Effect of deletion of the protein kinase PRKD1 on development of the mouse embryonic heart.

Congenital heart disease (CHD) is the most common congenital anomaly, with an overall incidence of approximately 1% in the United Kingdom. Exome sequencing in large CHD cohorts has been performed to provide insights into the genetic aetiology of CHD. This includes a study of 1891 probands by our group in collaboration with others, which identified three novel genes-CDK13, PRKD1, and CHD4, in patients with syndromic CHD. PRKD1 encodes a serine/threonine protein kinase, which is important in a variety of fundamental cellular functions. Individuals with a heterozygous mutation in PRKD1 may have facial dysmorphism, ectodermal dysplasia and may have CHDs such as pulmonary stenosis, atrioventricular septal defects, coarctation of the aorta and bicuspid aortic valve. To obtain a greater appreciation for the role that this essential protein kinase plays in cardiogenesis and CHD, we have analysed a Prkd1 transgenic mouse model (Prkd1em1 ) carrying deletion of exon 2, causing loss of function. High-resolution episcopic microscopy affords detailed morphological 3D analysis of the developing heart and provides evidence for an essential role of Prkd1 in both normal cardiac development and CHD. We show that homozygous deletion of Prkd1 is associated with complex forms of CHD such as atrioventricular septal defects, and bicuspid aortic and pulmonary valves, and is lethal. Even in heterozygotes, cardiac differences occur. However, given that 97% of Prkd1 heterozygous mice display normal heart development, it is likely that one normal allele is sufficient, with the defects seen most likely to represent sporadic events. Moreover, mRNA and protein expression levels were investigated by RT-qPCR and western immunoblotting, respectively. A significant reduction in Prkd1 mRNA levels was seen in homozygotes, but not heterozygotes, compared to WT littermates. While a trend towards lower PRKD1 protein expression was seen in the heterozygotes, the difference was only significant in the homozygotes. There was no compensation by the related Prkd2 and Prkd3 at transcript level, as evidenced by RT-qPCR. Overall, we demonstrate a vital role of Prkd1 in heart development and the aetiology of CHD.

STIGMA: Single-cell tissue-specific gene prioritization using machine learning.

Clinical exome and genome sequencing have revolutionized the understanding of human disease genetics. Yet many genes remain functionally uncharacterized, complicating the establishment of causal disease links for genetic variants. While several scoring methods have been devised to prioritize these candidate genes, these methods fall short of capturing the expression heterogeneity across cell subpopulations within tissues. Here, we introduce single-cell tissue-specific gene prioritization using machine learning (STIGMA), an approach that leverages single-cell RNA-seq (scRNA-seq) data to prioritize candidate genes associated with rare congenital diseases. STIGMA prioritizes genes by learning the temporal dynamics of gene expression across cell types during healthy organogenesis. To assess the efficacy of our framework, we applied STIGMA to mouse limb and human fetal heart scRNA-seq datasets. In a cohort of individuals with congenital limb malformation, STIGMA prioritized 469 variants in 345 genes, with UBA2 as a notable example. For congenital heart defects, we detected 34 genes harboring nonsynonymous de novo variants (nsDNVs) in two or more individuals from a set of 7,958 individuals, including the ortholog of Prdm1, which is associated with hypoplastic left ventricle and hypoplastic aortic arch. Overall, our findings demonstrate that STIGMA effectively prioritizes tissue-specific candidate genes by utilizing single-cell transcriptome data. The ability to capture the heterogeneity of gene expression across cell populations makes STIGMA a powerful tool for the discovery of disease-associated genes and facilitates the identification of causal variants underlying human genetic disorders.

Genetic Screening Reveals Heterogeneous Clinical Phenotypes in Patients with Dilated Cardiomyopathy and Troponin T2 Variants.

BACKGROUND: Cardiomyopathies (CMs) are a heterogeneous and severe group of diseases that shows a highly variable cardiac phenotype and an incidence of app. 1/100.000. Genetic screening of family members is not yet performed routinely. PATIENTS AND METHODS: Three families with dilated cardiomyopathy (DCM) and pathogenic variants in the troponin T2, Cardiac Type (TNNT2) gene were included. Pedigrees and clinical data of the patients were collected. The reported variants in the TNNT2 gene showed a high penetrance and a poor outcome, with 8 of 16 patients dying or receiving heart transplantation. The age of onset varied from the neonatal period to the age of 52. Acute heart failure and severe decompensation developed within a short period in some patients. CONCLUSION: Family screening of patients with DCM improves risk assessment, especially for individuals who are currently asymptomatic. Screening contributes to improved treatment by enabling practitioners to set appropriate control intervals and quickly begin interventional measures, such as heart failure medication or, in selected cases, pulmonary artery banding.

Aberrant phase separation and nucleolar dysfunction in rare genetic diseases.

Thousands of genetic variants in protein-coding genes have been linked to disease. However, the functional impact of most variants is unknown as they occur within intrinsically disordered protein regions that have poorly defined functions1-3. Intrinsically disordered regions can mediate phase separation and the formation of biomolecular condensates, such as the nucleolus4,5. This suggests that mutations in disordered proteins may alter condensate properties and function6-8. Here we show that a subset of disease-associated variants in disordered regions alter phase separation, cause mispartitioning into the nucleolus and disrupt nucleolar function. We discover de novo frameshift variants in HMGB1 that cause brachyphalangy, polydactyly and tibial aplasia syndrome, a rare complex malformation syndrome. The frameshifts replace the intrinsically disordered acidic tail of HMGB1 with an arginine-rich basic tail. The mutant tail alters HMGB1 phase separation, enhances its partitioning into the nucleolus and causes nucleolar dysfunction. We built a catalogue of more than 200,000 variants in disordered carboxy-terminal tails and identified more than 600 frameshifts that create arginine-rich basic tails in transcription factors and other proteins. For 12 out of the 13 disease-associated variants tested, the mutation enhanced partitioning into the nucleolus, and several variants altered rRNA biogenesis. These data identify the cause of a rare complex syndrome and suggest that a large number of genetic variants may dysregulate nucleoli and other biomolecular condensates in humans.

Exome sequencing in individuals with cardiovascular laterality defects identifies potential candidate genes.

The birth prevalence of laterality defects is about 1.1/10,000 comprising different phenotypes ranging from situs inversus totalis to heterotaxy, mostly associated with complex congenital heart defects (CHD) and situs abnormalities such as intestinal malrotation, biliary atresia, asplenia, or polysplenia. A proportion of laterality defects arise in the context of primary ciliary dyskinesia (PCD) accompanied by respiratory symptoms or infertility. In this study, exome sequencing (ES) was performed in 14 case-parent trios/quattros with clinical exclusion of PCD prior to analysis. Moreover, all cases and parents underwent detailed clinical phenotyping including physical examination, echocardiography by a skilled paediatric cardiologist and abdominal ultrasound examinations not to miss mildly affected individuals. Subsequent survey of the exome data comprised filtering for monoallelic de novo, rare biallelic, and X-linked recessive variants. In two families, rare variants of uncertain significance (VUS) in PKD1L1 and ZIC3 were identified. Both genes have been associated with laterality defects. In two of the remaining families, biallelic variants in LMBRD1 and DNAH17, respectively, were prioritized. In another family, an ultra-rare de novo variant in WDR47 was found. Extensive exome survey of 2,109 single exomes of individuals with situs inversus totalis, heterotaxy, or isolated CHD identified two individuals with novel monoallelic variants in WDR47, but no further individuals with biallelic variants in DNAH17 or LMBRD1. Overall, ES of 14 case-parent trios/quattros with cardiovascular laterality defects identified rare VUS in two families in known disease-associated genes PKD1L1 and ZIC3 and suggests DNAH17, LMBRD1, and WDR47 as potential genes involved in laterality defects.

Common Genetic Variants Contribute to Risk of Transposition of the Great Arteries.

RATIONALE: Dextro-transposition of the great arteries (D-TGA) is a severe congenital heart defect which affects approximately 1 in 4,000 live births. While there are several reports of D-TGA patients with rare variants in individual genes, the majority of D-TGA cases remain genetically elusive. Familial recurrence patterns and the observation that most cases with D-TGA are sporadic suggest a polygenic inheritance for the disorder, yet this remains unexplored. OBJECTIVE: We sought to study the role of common single nucleotide polymorphisms (SNPs) in risk for D-TGA. METHODS AND RESULTS: We conducted a genome-wide association study in an international set of 1,237 patients with D-TGA and identified a genome-wide significant susceptibility locus on chromosome 3p14.3, which was subsequently replicated in an independent case-control set (rs56219800, meta-analysis P=8.6x10-10, OR=0.69 per C allele). SNP-based heritability analysis showed that 25% of variance in susceptibility to D-TGA may be explained by common variants. A genome-wide polygenic risk score derived from the discovery set was significantly associated to D-TGA in the replication set (P=4x10-5). The genome-wide significant locus (3p14.3) co-localizes with a putative regulatory element that interacts with the promoter of WNT5A, which encodes the Wnt Family Member 5A protein known for its role in cardiac development in mice. We show that this element drives reporter gene activity in the developing heart of mice and zebrafish and is bound by the developmental transcription factor TBX20. We further demonstrate that TBX20 attenuates Wnt5a expression levels in the developing mouse heart. CONCLUSIONS: This work provides support for a polygenic architecture in D-TGA and identifies a susceptibility locus on chromosome 3p14.3 near WNT5A. Genomic and functional data support a causal role of WNT5A at the locus.

Correction: Integrative analysis of genomic variants reveals new associations of candidate haploinsufficient genes with congenital heart disease.

[This corrects the article DOI: 10.1371/journal.pgen.1009679.].

Integrative analysis of genomic variants reveals new associations of candidate haploinsufficient genes with congenital heart disease.

Numerous genetic studies have established a role for rare genomic variants in Congenital Heart Disease (CHD) at the copy number variation (CNV) and de novo variant (DNV) level. To identify novel haploinsufficient CHD disease genes, we performed an integrative analysis of CNVs and DNVs identified in probands with CHD including cases with sporadic thoracic aortic aneurysm. We assembled CNV data from 7,958 cases and 14,082 controls and performed a gene-wise analysis of the burden of rare genomic deletions in cases versus controls. In addition, we performed variation rate testing for DNVs identified in 2,489 parent-offspring trios. Our analysis revealed 21 genes which were significantly affected by rare CNVs and/or DNVs in probands. Fourteen of these genes have previously been associated with CHD while the remaining genes (FEZ1, MYO16, ARID1B, NALCN, WAC, KDM5B and WHSC1) have only been associated in small cases series or show new associations with CHD. In addition, a systems level analysis revealed affected protein-protein interaction networks involved in Notch signaling pathway, heart morphogenesis, DNA repair and cilia/centrosome function. Taken together, this approach highlights the importance of re-analyzing existing datasets to strengthen disease association and identify novel disease genes and pathways.

Systems genetics analysis identifies calcium-signaling defects as novel cause of congenital heart disease.

BACKGROUND: Congenital heart disease (CHD) occurs in almost 1% of newborn children and is considered a multifactorial disorder. CHD may segregate in families due to significant contribution of genetic factors in the disease etiology. The aim of the study was to identify pathophysiological mechanisms in families segregating CHD. METHODS: We used whole exome sequencing to identify rare genetic variants in ninety consenting participants from 32 Danish families with recurrent CHD. We applied a systems biology approach to identify developmental mechanisms influenced by accumulation of rare variants. We used an independent cohort of 714 CHD cases and 4922 controls for replication and performed functional investigations using zebrafish as in vivo model. RESULTS: We identified 1785 genes, in which rare alleles were shared between affected individuals within a family. These genes were enriched for known cardiac developmental genes, and 218 of these genes were mutated in more than one family. Our analysis revealed a functional cluster, enriched for proteins with a known participation in calcium signaling. Replication in an independent cohort confirmed increased mutation burden of calcium-signaling genes in CHD patients. Functional investigation of zebrafish orthologues of ITPR1, PLCB2, and ADCY2 verified a role in cardiac development and suggests a combinatorial effect of inactivation of these genes. CONCLUSIONS: The study identifies abnormal calcium signaling as a novel pathophysiological mechanism in human CHD and confirms the complex genetic architecture underlying CHD.

The omics discovery REST interface.

The Omics Discovery Index is an open source platform that can be used to access, discover and disseminate omics datasets. OmicsDI integrates proteomics, genomics, metabolomics, models and transcriptomics datasets. Using an efficient indexing system, OmicsDI integrates different biological entities including genes, transcripts, proteins, metabolites and the corresponding publications from PubMed. In addition, it implements a group of pipelines to estimate the impact of each dataset by tracing the number of citations, reanalysis and biological entities reported by each dataset. Here, we present the OmicsDI REST interface (www.omicsdi.org/ws/) to enable programmatic access to any dataset in OmicsDI or all the datasets for a specific provider (database). Clients can perform queries on the API using different metadata information such as sample details (species, tissues, etc), instrumentation (mass spectrometer, sequencer), keywords and other provided annotations. In addition, we present two different libraries in R and Python to facilitate the development of tools that can programmatically interact with the OmicsDI REST interface.

Loss of ADAMTS19 causes progressive non-syndromic heart valve disease.

Valvular heart disease is observed in approximately 2% of the general population1. Although the initial observation is often localized (for example, to the aortic or mitral valve), disease manifestations are regularly observed in the other valves and patients frequently require surgery. Despite the high frequency of heart valve disease, only a handful of genes have so far been identified as the monogenic causes of disease2-7. Here we identify two consanguineous families, each with two affected family members presenting with progressive heart valve disease early in life. Whole-exome sequencing revealed homozygous, truncating nonsense alleles in ADAMTS19 in all four affected individuals. Homozygous knockout mice for Adamts19 show aortic valve dysfunction, recapitulating aspects of the human phenotype. Expression analysis using a lacZ reporter and single-cell RNA sequencing highlight Adamts19 as a novel marker for valvular interstitial cells; inference of gene regulatory networks in valvular interstitial cells positions Adamts19 in a highly discriminatory network driven by the transcription factor lymphoid enhancer-binding factor 1 downstream of the Wnt signaling pathway. Upregulation of endocardial Krüppel-like factor 2 in Adamts19 knockout mice precedes hemodynamic perturbation, showing that a tight balance in the Wnt-Adamts19-Klf2 axis is required for proper valve maturation and maintenance.

Enabling Global Clinical Collaborations on Identifiable Patient Data: The Minerva Initiative.

The clinical utility of computational phenotyping for both genetic and rare diseases is increasingly appreciated; however, its true potential is yet to be fully realized. Alongside the growing clinical and research availability of sequencing technologies, precise deep and scalable phenotyping is required to serve unmet need in genetic and rare diseases. To improve the lives of individuals affected with rare diseases through deep phenotyping, global big data interrogation is necessary to aid our understanding of disease biology, assist diagnosis, and develop targeted treatment strategies. This includes the application of cutting-edge machine learning methods to image data. As with most digital tools employed in health care, there are ethical and data governance challenges associated with using identifiable personal image data. There are also risks with failing to deliver on the patient benefits of these new technologies, the biggest of which is posed by data siloing. The Minerva Initiative has been designed to enable the public good of deep phenotyping while mitigating these ethical risks. Its open structure, enabling collaboration and data sharing between individuals, clinicians, researchers and private enterprise, is key for delivering precision public health.

DNA methylation profiling allows for characterization of atrial and ventricular cardiac tissues and hiPSC-CMs.

BACKGROUND: Cardiac disease modelling using human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM) requires thorough insight into cardiac cell type differentiation processes. However, current methods to discriminate different cardiac cell types are mostly time-consuming, are costly and often provide imprecise phenotypic evaluation. DNA methylation plays a critical role during early heart development and cardiac cellular specification. We therefore investigated the DNA methylation pattern in different cardiac tissues to identify CpG loci for further cardiac cell type characterization. RESULTS: An array-based genome-wide DNA methylation analysis using Illumina Infinium HumanMethylation450 BeadChips led to the identification of 168 differentially methylated CpG loci in atrial and ventricular human heart tissue samples (n = 49) from different patients with congenital heart defects (CHD). Systematic evaluation of atrial-ventricular DNA methylation pattern in cardiac tissues in an independent sample cohort of non-failing donor hearts and cardiac patients using bisulfite pyrosequencing helped us to define a subset of 16 differentially methylated CpG loci enabling precise characterization of human atrial and ventricular cardiac tissue samples. This defined set of reproducible cardiac tissue-specific DNA methylation sites allowed us to consistently detect the cellular identity of hiPSC-CM subtypes. CONCLUSION: Testing DNA methylation of only a small set of defined CpG sites thus makes it possible to distinguish atrial and ventricular cardiac tissues and cardiac atrial and ventricular subtypes of hiPSC-CMs. This method represents a rapid and reliable system for phenotypic characterization of in vitro-generated cardiomyocytes and opens new opportunities for cardiovascular research and patient-specific therapy.

Patients with congenital heart defect and their families support genetic heart research.

BACKGROUND: Congenital heart disease (CHD) affects up to 1% of live births the etiology remains relatively poorly understood. Thus, cardiac research is needed to understand the underlying pathomechanisms of the disease. About 51 000 CHD patients are registered in the German National Register for Congenital Heart Defects (NRCHD). Patients and relatives were interviewed online about their willingness to support genetic heart research in order to donate a biological sample. METHODS: Study participants were recruited via the database of the NRCHD. Seven thousand nine hundred eighty-nine patients were invited to participate in the study. Participants have been asked to rate three questions on a ten-staged Likert scale about their willingness to provide a saliva/blood sample and their motivation to ask family members to support genetic heart research. RESULTS: Overall, 2035 participants (patients/relatives) responded the online survey (25.5%). Two-thirds of the participants are willing to donate a saliva sample. Whereas the motivation to provide a blood sample is slightly lower (patients: 63.8%, relatives: 60.6%). Female relatives are more fain to provide a saliva sample as well as a blood sample compared to men (saliva sample: P < .001, blood sample: P < .01). The motivation to ask an additional family member for a biological sample was significantly higher in relatives (59.2%) compared to patients (48.4%). CONCLUSIONS: The motivation to provide biological samples is high reflecting the need for genetic research to unravel the pathomechanism of CHD. A future aim should be to offer an individual risk assessment for each patient based on the underlying genetics.

Accurate and fast feature selection workflow for high-dimensional omics data.

We are moving into the age of 'Big Data' in biomedical research and bioinformatics. This trend could be encapsulated in this simple formula: D = S * F, where the volume of data generated (D) increases in both dimensions: the number of samples (S) and the number of sample features (F). Frequently, a typical omics classification includes redundant and irrelevant features (e.g. genes or proteins) that can result in long computation times; decrease of the model performance and the selection of suboptimal features (genes and proteins) after the classification/regression step. Multiple algorithms and reviews has been published to describe all the existing methods for feature selection, their strengths and weakness. However, the selection of the correct FS algorithm and strategy constitutes an enormous challenge. Despite the number and diversity of algorithms available, the proper choice of an approach for facing a specific problem often falls in a 'grey zone'. In this study, we select a subset of FS methods to develop an efficient workflow and an R package for bioinformatics machine learning problems. We cover relevant issues concerning FS, ranging from domain's problems to algorithm solutions and computational tools. Finally, we use seven different proteomics and gene expression datasets to evaluate the workflow and guide the FS process.

Recent advances in congenital heart disease genomics.

Congenital heart disease is the most common congenital abnormality, and advances in medical care mean that this population of individuals is surviving for longer than ever before. It represents a significant healthcare challenge, as many patients require life-long care and individuals may ask about the likelihood of their children being affected. Whilst a number of genes have been identified previously from investigation of families with Mendelian inheritance patterns, sequencing the DNA from large cohorts of individuals with congenital heart disease is now providing fresh insights into the genetics of these conditions. This research has enabled novel gene discovery and uncovered the different genetic mechanisms underlying both isolated congenital heart disease and that which occurs in association with other medical problems. This article discusses the most recent advances in this field and the implications for patient care. In addition, we consider the challenges facing researchers in this field and emphasise the need for close working relationships between clinicians and researchers.

The analysis of heterotaxy patients reveals new loss-of-function variants of GRK5.

G protein-coupled receptor kinase 5 (GRK5) is a regulator of cardiac performance and a potential therapeutic target in heart failure in the adult. Additionally, we have previously classified GRK5 as a determinant of left-right asymmetry and proper heart development using zebrafish. We thus aimed to identify GRK5 variants of functional significance by analysing 187 individuals with laterality defects (heterotaxy) that were associated with a congenital heart defect (CHD). Using Sanger sequencing we identified two moderately frequent variants in GRK5 with minor allele frequencies <10%, and seven very rare polymorphisms with minor allele frequencies <1%, two of which are novel variants. Given their evolutionarily conserved position in zebrafish, in-depth functional characterisation of four variants (p.Q41L, p.G298S, p.R304C and p.T425M) was performed. We tested the effects of these variants on normal subcellular localisation and the ability to desensitise receptor signalling as well as their ability to correct the left-right asymmetry defect upon Grk5l knockdown in zebrafish. While p.Q41L, p.R304C and p.T425M responded normally in the first two aspects, neither p.Q41L nor p.R304C were capable of rescuing the lateralisation phenotype. The fourth variant, p.G298S was identified as a complete loss-of-function variant in all assays and provides insight into the functions of GRK5.

Distinct genetic architectures for syndromic and nonsyndromic congenital heart defects identified by exome sequencing.

Congenital heart defects (CHDs) have a neonatal incidence of 0.8-1% (refs. 1,2). Despite abundant examples of monogenic CHD in humans and mice, CHD has a low absolute sibling recurrence risk (∼2.7%), suggesting a considerable role for de novo mutations (DNMs) and/or incomplete penetrance. De novo protein-truncating variants (PTVs) have been shown to be enriched among the 10% of 'syndromic' patients with extra-cardiac manifestations. We exome sequenced 1,891 probands, including both syndromic CHD (S-CHD, n = 610) and nonsyndromic CHD (NS-CHD, n = 1,281). In S-CHD, we confirmed a significant enrichment of de novo PTVs but not inherited PTVs in known CHD-associated genes, consistent with recent findings. Conversely, in NS-CHD we observed significant enrichment of PTVs inherited from unaffected parents in CHD-associated genes. We identified three genome-wide significant S-CHD disorders caused by DNMs in CHD4, CDK13 and PRKD1. Our study finds evidence for distinct genetic architectures underlying the low sibling recurrence risk in S-CHD and NS-CHD.