Rare Variants Research Articles

Functional significance of CYP2B6 gene rare allelic variants identified in Japanese individuals

Cytochrome P450 2B6 (CYP2B6) catalyzes the metabolism of many drugs, including efavirenz and propofol. Genetic polymorphisms in CYP2B6 alter its enzymatic activity and substantially affect its pharmacokinetics. High-frequency variants, such as CYP2B6*6, are associated with the risk of developing side effects due to reduced CYP2B6 activity. However, the impact of rare alterations on enzyme function remains unknown, and some of these variants may significantly decrease the CYP2B6 activity. Therefore, in this study, we evaluated in vitro the functional alterations in 29 missense variants of the CYP2B6 gene identified in 8,380 Japanese individuals. Wild-type CYP2B6 and 29 rare CYP2B6 variants were transiently expressed in mammalian cells. The expression levels of variant CYP2B6 proteins in the microsomal fractions extracted from 293FT cells were assessed using western blotting and reduced-carbon monoxide difference spectroscopy, and a specific peak at 450 nm was detected in the wild-type and 19 variants. Furthermore, kinetic parameters were determined by assaying the reactions with efavirenz and propofol and quantifying the metabolite concentrations. We found that 12 variants had significantly lower or abolished enzymatic activity with both the substrates. In silico three-dimensional docking and molecular-dynamics simulations suggested that these functional changes were due to conformational changes in essential regions, such as the heme-binding site and ligand channels involved in transporting substrates to the active site. These findings have implications for predicting the plasma concentrations of CYP2B6 substrates and controlling their side effects.

Finding MeVO: Identifying Intracranial Medium-Vessel Occlusions at CT Angiography.

The development of methods to detect and treat intracranial large-vessel occlusions (LVOs) has revolutionized the management of acute ischemic stroke. CT angiography (CTA) of the head and neck is effective in depicting LVOs and widely used in the evaluation of patients who have had a stroke. Ongoing efforts are now focused on the potential to detect and treat intracranial medium-vessel occlusions (MeVOs), which by definition are smaller than LVOs and thus more difficult to detect with CTA. The authors review common and variant anatomies of medium-sized cerebral arteries and the appearance of a variety of MeVOs on CT angiograms. Possible pitfalls in MeVO detection include rare anatomic variants, calcified thrombi, and stump occlusions. Current recommendations for performing CTA and ancillary methods that might aid in MeVO detection are discussed. Understanding the relevant anatomy and the variety of appearances of MeVOs aids radiologists in identifying these occlusions, particularly in the setting of urgent stroke. ©RSNA, 2024 See the invited commentary by Ospel and Nguyen in this issue.

Early-onset atrial fibrillation is a risk marker for cardiomyopathy: genetic insights from the UK Biobank

Abstract Introduction Atrial fibrillation (AF) is a common cardiac arrhythmia associated with an increased risk of stroke, heart failure and premature death. Genetic associations between AF and rare variants have been identified in several cardiomyopathy-associated genes, and previous studies have shown a high prevalence of deleterious variants among individuals with early onset of AF. Consequently, genetic testing has been suggested in patients with AF onset before 45 years of age. Purpose This study aimed to explore the prevalence and distribution of deleterious genetic variants in cardiomyopathy genes according to age at AF diagnosis. Methods The UK Biobank is a large population-based biobank, comprised of clinical and genetic information on more than 500,000 individuals, enrolled between 2006 and 2010. We analyzed whole-exome sequencing data among unrelated individuals of European ancestry. The cohort was stratified by age at AF onset (AF onset <45 years, AF onset between 45-54 years, AF onset between 55-64 years, AF onset >=65 years, and individuals with no AF diagnosis). We evaluated the presence of rare (minor allele frequency <0.1%) genetic variants in core cardiomyopathy genes, according to guidelines by the American College of Medical Genomics and focused on variants predicted to lead to loss of function. Individuals with a diagnosis of cardiomyopathy prior to AF were excluded. Results Among 374,365 unrelated individuals of European ancestry, 29,119 were diagnosed with AF. Of these, 685 had onset of AF<45 years (2.35%), 2465 had onset between 45-54 years (8.46%), 7778 had onset between 55-64 years (26.71%), and 18191 had onset at or above 65 years of age (62.48%). A total of 884 were carriers of rare loss-of-function variants in cardiomyopathy genes. Among carriers, the majority of variants were in key genes for dilated cardiomyopathy (TTN), hypertrophic cardiomyopathy (MYBPC3), and arrhythmogenic right ventricular cardiomyopathy (PKP2). We observed an inverse dose-response-like relationship between prevalence of the rare genetic variants and age at AF diagnosis. The highest prevalence of carriers was observed among individuals with onset before 45 years (4.96%). In comparison, the proportion of carriers was 3.45% in individuals with AF onset between 45-54 years, 2.96% in individuals with AF onset between 55-64 years, 2.75% in individuals with onset at or after 65 years, and 2.05% among individuals without AF diagnosis. Conclusions Using whole exome sequencing, we identified a high proportion of carriers of deleterious variants in actionable genes of cardiomyopathies among individuals with early onset of AF. We observed an inverse dose-response-like relationship between age of AF diagnosis and prevalence of deleterious genetic variants. Our findings support that very early onset of AF, before 45 years of age, is a potential risk marker for cardiomyopathy and support that genetic screening may be relevant in this patient group.

Prevalence and implications of cardiomyopathy-associated genetic variants in early-onset atrial fibrillation

Abstract Background Atrial fibrillation (AF) is a common and morbid arrhythmia. Despite a substantial heritable component, genetics does not currently play a role in personalized medicine for AF. Rare genetic variants in genes associated with inherited cardiomyopathies (CMP) are enriched in AF patients. However, prior studies on rare variants in AF mainly relied on hospital-based populations, and knowledge on clinical outcomes remains limited. Purpose We aimed to evaluate the potential diagnostic yield and prognostic implication of pathogenic or likely pathogenic (PLP) genetic variants for CMP in persons with AF, using large population-based cohorts. Methods This study utilized sequencing data and electronic health records (EHR) from the All of Us Researh Program (AllofUs) and UK Biobank (UKB). Using ClinVar, we curated a set of PLP variants in 36 CMP-associated genes and assessed the carrier prevalence overall, in participants with AF, and in participants with early-onset AF (below 65, 55 and 45 years). Next, we used Cox proportional hazards models to evaluate the association between variant carrier status and incident risk of heart failure or CMP, after AF diagnosis. In all time-to-event analyses, individuals with prevalent heart failure or CMP at AF diagnosis were excluded and models were adjusted for age, sex, and principal components of ancestry. Sensitivity analyses were performed requiring a minimum period from AF to HF or CMP, of 1, 3 and 6 months. Results After excluding related individuals, we identified 32,281 (8.19%) and 9,666 (6.06%) AF cases in UKB and AllofUs, respectively. Compared to the overall populations (UKB: 1.15%; AllofUs: 1.36%), PLP variants for CMP were about ~5 times more prevalent in AF with onset before 45 (UKB: 4.98%; AllofUs: 5.26%), ~3 times more prevalent in AF with onset before 55 (UKB: 3.41%; AllofUs: 4.34%) and ~2 times more prevalent in all AF patients (UKB: 2.03%; AllofUs: 2.67%). In turn, AF patients carrying PLP variants had increased risk of developing heart failure or CMP, after AF diagnosis (AllofUs HR 1.81, 1.44-2.29, p<1e10-6, UKB:HR=1.39 1.08-1.78, p<0.01), which remained present when requiring a minimum of 6 months after AF diagnosis (AllofUs:HR 1.70, 1.29-2.25, p<0.001; UKB:HR=1.59, 1.21-2.07, p<0.001). Effect sizes were greater when limiting analysis to AF patients with onset before 65 (cases=1021, HR 1.91, 1.35-2.68, p<0.0001) and before 55 years (cases=384, HR 2.53, 1.55-4.1, p <0.001) in AllofUs. UK Biobank did not reflect this increase (cases<65=513, HR<65=1.27, 0.63-2.39, p<65>0.05). Considering only HF events in AllofUs, the effect remained present (HR 1.70, 1.32-2.19, p<0.0001). Conclusion The yield of CMP-associated PLP variants is substantial among persons with early-onset AF, even when considering a 55 year cutoff. AF patients with PLP variants have an increased risk of future heart failure or CMP. Our results further support the clinical relevance of genetic testing in early-onset AF.Prevalence of CMP variants in AF by age

Pathogenic cardiomyopathy gene variants inform prognosis in atrial fibrillation: results from exome sequencing in over 17,000 patients in TIMI trials

Abstract Background Rare genetic variants in cardiomyopathy genes are associated with risk of atrial fibrillation (AF), even in the absence of overt ventricular dysfunction. Data on clinical outcomes for rare genetic variant carriers among patients with AF remain sparse. Purpose We aimed to study the prognostic implication of rare pathogenic/likely pathogenic (PLP) variants for dilated cardiomyopathy (DCM), hypertrophic cardiomyopathy (HCM) and arrhythmogenic right ventricular cardiomyopathy (ARVC) in patients with AF from large, well-phenotyped randomized clinical trials. Methods and results Rare variants were called using exome sequencing data in 5 large clinical trials from the TIMI study group (ENGAGE-AF, FOURIER, SAVOR, PEGASUS, DECLARE). PLP variants for cardiomyopathy were identified using phenotype- and gene-specific curation of protein-truncating variants and high-confidence variant classifications from the ClinVar database. In 17,190 patients with a history of AF, we identified 421 (2.4%) PLP variant carriers (age 67±10, 35% women) and 16,769 (97.6%) pts without PLP variants (age 70±9, 36% women). Among these individuals, we identified 265 DCM carriers (1.5%), 106 (0.6%) HCM carriers and 54 (0.3%) ARVC carriers. In this cohort, 9,275 (54%) had a history of heart failure (HF) and 2,991 (17.4%) prior ischemic stroke. Over 2.5 years median follow-up, 1,365 pts (7.9%) were hospitalized for HF, 599 (3.5%) had an ischemic stroke, and 1147 (6.7%) died of cardiovascular causes. In logistic regression analyses adjusting for age, sex, trial, and principal components of ancestry, PLP variants were significantly associated with a history of HF (OR 1.66, p<0.0001), most notably for DCM variants (OR 1.97, 1.48-2.62, p<0.0001). PLP variants were independently associated with incident HF admissions (adj HR 1.75, 1.39-2.29, p<0.0001), most notably for HCM (adj HR 2.59, 1.68-3.99, p<0.0001) and ARVC variants (adj HR 2.50, 1.34-4.66, p=0.004). The increased risk of HF admissions remained consistent in patients with (adj HR 1.49, 1.11-2.00, p=0.009) and those without (adj HR 1.88, 1.00-3.54, p=0.049) a history of HF. PLP variants were also associated with higher risk of cardiovascular death (adj HR 1.46, 1.06-2.02, p=0.02), most notably for DCM variants (adj HR 1.77, 1.21-2.58, p=0.003). In contrast, PLP variants were not associated with history of ischemic stroke at baseline (adj OR 0.99, p=0.96) nor with incident ischemic stroke (adj HR 0.95, p=0.84). Conclusion In patients with AF, rare cardiomyopathy gene variants are associated with increased risks of HF and of cardiovascular death, but not stroke. These results, collected from large well-phenotyped randomized clinical trials, demonstrate an important prognostic implication for rare genetic variants for CMP in pts with AF.

Rare genetic variants in LDLR, APOB, and PCSK9 are associated with aortic stenosis

Abstract Background Aortic stenosis (AS) is the most common cardiac valvular disease in the developed world. Although AS is associated with substantial morbidity and mortality, current treatment options are limited to invasive procedures and reserved for severe symptomatic disease. Genetic studies have linked common variants near lipid genes to AS and cohort studies have linked diagnoses of familial hypercholesterolemia to AS. In contrast, randomized controlled trials have shown no benefit of lipid-lowering therapy in AS. Purpose We aimed to assess the impact on AS conferred by lifelong decreased or increased LDL levels, by studying rare genetic variation in three important lipid handling genes (LDLR, APOB, PCSK9) from a genome-first perspective. Methods We utilized sequencing data and electronic health records from the UK Biobank (UKB) and the All of Us Research Program (AllofUs). We used LOFTEE to identify carriers of truncating variants in LDLR (LDLRtv), APOB (APOBtv) and PCSK9 (PCSK9tv); we used AlphaMissense to identify predicted-damaging missense variants (LDLR-AM, APOB-AM, PCSK9-AM). Linear regression analyses were used to assess the impact of the variant groupings on LDL levels in the UK Biobank, adjusting for sex, age, age^2, and principal components of ancestry. We then conducted Firth’s logistic regression analyses in UK Biobank and AllofUs modelling AS as outcome and variant status as predictor, adjusting for the same covariates; we used an inverse-variance-weighted meta-analysis to combine results. Results We identified 421,058 unrelated participants (N=5,322 AS cases) in the UK Biobank, and 232,170 unrelated participants (N=1,087 AS cases) in AllofUs. Across both cohorts, we identified 198 LDLRtv carriers, 1095 LDLR-AM carriers, 662 APOBtv carriers, 1422 APOB-AM carriers, 712 PCSK9tv carriers and 794 PCSK9-AM carriers. In the UK Biobank LDL values were substantially elevated in LDLRtv (P=1.9x10-48) and LDLR-AM carriers (P=7.5e-200), while LDL levels were substantially decreased in APOBtv (P<1x10-200), APOB-AM (P=6.3x10-19), PCSK9tv (P=1.2x10-114) and PCSK9-AM carriers (P=9.9x10-73; Figure 1). Across UK Biobank and AllofUs, the risk of being diagnosed with AS was strongly increased in LDLRtv (odds ratio [OR]=9.2 [4.32–19.50], P=8e-9) and LDLR-AM carriers (OR=2.76 [1.75–4.35], P=1e-5; Figure 2). Directionally consistent with these effects, we observed a trend towards decreased AS risk among carriers of either APOBtv or PCSK9tv (OR=0.57, [0.30–1.08], P=0.08) and a significantly reduced risk among carriers of APOB-AM or PCSK9-AM (OR=0.46, [0.26-0.82], P=0.009). Conclusion Rare genetic variants that confer lifelong increased LDL levels are associated with substantially increased risk of AS, and vice versa. Our results support a causal role of LDL in AS pathogenesis. In the context of trials demonstrating no benefit in AS, our findings suggest that lipid-lowering may need to be initiated earlier to affect AS development.LDL levels in UK BiobankAS risk in UK Biobank and AllofUs

Phenotype heterogeneity of SCN5A mutations in Brugada syndrome

Abstract Introduction Although SCN5A is the main gene associated with Brs syndrome (Brs), rare variants in this gene only affect 20 to 30 % of patients. Additionally, associated phenotype may differ even among relatives sharing the same mutation emphasizing a phenotype heterogeneity that is poorly understood for now. Objective Here we aim to investigate the association between the presence of SCN5A mutations and the expression of a BrS phenotype in large families. Methods Among Brugada patients enrolled in our prospective cohort, we included patients from families with affected proband carrier of a SCN5A mutation and at least 4 relatives carriers of the same SCN5A mutation. Patient without a spontaneous type 1 ECG and no pharmacological provocative test were excluded. Results A total of 463 individuals from 45 large families were enrolled. Among them, 258 (56%) were mutation carriers of one of the 33 identified SCN5A mutations. After pharmacological test, 219 (47%) individuals were diagnosed with BrS, including 32 not carriers of the familial mutation. Seventy-five patients (30%), carriers of the familial SCN5A mutation, remain negative for Brugada syndrome after pharmacological test. The prevalence of genotype-phenotype mismatch was 24%, including 32 BrS patients non carrier of the familial mutation (phenocopy) and 75 patients with the familial mutation but without BrS (30% of uncomplete penetrance). Conclusion Our data strongly suggest that SCN5A mutation is not either necessary nor sufficient to explain the occurrence of BrS phenotype. We now aim to identify which associated factors might interfere, focusing first on the genetic background of phenotype/genotype mismatched individuals.

Genetic and phenotypic architecture of biventricular trabeculation

Abstract Introduction Cardiac trabeculae form a network of muscular strands that line the inner surfaces of the heart, and their development involves molecular pathways that regulate structural complexity. Excessive or hypertrabeculation occurs as part of normal variation in apparently healthy individuals, as an adaptation to altered loading conditions, and is observed in patients with cardiomyopathies (CMs) and heart failure (HF). Purpose In adults, trabeculation is not a prognostic factor independent of the underlying myocardial disease but may play a role in the natural history of ventricular remodelling. We sought to (i) understand the genetic and non-genetic determinants of trabeculation, (ii) understand its role in the causality of disease, and (iii) evaluate trabeculation as a biomarker for diagnosis and stratification. Methods We report genes with a burden of rare variants and novel common variant associations across the allele frequency spectrum for biventricular trabecular morphology in 47,803 participants of the UK Biobank using fractal dimension analysis of cardiac imaging (Figure 1). We assessed environmental modifiers of trabecular morphology, correlation with cardiac traits, phenome-wide association studies, and the relationship with the progression of CMs and HF. Results We identified a burden of trabeculation-associated rare variants in genes that regulate myocardial contractility and cardiac development and GWAS identified novel loci near genes implicated in CMs, conduction traits, and signalling pathways that define the early development of trabeculation. For example, we identified 56 genes with a burden of rare variants and 68 novel loci from GWAS (e.g., CASQ2, CACNA1C, MYBPC3, MYH7, NKX2-5, NOTCH1, TBX20) for the left ventricle. The strongest imaging relationships with trabeculation were with measures of volume and strain. Modifiers of trabeculation included African ancestry, alcohol intake, and physical activity. Carriers of CM-associated pathogenic variants had increased trabeculation. Of participants with CM reported after imaging, 25% had hypertrabeculation on imaging and hypertrabeculation was a risk factor for a subsequent diagnosis of HF (HR=1.3), mitral valve disorders (HR=1.4), bundle branch block (HR=1.2). Comparisons of biventricular trabeculation showed similarities in trabeculation across the ventricles in CM. Reduced right ventricular trabeculation and end-diastolic volume associated with Type-2 diabetes. Conclusions These data provide new insights into the mechanisms that regulate structural complexity in the heart. Changes in trabeculation may occur early in the pathogenesis of heart disease, can be modified by genes regulating pathways outside the sarcomere, and causality depends on the underlying cardiomyopathic substrate. Trabeculation progresses with cardiovascular disease, is a useful marker of remodelling, and identifies novel genetic modifiers of ventricular complexity.Figure 1

Accurate detection of dilated cardiomyopathy onset through machine learning predictions from ECG data

Abstract Background Dilated cardiomyopathy (DCM) is a primary heart muscle disease characterised by left-ventricular dilatation and reduced contractility, often associated with arrhythmia and conduction disease. DCM often has a genetic component, putting family members of diagnosed patients at risk for the disease. Stratification tools to provide personalized screening advice are currently lacking. Artificial intelligence (AI) based analysis of the electrocardiogram (ECG) offers a potential solution to this challenge. Purpose Our study aims to develop and validate a novel AI-ECG model capable of prediction and early detection of DCM. Methods An AI-ECG model was developed on a United States (US) based secondary care centre dataset including 337,463 ECGs from 50,932 patients within 4 months of diagnostic echocardiography and 265,576 ECGs from 51,086 patients prior to the first diagnostic echo. The data was split 50/10/40% for training, validation, and testing, with each subset containing 9-12% DCM positive labels. The model architecture was based on a convolutional neural network with residual blocks with a modified final layer for a discrete-time survival model. The AI-ECG score was linked to changes in the median ECG within the test set to provide explainability. External validation was performed on 68,885 diagnostic ECGs (0.08% DCM positive) from the UK biobank (UKB) and a Chinese general hospital dataset with 317,854 diagnostic ECGs (2.2% DCM positive) and 76,936 predictive ECGs (1.7% DCM positive). We performed common and rare variant association studies for the AI ECG scores on quality-controlled UKB data. Results The AI-ECG score for predicted future DCM was associated with diverse ECG features (Fig. 1). In the US cohort test set, the model achieved high diagnostic accuracy with an AUC of 0.9 (95% CI 0.89-0.90) overall, and 0.89 (0.85-0.92) in a subset excluding ischemic or valvular heart disease. External datasets showed AUCs of 0.86 (0.81-0.91) in the UKB and 0.97 (96-0.97) in the Chinese dataset. The predictive performance of the AI-ECG score, adjusted for age and sex, closely approximated echocardiographic traits (LVEF and LVEDD, Fig. 2) with a concordance index (CI) of 0.79 (0.76-0.83) and 0.81 (0.77-0.85), respectively, at 10 years of follow up (FU). Combining AI-ECG scores with echocardiographic traits enhanced the CI to 0.84 (0.8-0.87). Similar findings were observed in the Chinese dataset, with a CI of 0.87 (0.85-0.89) for the AI-ECG score and 0.9 (0.88-0.92) for echocardiographic traits. Genetic analyses in UKB identified associations between the AI-ECG score and rare TTN variants as well as 25 common variant loci. Conclusion Our explainable AI ECG model for future DCM prediction demonstrates robust performance across datasets, providing comparable predictive accuracy to echocardiographic traits up to 10 years pre-diagnosis. Genetic associations support the model's validity and provide new tools for DCM genetic discovery.

Role of common variants and new genes associated with arrhythmogenic cardiomyopathy

Abstract Introduction Arrhythmogenic Cardiomyopathy (ACM) is an inherited cardiac disease, predominantly affecting males, characterized by fibro-fatty myocardial replacement mainly in the right ventricle. It leads to 5% sudden cardiac death in affected young adults (<25 yo) without an implantable cardioverter defibrillator. Early diagnosis is crucial for appropriate clinical management to reduce mortality and prevent disease progression. Rare variants in desmosomal genes (PKP2,DSC2,DSG2,DSP and JUP) are found in 50% of cases. However, challenges persist since we observe a low penetrance in relatives (28-58%) and a high variability in expressivity and severity annihilating any preventive strategy. Objective We aim to decipher the genetic architecture of ACM by investigating the role of common variants in disease susceptibility/severity and to idendify new genes associated to ACM. Method A Genome Wide Association Study (GWAS) was performed on 1079 ACM index patients and 7305 controls, followed by conditional analysis. New candidate genes were knocked out (KO) in Zebrafish and/or hiPSC using CRISPR/Cas9. Impedance and external field potential measurements were performed on hiPSC derived cardiomyocytes (CM-hiPSC). Results The GWAS identified 5 significant loci (Figure 1, P<5.10-8), including 2 desmosomal genes (PKP2 a n d DSG2) and 3 new candidates (KLF12, CTNNA3, and ARL17B/WNT3). Conditional analysis revealed 3 additional loci with suggestive p-values (P<1.10-6), highlighting 3 new susceptible loci. Among them, we uncovered key non-coding regulatory regions near desmosomal genes (DSC2 and DSG2). Initial findings in PKP2-KO zebrafish present hearts with structural defects, while CM-hiPS KLF12-KO(-/-) exhibited altered interbeat interval and relaxation time compared to isogenic controls. Conclusion Our findings reveal ACM's complex genetic architecture, implicating common variants in disease susceptibility. A polygenic risk score will be implemented to improve patient risk stratification. Three novel loci/genes for ACM as well as specific regulatory regions of desmosomal genes have been highlighted. Their functional studies in isogenic hiPSC and Zebrafish models will offer new insights in ACM underlying molecular mechanism and potential therapeutic targets.

SLC16A8 is a causal contributor to age-related macular degeneration risk

Age-related macular degeneration (AMD), a complex neurodegenerative disease, is a leading cause of visual impairment worldwide with a strong genetic component. Genetic studies have identified several loci, but few causal genes with functional characterization. Here we highlight multiple lines of evidence which show a causal role in AMD for SLC16A8, which encodes MCT3, a retinal pigment epithelium (RPE) specific lactate transporter. First, in an unbiased, genome-wide analysis of rare coding variants we show multiple SLC16A8 rare variants are associated with AMD risk, corroborating previous borderline significant reports from AMD rare variant studies. Second, we report a novel SLC16A8 mutation in a three-generation family with early onset macular degeneration. Finally, mis-expression in multiple model organisms shows functional and anatomic retinal consequences. This study highlights the important role for SLC16A8 and lactate regulation towards outer retina/RPE health and highlights a potential new therapeutic opportunity for the treatment of AMD.

Identification of genetic variants by using a whole exome sequencing approach in Taiwanese patients with Brugada Syndrome

Abstract Background Brugada Syndrome (BrS) is a life-threatening arrhythmia disease primarily affecting young men. Many genetic studies have been conducted mainly in Caucasian BrS patients to identify potential genetic drivers. SCN5A mutations are less common in Asian BrS patients (around 10%) compared to Caucasian patients (20-30%). This means the pathogenic process of more than 70% of BrS patients remains unclear. With the advancement in NGS technologies, we can conduct genome-wide screening of DNA variants in BrS patients efficiently. Purpose Since less than 30% of the BrS patients have known genetic drivers for the disease, we aimed to identify more DNA variants in BrS patients by using the whole exome sequencing (WES) approach. Furthermore, we evaluated the landscape of DNA variants in the two groups of BrS patients according to whether they have SCN5A mutations or not. Methods A total of 201 BrS patients were recruited for the WES experiments. After obtaining the raw sequencing data, we performed the quality check procedures using the multiQC and Trimmomatic softwares (Figure 1). For reads passing the quality check, the BWA algorithm was used for the alignment. Next, the samtools, bamtools, and Picard methods were used to remove duplicates and perform the sorting. Subsequently, those sorted sequencing files were used to call the DNA variants by using the GATK approach and annotate them using the ANNOVAR method. The 201 BrS patients were classified into two different groups based on their mutation status of SCN5A, presentation of sudden cardiac death (SCD), and SCD along with syncope. The gene-based algorithm, SKAT, was used to analyze the summarized effects of DNA variants located in a single gene. For each DNA variant, Fisher's exact test was used to compare the allele frequency in the BrS patients under their groupings. Results The WES approach in the 201 BrS patients revealed a total of 205,454 variants, which were further categorized into two groups, common variants (51,867) and rare variants (153,587), based on their allele frequencies (5%). The SKAT algorithm was performed in the 30 genes that have been previously reported to be associated with BrS. No significant differences were observed in any gene in BrS patients for the common variants. Intriguingly, KCNJ8, SCN1B, ZFPM2, MAPRE2, and KCNE5 showed significant differences in allele frequencies between the SCN5A+ and SCN5A- patients (Figure 2). Fisher's exact test further revealed that three DNA variants (chr19:35524980, chr12:21926440, chr6:126210346) were significantly enriched in SCN5A+ patients. The 5 DNA variants located in ZFPM2 showed a linkage disequilibrium block and were enriched in SCN5A+ patients. Conclusions The WES approach in BrS patients revealed DNA variants that were reported in previous studies. Several DNA variants were significantly enriched in SCN5A+ patients, suggesting that the genome-wide mutation landscape was different in SCN5A+ and SCN5A- BrS patients.Figure 1Figure 2

Genome-wide association analysis reveals insights into the molecular etiology of dilated cardiomyopathy

Abstract Introduction Dilated cardiomyopathy (DCM) is a primary heart muscle disease characterized by ventricular dilatation and impaired contractility. While considered a Mendelian disorder, recent evidence highlights the important role of common genetic variation. Better characterization of the genetic architecture will provide opportunities for improved diagnosis, risk stratification and biological understanding. Methods We performed a GWAS meta-analysis of 14,256 DCM cases and 1,185,671 controls of European ancestry from 16 studies (GWASDCM). To improve discovery power, we performed multi-trait analysis of GWAS (GWASMTAG) with three genetically correlated and clinically relevant cardiac imaging traits in 36,203 individuals. To identify effector genes at loci, we used a two-step approach: 1) the nearest gene and top 3 genes prioritized by PoPS or V2G were selected as candidates; and 2) totality of evidence including 5 additional methods (coding variant, co-localization with expression, TWAS, ABC-model, and known Mendelian cardiomyopathy genes) was summarized in a single score. We performed rare variant burden analysis (MAF<0.1%) for predicted truncating variants (PTV) in established DCM-causing genes to highlight DCM genetic architecture, and in prioritized GWAS genes, against DCM and quantitative CMR traits in UK Biobank (UKB) and 100,000 Genomes Project (GeL), implemented by REGENIE. A polygenic score (PGS) generated using a Bayesian framework (PRS-CS) was assessed for association with the same outcomes in UKB participants, including among PTV carriers in established DCM-causing genes. Results We identified 80 independent loci, of which 65 were novel (62 loci in GWASDCM, and 54 loci in GWASMTAG) (Figure 1A). High-confidence genes were prioritized at 62 loci, including in genes with established roles in Mendelian cardiomyopathies (TTN, BAG3, FLNC, MYBPC3, FHOD3, ALPK3), and were enriched in key biological processes (Figure 1B). We characterized DCM genetic architecture across the allelic spectrum (Figure 2A). Rare variant burden analysis highlighted novel associations with DCM and quantitative traits for PTVs in NEDD4L and MAP3K7 in UKB that were replicated in GeL (Figure 2B). PGS was associated with DCM and quantitative CMR traits (OR per PGS SD 1.8, P<1x10-16) (Figure 2C). Individuals in the top centile had 4-fold increased risk of having DCM compared with median risk. PGS stratified penetrance of rare variants in 1,546 carriers of pathogenic variants (top quintile 7.3%, bottom quintile 1.7%, P 0.005). Conclusion We have performed the largest DCM GWAS, resulting in 80 significant loci (65 novel), and prioritized genes using a systematic approach. We identify novel DCM-causing genes (NEDD4L and MAP3K7) and generate a PGS that associates with DCM and modulates penetrance in carriers of Mendelian disease-causing rare variants.Figure 1Figure 2

Utility of polygenic risk score for prediction of dilated cardiomyopathy and modulation of severity of LV dysfunction among cases

Abstract Background Dilated cardiomyopathy (DCM) is a predominant cause of heart failure and a leading indication for cardiac transplantation. While rare genetic variants are established as causative factors in familial forms of the disease, recent genome-wide association studies (GWAS) have also underscored the significant contribution of common genetic variation to DCM. Polygenic scores (PGS) constructed from GWAS have demonstrated promise in risk stratification for a range of common diseases and may similarly have value for risk prediction in DCM. However, data regarding the clinical utility of PGS in DCM remains sparse. Purpose We aimed to evaluate the utility of PGS for prediction of DCM and its association with left ventricular ejection fraction (LVEF) and family history. We further aimed to assess the contribution of PGS in DCM patients with established causative rare variants (genotype-positive) and those without (genotype-negative). Methods We used a previously-constructed PGS, which was developed from a GWAS meta-analysis (8387 DCM cases and 939161 controls) and multi-trait analysis (MTAG) with cardiac MRI traits. In the present analysis, we calculated PGS for a newly assembled cohort of 978 DCM cases from a major university medical centre and 7207 controls from a national register. To evaluate the clinical utility of PGS, we built logistic regression models and assessed the association between PGS and DCM status. Subsequently, we performed subgroup analyses, including: i) individuals of European ancestry, ii) non-European ancestry, iii) males, iv) females, v) genotype-positive participants(n=193), and vi) genotype-negative participants (n=294). We then used linear and logistic regression models, respectively, to assess the associations of PGS with LVEF and documented family history of DCM. Results PGS demonstrated a significant enrichment among DCM cases compared to controls (OR per SD 1.93, P = 9.47E-68). This association persisted with consistent effect estimates - ranging from OR 1.5 to 2.2 - across all examined subgroups and demonstrated sufficient statistical significance (all P<1.58E-06) (Figure 1). Genotype-negative cases had a significantly higher PGS compared to genotype-positive individuals (P = 0.0015), although PGS was significantly enriched in both groups as compared to controls. Furthermore, among DCM cases, higher PGS was significantly associated with lower LVEF at first presentation (P=0.03, beta=-0.5% per SD) (Figure 2). There was no significant association found between PGS and family history. Conclusions PGS is strongly associated with risk of DCM, and may modulate the severity of LV dysfunction among DCM cases. Polygenic burden contributes to DCM risk in both genotype-positive and negative cases, although the contribution is stronger in patients without known causative rare variants. Overall, our results suggest a potential clinical applicability for PGS in DCM risk stratification.Figure 1.Association of PGS with DCMFigure 2.Association of PGS with LVEF

Exome sequencing in over 63,000 patients in TIMI trials uncovers pathogenic cardiomyopathy variant carriers with high risk for heart failure and cardiovascular death

Abstract Background Rare genetic variants predisposing to cardiomyopathy (CMP) confer increased risk for adverse events. The prevalence of CMP variants in contemporary cardiovascular (CV) trials and their association with prevalent heart failure (HF) and incident HF hospitalizations (HHF) is not established. Purpose We aimed to identify carriers of rare pathogenic/likely pathogenic (PLP) variants for dilated cardiomyopathy (DCM), hypertrophic cardiomyopathy (HCM), and arrhythmogenic right ventricular cardiomyopathy (ARVC) in well-phenotyped clinical trial cohorts and to evaluate their prognostic significance. Methods Rare variants were identified from high-quality exome sequencing data from 5 large clinical trials (ENGAGE AF-TIMI 48, SAVOR-TIMI 53, PEGASUS-TIMI 54, DECLARE-TIMI 58, FOURIER (TIMI 59)). Putatively pathogenic variants for cardiomyopathy were identified using phenotype- and gene-specific curation of protein-truncating variants and high-confidence variant classifications from ClinVar. We conducted logistic regression for prevalent disease and Cox proportional hazard models for incident HHF, both adjusted by age, sex, trial, and first 10 principal components and using those without CMP variants as the reference. Sensitivity analysis by history of HF at baseline was performed for prospective outcomes. Results In 63,700 participants, we identified 866 CMP variant carriers of which 518 identified as DCM carriers (age 65±9 yrs, male 66%), 194 HCM carriers (65.5±9 yrs, male 69%), and 125 ARVC carriers (66±9 yrs, male 77%). Out of the 518 DCM variant carriers, 402 had a PLP variant in TTN. DCM variant carriers had higher odds of history of HF (Odds ratio [OR] 1.94, 1.57-2.39, p<0.0001) whereas this was not observed for HCM variant carriers (OR 1.18, 0.85-1.65, p=0.33) or ARVC variant carriers (OR 1.23, 0.80-1.90, p=0.35). Over a mean follow-up of 2.5 years, the rate of HHF was significantly higher for DCM variant carriers (Hazard ratio [HR] 1.58, 1.14-2.20, p=0.006), HCM variant carriers (HR 2.78, 1.87-4.13, p<0.001), and ARVC variant carriers (HR 1.89, 1.02-3.53, p=0.04). These associations were, if anything, stronger in patients without HF at baseline (HR 2.06, 1.30-3.25) than in patients with HF at baseline (HR 1.48, 1.12-1.95). DCM variant carriers also had a higher rate of CV death (HR 1.50, 1.05-2.12, p=0.02), which was not observed for HCM (HR 1.10, 0.57-2.11, p=0.78) or ARVC (HR 0.35, 0.09-1.41, p=0.14) variant carriers. Conclusion In 5 contemporary CV trials, CMP variant carriers have an increased rate of HHF, while DCM variant carriers also have a higher rate of CV death. These findings motivate better identification of these high-risk individuals and the incorporation of genetic testing in CV trials.

A burden of rare copy number variants in obsessive-compulsive disorder.

Current genetic research on obsessive-compulsive disorder (OCD) supports contributions to risk specifically from common single nucleotide variants (SNVs), along with rare coding SNVs and small insertion-deletions (indels). The contribution to OCD risk from rare copy number variants (CNVs), however, has not been formally assessed at a similar scale. Here we describe an analysis of rare CNVs called from genotype array data in 2248 deeply phenotyped OCD cases and 3608 unaffected controls from Sweden and Norway. Cases carry an elevated burden of CNVs ≥30 kb in size (OR = 1.12, P = 1.77 × 10-3). The excess rate of these CNVs in cases versus controls was around 0.07 (95% CI 0.02-0.11, P = 2.58 × 10-3). This signal was largely driven by CNVs overlapping protein-coding regions (OR = 1.19, P = 3.08 × 10-4), particularly deletions impacting loss-of-function intolerant genes (pLI >0.995, OR = 4.12, P = 2.54 × 10-5). We did not identify any specific locus where CNV burden was associated with OCD case status at genome-wide significance, but we noted non-random recurrence of CNV deletions in cases (permutation P = 2.60 × 10-3). In cases where sufficient clinical data were available (n = 1612) we found that carriers of neurodevelopmental duplications were more likely to have comorbid autism (P < 0.001), and that carriers of deletions overlapping neurodevelopmental genes had lower treatment response (P = 0.02). The results demonstrate a contribution of rare CNVs to OCD risk, and suggest that studies of rare coding variation in OCD would have increased power to identify risk genes if this class of variation were incorporated into formal tests.

Are rare heterozygous SYNJ1 variants associated with Parkinson’s disease?

Previous studies have established that rare biallelic SYNJ1 mutations cause autosomal recessive parkinsonism and Parkinson’s disease (PD). We analyzed 8165 PD cases, 818 early-onset-PD (EOPD, < 50 years) and 70,363 controls. Burden meta-analysis revealed an association between rare nonsynonymous variants and variants with high Combined Annotation-Dependent Depletion score (> 20) in the Sac1 SYNJ1 domain and PD (Pfdr = 0.040). A meta-analysis of EOPD patients demonstrated an association between all rare heterozygous SYNJ1 variants and PD (Pfdr = 0.029).

Enrichment Strategies for Low-Abundant Single Nucleotide Mutations.

Over the past three decades, significant advancements have been made in mutation enrichment methods, driven by the increasing need for precise and efficient identification of rare genetic variants associated with diseases. Mutation-enrichment methods have emerged to boost sensitivity and enable easy detection of low-frequency mutations. These methods are crucial in genomics research and clinical diagnostics, allowing for the detection of low-frequency mutations within large genomic datasets. This review presents a summary of technological developments in rare mutation enrichment and emphasizes their mechanisms and applications in liquid biopsies.

Identification of osteoporosis genes using family studies

Osteoporosis is a multifactorial bone disease characterised by reduced bone mass and increased fracture risk. Family studies have made significant contribution in unravelling the genetics of osteoporosis. Yet, most of the underlying molecular and biological mechanisms remain unknown prompting the need for further studies. This review outlines the proper phenotyping and advanced genetic techniques in the form of high-throughput DNA sequencing used to identify genetic factors underlying monogenic osteoporosis in a family-based setting. The steps related to variant filtering prioritisation and curation are also described. From an evolutionary perspective, deleterious risk variants with higher penetrance tend to be rare as a result of negative selection. High-throughput sequencing (HTS) can identify rare variants with large effect sizes which are likely to be missed by candidate gene analysis or genome-wide association studies (GWAS) wherein common variants with small to moderate effect sizes are identified. We also describe the importance of replicating implicated genes, and possibly variants, identified following HTS to confirm their causality. Replication of the gene in other families, singletons or independent cohorts confirms that the shortlisted genes and/or variants are indeed causal. Furthermore, novel genes and/or variants implicated in monogenic osteoporosis require a thorough validation by means of in vitro and in vivo assessment. Therefore, analyses of families can continue to elucidate the genetic architecture of osteoporosis, paving the way for improved diagnostic and therapeutic strategies.

Identifying pathogenic variants in rare pediatric neurological diseases using exome sequencing.

Variant annotations are crucial for efficient identification of pathogenic variants. In this study, we retrospectively analyzed the utility of four annotation tools (allele frequency, ClinVar, SpliceAI, and Phenomatcher) in identifying 271 pathogenic single nucleotide and small insertion/deletion variants (SNVs/small indels). Although variant filtering based on allele frequency is essential for narrowing down on candidate variants, we found that 13 de novo pathogenic variants in autosomal dominant or X-linked dominant genes are registered in gnomADv4.0 or 54KJPN, with an allele frequency of less than 0.001%, suggesting that very rare variants in large cohort data can be pathogenic de novo variants. Notably, 38.4% candidate SNVs/small indels are registered in the ClinVar database as pathogenic or likely pathogenic, which highlights the significance of this database. SpliceAI can detect candidate variants affecting RNA splicing, leading to the identification of four variants located 11 to 50bp away from the exon-intron boundary. Prioritization of candidate genes by proband phenotype using the PhenoMatcher module revealed that approximately 95% of the candidate genes had a maximum PhenoMatch score ≥ 0.6, suggesting the utility of phenotype-based variant prioritization. Our results suggest that a combination of multiple annotation tools and appropriate evaluation can improve the diagnosis of rare diseases.