The penetrance of rare variants in cardiomyopathy-associated genes: A cross-sectional approach to estimating penetrance for secondary findings.

Understanding the penetrance of pathogenic variants identified as secondary findings (SFs) is of paramount importance with the growing availability of genetic testing. We estimated penetrance through large-scale analyses of individuals referred for diagnostic sequencing for hypertrophic cardiomyopathy (HCM; 10,400 affected individuals, 1,332 variants) and dilated cardiomyopathy (DCM; 2,564 affected individuals, 663 variants), using a cross-sectional approach comparing allele frequencies against reference populations (293,226 participants from UK Biobank and gnomAD). We generated updated prevalence estimates for HCM (1:543) and DCM (1:220). In aggregate, the penetrance by late adulthood of rare, pathogenic variants (23% for HCM, 35% for DCM) and likely pathogenic variants (7% for HCM, 10% for DCM) was substantial for dominant cardiomyopathy (CM). Penetrance was significantly higher for variant subgroups annotated as loss of function or ultra-rare and for males compared to females for variants in HCM-associated genes. We estimated variant-specific penetrance for 316 recurrent variants most likely to be identified as SFs (found in 51% of HCM- and 17% of DCM-affected individuals). 49 variants were observed at least ten times (14% of affected individuals) in HCM-associated genes. Median penetrance was 14.6% (±14.4% SD). We explore estimates of penetrance by age, sex, and ancestry and simulate the impact of including future cohorts. This dataset reports penetrance of individual variants at scale and will inform the management of individuals undergoing genetic screening for SFs. While most variants had low penetrance and the costs and harms of screening are unclear, some individuals with highly penetrant variants may benefit from SFs.

Ethnicity, consanguinity, and genetic architecture of hypertrophic cardiomyopathy.

AIMS: Hypertrophic cardiomyopathy (HCM) is characterized by phenotypic heterogeneity that is partly explained by the diversity of genetic variants contributing to disease. Accurate interpretation of these variants constitutes a major challenge for diagnosis and implementing precision medicine, especially in understudied populations. The aim is to define the genetic architecture of HCM in North African cohorts with high consanguinity using ancestry-matched cases and controls. METHODS AND RESULTS: Prospective Egyptian patients (n = 514) and controls (n = 400) underwent clinical phenotyping and genetic testing. Rare variants in 13 validated HCM genes were classified according to standard clinical guidelines and compared with a prospective HCM cohort of majority European ancestry (n = 684). A higher prevalence of homozygous variants was observed in Egyptian patients (4.1% vs. 0.1%, P = 2 × 10-7), with variants in the minor HCM genes MYL2, MYL3, and CSRP3 more likely to present in homozygosity than the major genes, suggesting these variants are less penetrant in heterozygosity. Biallelic variants in the recessive HCM gene TRIM63 were detected in 2.1% of patients (five-fold greater than European patients), highlighting the importance of recessive inheritance in consanguineous populations. Finally, rare variants in Egyptian HCM patients were less likely to be classified as (likely) pathogenic compared with Europeans (40.8% vs. 61.6%, P = 1.6 × 10-5) due to the underrepresentation of Middle Eastern populations in current reference resources. This proportion increased to 53.3% after incorporating methods that leverage new ancestry-matched controls presented here. CONCLUSION: Studying consanguineous populations reveals novel insights with relevance to genetic testing and our understanding of the genetic architecture of HCM.

Exploring the complex spectrum of dominance and recessiveness in genetic cardiomyopathies.

Discrete categorization of Mendelian disease genes into dominant and recessive models often oversimplifies their underlying genetic architecture. Cardiomyopathies (CMs) are genetic diseases with complex etiologies for which an increasing number of recessive associations have recently been proposed. Here, we comprehensively analyze all published evidence pertaining to biallelic variation associated with CM phenotypes to identify high-confidence recessive genes and explore the spectrum of monoallelic and biallelic variant effects in established recessive and dominant disease genes. We classify 18 genes with robust recessive association with CMs, largely characterized by dilated phenotypes, early disease onset and severe outcomes. Several of these genes have monoallelic association with disease outcomes and cardiac traits in the UK Biobank, including LMOD2 and ALPK3 with dilated and hypertrophic CM, respectively. Our data provide insights into the complex spectrum of dominance and recessiveness in genetic heart disease and demonstrate how such approaches enable the discovery of unexplored genetic associations.

Systematic large-scale assessment of the genetic architecture of left ventricular noncompaction reveals diverse etiologies.

PURPOSE: To characterize the genetic architecture of left ventricular noncompaction (LVNC) and investigate the extent to which it may represent a distinct pathology or a secondary phenotype associated with other cardiac diseases. METHODS: We performed rare variant association analysis with 840 LVNC cases and 125,748 gnomAD population controls, and compared results to similar analyses on dilated cardiomyopathy (DCM) and hypertrophic cardiomyopathy (HCM). RESULTS: We observed substantial genetic overlap indicating that LVNC often represents a phenotypic variation of DCM or HCM. In contrast, truncating variants in MYH7, ACTN2, and PRDM16 were uniquely associated with LVNC and may reflect a distinct LVNC etiology. In particular, MYH7 truncating variants (MYH7tv), generally considered nonpathogenic for cardiomyopathies, were 20-fold enriched in LVNC cases over controls. MYH7tv heterozygotes identified in the UK Biobank and healthy volunteer cohorts also displayed significantly greater noncompaction compared with matched controls. RYR2 exon deletions and HCN4 transmembrane variants were also enriched in LVNC, supporting prior reports of association with arrhythmogenic LVNC phenotypes. CONCLUSION: LVNC is characterized by substantial genetic overlap with DCM/HCM but is also associated with distinct noncompaction and arrhythmia etiologies. These results will enable enhanced application of LVNC genetic testing and help to distinguish pathological from physiological noncompaction.

Disease-specific variant pathogenicity prediction significantly improves variant interpretation in inherited cardiac conditions.

PURPOSE: Accurate discrimination of benign and pathogenic rare variation remains a priority for clinical genome interpretation. State-of-the-art machine learning variant prioritization tools are imprecise and ignore important parameters defining gene-disease relationships, e.g., distinct consequences of gain-of-function versus loss-of-function variants. We hypothesized that incorporating disease-specific information would improve tool performance. METHODS: We developed a disease-specific variant classifier, CardioBoost, that estimates the probability of pathogenicity for rare missense variants in inherited cardiomyopathies and arrhythmias. We assessed CardioBoost's ability to discriminate known pathogenic from benign variants, prioritize disease-associated variants, and stratify patient outcomes. RESULTS: CardioBoost has high global discrimination accuracy (precision recall area under the curve [AUC] 0.91 for cardiomyopathies; 0.96 for arrhythmias), outperforming existing tools (4-24% improvement). CardioBoost obtains excellent accuracy (cardiomyopathies 90.2%; arrhythmias 91.9%) for variants classified with >90% confidence, and increases the proportion of variants classified with high confidence more than twofold compared with existing tools. Variants classified as disease-causing are associated with both disease status and clinical severity, including a 21% increased risk (95% confidence interval [CI] 11-29%) of severe adverse outcomes by age 60 in patients with hypertrophic cardiomyopathy. CONCLUSIONS: A disease-specific variant classifier outperforms state-of-the-art genome-wide tools for rare missense variants in inherited cardiac conditions ( https://www.cardiodb.org/cardioboost/ ), highlighting broad opportunities for improved pathogenicity prediction through disease specificity.

An Investigation of Fibulin-2 in Hypertrophic Cardiomyopathy.

Hypertrophic cardiomyopathy (HCM) is the most common inherited heart muscle disease, with a prevalence of at least 1 in 500 in the general population. The disease is pleiotropic and is characterized by an increased stiffness of the myocardium, partly due to changes in the extracellular matrix (ECM), with elevated levels of interstitial fibrosis. Myocardial fibrosis is linked to impaired diastolic function and possibly phenotypic heterogeneity of HCM. The ECM consists of a very large number of proteins, which actively interact with each other as well as with myocardial cells. The role of other multiple components of the ECM in HCM has not been defined. Fibulin-2 is a glycoprotein component of the ECM, which plays an important role during embryogenesis of the heart; however, its role in adult myocardium has not been adequately studied. We here describe, for the first time, abnormal expression of fibulin-2 in the myocardium in patients with HCM as compared to normal controls. This abnormal expression was localized in the cytoplasm of myocardial cells and in the interstitial fibroblasts. In addition, fibulin-2 levels, measured by ELISA, were significantly elevated in the serum of patients with HCM as compared to normal controls.

The Egyptian Collaborative Cardiac Genomics (ECCO-GEN) Project: defining a healthy volunteer cohort.

The integration of comprehensive genomic and phenotypic data from diverse ethnic populations offers unprecedented opportunities toward advancements in precision medicine and novel diagnostic technologies. Current reference genomic databases are not representative of the global human population, making variant interpretation challenging, especially in underrepresented populations, such as the North African population. To address this, the Egyptian Collaborative Cardiac Genomics (ECCO-GEN) Project launched a study comprising 1000 individuals free of cardiovascular disease (CVD). Here, we present the first 391 Egyptian healthy volunteers recruited to establish a pilot phenotyped control cohort. All individuals underwent detailed clinical investigation, including cardiac magnetic resonance imaging (MRI), and were sequenced using a targeted panel of 174 genes with reported roles in inherited cardiac conditions. We identified 1262 variants in 27 cardiomyopathy genes of which 15.1% were not captured in current global and regional genetic reference databases (here: gnomAD and Great Middle Eastern Variome). The ECCO-GEN project aims at defining the genetic landscape of an understudied population and providing individual-level genetic and phenotypic data to support future studies in CVD and population genetics.

Quantitative approaches to variant classification increase the yield and precision of genetic testing in Mendelian diseases: the case of hypertrophic cardiomyopathy.

BACKGROUND: International guidelines for variant interpretation in Mendelian disease set stringent criteria to report a variant as (likely) pathogenic, prioritising control of false-positive rate over test sensitivity and diagnostic yield. Genetic testing is also more likely informative in individuals with well-characterised variants from extensively studied European-ancestry populations. Inherited cardiomyopathies are relatively common Mendelian diseases that allow empirical calibration and assessment of this framework. METHODS: We compared rare variants in large hypertrophic cardiomyopathy (HCM) cohorts (up to 6179 cases) to reference populations to identify variant classes with high prior likelihoods of pathogenicity, as defined by etiological fraction (EF). We analysed the distribution of variants using a bespoke unsupervised clustering algorithm to identify gene regions in which variants are significantly clustered in cases. RESULTS: Analysis of variant distribution identified regions in which variants are significantly enriched in cases and variant location was a better discriminator of pathogenicity than generic computational functional prediction algorithms. Non-truncating variant classes with an EF ≥ 0.95 were identified in five established HCM genes. Applying this approach leads to an estimated 14-20% increase in cases with actionable HCM variants, i.e. variants classified as pathogenic/likely pathogenic that might be used for predictive testing in probands' relatives. CONCLUSIONS: When found in a patient confirmed to have disease, novel variants in some genes and regions are empirically shown to have a sufficiently high probability of pathogenicity to support a "likely pathogenic" classification, even without additional segregation or functional data. This could increase the yield of high confidence actionable variants, consistent with the framework and recommendations of current guidelines. The techniques outlined offer a consistent and unbiased approach to variant interpretation for Mendelian disease genetic testing. We propose adaptations to ACMG/AMP guidelines to incorporate such evidence in a quantitative and transparent manner.

NaNog: A pluripotency homeobox (master) molecule.

One of the most intriguing aspects of cell biology is the state of pluripotency, where the cell is capable of self-renewal for as many times as deemed "necessary", then at a specified time can differentiate into any type of cell. This fundamental process is required during organogenesis in foetal life and importantly during tissue repair in health and disease. Pluripotency is very tightly regulated, as any dysregulation can result in congenital defects, inability to repair damage, or cancer. Fuelled by the relatively recent interest in stem cell biology and tissue regeneration, the molecules implicated in regulating pluripotency have been the subject of extensive research. One of the important molecules involved in pluripotency, is NaNog, the subject of this article.

Reprogramming for cardiac regeneration.

Treatment of cardiovascular diseases remains challenging considering the limited regeneration capacity of the heart muscle. Developments of reprogramming strategies to create in vitro and in vivo cardiomyocytes have been the focus point of a considerable amount of research in the past decades. The choice of cells to employ, the state-of-the-art methods for different reprogramming strategies, and their promises and future challenges before clinical entry, are all discussed here.