A polygenic risk score predicts atrial fibrillation in cardiovascular disease

The Risk of Atrial Fibrillation and Previous Ischemic Stroke in Cognitive Decline

Objectives: Our study investigated the inverse relationship between cognitive decline (CD) and the presence of documented atrial fibrillation (AFib), ischemic stroke, heart failure, lower extremity peripheral artery disease, and diabetes mellitus. Methods: We conducted a retrospective cross-sectional study between December 2016 and November 2019. A total of 469 patients were enrolled who underwent cognitive evaluation with three cognitive tests (Montreal Cognitive Assessment-MOCA, Mini-Mental State Examination-MMSE, and General Practitioner Assessment of Cognition-GPCOG). We used the standard cut-off values, and the optimal thresholds were obtained from the receiver operating characteristic curves. Results: The standard cut-off level of the MOCA (<26 points) was associated with the presence of AFib (OR: 1.83, 95% CI: 1.11-3.01) and the optimal cut-off level with <23 points with ischemic stroke (OR: 2.64, 95% CI: 1.47-4.74; p = 0.0011). The optimal cut-off value of the MMSE (<28 points) was associated with the presence of ischemic stroke (OR: 3.07, 95% CI: 1.56-6.07; p = 0.0012), AFib (OR: 1.65, 95% CI: 1.05-2.60; p = 0.0287), and peripheral artery disease (OR: 2.72, 95% CI: 1.38-5.36; p = 0.0039). GPCOG < 8 points were associated with ischemic stroke (OR: 2.18, 95% CI: 1.14-4.14; p = 0.0176) and heart failure (OR: 1.49, 95% CI: 1.01-2.21; p = 0.0430). Conclusions: Our research highlighted the broader utility of cognitive assessment. The MOCA and MMSE scores proved to be associated with documented AFib. Higher cognitive test results than the standard threshold for CD of the MMSE, GPCOG, and lower MOCA scores represented risk factors for the presence of previous ischemic stroke.

Atrial fibrillation burden: a new outcome predictor and therapeutic target

Atrial fibrillation (AF), the most common sustained cardiac arrhythmia, is not a dichotomous disease trait. Technological innovations enable long-term rhythm monitoring in many patients and can estimate AF burden. These technologies are already used to detect and monitor AF. This review describes the relation between AF burden and outcomes and potential effects of AF burden reduction. A lower AF burden is associated with a lower risk of stroke and heart failure in patients with AF: stroke risk without anticoagulation is lower in patients with device-detected AF and a low AF burden (stroke rate 1%/year) than in patients with persistent and permanent AF (stroke rate 3%/year). Paroxysmal AF shows intermediate stroke rates (2%/year). Atrial fibrillation burden-reducing interventions can reduce cardiovascular outcomes in patients with AF: early rhythm control reduces cardiovascular events including stroke and heart failure in patients with recently diagnosed AF and cardiovascular conditions. In patients with heart failure and AF, early rhythm control and AF ablation, interventions that reduce AF burden, reduce mortality and heart failure events. Recent technological innovations allow to estimate AF burden in clinical care, creating opportunities and challenges. While evidence remains limited, the existing data already suggest that AF burden reduction could be a therapeutic goal. In addition to anticoagulation and treatment of cardiovascular conditions, AF burden reduction emerges as a therapeutic goal. Future research will define the AF burden that constitutes a relevant risk of stroke and heart failure. Technologies quantifying AF burden need careful validation to advance the field.

Atrial fibrillation: age at diagnosis, incident cardiovascular events, and mortality

BACKGROUND AND AIMS

Patients with atrial fibrillation (AF) are at increased risks of cardiovascular diseases and mortality, but risks according to age at diagnosis have not been reported. This study investigated age-specific risks of outcomes among patients with AF and the background population.

METHODS

This nationwide population-based cohort study included patients with AF and controls without outcomes by the application of exposure density matching on the basis of sex, year of birth, and index date. The absolute risks and hazard rates were stratified by age groups and assessed using competing risk survival analyses and Cox regression models, respectively. The expected differences in residual life years among participants were estimated.

RESULTS

The study included 216 579 AF patients from year 2000 to 2020 and 866 316 controls. The mean follow-up time was 7.9 years. Comparing AF patients with matched controls, the hazard ratios among individuals ≤50 years was 8.90 [95% confidence interval (CI), 7.17-11.0] for cardiomyopathy, 8.64 (95% CI, 7.74-9.64) for heart failure, 2.18 (95% CI, 1.89-2.52) for ischaemic stroke, and 2.74 (95% CI, 2.53-2.96) for mortality. The expected average loss of life years among individuals ≤50 years was 9.2 years (95% CI, 9.0-9.3) years. The estimates decreased with older age.

CONCLUSIONS

The findings show that earlier diagnosis of AF is associated with a higher hazard ratio of subsequent myocardial disease and shorter life expectancy. Further studies are needed to determine causality and whether AF could be used as a risk marker among particularly younger patients.

Polygenic risk scores in atrial fibrillation: Associations and clinical utility in disease prediction

Atrial fibrillation (AF) is a common heart arrhythmia and a major cause of cardioembolic stroke. Therefore, accurate prediction is desirable to allow high-risk individuals to be identified early and their risk lowered before complications arise. Polygenic risk scores (PRSs) have become a popular method of quantifying aggregated genetic risk from common variants, but their clinical value in AF remains uncertain. This literature review summarizes the associations between PRS and AF risk and discusses the evidence for the clinical utility of PRS for AF prediction. Stroke risk in patients with AF is also considered. Despite consistent associations between PRS and AF risk, the performance of PRS as a stand-alone tool for AF prediction was poor. However, addition of PRS to the existing AF prediction models commonly improved the predictive performance above that of the clinical models alone, including in cohorts with comorbid cardiovascular disease. Associations between PRS and cardioembolic stroke risk in patients with AF have also been reported, but improvements in stroke prediction models from PRS have been minimal. PRS are likely to add value to the existing clinical AF prediction models; however, standardization of PRS across studies and populations will likely be required before they can be meaningfully adopted into routine clinical practice.

Genetic testing in cardiovascular disease

Cardiovascular disease (CVD) is the leading cause of morbidity and mortality globally and is responsible for an estimated one-third of deaths as well as significant morbidity and health care utilisation. Technological and bioinformatic advances have facilitated the discovery of pathogenic germline variants for some specific CVDs, including familial hypercholesterolaemia, cardiomyopathies and arrhythmic syndromes. Use of these genetic tests for earlier disease identification is increasing due, in part, to decreasing costs, Medicare rebates, and consumer comfort with genetic testing. However, CVDs that occur more commonly, including coronary artery disease and atrial fibrillation, do not display monogenic inheritance patterns. Genetically, these diseases have generally been associated with many genetic variants each with a small effect size. This complexity can be expressed mathematically as a polygenic risk score. Genetic testing kits that provide polygenic risk scoring are becoming increasingly available directly to private-paying consumers outside the traditional clinical setting. An improved understanding of the evidence of genetics in CVD will offer clinicians new opportunities for individualised risk prediction and preventive therapy.

Interaction of genetic risk and lifestyle on the incidence of atrial fibrillation

BACKGROUND

The relationship between combined genetic predisposition and lifestyle and the risk of incident atrial fibrillation (AF) is unclear. Therefore, we aimed to assess a possible interaction between lifestyle and genetics on AF risk.

METHODS

We included AF cases and a randomly drawn subcohort of 4040 participants from the Danish Diet, Cancer and Health cohort. Lifestyle risk factors were assessed, a score was calculated, and participants were categorised as having a poor, intermediate, or ideal lifestyle. We calculated a genetic risk score comprising 142 variants, and categorised participants into low (quintile 1), intermediate (quintiles 2-4) or high (quintile 5) genetic risk of AF.

RESULTS

3094 AF cases occurred during a median follow-up of 12.9 years. Regardless of genetic risk, incidence rates per 1000 person-years were gradually higher with worse lifestyle. For participants with high genetic risk, the incidence rates of AF per 1000 person-years were 5.0 (95% CI 3.4 to 7.3) among individuals with ideal lifestyle, 6.6 (95% CI 5.4 to 8.1) among those with intermediate lifestyle and 10.4 (95% CI 9.2 to 11.8) among participants with poor lifestyle. On an additive scale, there was a positive statistically significant interaction between genetic risk and lifestyle (relative excess risk due to interaction=0.86, 95% CI 0.68 to 1.03, p<0.001).

CONCLUSIONS

The rates of AF increased gradually with worse lifestyle within each category of genetic risk. We found a positive interaction on an additive scale between genetic risk and lifestyle, suggesting that risk factor modification is especially important in individuals with a high genetic risk of AF.

Novel Polygenic Risk Score and Established Clinical Risk Factors for Risk Estimation of Aortic Stenosis

Importance

Polygenic risk scores (PRSs) have proven to be as strong as or stronger than established clinical risk factors for many cardiovascular phenotypes. Whether this is true for aortic stenosis remains unknown.

Objective

To develop a novel aortic stenosis PRS and compare its aortic stenosis risk estimation to established clinical risk factors.

Design, Setting, and Participants

This was a longitudinal cohort study using data from the Million Veteran Program (MVP; 2011-2020), UK Biobank (2006-2010), and 6 Thrombolysis in Myocardial Infarction (TIMI) trials, including DECLARE-TIMI 58 (2013-2018), FOURIER (TIMI 59; 2013-2017), PEGASUS-TIMI 54 (2010-2014), SAVOR-TIMI 53 (2010-2013), SOLID-TIMI 52 (2009-2014), and ENGAGE AF-TIMI 48 (2008-2013), which were a mix of population-based and randomized clinical trials. Individuals from UK Biobank and the MVP meeting a previously validated case/control definition for aortic stenosis were included. All individuals from TIMI trials were included unless they had a documented preexisting aortic valve replacement. Analysis took place from January 2022 to December 2023.

Exposures

PRS for aortic stenosis (developed using data from MVP and validated in UK Biobank) and other previously validated cardiovascular PRSs, defined either as a continuous variable or as low (bottom 20%), intermediate, and high (top 20%), and clinical risk factors.

Main Outcomes

Aortic stenosis (defined using International Classification of Diseases or Current Procedural Terminology codes in UK Biobank and MVP or safety event data in the TIMI trials).

Results

The median (IQR) age in MVP was 67 (57-73) years, and 135 140 of 147 104 participants (92%) were male. The median (IQR) age in the TIMI trials was 66 (54-78) years, and 45 524 of 59 866 participants (71%) were male. The best aortic stenosis PRS incorporated 5 170 041 single-nucleotide variants and was associated with aortic stenosis in both the MVP testing sample (odds ratio, 1.41; 95% CI, 1.37-1.45 per 1 SD PRS; P = 4.6 × 10-116) and TIMI trials (hazard ratio, 1.44; 95% CI, 1.27-1.62 per 1 SD PRS; P = 3.2 × 10-9). Among genetic and clinical risk factors, the aortic stenosis PRS performed comparably to most risk factors besides age, and within a given age range, the combination of clinical and genetic risk factors was additive, providing a 3- to 4-fold increased gradient of risk of aortic stenosis. However, the addition of the aortic stenosis PRS to a model including clinical risk factors only improved risk discrimination of aortic stenosis by 0.01 to 0.02 (C index in MVP: 0.78 with clinical risk factors, 0.79 with risk factors and aortic stenosis PRS; C index in TIMI: 0.71 with clinical risk factors, 0.73 with risk factors and aortic stenosis PRS).

Conclusions

This study developed and validated 1 of the first aortic stenosis PRSs. While aortic stenosis genetic risk was independent from clinical risk factors and performed comparably to all other risk factors besides age, genetic risk resulted in only a small improvement in overall aortic stenosis risk discrimination beyond age and clinical risk factors. This work sets the stage for further development of an aortic stenosis PRS.

[Genetic basis of atrial fibrillation-on the road to precision medicine]

Atrial fibrillation (AF) is the most common cardiac arrhythmia and has complex genetic underpinnings. Despite advancements in treatment, mortality of AF patients remains high. This review discusses the genetic basis of AF and its implications for diagnosis and therapy. Although AF pathology has long been known to include a hereditary component, the first genes associated with AF were not identified until the early 2000s. Subsequent research with genome-wide association studies (GWAS) has implicated other genes and numerous genetic variants in AF. These studies have revealed nearly 140 different regions in the DNA with genome-wide significance associated with AF. In addition to common variants, rare variants with large effects have also been identified. The integration of these genetic findings into clinical practice holds promise for improving AF diagnosis and treatment, moving us closer to precision medicine. However, challenges remain, including the need for more diverse genetic data of non-European ancestry and improved genetic analyses of responses to AF therapy.

Precision medicine: Hype or hope?

In recent years, precision medicine has steadily risen to the forefront of many aspects of medicine, including cardiology [1]. While this field has exponentially expanded and advanced in the last few years, a lot of questions remain regarding exact definition, usage, and clinical applications [2,3]. This review will provide a brief synopsis of the current state of precision medicine, its limitations, future directions, as well as analyze emerging clinical applications in cardiology.

Role of Genetic Variation in Transcriptional Regulatory Elements in Heart Rhythm

Genetic predisposition to cardiac arrhythmias has been a field of intense investigation. Research initially focused on rare hereditary arrhythmias, but over the last two decades, the role of genetic variation (single nucleotide polymorphisms) in heart rate, rhythm, and arrhythmias has been taken into consideration as well. In particular, genome-wide association studies have identified hundreds of genomic loci associated with quantitative electrocardiographic traits, atrial fibrillation, and less common arrhythmias such as Brugada syndrome. A significant number of associated variants have been found to systematically localize in non-coding regulatory elements that control the tissue-specific and temporal transcription of genes encoding transcription factors, ion channels, and other proteins. However, the identification of causal variants and the mechanism underlying their impact on phenotype has proven difficult due to the complex tissue-specific, time-resolved, condition-dependent, and combinatorial function of regulatory elements, as well as their modest conservation across different model species. In this review, we discuss research efforts aimed at identifying and characterizing-trait-associated variant regulatory elements and the molecular mechanisms underlying their impact on heart rate or rhythm.

A proteomic analysis of atrial fibrillation in a prospective longitudinal cohort (AGES-Reykjavik study)

AIMS

Atrial fibrillation (AF) is associated with high risk of comorbidities and mortality. Our aim was to examine causal and predictive relationships between 4137 serum proteins and incident AF in the prospective population-based Age, Gene/Environment Susceptibility-Reykjavik (AGES-Reykjavik) study.

METHODS AND RESULTS

The study included 4765 participants, of whom 1172 developed AF. Cox proportional hazards regression models were fitted for 4137 baseline protein measurements adjusting for known risk factors. Protein associations were tested for replication in the Cardiovascular Health Study (CHS). Causal relationships were examined in a bidirectional, two-sample Mendelian randomization analysis. The time-dependent area under the receiver operating characteristic curve (AUC)-statistic was examined as protein levels and an AF-polygenic risk score (PRS) were added to clinical risk models. The proteomic signature of incident AF consisted of 76 proteins, of which 63 (83%) were novel and 29 (38%) were replicated in CHS. The signature included both N-terminal prohormone of brain natriuretic peptide (NT-proBNP)-dependent (e.g. CHST15, ATP1B1, and SVEP1) and independent components (e.g. ASPN, AKR1B, and LAMA1/LAMB1/LAMC1). Nine causal candidates were identified (TAGLN, WARS, CHST15, CHMP3, COL15A1, DUSP13, MANBA, QSOX2, and SRL). The reverse causal analysis suggested that most AF-associated proteins were affected by the genetic liability to AF. N-terminal prohormone of brain natriuretic peptide improved the prediction of incident AF events close to baseline with further improvements gained by the AF-PRS at all time points.

CONCLUSION

The AF proteomic signature includes biologically relevant proteins, some of which may be causal. It mainly reflects an NT-proBNP-dependent consequence of the genetic liability to AF. N-terminal prohormone of brain natriuretic peptide is a promising marker for incident AF in the short term, but risk assessment incorporating a PRS may improve long-term risk assessment.

Future Perspectives to Improve CHA2DS2VASc Score: The Role of Left Atrium Remodelling, Inflammation and Genetics in Anticoagulation of Atrial Fibrillation

In 10% of ischemic strokes, non-valvular atrial fibrillation (NVAF) is detected retroactively. Milder, or even asymptomatic forms of NVAF have shown high mortality, thrombotic risk, and deterioration of cognitive function. The current guidelines for the diagnosis and treatment of AF contain "grey areas", such as the one related to anticoagulant treatment in men with CHA2DS2-VASc score 1 and women with score 2. Moreover, parameters such as renal function, patient weight or left atrium remodelling are missing from the recommended guidelines scores. Vulnerable categories of patients including the elderly population, high hemorrhagic risk patients or patients with newly diagnosed paroxysmal episodes of atrial high rate at device interrogation are at risk of underestimation of the thrombotic risk. This review presents a systematic exposure of the most important gaps in evaluation of thrombotic and hemorrhagic risk in patients with NVAF. The authors propose new algorithms and risk factors that should be taken into consideration for an accurate thrombotic and hemorrhagic risk estimation, especially in vulnerable categories of patients.

A Discussion of the Contemporary Prediction Models for Atrial Fibrillation

Atrial Fibrillation is a complex disease state with many environmental and genetic risk factors. While there are environmental factors that have been shown to increase an individual's risk of atrial fibrillation, it has become clear that atrial fibrillation has a genetic component that influences why some patients are at a higher risk of developing atrial fibrillation compared to others. This review will first discuss the clinical diagnosis of atrial fibrillation and the corresponding rhythm atrial flutter. We will then discuss how a patients' risk of stroke can be assessed by using other clinical co-morbidities. We will then review the clinical risk factors that can be used to help predict an individual patient's risk of atrial fibrillation. Many of the clinical risk factors have been used to create several different risk scoring methods that will be reviewed. We will then discuss how genetics can be used to identify individuals who are at higher risk for developing atrial fibrillation. We will discuss genome-wide association studies and other sequencing high-throughput sequencing studies. Finally, we will touch on how genetic variants derived from a genome-wide association studies can be used to calculate an individual's polygenic risk score for atrial fibrillation. An atrial fibrillation polygenic risk score can be used to identify patients at higher risk of developing atrial fibrillation and may allow for a reduction in some of the complications associated with atrial fibrillation such as cerebrovascular accidents and the development of heart failure. Finally, there is a brief discussion of how artificial intelligence models can be used to predict which patients will develop atrial fibrillation.

Association of genetic risk and outcomes in patients with atrial fibrillation: interactions with early rhythm control in the EAST-AFNET4 trial

AIMS

The randomized Early Treatment of Atrial Fibrillation for Stroke Prevention Trial found that early rhythm control reduces cardiovascular events in patients with recently diagnosed atrial fibrillation (AF) compared with usual care. How genetic predisposition to AF and stroke interacts with early rhythm-control therapy is not known.

METHODS AND RESULTS

Array genotyping and imputation for common genetic variants were performed. Polygenic risk scores (PRS) were calculated for AF (PRS-AF) and ischaemic stroke risk (PRS-stroke). The effects of PRS-AF and PRS-stroke on the primary outcome (composite of cardiovascular death, stroke, and hospitalization for acute coronary syndrome or worsening heart failure), its components, and recurrent AF were determined.A total of 1567 of the 2789 trial patients were analysed [793 randomized to early rhythm control; 774 to usual care, median age 71 years (65-75), 704 (44%) women]. Baseline characteristics were similar between randomized groups. Early rhythm control reduced the primary outcome compared with usual care [HR 0.67, 95% CI: (0.53, 0.84), P < 0.001]. The randomized intervention, early rhythm control, did not interact with PRS-AF (interaction P = 0.806) or PRS-stroke (interaction P = 0.765). PRS-AF was associated with recurrent AF [HR 1.08 (01.0, 1.16), P = 0.047]. PRS-stroke showed an association with the primary outcome [HR 1.13 (1.0, 1.27), P = 0.048], driven by more heart failure events [HR 1.23 (1.05-1.43), P = 0.010] without differences in stroke [HR 1.0 (0.75, 1.34), P = 0.973] in this well-anticoagulated cohort. In a replication analysis, PRS-stroke was associated with incident AF [HR 1.16 (1.14, 1.67), P < 0.001] and with incident heart failure in the UK Biobank [HR 1.08 (1.06, 1.10), P < 0.001]. The association with heart failure was weakened when excluding AF patients [HR 1.03 (1.01, 1.05), P = 0.001].

CONCLUSIONS

Early rhythm control is effective across the spectrum of genetic AF and stroke risk. The association between genetic stroke risk and heart failure calls for research to understand the interactions between polygenic risk and treatment.

REGISTRATION

ISRCTN04708680, NCT01288352, EudraCT2010-021258-20, www.easttrial.org.

Advances in basic and translational research in atrial fibrillation

Atrial fibrillation (AF) is a very common cardiac arrhythmia with an estimated prevalence of 33.5 million patients globally. It is associated with an increased risk of death, stroke and peripheral embolism. Although genetic studies have identified a growing number of genes associated with AF, the definitive impact of these genetic findings is yet to be established. Several mechanisms, including electrical, structural and neural remodelling of atrial tissue, have been proposed to contribute to the development of AF. Despite over a century of exploration, the molecular and cellular mechanisms underlying AF have not been fully established. Current antiarrhythmic drugs are associated with a significant rate of adverse events and management of AF using ablation is not optimal, especially in cases of persistent AF. This review discusses recent advances in our understanding and management of AF, including new concepts of epidemiology, genetics and pathophysiological mechanisms. We review the current status of antiarrhythmic drug therapy for AF, new potential agents, as well as mechanism-based AF ablation. This article is part of the theme issue 'The heartbeat: its molecular basis and physiological mechanisms'.

Genome and atrial fibrillation

Atrial fibrillation (AF), the most common type of arrhythmia, can cause several adverse effects, such as stroke, heart failure, and cognitive dysfunction, also in addition to reducing quality of life and increasing mortality. Evidence suggests that AF is caused by a combination of genetic and clinical predispositions. In line with this, genetic studies on AF have progressed significantly through linkage studies, genome-wide association studies, use of polygenic risk scores, and studies on rare coding variations, gradually elucidating the relationship between genes and the pathogenesis and prognosis of AF. This article will review current trends in genetic analysis concerning AF.

Genetics of atrial fibrillation

PURPOSE OF REVIEW

Atrial fibrillation is the most common cardiac arrhythmia worldwide. There is considerable interest in better understanding the molecular genetics and biology of atrial fibrillation to inform the development of new therapies and improve clinical management. This review summarizes recent advances in our understanding of the genetic basis of atrial fibrillation and new efforts to utilize genetics to inform clinical management.

RECENT FINDINGS

Genome-wide association studies in diverse populations have increased the number of genetic loci associated with atrial fibrillation and its specific subtypes. Large-scale biobanks with deep phenotyping have provided invaluable data to study the impact of both common and rare variants on atrial fibrillation, susceptibility, and prognosis. Polygenic risk scores help improve individual atrial fibrillation risk stratification and prognostication.

SUMMARY

Our understanding of atrial fibrillation genetics is rapidly improving with larger and more diverse genome-wide association studies. Translating genetic discoveries into molecular pathways and new therapeutic targets remains a bottleneck in the development of new therapies for atrial fibrillation. Genetic risk scores have shown early promise in improving atrial fibrillation risk stratification; however, their broader utility for the general population remains unclear.

Polygenic risk scores for the prediction of cardiometabolic disease

Cardiometabolic diseases contribute more to global morbidity and mortality than any other group of disorders. Polygenic risk scores (PRSs), the weighted summation of individually small-effect genetic variants, represent an advance in our ability to predict the development and complications of cardiometabolic diseases. This article reviews the evidence supporting the use of PRS in seven common cardiometabolic diseases: coronary artery disease (CAD), stroke, hypertension, heart failure and cardiomyopathies, obesity, atrial fibrillation (AF), and type 2 diabetes mellitus (T2DM). Data suggest that PRS for CAD, AF, and T2DM consistently improves prediction when incorporated into existing clinical risk tools. In other areas such as ischaemic stroke and hypertension, clinical application appears premature but emerging evidence suggests that the study of larger and more diverse populations coupled with more granular phenotyping will propel the translation of PRS into practical clinical prediction tools.