Dorien Daneels

DIDA: A curated and annotated digenic diseases database

DIDA (DIgenic diseases DAtabase) is a novel database that provides for the first time detailed information on genes and associated genetic variants involved in digenic diseases, the simplest form of oligogenic inheritance. The database is accessible via http://dida.ibsquare.be and currently includes 213 digenic combinations involved in 44 different digenic diseases. These combinations are composed of 364 distinct variants, which are distributed over 136 distinct genes. The web interface provides browsing and search functionalities, as well as documentation and help pages, general database statistics and references to the original publications from which the data have been collected. The possibility to submit novel digenic data to DIDA is also provided. Creating this new repository was essential as current databases do not allow one to retrieve detailed records regarding digenic combinations. Genes, variants, diseases and digenic combinations in DIDA are annotated with manually curated information and information mined from other online resources. Next to providing a unique resource for the development of new analysis methods, DIDA gives clinical and molecular geneticists a tool to find the most comprehensive information on the digenic nature of their diseases of interest.

SCN4A variants and Brugada syndrome: phenotypic and genotypic overlap between cardiac and skeletal muscle sodium channelopathies

SCN5A mutations involving the α-subunit of the cardiac voltage-gated muscle sodium channel (NaV1.5) result in different cardiac channelopathies with an autosomal-dominant inheritance such as Brugada syndrome. On the other hand, mutations in SCN4A encoding the α-subunit of the skeletal voltage-gated sodium channel (NaV1.4) cause non-dystrophic myotonia and/or periodic paralysis. In this study, we investigated whether cardiac arrhythmias or channelopathies such as Brugada syndrome can be part of the clinical phenotype associated with SCN4A variants and whether patients with Brugada syndrome present with non-dystrophic myotonia or periodic paralysis and related gene mutations. We therefore screened seven families with different SCN4A variants and non-dystrophic myotonia phenotypes for Brugada syndrome and performed a neurological, neurophysiological and genetic work-up in 107 Brugada families. In the families with an SCN4A-associated non-dystrophic myotonia, three patients had a clinical diagnosis of Brugada syndrome, whereas we found a remarkably high prevalence of myotonic features involving different genes in the families with Brugada syndrome. One Brugada family carried an SCN4A variant that is predicted to probably affect function, one family suffered from a not genetically confirmed non-dystrophic myotonia, one family was diagnosed with myotonic dystrophy (DMPK gene) and one family had a Thomsen disease myotonia congenita (CLCN1 variant that affects function). Our findings and data suggest a possible involvement of SCN4A variants in the pathophysiological mechanism underlying the development of a spontaneous or drug-induced type 1 electrocardiographic pattern and the occurrence of malignant arrhythmias in some patients with Brugada syndrome.

Contribution of Cardiac Sodium Channel β-Subunit Variants to Brugada Syndrome

BACKGROUND Brugada syndrome (BrS) is an inheritable cardiac disease associated with syncope, malignant ventricular arrhythmias and sudden cardiac death. The largest proportion of mutations in BrS is found in the SCN5A gene encoding the α-subunit of cardiac sodium channels (Nav1.5). Causal SCN5A mutations are present in 18-30% of BrS patients. The additional genetic diagnostic yield of variants in cardiac sodium channel β-subunits in BrS patients was explored and functional studies on 3 novel candidate variants were performed. METHODSANDRESULTS TheSCN1B-SCN4B genes were screened, which encode the 5 sodium channel β-subunits, in a SCN5A negative BrS population (n=74). Five novel variants were detected; in silico pathogenicity prediction classified 4 variants as possibly disease causing. Three variants were selected for functional study. These variants caused only limited alterations of Nav1.5 function. Next generation sequencing of a panel of 88 arrhythmia genes could not identify other major causal mutations. CONCLUSIONS It was hypothesized that the studied variants are not the primary cause of BrS in these patients. However, because small functional effects of these β-subunit variants can be discriminated, they might contribute to the BrS phenotype and be considered a risk factor. The existence of these risk factors can give an explanation to the reduced penetrance and variable expressivity seen in this syndrome. We therefore recommend including the SCN1-4B genes in a next generation sequencing-based gene panel.

Prolonged right ventricular ejection delay identifies high risk patients and gender differences in Brugada syndrome.

BACKGROUND AND OBJECTIVES Right ventricular (RV) conduction delay has been suggested as an underlying pathophysiological mechanism in Brugada syndrome (BS). In this cross-sectional study we non-invasively assessed the value of echocardiographic markers reflecting ventricular ejection delay to further assess electromechanical abnormalities in BS and to identify patients at risk for life-threatening arrhythmic events. Furthermore, we sought to assess differences in ejection delays between genders because male BS patients demonstrate a more malignant clinical phenotype. METHODS 124 BS patients (57.3% males) and 62 controls (CTR) (48.4% males) were included. Using Tissue Velocity Imaging, the ejection delay, determined as the time from QRS onset to the onset of the sustained systolic contraction, was measured for both RV free wall (RVED) and lateral LV wall (LVED). From these parameters, the interventricular ejection delay between both walls (IVED) was calculated. RESULTS BS patients had longer RVEDs and IVEDs compared to the CTR. BS patients with a previous history of syncope or spontaneous ventricular arrhythmia showed the longest RVEDs and IVEDs. Male BS patients demonstrated longer RVEDs and IVEDs than females. Male BS patients with malignant events had the longest delays. No significant differences regarding LVED were observed between BS patients and CTR. CONCLUSIONS We demonstrated that a previous history of malignant events was associated with longer RVEDs. Our findings supported the RV conduction delay mechanism behind BS and demonstrated for the first time that the predominant malignant male Brugada phenotype might also be the result of a more delayed RV conduction in males.

Accurate and comprehensive analysis of single nucleotide variants and large deletions of the human mitochondrial genome in DNA and single cells

Massive parallel sequencing (MPS) can accurately quantify mitochondrial DNA (mtDNA) single nucleotide variants (SNVs), but no MPS methods are currently validated to simultaneously and accurately establish the breakpoints and frequency of large deletions at low heteroplasmic loads. Here we present the thorough validation of an MPS protocol to quantify the load of very low frequency, large mtDNA deletions in bulk DNA and single cells, along with SNV calling by standard methods. We used a set of well-characterized DNA samples, DNA mixes and single cells to thoroughly control the study. We developed a custom script for the detection of mtDNA rearrangements that proved to be more accurate in detecting and quantifying deletions than pre-existing tools. We also show that PCR conditions and primersets must be carefully chosen to avoid biases in the retrieved variants and an increase in background noise, and established a lower detection limit of 0.5% heteroplasmic load for large deletions, and 1.5 and 2% for SNVs, for bulk DNA and single cells, respectively. Finally, the analysis of different single cells provided novel insights into mtDNA cellular mosaicism.

Genomic Variant Classifier Tool

The exome or genome based high throughput screening techniques are becoming a definitive criterion in the conventional clinical analysis of the genetic diseases. However, pathogenic classification of an identified variant, is still a manual and time consuming process for clinical geneticists. Thus, to facilitate the variant classification process, we have developed GeVaCT, a Java based tool that implements a classification approach based on the literature review of cardiac arrhythmia syndromes. Furthermore, the adoption of this automated knowledge engineer by the clinical geneticists will aid to build a knowledge base for the evolution of the variant classification process by use of novel machine learning approaches.

Convert your favorite protein modeling program into a mutation predictor: "MODICT".

BackgroundPredict whether a mutation is deleterious based on the custom 3D model of a protein.ResultsWe have developed modict, a mutation prediction tool which is based on per residue rmsd (root mean square deviation) values of superimposed 3D protein models. Our mathematical algorithm was tested for 42 described mutations in multiple genes including renin (REN), beta-tubulin (TUBB2B), biotinidase (BTD), sphingomyelin phosphodiesterase-1 (SMPD1), phenylalanine hydroxylase (PAH) and medium chain Acyl-Coa dehydrogenase (ACADM). Moreover, modict scores corresponded to experimentally verified residual enzyme activities in mutated biotinidase, phenylalanine hydroxylase and medium chain Acyl-CoA dehydrogenase. Several commercially available prediction algorithms were tested and results were compared. The modictperl package and the manual can be downloaded from https://github.com/IbrahimTanyalcin/MODICT.ConclusionsWe show here that modict is capable tool for mutation effect prediction at the protein level, using superimposed 3D protein models instead of sequence based algorithms used by polyphen and sift.