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A genetic etiology is identified for one-third of patients with congenital heart disease (CHD), with 8% of cases attributable to coding de novo variants (DNVs). To assess the contribution of noncoding DNVs to CHD, we compared genome sequences from 749 CHD probands and their parents with those from 1,611 unaffected trios. Neural network prediction of noncoding DNV transcriptional impact identified a burden of DNVs in individuals with CHD (n = 2,238 DNVs) compared to controls (n = 4,177; P = 8.7 × 10-4). Independent analyses of enhancers showed an excess of DNVs in associated genes (27 genes versus 3.7 expected, P = 1 × 10-5). We observed significant overlap between these transcription-based approaches (odds ratio (OR) = 2.5, 95% confidence interval (CI) 1.1-5.0, P = 5.4 × 10-3). CHD DNVs altered transcription levels in 5 of 31 enhancers assayed. Finally, we observed a DNV burden in RNA-binding-protein regulatory sites (OR = 1.13, 95% CI 1.1-1.2, P = 8.8 × 10-5). Our findings demonstrate an enrichment of potentially disruptive regulatory noncoding DNVs in a fraction of CHD at least as high as that observed for damaging coding DNVs.

Wearable digital devices offer potential advantages over traditional methods for the collection of health-related information, including continuous collection of dense data while study subjects are ambulatory or in remote settings. We assessed the utility of collecting continuous actigraphy and cardiac monitoring by deploying two US Food and Drug Administration (FDA) 510(k)-cleared devices in a phase I clinical trial of a novel compound, which included the use of an amphetamine challenge. The Phillips Actiwatch Spectrum Pro (Actiwatch) was used to assess mobility and sleep. The Preventice BodyGuardian (BodyGuardian) was used for monitoring heart rate (HR) and respiratory rate (RR), via single-lead electrocardiogram (ECG) recordings, together with physical activity. We measured data collection rates, compared device readouts with conventional measures, and monitored changes in HR measures during the amphetamine challenge. Completeness of data collection was good for the Actiwatch (96%) and lower for the BodyGuardian (80%). A good correlation was observed between device and in-clinic measures for HR (r = 0.99; P < 0.001), but was poor for RR (r = 0.39; P = 0.004). Manual reviews of selected ECG strips corresponding to HR measures below, within, and above the normal range were consistent with BodyGuardian measurements. The BodyGuardian device detected clear HR responses after amphetamine administration while subjects were physically active, whereas conventional measures collected at predefined timepoints while subjects were resting and supine did not. Wearable digital technology shows promise for monitoring human subjects for physiologic changes and pharmacologic responses, although fit-for-purpose evaluation and validation continues to be important prior to the wider deployment of these devices.

Rationale: NAA15 (N-alpha-acetyltransferase 15) is a component of the NatA (N-terminal acetyltransferase complex). The mechanism by which NAA15 haploinsufficiency causes congenital heart disease remains unknown. To better understand molecular processes by which NAA15 haploinsufficiency perturbs cardiac development, we introduced NAA15 variants into human induced pluripotent stem cells (iPSCs) and assessed the consequences of these mutations on RNA and protein expression. Objective: We aim to understand the role of NAA15 haploinsufficiency in cardiac development by investigating proteomic effects on NatA complex activity and identifying proteins dependent upon a full amount of NAA15. Methods and Results: We introduced heterozygous loss of function, compound heterozygous, and missense residues (R276W) in iPSCs using CRISPR/Cas9. Haploinsufficient NAA15 iPSCs differentiate into cardiomyocytes, unlike NAA15 -null iPSCs, presumably due to altered composition of NatA. Mass spectrometry analyses reveal ≈80% of identified iPSC NatA targeted proteins displayed partial or complete N-terminal acetylation. Between null and haploinsufficient NAA15 cells, N-terminal acetylation levels of 32 and 9 NatA-specific targeted proteins were reduced, respectively. Similar acetylation loss in few proteins occurred in NAA15 R276W induced pluripotent stem cells. In addition, steady-state protein levels of 562 proteins were altered in both null and haploinsufficient NAA15 cells; 18 were ribosomal-associated proteins. At least 4 proteins were encoded by genes known to cause autosomal dominant congenital heart disease. Conclusions: These studies define a set of human proteins that requires a full NAA15 complement for normal synthesis and development. A 50% reduction in the amount of NAA15 alters levels of at least 562 proteins and N-terminal acetylation of only 9 proteins. One or more modulated proteins are likely responsible for NAA15-haploinsufficiency mediated congenital heart disease. Additionally, genetically engineered induced pluripotent stem cells provide a platform for evaluating the consequences of amino acid sequence variants of unknown significance on NAA15 function.

Clinical safety findings remain one of the reasons for attrition of drug candidates during clinical development. Cardiovascular liabilities are not consistently detected in early-stage clinical trials and often become apparent when drugs are administered chronically for extended periods of time. Vital sign data collection outside of the clinic offers an opportunity for deeper physiological characterization of drug candidates and earlier safety signal detection. A working group representing expertise from biopharmaceutical and technology sectors, US Food and Drug Administration (FDA) public-private partnerships, academia, and regulators discussed and presented a remote cardiac monitoring case study at the FNIH Biomarkers Consortium Remote Digital Monitoring for Medical Product Development workshop to examine applicability of the biomarker qualification evidentiary framework by the FDA. This use case examined the components of the framework, including the statement of need, the context of use, the state of the evidence, and the benefit/risk profile. Examination of results from 2 clinical trials deploying 510(k)-cleared devices for remote cardiac data collection demonstrated the need for analytical and clinical validity irrespectively of the regulatory status of a device of interest, emphasizing the importance of data collection method assessment in the context of intended use. Additionally, collection of large amounts of ambulatory data also highlighted the need for new statistical methods and contextual information to enable data interpretation. A wider adoption of this approach for drug development purposes will require collaborations across industry, academia, and regulatory agencies to establish methodologies and supportive data sets to enable data interpretation and decision-making.

Supplemental Digital Content is available in the text., Background: De novo genic and copy number variants are enriched in patients with congenital heart disease, particularly those with extra-cardiac anomalies. The impact of de novo damaging variants on outcomes following cardiac repair is unknown. Methods: We studied 2517 patients with congenital heart disease who had undergone whole-exome sequencing as part of the CHD GENES study (Congenital Heart Disease Genetic Network). Results: Two hundred ninety-four patients (11.7%) had clinically significant de novo variants. Patients with de novo damaging variants were 2.4 times more likely to have extra-cardiac anomalies (P=5.63×10−12). In 1268 patients (50.4%) who had surgical data available and underwent open-heart surgery exclusive of heart transplantation as their first operation, we analyzed transplant-free survival following the first operation. Median follow-up was 2.65 years. De novo variants were associated with worse transplant-free survival (hazard ratio, 3.51; P=5.33×10−04) and longer times to final extubation (hazard ratio, 0.74; P=0.005). As de novo variants had a significant interaction with extra-cardiac anomalies for transplant-free survival (P=0.003), de novo variants conveyed no additional risk for transplant-free survival for patients with these anomalies (adjusted hazard ratio, 1.96; P=0.06). By contrast, de novo variants in patients without extra-cardiac anomalies were associated with worse transplant-free survival during follow-up (hazard ratio, 11.21; P=1.61×10−05) than that of patients with no de novo variants. Using agnostic machine-learning algorithms, we identified de novo copy number variants at 15q25.2 and 15q11.2 as being associated with worse transplant-free survival and 15q25.2, 22q11.21, and 3p25.2 as being associated with prolonged time to final extubation. Conclusions: In patients with congenital heart disease undergoing open-heart surgery, de novo variants were associated with worse transplant-free survival and longer times on the ventilator. De novo variants were most strongly associated with adverse outcomes among patients without extra-cardiac anomalies, suggesting a benefit for preoperative genetic testing even when genetic abnormalities are not suspected during routine clinical practice. Registration: URL: https://www.clinicaltrials.gov. Unique identifier: NCT01196182.

MotivationDe novo variant (DNV) calling typically relies on heuristic filters intrinsic to specific platforms and variant calling algorithms. FreeBayes and neural network approaches have overcome this limitation for variant calling, and we implemented a similar approach for DNV identification.ResultsWe developed a DNV calling framework that uses Genome Analysis Toolkit (GATK), FreeBayes and a neural network trained on Integrative Genomics Viewer pile-up plots (IGV-bot). We identified DNVs in 2,390 WGS trios and benchmarked results against heuristics based on GATK parameters. Results were validated in silico and with Sanger sequencing, with the latter showing true positive rates of 98.4% and 97.3% for SNVs and indels, respectively. Taken together we describe a scalable framework for DNV identification based on both FreeBayes and neural network methods.AvailabilitySource code and documentation are available at https://github.com/ShenLab/igv-classifier and https://github.com/frichter/dnv_pipeline under the MIT license.Contactys2411@cumc.columbia.edu

Mosaicism due to somatic mutations can cause multiple diseases including cancer, developmental and overgrowth syndromes, neurodevelopmental disorders, autoinflammatory diseases, and atrial fibrillation. With the increased use of next generation sequencing technology, multiple tools have been developed to identify low-frequency variants, specifically from matched tumor-normal tissues in cancer studies. To investigate whether mosaic variants are implicated in congenital heart disease (CHD), we developed a pipeline using the cancer somatic variant caller MuTect to identify mosaic variants in whole-exome sequencing (WES) data from a cohort of parent/affected child trios (n = 715) and a cohort of healthy individuals (n = 416). This is a novel application of the somatic variant caller designed for cancer to WES trio data. We identified two cases with mosaic KMT2D mutations that are likely pathogenic for CHD, but conclude that, overall, mosaicism detectable in peripheral blood or saliva does not account for a significant portion of CHD etiology.

Congenital heart disease (CHD) is the leading cause of mortality from birth defects. Here, exome sequencing of a single cohort of 2,871 CHD probands, including 2,645 parent-offspring trios, implicated rare inherited mutations in 1.8%, including a recessive founder mutation in GDF1 accounting for ∼5% of severe CHD in Ashkenazim, recessive genotypes in MYH6 accounting for ∼11% of Shone complex, and dominant FLT4 mutations accounting for 2.3% of Tetralogy of Fallot. De novo mutations (DNMs) accounted for 8% of cases, including ∼3% of isolated CHD patients and ∼28% with both neurodevelopmental and extra-cardiac congenital anomalies. Seven genes surpassed thresholds for genome-wide significance, and 12 genes not previously implicated in CHD had >70% probability of being disease related. DNMs in ∼440 genes were inferred to contribute to CHD. Striking overlap between genes with damaging DNMs in probands with CHD and autism was also found.

There are established associations between advanced paternal age and offspring risk for psychiatric and developmental disorders. These are commonly attributed to genetic mutations, especially de novo single nucleotide variants (dnSNVs), that accumulate with increasing paternal age. However, the actual magnitude of risk from such mutations in the male germline is unknown. Quantifying this risk would clarify the clinical significance of delayed paternity. Using parent-child trio whole-exome-sequencing data, we estimate the relationship between paternal-age-related dnSNVs and risk for five disorders: autism spectrum disorder (ASD), congenital heart disease, neurodevelopmental disorders with epilepsy, intellectual disability and schizophrenia (SCZ). Using Danish registry data, we investigate whether epidemiologic associations between each disorder and older fatherhood are consistent with the estimated role of dnSNVs. We find that paternal-age-related dnSNVs confer a small amount of risk for these disorders. For ASD and SCZ, epidemiologic associations with delayed paternity reflect factors that may not increase with age., Advanced paternal age associates with increased risk for psychiatric and developmental disorders in offspring. Here, Taylor et al. utilize parent-child trio exome sequencing data sets to estimate the contribution of paternal age-related de novo mutations to multiple disorders, including heart disease and schizophrenia.

Multiple tools have been developed to identify copy number variants (CNVs) from whole exome (WES) and whole genome sequencing (WGS) data. Current tools such as XHMM for WES and CNVnator for WGS identify CNVs based on changes in read depth. For WGS, other methods to identify CNVs include utilizing discordant read pairs and split reads and genome-wide local assembly with tools such as Lumpy and SvABA, respectively. Here, we introduce a new method to identify deletion CNVs from WES and WGS trio data based on the clustering of Mendelian errors (MEs). Using our Mendelian Error Method (MEM), we identified 127 deletions (inherited and de novo) in 2,601 WES trios from the Pediatric Cardiac Genomics Consortium, with a validation rate of 88% by digital droplet PCR. MEM identified additional de novo deletions compared to XHMM, and also identified sample switches, DNA contamination, a significant enrichment of 15q11.2 deletions compared to controls and eight cases of uniparental disomy. We applied MEM to WGS data from the Genome In A Bottle Ashkenazi trio and identified deletions with 97% specificity. MEM provides a robust, computationally inexpensive method for identifying deletions, and an orthogonal approach for verifying deletions called by other tools.

Congenital heart disease (CHD) patients have an increased prevalence of extracardiac congenital anomalies (CAs) and risk of neurodevelopmental disabilities (NDDs). Exome sequencing of 1213 CHD parent-offspring trios identified an excess of protein-damaging de novo mutations, especially in genes highly expressed in the developing heart and brain. These mutations accounted for 20% of patients with CHD, NDD, and CA but only 2% of patients with isolated CHD. Mutations altered genes involved in morphogenesis, chromatin modification, and transcriptional regulation, including multiple mutations in RBFOX2, a regulator of mRNA splicing. Genes mutated in other cohorts examined for NDD were enriched in CHD cases, particularly those with coexisting NDD. These findings reveal shared genetic contributions to CHD, NDD, and CA and provide opportunities for improved prognostic assessment and early therapeutic intervention in CHD patients.

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.

Activation of complex molecular programs in specific cell lineages governs mammalian heart development, from a primordial linear tube to a four-chamber organ. To characterize lineage-specific, spatiotemporal developmental programs, we performed single-cell RNA sequencing of >1,200 murine cells isolated at seven time points spanning embryonic day 9.5 (primordial heart tube) to postnatal day 21 (mature heart). Using unbiased transcriptional data, we classified cardiomyocytes, endothelial cells, and fibroblast-enriched cells, thus identifying markers for temporal and chamber-specific developmental programs. By harnessing these datasets, we defined developmental ages of human and mouse pluripotent stem-cell-derived cardiomyocytes and characterized lineage-specific maturation defects in hearts of mice with heterozygous mutations in Nkx2.5 that cause human heart malformations. This spatiotemporal transcriptome analysis of heart development reveals lineage-specific gene programs underlying normal cardiac development and congenital heart disease.

Spontaneously arising (de novo) genetic variants are important in human disease, yet every individual carries many such variants, with a median of 1 de novo variant affecting the protein-coding portion of the genome. A recently described mutational model (Samocha et al., 2014) provides a powerful framework for the robust statistical evaluation of such coding variants, enabling the interpretation of de novo variation in human disease. Here we describe a new open-source software package, denovolyzeR, that implements this model and provides tools for the analysis of de novo coding sequence variants.

Human mutations that truncate the massive sarcomere protein titin [TTN-truncating variants (TTNtvs)] are the most common genetic cause for dilated cardiomyopathy (DCM), a major cause of heart failure and premature death. Here we show that cardiac microtissues engineered from human induced pluripotent stem (iPS) cells are a powerful system for evaluating the pathogenicity of titin gene variants. We found that certain missense mutations, like TTNtvs, diminish contractile performance and are pathogenic. By combining functional analyses with RNA sequencing, we explain why truncations in the A-band domain of TTN cause DCM, whereas truncations in the I band are better tolerated. Finally, we demonstrate that mutant titin protein in iPS cell-derived cardiomyocytes results in sarcomere insufficiency, impaired responses to mechanical and β-adrenergic stress, and attenuated growth factor and cell signaling activation. Our findings indicate that titin mutations cause DCM by disrupting critical linkages between sarcomerogenesis and adaptive remodeling.

A giant disruption of the heart Certain forms of heart failure originate from genetic mutations. Understanding how the culprit mutant proteins alter normal heart function could lead to more effective treatments. One candidate is the giant protein tintin, which is mutated in a subset of patients with dilated cardiomyopathy. Through a combination of patient-derived stem cells, tissue engineering, and gene editing, Hinson et al. found that disease-associated titin mutations disrupt the function of the contractile unit in heart muscle. As a result, the heart does not respond properly to mechanical and other forms of stress. Science , this issue p. 982

Alternative splicing (AS) of protein isoforms is an integral mechanism for cardiac development. RNA Binding Protein, Fox-1 Homolog (C. Elegans) 2 (RBFOX2) is an RNA binding protein preferentially expressed in muscle and neuronal cells and regulates tissue-specific alternate exon splicing in ~2,100 target genes by binding the conserved RNA sequence motif (U)GCAUG. RBFOX2 was recently implicated in the pathogenesis of abnormal cardiac and cerebral development via loss-of-function studies in zebrafish and mouse. However, convincing evidence remains incomplete, as the full complement of RBFOX2 target genes and differential exon usage (DEU) in human cardiovascular cell lines are incompletely defined. We identified de novo mutations in RBFOX2 from four human cases of congenital heart disease (CHD) with hypoplastic left heart syndrome (HLHS) via whole exome sequencing. To test the hypothesis that RBFOX2 mutations alter DEU in known target genes, we performed RNA-seq on ductus arteriosus tissue from human CHD cases with and without RBFOX2 mutation. Analysis of RNA-seq for DEU was performed with DEXSeq. To limit the effect of differential gene expression, we restricted analysis to subjects with high global gene expression correlation (r2 > 0.9, case=1 vs. control=5). DEU in known RBFOX2 target genes were highly enriched compared to all known genes (115/2,100 vs. 589/26,310, p=5.78e-15). A high percentage of the DEU genes (60.0%, 69/115) have high heart expression (HHE) in the developing mouse (mean expression of four cardiac chambers at e14.5). DEU genes with HHE include VCL, TPM1, FN1, ACTN1, and CALD1. Functional annotation clustering reveals enrichment for several actin, cytoskeletal, and contractile Gene Ontology terms, suggesting a possible role in the epithelial-mesenchymal transition (EMT) developmental processes active during early cardiac formation. We also identified enrichment from genes implicated in CHD by allelic specific expression or de novo mutations (44/1,263 vs. 589/26,310, p=0.007). These results are the first in humans to identify differentially expressed exons associated with RBFOX2 mutations in CHD and suggests RBFOX2-mediated alternate splicing may influence EMT pathways implicated in the pathogenesis of HLHS.

CRISPR/Cas9 has demonstrated a high-efficiency in site-specific gene targeting. However, potential off-target effects of the Cas9 nuclease represent a major safety concern for any therapeutic application. Here, we knock out the Tafazzin gene by CRISPR/Cas9 in human-induced pluripotent stem cells with 54% efficiency. We combine whole-genome sequencing and deep-targeted sequencing to characterise the off-target effects of Cas9 editing. Whole-genome sequencing of Cas9-modified hiPSC clones detects neither gross genomic alterations nor elevated mutation rates. Deep sequencing of in silico predicted off-target sites in a population of Cas9-treated cells further confirms high specificity of Cas9. However, we identify a single high-efficiency off-target site that is generated by a common germline single-nucleotide variant (SNV) in our experiment. Based on in silico analysis, we estimate a likelihood of SNVs creating off-target sites in a human genome to be ~1.5–8.5%, depending on the genome and site-selection method, but also note that mutations might be generated at these sites only at low rates and may not have functional consequences. Our study demonstrates the feasibility of highly specific clonal ex vivo gene editing using CRISPR/Cas9 and highlights the value of whole-genome sequencing before personalised CRISPR design., The microbial RNA-guided CRISPR/Cas9 system has robust genome-editing activities, but the off-target effects of the Cas9 nuclease have only recently begun to be analysed. Here the authors provide evidence for high specificity of the Cas9 nuclease on targeting of the Tafazzin gene in human-induced pluripotent stem cells and demonstrate the impact of single-nucleotide variations of the human genome on Cas9 specificity.

We present CANOES, an algorithm for the detection of rare copy number variants from exome sequencing data. CANOES models read counts using a negative binomial distribution and estimates variance of the read counts using a regression-based approach based on selected reference samples in a given dataset. We test CANOES on a family-based exome sequencing dataset, and show that its sensitivity and specificity is comparable to that of XHMM. Moreover, the method is complementary to Gaussian approximation-based methods (e.g. XHMM or CoNIFER). When CANOES is used in combination with these methods, it will be possible to produce high accuracy calls, as demonstrated by a much reduced and more realistic de novo rate in results from trio data.