Evaluating pathogenicity of rare variants from dilated cardiomyopathy in the exome era

Investigating genes associated with heart failure, atrial fibrillation, and other cardiovascular diseases, and predicting disease using machine learning techniques for translational research and precision medicine

Cardiovascular disease (CVD) is the leading cause of mortality and loss of disability adjusted life years (DALYs) globally. CVDs like Heart Failure (HF) and Atrial Fibrillation (AF) are associated with physical effects on the heart muscles. As a result of the complex nature, progression, inherent genetic makeup, and heterogeneity of CVDs, personalized treatments are believed to be critical. Rightful application of artificial intelligence (AI) and machine learning (ML) approaches can lead to new insights into CVDs for providing better personalized treatments with predictive analysis and deep phenotyping. In this study we focused on implementing AI/ML techniques on RNA-seq driven gene-expression data to investigate genes associated with HF, AF, and other CVDs, and predict disease with high accuracy. The study involved generating RNA-seq data derived from the serum of consented CVD patients. Next, we processed the sequenced data using our RNA-seq pipeline and applied GVViZ for gene-disease data annotation and expression analysis. To achieve our research objectives, we developed a new Findable, Accessible, Intelligent, and Reproducible (FAIR) approach that includes a five-level biostatistical evaluation, primarily based on the Random Forest (RF) algorithm. During our AI/ML analysis, we have fitted, trained, and implemented our model to classify and distinguish high-risk CVD patients based on their age, gender, and race. With the successful execution of our model, we predicted the association of highly significant HF, AF, and other CVDs genes with demographic variables.

Genome-wide fetalization of enhancer architecture in heart disease

Heart disease is associated with re-expression of key transcription factors normally active only during prenatal development of the heart. However, the impact of this reactivation on the regulatory landscape in heart disease is unclear. Here, we use RNA-seq and ChIP-seq targeting a histone modification associated with active transcriptional enhancers to generate genome-wide enhancer maps from left ventricle tissue from up to 26 healthy controls, 18 individuals with idiopathic dilated cardiomyopathy (DCM), and five fetal hearts. Healthy individuals have a highly reproducible epigenomic landscape, consisting of more than 33,000 predicted heart enhancers. In contrast, we observe reproducible disease-associated changes in activity at 6,850 predicted heart enhancers. Combined analysis of adult and fetal samples reveals that the heart disease epigenome and transcriptome both acquire fetal-like characteristics, with 3,400 individual enhancers sharing fetal regulatory properties. We also provide a comprehensive data resource (http://heart.lbl.gov) for the mechanistic exploration of DCM etiology.

Validation of New Gene Variant Classification Methods: a Field-Test in Diagnostic Cardiogenetics

Background: In the molecular genetic diagnostics of Mendelian disorders, solutions are needed for the major challenge of dealing with the large number of variants of uncertain significance (VUSs) identified using next-generation sequencing (NGS). Recently, promising approaches using constraint metrics to calculate case excess scores (CE), etiological fractions (EF), and gnomAD-derived constraint scores have been reported that estimate the likelihood of rare variants in specific genes or regions that are pathogenic. Our objective is to study the usability of these constraint data into variant interpretation in a diagnostic setting, using our cardiomyopathy cohort.

Methods and Results: Patients (N = 2002) referred for clinical genetic diagnostics underwent NGS testing of 55–61 genes associated with cardiomyopathies. Previously classified likely pathogenic (LP) and pathogenic (P) variants were used to validate the use of data from CE, EF, and gnomAD constraint analyses for (re)classification of associated variant types in specific cardiomyopathy subtype-related genes. The classifications corroborated in 94% (354/378) of cases. Next, we reclassified 23 unique VUSs to LP, increasing the diagnostic yield by 1.2%. In addition, 106 unique VUSs (5.3% of patients) were prioritized for co-segregation or functional analyses.

Conclusions: Our analysis confirms that the use of constraint metrics data can improve variant interpretation, and we, therefore, recommend using constraint scores on other cohorts and disorders and its inclusion in variant interpretation protocols.

Clinical Implication of Genetic Testing in Dilated Cardiomyopathy

Dilated cardiomyopathy (DCM) is one of the important causes of heart failure (HF). With the rapidly evolving technologies for gene analysis and tremendous advances in knowledge of HF genetics, the importance of genetic testing in DCM is currently highlighted. Several genetic variants causing DCM have been identified and this information is used for diagnosis, risk stratification and family screening of DCM patients. However, there are still several challenges in applying genetic testing to real clinical practice. In this review, we will summarize recent understandings in DCM genetics and provide an evidence-based practical guide to the use of genetic testing for DCM patients.

Gain-of-function cardiomyopathic mutations in RBM20 rewire splicing regulation and re-distribute ribonucleoprotein granules within processing bodies

Mutations in the cardiac splicing factor RBM20 lead to malignant dilated cardiomyopathy (DCM). To understand the mechanism of RBM20-associated DCM, we engineered isogenic iPSCs with DCM-associated missense mutations in RBM20 as well as RBM20 knockout (KO) iPSCs. iPSC-derived engineered heart tissues made from these cell lines recapitulate contractile dysfunction of RBM20-associated DCM and reveal greater dysfunction with missense mutations than KO. Analysis of RBM20 RNA binding by eCLIP reveals a gain-of-function preference of mutant RBM20 for 3' UTR sequences that are shared with amyotrophic lateral sclerosis (ALS) and processing-body associated RNA binding proteins (FUS, DDX6). Deep RNA sequencing reveals that the RBM20 R636S mutant has unique gene, splicing, polyadenylation and circular RNA defects that differ from RBM20 KO. Super-resolution microscopy verifies that mutant RBM20 maintains very limited nuclear localization potential; rather, the mutant protein associates with cytoplasmic processing bodies (DDX6) under basal conditions, and with stress granules (G3BP1) following acute stress. Taken together, our results highlight a pathogenic mechanism in cardiac disease through splicing-dependent and -independent pathways.

X-CNV: genome-wide prediction of the pathogenicity of copy number variations

Background

Gene copy number variations (CNVs) contribute to genetic diversity and disease prevalence across populations. Substantial efforts have been made to decipher the relationship between CNVs and pathogenesis but with limited success.

Results

We have developed a novel computational framework X-CNV (www.unimd.org/XCNV), to predict the pathogenicity of CNVs by integrating more than 30 informative features such as allele frequency (AF), CNV length, CNV type, and some deleterious scores. Notably, over 14 million CNVs across various ethnic groups, covering nearly 93% of the human genome, were unified to calculate the AF. X-CNV, which yielded area under curve (AUC) values of 0.96 and 0.94 in training and validation sets, was demonstrated to outperform other available tools in terms of CNV pathogenicity prediction. A meta-voting prediction (MVP) score was developed to quantitively measure the pathogenic effect, which is based on the probabilistic value generated from the XGBoost algorithm. The proposed MVP score demonstrated a high discriminative power in determining pathogenetic CNVs for inherited traits/diseases in different ethnic groups.

Conclusions

The ability of the X-CNV framework to quantitatively prioritize functional, deleterious, and disease-causing CNV on a genome-wide basis outperformed current CNV-annotation tools and will have broad utility in population genetics, disease-association studies, and diagnostic screening.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13073-021-00945-4.

Sex Differences, Genetic and Environmental Influences on Dilated Cardiomyopathy

Dilated cardiomyopathy (DCM) is characterized by dilatation of the left ventricle and impaired systolic function and is the second most common cause of heart failure after coronary heart disease. The etiology of DCM is diverse including genetic pathogenic variants, infection, inflammation, autoimmune diseases, exposure to chemicals/toxins as well as endocrine and neuromuscular causes. DCM is inherited in 20–50% of cases where more than 30 genes have been implicated in the development of DCM with pathogenic variants in TTN (Titin) most frequently associated with disease. Even though male sex is a risk factor for heart failure, few studies have examined sex differences in the pathogenesis of DCM. We searched the literature for studies examining idiopathic or familial/genetic DCM that reported data by sex in order to determine the sex ratio of disease. We found 31 studies that reported data by sex for non-genetic DCM with an average overall sex ratio of 2.5:1 male to female and 7 studies for familial/genetic DCM with an overall average sex ratio of 1.7:1 male to female. No manuscripts that we found had more females than males in their studies. We describe basic and clinical research findings that may explain the increase in DCM in males over females based on sex differences in basic physiology and the immune and fibrotic response to damage caused by mutations, infections, chemotherapy agents and autoimmune responses.

FREQMAX provides an alternative approach for determining high-resolution allele frequency thresholds in carrier screening

As whole-genome data become available for increasing numbers of individuals across diverse populations, the list of genomic variants of unknown significance (VOUS) continues to grow. One powerful tool in VOUS interpretation is determining whether an allele is too common to be considered pathogenic. As genetic and epidemiological parameters vary across disease models, so too does the pathogenic allele frequency threshold for each disease gene. One threshold-setting approach is the maximum credible allele frequency (MCAF) method. However, estimating some of the input values MCAF requires, especially those involving heterogeneity, can present nontrivial statistical challenges. Here, we introduce FREQMAX, our alternative approach for determining allele frequency thresholds in carrier screening. FREQMAX makes efficient use of the data available for well-studied traits and exhibits flexibility for traits where information may be less complete. For cystic fibrosis, more alleles are excluded as benign by FREQMAX than by MCAF. For less-comprehensively characterized traits like ciliary dyskinesia and Smith-Lemli-Opitz syndrome, FREQMAX is able to set the allele frequency threshold without requiring a priori estimates of maximum genetic and allelic contributions. Furthermore, though we describe FREQMAX in the context of carrier screening, its classical population genetics framework also provides context for adaptation to other trait models.

The Frequency of Discordant Variant Classification in the Human Gene Mutation Database: A Comparison of the American College of Medical Genetics and Genomics Guidelines and ClinVar

OBJECTIVE

Discordant variant classifications among public databases is one of the well-documented limitations when interpreting the pathogenicity of variants. The aim of this study is to investigate the level of germline variant misannotation from the Human Gene Mutation Database (HGMD) and the annotation concordance between databases.

METHODS

We used a total of 188,106 classified variants (disease-causing mutations [n = 179,454] and polymorphisms [n = 8652]) in 6466 genes from the HGMD. All variants were reanalyzed based on the American College of Medical Genetics and Genomics (ACMG) guidelines and compared to ClinVar database variants.

RESULTS

When variants were classified based on the ACMG guidelines, misclassification was observed in 3.47% (2289/65,896) of variants. The overall concordance between HGMD and ClinVar was 97.62% (52,499/53,780) of variants studied.

CONCLUSION

Variants in databases must be used with caution when variant pathogenicity is interpreted. This study reveals the frequency of misannotation of the HGMD variants and annotation concordance between databases in depth.

Epidemiology of the inherited cardiomyopathies

In the absence of contemporary, population-based epidemiological studies, estimates of the incidence and prevalence of the inherited cardiomyopathies have been derived from screening studies, most often of young adult populations, to assess cardiovascular risk or to detect the presence of disease in athletes or military recruits. The global estimates for hypertrophic cardiomyopathy (1/500 individuals), dilated cardiomyopathy (1/250) and arrhythmogenic right ventricular cardiomyopathy (1/5,000) are probably conservative given that only individuals who fulfil diagnostic criteria would have been included. This caveat is highly relevant because a substantial minority or even a majority of individuals who carry disease-causing genetic variants and are at risk of disease complications have incomplete and/or late-onset disease expression. The genetic literature on cardiomyopathy, which is often focused on the identification of genetic variants, has been biased in favour of pedigrees with higher penetrance. In clinical practice, an abnormal electrocardiogram with normal or non-diagnostic imaging results is a common finding for the sarcomere variants that cause hypertrophic cardiomyopathy, the titin and sarcomere variants that cause dilated cardiomyopathy and the desmosomal variants that cause either arrhythmogenic right ventricular cardiomyopathy or dilated cardiomyopathy. Therefore, defining the genetic epidemiology is also challenging given the overlapping phenotypes, incomplete and age-related expression, and highly variable penetrance even within individual families carrying the same genetic variant.

The CnB1 p.D102A variant is linked to dilated cardiomyopathy via impaired Calcineurin activity

BACKGROUND

The role of calcineurin (protein phosphatase 2B (PP2B)) in the pathogenesis of human dilated cardiomyopathy (DCM) has not been fully elucidated. We determined the potential involvement of calcineurin in the pathogenesis of DCM caused by mutations in CnB1, a subunit of calcineurin.

METHODS

By whole-exome sequencing, we identified a new CnB1 variant in a Han Chinese proband with cardiomyopathy from a 3-generation family with 2 normal individuals and 3 individuals with familial dilated cardiomyopathy. The potential pathogenic variant was validated by Sanger sequencing. We performed functional and mechanistic experiments in a CnB1-knockin (KI) mouse model and at the cellular level.

RESULTS

We detected a rare heterozygous CnB1 variant (p.D102A) in a proband with dilated cardiomyopathy. This variant was localized to the EF hand 3 region of CnB1, where no variants have been previously reported. KI mice harboring the p.D102A variant exhibited decreased cardiac function and cardiac dilatation. Immunoblotting, RT-PCR and immunofluorescence results showed decreased cardiomyocyte size and heart failure-related protein expression. A calcineurin activity assay demonstrated decreased calcineurin activity in the KI mice, accompanied by the decreased ability of CnB1 to bind CnA.

CONCLUSIONS

CnB1 p.D102A is a disease-associated variant that confers susceptibility to cardiac dilatation. This variant is associated with impaired calcineurin activity and a subsequent decrease in the ability of CnB1 to bind CnA.

Genetic aspects of the oxidative phosphorylation dysfunction in dilated cardiomyopathy

Dilated cardiomyopathy is a frequent and extremely heterogeneous medical condition. Deficits in the oxidative phosphorylation system have been described in patients suffering from dilated cardiomyopathy. Hence, mutations in proteins related to this biochemical pathway could be etiological factors for some of these patients. Here, we review the clinical phenotypes of patients harboring pathological mutations in genes related to the oxidative phosphorylation system, either encoded in the mitochondrial or in the nuclear genome, presenting with dilated cardiomyopathy. In addition to the clinical heterogeneity of these patients, the large genetic heterogeneity has contributed to an improper allocation of pathogenicity for many candidate mutations. We suggest criteria to avoid incorrect assignment of pathogenicity to newly found mutations and discuss possible therapies targeting the oxidative phosphorylation function.

The Multifaced Perspectives of Genetic Testing in Pediatric Cardiomyopathies and Channelopathies

Pediatric inherited cardiomyopathies (CMPs) and channelopathies (CNPs) remain important causes of death in this population, therefore, there is a need for prompt diagnosis and tailored treatment. Conventional evaluation fails to establish the diagnosis of pediatric CMPs and CNPs in a significant proportion, prompting further, more complex testing to make a diagnosis that could influence the implementation of lifesaving strategies. Genetic testing in CMPs and CNPs may help unveil the underlying cause, but needs to be carried out with caution given the lack of uniform recommendations in guidelines about the precise time to start the genetic evaluation or the type of targeted testing or whole-genome sequencing. A very diverse etiology and the scarce number of randomized studies of pediatric CMPs and CNPs make genetic testing of these maladies far more particular than their adult counterpart. The genetic diagnosis is even more puzzling if the psychological impact point of view is taken into account. This review aims to put together different perspectives, state-of-the art recommendations-synthetizing the major indications from European and American guidelines-and psychosocial outlooks to construct a comprehensive genetic assessment of pediatric CMPs and CNPs.

Prospective Evaluation of the Utility of Whole Exome Sequencing in Dilated Cardiomyopathy

Background Dilated cardiomyopathy may be heritable but shows extensive genetic heterogeneity. The utility of whole exome sequencing as a first-line genetic test for patients with dilated cardiomyopathy in a contemporary "real-world" setting has not been specifically established. Using whole exome sequencing with rigorous, evidence-based variant interpretation, we aimed to identify the prevalence of a molecular diagnosis in patients with dilated cardiomyopathy in a clinical setting. Methods and Results Whole exome sequencing was performed in eligible patients (n=83) with idiopathic or familial dilated cardiomyopathy. Variants were prioritized for curation in up to 247 genes and classified using American College of Medical Genetics and Genomics-based criteria. Ten (12%) had a pathogenic or likely pathogenic variant. Eight (10%) participants had truncating TTN variants classified as variants of uncertain significance. Five (6%) participants had variants of unknown significance according to strict American College of Medical Genetics and Genomics criteria but classified as either pathogenic or likely pathogenic by other clinical laboratories. Pathogenic or likely pathogenic variants were found in 8 genes (all within tier 1 genes), 2 (20%) of which are not included in a standard commercially available dilated cardiomyopathy panel. Using our bioinformatics pipeline, there was an average of 0.74 variants of uncertain significance per case with ≈0.75 person-hours needed to interpret each of these variants. Conclusions Whole exome sequencing is an effective diagnostic tool for patients with dilated cardiomyopathy. With stringent classification using American College of Medical Genetics and Genomics criteria, the rate of detection of pathogenic variants is lower than previous reports. Efforts to improve adherence to these guidelines will be important to prevent erroneous misclassification of nonpathogenic variants in dilated cardiomyopathy genetic testing and inappropriate cascade screening.

The intrinsically disordered C terminus of troponin T binds to troponin C to modulate myocardial force generation

Aberrant regulation of myocardial force production represents an early biomechanical defect associated with sarcomeric cardiomyopathies, but the molecular mechanisms remain poorly defined. Here, we evaluated the pathogenicity of a previously unreported sarcomeric gene variant identified in a pediatric patient with sporadic dilated cardiomyopathy, and we determined a molecular mechanism. Trio whole-exome sequencing revealed a de novo missense variant in TNNC1 that encodes a p.I4M substitution in the N-terminal helix of cardiac troponin C (cTnC). Reconstitution of this human cTnC variant into permeabilized porcine cardiac muscle preparations significantly decreases the magnitude and rate of isometric force generation at physiological Ca2+-activation levels. Computational modeling suggests that this inhibitory effect can be explained by a decrease in the rates of cross-bridge attachment and detachment. For the first time, we show that cardiac troponin T (cTnT), in part through its intrinsically disordered C terminus, directly binds to WT cTnC, and we find that this cardiomyopathic variant displays tighter binding to cTnT. Steady-state fluorescence and NMR spectroscopy studies suggest that this variant propagates perturbations in cTnC structural dynamics to distal regions of the molecule. We propose that the intrinsically disordered C terminus of cTnT directly interacts with the regulatory N-domain of cTnC to allosterically modulate Ca2+ activation of force, perhaps by controlling the troponin I switching mechanism of striated muscle contraction. Alterations in cTnC-cTnT binding may compromise contractile performance and trigger pathological remodeling of the myocardium.

Minimal inflammatory foci of unknown etiology may be a tentative sign of early stage inherited cardiomyopathy

Although relatively uncommon, pathologists may encounter minimal inflammatory foci in the absence of typical structural heart disease; however, the clinicopathological significance of minimal inflammatory foci, including correlation with sudden unexpected death, is unexplored. From 1072 serial autopsy subjects, cases with unexplained minimal inflammatory foci, the extent of which was under 1% of the whole examined ventricle, were extracted to exclude cases with borderline/focal myocarditis resulting from local, systemic infection, or autoimmune mechanisms. Immunohistochemistry and genetic analysis targeting viral genomes and heart disease-related genes using next generation sequencing were performed. We detected 10 cases with unexplained minimal inflammatory foci (five males, five females, aged 15-68 years). The cause and/or manner of death were sudden unexpected death (6 cases, 60%), sudden unexpected death with epilepsy (1 case, 10%), drowning in a hot bath (1 case, 10%), and suicide (2 cases, 20%). In none of these cases was pathogen-derived DNA or RNA detected. In 8 of the 10 cases (80%), 17 possible pathogenic genetic variants causative for arrhythmogenic right ventricular cardiomyopathy or dilated cardiomyopathy; DSP was the most frequently involved gene (three cases with two different variants), followed by LAMA4 and MYBPC3 (two cases, two variants for each gene), LDB3 (two cases, one variant), and the remaining 10 variants occurred in seven cases (DSC2, RYR2, SOS1, SCN5A, SGCD, LPL, PKP2, MYH11, GATA6, and DSG2). All mutations were missense mutations. DSP_Lys1581Glu and DSC2_p.Thr275Met were classified according to American College of Medical Genetics and Genomics consensus statement guidelines as pathogenic or likely pathogenic for arrhythmogenic cardiomyopathy in three patients (30%). The remaining 15 variants were classified as potentially pathogenic variants. Unexplained minimal inflammatory foci may be an early sign of inherited cardiomyopathy, and such cases might already have arrhythmogenic potential that can lead to sudden unexpected death. Detection of minimal inflammatory foci by careful pathological examination may indicate the value of conducting comprehensive genetic analysis, even if significant structural abnormalities are not evident.

Challenges and Considerations in Sequence Variant Interpretation for Mendelian Disorders

In 2015, the American College of Medical Genetics and Genomics (ACMG), together with the Association for Molecular Pathology (AMP), published the latest guidelines for the interpretation of sequence variants, which have been widely adopted into clinical practice. Despite these standardized efforts, the degrees of subjectivity and uncertainty allowed by the guidelines can lead to inconsistent variant classification across clinical laboratories, making it difficult to assess the pathogenicity of identified variants. We describe the critical elements of variant interpretation processes and potential pitfalls through practical examples and provide updated information based on a review of recent literature. The variant classification we describe is meant to be applicable to sequence variants for Mendelian disorders, whether identified by single-gene tests, multi-gene panels, exome sequencing, or genome sequencing. Continuing efforts to improve the reproducibility and objectivity of sequence variant interpretation across individuals and laboratories are needed.

A study of the pathogenicity of variants in familial heart disease. The value of cosegregation

With the development of deep sequencing, a significant proportion of mutations already listed in studies have inconclusive pathogenicity. We aim to establish the proportion of cases in which familial studies are possible and cosegregation analysis is informative. We also compare cosegregation analysis with in silico software and a proposed pathogenicity score. 204 consecutive positive tests were reviewed. 4 different in silico software programs were used. Spaendonck-Zwarts' pathogenicity score was also calculated. A total of 73 of the missense variants could be classified by the score as being likely or definitively pathogenic. A high percentage of nonsense variants were found in desmosomal genes and missense variants in sarcomeric genes. 36.3% of the missense variants in our cohort classified as very likely or definitively pathogenic were novel. Cosegregation analysis was positive in 19.5% and could be discarded in 15.6%. There was a significant discrepancy between the in silico tools used in the setting of inherited heart disease. Multiparametric scoring systems which include cosegregation and functional studies seem to perform better than individual prediction software.

Complex roads from genotype to phenotype in dilated cardiomyopathy: scientific update from the Working Group of Myocardial Function of the European Society of Cardiology

Dilated cardiomyopathy (DCM) frequently affects relatively young, economically, and socially active adults, and is an important cause of heart failure and transplantation. DCM is a complex disease and its pathological architecture encounters many genetic determinants interacting with environmental factors. The old perspective that every pathogenic gene mutation would lead to a diseased heart, is now being replaced by the novel observation that the phenotype depends not only on the penetrance-malignancy of the mutated gene-but also on epigenetics, age, toxic factors, pregnancy, and a diversity of acquired diseases. This review discusses how gene mutations will result in mutation-specific molecular alterations in the heart including increased mitochondrial oxidation (sarcomeric gene e.g. TTN), decreased calcium sensitivity (sarcomeric genes), fibrosis (e.g. LMNA and TTN), or inflammation. Therefore, getting a complete picture of the DCM patient will include genomic data, molecular assessment by preference from cardiac samples, stratification according to co-morbidities, and phenotypic description. Those data will help to better guide the heart failure and anti-arrhythmic treatment, predict response to therapy, develop novel siRNA-based gene silencing for malignant gene mutations, or intervene with mutation-specific altered gene pathways in the heart.This article is part of the Mini Review Series from the Varenna 2017 meeting of the Working Group of Myocardial Function of the European Society of Cardiology.

A gene-centric strategy for identifying disease-causing rare variants in dilated cardiomyopathy

PURPOSE

We evaluated strategies for identifying disease-causing variants in genetic testing for dilated cardiomyopathy (DCM).

METHODS

Cardiomyopathy gene panel testing was performed in 532 DCM patients and 527 healthy control subjects. Rare variants in 41 genes were stratified using variant-level and gene-level characteristics.

RESULTS

A majority of DCM cases and controls carried rare protein-altering cardiomyopathy gene variants. Variant-level characteristics alone had limited discriminative value. Differentiation between groups was substantially improved by addition of gene-level information that incorporated ranking of genes based on literature evidence for disease association. The odds of DCM were increased to nearly 9-fold for truncating variants or high-impact missense variants in the subset of 14 genes that had the strongest biological links to DCM (P <0.0001). For some of these genes, DCM-associated variants appeared to be clustered in key protein functional domains. Multiple rare variants were present in many family probands, however, there was generally only one "driver" pathogenic variant that cosegregated with disease.

CONCLUSION

Rare variants in cardiomyopathy genes can be effectively stratified by combining variant-level and gene-level information. Prioritization of genes based on their a priori likelihood of disease causation is a key factor in identifying clinically actionable variants in cardiac genetic testing.

Current perspectives on the diagnosis and management of dilated cardiomyopathy Beyond heart failure: a Cardiomyopathy Clinic Doctor's point of view

Left ventricular enlargement and dysfunction are fundamental components of dilated cardiomyopathy (DCM). DCM is a major cause of heart failure and cardiac transplantation. A wide variety of etiologies underlie acquired and familial DCM. Familial disease is reported in 20% to 35% of cases. A genetic substrate is recognized in at least 30% of familial cases. A recently proposed scheme defines DCM as a continuum of subclinical and clinical phenotypes. The evolution of classification systems permitted use of effective treatment strategies in disorders sharing the same structural and functional characteristics and common clinical expression. The major causes of death are progressive heart failure and sudden cardiac death secondary to ventricular arrhythmias or less commonly bradyarrhythmias. Remarkable progress has been made in survival owing to well-defined evidence-based therapies and appropriate guidelines for risk stratification and sudden cardiac death prevention measures. Neurohormonal antagonists and device therapy decreased all-cause mortality in adult patients with DCM. However, additional red flags in diagnosis have to be addressed in everyday practice, and cardiologists have to be aware of the subsequent effect on risk stratification and treatment plan. Genetic substrate cannot be modified, but the presence of a peculiar type of gene mutation modifies thresholds for implantable cardioverter defibrillator (ICD) implantation. DCM is part of the spectrum of heart failure which is a syndrome with certain morphological and functional characteristics. Although significant progress has been achieved in the management of patients with DCM, it seems that the future treatments of this entity will be related to the specific pathological substrate.

Genome-wide association study of cardiotoxicity in the NCCTG N9831 (Alliance) adjuvant trastuzumab trial

OBJECTIVES

The major clinical side effect of the ERBB2-targeted breast cancer therapy, trastuzumab, is a decline in the left ventricular ejection fraction (LVEF). Improved markers are needed to better identify patients susceptible to cardiotoxicity.

METHODS

The NCCTG N9831 trial compared adjuvant doxorubicin and cyclophosphamide followed by either weekly paclitaxel (arm A); paclitaxel then trastuzumab (arm B); or concurrent paclitaxel and trastuzumab (arm C) in patients with HER2-positive breast cancer. A genome-wide association study was performed on all patients with available DNA (N=1446). We used linear regression to identify single nucleotide polymorphisms (SNPs) associated with decline in LVEF, adjusting for age, baseline LVEF, antihypertensive medications, and the first two principle components.

RESULTS

In total, 618 863 SNPs passed quality control and DNA from 1191 patients passed genotyping quality control and were identified as Whites of non-Hispanic origin. SNPs at six loci were associated with a decline in LVEF (P=7.73×10 to 8.93×10), LDB2, BRINP1, chr6 intergenic, RAB22A, TRPC6, and LINC01060, in patients who received chemotherapy plus trastuzumab (arms BC, N=800). None of these loci were significant in patients who received chemotherapy only (arm A, N=391) and did not increase in significance in the combined analysis of all patients. We did not observe association, P<0.05, with SNPs previously associated with trastuzumab-induced cardiotoxicity at ERBB2, I655V, and P1170A. We replicated association, P<0.05, with SNPs previously associated with anthracycline-induced cardiotoxicity at CBR3 and ABCB1.

CONCLUSION

Our study identified six putative novel cardiotoxicity loci in patients treated with combination chemotherapy and trastuzumab that require further investigation and confirmed known associations of anthracycline-induced cardiotoxicity.

Novel mutations and phenotypes of epilepsy-associated genes in epileptic encephalopathies

Epileptic encephalopathies are severe epilepsy disorders with strong genetic bases. We performed targeted next-generation sequencing (NGS) in 70 patients with epileptic encephalopathies. The likely pathogenicity of variants in candidate genes was evaluated by American College of Medical Genetics and Genomics (ACMG) scoring taken together with the accepted clinical presentation. Thirty-three candidate variants were detected after population filtration and computational prediction. According to ACMG, 21 candidate variants, including 18 de novo variants, were assessed to be pathogenic/likely pathogenic with clinical concordance. Twelve variants were initially assessed as uncertain significance by ACMG, among which 3 were considered causative and 3 others were considered possibly causative after analysis of clinical concordance. In total, 24 variants were identified as putatively causative, among which 19 were novel findings. SCN1A mutations were identified in 50% of patients with Dravet syndrome. TSC1/TSC2 mutations were detected in 66.7% of patients with tuberous sclerosis. STXBP1 mutations were the main findings in patients with West syndrome. Mutations in SCN2A, KCNT1, KCNQ2 and CLCN4 were identified in patients with epileptic infantile with migrating focal seizures; among them, KCNQ2 and CLCN4 were first identified as potential causative genes. Only one CHD2 mutation was detected in patients with Lennox-Gastaut syndrome. This study highlighted the utility of targeted NGS in genetic diagnoses of epileptic encephalopathies and a comprehensive evaluation of the pathogenicity of variants based on ACMG scoring and assessment of clinical concordance. Epileptic encephalopathies differ in genetic causes, and the genotype-phenotype correlations would provide insights into the underlying pathogenic mechanisms.

Human Genome Sequencing at the Population Scale: A Primer on High-Throughput DNA Sequencing and Analysis

Most human diseases have underlying genetic causes. To better understand the impact of genes on disease and its implications for medicine and public health, researchers have pursued methods for determining the sequences of individual genes, then all genes, and now complete human genomes. Massively parallel high-throughput sequencing technology, where DNA is sheared into smaller pieces, sequenced, and then computationally reordered and analyzed, enables fast and affordable sequencing of full human genomes. As the price of sequencing continues to decline, more and more individuals are having their genomes sequenced. This may facilitate better population-level disease subtyping and characterization, as well as individual-level diagnosis and personalized treatment and prevention plans. In this review, we describe several massively parallel high-throughput DNA sequencing technologies and their associated strengths, limitations, and error modes, with a focus on applications in epidemiologic research and precision medicine. We detail the methods used to computationally process and interpret sequence data to inform medical or preventative action.

The genetics of congenital heart disease… understanding and improving long-term outcomes in congenital heart disease: a review for the general cardiologist and primary care physician

PURPOSE OF REVIEW

This review has two purposes: to provide an updated review of the genetic causes of congenital heart disease (CHD) and the clinical implications of these genetic mutations, and to provide a clinical algorithm for clinicians considering a genetics evaluation of a CHD patient.

RECENT FINDINGS

A large portion of congenital heart disease is thought to have a significant genetic contribution, and at this time a genetic cause can be identified in approximately 35% of patients. Through the advances made possible by next generation sequencing, many of the comorbidities that are frequently seen in patients with genetic congenital heart disease patients can be attributed to the genetic mutation that caused the congenital heart disease. These comorbidities are both cardiac and noncardiac and include: neurodevelopmental disability, pulmonary disease, heart failure, renal dysfunction, arrhythmia and an increased risk of malignancy. Identification of the genetic cause of congenital heart disease helps reduce patient morbidity and mortality by improving preventive and early intervention therapies to address these comorbidities.

SUMMARY

Through an understanding of the clinical implications of the genetic underpinning of congenital heart disease, clinicians can provide care tailored to an individual patient and continue to improve the outcomes of congenital heart disease patients.

Potential and pitfalls in the genetic diagnosis of kidney diseases

Next-generation sequencing has dramatically decreased the cost of gene sequencing, facilitating the simultaneous analysis of multiple genes at the same time; obtaining a genetic result for an individual patient has become much easier. The article by Ars and Torra in this issue of the Clinical Kidney Journal provides examples of the ever-increasing ability to understand a given patient's disease on the molecular level, so that in some cases not only the causative variants in a disease gene are identified, but also potential modifiers in other genes. Yet, with increased sequencing, a large number of variants are discovered that are difficult to interpret. These so-called 'variants of uncertain significance' raise important questions: when and how can pathogenicity be clearly attributed? This is of critical importance, as there are potentially serious consequences attached: decisions about various forms of treatment and even about life and death, such as termination of pregnancy, may hinge on the answer to these questions. Geneticists, thus, need to use the utmost care in the interpretation of identified variants and clinicians must be aware of this problem. We here discuss the potential of genetics to facilitate personalized treatment, but also the pitfalls and how to deal with them.

Genetic bases of dilated cardiomyopathy

Cardiomyopathies represent a wide and heterogeneous group of diseases wherein a genetic cause has been consistently identified.Dilated cardiomyopathy (DCM) is characterized by ventricular dilation and progressive systolic dysfunction, and it is the most common form of cardiomyopathy.Causative genetic mutations have been identified in more than 40 genes encoding proteins belonging to different cellular structures and pathways.A great diversity of pathways has been implied in the pathogenesis of DCM, depending on the affected genes and on the dislodged intracellular structures or mechanisms.This review describes the major genes and focus on the pathophysiologic mechanisms of DCM, with a special consideration of the most recent discoveries in the field.

Clinical Variant Classification: A Comparison of Public Databases and a Commercial Testing Laboratory

BACKGROUND

There is a growing move to consult public databases following receipt of a genetic test result from a clinical laboratory; however, the well-documented limitations of these databases call into question how often clinicians will encounter discordant variant classifications that may introduce uncertainty into patient management. Here, we evaluate discordance in BRCA1 and BRCA2 variant classifications between a single commercial testing laboratory and a public database commonly consulted in clinical practice.

MATERIALS AND METHODS

BRCA1 and BRCA2 variant classifications were obtained from ClinVar and compared with the classifications from a reference laboratory. Full concordance and discordance were determined for variants whose ClinVar entries were of the same pathogenicity (pathogenic, benign, or uncertain). Variants with conflicting ClinVar classifications were considered partially concordant if ≥1 of the listed classifications agreed with the reference laboratory classification.

RESULTS

Four thousand two hundred and fifty unique BRCA1 and BRCA2 variants were available for analysis. Overall, 73.2% of classifications were fully concordant and 12.3% were partially concordant. The remaining 14.5% of variants had discordant classifications, most of which had a definitive classification (pathogenic or benign) from the reference laboratory compared with an uncertain classification in ClinVar (14.0%).

CONCLUSION

Here, we show that discrepant classifications between a public database and single reference laboratory potentially account for 26.7% of variants in BRCA1 and BRCA2. The time and expertise required of clinicians to research these discordant classifications call into question the practicality of checking all test results against a database and suggest that discordant classifications should be interpreted with these limitations in mind.

IMPLICATIONS FOR PRACTICE

With the increasing use of clinical genetic testing for hereditary cancer risk, accurate variant classification is vital to ensuring appropriate medical management. There is a growing move to consult public databases following receipt of a genetic test result from a clinical laboratory; however, we show that up to 26.7% of variants in BRCA1 and BRCA2 have discordant classifications between ClinVar and a reference laboratory. The findings presented in this paper serve as a note of caution regarding the utility of database consultation.

Clinical and Mechanistic Insights Into the Genetics of Cardiomyopathy

Over the last quarter-century, there has been tremendous progress in genetics research that has defined molecular causes for cardiomyopathies. More than a thousand mutations have been identified in many genes with varying ontologies, therein indicating the diverse molecules and pathways that cause hypertrophic, dilated, restrictive, and arrhythmogenic cardiomyopathies. Translation of this research to the clinic via genetic testing can precisely group affected patients according to molecular etiology, and identify individuals without evidence of disease who are at high risk for developing cardiomyopathy. These advances provide insights into the earliest manifestations of cardiomyopathy and help to define the molecular pathophysiological basis for cardiac remodeling. Although these efforts remain incomplete, new genomic technologies and analytic strategies provide unparalleled opportunities to fully explore the genetic architecture of cardiomyopathies. Such data hold the promise that mutation-specific pathophysiology will uncover novel therapeutic targets, and herald the beginning of precision therapy for cardiomyopathy patients.

Analysis of selected genes associated with cardiomyopathy by next-generation sequencing

BACKGROUND

As the leading cause of congestive heart failure, cardiomyopathy represents a heterogenous group of heart muscle disorders. Despite considerable progress being made in the genetic diagnosis of cardiomyopathy by detection of the mutations in the most prevalent cardiomyopathy genes, the cause remains unsolved in many patients. High-throughput mutation screening in the disease genes for cardiomyopathy is now possible because of using target enrichment followed by next-generation sequencing. The aim of the study was to analyze a panel of genes associated with dilated or hypertrophic cardiomyopathy based on previously published results in order to identify the subjects at risk.

METHODS

The method of next-generation sequencing by IlluminaHiSeq 2500 platform was used to detect sequence variants in 16 individuals diagnosed with dilated or hypertrophic cardiomyopathy. Detected variants were filtered and the functional impact of amino acid changes was predicted by computational programs.

RESULTS

DNA samples of the 16 patients were analyzed by whole exome sequencing. We identified six nonsynonymous variants that were shown to be pathogenic in all used prediction softwares: rs3744998 (EPG5), rs11551768 (MGME1), rs148374985 (MURC), rs78461695 (PLEC), rs17158558 (RET) and rs2295190 (SYNE1). Two of the analyzed sequence variants had minor allele frequency (MAF)<0.01: rs148374985 (MURC), rs34580776 (MYBPC3).

CONCLUSION

Our data support the potential role of the detected variants in pathogenesis of dilated or hypertrophic cardiomyopathy; however, the possibility that these variants might not be true disease-causing variants but are susceptibility alleles that require additional mutations or injury to cause the clinical phenotype of disease must be considered.

Breast Cancer Clinical Trial of Chemotherapy and Trastuzumab: Potential Tool to Identify Cardiac Modifying Variants of Dilated Cardiomyopathy

Doxorubicin and the ERBB2 targeted therapy, trastuzumab, are routinely used in the treatment of HER2+ breast cancer. In mouse models, doxorubicin is known to cause cardiomyopathy and conditional cardiac knock out of Erbb2 results in dilated cardiomyopathy and increased sensitivity to doxorubicin-induced cell death. In humans, these drugs also result in cardiac phenotypes, but severity and reversibility is highly variable. We examined the association of decline in left ventricular ejection fraction (LVEF) at 15,204 single nucleotide polymorphisms (SNPs) spanning 72 cardiomyopathy genes, in 800 breast cancer patients who received doxorubicin and trastuzumab. For 7033 common SNPs (minor allele frequency (MAF) > 0.01) we performed single marker linear regression. For all SNPs, we performed gene-based testing with SNP-set (Sequence) Kernel Association Tests: SKAT, SKAT-O and SKAT-common/rare under rare variant non-burden; rare variant optimized burden and non-burden tests; and a combination of rare and common variants respectively. Single marker analyses identified seven missense variants in OBSCN (p = 0.0045-0.0009, MAF = 0.18-0.50) and two in TTN (both p = 0.04, MAF = 0.22). Gene-based rare variant analyses, SKAT and SKAT-O, performed very similarly (ILK, TCAP, DSC2, VCL, FXN, DSP and KCNQ1, p = 0.042-0.006). Gene-based tests of rare/common variants were significant at the nominal 5% level for OBSCN as well as TCAP, DSC2, VCL, NEXN, KCNJ2 and DMD (p = 0.044-0.008). Our results suggest that rare and common variants in OBSCN, as well as in other genes, could have modifying effects in cardiomyopathy.

Identification and characterization of Aurora kinase B and C variants associated with maternal aneuploidy

STUDY QUESTION

Are single nucleotide variants (SNVs) in Aurora kinases B and C (AURKB, AURKC) associated with risk of aneuploid conception?

SUMMARY ANSWER

Two SNVs were found in patients with extreme aneuploid concepti rates with respect to their age; one variant, AURKC p.I79V, is benign, while another, AURKB p.L39P, is a potential gain-of-function mutant with increased efficiency in promoting chromosome alignment.

WHAT IS KNOWN ALREADY

Maternal age does not always predict aneuploidy risk, and rare gene variants can be drivers of disease. The AURKB and AURKC regulate chromosome segregation, and are associated with reproductive impairments in mouse and human.

STUDY DESIGN, SIZE, DURATION

An extreme phenotype sample selection scheme was performed for variant discovery. Ninety-six DNA samples were from young patients with higher than average embryonic aneuploidy rates and an additional 96 DNA samples were from older patients with lower than average aneuploidy rates.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Using the192 DNA samples, the coding regions of AURKB and AURKC were sequenced using next generation sequencing. To assess biological significance, we expressed complementary RNA encoding the human variants in mouse oocytes. Assays such as determining subcellular localization and assessing catalytic activity were performed to determine alterations in protein function during meiosis.

MAIN RESULTS AND THE ROLE OF CHANCE

Ten SNVs were identified using three independent variant-calling methods. Two of the SNVs (AURKB p.L39P and AURKC p.I79V) were non-synonymous and identified by at least two variant-identification methods. The variant encoding AURKC p.I79V, identified in a young woman with a higher than average rate of aneuploid embryos, showed wild-type localization pattern and catalytic activity. On the other hand, the variant encoding AURKB p.L39P, identified in an older woman with lower than average rates of aneuploid embryos, increased the protein's ability to regulate alignment of chromosomes at the metaphase plate. These experiments were repeated three independent times using 2-3 mice for each trial.

LARGE SCALE DATA

N/A.

LIMITATIONS, REASONS FOR CAUTION

Biological significance of the human variants was assessed in an in vitro mouse oocyte model where the variants are over-expressed. Therefore, the human protein may not function identically to the mouse homolog, or the same in mouse oocytes as in human oocytes. Furthermore, supraphysiological expression levels may not accurately reflect endogenous activity. Moreover, the evaluated variants were identified in one patient each, and no trial linking the SNV to pregnancy outcomes was conducted. Finally, the patient aneuploidy rates were established by performing comprehensive chromosome screening in blastocysts, and because of the link between female gamete aneuploidy giving rise to aneuploid embryos, we evaluate the role of the variants in Meiosis I. However, it is possible that the chromosome segregation mistake arose during Meiosis II or in mitosis in the preimplantation embryo. Their implications in human female meiosis and aneuploidy risk remain to be determined.

WIDER IMPLICATIONS OF THE FINDINGS

The data provide evidence that gene variants exist in reproductively younger or advanced aged women that are predictive of the risk of producing aneuploid concepti in humans. Furthermore, a single amino acid in the N-terminus of AURKB is a gain-of-function mutant that could be protective of euploidy.

STUDY FUNDING/COMPETING INTERESTS

This work was supported by a Research Grant from the American Society of Reproductive Medicine and support from the Charles and Johanna Busch Memorial Fund at Rutgers, the State University of NJ to K.S. and the Foundation for Embryonic Competence, Inc to N.T. The authors declare no conflicts of interest.

GeneImp: Fast Imputation to Large Reference Panels Using Genotype Likelihoods from Ultralow Coverage Sequencing

We address the task of genotype imputation to a dense reference panel given genotype likelihoods computed from ultralow coverage sequencing as inputs. In this setting, the data have a high-level of missingness or uncertainty, and are thus more amenable to a probabilistic representation. Most existing imputation algorithms are not well suited for this situation, as they rely on prephasing for computational efficiency, and, without definite genotype calls, the prephasing task becomes computationally expensive. We describe GeneImp, a program for genotype imputation that does not require prephasing and is computationally tractable for whole-genome imputation. GeneImp does not explicitly model recombination, instead it capitalizes on the existence of large reference panels-comprising thousands of reference haplotypes-and assumes that the reference haplotypes can adequately represent the target haplotypes over short regions unaltered. We validate GeneImp based on data from ultralow coverage sequencing (0.5×), and compare its performance to the most recent version of BEAGLE that can perform this task. We show that GeneImp achieves imputation quality very close to that of BEAGLE, using one to two orders of magnitude less time, without an increase in memory complexity. Therefore, GeneImp is the first practical choice for whole-genome imputation to a dense reference panel when prephasing cannot be applied, for instance, in datasets produced via ultralow coverage sequencing. A related future application for GeneImp is whole-genome imputation based on the off-target reads from deep whole-exome sequencing.

Pathogenic variant burden in the ExAC database: an empirical approach to evaluating population data for clinical variant interpretation

Background

The frequency of a variant in the general population is a key criterion used in the clinical interpretation of sequence variants. With certain exceptions, such as founder mutations, the rarity of a variant is a prerequisite for pathogenicity. However, defining the threshold at which a variant should be considered “too common” is challenging and therefore diagnostic laboratories have typically set conservative allele frequency thresholds.

Methods

Recent publications of large population sequencing data, such as the Exome Aggregation Consortium (ExAC) database, provide an opportunity to characterize with accuracy and precision the frequency distributions of very rare disease-causing alleles. Allele frequencies of pathogenic variants in ClinVar, as well as variants expected to be pathogenic through the nonsense-mediated decay (NMD) pathway, were analyzed to study the burden of pathogenic variants in 79 genes of clinical importance.

Results

Of 1364 BRCA1 and BRCA2 variants that are well characterized as pathogenic or that are expected to lead to NMD, 1350 variants had an allele frequency of less than 0.0025%. The remaining 14 variants were previously published founder mutations. Importantly, we observed no difference in the distributions of pathogenic variants expected to be lead to NMD compared to those that are not. Therefore, we expanded the analysis to examine the distributions of NMD expected variants in 77 additional genes. These 77 genes were selected to represent a broad set of clinical areas, modes of inheritance, and penetrance. Among these variants, most (97.3%) had an allele frequency of less than 0.01%. Furthermore, pathogenic variants with allele frequencies greater than 0.01% were well characterized in publications and included many founder mutations.

Conclusions

The observations made in this study suggest that, with certain caveats, a very low allele frequency threshold can be adopted to more accurately interpret sequence variants.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-017-0403-7) contains supplementary material, which is available to authorized users.

The current state of clinical interpretation of sequence variants

Accurate and consistent variant classification is required for Precision Medicine. But clinical variant classification remains in its infancy. While recent guidelines put forth jointly by the American College of Medical Genetics and Genomics (ACMG) and Association of Molecular Pathology (AMP) for the classification of Mendelian variants has advanced the field, the degree of subjectivity allowed by these guidelines can still lead to inconsistent classification across clinical molecular genetic laboratories. In addition, there are currently no such guidelines for somatic cancer variants, only published institutional practices. Additional variant classification guidelines, including disease- or gene-specific criteria, along with inter-laboratory data sharing is critical for accurate and consistent variant interpretation.

Function-driven discovery of disease genes in zebrafish using an integrated genomics big data resource

Whole exome sequencing (WES) accelerates disease gene discovery using rare genetic variants, but further statistical and functional evidence is required to avoid false-discovery. To complement variant-driven disease gene discovery, here we present function-driven disease gene discovery in zebrafish (Danio rerio), a promising human disease model owing to its high anatomical and genomic similarity to humans. To facilitate zebrafish-based function-driven disease gene discovery, we developed a genome-scale co-functional network of zebrafish genes, DanioNet (www.inetbio.org/danionet), which was constructed by Bayesian integration of genomics big data. Rigorous statistical assessment confirmed the high prediction capacity of DanioNet for a wide variety of human diseases. To demonstrate the feasibility of the function-driven disease gene discovery using DanioNet, we predicted genes for ciliopathies and performed experimental validation for eight candidate genes. We also validated the existence of heterozygous rare variants in the candidate genes of individuals with ciliopathies yet not in controls derived from the UK10K consortium, suggesting that these variants are potentially involved in enhancing the risk of ciliopathies. These results showed that an integrated genomics big data for a model animal of diseases can expand our opportunity for harnessing WES data in disease gene discovery.

Analyses of more than 60,000 exomes questions the role of numerous genes previously associated with dilated cardiomyopathy

Background

Hundreds 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.

Methods

Variants 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.

Results

Of 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).

Conclusion

In 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.

Genetic Factors of the Disease Course After Sepsis: Rare Deleterious Variants Are Predictive

Sepsis is a life-threatening organ dysfunction caused by dysregulated host response to infection. For its clinical course, host genetic factors are important and rare genomic variants are suspected to contribute. We sequenced the exomes of 59 Greek and 15 German patients with bacterial sepsis divided into two groups with extremely different disease courses. Variant analysis was focusing on rare deleterious single nucleotide variants (SNVs).

We identified significant differences in the number of rare deleterious SNVs per patient between the ethnic groups. Classification experiments based on the data of the Greek patients allowed discrimination between the disease courses with estimated sensitivity and specificity > 75%. By application of the trained model to the German patients we observed comparable discriminatory properties despite lower population-specific rare SNV load. Furthermore, rare SNVs in genes of cell signaling and innate immunity related pathways were identified as classifiers discriminating between the sepsis courses.

Sepsis patients with favorable disease course after sepsis, even in the case of unfavorable preconditions, seem to be affected more often by rare deleterious SNVs in cell signaling and innate immunity related pathways, suggesting a protective role of impairments in these processes against a poor disease course.

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Rare SNV load is higher in the Greek vs. German population.

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Subsets of rare deleterious SNVs are predictive for the disease course after sepsis.

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Patients with favorable disease course seem to carry protective deleterious variants in sepsis related pathways.

Sepsis is a life-threatening disease caused by improper response to infection. Only little is known about the role of genetic factors. From > 4000 patients we selected the most extreme cases showing either a favorable or adverse disease course. We determined rare (< 1/200) protein-damaging genetic variants, as they may have a large effect. Using a computational model that includes knowledge on genes we can predict the disease course with > 75% accuracy. Surprisingly, favorable courses can be expected if defense mechanisms are damaged and prevented from overshooting. This underlines the relevance of rare variants for better understanding of sepsis and may offer new treatment options.

Exploration of pathomechanisms triggered by a single-nucleotide polymorphism in titin's I-band: the cardiomyopathy-linked mutation T2580I

Missense single-nucleotide polymorphisms (mSNPs) in titin are emerging as a main causative factor of heart failure. However, distinguishing between benign and disease-causing mSNPs is a substantial challenge. Here, we research the question of whether a single mSNP in a generic domain of titin can affect heart function as a whole and, if so, how. For this, we studied the mSNP T2850I, seemingly linked to arrhythmogenic right ventricular cardiomyopathy (ARVC). We used structural biology, computational simulations and transgenic muscle in vivo methods to track the effect of the mutation from the molecular to the organismal level. The data show that the T2850I exchange is compatible with the domain three-dimensional fold, but that it strongly destabilizes it. Further, it induces a change in the conformational dynamics of the titin chain that alters its reactivity, causing the formation of aberrant interactions in the sarcomere. Echocardiography of knock-in mice indicated a mild diastolic dysfunction arising from increased myocardial stiffness. In conclusion, our data provide evidence that single mSNPs in titin's I-band can alter overall muscle behaviour. Our suggested mechanisms of disease are the development of non-native sarcomeric interactions and titin instability leading to a reduced I-band compliance. However, understanding the T2850I-induced ARVC pathology mechanistically remains a complex problem and will require a deeper understanding of the sarcomeric context of the titin region affected.

Genetic Misdiagnoses and the Potential for Health Disparities

BACKGROUND

For more than a decade, risk stratification for hypertrophic cardiomyopathy has been enhanced by targeted genetic testing. Using sequencing results, clinicians routinely assess the risk of hypertrophic cardiomyopathy in a patient's relatives and diagnose the condition in patients who have ambiguous clinical presentations. However, the benefits of genetic testing come with the risk that variants may be misclassified.

METHODS

Using publicly accessible exome data, we identified variants that have previously been considered causal in hypertrophic cardiomyopathy and that are overrepresented in the general population. We studied these variants in diverse populations and reevaluated their initial ascertainments in the medical literature. We reviewed patient records at a leading genetic-testing laboratory for occurrences of these variants during the near-decade-long history of the laboratory.

RESULTS

Multiple patients, all of whom were of African or unspecified ancestry, received positive reports, with variants misclassified as pathogenic on the basis of the understanding at the time of testing. Subsequently, all reported variants were recategorized as benign. The mutations that were most common in the general population were significantly more common among black Americans than among white Americans (P<0.001). Simulations showed that the inclusion of even small numbers of black Americans in control cohorts probably would have prevented these misclassifications. We identified methodologic shortcomings that contributed to these errors in the medical literature.

CONCLUSIONS

The misclassification of benign variants as pathogenic that we found in our study shows the need for sequencing the genomes of diverse populations, both in asymptomatic controls and the tested patient population. These results expand on current guidelines, which recommend the use of ancestry-matched controls to interpret variants. As additional populations of different ancestry backgrounds are sequenced, we expect variant reclassifications to increase, particularly for ancestry groups that have historically been less well studied. (Funded by the National Institutes of Health.).

EFHC1 variants in juvenile myoclonic epilepsy: reanalysis according to NHGRI and ACMG guidelines for assigning disease causality

PURPOSE

EFHC1 variants are the most common mutations in inherited myoclonic and grand mal clonic-tonic-clonic (CTC) convulsions of juvenile myoclonic epilepsy (JME). We reanalyzed 54 EFHC1 variants associated with epilepsy from 17 cohorts based on National Human Genome Research Institute (NHGRI) and American College of Medical Genetics and Genomics (ACMG) guidelines for interpretation of sequence variants.

METHODS

We calculated Bayesian LOD scores for variants in coinheritance, unconditional exact tests and odds ratios (OR) in case-control associations, allele frequencies in genome databases, and predictions for conservation/pathogenicity. We reviewed whether variants damage EFHC1 functions, whether efhc1^-/- KO mice recapitulate CTC convulsions and "microdysgenesis" neuropathology, and whether supernumerary synaptic and dendritic phenotypes can be rescued in the fly model when EFHC1 is overexpressed. We rated strengths of evidence and applied ACMG combinatorial criteria for classifying variants.

RESULTS

Nine variants were classified as "pathogenic," 14 as "likely pathogenic," 9 as "benign," and 2 as "likely benign." Twenty variants of unknown significance had an insufficient number of ancestry-matched controls, but ORs exceeded 5 when compared with racial/ethnic-matched Exome Aggregation Consortium (ExAC) controls.

CONCLUSIONS

NHGRI gene-level evidence and variant-level evidence establish EFHC1 as the first non-ion channel microtubule-associated protein whose mutations disturb R-type VDCC and TRPM2 calcium currents in overgrown synapses and dendrites within abnormally migrated dislocated neurons, thus explaining CTC convulsions and "microdysgenesis" neuropathology of JME.Genet Med 19 2, 144-156.

Using Population Genetics to Interrogate the Monogenic Nephrotic Syndrome Diagnosis in a Case Cohort

To maximize clinical benefits of genetic screening of patients with nephrotic syndrome (NS) to diagnose monogenic causes, reliably distinguishing NS-causing variants from the background of rare, noncausal variants prevalent in all genomes is vital. To determine the prevalence of monogenic NS in a North American case cohort while accounting for background prevalence of genetic variation, we sequenced 21 implicated monogenic NS genes in 312 participants from the Nephrotic Syndrome Study Network and 61 putative controls from the 1000 Genomes Project (1000G). These analyses were extended to available sequence data from approximately 2500 subjects from the 1000G. A typical pathogenicity filter identified causal variants for NS in 4.2% of patients and 5.8% of subjects from the 1000G. We devised a more stringent pathogenicity filtering strategy, reducing background prevalence of causal variants to 1.5%. When applying this stringent filter to patients, prevalence of monogenic NS was 2.9%; of these patients, 67% were pediatric, and 44% had FSGS on biopsy. The rate of complete remission did not associate with monogenic classification. Thus, we identified factors contributing to inaccurate monogenic classification of NS and developed a more accurate variant filtering strategy. The prevalence and clinical correlates of monogenic NS in this sporadically affected cohort differ substantially from those reported for patients referred for genetic analysis. Particularly in unselected, population-based cases, considering putative causal variants in known NS genes from a probabilistic rather than a deterministic perspective may be more precise. We also introduce GeneVetter, a web tool for monogenic assessment of rare disease.

Mutations in NEBL encoding the cardiac Z-disk protein nebulette are associated with various cardiomyopathies

INTRODUCTION

Transgenic mice overexpressing mutated NEBL, encoding the cardiac-specific Z-disk protein nebulette, develop severe cardiac phenotypes. Since cardiomyopathies are commonly familial and because mutations in a single gene may result in variable phenotypes, we tested the hypothesis that NEBL mutations are associated with cardiomyopathy.

MATERIAL AND METHODS

We analyzed 389 patients, including cohorts of patients with dilated cardiomyopathy (DCM), hypertrophic cardiomyopathy (HCM), and left ventricular non-compaction cardiomyopathy (LVNC). The 28 coding exons of the NEBL gene were sequenced. Further bioinformatic analysis was used to distinguish variants.

RESULTS

In total, we identified six very rare heterozygous missense mutations in NEBL in 7 different patients (frequency 1.8%) in highly conserved codons. The mutations were not detectable in 320 Caucasian sex-matched unrelated individuals without cardiomyopathy and 192 Caucasian sex-matched blood donors without heart disease. Known cardiomyopathy genes were excluded in these patients. The mutations p.H171R and p.I652L were found in 2 HCM patients. Further, p.Q581R and p.S747L were detected in 2 DCM patients, while the mutation p.A175T was identified independently in two unrelated patients with DCM. One LVNC patient carried the mutation p.P916L. All HCM and DCM related mutations were located in the nebulin-like repeats, domains responsible for actin binding. Interestingly, the mutation associated with LVNC was located in the C-terminal serine-rich linker region.

CONCLUSIONS

Our data suggest that NEBL mutations may cause various cardiomyopathies. We herein describe the first NEBL mutations in HCM and LVNC. Our findings underline the notion that the cardiomyopathies are true allelic diseases.