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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.

The TGFβ secreted factor NODAL is a major left determinant required for the asymmetric morphogenesis of visceral organs, including the heart. Yet, when this signaling is absent, shape asymmetry, for example of the embryonic heart loop, is not fully abrogated, indicating that there are other factors regulating left–right patterning. Here, we used a tailored transcriptomic approach to screen for genes asymmetrically expressed in the field of heart progenitors. We thus identify Notch3 as a novel left-enriched gene and validate, by quantitative in situ hybridization, its transient asymmetry in the lateral plate mesoderm and node crown, overlapping with Nodal . In mutant embryos, we analyzed the regulatory hierarchy and demonstrate that Nodal in the lateral plate mesoderm amplifies Notch3 asymmetric expression. The function of Notch3 was uncovered in an allelic series of mutants. In single neonate mutants, we observe that Notch3 is required with partial penetrance for ventricle thickness, septation and aortic valve, in addition to its known role in coronary arteries. In compound mutants, we reveal that Notch3 acts as a genetic modifier of heart looping direction and shape defects in Nodal mutants. Whereas Notch3 was previously mainly associated with the CADASIL syndrome, our observations in the mouse and a human cohort support a novel role in congenital heart defects and laterality defects.

Heterozygous pathogenic variants in ADAR have been associated with dyschromatosis symmetrica hereditaria, while biallelic pathogenic variants have been associated with Aicardi-Goutières syndrome 6 (AGS6). However, the heterozygous variant c.3019G>A, (p.Gly1007Arg) has been described to cause neurological manifestations, which resemble AGS6 and are associated with an upregulation of interferon-stimulated genes. We report a four-generation family with two symptomatic family members and five unaffected carriers of the heterozygous pathogenic ADAR variant c.3019G>A. The index (patient 1) manifested a gait disorder at three years of age (weakness in his legs, a tendency to fall and hyperreflexia), dyslalia, and mild cognitive developmental delay. A paternal half-brother (patient 4) to patient´s father (patient 2) presented with irritability and regression of previous skills at the age of 6 months after a fever reaction, following the second routine hexavalent vaccination at the age of 4 months. At 20 years of age, the patient was wheelchair-bound, had spasticity and severe global development delay. A blood test in both patients showed increased interferon signature with activation of type 1-interferon. Five asymptomatic carriers were identified in this family (age range 2–81 years of age) nearly all of them (except the 81-year old patient) showed a strong activation of type 1 interferon response in peripheral blood. Affected individuals had higher interferon signature than asymptomatic, underlining the possible role of interferon activation in disease mechanism. To our knowledge, this is the biggest family reported to date, encompassing a wide age-range of carriers, including an asymptotic carrier of advanced age (81 years of age).

Background Congenital heart disease (CHD) is the most common congenital anomaly. Almost 90% of isolated cases have an unexplained genetic etiology after clinical testing. Non-canonical splice variants that disrupt mRNA splicing through the loss or creation of exon boundaries are not routinely captured and/or evaluated by standard clinical genetic tests. Recent computational algorithms such as SpliceAI have shown an ability to predict such variants, but are not specific to cardiac-expressed genes and transcriptional isoforms. Methods We used genome sequencing (GS) ( n  = 1101 CHD probands) and myocardial RNA-Sequencing (RNA-Seq) ( n  = 154 CHD and n  = 43 cardiomyopathy probands) to identify and validate splice disrupting variants, and to develop a heart-specific model for canonical and non-canonical splice variants that can be applied to patients with CHD and cardiomyopathy. Two thousand five hundred seventy GS samples from the Medical Genome Reference Bank were analyzed as healthy controls. Results Of 8583 rare DNA splice-disrupting variants initially identified using SpliceAI, 100 were associated with altered splice junctions in the corresponding patient myocardium affecting 95 genes. Using strength of myocardial gene expression and genome-wide DNA variant features that were confirmed to affect splicing in myocardial RNA, we trained a machine learning model for predicting cardiac-specific splice-disrupting variants (AUC 0.86 on internal validation). In a validation set of 48 CHD probands, the cardiac-specific model outperformed a SpliceAI model alone (AUC 0.94 vs 0.67 respectively). Application of this model to an additional 947 CHD probands with only GS data identified 1% patients with canonical and 11% patients with non-canonical splice-disrupting variants in CHD genes. Forty-nine percent of predicted splice-disrupting variants were intronic and > 10 bp from existing splice junctions. The burden of high-confidence splice-disrupting variants in CHD genes was 1.28-fold higher in CHD cases compared with healthy controls. Conclusions A new cardiac-specific in silico model was developed using complementary GS and RNA-Seq data that improved genetic yield by identifying a significant burden of non-canonical splice variants associated with CHD that would not be detectable through panel or exome sequencing.

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.

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.

Matthew Hurles and colleagues report exome sequencing of 1,891 individuals with syndromic or nonsyndromic congenital heart defects (CHD). They found that nonsyndromic CHD patients were enriched for protein-truncating variants in CHD-associated genes inherited from unaffected parents and identified three new syndromic CHD disorders caused by de novo mutations. 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%) 3 , suggesting a considerable role for de novo mutations (DNMs) and/or incomplete penetrance 4 , 5 . De novo protein-truncating variants (PTVs) have been shown to be enriched among the 10% of 'syndromic' patients with extra-cardiac manifestations 6 , 7 . 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 8 . 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.

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.

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.

Valvular heart disease is observed in approximately 2% of the general population 1 . 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 disease 2 – 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. Mutations in ADAMTS19 lead to progressive heart valve disease in humans. Analysis of mice lacking Adamts19 highlights the role of a Wnt–Adamts19–Klf2 axis in proper valve function.