Explore the vast range of titles available.

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.

Increasing numbers of genes are being implicated in Mendelian disorders and incorporated into clinical test panels. However, lack of evidence supporting the gene-disease relationship can hinder interpretation. We explored the utility of testing 51 additional genes for hypertrophic cardiomyopathy (HCM), one of the most commonly tested Mendelian disorders. Using genome sequencing data from 240 sarcomere gene negative HCM cases and 6229 controls, we undertook case-control and individual variant analyses to assess 51 genes that have been proposed for HCM testing. We found no evidence to suggest that rare variants in these genes are prevalent causes of HCM. One variant, in a single case, was categorized as likely to be pathogenic. Over 99% of variants were classified as a variant of uncertain significance (VUS) and 54% of cases had one or more VUS. For almost all genes, the gene-disease relationship could not be validated and lack of evidence precluded variant interpretation. Thus, the incremental diagnostic yield of extending testing was negligible, and would, we propose, be outweighed by problems that arise with a high rate of uninterpretable findings. These findings highlight the need for rigorous, evidence-based selection of genes for clinical test panels.

Background A multi-disciplinary approach to promote engagement, inform decision-making and support clinicians and patients is increasingly advocated to realise the potential of genome-scale sequencing in the clinic for patient benefit. Here we describe the results of establishing a genomic medicine multi-disciplinary team (GM-MDT) for case selection, processing, interpretation and return of results. Methods We report a consecutive case series of 132 patients (involving 10 medical specialties with 43.2% cases having a neurological disorder) undergoing exome sequencing over a 10-month period following the establishment of the GM-MDT in a UK NHS tertiary referral hospital. The costs of running the MDT are also reported. Results In total 76 cases underwent exome sequencing following triage by the GM-MDT with a clinically reportable molecular diagnosis in 24 (31.6%). GM-MDT composition, operation and rationale for whether to proceed to sequencing are described, together with the health economics (cost per case for the GM-MDT was £399.61), the utility and informativeness of exome sequencing for molecular diagnosis in a range of traits, the impact of choice of sequencing strategy on molecular diagnostic rates and challenge of defining pathogenic variants. In 5 cases (6.6%), an alternative clinical diagnosis was indicated by sequencing results. Examples were also found where findings from initial genetic testing were reconsidered in the light of exome sequencing including TP63 and PRKAG2 (detection of a partial exon deletion and a mosaic missense pathogenic variant respectively); together with tissue-specific mosaicism involving a cytogenetic abnormality following a normal prenatal array comparative genomic hybridization. Conclusions This consecutive case series describes the results and experience of a multidisciplinary team format that was found to promote engagement across specialties and facilitate return of results to the responsible clinicians.

The accurate interpretation of variation in Mendelian disease genes has lagged behind data generation as sequencing has become increasingly accessible. Ongoing large sequencing efforts present huge interpretive challenges, but they also provide an invaluable opportunity to characterize the spectrum and importance of rare variation. We analyzed sequence data from 7,855 clinical cardiomyopathy cases and 60,706 Exome Aggregation Consortium (ExAC) reference samples to obtain a better understanding of genetic variation in a representative autosomal dominant disorder. We found that in some genes previously reported as important causes of a given cardiomyopathy, rare variation is not clinically informative because there is an unacceptably high likelihood of false-positive interpretation. By contrast, in other genes, we find that diagnostic laboratories may be overly conservative when assessing variant pathogenicity. We outline improved analytical approaches that evaluate which genes and variant classes are interpretable and propose that these will increase the clinical utility of testing across a range of Mendelian diseases.

Inherited cardiomyopathies and arrhythmias (ICAs) are a prevalent and clinically heterogeneous group of genetic disorders that are associated with increased risk of sudden cardiac death and heart failure. Making a genetic diagnosis can inform the management of patients and their at-risk relatives and, as such, molecular genetic testing is now considered an integral component of the clinical care pathway. However, ICAs are characterised by high genetic and allelic heterogeneity, incomplete / age-related penetrance, and variable expressivity. Therefore, despite our improved understanding of the genetic basis of these conditions, and significant technological advances over the past two decades, identifying and recognising the causative genotype remains challenging. As clinical genetic testing for ICAs becomes more widely available, it is increasingly important for clinical laboratories to consolidate existing knowledge and experience to inform and improve future practice. These recommendations have been compiled to help clinical laboratories navigate the challenges of ICAs and thereby facilitate best practice and consistency in genetic test provision for this group of disorders. General recommendations on internal and external quality control, referral, analysis, result interpretation, and reporting are described. Also included are appendices that provide specific information pertinent to genetic testing for hypertrophic, dilated, and arrhythmogenic right ventricular cardiomyopathies, long QT syndrome, Brugada syndrome, and catecholaminergic polymorphic ventricular tachycardia.

Disclosing secondary findings (SF) from genome sequencing (GS) can alert carriers to disease risk. However, evidence around variant-disease association and consequences of disclosure for individuals and healthcare services is limited. We report on the feasibility of an approach to identification of SF in inherited cardiac conditions (ICC) genes in participants in a rare disease GS study, followed by targeted clinical evaluation. Qualitative methods were used to explore behavioural and psychosocial consequences of disclosure. ICC genes were analysed in genome sequence data from 7203 research participants; a two-stage approach was used to recruit genotype-blind variant carriers and matched controls. Cardiac-focused medical and family history collection and genetic counselling were followed by standard clinical tests, blinded to genotype. Pathogenic ICC variants were identified in 0.61% of individuals; 20 were eligible for the present study. Four variant carriers and seven non-carrier controls participated. One variant carrier had a family history of ICC and was clinically affected; a second was clinically unaffected and had no relevant family history. One variant, in two unrelated participants, was subsequently reclassified as being of uncertain significance. Analysis of qualitative data highlights participant satisfaction with approach, willingness to follow clinical recommendations, but variable outcomes of relatives’ engagement with healthcare services. In conclusion, when offered access to SF, many people choose not to pursue them. For others, disclosure of ICC SF in a specialist setting is valued and of likely clinical utility, and can be expected to identify individuals with, and without a phenotype.

Next generation sequencing (NGS) approaches are moving from research into clinical practice. However, the optimal NGS approach in well-defined adult-onset familial diseases, such as inherited cardiovascular disease, remains unclear. We aimed to determine which attributes encouraged or discouraged the uptake of genomic tests in this context, and whether this differed by test type. We conducted a web-based discrete choice experiment in health professionals in the UK who order NGS tests for inherited cardiovascular disease. Respondents completed 12 hypothetical choice tasks in which they selected a preferred test from four alternatives: whole genome sequencing, whole exome sequencing, panel testing and genetic testing not indicated. Tests were specified in terms of five attributes: diagnostic yield, detection rate for variants of unknown significance, cost, quantity of counselling received and disclosure of secondary findings. Mixed logit regression analysis was used to analyse the choice data. We found that uptake of NGS increases if tests identify more pathogenic mutations, identify fewer variants of unknown significance, or cost less. Respondents were willing to pay £117 for every 1% increase in diagnostic yield. Considerable heterogeneity was observed around preferences for several test attributes. Overall, panel testing had the highest predicted uptake rate. Our results indicate that NGS tests are valued by health professionals for well-defined adult-onset familial diseases, however, these professionals have strong preferences for panel testing rather than whole genome sequencing and whole exome sequencing. This finding suggests that different uptake rates should be explicitly modelled when designing and evaluating future genomic testing services.

Cardiomyopathies are a diverse group of cardiac disorders with distinct phenotypes, depending on the proteins and pathways affected. A substantial proportion of cardiomyopathies are inherited and those will be the focus of this review article. With the wide application of high-throughput sequencing in the practice of clinical genetics, the roles of novel genes in cardiomyopathies are recognised. Here, we focus on a subgroup of cardiomyopathy genes [TTN, FHL1, CSRP3, FLNC and PLN, coding for Titin, Four and a Half LIM domain 1, Muscle LIM Protein, Filamin C and Phospholamban, respectively], which, despite their diverse biological functions, all have important signalling functions in the heart, suggesting that disturbances in signalling networks can contribute to cardiomyopathies.

Hypertrophic cardiomyopathy (HCM) is a common, serious, genetic heart disorder. Rare pathogenic variants in sarcomere genes cause HCM, but with unexplained phenotypic heterogeneity. Moreover, most patients do not carry such variants. We report a genome-wide association study of 2,780 cases and 47,486 controls that identified 12 genome-wide-significant susceptibility loci for HCM. Single-nucleotide polymorphism heritability indicated a strong polygenic influence, especially for sarcomere-negative HCM (64% of cases; h 2 g  = 0.34 ± 0.02). A genetic risk score showed substantial influence on the odds of HCM in a validation study, halving the odds in the lowest quintile and doubling them in the highest quintile, and also influenced phenotypic severity in sarcomere variant carriers. Mendelian randomization identified diastolic blood pressure (DBP) as a key modifiable risk factor for sarcomere-negative HCM, with a one standard deviation increase in DBP increasing the HCM risk fourfold. Common variants and modifiable risk factors have important roles in HCM that we suggest will be clinically actionable. Genome-wide association analyses identify 12 susceptibility loci for hypertrophic cardiomyopathy (HCM). A genetic risk score for HCM was associated with disease status in a validation study and influenced phenotypic severity in carriers of risk variants in sarcomere genes.

Hypertrophic cardiomyopathy (HCM) is an important cause of morbidity and mortality with both monogenic and polygenic components. Here, we report results from a large genome-wide association study and multitrait analysis including 5,900 HCM cases, 68,359 controls and 36,083 UK Biobank participants with cardiac magnetic resonance imaging. We identified 70 loci (50 novel) associated with HCM and 62 loci (20 novel) associated with relevant left ventricular traits. Among the prioritized genes in the HCM loci, we identify a novel HCM disease gene, SVIL , which encodes the actin-binding protein supervillin, showing that rare truncating SVIL variants confer a roughly tenfold increased risk of HCM. Mendelian randomization analyses support a causal role of increased left ventricular contractility in both obstructive and nonobstructive forms of HCM, suggesting common disease mechanisms and anticipating shared response to therapy. Taken together, these findings increase our understanding of the genetic basis of HCM, with potential implications for disease management. Genome-wide and multitrait analyses identify novel loci associated with hypertrophic cardiomyopathy and relevant left ventricular traits. Gene-level burden analyses show that rare truncating SVIL variants are associated with high risk of hypertrophic cardiomyopathy.