Loss of Function Mutations in NNT Are Associated With Left Ventricular Noncompaction.

Hypertrophic cardiomyopathy (HCM) may be associated with very narrow QRS, while left ventricular hypertrophy (LVH) may increase QRS duration. We investigated the relationships between QRS duration and LV mass (LVM) in subtypes of abnormal LV wall thickness. Automated measurement of LVM on MRI was correlated to automated measurement of QRS duration on ECG in HCM, left ventricular non compaction (LVNC), left ventricular hypertrophy (LVH), and controls with healthy hearts. Uni and multivariate analyses were performed between groups including explanatory variables expected to influence LVM and QRS duration. The relationships between QRS duration and LVM were further studied within each group. Two hundred and twenty-one HCM, 28 LVNC, 16 LVH, and 40 controls were retrospectively included. Mean QRS duration was 92 ms for HCM, 104 for LVNC, 110 for LVH, and 92 for controls (P < 0.01). Mean LVM was 100, 90, 108, and 68 g/m2 (P < 0.01). QRS duration, LVM, hypertension, maximal wall thickness, and late gadolinium enhancement were significantly linked to HCM in multivariate analysis (w/wo bundle branch block). An independent negative correlation was found between LVM and QRS duration in the HCM group, while the relationship was reverse in LVNC, LVH, and controls. QRS duration increases with LVM in LVNC, LVH, or in healthy hearts, while reverse relationship is present in HCM. These relationships were independent from other parameters. These results warrant additional investigations for refining diagnosis criteria for HCM in the future.

Aim. To study the association of genetic variants in the titin gene ( TTN ) with the development and clinical course of left ventricular noncompaction in different age groups. Material and methods. The article discusses three clinical cases of patients with left ventricular noncompaction who were treated at theAlmazovNationalMedicalResearchCenter. We performed a new-generation sequencing of 108 genes associated with cardiomyopathies, as well as whole exome sequencing and Sanger sequencing. Results. We identified genetic variants in the TTN gene leading to the synthesis of truncated protein: in the first two cases, the cause of noncompaction was a thirteen nucleotide deletion with a reading frame shift, in the second, a nonsense mutation. An algorithm for assessing the pathogenicity of the identified variants and a scheme of diagnostic genetic search are presented. Conclusion. Causal role of TTN -truncating variants in development of cardiomyopathies and, in particular, left ventricular noncompaction, requires a comprehensive clinical, segregation and bioinformatic analysis using international databases and the use of bioinformatics software.

Combining whole exome sequencing with in silico analysis and clinical data to identify candidate variants in pediatric left ventricular noncompaction

We want to thank the authors for their carefully provided comments on our manuscript BFetal left ventricular non compaction cardiomyopathy and fatal outcome due to complete deficiency of mitochondrial trifunctional protein.^ The authors asked why left ventricular hypertrabeculation/ noncompaction was not diagnosed already prenatally during fetal echocardiography? As mentioned in the manuscript, fetal cardiac echocardiography showed significant biventricular cardiac hypertrophy already in the first fetal echocardiography at 22 gestational weeks. However, left ventricular noncompaction was overlooked and was not diagnosed before the patient was born. As pointed out by the authors, left ventricular noncompaction should be suspected if ventricular walls are thickened. We found the left ventricular noncompaction in postnatal echocardiography as shown in Figure 2 in the manuscript. In the postmortem examinations, cardiac findings were not in focus and we are not aware whether cardiomyopathy findings could even be conclusively studied by postmortem MRI. Both parents were heterozygous carriers of the mutation (HADHB gene, c.1109+243_1438-703del). We are not aware of any report in the literature that heterozygous carriers would have any abnormalities. Both the parents and the younger sister are without symptoms. The echocardiography with normal findings was done to the sister. Three different phenotypes have been described: the lethal phenotype, the infant-onset hepatic phenotype, and the lateronset neuromyopathic phenotype. The lethal phenotype is characterized by severe cardiomyopathy, lactic acidosis, hypoketotic hypoglycemia, and neonatal death. The phenotype of our patient was the most severe form of TFP deficiency. We appreciate that we have been given the opportunity for these clarifications. Tiina Ojala, MD, PhD

Left ventricular noncompaction (LVNC) is a reportedly uncommon genetic disorder of endocardial morphogenesis with a reportedly high mortality rate. The purpose of this study was to identify the clinical characteristics of children with LVNC. We retrospectively reviewed 36 children with LVNC evaluated at Texas Children's Hospital (TCH) from January 1997 to December 2002. Five children had associated cardiac lesions. There were 16 girls and 20 boys. The median age at presentation was 90 days (range, 1 day to 17 years). The median duration of follow-up was 3.2 years (range, 0.5 to 12 years). Twenty-seven patients (75%) had ECG abnormalities, most commonly biventricular hypertrophy (10 patients, 28%). Both ventricles were involved in 8 patients (22%) and only the left ventricle in 28 patients (78%). Left ventricular systolic function was depressed in 30 patients (83%), with a median ejection fraction of 30% (range, 15% to 66%) at diagnosis. Nine patients presenting in the first year of life with depressed left ventricular contractility had a transient recovery of function; however, ejection fraction deteriorated later in life, at a median interval of 6.3years (range, 3 to 12 years). Two patients had an "undulating" phenotype from dilated to hypertrophic cardiomyopathy. Two patients (6%) were identified with an underlying G4.5 gene mutation. Five patients (14%) died during the study. LVNC does not have an invariably fatal course when diagnosed in the neonatal period. A significant number of patients have transient recovery of function followed by later deterioration, which may account for many patients presenting as adults, some manifesting an "undulating" phenotype.

CLINICAL CASEA 48-year-old male proband presented with atypical chest pain.An echocardiogram revealed possible left ventricular apical noncompaction that was confirmed by cardiac magnetic resonance imaging as left ventricular noncompaction cardiomyopathy (LVNC; Figure 1A).His ejection fraction was initially preserved at 60% but declined to 45% over the subsequent 6 years despite optimal medical therapy.His asymptomatic 19-year-old son was diagnosed with LVNC at the time of a screening echocardiogram, and follow-up cardiac magnetic resonance imaging confirmed the diagnosis (Figure 1B).His ejection fraction was 50% at the time of diagnosis and was subsequently stable for 5 years with medical therapy.An echocardiogram from the proband's father showed normal left ventricular structure and function with no excess trabeculation (Figure 1C and1D).The proband's daughter had a normal echocardiogram.There were no other family members with a known history of cardiomyopathy or heart failure (Figure 1E).

Left Ventricular Non-Compaction: Insights From Cardiovascular Magnetic Resonance Imaging

Transcriptome sequencing (mRNA-seq) is becoming a very versatile technique for profiling tumors, extending beyond its original intent of transcript quantification, identification of alternative transcripts, and detection of gene fusions. For instance, through recent advancements in RNA-seq data analyses, one can now computationally assess allele-specific gene expression and generate profiles of expressed somatic mutations. Here, we demonstrate the ability to identify chromosomal allelic imbalances (AI) through detection of haplotype-specific patterns in gene transcripts. This class of RNA-based observations may potentially reveal DNA-level chromosomal allelic imbalances or uncover large regions of transcription deregulation. From the TCGA Uterine Carcinosarcoma project, we downloaded exome and RNA sequencing data for 48 patients’ tumor/normal sample pairs in addition to their clinical annotations. We also downloaded Affymetrix SNP6-based DNA copy number event calls made by the TCGA for use as a gold standard when evaluating the AI calls in the exome and RNA-seq. AI calls were made in both the exome and RNA-seq data by: (1) calling 1000 Genomes genotypes in the sequencing data, (2) phasing haplotypes and then (3) characterizing haplotype imbalances using a tool that we developed called hapLOHseq. hapLOHseq applied to the exome and RNA-seq data both resulted in a 72% specificity for identifying the gold standard AI events. In RNA-seq data we detected 43% of the chromosomal AI events identified in the exome sequencing data. When considering AI events specifically detected in the RNA-seq and not the gold standard (RNA-specific AI), the data suggest that higher RNA-specific AI loads could be negatively associated with survival (p-val = 0.076), with higher RNA-specific AI load patients having a median survival of 771 days compared to 1526 days for those patients with lower loads of RNA-specific AI. In conclusion, our results suggest that analysis of chromosomal AI in RNA-seq has equal specificity for detecting DNA-level AI when compared to exome sequencing, although at lower sensitivities. Clinically, our analyses suggest that patients with higher RNA-specific AI load may have a worse overall survival prognosis. The AI we are identifying in the RNA-seq samples may reflect large-scale transcription defects, resulting in a negative impact on the survival of patients. One possible cause of RNA-specific allelic imbalance could be the presence of cis mutations that impact a large-region of the transcription of one of the two haplotypes. Currently, we are identifying areas for improvement in our analytical methods, while interrogating and characterizing exome and RNA-seq AI in additional data sets. Citation Format: Francis A. San Lucas, Yihua Liu, Zachary Weber, Erik Ehli, Gareth Davies, Paul Scheet. Characterization of chromosomal allelic imbalances through RNA-seq [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3572. doi:10.1158/1538-7445.AM2017-3572

Left Ventricular Non-compaction in Holt-Oram Syndrome

Targeted gene disruption in mice has provided valuable insights into the functions of matricellular proteins. Apart from missense and loss of function mutations that have been associated with inherited diseases, however, their functions in humans remain unclear. The availability of deep exome sequencing data from over 140,000 individuals in the Genome Aggregation Database provided an opportunity to examine intolerance to loss of function and missense mutations in human matricellular genes. The probability of loss-of-function intolerance (pLI) differed widely within members of the thrombospondin, CYR61/CTGF/NOV (CCN), tenascin, small integrin-binding ligand N-linked glycoproteins (SIBLING), and secreted protein, acidic and rich in cysteine (SPARC) gene families. Notably, pLI values in humans had limited correlation with viability of the corresponding homozygous null mice. Among the thrombospondins, only THBS1 was highly loss-intolerant (pLI = 1). In contrast, Thbs1 is not essential for viability in mice. Several known thrombospondin-1 receptors were similarly loss-intolerant, although thrombospondin-1 is not the exclusive ligand for some of these receptors. The frequencies of missense mutations in THBS1 and the gene encoding its signaling receptor CD47 indicated conservation of some residues implicated in specific receptor binding. Deficits in missense mutations were also observed for other thrombospondin genes and for SPARC, SPOCK1, SPOCK2, TNR, and DSPP. The intolerance of THBS1 to loss of function in humans and elevated pLI values for THBS2, SPARC, SPOCK1, TNR, and CCN1 support important functions for these matricellular protein genes in humans, some of which may relate to functions in reproduction or responding to environmental stresses.

Copy number variants (CNV) are shown to contribute to the etiology of several genetic disorders. Accurate detection of CNVs on whole exome sequencing (WES) data has been a long sought-after goal for use in clinics. This was not possible despite recent improvements in performance because algorithms mostly suffer from low precision and even lower recall on expert-curated gold standard call sets. Here, we present a deep learning-based somatic and germline CNV caller for WES data, named ECOLE. Based on a variant of the transformer architecture, the model learns to call CNVs per exon, using high-confidence calls made on matched WGS samples. We further train and fine-tune the model with a small set of expert calls via transfer learning. We show that ECOLE achieves high performance on human expert labelled data for the first time with 68.7% precision and 49.6% recall. This corresponds to precision and recall improvements of 18.7% and 30.8% over the next best-performing methods, respectively. We also show that the same fine-tuning strategy using tumor samples enables ECOLE to detect RT-qPCR-validated variations in bladder cancer samples without the need for a control sample. ECOLE is available at https://github.com/ciceklab/ECOLE .

It is more than 50 years since the first modern description of hypertrophic cardiomyopathy (HCM).1 Understanding has been driven by technology, with the first descriptions focusing on clinical examination, ECG changes, and histological changes from autopsy study. As technology evolved from ventriculography, M-mode, then 2-dimensional echocardiography, and cardiovascular magnetic resonance (CMR), understanding has evolved and the known phenotype of the disease has extended. Recent notable examples of this have been hypertrophy missed by echo, particularly but not exclusively at the apex, mitral valve abnormalities, apical aneurysms, and proposed familial criteria, where even subtle abnormalities may be adjudged significant in the context of a pretest probability of 50% of genetic mutation carriage. In this issue of Circulation: Cardiovascular Imaging , Maron et al2 have explored the potential significance of myocardial crypts. These “architectural abnormalities” of the left ventricle (LV) occur particularly in the septum and inferior (posterior) right ventricular (RV) insertion point and had been observed at increased frequency in HCM. …

Mutations in FBXL4 (F-Box and Leucine rich repeat protein 4), a nuclear-encoded mitochondrial protein with an unknown function, cause mitochondrial DNA depletion syndrome. We report two siblings, from consanguineous parents, harbouring a previously uncharacterized homozygous variant in FBXL4 (c.1750 T > C; p.Cys584Arg). Both patients presented with encephalomyopathy, lactic acidosis and cardiac hypertrophy, which are reported features of FBXL4 impairment. Remarkably, dichloroacetate (DCA) administration to the younger sibling improved metabolic acidosis and reversed cardiac hypertrophy. Characterization of FBXL4 patient fibroblasts revealed severe bioenergetic defects, mtDNA depletion, fragmentation of mitochondrial networks, and abnormalities in mtDNA nucleoids. These phenotypes, observed with other pathogenic FBXL4 variants, confirm the pathogenicity of the p.Cys584Arg variant. Although treating FBXL4 fibroblasts with DCA improved extracellular acidification, in line with reduced lactate levels in patients, DCA treatment did not improve any of the other mitochondrial functions. Nonetheless, we highlight DCA as a potentially effective drug for the management of elevated lactate and cardiomyopathy in patients with pathogenic FBXL4 variants. Finally, as the exact mechanism through which FBXL4 mutations lead to mtDNA depletion was unknown, we tested the hypothesis that FBXL4 promotes mitochondrial fusion. Using a photo-activatable GFP fusion assay, we found reduced mitochondrial fusion rates in cells harbouring a pathogenic FBXL4 variant. Meanwhile, overexpression of wildtype FBXL4, but not the p.Cys584Arg variant, promoted mitochondrial hyperfusion. Thus, we have uncovered a novel function for FBXL4 in promoting mitochondrial fusion, providing important mechanistic insights into the pathogenic mechanism underlying FBXL4 dysfunction.

Mucosa-associated lymphoid tissue lymphoma (MALToma) is an extranodal B cell lymphoma, predominantly associated with bacterial infection of the stomach by Helicobacter pylori (H. pylori). Infection of H. pylori can be divided into four steps: 1) entrance into host and survival; 2) motility and chemotaxis; 3) Interaction between adhesion-receptors and colonization, and 4) release of toxins and damage to host. To date, pathogenesis of bacteria related lymphoma and individual functions of H. pylori genes are not yet unearthed. Hence, we aim to characterize the carcinogenic mechanism of H. pylori-related MALToma throughout this study.We obtained fresh gastric tissues of both tumor and adjacent normal region from MALToma patients. Using the tissue and saliva samples, we generated 12 sets of whole exome and transcriptome sequencing data. To identify the gene expression pattern, we aligned the raw data using STAR algorithm and quantified expression of genes in both H. pylori and human genome. Next, we estimated the relative abundance of immune cells in each tissue, employing a linear support vector regression (SVR) based analytical algorithm, CIBERSORT. Besides, we investigated somatic mutations in the patients using our internal pipeline.Gene expression profiling of H. pylori enabled us to identify frequently expressed genes in MALToma, and among them, aliphatic amidase (aimE) was expressed in 9 of 21 lesion tissues. The role of aimE is to contribute to ammonia production, which is analogous to that urease. Then, we explored gene expression pattern of immune checkpoint modulators. We determined that major groups of high CD112, CD155, and VISTA expression, and minor groups of high CD86 and PD-L1 expression, signifying cell adhesion and regulation of T cell activation.From CIBERSORT data, we found that increment of resting CD4 memory T cells and decrease of plasma cells in pair-wise MALToma donors. Since CD4+ T cells are abundantly distributed in the gastric cellular infiltrates, this immune cell composition implies that CD4 memory T cells might have been re-activated by exposure to bacterial antigens. In addition, majority of B cells including plasma cells die after they fight against infected cells, and this supports the decreased plasma cells in the tumor tissues.Using exome sequencing data, we identified two recurrent missense mutations (K169R and N175S) of a cell cycle gene, CDC27, in ~20% of MALToma patients. across the donors. Previous studies mentioned that impaired functions of CDC27 facilitate cell growth as it fails to regulate the cell growth inhibition.To understand carcinogenesis of H. pylori-related MALToma, we focused on determining gene expression patterns, immune cell composition, and recurrent somatic mutations. In conclusion, we demonstrated expression profiling of both H. pylori genes and human checkpoint modulators, estimation of immune cell abundance, and verification of recurrent DNA mutations, in MALToma. Citation Format: Hyojin Song, Eun Ae Kang, Hosim Soh, Sungyoung Lee, Hongseok Yun, Hyunsoo Chung, Jaeyoung Chun, Sung-Soo Yoon, Youngil Koh. Understanding H. pylori-related gastric MALToma using multi-omics data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3794.

BackgroundOne of the major hurdles in clinical genetics is interpreting the clinical consequences associated with germline missense variants in humans. Recent significant advances have leveraged natural variation observed in large-scale human populations to uncover genes or genomic regions that show a depletion of natural variation, indicative of selection pressure. We refer to this as “genetic constraint”. Although existing genetic constraint metrics have been demonstrated to be successful in prioritising genes or genomic regions associated with diseases, their spatial resolution is limited in distinguishing pathogenic variants from benign variants within genes.MethodsWe aim to identify missense variants that are significantly depleted in the general human population. Given the size of currently available human populations with exome or genome sequencing data, it is not possible to directly detect depletion of individual missense variants, since the average expected number of observations of a variant at most positions is less than one. We instead focus on protein domains, grouping homologous variants with similar functional impacts to examine the depletion of natural variations within these comparable sets. To accomplish this, we develop the Homologous Missense Constraint (HMC) score. We utilise the Genome Aggregation Database (gnomAD) 125 K exome sequencing data and evaluate genetic constraint at quasi amino-acid resolution by combining signals across protein homologues.ResultsWe identify one million possible missense variants under strong negative selection within protein domains. Though our approach annotates only protein domains, it nonetheless allows us to assess 22% of the exome confidently. It precisely distinguishes pathogenic variants from benign variants for both early-onset and adult-onset disorders. It outperforms existing constraint metrics and pathogenicity meta-predictors in prioritising de novo mutations from probands with developmental disorders (DD). It is also methodologically independent of these, adding power to predict variant pathogenicity when used in combination. We demonstrate utility for gene discovery by identifying seven genes newly significantly associated with DD that could act through an altered-function mechanism.ConclusionsGrouping variants of comparable functional impacts is effective in evaluating their genetic constraint. HMC is a novel and accurate predictor of missense consequence for improved variant interpretation.