Dataset Information

Interpreting Genetic Variants in Titin in Patients With Muscle Disorders.

ABSTRACT: Importance:Mutations in the titin gene (TTN) cause a wide spectrum of genetic diseases. The interpretation of the numerous rare variants identified in TTN is a difficult challenge given its large size. Objective:To identify genetic variants in titin in a cohort of patients with muscle disorders. Design, Setting, and Participants:In this case series, 9 patients with titinopathy and 4 other patients with possibly disease-causing variants in TTN were identified. Titin mutations were detected through targeted resequencing performed on DNA from 504 patients with muscular dystrophy, congenital myopathy, or other skeletal muscle disorders. Patients were enrolled from 10 clinical centers in April 2012 to December 2013. All of them had not received a diagnosis after undergoing an extensive investigation, including Sanger sequencing of candidate genes. The data analysis was performed between September 2013 and January 2017. Sequencing data were analyzed using an internal custom bioinformatics pipeline. Main Outcomes and Measures:The identification of novel mutations in the TTN gene and novel patients with titinopathy. We performed an evaluation of putative causative variants in the TTN gene, combining genetic, clinical, and imaging data with messenger RNA and/or protein studies. Results:Of the 9 novel patients with titinopathy, 5 (55.5%) were men and the mean (SD) age at onset was 25 (15.8) years (range, 0-46 years). Of the 4 other patients (3 men and 1 woman) with possibly disease-causing TTN variants, 2 (50%) had a congenital myopathy and 2 (50%) had a slowly progressive distal myopathy with onset in the second decade. Most of the identified mutations were previously unreported. However, all the variants, even the already described mutations, require careful clinical and molecular evaluation of probands and relatives. Heterozygous truncating variants or unique missense changes are not sufficient to make a diagnosis of titinopathy. Conclusions and Relevance:The interpretation of TTN variants often requires further analyses, including a comprehensive evaluation of the clinical phenotype (deep phenotyping) as well as messenger RNA and protein studies. We propose a specific workflow for the clinical interpretation of genetic findings in titin.

SUBMITTER: Savarese M

PROVIDER: S-EPMC5885217 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Heart failure (HF) is a complex clinical syndrome defined by the inability of the heart to pump enough blood to meet the body's metabolic demands. Major causes of HF are cardiomyopathies (diseases of the myocardium associated with mechanical and/or electrical dysfunction), among which the most common form is dilated cardiomyopathy (DCM). DCM is defined by ventricular chamber enlargement and systolic dysfunction with normal left ventricular wall thickness, which leads to progressive HF. Over 60 genes are linked to the etiology of DCM. Titin (TTN) is the largest known protein in biology, spanning half the cardiac sarcomere and, as such, is a basic structural and functional unit of striated muscles. It is essential for heart development as well as mechanical and regulatory functions of the sarcomere. Next-generation sequencing (NGS) in clinical DCM cohorts implicated truncating variants in titin (TTNtv) as major disease alleles, accounting for more than 25% of familial DCM cases, but these variants have also been identified in 2-3% of the general population, where these TTNtv blur diagnostic and clinical utility. Taking into account the published TTNtv and their association to DCM, it becomes clear that TTNtv harm the heart with position-dependent occurrence, being more harmful when present in the A-band TTN, presumably with dominant negative/gain-of-function mechanisms. However, these insights are challenged by the depiction of position-independent toxicity of TTNtv acting via haploinsufficient alleles, which are sufficient to induce cardiac pathology upon stress. In the current review, we provide an overview of TTN and discuss studies investigating various TTN mutations. We also present an overview of different mechanisms postulated or experimentally validated in the pathogenicity of TTNtv. DCM-causing genes are also discussed with respect to non-truncating mutations in the etiology of DCM. One way of understanding pathogenic variants is probably to understand the context in which they may or may not affect protein-protein interactions, changes in cell signaling, and substrate specificity. In this regard, we also provide a brief overview of TTN interactions in situ. Quantitative models in the risk assessment of TTNtv are also discussed. In summary, we highlight the importance of gene-environment interactions in the etiology of DCM and further mechanistic studies used to delineate the pathways which could be targeted in the management of DCM.

Project description:BackgroundNext-generation sequencing (NGS) is an efficient tool used for identifying pathogenic variants that cause Mendelian disorders. However, the lack of bioinformatics training of researchers makes the interpretation of identified variants a challenge in terms of precision and efficiency. In addition, the non-standardized phenotypic description of human diseases also makes it difficult to establish an integrated analysis pathway for variant annotation and interpretation. Solutions to these bottlenecks are urgently needed.ResultsWe develop a tool named "Cruxome" to automatically annotate and interpret single nucleotide variants (SNVs) and small insertions and deletions (InDels). Our approach greatly simplifies the current burdensome task of clinical geneticists and scientists to identify the causative pathogenic variants and build personal knowledge reference bases. The integrated architecture of Cruxome offers key advantages such as an interactive and user-friendly interface and the assimilation of electronic health records of the patient. By combining a natural language processing algorithm, Cruxome can efficiently process the clinical description of diseases to HPO standardized vocabularies. By using machine learning, in silico predictive algorithms, integrated multiple databases and supplementary tools, Cruxome can automatically process SNVs and InDels variants (trio-family or proband-only cases) and clinical diagnosis records, then annotate, score, identify and interpret pathogenic variants to finally generate a standardized clinical report following American College of Medical Genetics and Genomics/ Association for Molecular Pathology (ACMG/AMP) guidelines. Cruxome also provides supplementary tools to examine and visualize the genes or variations in historical cases, which can help to better understand the genetic basis of the disease.ConclusionsCruxome is an efficient tool for annotation and interpretation of variations and dramatically reduces the workload for clinical geneticists and researchers to interpret NGS results, simplifying their decision-making processes. We present an online version of Cruxome, which is freely available to academics and clinical researchers. The site is accessible at http://114.251.61.49:10024/cruxome/ .

Project description:ImportanceThere is a need for better arrhythmic risk stratification in nonischemic dilated cardiomyopathy (DCM). Titin-truncating variants (TTNtvs) in the TTN gene are the most common genetic cause of DCM and may be associated with higher risk of arrhythmias in patients with DCM.ObjectiveTo determine if TTNtv status is associated with the development of life-threatening ventricular arrhythmia and new persistent atrial fibrillation in patients with DCM and implanted cardioverter defibrillator (ICD) or cardiac resynchronization therapy defibrillator (CRT-D) devices.Design, setting, and participantsThis retrospective, multicenter cohort study recruited 148 patients with or without TTNtvs who had nonischemic DCM and ICD or CRT-D devices from secondary and tertiary cardiology clinics in the United Kingdom from February 1, 2011, to June 30, 2016, with a median (interquartile range) follow-up of 4.2 (2.1-6.5) years. Exclusion criteria were ischemic cardiomyopathy, primary valve disease, congenital heart disease, or a known or likely pathogenic variant in the lamin A/C gene. Analyses were performed February 1, 2017, to May 31, 2017.Main outcome and measuresThe primary outcome was time to first device-treated ventricular tachycardia of more than 200 beats/min or first device-treated ventricular fibrillation. Secondary outcome measures included time to first development of persistent atrial fibrillation.ResultsOf 148 patients recruited, 117 adult patients with nonischemic DCM and an ICD or CRT-D device (mean [SD] age, 56.9 [12.5] years; 76 [65.0%] men; 106 patients [90.6%] with primary prevention indications) were included. Having a TTNtv was associated with a higher risk of receiving appropriate ICD therapy (shock or antitachycardia pacing) for ventricular tachycardia or fibrillation (hazard ratio [HR], 4.9; 95% CI, 2.2-10.7; P < .001). This association was independent of all covariates, including midwall fibrosis measured by late gadolinium enhancement on cardiac magnetic resonance images (adjusted HR, 8.3; 95% CI, 1.8-37.6; P = .006). Having a TTNtv was also associated with the risk of receiving a shock (HR, 3.6; 95% CI, 1.1-11.6; P = .03). Individuals with a TTNtv and fibrosis had a greater rate of receiving appropriate device therapy than those with neither (HR, 16.6; 95% CI, 3.5-79.3; P < .001). Having a TTNtv was also a risk factor for developing new persistent atrial fibrillation (HR, 3.9; 95% CI, 1.3-12.0; P = .01).Conclusions and relevanceHaving a TTNtv was an important risk factor for clinically significant arrhythmia in patients with DCM and ICD or CRT-D devices. Having a TTNtv, especially in combination with midwall fibrosis confirmed with cardiovascular magnetic resonance imaging, may provide a risk stratification approach for evaluating the need for ICD therapy in patients with DCM. This hypothesis should be tested in larger studies.

Project description:ObjectiveThe diagnostic boundaries of sleep disorders are under considerable debate. The main sleep disorders are partly heritable; therefore, defining heritable pathophysiologic mechanisms could delineate diagnoses and suggest treatment. We collected clinical data and DNA from consenting patients scheduled to undergo clinical polysomnograms, to expand our understanding of the polymorphisms associated with the phenotypes of particular sleep disorders.MethodsPatients at least 21 years of age were recruited to contribute research questionnaires, and to provide access to their medical records, saliva for deoxyribonucleic acid (DNA), and polysomnographic data. From these complex data, 38 partly overlapping phenotypes were derived indicating complaints, subjective and objective sleep timing, and polysomnographic disturbances. A custom chip was used to genotype 768 single-nucleotide polymorphisms (SNPs). Additional assays derived ancestry-informative markers (eg, 751 participants of European ancestry). Linear regressions controlling for age, gender, and ancestry were used to assess the associations of each phenotype with each of the SNPs, highlighting those with Bonferroni-corrected significance.ResultsIn peroxisome proliferator-activated receptor gamma, coactivator 1 beta (PPARGC1B), rs6888451 was associated with several markers of obstructive sleep apnea. In aryl hydrocarbon receptor nuclear translocator-like (ARNTL), rs10766071 was associated with decreased polysomnographic sleep duration. The association of rs3923809 in BTBD9 with periodic limb movements in sleep was confirmed. SNPs in casein kinase 1 delta (CSNK1D rs11552085), cryptochrome 1 (CRY1 rs4964515), and retinoic acid receptor-related orphan receptor A (RORA rs11071547) were less persuasively associated with sleep latency and time of falling asleep.ConclusionsSNPs associated with several sleep phenotypes were suggested, but due to risks of false discovery, independent replications are needed before the importance of these associations can be assessed, followed by investigation of molecular mechanisms.

Dataset Information

Interpreting Genetic Variants in Titin in Patients With Muscle Disorders.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets