Next Article in Journal
Cardiac Involvement in Patients with MELAS-Related mtDNA 3243A>G Variant
Previous Article in Journal
Pathophysiological Bases and Clinical Uses of Metalloproteases in Cardiovascular Disease: A Scoping Review
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Novel Perspectives on Genetic Evaluation in Early-Onset Atrial Fibrillation: Clinical Implications and Future Directions

1
Clinical and Interventional Cardiology, AOU Sassari, 07100 Sassari, Italy
2
Department of Medicine, Surgery and Pharmacy, University of Sassari, 07100 Sassari, Italy
3
Department of Biomedical Sciences, University of Sassari, 07100 Sassari, Italy
*
Authors to whom correspondence should be addressed.
Cardiogenetics 2025, 15(2), 15; https://doi.org/10.3390/cardiogenetics15020015
Submission received: 7 April 2025 / Revised: 21 May 2025 / Accepted: 28 May 2025 / Published: 30 May 2025
(This article belongs to the Section Cardiovascular Genetics in Clinical Practice)

Abstract

:
Background: Early-onset atrial fibrillation (AF) exhibits distinct clinical and genetic profiles compared to AF in older adults. The increasing detection of AF among younger patients—often in the absence of traditional risk factors—has raised interest in the genetic determinants underlying the condition. This review aims to synthesize current evidence on the genetic architecture of early-onset AF, assess the clinical utility of genetic testing, and discuss future directions for integrating genetic insights into personalized management strategies. Methods: We conducted a comprehensive analysis of recent studies, including genome-wide association studies and targeted sequencing efforts, that examined rare pathogenic variants and polygenic risk scores in early-onset AF. The review also considers emerging data on atrial cardiomyopathy and evaluates current guideline recommendations for genetic testing. Results: Data indicate that rare variants, particularly in genes such as TTN, LMNA, and KCNQ1, play a significant role in early-onset AF, with evidence suggesting an association between these mutations and adverse clinical outcomes. Polygenic risk scores further complement traditional risk factors, providing a more nuanced risk stratification. Despite these advances, challenges remain in the interpretation of variants of uncertain significance, cost-effectiveness, and the need for interdisciplinary collaboration in clinical implementation. Conclusions: Integrating genetic evaluation into the diagnostic and management framework of early-onset AF holds promise for improved risk stratification and personalized therapy. Future large-scale, multi-ethnic studies and ongoing refinement of genetic risk models are essential to overcome current limitations and enhance the clinical applicability of genetic testing in this rapidly evolving field.

1. Introduction

Atrial fibrillation (AF) and atrial flutter (AFL) are common tachyarrhythmias associated with severe complications such as heart failure and stroke, significantly affecting patients’ health and quality of life. Their etiology is multifactorial, with known modifiable risk factors such as obesity, hypertension, diabetes mellitus, obstructive sleep apnea, and alcohol use. These conditions often coexist with biological changes observed in AF patients, including elevated pro-inflammatory cytokines, increased epicardial fat, and diffuse myocardial fibrosis [1,2]. The global prevalence of AF doubled from 1990 to 2019, with cases expected to rise further, particularly in aging populations [3]. Economic disparities influence disease burden, with lower-resource regions facing higher morbidity and mortality, while developed countries benefit from better diagnostic and treatment measures [4]. Recent studies underscore the complex genetic landscape of AF, involving both rare and common variants, paving the way for improved risk assessment and personalized management strategies [5]. Autosomal dominant atrial fibrillation (AF) has been linked to rare mutations in several ion channel genes, including KCNQ1, KCNJ2, KCNE2, SCN5A, KCNA5, and NPPA. Additionally, genes encoding cardiac connexins, such as GJA1 and GJA5, have been implicated in sporadic AF cases.
These mutations are typically family-specific and represent rare causes of AF. In contrast, genome-wide association studies (GWAS) have identified common single nucleotide polymorphisms (SNPs) across several loci that are associated with increased AF risk [6]. Roselli et al. conducted a large meta-analysis of GWAS that identified over 350 AF-associated loci, implicating genes involved in contractility, cardiac development, and cell–cell communication [7,8]. Compared to older adults, young individuals are generally less prone to AF and its related strokes [9]. However, the increasing use of wearable devices has led to earlier detection of AF among the young. In patients under 30, about 25% exhibit atrioventricular nodal or atrioventricular reentrant tachycardia, which, when treated with targeted ablation, often results in the resolution of AF episodes. AF is associated with inherited cardiac conditions (Figure 1), including dilated and hypertrophic cardiomyopathies, long QT syndrome (LQTS), short QT syndrome (SQTS), Brugada syndrome (BrS), catecholaminergic polymorphic ventricular tachycardia (CPVT), congenital heart defects, and pre-excitation syndromes [10]. Recent advances in genetic research have significantly deepened the understanding of the molecular mechanisms underlying cardiomyopathies. The identification of over a thousand mutations across approximately 100 genes underscores the complexity of pathological cardiac remodeling. This has prompted a paradigm shift from traditional morphology- and physiology-based classifications toward genotype-driven frameworks. High-throughput sequencing technologies now facilitate early genetic diagnosis, often preceding evident clinical symptoms [11]. The most common genetic causes of HCM are pathogenic variants (PVs) in sarcomeric genes, particularly MYH7 (β-myosin heavy chain) and MYBPC3 (myosin binding protein C), together accounting for over 50% of cases. Other implicated genes include TNNT2, TNNI3, TPM1, ACTC1, MYL2, and MYL3. These genes encode key components of the contractile apparatus and calcium sensitivity. The majority of PVs are missense mutations that disrupt sarcomeric function, ATPase activity, and calcium homeostasis, resulting in myocyte disarray, hypertrophy, and fibrosis. In rarer cases, mutations in non-sarcomeric genes, such as CSRP3, TCAP, VCL, and TTN, affect Z-disc or cytoskeletal integrity. Restrictive cardiomyopathy (RCM) shares a genetic basis with HCM, frequently involving TNNI3, MYH7, MYBPC3, and MYPN. Mutations in these genes disrupt sarcomeric structure and calcium regulation, leading to diastolic dysfunction and biatrial enlargement. DCM has a broad genetic spectrum. Titin truncating variants (TTNtv) are the most frequent, impairing sarcomere elasticity and contributing to familial DCM. LMNA variants disrupt the nuclear envelope and cytoskeletal architecture, increasing arrhythmogenic risk. Other notable genes include MYH7, MYPN, RBM20, SCN5A, DSP, TNNT2, and TPM1, involving sarcomeric, cytoskeletal, spliceosomal, and ion channel pathways. Left ventricular noncompaction (LVNC) is genetically heterogeneous, with frequent involvement of MYH7, MYBPC3, TTN, and ACTC1. These mutations interfere with embryonic myocardial compaction, leading to excessive trabeculation, systolic dysfunction, arrhythmias, and thromboembolic complications. ARVC is most often associated with desmosomal gene mutations, particularly in PKP2, DSC2, DSG2, and DSP. These genes encode cell–cell adhesion proteins, and their dysfunction leads to mechanical uncoupling of cardiomyocytes. The resulting fibroadipose myocardial replacement creates a substrate for arrhythmias, particularly under physical stress [12]. Mutations in the DES gene, which encodes the intermediate filament protein desmin, are known to cause various cardiomyopathies and atrial fibrillation due to their impact on cytoskeletal stability in cardiomyocytes. Ebrahim et al. (2025) investigated a heterozygous DES missense mutation (c.380G>C, p.R127P) in a large six-generation Kuwaiti family with a history of diverse cardiomyopathies, sudden cardiac death, conduction disease, and atrial fibrillation [13]. Functional analyses revealed a severe defect in desmin filament assembly. Co-expression with wild-type desmin demonstrated dominant-negative effects, supporting the mutation’s pathogenicity. The variant is absent or extremely rare in population databases and affects a highly conserved residue. Based on ACMG guidelines, the authors classified DES-p.R127P as likely pathogenic, emphasizing its clinical relevance for genetic counseling and disease management [13]. Buckley et al. analyzed over 630,000 patients with cardiomyopathy using global electronic health records and found a high prevalence of atrial fibrillation (AF), particularly in dilated (44.4%) and restrictive (42.5%) types. AF was linked to increased all-cause mortality in hypertrophic and dilated cardiomyopathies, and it raised the risk of hospitalization, new-onset heart failure, and stroke across all cardiomyopathy subtypes [14]. Moreover, a large-scale analysis of the UK Biobank cohort identified that early-onset atrial fibrillation (before 45 years of age) is significantly associated with an increased prevalence of pathogenic variants in core cardiomyopathy genes, notably TTN, MYBPC3, and PKP2, emphasizing the potential value of genetic screening in these patients [15]. Emerging evidence suggests that young patients with AF may also carry a genetic susceptibility to inherited ion channel or cardiomyopathic disorders—even when standard echocardiograms appear normal [16]. Therefore, alongside routine evaluation for newly diagnosed AF, incorporating genetic testing for rare pathogenic variants, advanced imaging, and regular screening could help uncover occult cardiomyopathy [17]. Although mounting evidence underscores the significant role of genetic factors in AF—particularly in younger patients—the optimal integration of these insights into clinical practice remains an ongoing challenge. In this review, we critically assess current genetic testing strategies and examine their clinical implications for personalized patient management.

2. Materials and Methods

This review was conducted through a comprehensive analysis of the published literature, including GWAS, whole-exome and whole-genome sequencing studies, clinical cohort analyses, and current guideline recommendations. Relevant articles were identified using databases such as PubMed, Embase, and Google Scholar, with search terms including “early-onset atrial fibrillation”, “genetic testing in AF”, “atrial cardiomyopathy”, “AF and cardiomyopathy”, and “polygenic risk scores in AF”. Studies were included if they focused on the genetic contributions to early-onset atrial fibrillation, investigated monogenic or polygenic risk factors, evaluated the role of genetic testing in clinical management and risk stratification, or included large-scale population-based genetic studies or clinically relevant cohort studies. Studies were excluded if they primarily addressed atrial fibrillation in older adults (>65 years) without genetic considerations, were limited to case reports or small-scale studies lacking statistical power, or did not include genetic analysis or relevant clinical outcomes (Figure 2).
The genetic data analysis incorporated findings from sequencing efforts such as targeted gene panels, exome sequencing, and GWAS. Emphasis was placed on genes implicated in cardiomyopathies and inherited arrhythmia syndromes. Current guidelines from major cardiology societies, including the ESC and AHA/ACC, were reviewed to evaluate recommendations regarding genetic testing in early-onset AF. All selected studies were systematically reviewed, and findings were synthesized to highlight major trends in genetic predisposition, the clinical implications of genetic testing, and future directions in personalized medicine for AF management (Table 1).

3. Clinical and Genetic Landscape of Early-Onset Atrial Fibrillation

The independent link between AF and increased mortality is well documented in older populations. However, less is known about younger patients with AF, despite the absence of traditional risk factors. Early observations linking a family history of AF to increased risk provided initial evidence of a heritable component to the disease. In families with a clear hereditary pattern, Mendelian inheritance has enabled linkage analyses to uncover rare variants. The first mutation identified via this approach was a gain-of-function (p.Ser140Gly) variant in the KCNQ1 gene—which encodes a subunit of the cardiac IKs channel—resulting in reduced action potential duration and refractory period, thereby predisposing affected individuals to persistent AF. Notably, KCNQ1 mutations have also been implicated in long QT and short QT syndromes. Since this discovery, nearly 40 additional genes harboring rare mutations associated with familial and early-onset AF have been reported. Although many of these genes encode ion channel components, an increasing number involve non-ion channel proteins, such as transcription factors, myocardial structural elements, and signaling molecules. Experimental models have further revealed that such mutations may disrupt sarcomere structure, impair calcium binding, and reduce conduction velocity—mechanisms that contribute to AF pathogenesis. More recently, rare variants in genes traditionally linked to dilated cardiomyopathy have been associated with early-onset AF even in the absence of overt structural abnormalities [9]. Studies have revealed that early-onset AF is frequently associated with rare genetic variants in genes implicated in inherited cardiomyopathy and arrhythmia syndromes, suggesting that in some cases, AF may represent the initial manifestation of an underlying genetic disorder. For example, sequencing of a 145-gene panel for cardiomyopathy and arrhythmia identified pathogenic or likely pathogenic variants in 16.8% of those diagnosed with AF before age 30 [18,19]. Similarly, among 23 unrelated patients with AF onset before age 45 who had normal echocardiograms and no other identifiable causes, 24% carried a pathogenic or likely pathogenic variant mainly involving cardiomyopathy-associated genes [20]. In a sensitivity analysis excluding participants with pre-existing cardiovascular risk factors, heart failure, or echocardiographic signs of cardiomyopathy, TTN LOF variants were present in 2.1% of cases versus 1.1% of controls (OR, 1.76; P  =  3.42 × 10−2). Notably, among individuals with AF onset before age 30, 6.5% carried a TTN LOF variant (OR, 5.94; P  =  1.65 × 10−5), and carriers experienced AF approximately 5.3 years earlier than noncarriers. Analysis of rare loss-of-function variants across candidate genes demonstrated a significant association between TTN LOF variants and early-onset AF (OR, 2.16; P  =  1.55 × 10−3). Restricting the analysis to exons with high cardiac expression further strengthened this association (OR, 4.41; P  =  7.34 × 10−4) [19].
In a large-scale, population-based genomic study, Barrett et al. demonstrated that early-onset atrial fibrillation (EOAF) is a strong clinical marker of cardiomyopathy (CM) risk in individuals harboring TTNtv in highly expressed cardiac exons (hiPSI). The prevalence of CM reached 33% in TTNtv carriers with early AF, a more than fivefold increase compared to individuals without TTNtv but with early AF (6%), and 80-fold higher than the general population. Notably, AF often preceded CM diagnosis, supporting its role as an early phenotypic manifestation of TTNtv-mediated disease. These findings suggest that integrating AF status with TTN genotype may enhance risk stratification for cardiomyopathy in population screening efforts [21].
Rudaka et al. conducted a diagnostic-level exome sequencing study on 54 Latvian patients with EOAF lacking traditional risk factors. Pathogenic or likely pathogenic variants were identified in 24% of cases, exclusively in cardiomyopathy-associated genes, with no variants found in traditional arrhythmia genes. Truncating variants in TTN were most frequent, including two likely founder variants (p.Gln4566Ter and p.Arg27414Ter). In 5 of 13 patients with early-onset AF with P/LP variants in cardiomyopathy genes, initially, normal echocardiograms were later followed by ventricular dilation on cardiac MRI, consistent with evolving cardiomyopathy. These results support the concept that EOAF may represent an early electrical phenotype of cardiomyopathy and underscore the utility of genetic testing and cardiac imaging in these patients [22]. In spite of these findings, the impact of rare genetic variants on long-term clinical outcomes in early-onset AF remains undefined. In conditions such as hypertrophic and dilated cardiomyopathy, Brugada syndrome, and long QT syndrome, genotype-positive patients consistently exhibit worse outcomes, including higher rates of malignant ventricular arrhythmias, progression to end-stage heart failure, and increased mortality. Based on these observations, it has been hypothesized that disease-associated rare variants in patients with early-onset AF would correlate with a higher risk of mortality and that there might be an interaction between genotype-positive status and younger age at diagnosis regarding mortality risk. In a prospective observational cohort of 1293 patients diagnosed with AF before the age of 66, sequencing with ion channelopathy and cardiomyopathy gene panels identified disease-associated variants in 10% of cases, predominantly in cardiomyopathy-related genes. After following for a median of 9.9 years (IQR 6.9–13.2 years), Yoneda et al. reported that 219 patients (16.9%) died during the follow-up period. Genetic variants were detected across all groups defined by baseline left ventricular ejection fraction (LVEF) at enrollment, with LVEF independently associated with mortality risk both in participants with reduced (<50%) and preserved (≥50%) LVEF. Notably, most individuals with depressed LVEF did not harbor a disease-associated variant. Among participants carrying disease-associated variants, all-cause mortality was markedly higher in those with reduced LVEF. There were 73 cardiomyopathy-related deaths, 40 sudden deaths, and 10 stroke-related deaths, indicating that adverse outcomes are often driven by the underlying cardiomyopathy rather than AF itself. Whole-genome sequencing identified disease-associated rare variants in 10.1% of the cohort (131 patients). Of these, the majority were found in cardiomyopathy (CM) genes—with 93 carriers in Dilated CM (DCM; OMIM #604145) genes, 43 in Hypertrophic CM (HCM; OMIM #192600) genes, and 37 in Arrhythmogenic CM (AC/ARVC; OMIM #107970) genes—while only 15 patients carried variants associated with channelopathies: 2 (0.2%) variants for Brugada syndrome, 12 (0.9%) for LQTS, and 1 (0.1%) for CPVT [4,9]. Notably, patients with a disease-associated variant had a higher mortality rate (24% vs. 16% in those without) and multivariable analysis confirmed that variant status significantly increased the risk of all-cause mortality, particularly among those diagnosed with AF at a younger age. When stratified by specific genes, the most prevalent variants were observed in TTN (26% mortality among 38 carriers), MYH7 (33% mortality among 18 carriers), and LMNA (22% mortality among 9 carriers), with no deaths observed among carriers of MYH6 (0/10) or KCNQ1 (0/8). These findings highlight the prognostic significance of rare, primarily CM-related genetic variants in early-onset AF [23]. Recent findings have increasingly emphasized the need to distinguish whether rare genetic variants associated with early-onset AF contribute directly to arrhythmogenesis or indirectly through the development of a cardiomyopathic substrate. For instance, Huang et al. [24] demonstrated that TTN variants confer an increased risk of AF independently of overt cardiomyopathy, although interplay between subclinical structural remodeling and arrhythmogenesis remains possible. Using the UK Biobank exome sequencing cohort confirmed the association between TTN truncating variants (TTNtvs) and an increased risk of AF and DCM. Notably, TTNtvs and polygenic risk scores (PRSs) showed additive effects with traditional AF risk factors, indicating that genetic factors contribute to AF risk beyond modifiable clinical factors. Even after excluding participants with DCM, TTNtv remained associated with a higher risk of AF, suggesting a potential independent role in AF development, possibly through subclinical structural remodeling. In participants who developed AF, TTNtvs were also linked to a higher risk of DCM, underscoring the importance of long-term cardiac monitoring for TTNtv carriers and their at-risk relatives. Additionally, the study highlighted the importance of risk factor management, even in those with high genetic risk. Individuals with TTNtvs or an elevated PRS but no clinical risk factors had a lower AF risk than those with low genetic risk and multiple risk factors. These findings suggest that genetic data could enhance AF risk stratification, guide early prevention strategies, and support personalized management in at-risk individuals through targeted lifestyle modifications and medical interventions. These observations highlight the complex relationship between genetic and epigenetic factors in early-onset AF and underscore the importance of considering both direct electrophysiological mechanisms and indirect structural pathways (Figure 3).
These observations emphasize the potential importance of incorporating genetic testing into the clinical assessment of early-onset AF to improve risk stratification and guide personalized management strategies.

4. Atrial Cardiomyopathy and Early Onset Atrial Fibrillation

Unlike ventricular cardiomyopathies such as dilated, hypertrophic, and arrhythmogenic right ventricular cardiomyopathy, which are diagnosed based on well-defined structural abnormalities, the recent consensus on atrial cardiomyopathy (AtCM) proposes that a diagnosis may be established with a broad array of alterations in atrial electrical properties, chamber size, or contractile function. These changes can be detected using noninvasive methods, including ECG tracings (with or without Holter monitoring or invasive electrophysiological studies), transthoracic echocardiography, or cardiac MRI [25].
Primary atrial cardiomyopathy arises from variants in genes that are functionally active in the atria and play key roles in atrial development and the maintenance of electrical, structural, and metabolic properties. For instance, variants in the NPPA gene, which encodes atrial natriuretic peptide A, have been linked to a distinctive phenotype characterized by massive bi-atrial dilation, early supraventricular arrhythmias, and progressive contractile dysfunction leading to atrial standstill [26]. Similarly, mutations in the MYL4 gene, which encodes the atrial-selective essential myosin light chain, have been associated with both electrical and mechanical defects [27,28].
Notably, genes such as SCN5A and LMNA, despite their widespread expression, can also contribute to atrial standstill, although they are more commonly associated with extra-atrial manifestations [29,30]. In LMNA cardiomyopathy, atrial fibrillation (AF) often precedes ventricular dysfunction and is linked to a distinct intrinsic atrial myopathy, evidenced by reduced left atrial strain on echocardiography; this strain reduction is independent of loading conditions, predicts incident AF with a fourfold increased risk, and may offer a low-cost, early marker for atrial disease progression and monitoring [31]. Ahlberg et al. observed a significant enrichment of TTNtv in familial and early-onset lone AF, with validation in independent cohorts indicating that TTNtvs are a major genetic contributor to this condition. Experimental studies in a CRISPR/Cas9-modified zebrafish model further demonstrated that TTNtvs lead to disrupted sarcomere structure, increased atrial fibrosis, and electrophysiological abnormalities, such as prolonged PR intervals [32]. Considering the potential development of atrial cardiomyopathy in diverse clinical contexts is essential, and a high index of suspicion should prompt targeted electrical and imaging investigations. Recognizing atrial cardiomyopathy is practically relevant, especially for predicting AF recurrence after interventions such as cardioversion or ablation and for guiding thromboembolic prophylaxis decisions. Although the genetics of atrial cardiomyopathy is still in its early stages—with causative rare variants proving useful in Mendelian forms of disease, the role of genetic testing in predicting individual risk remains largely unestablished [25]. Advances in polygenic risk scores derived from common SNPs have shown incremental value in AF risk stratification, sometimes equaling the impact of single rare pathogenic variants [33,34]. However, cohort studies indicate that known genes and loci account for only a small fraction of AF heritability [35], which currently limits the utility of routine genetic testing. A deeper understanding of the genetic basis of atrial cardiomyopathy may help explain the missing heritability of AF and yield novel risk markers for AF, heart failure, and stroke. Finally, emerging evidence suggests that atrial fibrillation in younger patients may represent the initial presentation of an underlying atrial cardiomyopathy driven by rare variants in cardiomyopathy or arrhythmia syndrome genes. Despite data indicating the potential utility of genetic testing for AtCM, current guidelines from major scientific societies do not yet endorse its routine use [36].

5. Current Guideline Recommendation on Genetic Testing in Atrial Fibrillation

European Society of Cardiology’s Guidelines do not provide a recommendation for genetic testing in early-onset atrial fibrillation, although an increasing number of common genetic polymorphisms and variations discovered through sequencing have been linked to AF. These genetic factors can be aggregated into instruments, which yield cumulative risk estimates that exceed those associated with single, monogenic AF mutations. Polygenic risk scores, which combine this genetic information, enhance the prediction of AF by providing additional insights beyond traditional risk factors and will likely improve further as more AF-associated variants are identified. Ultimately, polygenic and genome-wide risk scores could help pinpoint individuals at the highest risk for targeted AF screening. However, because such genetic data are not yet widely available, their clinical applicability and cost-effectiveness still need to be demonstrated [27]. On the other hand, the 2023 ACC/AHA guidelines assign a Class IIb recommendation for genetic testing in patients with atrial fibrillation under 45 years of age. Additionally, those under 30 with unexplained AF may be considered for an electrophysiological study to evaluate and treat supraventricular tachycardia, which is a potential trigger for AF, also under a Class IIb recommendation [17]. Finally, the consensus document from European, US, Latin American, and Asian-Pacific societies recommends considering genetic testing for individuals with familial AF who are under 60 years of age [10].

6. Clinical Implications of Genetic Testing

Advances in our understanding of the genetic underpinnings of AF emphasize the importance of integrating genetic testing for early-onset AF into clinical practice. Genetic testing should be performed by an interdisciplinary team, comprising cardiologists specializing in electrophysiology and cardiomyopathies, cardiovascular geneticists, and genetic counselors. The ACMG currently advises the reporting of secondary findings for many genes implicated in early-onset AF (e.g., TTN, LMNA, MYBPC3, KCNQ1, and PKP2) regardless of the primary indication for testing [37]. When genetic testing is pursued specifically for early-onset AF, a comprehensive evaluation of supporting and opposing factors is essential. Favorable indicators include very early disease onset (<45 years) or a family history of AF or cardiomyopathy in individuals under 65, as well as imaging evidence suggestive of ventricular cardiomyopathy, such as increased chamber volumes or subtly reduced contractile function. Additionally, clinical features pointing to a specific monogenic defect—such as early-onset AF with conduction disease or ventricular arrhythmias (as seen with LMNA mutations) or with QT abnormalities (as observed with KCNQ1 mutations)—should raise suspicion of a genetic cause. ECG can also offer clues, including bundle branch block, atrioventricular block, T-wave inversions, or QRS abnormalities, indicative of underlying cardiomyopathy. Conversely, AF typically associated with common risk factors—such as obesity, diabetes, hypertension, sedentary lifestyle, sleep apnea, or smoking—predominantly affects older individuals, making age the strongest marker for a non-genetic etiology. Nevertheless, some risk factors are age-independent, and others, like endurance sports, are prevalent in younger populations. Moreover, toxic exposures (alcohol, drugs) and hormonal imbalances (hyperthyroidism) can also trigger AF in younger patients [38,39]. The primary objective of genetic testing in early-onset AF is to identify carriers of pathogenic or likely pathogenic (P/LP) variants that underlie inherited cardiomyopathies and arrhythmia syndromes. Consequently, gene panels focusing on cardiomyopathy and arrhythmia should be considered, with particular emphasis on those genes with robust evidence linking them to these conditions, especially those for which P/LP variants are deemed actionable by the ACMG. Furthermore, the identification of a cardiomyopathy variant should prompt rigorous clinical and instrumental follow-up to monitor for the eventual emergence of a phenotype, inform sudden cardiac death risk stratification, and guide decisions regarding potential implantable cardioverter-defibrillator (ICD) implantation. Finally, identifying a rare cardiomyopathy or arrhythmia syndrome variant allows for cascade screening to detect at-risk family members for heart failure and sudden cardiac death [40].

7. Challenges, Limitations, and Future Directions

One of the biggest challenges is related to the interpretation and management of variants of uncertain significance (VUS). Yoneda et al. highlighted that most patients with early-onset AF carry a VUS [41]. Variants initially classified as VUS or pathogenic may be reclassified over time as new evidence emerges, including validated biomarkers, additional cases or family studies confirming or refuting pathogenicity, functional research, or the discovery of novel causative genes. Conversely, it is rare for a variant initially deemed benign to be later classified as pathogenic, though exceptions may occur with rare synonymous variants that introduce cryptic splice sites identified through functional studies. Regular reassessment of genetic data, incorporating familial segregation and functional evidence, is essential to reduce clinical uncertainty. While a VUS remains clinically inactionable, its reclassification as pathogenic can have significant clinical implications, including enhanced monitoring of carriers, early therapeutic interventions, evaluation of concealed arrhythmogenic risk, and consideration of prenatal or pre-implantation genetic diagnosis [42]. A further challenge in patients with early-onset AF with genetic positivity, particularly carriers of LMNA pathogenic or likely pathogenic variants, lies in the management of thromboembolic risk. As shown by Chen et al. [43], LMNA p.A242V variants were implicated in familial cases of ARVC complicated by right ventricular failure and cerebral thromboembolism, suggesting a direct contribution of genetic background to thromboembolic complications. Furthermore, evidence from van Rijsingen et al. [44] demonstrated that LMNA mutation carriers exhibit a significantly increased risk of both arterial and venous thromboembolic events, independent of conventional risk factors, such as atrial tachyarrhythmias and reduced left ventricular function. Laboratory studies further suggested that LMNA mutation carriers, even without overt cardiac disease, possess a prothrombotic phenotype characterized by altered platelet function and enhanced thrombin generation. These findings raise important questions about whether conventional risk stratification tools such as the CHA2DS2-VA score are sufficient in genetically predisposed patients or whether a genotype-informed approach should guide anticoagulation decisions. Given the lack of robust prospective data and the observed heightened thromboembolic risk in LMNA mutation carriers independent of traditional risk factors, there is a critical need to integrate genetic information into anticoagulation strategies. Future research is urgently needed to determine optimal anticoagulation strategies in this vulnerable population. Among the limitations, the primary concern is the cost of genetic testing and data analysis. Cost-effectiveness studies are necessary, and careful patient selection is essential to minimize healthcare expenditures and avoid inconclusive outcomes. A thorough family history assessment and the exclusion of secondary causes of AF in otherwise healthy individuals are crucial to prevent unnecessary testing. Genetic testing in early-onset AF represents a promising avenue for improved prognostic stratification and to enhance clinical and cardiovascular imaging surveillance for carriers of pathogenic or likely pathogenic (P/LP) genetic variants. Additionally, it offers the opportunity for cascade testing in at-risk family members. To ensure accurate interpretation of results, especially in cases of VUS or inconclusive findings that may cause unnecessary anxiety, collaboration between cardiologists with genetic expertise and clinical geneticists is essential for effective personalized medicine.

8. Conclusions

In summary, the integration of genetic testing into the clinical management of early-onset atrial fibrillation (AF) offers significant potential for improving risk stratification, guiding therapeutic decisions, and enabling the early detection of inherited cardiomyopathies and arrhythmia syndromes. Advances in genetic research have highlighted the importance of rare pathogenic variants, particularly in genes like TTNLMNA, and KCNQ1, while polygenic risk scores provide additional insights into the complex interplay of genetic and clinical risk factors. Although current guidelines offer limited recommendations for genetic testing, particularly in younger patients with AF, the expanding evidence base underscores the value of tailored genetic evaluation. Additionally, cascade testing of at-risk relatives can facilitate early diagnosis and preventive care, further reducing the burden of adverse cardiovascular outcomes. Nevertheless, challenges remain, including the interpretation of VUS, ensuring equitable access to testing, and the need for interdisciplinary collaboration to optimize the clinical application of genetic data. Future large-scale, multi-ethnic studies and ongoing re-evaluation of genetic variants are essential to refine classification frameworks and enhance predictive accuracy. Ultimately, a personalized, genetics-informed approach to early-onset AF management could significantly improve patient outcomes, underscoring the need for continued research, clinical integration, and guideline adaptation in this rapidly evolving field.

Author Contributions

A.L.: Conceptualization, Methodology, Formal analysis, Investigation, Resources, Data Curation, Writing—Original Draft, Writing—Review and Editing, Supervision; T.F.: Conceptualization, Methodology, Formal analysis, Data Curation, Writing—Review and Editing, Supervision; G.S.: Conceptualization, Methodology, Formal analysis, Data Curation Writing—Review and Editing, Supervision, Project administration; G.C.: Conceptualization, Methodology, Formal analysis, Investigation, Resources, Data Curation Writing—Review and Editing, Supervision, Project administration. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
AFAtrial Fibrillation
AFLAtrial Flutter
AtCMAtrial Cardiomyopathy
GWASGenome-Wide Association Study
eQTLExpression Quantitative Trait Locus
BrSBrugada Syndrome
EOAFEarly-Onset Atrial Fibrillation
LOFLoss of Function
LQTSLong QT Syndrome
SQTSShort QT Syndrome
TTNTitin
CPVTCatecholaminergic Polymorphic Ventricular Tachycardia
P/LPPathogenic or Likely Pathogenic
IKsSlow Delayed Rectifier Potassium Current
DCMDilated Cardiomyopathy
OMIMOnline Mendelian Inheritance in Man
HCMHypertrophic Cardiomyopathy
ACM/ARVCArrhythmogenic Cardiomyopathy/Arrhythmogenic Right Ventricular Cardiomyopathy
PRSPolygenic Risk Score
CPVTCatecholaminergic Polymorphic Ventricular Tachycardia
LQTSLong QT Syndrome
SCNSodium Channel Voltage-Gated
AtCMAtrial Cardiomyopathy
ECGElectrocardiogram
MRIMagnetic Resonance Imaging
TTNtvTitin-Truncating Variants
PRSPolygenic Risk Score
NPPANatriuretic Peptide Precursor A
ICDImplantable Cardioverter-Defibrillator
ACMGAmerican College of Medical Genetics
VCLVinculin
VUSVariant of Uncertain Significance
ACC/AHAAmerican College of Cardiology/American Heart Association

References

  1. Shantsila, E.; Choi, E.K.; Lane, D.A.; Joung, B.; Lip, G.Y.H. Atrial fibrillation: Comorbidities, lifestyle, and patient factors. The Lancet regional health. Europe 2024, 37, 100784. [Google Scholar] [CrossRef]
  2. Čarná, Z.; Osmančík, P. The effect of obesity, hypertension, diabetes mellitus, alcohol, and sleep apnea on the risk of atrial fibrillation. Physiol. Res. 2021, 70 (Suppl. S4), S511–S525. [Google Scholar] [CrossRef]
  3. Jiao, M.; Liu, C.; Liu, Y.; Wang, Y.; Gao, Q.; Ma, A. Estimates of the global, regional, and national burden of atrial fibrillation in older adults from 1990 to 2019: Insights from the Global Burden of Disease study 2019. Front. Public Health 2023, 11, 1137230. [Google Scholar] [CrossRef]
  4. Ohlrogge, A.H.; Brederecke, J.; Schnabel, R.B. Global Burden of Atrial Fibrillation and Flutter by National Income: Results from the Global Burden of Disease 2019 Database. J. Am. Heart Assoc. 2023, 12, e030438. [Google Scholar] [CrossRef]
  5. Choi, S.H.; Jurgens, S.J.; Xiao, L.; Hill, M.C.; Haggerty, C.M.; Sveinbjörnsson, G.; Morrill, V.N.; Marston, N.A.; Weng, L.C.; Pirruccello, J.P.; et al. Sequencing in over 50,000 cases identifies coding and structural variation underlying atrial fibrillation risk. Nat. Genet. 2025, 57, 548–562. [Google Scholar] [CrossRef]
  6. Ackerman, M.J.; Priori, S.G.; Willems, S.; Berul, C.; Brugada, R.; Calkins, H.; Camm, A.J.; Ellinor, P.T.; Gollob, M.; Hamilton, R.; et al. HRS/EHRA expert consensus statement on the state of genetic testing for the channelopathies and cardiomyopathies this document was developed as a partnership between the Heart Rhythm Society (HRS) and the European Heart Rhythm Association (EHRA). Heart Rhythm. 2011, 8, 1308–1339. [Google Scholar] [CrossRef]
  7. Roselli, C.; Chaffin, M.D.; Weng, L.C.; Aeschbacher, S.; Ahlberg, G.; Albert, C.M.; Almgren, P.; Alonso, A.; Anderson, C.D.; Aragam, K.G.; et al. Multi-ethnic genome-wide association study for atrial fibrillation. Nat. Genet. 2018, 50, 1225–1233. [Google Scholar] [CrossRef]
  8. Roselli, C.; Surakka, I.; Olesen, M.S.; Sveinbjornsson, G.; Marston, N.A.; Choi, S.H.; Holm, H.; Chaffin, M.; Gudbjartsson, D.; Hill, M.C.; et al. Meta-analysis of genome-wide associations and polygenic risk prediction for atrial fibrillation in more than 180,000 cases. Nat. Genet. 2025, 57, 539–547. [Google Scholar] [CrossRef]
  9. Cheng, Y.J.; Deng, H.; Wei, H.Q.; Lin, W.D.; Liang, Z.; Chen, Y.; Dong, Y.; Fang, X.H.; Liao, H.T.; Wu, S.L.; et al. Association Between Age at Diagnosis of Atrial Fibrillation and Subsequent Risk of Ischemic Stroke. J. Am. Heart Assoc. 2025, 14, e038367. [Google Scholar] [CrossRef]
  10. Wilde, A.A.M.; Semsarian, C.; Márquez, M.F.; Shamloo, A.S.; Ackerman, M.J.; Ashley, E.A.; Sternick, E.B.; Barajas-Martinez, H.; Behr, E.R.; Bezzina, C.R.; et al. European Heart Rhythm Association (EHRA)/Heart Rhythm Society (HRS)/Asia Pacific Heart Rhythm Society (APHRS)/Latin American Heart Rhythm Society (LAHRS) Expert Consensus Statement on the state of genetic testing for cardiac diseases. Europace 2022, 24, 1307–1367. [Google Scholar] [CrossRef]
  11. Kodo, K.; Yamagishi, H. The Role of Genetics in Cardiomyopathy. In Pediatric Cardiology: Fetal, Pediatric, and Adult Congenital Heart Diseases; Springer International Publishing: Cham, Switzerland, 2024; pp. 2473–2502. [Google Scholar]
  12. Kim, K.H.; Pereira, N.L. Genetics of Cardiomyopathy: Clinical and Mechanistic Implications for Heart Failure. Korean Circ. J. 2021, 51, 797–836. [Google Scholar] [CrossRef]
  13. Ebrahim, M.A.; Ali, N.M.; Albash, B.Y.; Al Sayegh, A.H.; Ahmad, N.B.; Voß, S.; Klag, F.; Groß, J.; Holler, S.; Walhorn, V.; et al. Phenotypic Diversity Caused by the DES Missense Mutation p.R127P (c.380G > C) Contributing to Significant Cardiac Mortality and Morbidity Associated with a Desmin Filament Assembly Defect. Circ. Genom. Precis. Med. 2025, e004896. [Google Scholar] [CrossRef] [PubMed]
  14. Buckley, B.J.R.; Harrison, S.L.; Gupta, D.; Fazio-Eynullayeva, E.; Underhill, P.; Lip, G.Y.H. Atrial Fibrillation in Patients with Cardiomyopathy: Prevalence and Clinical Outcomes from Real-World Data. J. Am. Heart Assoc. 2021, 10, e021970. [Google Scholar] [CrossRef]
  15. Bech, Q.; Vad, O.B.; Paludan-Müller, C.; Svendsen, J.H.; Olesen, M.S. Early-onset atrial fibrillation is a risk marker for cardiomyopathy: Genetic insights from the UK Biobank. Eur. Heart J. 2024, 45 (Suppl. S1), ehae666.445. [Google Scholar] [CrossRef]
  16. Chalazan, B.; Freeth, E.; Mohajeri, A.; Ramanathan, K.; Bennett, M.; Walia, J.; Halperin, L.; Roston, T.; Lazarte, J.; Hegele, R.A.; et al. Genetic testing in monogenic early-onset atrial fibrillation. Eur. J. Hum. Genet. EJHG 2023, 31, 769–775. [Google Scholar] [CrossRef]
  17. Joglar, J.A.; Chung, M.K.; Armbruster, A.L.; Benjamin, E.J.; Chyou, J.Y.; Cronin, E.M.; Deswal, A.; Eckhardt, L.L.; Goldberger, Z.D.; Gopinathannair, R.; et al. Peer Review Committee Members 2023 ACC/AHA/ACCP/HRS Guideline for the Diagnosis and Management of Atrial Fibrillation: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation 2024, 149, e1–e156. [Google Scholar] [CrossRef]
  18. Kim, J.A.; Chelu, M.G.; Li, N. Genetics of atrial fibrillation. Curr. Opin. Cardiol. 2021, 36, 281–287. [Google Scholar] [CrossRef]
  19. Choi, S.H.; Weng, L.C.; Roselli, C.; Lin, H.; Haggerty, C.M.; Shoemaker, M.B.; Barnard, J.; Arking, D.E.; Chasman, D.I.; Albert, C.M.; et al. Association Between Titin Loss-of-Function Variants and Early-Onset Atrial Fibrillation. JAMA 2018, 320, 2354–2364. [Google Scholar] [CrossRef]
  20. Goodyer, W.R.; Dunn, K.; Caleshu, C.; Jackson, M.; Wylie, J.; Moscarello, T.; Platt, J.; Reuter, C.; Smith, A.; Trela, A.; et al. Broad Genetic Testing in a Clinical Setting Uncovers a High Prevalence of Titin Loss-of-Function Variants in Very Early Onset Atrial Fibrillation. Circulation. Genom. Precis. Med. 2019, 12, e002713. [Google Scholar] [CrossRef]
  21. Schiabor Barrett, K.M.; Cirulli, E.T.; Bolze, A.; Rowan, C.; Elhanan, G.; Grzymski, J.J.; Lee, W.; Washington, N.L. Cardiomyopathy prevalence exceeds 30% in individuals with TTN variants and early atrial fibrillation. Genet. Med. Off. J. Am. Coll. Med. Genet. 2023, 25, 100012. [Google Scholar] [CrossRef]
  22. Rudaka, I.; Vilne, B.; Isakova, J.; Kalejs, O.; Gailite, L.; Rots, D. Genetic Basis of Early Onset Atrial Fibrillation in Patients without Risk Factors. J. Cardiovasc. Dev. Dis. 2023, 10, 104. [Google Scholar] [CrossRef]
  23. Yoneda, Z.T.; Anderson, K.C.; Ye, F.; Quintana, J.A.; O’Neill, M.J.; Sims, R.A.; Sun, L.; Glazer, A.M.; Davogustto, G.; El-Harasis, M.; et al. Mortality Among Patients with Early-Onset Atrial Fibrillation and Rare Variants in Cardiomyopathy and Arrhythmia Genes. JAMA Cardiol. 2022, 7, 733–741. [Google Scholar] [CrossRef]
  24. Huang, K.; Trinder, M.; Roston, T.M.; Laksman, Z.W.; Brunham, L.R. The Interplay Between Titin, Polygenic Risk, and Modifiable Cardiovascular Risk Factors in Atrial Fibrillation. Can. J. Cardiol. 2021, 37, 848–856. [Google Scholar] [CrossRef]
  25. Fatkin, D.; Huttner, I.G.; Johnson, R. Genetics of atrial cardiomyopathy. Curr. Opin. Cardiol. 2019, 34, 275–281. [Google Scholar] [CrossRef]
  26. Disertori, M.; Quintarelli, S.; Grasso, M.; Pilotto, A.; Narula, N.; Favalli, V.; Canclini, C.; Diegoli, M.; Mazzola, S.; Marini, M.; et al. Autosomal recessive atrial dilated cardiomyopathy with standstill evolution associated with mutation of Natriuretic Peptide Precursor A. Circ. Cardiovasc. Genet. 2013, 6, 27–36. [Google Scholar] [CrossRef]
  27. Peng, W.; Li, M.; Li, H.; Tang, K.; Zhuang, J.; Zhang, J.; Xiao, J.; Jiang, H.; Li, D.; Yu, Y.; et al. Dysfunction of Myosin Light-Chain 4 (MYL4) Leads to Heritable Atrial Cardiomyopathy with Electrical, Contractile, and Structural Components: Evidence from Genetically-Engineered Rats. J. Am. Heart Assoc. 2017, 6, e007030. [Google Scholar] [CrossRef]
  28. Gudbjartsson, D.F.; Holm, H.; Sulem, P.; Masson, G.; Oddsson, A.; Magnusson, O.T.; Saemundsdottir, J.; Helgadottir, H.T.; Helgason, H.; Johannsdottir, H.; et al. A frameshift deletion in the sarcomere gene MYL4 causes early-onset familial atrial fibrillation. Eur. Heart J. 2017, 38, 27–34. [Google Scholar] [CrossRef]
  29. Tan, R.B.; Gando, I.; Bu, L.; Cecchin, F.; Coetzee, W. A homozygous SCN5A mutation associated with atrial standstill and sudden death. Pacing Clin. Electrophysiol. PACE 2018, 41, 1036–1042. [Google Scholar] [CrossRef]
  30. Duparc, A.; Cintas, P.; Somody, E.; Bieth, E.; Richard, P.; Maury, P.; Delay, M. A cardio-neurological form of laminopathy: Dilated cardiomyopathy with permanent partial atrial standstill and axonal neuropathy. Pacing Clin. Electrophysiol. PACE 2009, 32, 410–415. [Google Scholar] [CrossRef]
  31. Tremblay-Gravel, M.; Ichimura, K.; Picard, K.; Kawano, Y.; Dries, A.M.; Haddad, F.; Lakdawala, N.K.; Wheeler, M.T.; Parikh, V.N. Intrinsic Atrial Myopathy Precedes Left Ventricular Dysfunction and Predicts Atrial Fibrillation in Lamin A/C Cardiomyopathy. Circ. Genom. Precis. Med. 2023, 16, e003480. [Google Scholar] [CrossRef]
  32. Ahlberg, G.; Refsgaard, L.; Lundegaard, P.R.; Andreasen, L.; Ranthe, M.F.; Linscheid, N.; Nielsen, J.B.; Melbye, M.; Haunsø, S.; Sajadieh, A.; et al. Rare truncating variants in the sarcomeric protein titin associate with familial and early-onset atrial fibrillation. Nat. Commun. 2018, 9, 4316. [Google Scholar] [CrossRef]
  33. Weng, L.C.; Preis, S.R.; Hulme, O.L.; Larson, M.G.; Choi, S.H.; Wang, B.; Trinquart, L.; McManus, D.D.; Staerk, L.; Lin, H.; et al. Genetic Predisposition, Clinical Risk Factor Burden, and Lifetime Risk of Atrial Fibrillation. Circulation 2018, 137, 1027–1038. [Google Scholar] [CrossRef]
  34. Khera, A.V.; Chaffin, M.; Aragam, K.G.; Haas, M.E.; Roselli, C.; Choi, S.H.; Natarajan, P.; Lander, E.S.; Lubitz, S.A.; Ellinor, P.T.; et al. Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations. Nat. Genet. 2018, 50, 1219–1224. [Google Scholar] [CrossRef]
  35. Nielsen, J.B.; Thorolfsdottir, R.B.; Fritsche, L.G.; Zhou, W.; Skov, M.W.; Graham, S.E.; Herron, T.J.; McCarthy, S.; Schmidt, E.M.; Sveinbjornsson, G.; et al. Biobank-driven genomic discovery yields new insight into atrial fibrillation biology. Nat. Genet. 2018, 50, 1234–1239. [Google Scholar] [CrossRef]
  36. Van Gelder, I.C.; Rienstra, M.; Bunting, K.V.; Casado-Arroyo, R.; Caso, V.; Crijns, H.J.G.M.; De Potter, T.J.R.; Dwight, J.; Guasti, L.; Hanke, T.; et al. 2024 ESC Guidelines for the management of atrial fibrillation developed in collaboration with the European Association for Cardio-Thoracic Surgery (EACTS). Eur. Heart J. 2024, 45, 3314–3414. [Google Scholar] [CrossRef]
  37. Miller, D.T.; Lee, K.; Gordon, A.S.; Amendola, L.M.; Adelman, K.; Bale, S.J.; Chung, W.K.; Gollob, M.H.; Harrison, S.M.; Herman, G.E.; et al. Secondary Findings Working Group Recommendations for reporting of secondary findings in clinical exome and genome sequencing 2021, 2021 update: A policy statement of the American College of Medical Genetics and Genomics (ACMG). Genet. Med. Off. J. Am. Coll. Med. Genet. 2021, 23, 1391–1398. [Google Scholar] [CrossRef]
  38. Abdulla, J.; Nielsen, J.R. Is the risk of atrial fibrillation higher in athletes than in the general population? A systematic review and meta-analysis. Europace 2009, 11, 1156–1159. [Google Scholar] [CrossRef]
  39. Marcus, G.M.; Vittinghoff, E.; Whitman, I.R.; Joyce, S.; Yang, V.; Nah, G.; Gerstenfeld, E.P.; Moss, J.D.; Lee, R.J.; Lee, B.K.; et al. Acute Consumption of Alcohol and Discrete Atrial Fibrillation Events. Ann. Intern. Med. 2021, 174, 1503–1509. [Google Scholar] [CrossRef]
  40. Kany, S.; Jurgens, S.J.; Rämö, J.T.; Christophersen, I.E.; Rienstra, M.; Chung, M.K.; Olesen, M.S.; Ackerman, M.J.; McNally, E.M.; Semsarian, C.; et al. Genetic testing in early-onset atrial fibrillation. Eur. Heart J. 2024, 45, 3111–3123. [Google Scholar] [CrossRef]
  41. Yoneda, Z.T.; Anderson, K.C.; Quintana, J.A.; O’Neill, M.J.; Sims, R.A.; Glazer, A.M.; Shaffer, C.M.; Crawford, D.M.; Stricker, T.; Ye, F.; et al. Early-Onset Atrial Fibrillation and the Prevalence of Rare Variants in Cardiomyopathy and Arrhythmia Genes. JAMA Cardiol. 2021, 6, 1371–1379. [Google Scholar] [CrossRef]
  42. Arbustini, E.; Behr, E.R.; Carrier, L.; van Duijn, C.; Evans, P.; Favalli, V.; van der Harst, P.; Haugaa, K.H.; Jondeau, G.; Kääb, S.; et al. Interpretation and actionability of genetic variants in cardiomyopathies: A position statement from the European Society of Cardiology Council on cardiovascular genomics. Eur. Heart J. 2022, 43, 1901–1916. [Google Scholar] [CrossRef] [PubMed]
  43. Chen, J.; Ma, Y.; Li, H.; Lin, Z.; Yang, Z.; Zhang, Q.; Wang, F.; Lin, Y.; Ye, Z.; Lin, Y. Rare and potential pathogenic mutations of LMNA and LAMA4 associated with familial arrhythmogenic right ventricular cardiomyopathy/dysplasia with right ventricular heart failure, cerebral thromboembolism and hereditary electrocardiogram abnormality. Orphanet J. Rare Dis. 2022, 17, 183. [Google Scholar] [CrossRef]
  44. van Rijsingen, I.A.; Bakker, A.; Azim, D.; Hermans-van Ast, J.F.; van der Kooi, A.J.; van Tintelen, J.P.; van den Berg, M.P.; Christiaans, I.; Lekanne Dit Deprez, R.H.; Wilde, A.A.; et al. Lamin A/C mutation is independently associated with an increased risk of arterial and venous thromboembolic complications. Int. J. Cardiol. 2013, 168, 472–477. [Google Scholar] [CrossRef]
Figure 1. Venn diagram showing the overlap of genes associated with early-onset AF and cardiomyopathies/inherited arrhythmia syndromes.
Figure 1. Venn diagram showing the overlap of genes associated with early-onset AF and cardiomyopathies/inherited arrhythmia syndromes.
Cardiogenetics 15 00015 g001
Figure 2. Flow diagram of manuscripts and studies included in our review.
Figure 2. Flow diagram of manuscripts and studies included in our review.
Cardiogenetics 15 00015 g002
Figure 3. Genetic and epigenetic mechanisms, alongside conventional risk factors such as hypertension, obesity, and lifestyle exposures, converge to drive early-onset atrial fibrillation.
Figure 3. Genetic and epigenetic mechanisms, alongside conventional risk factors such as hypertension, obesity, and lifestyle exposures, converge to drive early-onset atrial fibrillation.
Cardiogenetics 15 00015 g003
Table 1. Summary of systematically reviewed studies.
Table 1. Summary of systematically reviewed studies.
Ref.Study TypeMain Findings
1ReviewComorbidities and lifestyle factors influence AF burden
2ReviewHTN, diabetes, alcohol, and sleep apnea increase AF risk
3GBD analysisAF burden increasing globally in older adults
4GBD analysisAF varies by national income levels
5Genetic studyGenetic insights from 50,000 AF cases
6ConsensusGenetic testing guidance for inherited cardiac diseases
7GWASMulti-ethnic GWAS identified AF loci
8Meta-GWAS/PRSPolygenic risk prediction for AF improved
9Prospective cohortYounger age at AF diagnosis increases stroke risk
10ConsensusConsensus on genetic testing for cardiac diseases
11Book ChapterRole of genetics in pediatric/adult cardiomyopathy
12ReviewClinical implications of cardiomyopathy genetics
13NGS Genetic studyDSM p.R127P variant linked to high cardiac mortality
14Retrospective cohortAF in cardiomyopathy predicts poor outcomes
15Population studyEarly-onset AF is a marker for cardiomyopathy
16Genetic studyMonogenic variants in early-onset AF identified
17Guideline2023 ACC/AHA AF management guideline
18ReviewGenetic architecture of AF
19Case–control studyTTN LoF variants linked to early-onset AF
20Cohort studyHigh TTN LoF prevalence in early-onset AF
21Cohort studyTTNtv carriers with AF have high cardiomyopathy risk
22Genetic studyGenetic bases of early-onset AF without risk factors
23Cohort studyRare variants in early-onset AF predict higher mortality
24Population studyTitin and lifestyle interact in AF risk
25ReviewGenetic basis of atrial cardiomyopathy
26Case seriesNPPA mutation linked to atrial cardiomyopathy
27Animal modelMYL4 dysfunction causes atrial abnormalities
28Genetic studyMYL4 frameshift causes early-onset AF
29Case seriesSCN5A mutation leads to atrial standstill
30Case reportLMNA mutation linked to atrial standstill
31Genetic studyAtrial dysfunction precedes ventricular in LMNA mutation
32Retrospective cohortTTNtv linked to familial/early onset AF
33Genetic studyGenetic predisposition + clinical risk factors affect AF risk
34Genetic risk modelPRS for AF risk equivalent to monogenic mutations
35Polygenic risk scoreNew insights into AF biology from Biobank data
36GuidelineESC 2024 management of AF guideline recommendations
37GuidelineACMG 2021 secondary findings guidance
38MetanalysisAF risk higher in athletes than general population
39ReviewAcute alcohol consumption triggers AF episodes
40ReviewGenetic testing in early-onset AF
41Cohort studyRare variant prevalence in patients with early-onset AF
42Position statementESC guidance on cardiomyopathy variant interpretation
43Case seriesLMNA/LAMA4 mutations in familial ARVC
44Cohort studyLMNA mutation raises thromboembolic risk
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Laconi, A.; Fancello, T.; Solinas, G.; Casu, G. Novel Perspectives on Genetic Evaluation in Early-Onset Atrial Fibrillation: Clinical Implications and Future Directions. Cardiogenetics 2025, 15, 15. https://doi.org/10.3390/cardiogenetics15020015

AMA Style

Laconi A, Fancello T, Solinas G, Casu G. Novel Perspectives on Genetic Evaluation in Early-Onset Atrial Fibrillation: Clinical Implications and Future Directions. Cardiogenetics. 2025; 15(2):15. https://doi.org/10.3390/cardiogenetics15020015

Chicago/Turabian Style

Laconi, Angelo, Tatiana Fancello, Giuliana Solinas, and Gavino Casu. 2025. "Novel Perspectives on Genetic Evaluation in Early-Onset Atrial Fibrillation: Clinical Implications and Future Directions" Cardiogenetics 15, no. 2: 15. https://doi.org/10.3390/cardiogenetics15020015

APA Style

Laconi, A., Fancello, T., Solinas, G., & Casu, G. (2025). Novel Perspectives on Genetic Evaluation in Early-Onset Atrial Fibrillation: Clinical Implications and Future Directions. Cardiogenetics, 15(2), 15. https://doi.org/10.3390/cardiogenetics15020015

Article Metrics

Back to TopTop