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.

DECIPHER: Improving Genetic Diagnosis Through Dynamic Integration of Genomic and Clinical Data.

DECIPHER (Database of Genomic Variation and Phenotype in Humans Using Ensembl Resources) shares candidate diagnostic variants and phenotypic data from patients with genetic disorders to facilitate research and improve the diagnosis, management, and therapy of rare diseases. The platform sits at the boundary between genomic research and the clinical community. DECIPHER aims to ensure that the most up-to-date data are made rapidly available within its interpretation interfaces to improve clinical care. Newly integrated cardiac case-control data that provide evidence of gene-disease associations and inform variant interpretation exemplify this mission. New research resources are presented in a format optimized for use by a broad range of professionals supporting the delivery of genomic medicine. The interfaces within DECIPHER integrate and contextualize variant and phenotypic data, helping to determine a robust clinico-molecular diagnosis for rare-disease patients, which combines both variant classification and clinical fit. DECIPHER supports discovery research, connecting individuals within the rare-disease community to pursue hypothesis-driven research.

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.

Reevaluating the Genetic Contribution of Monogenic Dilated Cardiomyopathy.

BACKGROUND: Dilated cardiomyopathy (DCM) is genetically heterogeneous, with >100 purported disease genes tested in clinical laboratories. However, many genes were originally identified based on candidate-gene studies that did not adequately account for background population variation. Here we define the frequency of rare variation in 2538 patients with DCM across protein-coding regions of 56 commonly tested genes and compare this to both 912 confirmed healthy controls and a reference population of 60 706 individuals to identify clinically interpretable genes robustly associated with dominant monogenic DCM. METHODS: We used the TruSight Cardio sequencing panel to evaluate the burden of rare variants in 56 putative DCM genes in 1040 patients with DCM and 912 healthy volunteers processed with identical sequencing and bioinformatics pipelines. We further aggregated data from 1498 patients with DCM sequenced in diagnostic laboratories and the Exome Aggregation Consortium database for replication and meta-analysis. RESULTS: Truncating variants in TTN and DSP were associated with DCM in all comparisons. Variants in MYH7, LMNA, BAG3, TNNT2, TNNC1, PLN, ACTC1, NEXN, TPM1, and VCL were significantly enriched in specific patient subsets, with the last 2 genes potentially contributing primarily to early-onset forms of DCM. Overall, rare variants in these 12 genes potentially explained 17% of cases in the outpatient clinic cohort representing a broad range of adult patients with DCM and 26% of cases in the diagnostic referral cohort enriched in familial and early-onset DCM. Although the absence of a significant excess in other genes cannot preclude a limited role in disease, such genes have limited diagnostic value because novel variants will be uninterpretable and their diagnostic yield is minimal. CONCLUSIONS: In the largest sequenced DCM cohort yet described, we observe robust disease association with 12 genes, highlighting their importance in DCM and translating into high interpretability in diagnostic testing. The other genes analyzed here will need to be rigorously evaluated in ongoing curation efforts to determine their validity as Mendelian DCM genes but have limited value in diagnostic testing in DCM at present. This data will contribute to community gene curation efforts and will reduce erroneous and inconclusive findings in diagnostic testing.

Genetic Variants Associated With Cancer Therapy-Induced Cardiomyopathy.

BACKGROUND: Cancer therapy-induced cardiomyopathy (CCM) is associated with cumulative drug exposures and preexisting cardiovascular disorders. These parameters incompletely account for substantial interindividual susceptibility to CCM. We hypothesized that rare variants in cardiomyopathy genes contribute to CCM. METHODS: We studied 213 patients with CCM from 3 cohorts: retrospectively recruited adults with diverse cancers (n=99), prospectively phenotyped adults with breast cancer (n=73), and prospectively phenotyped children with acute myeloid leukemia (n=41). Cardiomyopathy genes, including 9 prespecified genes, were sequenced. The prevalence of rare variants was compared between CCM cohorts and The Cancer Genome Atlas participants (n=2053), healthy volunteers (n=445), and an ancestry-matched reference population. Clinical characteristics and outcomes were assessed and stratified by genotypes. A prevalent CCM genotype was modeled in anthracycline-treated mice. RESULTS: CCM was diagnosed 0.4 to 9 years after chemotherapy; 90% of these patients received anthracyclines. Adult patients with CCM had cardiovascular risk factors similar to the US population. Among 9 prioritized genes, patients with CCM had more rare protein-altering variants than comparative cohorts ( P≤1.98e-04). Titin-truncating variants (TTNtvs) predominated, occurring in 7.5% of patients with CCM versus 1.1% of The Cancer Genome Atlas participants ( P=7.36e-08), 0.7% of healthy volunteers ( P=3.42e-06), and 0.6% of the reference population ( P=5.87e-14). Adult patients who had CCM with TTNtvs experienced more heart failure and atrial fibrillation ( P=0.003) and impaired myocardial recovery ( P=0.03) than those without. Consistent with human data, anthracycline-treated TTNtv mice and isolated TTNtv cardiomyocytes showed sustained contractile dysfunction unlike wild-type ( P=0.0004 and P<0.002, respectively). CONCLUSIONS: Unrecognized rare variants in cardiomyopathy-associated genes, particularly TTNtvs, increased the risk for CCM in children and adults, and adverse cardiac events in adults. Genotype, along with cumulative chemotherapy dosage and traditional cardiovascular risk factors, improves the identification of patients who have cancer at highest risk for CCM. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov . Unique identifiers: NCT01173341; AAML1031; NCT01371981.

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.

ViroFind: A novel target-enrichment deep-sequencing platform reveals a complex JC virus population in the brain of PML patients.

Deep nucleotide sequencing enables the unbiased, broad-spectrum detection of viruses in clinical samples without requiring an a priori hypothesis for the source of infection. However, its use in clinical research applications is limited by low cost-effectiveness given that most of the sequencing information from clinical samples is related to the human genome, which renders the analysis of viral genomes challenging. To overcome this limitation we developed ViroFind, an in-solution target-enrichment platform for virus detection and discovery in clinical samples. ViroFind comprises 165,433 viral probes that cover the genomes of 535 selected DNA and RNA viruses that infect humans or could cause zoonosis. The ViroFind probes are used in a hybridization reaction to enrich viral sequences and therefore enhance the detection of viral genomes via deep sequencing. We used ViroFind to detect and analyze all viral populations in the brain of 5 patients with progressive multifocal leukoencephalopathy (PML) and of 18 control subjects with no known neurological disease. Compared to direct deep sequencing, by using ViroFind we enriched viral sequences present in the clinical samples up to 127-fold. We discovered highly complex polyoma virus JC populations in the PML brain samples with a remarkable degree of genetic divergence among the JC virus variants of each PML brain sample. Specifically for the viral capsid protein VP1 gene, we identified 24 single nucleotide substitutions, 12 of which were associated with amino acid changes. The most frequent (4 of 5 samples, 80%) amino acid change was D66H, which is associated with enhanced tissue tropism, and hence likely a viral fitness advantage, compared to other variants. Lastly, we also detected sparse JC virus sequences in 10 of 18 (55.5%) of control samples and sparse human herpes virus 6B (HHV6B) sequences in the brain of 11 of 18 (61.1%) control subjects. In sum, ViroFind enabled the in-depth analysis of all viral genomes in PML and control brain samples and allowed us to demonstrate a high degree of JC virus genetic divergence in vivo that has been previously underappreciated. ViroFind can be used to investigate the structure of the virome with unprecedented depth in health and disease state.

The Long Noncoding RNA Landscape of the Ischemic Human Left Ventricle.

BACKGROUND: The discovery of functional classes of long noncoding RNAs (lncRNAs) has expanded our understanding of the variety of RNA species that exist in cells. In the heart, lncRNAs have been implicated in the regulation of development, ischemic and dilated cardiomyopathy, and myocardial infarction. Nevertheless, there is a limited description of expression profiles for these transcripts in human subjects. METHODS AND RESULTS: We obtained left ventricular tissue from human patients undergoing cardiac surgery and used RNA sequencing to describe an lncRNA profile. We then identified a list of lncRNAs that were differentially expressed between pairs of samples before and after the ischemic insult of cardiopulmonary bypass. The expression of some of these lncRNAs correlates with ischemic time. Coding genes in close proximity to differentially expressed lncRNAs and coding genes that have coordinated expression with these lncRNAs are enriched in functional categories related to myocardial infarction, including heart function, metabolism, the stress response, and the immune system. CONCLUSIONS: We describe a list of lncRNAs that are differentially expressed after ischemia in the human heart. These genes are predicted to function in pathways consistent with myocardial injury. As a result, lncRNAs may serve as novel diagnostic and therapeutic targets for ischemic heart disease. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT00985049.

Shared Genetic Predisposition in Peripartum and Dilated Cardiomyopathies.

Background Peripartum cardiomyopathy shares some clinical features with idiopathic dilated cardiomyopathy, a disorder caused by mutations in more than 40 genes, including TTN, which encodes the sarcomere protein titin. Methods In 172 women with peripartum cardiomyopathy, we sequenced 43 genes with variants that have been associated with dilated cardiomyopathy. We compared the prevalence of different variant types (nonsense, frameshift, and splicing) in these women with the prevalence of such variants in persons with dilated cardiomyopathy and with population controls. Results We identified 26 distinct, rare truncating variants in eight genes among women with peripartum cardiomyopathy. The prevalence of truncating variants (26 in 172 [15%]) was significantly higher than that in a reference population of 60,706 persons (4.7%, P=1.3×10(-7)) but was similar to that in a cohort of patients with dilated cardiomyopathy (55 of 332 patients [17%], P=0.81). Two thirds of identified truncating variants were in TTN, as seen in 10% of the patients and in 1.4% of the reference population (P=2.7×10(-10)); almost all TTN variants were located in the titin A-band. Seven of the TTN truncating variants were previously reported in patients with idiopathic dilated cardiomyopathy. In a clinically well-characterized cohort of 83 women with peripartum cardiomyopathy, the presence of TTN truncating variants was significantly correlated with a lower ejection fraction at 1-year follow-up (P=0.005). Conclusions The distribution of truncating variants in a large series of women with peripartum cardiomyopathy was remarkably similar to that found in patients with idiopathic dilated cardiomyopathy. TTN truncating variants were the most prevalent genetic predisposition in each disorder.

Using next-generation RNA sequencing to examine ischemic changes induced by cold blood cardioplegia on the human left ventricular myocardium transcriptome.

BACKGROUND: The exact mechanisms that underlie the pathological processes of myocardial ischemia in humans are unclear. Cardiopulmonary bypass with cardioplegic arrest allows the authors to examine the whole transcriptional profile of human left ventricular myocardium at baseline and after exposure to cold cardioplegia-induced ischemia as a human ischemia model. METHODS: The authors obtained biopsies from 45 patients undergoing aortic valve replacement surgery at baseline and after an average of 79 min of cold cardioplegic arrest. Samples were RNA sequenced and analyzed with the Partek Genomics Suite (Partek Inc., St. Louis, MO) for differential expression. Ingenuity Pathway Analysis (Ingenuity Systems, Redwood City, CA) and Biobase ExPlain (Biobase GmbH, Wolfenbuettel, Germany) systems were used for functional and pathway analyses. RESULTS: Of the 4,098 genes with a mean expression value greater than 5, 90% were down-regulated and 9.1% were up-regulated. Of those, 1,241 were significantly differentially expressed. Gene ontology analysis revealed significant down-regulation in immune inflammatory response and complement activation categories and highly consistent was the down-regulation of intelectin 1, proteoglycan, and secretory leukocyte peptidase inhibitor. Up-regulated genes of interest were FBJ murine osteosarcoma viral oncogene homolog and the hemoglobin genes hemoglobin α1 (HBA1) and hemoglobin ß. In addition, analysis of transcription factor-binding sites revealed interesting targets in factors regulating reactive oxygen species production, apoptosis, immunity, cytokine production, and inflammatory response. CONCLUSIONS: The authors have shown that the human left ventricle exhibits significant changes in gene expression in response to cold cardioplegia-induced ischemia during cardiopulmonary bypass, which provides great insight into the pathophysiology of ventricular ischemia, and thus, may help guide efforts to reduce myocardial damage during surgery.

Increased frequency of de novo copy number variants in congenital heart disease by integrative analysis of single nucleotide polymorphism array and exome sequence data.

RATIONALE: Congenital heart disease (CHD) is among the most common birth defects. Most cases are of unknown pathogenesis. OBJECTIVE: To determine the contribution of de novo copy number variants (CNVs) in the pathogenesis of sporadic CHD. METHODS AND RESULTS: We studied 538 CHD trios using genome-wide dense single nucleotide polymorphism arrays and whole exome sequencing. Results were experimentally validated using digital droplet polymerase chain reaction. We compared validated CNVs in CHD cases with CNVs in 1301 healthy control trios. The 2 complementary high-resolution technologies identified 63 validated de novo CNVs in 51 CHD cases. A significant increase in CNV burden was observed when comparing CHD trios with healthy trios, using either single nucleotide polymorphism array (P=7×10(-5); odds ratio, 4.6) or whole exome sequencing data (P=6×10(-4); odds ratio, 3.5) and remained after removing 16% of de novo CNV loci previously reported as pathogenic (P=0.02; odds ratio, 2.7). We observed recurrent de novo CNVs on 15q11.2 encompassing CYFIP1, NIPA1, and NIPA2 and single de novo CNVs encompassing DUSP1, JUN, JUP, MED15, MED9, PTPRE SREBF1, TOP2A, and ZEB2, genes that interact with established CHD proteins NKX2-5 and GATA4. Integrating de novo variants in whole exome sequencing and CNV data suggests that ETS1 is the pathogenic gene altered by 11q24.2-q25 deletions in Jacobsen syndrome and that CTBP2 is the pathogenic gene in 10q subtelomeric deletions. CONCLUSIONS: We demonstrate a significantly increased frequency of rare de novo CNVs in CHD patients compared with healthy controls and suggest several novel genetic loci for CHD.

Nationwide study on hypertrophic cardiomyopathy in Iceland: evidence of a MYBPC3 founder mutation.

BACKGROUND: The geographic isolation and homogeneous population of Iceland are ideally suited to ascertain clinical and genetic characteristics of hypertrophic cardiomyopathy (HCM) at the population level. METHODS AND RESULTS: Medical records and cardiac imaging studies obtained between 1997 and 2010 were reviewed to identify Icelandic patients with HCM. Surviving patients were recruited for clinical and genetic studies. A previously identified Icelandic mutation, MYBPC3 c.927-2A>G, was genotyped, and mutation-negative samples were sequenced for HCM genes and other hypertrophic genes. Record review identified 180 patients with HCM. Genetic analyses of 151 patients defined pathogenic mutations in 101 (67%), including MYBPC3 c.927-2A>G (88 patients, 58%), 4 other MYBPC3 or MYH7 mutations (5 patients, 3.3%), and 2 GLA mutations (8 patients, 5.3%). Haplotype and genetic genealogical data defined MYBPC3 c.927-2A>G as a founder mutation, introduced into the Icelandic population in the 15th century, with a current population prevalence of 0.36%. MYBPC3 c.927-2A>G mutation carriers exhibited phenotypic diversity but were younger at diagnosis (42 versus 49 years; P=0.001) and sustained more adverse events (15% versus 2%; P=0.02) than mutation-negative patients. All-cause mortality for patients with HCM was similar to that of an age-matched Icelandic population (hazard ratio, 0.98; P=0.9). HCM-related mortality (0.78%/y) occurred at a mean age of 68 compared with 81 years for non-HCM-related mortality (P=0.02). CONCLUSIONS: A founder MYBPC3 mutation that arose >550 years ago is the predominant cause of HCM in Iceland. The MYBPC3 c.927-2A>G mutation is associated with low adverse event rates but earlier cardiovascular mortality, illustrating the impact of genotype on outcomes in HCM.

Digital Droplet PCR: CNV Analysis and Other Applications.

Digital droplet PCR (ddPCR) is an assay that combines state-of-the-art microfluidics technology with TaqMan-based PCR to achieve precise target DNA quantification at high levels of sensitivity and specificity. Because quantification is achieved without the need for standard assays in an easy to interpret, unambiguous digital readout, ddPCR is far simpler, faster, and less error prone than real-time qPCR. The basic protocol can be modified with minor adjustments to suit a wide range of applications, such as CNV analysis, rare variant detection, SNP genotyping, and transcript quantification. This unit describes the ddPCR workflow in detail for the Bio-Rad QX100 system, but the theory and data interpretation are generalizable to any ddPCR system.

Optimization of protocol for sequencing of difficult templates.

In this paper, we have fine-tuned a DNA sequencing protocol suitable for a wide range of difficult templates. The primary goal was to evaluate a number of parameters--such as various dye terminator mixes in the presence or absence of additives, the amount of DNA or primer, and cycling protocols--about the effectiveness of reading through complex regions. We showed that the modification of a published protocol leads to significant (75%) cost reduction without forfeiting quality of the data. In the recommended protocol, we used betaine as a standard additive, but better results can be obtained when betaine and Reagent A are mixed in an equivalent ratio.