).…”

Section: Introductionmentioning

confidence: 99%

“…As a consequence, AF is correlated with increased morbidity and mortality (8). Current treatments of AF target stroke prevention, rate and rhythm control (8,9). Many research studies proposed gene therapy as a method to reduce the expression of abnormal genes related to the pathogenesis of AF such as ion channels, gap junctions, parasympathetic nervous system, and fibrosis (11).…”

Section: Introductionmentioning

confidence: 99%

Genomic and Proteomic Study of the Inflammatory Pathway in Patients With Atrial Fibrillation and Cardiometabolic Syndrome

Itani

Jaffa

Elias

et al. 2020

Front. Cardiovasc. Med.

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Atrial fibrillation (AF) and cardiometabolic syndrome (CMS) have been linked to inflammation and fibrosis. However, it is still unknown which inflammatory cytokines contribute to the pathogenesis of AF. Furthermore, cardiometabolic syndrome (CMS) risk factors such as obesity, hypertension, insulin resistance/glucose intolerance are also associated with inflammation and increased level of cytokines and adipokines. We hypothesized that the inflammatory immune response is exacerbated in patients with both AF and CMS compared to either AF or CMS alone. We investigated inflammatory cytokines and fibrotic markers as well as cytokine genetic profiles in patients with lone AF and CMS. CMS, lone AF patients, patients with both lone AF and CMS, and control patients were recruited. Genetic polymorphisms in inflammatory and fibrotic markers were assessed. Serum levels of connective tissue growth factor (CTGF) were tested along with other inflammatory markers including platelet-to-lymphocyte ratio (PLR), monocyte-to-HDL ratio (MHR) in three groups of AF+CMS, AF, and CMS patients. There was a trend in the CTGF levels for statistical significance between the AF and AF+CMS group (P = 0.084). Genotyping showed high percentages of patients in all groups with high secretor genotypes of Interleukin-6 (IL-6) (P = 0.037). Genotyping of IFN-γ and IL-10 at high level showed an increase in expression in the AF + CMS group compared to AF and CMS alone suggesting an imbalance between the inflammatory and anti-inflammatory cytokines which is exacerbated by AF. Serum cytokine inflammatory cytokine levels showed that IL-4, IL-5, IL-10, IL-17F, and IL-22 were significant between the AF, AF+CMS, and CMS patients. Combination of both CMS and AF may be associated with a higher degree of inflammation than what is seen in either CMS or AF alone. Thus, the identification of a biomarker capable of identifying metabolic syndrome associated with disease will help in identification of a therapeutic target in treating this devastating disease.

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“…1 AF is a progressive condition that involves medical management such as rate control, rhythm control, and anti-coagulation, as well as lifestyle change and self-management behaviors. 2,3 AF is also associated with significant psychologic distress, particularly for patients who are symptomatic, perceive AF to be dangerous, or have low AF health literacy 4 ; research to date suggests high rates of anxiety and depression, 35% and 20%, respectively, in AF samples. 5 Daily management of AF involves adherence to medical therapies (e.g rate/rhythm control, stroke prophylaxis), management of comorbidities, abstinence from smoking, avoiding alcohol consumption, and sustaining regular physical activity.…”

Section: Introductionmentioning

confidence: 99%

Measurement of Patient Confidence in Self-Management of Atrial Fibrillation: Initial Validation of The Confidence in Atrial fibriLlation Management (CALM) Scale

Tripp

Gehi

Rosman

et al. 2020

Preprint

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Background: The patient experience of atrial fibrillation (AF) involves several daily self-care behaviors and ongoing confidence to manage their condition. Currently, no standardized self-report measure of AF patient confidence exists. The purpose of this study is to establish the reliability and validity of a newly developed confidence in AF management measure. Methods: This study provides preliminary analysis of the Confidence in Atrial FibriLlation Management (CALM) scale, which was rationally developed to measure patient confidence related to self-management of AF. The scale was provided to a sample of AF patients N=120, (59% male) electronically through a patient education platform. Principle components analysis (PCA) and Cronbach’s alpha were employed to provide preliminary assessment of the validity and reliability of the measure. Results: PCA identified a four-factor solution. Internal consistency of the CALM was considered excellent with Cronbach’s α = .910. Additional PCA confirmed the value of a single factor solution to produce a total confidence score for improved utility and ease of clinical interpretation. Conclusions: Initial assessment of a novel scale measuring patient confidence in managing AF provided promising reliability and validity. Patient confidence in self-management of AF may prove useful as a key marker and endpoint of the patient experience beyond QOL.

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Atrial Fibrillation

Cited by 172 publications

References 146 publications

Identifying ceRNA Networks Associated With the Susceptibility and Persistence of Atrial Fibrillation Through Weighted Gene Co-Expression Network Analysis

Identifying ceRNA Networks Associated With the Susceptibility and Persistence of Atrial Fibrillation Through Weighted Gene Co-Expression Network Analysis

Genomic and Proteomic Study of the Inflammatory Pathway in Patients With Atrial Fibrillation and Cardiometabolic Syndrome

Measurement of Patient Confidence in Self-Management of Atrial Fibrillation: Initial Validation of The Confidence in Atrial fibriLlation Management (CALM) Scale

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