Atrial fibrillation (AF) affects over 33 million individuals worldwide1 and has a complex heritability.2 We conducted the largest meta-analysis of genome-wide association studies for AF to date, consisting of over half a million individuals including 65,446 with AF. In total, we identified 97 loci significantly associated with AF including 67 of which were novel in a combined-ancestry analysis, and 3 in a European specific analysis. We sought to identify AF-associated genes at the GWAS loci by performing RNA-sequencing and expression quantitative trait loci (eQTL) analyses in 101 left atrial samples, the most relevant tissue for AF. We also performed transcriptome-wide analyses that identified 57 AF-associated genes, 42 of which overlap with GWAS loci. The identified loci implicate genes enriched within cardiac developmental, electrophysiological, contractile and structural pathways. These results extend our understanding of the biological pathways underlying AF and may facilitate the development of therapeutics for AF.

A family history of atrial fibrillation constitutes a substantial risk of developing the disease, however, the pathogenesis of this complex disease is poorly understood. We perform whole-exome sequencing on 24 families with at least three family members diagnosed with atrial fibrillation (AF) and find that titin-truncating variants (TTNtv) are significantly enriched in these patients (P = 1.76 × 10−6). This finding is replicated in an independent cohort of early-onset lone AF patients (n = 399; odds ratio = 36.8; P = 4.13 × 10−6). A CRISPR/Cas9 modified zebrafish carrying a truncating variant of titin is used to investigate TTNtv effect in atrial development. We observe compromised assembly of the sarcomere in both atria and ventricle, longer PR interval, and heterozygous adult zebrafish have a higher degree of fibrosis in the atria, indicating that TTNtv are important risk factors for AF. This aligns with the early onset of the disease and adds an important dimension to the understanding of the molecular predisposition for AF.

We present QTc data and register data, indicating that 26 cLQTS-associated variants neither had any effect on the QTc intervals nor on syncope propensity or overall mortality. Based on the frequency of individual gene variants, we suggest that the 10 variants frequently identified, assumed to relate to cLQTS, are less likely to associate with a dominant monogenic form of the disease.

Aims Atrial fibrillation (AF) is the most common type of cardiac arrhythmias, whose incidence is likely to increase with the aging of the population. It is considered a progressive condition, frequently observed as a complication of other cardiovascular disorders. However, recent genetic studies revealed the presence of several mutations and variants linked to AF, findings that define AF as a multifactorial disease. Due to the complex genetics and paucity of models, molecular mechanisms underlying the initiation of AF are still poorly understood. Here we investigate the pathophysiological mechanisms of a familial form of AF, with particular attention to the identification of putative triggering cellular mechanisms, using patient’s derived cardiomyocytes (CMs) differentiated from induced pluripotent stem cells (iPSCs). Methods and results Here we report the clinical case of three siblings with untreatable persistent AF whose whole-exome sequence analysis revealed several mutated genes. To understand the pathophysiology of this multifactorial form of AF we generated three iPSC clones from two of these patients and differentiated these cells towards the cardiac lineage. Electrophysiological characterization of patient-derived CMs (AF-CMs) revealed that they have higher beating rates compared to control (CTRL)-CMs. The analysis showed an increased contribution of the If and ICaL currents. No differences were observed in the repolarizing current IKr and in the sarcoplasmic reticulum calcium handling. Paced AF-CMs presented significantly prolonged action potentials and, under stressful conditions, generated both delayed after-depolarizations of bigger amplitude and more ectopic beats than CTRL cells. Conclusions Our results demonstrate that the common genetic background of the patients induces functional alterations of If and ICaL currents leading to a cardiac substrate more prone to develop arrhythmias under demanding conditions. To our knowledge this is the first report that, using patient-derived CMs differentiated from iPSC, suggests a plausible cellular mechanism underlying this complex familial form of AF.

Atrial fibrillation (AF) is the most common type of cardiac arrhythmia. The major AF susceptibility locus 4q25 establishes long-range interactions with the promoter of PITX2, a transcription factor gene with critical functions during cardiac development. While many AF-linked loci have been identified in genome-wide association studies, mechanistic understanding into how genetic variants, including those at the 4q25 locus, increase vulnerability to AF is mostly lacking. Here, we show that loss of pitx2c in zebrafish leads to adult cardiac phenotypes with substantial similarities to pathologies observed in AF patients, including arrhythmia, atrial conduction defects, sarcomere disassembly, and altered cardiac metabolism. These phenotypes are also observed in a subset of pitx2c+/− fish, mimicking the situation in humans. Most notably, the onset of these phenotypes occurs at an early developmental stage. Detailed analyses of pitx2c loss- and gain-of-function embryonic hearts reveal changes in sarcomeric and metabolic gene expression and function that precede the onset of cardiac arrhythmia first observed at larval stages. We further find that antioxidant treatment of pitx2c−/− larvae significantly reduces the incidence and severity of cardiac arrhythmia, suggesting that metabolic dysfunction is an important driver of conduction defects. We propose that these early sarcomere and metabolic defects alter cardiac function and contribute to the electrical instability and structural remodeling observed in adult fish. Overall, these data provide insight into the mechanisms underlying the development and pathophysiology of some cardiac arrhythmias and importantly, increase our understanding of how developmental perturbations can predispose to functional defects in the adult heart.

Aims  Left atrial (LA) volume and function impose significant impact on cardiovascular pathogenesis if compromised. We aimed at investigating the genetic architecture of LA volume and function using cardiac magnetic resonance imaging data. Methods and results  We used the UK Biobank, which is a large prospective population study with available phenotypic and genetic data. On a subset of 35 658 European individuals, we performed genome-wide association studies on five volumetric and functional LA variables, generated using a machine learning algorithm. In total, we identified 18 novel genetic loci, mapped to genes with known roles in cardiomyopathy (e.g. MYO18B, TTN, DSP, ANKRD1) and arrhythmia (e.g. TTN, CASQ2, MYO18B, C9orf3). We observed high genetic correlation between LA volume and function and stroke, which was most pronounced for LA passive emptying fraction (rg = 0.40, P = 4 × 10−6). To investigate whether the genetic risk of atrial fibrillation (AF) is associated with LA traits that precede overt AF, we produced a polygenetic risk score for AF. We found that polygenetic risk for AF is associated with increased LA volume and decreased LA function in participants without AF [LAmax 0.25 (mL/m2)/standard deviation (SD), 95% confidence interval (CI) (0.15; 0.36), P = 5.13 × 10−6; LAmin 0.21 (mL/m2)/SD, 95% CI (0.15; 0.28), P = 1.86 × 10−10; LA active emptying fraction −0.35%/SD, 95% CI (−0.43; −0.26), P = 3.14 × 10−14]. Conclusion  We report on 18 genetic loci associated with LA volume and function and show evidence for several plausible candidate genes important for LA structure.

BackgroundHundreds of genetic variants have been described as disease causing in dilated cardiomyopathy (DCM). Some of these associations are now being questioned. We aimed to identify the prevalence of previously DCM associated variants in the Exome Aggregation Consortium (ExAC), in order to identify potentially false‐positive DCM variants.MethodsVariants listed as DCM disease‐causing variants in the Human Gene Mutation Database were extracted from ExAC. Pathogenicity predictions for these variants were mined from dbNSFP v 2.9 database.ResultsOf the 473 DCM variants listed in HGMD, 148 (31%) were found in ExAC. The expected number of individuals with DCM in ExAC is 25 based on the prevalence in the general population. Yet, 35 variants were found in more than 25 individuals. In 13 genes, we identified all variants previously associated with DCM; four genes contained variants above our estimated cut‐off. Prediction tools found ExAC variants to be significantly more tolerated when compared to variants not found in ExAC (P = 0.004).ConclusionIn ExAC, we identified a higher genotype prevalence of variants considered disease‐causing than expected. More importantly, we found 13 genes in which all variants previously associated with DCM were identified in ExAC, questioning the association of these genes with the monogenic form of DCM.

Advances in clinical genetic testing have led to increased insight into the human genome, including how challenging it is to interpret rare genetic variation. In some cases, the ability to detect genetic mutations exceeds the ability to understand their clinical impact, limiting the advantage of these technologies. Obstacles in genomic medicine are many and include: understanding the level of certainty/uncertainty behind pathogenicity determination, the numerous different variant interpretation-guidelines used by clinical laboratories, delivering the certain or uncertain result to the patient, helping patients evaluate medical decisions in light of uncertainty regarding the consequence of the findings. Through publication of large publicly available exome/genome databases, researchers and physicians are now able to highlight dubious variants previously associated with different cardiac traits. Also, continuous efforts through data sharing, international collaborative efforts to develop disease-gene-specific guidelines, and computational analyses using large data, will indubitably assist in better variant interpretation and classification. This article discusses the current, and quickly changing, state of variant interpretation resources within cardiovascular genetic research, e.g., publicly available databases and ways of how cardiovascular genetic counselors and geneticists can aid in improving variant interpretation in cardiology.