Deep learning of left atrial structure and function provides link to atrial fibrillation risk.

Increased left atrial volume and decreased left atrial function have long been associated with atrial fibrillation. The availability of large-scale cardiac magnetic resonance imaging data paired with genetic data provides a unique opportunity to assess the genetic contributions to left atrial structure and function, and understand their relationship with risk for atrial fibrillation. Here, we use deep learning and surface reconstruction models to measure left atrial minimum volume, maximum volume, stroke volume, and emptying fraction in 40,558 UK Biobank participants. In a genome-wide association study of 35,049 participants without pre-existing cardiovascular disease, we identify 20 common genetic loci associated with left atrial structure and function. We find that polygenic contributions to increased left atrial volume are associated with atrial fibrillation and its downstream consequences, including stroke. Through Mendelian randomization, we find evidence supporting a causal role for left atrial enlargement and dysfunction on atrial fibrillation risk.

Deciphering the Role of microRNAs: Unveiling Clinical Biomarkers and Therapeutic Avenues in Atrial Fibrillation and Associated Stroke-A Systematic Review.

MicroRNAs (miRNAs) are small non-coding RNA molecules that regulate gene expression by binding to target messenger RNAs (mRNAs). miRNAs have been implicated in a variety of cardiovascular and neurological diseases, such as myocardial infarction, cardiomyopathies of various geneses, rhythmological diseases, neurodegenerative illnesses and strokes. Numerous studies have focused on the expression of miRNA patterns with respect to atrial fibrillation (AF) or acute ischemic stroke (AIS) However, only a few studies have addressed the expression pattern of miRNAs in patients with AF and AIS in order to provide not only preventive information but also to identify therapeutic potentials. Therefore, the aim of this review is to summarize 18 existing manuscripts that have dealt with this combined topic of AF and associated AIS in detail and to shed light on the most frequently mentioned miRNAs-1, -19, -21, -145 and -146 with regard to their molecular mechanisms and targets on both the heart and the brain. From this, possible diagnostic and therapeutic consequences for the future could be derived.

Co-expression and interaction network analysis identifies neutrophil-related genes as the core mediator of atrial fibrillation.

Atrial fibrillation (AF) is the most common cardiac arrhythmia and can cause serious complications. Several studies have shown that neutrophils may influence AF progression. However, the key genes related to neutrophils in AF have not been fully elucidated. Here, we downloaded microarray expression data of AF, and screened differentially expressed genes. Key immune cells in AF were identified by immune cell infiltration analysis. Weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) analysis were used to construct gene co-expression modules and identify hub genes. The association between key genes and neutrophils was then verified. Our results showed that 303 differentially expressed genes (DEGs) were screened in AF and sinus rhythm (SR), of which 194 were up-regulated and 109 were down-regulated. DEGs were mainly enriched in functions and pathways of neutrophil activation and biological functions of neutrophil activation-mediated immune response. Immune infiltration analysis revealed elevated levels of neutrophil infiltration in AF. WGCNA analysis revealed that the modules in dark red were associated with neutrophils. PPI analysis of these modules yielded 10 hub genes. S100A12, FCGR3B and S100A8 are 3 potential key genes related to neutrophils in AF, which are significantly positively correlated with neutrophils. These genes deserve further investigation and may be potential therapeutic targets for AF.

Evaluation of Toll-like Receptor 4 (TLR4) Involvement in Human Atrial Fibrillation: A Computational Study.

In the present study, we have explored the involvement of Toll-like Receptor 4 (TLR4) in atrial fibrillation (AF), by using a meta-analysis of publicly available human transcriptomic data. The meta-analysis revealed 565 upregulated and 267 downregulated differentially expressed genes associated with AF. Pathway enrichment analysis highlighted a significant overrepresentation in immune-related pathways for the upregulated genes. A significant overlap between AF differentially expressed genes and TLR4-modulated genes was also identified, suggesting the potential role of TLR4 in AF-related transcriptional changes. Additionally, the analysis of other Toll-like receptors (TLRs) revealed a significant association with TLR2 and TLR3 in AF-related gene expression patterns. The examination of MYD88 and TICAM1, genes associated with TLR4 signalling pathways, indicated a significant yet nonspecific enrichment of AF differentially expressed genes. In summary, this study offers novel insights into the molecular aspects of AF, suggesting a pathophysiological role of TLR4 and other TLRs. By targeting these specific receptors, new treatments might be designed to better manage AF, offering hope for improved outcomes in affected patients.

Transcriptomic analysis of epicardial adipose tissue reveals the potential crosstalk genes and immune relationship between type 2 diabetes mellitus and atrial fibrillation.

BACKGROUND: The complex relationship between atrial fibrillation (AF) and type 2 diabetes mellitus (T2DM) suggests a potential role for epicardial adipose tissue (EAT) that requires further investigation. This study employs bioinformatics and experimental approaches to clarify EAT's role in linking T2DM and AF, aiming to unravel the biological mechanisms involved. METHOD: Bioinformatics analysis initially identified common differentially expressed genes (DEGs) in EAT from T2DM and AF datasets. Pathway enrichment and network analyses were then performed to determine the biological significance and network connections of these DEGs. Hub genes were identified through six CytoHubba algorithms and subsequently validated biologically, with further in-depth analyses confirming their roles and interactions. Experimentally, db/db mice were utilized to establish a T2DM model. AF induction was executed via programmed transesophageal electrical stimulation and burst pacing, focusing on comparing the incidence and duration of AF. Frozen sections and Hematoxylin and Eosin (H&E) staining illuminated the structures of the heart and EAT. Moreover, quantitative PCR (qPCR) measured the expression of hub genes. RESULTS: The study identified 106 DEGs in EAT from T2DM and AF datasets, underscoring significant pathways in energy metabolism and immune regulation. Three hub genes, CEBPZ, PAK1IP1, and BCCIP, emerged as pivotal in this context. In db/db mice, a marked predisposition towards AF induction and extended duration was observed, with HE staining verifying the presence of EAT. Additionally, qPCR validated significant changes in hub genes expression in db/db mice EAT. In-depth analysis identified 299 miRNAs and 33 TFs as potential regulators, notably GRHL1 and MYC. GeneMANIA analysis highlighted the hub genes' critical roles in stress responses and leukocyte differentiation, while immune profile correlations highlighted their impact on mast cells and neutrophils, emphasizing the genes' significant influence on immune regulation within the context of T2DM and AF. CONCLUSION: This investigation reveals the molecular links between T2DM and AF with a focus on EAT. Targeting these pathways, especially EAT-related ones, may enable personalized treatments and improved outcomes.

Gastroesophageal reflux disease and atrial fibrillation: a bidirectional Mendelian randomization study.

Background: In observational studies, gastroesophageal reflux disease (GERD) is linked to atrial fibrillation (AF). It is uncertain whether the relationship is due to GERD-induced AF or GERD caused by AF, or confusion with factors related to GERD and AF such as obesity and sleep-disordered breathing. We applied bidirectional Mendelian randomization (MR), in which genetic variations are used as instrumental variables to resolve confounding and reverse causation issues, to determine the causal effect between GERD and AF. Methods: Using summary data from the GERD and AF genome-wide association study (GWAS), a bidirectional MR was performed to estimate the causative impact of GERD on AF risk and AF on GERD risk. The GWAS of GERD meta-analysis comprised 78707 cases and 288734 controls. GWAS summary data for AF, including 45766 AF patients and 191924 controls, were used to genetically predicted AF. The inverse variance weighted (IVW) method was the major MR approach used. MR-PRESSO was implemented to detect heterogeneity and correct the effect of outliers. Weighted median and MR-Egger regression were applied to test heterogeneity and pleiotropy. Results: The genetic instruments of GERD related to increasing the risk of AF, with an OR of 1.339 (95% CI: 1.242-1.444, p < 0.001). However, after removing the outlier 8 SNPs, genetically predicted AF was not associated with an elevated risk of GERD (p = 0.351). Conclusions: Our result suggested that GERD had a causal effect on AF. However, no evidence was identified that AF elevated the risk of GERD.

Primary cilia suppress the fibrotic activity of atrial fibroblasts from patients with atrial fibrillation in vitro.

Atrial fibrosis serves as an arrhythmogenic substrate in atrial fibrillation (AF) and contributes to AF persistence. Treating atrial fibrosis is challenging because atrial fibroblast activity is multifactorial. We hypothesized that the primary cilium regulates the profibrotic response of AF atrial fibroblasts, and explored therapeutic potentials of targeting primary cilia to treat fibrosis in AF. We included 25 patients without AF (non-AF) and 26 persistent AF patients (AF). Immunohistochemistry using a subset of the patients (non-AF: n = 10, AF: n = 10) showed less ciliated fibroblasts in AF versus non-AF. Acetylated α-tubulin protein levels were decreased in AF, while the gene expressions of AURKA and NEDD9 were highly increased in AF patients' left atrium. Loss of primary cilia in human atrial fibroblasts through IFT88 knockdown enhanced expression of ECM genes, including FN1 and COL1A1. Remarkably, restoration or elongation of primary cilia by an AURKA selective inhibitor or lithium chloride, respectively, prevented the increased expression of ECM genes induced by different profibrotic cytokines in atrial fibroblasts of AF patients. Our data reveal a novel mechanism underlying fibrotic substrate formation via primary cilia loss in AF atrial fibroblasts and suggest a therapeutic potential for abrogating atrial fibrosis by restoring primary cilia.

Causal relationship between immune cells and atrial fibrillation: A Mendelian randomization study.

Atrial fibrillation (AF) is a prevalent cardiac arrhythmia, with recent research indicating a correlation between immune system characteristics and the development of AF. However, it remains uncertain whether the immunological response is the primary underlying component or a secondary consequence of AF. Initially, we investigated the effect of immune cells on AF by performing forward Mendelian randomization (MR) analyses with immune cells as the exposure variable and their associated genetic variants as instrumental variables. Subsequently, we performed reverse MR analyses with AF as the exposure variable and immune cells as the outcome variable to exclude the interference of reverse causality, to distinguish between primary and secondary effects, and to further elucidate the causal relationship between the immune system and AF. We discovered that membrane proteins on specific immune cells, such as CD25 on memory B cells-which functions as a part of the interleukin-2 receptor-may be risk factors for AF development, with odds ratios of 1.0233 (95% confidence interval: 1.0012-1.0458, P = .0383). In addition, certain immune cell counts, such as the CD4 regulatory T cell Absolute Count, play a protective factor in the development of AF (odds ratio: 0.9513, 95% confidence interval: 0.9165-0.9874; P = .0086). More detailed results are elaborated in the main text. Our MR study has yielded evidence that substantiates a genetically inferred causal association between the immune system and AF. Identifying the risk factors associated with AF is vital to facilitate the development of innovative pharmaceutical treatments.

Synergistic Effects of Weight Loss and Catheter Ablation: Can microRNAs Serve as Predictive Biomarkers for the Prevention of Atrial Fibrillation Recurrence?

In atrial fibrillation (AF), multifactorial pathologic atrial alterations are manifested by structural and electrophysiological changes known as atrial remodeling. AF frequently develops in the context of underlying cardiac abnormalities. A critical mechanistic role played by atrial stretch is played by abnormal substrates in a number of conditions that predispose to AF, including obesity, heart failure, hypertension, and sleep apnea. The significant role of overweight and obesity in the development of AF is known; however, the differential effect of overweight, obesity, cardiovascular comorbidities, lifestyle, and other modifiable risk factors on the occurrence and recurrence of AF remains to be determined. Reverse remodeling of the atrial substrate and subsequent reduction in the AF burden by conversion into a typical sinus rhythm has been associated with weight loss through lifestyle changes or surgery. This makes it an essential pillar in the management of AF in obese patients. According to recently published research, microRNAs (miRs) may function as post-transcriptional regulators of genes involved in atrial remodeling, potentially contributing to the pathophysiology of AF. The focus of this review is on their modulation by both weight loss and catheter ablation interventions to counteract atrial remodeling in AF. Our analysis outlines the experimental and clinical evidence supporting the synergistic effects of weight loss and catheter ablation (CA) in reversing atrial electrical and structural remodeling in AF onset and in recurrent post-ablation AF by attenuating pro-thrombotic, pro-inflammatory, pro-fibrotic, arrhythmogenic, and male-sex-associated hypertrophic remodeling pathways. Furthermore, we discuss the promising role of miRs with prognostic potential as predictive biomarkers in guiding approaches to AF recurrence prevention.

Gene polymorphism as a cause of hemorrhagic complications in patients with non-valvular atrial fibrillation treated with oral vitamin K-independent anticoagulants.

Atrial fibrillation (AF) accounts for 40% of all cardiac arrhythmias and is associated with a high risk of stroke and systemic thromboembolic complications. Dabigatran, rivaroxaban, apixaban, and edoxaban are direct oral anticoagulants (DOACs) that have been proven to prevent stroke in patients with non-valvular AF. This review summarizes the pharmacokinetics, pharmacodynamics, and drug interactions of DOACs, as well as new data from pharmacogenetic studies of these drugs. This review is aimed at analyzing the scientific literature on the gene polymorphisms involved in the metabolism of DOACs. We searched PubMed, Cochrane, Google Scholar, and CyberLeninka (Russian version) databases with keywords: 'dabigatran', 'apixaban', 'rivaroxaban', 'edoxaban', 'gene polymorphism', 'pharmacogenetics', 'ABCB1', 'CES1', 'SULT1A', 'ABCG2', and 'CYP3A4'. The articles referred for this review include (1) full-text articles; (2) study design with meta-analysis, an observational study in patients taking DOAC; and (3) data on the single-nucleotide polymorphisms and kinetic parameters of DOACs (plasma concentration), or a particular clinical outcome, published in English and Russian languages during the last 10 years. The ages of the patients ranged from 18 to 75 years. Out of 114 reviewed works, 24 were found eligible. As per the available pharmacogenomic data, polymorphisms affecting DOACs are different. This may aid in developing individual approaches to optimize DOAC pharmacotherapy to reduce the risk of hemorrhagic complications. However, large-scale population studies are required to determine the dosage of the new oral anticoagulants based on genotyping. Information on the genetic effects is limited owing to the lack of large-scale studies. Uncovering the mechanisms of the genetic basis of sensitivity to DOACs helps in developing personalized therapy based on patient-specific genetic variants and improves the efficacy and safety of DOACs in the general population.

Gene polymorphism as a cause of hemorrhagic complications in patients with non-valvular atrial fibrillation treated with oral vitamin K-independent anticoagulantsAtrial fibrillation (AF) accounts for 40% of all cardiac arrhythmias and is associated with a high risk of stroke and systemic thromboembolic complications. Dabigatran, rivaroxaban, apixaban, and edoxaban are direct oral anticoagulants (DOACs) that have been proven to prevent stroke in patients with non-valvular AF. This review summarizes the pharmacokinetics, pharmacodynamics, and drug interactions of DOACs, as well as new data from pharmacogenetic studies of these drugs.

Genetically predicted dietary macronutrient intakes and atrial fibrillation risk: a Mendelian randomization study.

BACKGROUND AND AIM: Previous observational investigations have indicated a potential association between relative dietary macronutrient intakes and atrial fibrillation and flutter (AF) risk. In this study, we employed Mendelian Randomization (MR) to evaluate the presence of causality and to elucidate the specific causal relationship. METHODS: We employed six, five, and three single nucleotide polymorphisms (SNPs) as instrumental variables for relative carbohydrate, protein, and fat intake, identified from a genome-wide association study that included 268,922 individuals of European descent. Furthermore, we acquired summary statistics for genome-wide association studies on AF from the FinnGen consortium, which involved 22,068 cases and 116,926 controls. To evaluate the causal estimates, we utilized the random effect inverse variance weighted method (IVW) and several other MR methods, including MR-Egger, weighted median, and MR-PRESSO, to confirm the robustness of our findings. RESULTS: Our analysis indicates a convincing causal relationship between genetically predicted relative carbohydrate and protein intake and reduced AF risk. Inverse variance weighted analysis results for carbohydrates (OR = 0.29; 95% CI (0.14, 0.59); P < 0.001) and protein (OR = 0.47; 95% CI (0.26, 0.85); P = 0.01) support this association. Our MR analysis did not identify a significant causal relationship between relative fat intake and AF risk. CONCLUSION: Our study provides evidence supporting a causal relationship between higher relative protein and carbohydrate intake and a lower risk of atrial fibrillation (AF).

Analyses of lncRNA and mRNA profiles in recurrent atrial fibrillation after catheter ablation.

BACKGROUND: Atrial fibrillation (AF) is the most common cardiac arrhythmia worldwide. Catheter ablation has become a crucial treatment for AF. However, there is a possibility of atrial fibrillation recurrence after catheter ablation. Our study sought to elucidate the role of lncRNA‒mRNA regulatory networks in late AF recurrence after catheter ablation. METHODS: We conducted RNA sequencing to profile the transcriptomes of 5 samples from the presence of recurrence after AF ablation (P-RAF) and 5 samples from the absence of recurrence after AF ablation (A-RAF). Differentially expressed genes (DEGs) and long noncoding RNAs (DE-lncRNAs) were analyzed using the DESeq2 R package. The functional correlations of the DEGs were assessed through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. A protein‒protein interaction (PPI) network was constructed using STRING and Cytoscape. We also established a lncRNA‒mRNA regulatory network between DE-lncRNAs and DEGs using BEDTools v2.1.2 software and the Pearson correlation coefficient method. To validate the high-throughput sequencing results of the hub genes, we conducted quantitative real-time polymerase chain reaction (qRT‒PCR) experiments. RESULTS: A total of 28,528 mRNAs and 42,333 lncRNAs were detected. A total of 96 DEGs and 203 DE-lncRNAs were identified between the two groups. GO analysis revealed that the DEGs were enriched in the biological processes (BPs) of "regulation of immune response" and "regulation of immune system process", the cellular components (CCs) of "extracellular matrix" and "cell‒cell junction", and the molecular functions (MFs) of "signaling adaptor activity" and "protein-macromolecule adaptor activity". According to the KEGG analysis, the DEGs were associated with the "PI3K-Akt signaling pathway" and "MAPK signaling pathway." Nine hub genes (MMP9, IGF2, FGFR1, HSPG2, GZMB, PEG10, GNLY, COL6A1, and KCNE3) were identified through the PPI network. lncRNA-TMEM51-AS1-201 was identified as a core regulator in the lncRNA‒mRNA regulatory network, suggesting its potential impact on the recurrence of AF after catheter ablation through the regulation of COL6A1, FGFR1, HSPG2, and IGF2. CONCLUSIONS: The recurrence of atrial fibrillation after catheter ablation may be associated with immune responses and fibrosis, with the extracellular matrix playing a crucial role. TMEM51-AS1-201 has been identified as a potential key target for AF recurrence after catheter ablation.

Exosomal miRNA Changes Associated with Restoration to Sinus Rhythm in Atrial Fibrillation Patients.

We aimed to identify serum exosomal microRNAs (miRNAs) associated with the transition from atrial fibrillation (AF) to sinus rhythm (SR) and investigate their potential as biomarkers for the early recurrence of AF within three months post-treatment. We collected blood samples from eight AF patients at Chang Gung Memorial Hospital in Taiwan both immediately before and within 14 days following rhythm control treatment. Exosomes were isolated from these samples, and small RNA sequencing was performed. Using DESeq2 analysis, we identified nine miRNAs (16-2-3p, 22-3p, 23a-3p, 23b-3p, 125a-5p, 328-3p, 423-5p, 504-5p, and 582-3p) associated with restoration to SR. Further analysis using the DIABLO model revealed a correlation between the decreased expression of miR-125a-5p and miR-328-3p and the early recurrence of AF. Furthermore, early recurrence is associated with a longer duration of AF, presumably indicating a more extensive state of underlying cardiac remodeling. In addition, the reads were mapped to mRNA sequences, leading to the identification of 14 mRNAs (AC005041.1, ARHGEF12, AMT, ANO8, BCL11A, DIO3OS, EIF4ENIF1, G2E3-AS1, HERC3, LARS, NT5E, PITX1, SLC16A12, and ZBTB21) associated with restoration to SR. Monitoring these serum exosomal miRNA and mRNA expression patterns may be beneficial for optimizing treatment outcomes in AF patients.

Transcriptomic Analysis of Extracellular Vesicles in the Search for Novel Plasma and Thrombus Biomarkers of Ischemic Stroke Etiologies.

Accurate etiologic diagnosis provides an appropriate secondary prevention and better prognosis in ischemic stroke (IS) patients; still, 45% of IS are cryptogenic, urging us to enhance diagnostic precision. We have studied the transcriptomic content of plasma extracellular vesicles (EVs) (n = 21) to identify potential biomarkers of IS etiologies. The proteins encoded by the selected genes were measured in the sera of IS patients (n = 114) and in hypertensive patients with (n = 78) and without atrial fibrillation (AF) (n = 20). IGFBP-2, the most promising candidate, was studied using immunohistochemistry in the IS thrombi (n = 23) and atrium of AF patients (n = 13). In vitro, the IGFBP-2 blockade was analyzed using thromboelastometry and endothelial cell cultures. We identified 745 differentially expressed genes among EVs of cardioembolic, atherothrombotic, and ESUS groups. From these, IGFBP-2 (cutoff > 247.6 ng/mL) emerged as a potential circulating biomarker of embolic IS [OR = 8.70 (1.84-41.13) p = 0.003], which was increased in patients with AF vs. controls (p < 0.001) and was augmented in cardioembolic vs. atherothrombotic thrombi (p < 0.01). Ex vivo, the blockage of IGFBP-2 reduced clot firmness (p < 0.01) and lysis time (p < 0.001) and in vitro, diminished endothelial permeability (p < 0.05) and transmigration (p = 0.06). IGFBP-2 could be a biomarker of embolic IS and a new therapeutic target involved in clot formation and endothelial dysfunction.

Causal associations between atrial fibrillation and breast cancer: A bidirectional Mendelian randomization analysis.

BACKGROUND: Previous observational studies indicated that atrial fibrillation may increase the risk of breast cancer. Following a breast cancer diagnosis, the chance of developing atrial fibrillation may increase as well. However, it is uncertain whether the link is causal or just due to confounding factors. OBJECTIVE: Using bidirectional Mendelian randomization (MR) analysis, we sought to assess the bidirectional causal relationship between atrial fibrillation and breast cancer from a genetic level. METHODS: Large genome-wide association studies yielded summary-level data for atrial fibrillation and breast cancer. The preliminary estimate was inverse variance weighted (IVW) under a random model. MR-Egger, weighted median, simple mode, weighted mode, and multivariable MR (adjusting body mass index, smoking, and alcohol drinking) were performed as sensitivity analyses. RESULTS: Genetically predicted atrial fibrillation presented no statistically significant association with overall breast cancer (odds ratio [OR] = 1.00; 95% confidence interval [CI]: 0.97-1.04; p = 0.79), estrogen receptor (ER) + (OR = 1.00; 95% CI: 0.96-1.03; p = 0.89) or ER- subtypes (OR = 1.00; 95% CI: 0.97-1.04; p = 0.89). Similarly, genetically predicted overall breast cancer (OR = 1.01; 95% CI: 0.98-1.04; p = 0.37), ER+ (OR = 1.02; 95% CI: 0.99-1.05; p = 0.16) or ER- (OR = 0.98; 95% CI: 0.93-1.02; p = 0.32) subtypes had no causal effect on atrial fibrillation. Sensitivity analyses yielded similar results. Individual single nucleotide polymorphism had little effect on the total estimate. We did not observe any evidence of horizontal pleiotropy. CONCLUSIONS: Our bidirectional MR studies revealed that there may be no causal links between atrial fibrillation and breast cancer.

High Dietary Intake of Iron Might Be Harmful to Atrial Fibrillation and Modified by Genetic Diversity: A Prospective Cohort Study.

Some studies suggest an association between iron overload and cardiovascular diseases (CVDs). However, the relationship between dietary iron intake and atrial fibrillation (AF) remains uncertain, as does the role of genetic loci on this association. The study involved 179,565 participants from UK Biobank, tracking incident atrial fibrillation (AF) cases. Iron intake was categorized into low, moderate, and high groups based on dietary surveys conducted from 2009 to 2012. The Cox regression model was used to estimate the risk of AF in relation to iron intake, assessing the hazard ratio (HR) and 95% confidence interval (95% CI). It also examined the impact of 165 AF-related and 20 iron-related genetic variants on this association. Pathway enrichment analyses were performed using Metascape and FUMA. During a median follow-up period of 11.6 years, 6693 (3.97%) incident AF cases were recorded. A total of 35,874 (20.0%) participants had high iron intake. High iron intake was associated with increased risk of AF [HR: 1.13 (95% CI: 1.05, 1.22)] in a fully adjusted model. Importantly, there were 83 SNPs (11 iron-related SNPs) that could enhance the observed associations. These genes are mainly involved in cardiac development and cell signal transduction pathways. High dietary iron intake increases the risk of atrial fibrillation, especially when iron intake exceeds 16.95 mg. The association was particularly significant among the 83 SNPs associated with AF and iron, the individuals with these risk genes. Gene enrichment analysis revealed that these genes are significantly involved in cardiac development and cell signal transduction processes.

Clinical Genetic Testing for Atrial Fibrillation: Are We There Yet?

Important progress has been made toward unravelling the complex genetics underlying atrial fibrillation (AF). Initial studies were aimed to identify monogenic causes; however, it has become increasingly clear that the most common predisposing genetic substrate for AF is polygenic. Despite intensive investigations, there is robust evidence for rare variants for only a limited number of genes and cases. Although the current yield for genetic testing in early onset AF might be modest, there is an increasing appreciation that genetic culprits for potentially life-threatening ventricular cardiomyopathies and channelopathies might initially present with AF. The potential clinical significance of this recognition is highlighted by evidence that suggests that identification of a pathogenic or likely pathogenic rare variant in a patient with early onset AF is associated with an increased risk of death. These findings suggest that it might be warranted to screen patients with early onset AF for these potentially more sinister cardiac conditions. Beyond facilitating the early identification of genetic culprits associated with potentially malignant phenotypes, insight into underlying AF genetic substrates might improve the selection of patients for existing therapies and guide the development of novel ones. Herein, we review the evidence that links genetic factors to AF, then discuss an approach to using genetic testing for early onset AF patients in the present context, and finally consider the potential value of genetic testing in the foreseeable future. Although further work might be necessary before recommending uniform integration of genetic testing in cases of early onset AF, ongoing research increasingly highlights its potential contributions to clinical care.

Combined polygenic scores for ischemic stroke risk factors aid risk assessment of ischemic stroke.

BACKGROUND: Current risk assessment for ischemic stroke (IS) is limited to clinical variables. We hypothesize that polygenic scores (PGS) of IS (PGSIS) and IS-associated diseases such as atrial fibrillation (AF), venous thromboembolism (VTE), coronary artery disease (CAD), hypertension (HTN), and Type 2 diabetes (T2D) may improve the performance of IS risk assessment. METHODS: Incident IS was followed for 479,476 participants in the UK Biobank who did not have an IS diagnosis prior to the recruitment. Lifestyle variables (obesity, smoking and alcohol) at the time of study recruitment, clinical diagnoses of IS-associated diseases, PGSIS, and five PGSs for IS-associated diseases were tested using the Cox proportional-hazards model. Predictive performance was assessed using the C-statistic and net reclassification index (NRI). RESULTS: During a median average 12.5-year follow-up, 8374 subjects were diagnosed with IS. Known clinical variables (age, gender, clinical diagnoses of IS-associated diseases, obesity, and smoking) and PGSIS were all independently associated with IS (P < 0.001). In addition, PGSIS and each PGS for IS-associated diseases was also independently associated with IS (P < 0.001). Compared to the clinical model, a joint clinical/PGS model improved the C-statistic for predicting IS from 0.71 to 0.73 (P < 0.001) and significantly reclassified IS risk (NRI = 0.017, P < 0.001), and 6.48% of subjects were upgraded from low to high risk. CONCLUSIONS: Adding PGSs of IS and IS-associated diseases to known clinical risk factors statistically improved risk assessment for IS, demonstrating the supplementary value of inherited susceptibility measurement . However, its clinical utility is likely limited due to modest improvements in predictive values.