Identification of body fat tissues in MRI data

In recent years non-invasive medical diagnostic techniques have been used widely in medical investigations. Among the various imaging modalities available, Magnetic Resonance Imaging is very attractive as it produces multi-slice images where the contrast between various types of body tissues such as muscle, ligaments and fat is well defined. The aim of this paper is to describe the implementation of an unsupervised image analysis algorithm able to identify the body fat tissues from a sequence of MR images encoded in DICOM format. The developed algorithm consists of three main steps. The first step pre-processes the MR images in order to reduce the level of noise. The second step extracts the image areas representing fat tissues by using an unsupervised clustering algorithm. Finally, image refinements are applied to reclassify the pixels adjacent to the initial fat estimate and to eliminate outliers. The experimental data indicates that the proposed implementation returns accurate results and furthermore is robust to noise and to greyscale in-homogeneity

De Novo Mutations in SLC1A2 and CACNA1A Are Important Causes of Epileptic Encephalopathies

Epileptic encephalopathies (EEs) are the most clinically important group of severe early-onset epilepsies. Next-generation sequencing has highlighted the crucial contribution of de novo mutations to the genetic architecture of EEs as well as to their underlying genetic heterogeneity. Our previous whole-exome sequencing study of 264 parent-child trios revealed more than 290 candidate genes in which only a single individual had a de novo variant. We sought to identify additional pathogenic variants in a subset (n = 27) of these genes via targeted sequencing in an unsolved cohort of 531 individuals with a diverse range of EEs. We report 17 individuals with pathogenic variants in seven of the 27 genes, defining a genetic etiology in 3.2% of this unsolved cohort. Our results provide definitive evidence that de novo mutations in SLC1A2 and CACNA1A cause specific EEs and expand the compendium of clinically relevant genotypes for GABRB3. We also identified EEs caused by genetic variants in ALG13, DNM1, and GNAO1 and report a mutation in IQSEC2. Notably, recurrent mutations accounted for 7/17 of the pathogenic variants identified. As a result of high-depth coverage, parental mosaicism was identified in two out of 14 cases tested with mutant allelic fractions of 5%–6% in the unaffected parents, carrying significant reproductive counseling implications. These results confirm that dysregulation in diverse cellular neuronal pathways causes EEs, and they will inform the diagnosis and management of individuals with these devastating disorders

Current practice in diagnostic genetic testing of the epilepsies

Epilepsy genetics is a rapidly developing field, in which novel disease-associated genes, novel mechanisms associated with epilepsy, and precision medicine approaches are continuously being identified. In the past decade, advances in genomic knowledge and analysis platforms have begun to make clinical genetic testing accessible for, in principle, people of all ages with epilepsy. For this reason, the Genetics Commission of the International League Against Epilepsy (ILAE) presents this update on clinical genetic testing practice, including current techniques, indications, yield of genetic testing, recommendations for pre- and post-test counseling, and follow-up after genetic testing is completed. We acknowledge that the resources vary across different settings but highlight that genetic diagnostic testing for epilepsy should be prioritized when the likelihood of an informative finding is high. Results of genetic testing, in particular the identification of causative genetic variants, are likely to improve individual care. We emphasize the importance of genetic testing for individuals with epilepsy as we enter the era of precision therapy.</p

Mutations in the mitochondrial cysteinyl-tRNA synthase gene, CARS2,

Background: Mitochondrial disease is often suspected in cases of severe epileptic encephalopathy especially when a complex movement disorder, liver involvement and progressive developmental regression are present. Although mutations in either mitochondrial DNA or POLG are often present, other nuclear defects in mitochondrial DNA replication and protein translation have been associated with a severe epileptic encephalopathy. Methods: and results We identified a proband with an epileptic encephalopathy, complex movement disorder and a combined mitochondrial respiratory chain enzyme deficiency. The child presented with neurological regression, complex movement disorder and intractable seizures. A combined deficiency of mitochondrial complexes I, III and IV was noted in liver tissue, along with increased mitochondrial DNA content in skeletal muscle. Incomplete assembly of complex V, using blue native polyacrylamide gel electrophoretic analysis and complex I, using western blotting, suggested a disorder of mitochondrial transcription or translation. Exome sequencing identified compound heterozygous mutations in CARS2, a mitochondrial aminoacyl-tRNA synthetase. Both mutations affect highly conserved amino acids located within the functional ligase domain of the cysteinyl-tRNA synthase. A specific decrease in the amount of charged mt-tRNACys was detected in patient fibroblasts compared with controls. Retroviral transfection of the wild-type CARS2 into patient skin fibroblasts led to the correction of the incomplete assembly of complex V, providing functional evidence for the role of CARS2 mutations in disease aetiology. Conclusions: Our findings indicate that mutations in CARS2 result in a mitochondrial translational defect as seen in individuals with mitochondrial epileptic encephalopathy

Neurodevelopmental and Epilepsy Phenotypes in Individuals With Missense Variants in the Voltage-Sensing and Pore Domains of KCNH5

Background and Objectives KCNH5 encodes the voltage-gated potassium channel EAG2/Kv10.2. We aimed to delineate the neurodevelopmental and epilepsy phenotypic spectrum associated with de novo KCNH5 variants.Methods We screened 893 individuals with developmental and epileptic encephalopathies for KCNH5 variants using targeted or exome sequencing. Additional individuals with KCNH5 variants were identified through an international collaboration. Clinical history, EEG, and imaging data were analyzed; seizure types and epilepsy syndromes were classified. We included 3 previously published individuals including additional phenotypic details.Results We report a cohort of 17 patients, including 9 with a recurrent de novo missense variant p.Arg327His, 4 with a recurrent missense variant p.Arg333His, and 4 additional novel missense variants. All variants were located in or near the functionally critical voltage-sensing or pore domains, absent in the general population, and classified as pathogenic or likely pathogenic using the American College of Medical Genetics and Genomics criteria. All individuals presented with epilepsy with a median seizure onset at 6 months. They had a wide range of seizure types, including focal and generalized seizures. Cognitive outcomes ranged from normal intellect to profound impairment. Individuals with the recurrent p.Arg333His variant had a self-limited drug-responsive focal or generalized epilepsy and normal intellect, whereas the recurrent p.Arg327His variant was associated with infantile-onset DEE. Two individuals with variants in the pore domain were more severely affected, with a neonatal-onset movement disorder, early-infantile DEE, profound disability, and childhood death.Discussion We describe a cohort of 17 individuals with pathogenic or likely pathogenic missense variants in the voltage-sensing and pore domains of Kv10.2, including 14 previously unreported individuals. We present evidence for a putative emerging genotype-phenotype correlation with a spectrum of epilepsy and cognitive outcomes. Overall, we expand the role of EAG proteins in human disease and establish KCNH5 as implicated in a spectrum of neurodevelopmental disorders and epilepsy.</p

Diagnostic Utility of DNA Methylation Analysis in Genetically Unsolved Pediatric Epilepsies and CHD2 Episignature Refinement

Sequence-based genetic testing identifies causative variants in ~ 50% of individuals with developmental and epileptic encephalopathies (DEEs). Aberrant changes in DNA methylation are implicated in various neurodevelopmental disorders but remain unstudied in DEEs. We interrogate the diagnostic utility of genome-wide DNA methylation array analysis on peripheral blood samples from 582 individuals with genetically unsolved DEEs. We identify rare differentially methylated regions (DMRs) and explanatory episignatures to uncover causative and candidate genetic etiologies in 12 individuals. Using long-read sequencing, we identify DNA variants underlying rare DMRs, including one balanced translocation, three CG-rich repeat expansions, and four copy number variants. We also identify pathogenic variants associated with episignatures. Finally, we refine the CHD2 episignature using an 850 K methylation array and bisulfite sequencing to investigate potential insights into CHD2 pathophysiology. Our study demonstrates the diagnostic yield of genome-wide DNA methylation analysis to identify causal and candidate variants as 2% (12/582) for unsolved DEE cases

Exome sequencing of 20,979 individuals with epilepsy reveals shared and distinct ultra-rare genetic risk across disorder subtypes

Identifying genetic risk factors for highly heterogeneous disorders like epilepsy remains challenging. Here, we present the largest whole-exome sequencing study of epilepsy to date, with >54,000 human exomes, comprising 20,979 deeply phenotyped patients from multiple genetic ancestry groups with diverse epilepsy subtypes and 33,444 controls, to investigate rare variants that confer disease risk. These analyses implicate seven individual genes, three gene sets, and four copy number variants at exome-wide significance. Genes encoding ion channels show strong association with multiple epilepsy subtypes, including epileptic encephalopathies, generalized and focal epilepsies, while most other gene discoveries are subtype-specific, highlighting distinct genetic contributions to different epilepsies. Combining results from rare single nucleotide/short indel-, copy number-, and common variants, we offer an expanded view of the genetic architecture of epilepsy, with growing evidence of convergence among different genetic risk loci on the same genes. Top candidate genes are enriched for roles in synaptic transmission and neuronal excitability, particularly postnatally and in the neocortex. We also identify shared rare variant risk between epilepsy and other neurodevelopmental disorders. Our data can be accessed via an interactive browser, hopefully facilitating diagnostic efforts and accelerating the development of follow-up studies

Ultra-rare genetic variation in common epilepsies: a case-control sequencing study

BACKGROUND:Despite progress in understanding the genetics of rare epilepsies, the more common epilepsies have proven less amenable to traditional gene-discovery analyses. We aimed to assess the contribution of ultra-rare genetic variation to common epilepsies. METHODS:We did a case-control sequencing study with exome sequence data from unrelated individuals clinically evaluated for one of the two most common epilepsy syndromes: familial genetic generalised epilepsy, or familial or sporadic non-acquired focal epilepsy. Individuals of any age were recruited between Nov 26, 2007, and Aug 2, 2013, through the multicentre Epilepsy Phenome/Genome Project and Epi4K collaborations, and samples were sequenced at the Institute for Genomic Medicine (New York, USA) between Feb 6, 2013, and Aug 18, 2015. To identify epilepsy risk signals, we tested all protein-coding genes for an excess of ultra-rare genetic variation among the cases, compared with control samples with no known epilepsy or epilepsy comorbidity sequenced through unrelated studies. FINDINGS:We separately compared the sequence data from 640 individuals with familial genetic generalised epilepsy and 525 individuals with familial non-acquired focal epilepsy to the same group of 3877 controls, and found significantly higher rates of ultra-rare deleterious variation in genes established as causative for dominant epilepsy disorders (familial genetic generalised epilepsy: odd ratio [OR] 2·3, 95% CI 1·7-3·2, p=9·1 × 10-8; familial non-acquired focal epilepsy 3·6, 2·7-4·9, p=1·1 × 10-17). Comparison of an additional cohort of 662 individuals with sporadic non-acquired focal epilepsy to controls did not identify study-wide significant signals. For the individuals with familial non-acquired focal epilepsy, we found that five known epilepsy genes ranked as the top five genes enriched for ultra-rare deleterious variation. After accounting for the control carrier rate, we estimate that these five genes contribute to the risk of epilepsy in approximately 8% of individuals with familial non-acquired focal epilepsy. Our analyses showed that no individual gene was significantly associated with familial genetic generalised epilepsy; however, known epilepsy genes had lower p values relative to the rest of the protein-coding genes (p=5·8 × 10-8) that were lower than expected from a random sampling of genes. INTERPRETATION:We identified excess ultra-rare variation in known epilepsy genes, which establishes a clear connection between the genetics of common and rare, severe epilepsies, and shows that the variants responsible for epilepsy risk are exceptionally rare in the general population. Our results suggest that the emerging paradigm of targeting of treatments to the genetic cause in rare devastating epilepsies might also extend to a proportion of common epilepsies. These findings might allow clinicians to broadly explain the cause of these syndromes to patients, and lay the foundation for possible precision treatments in the future. FUNDING:National Institute of Neurological Disorders and Stroke (NINDS), and Epilepsy Research UK

Genome-wide association meta-analyses of drug-resistant epilepsy

Background Epilepsy is one of the most common neurological disorders, affecting over 50 million people worldwide. One-third of people with epilepsy do not respond to currently available anti-seizure medications, constituting one of the most important problems in epilepsy. Little is known about the molecular pathology of drug resistance in epilepsy, in particular, possible underlying genetic factors are largely unknown. Methods We performed a genome-wide association study (GWAS) in two epilepsy cohorts of European ancestry, comparing drug-resistant (N = 4208) to drug-responsive individuals (N = 2618) followed by meta-analyses across the studies. Next, we performed subanalyses split into two broad subtypes: acquired or non-acquired focal and genetic generalized epilepsy. Findings Our drug-resistant versus drug-responsive epilepsy GWAS meta-analysis showed no significant loci when combining all epilepsy types. Sub-analyses on individuals with focal epilepsy (FE) identified a significant locus on chromosome 1q42.11-q42.12 (lead SNP: rs35915186, P = 1·51 × 10−8, OR[C] = 0·74). This locus was not associated with any epilepsy subtype in the latest epilepsy GWAS (lowest uncorrected P = 0·009 for FE vs. healthy controls), and drug resistance in FE was not genetically correlated with susceptibility to FE itself. Seven genome-wide significant SNPs within this locus, encompassing the genes CNIH4, WDR26, and CNIH3, were identified to protect against drug-resistant FE. Further transcriptome-wide association studies (TWAS) imply significantly higher expression levels of CNIH3 and WDR26 in drug-resistant FE than in drug-responsive FE. CNIH3 is implicated in AMPA receptor assembly and function, while WDR26 haploinsufficiency is linked to intellectual disability and seizures. These findings suggest that CNIH3 and WDR26 may play a role in mediating drug response in focal epilepsy. Interpretation We identified a contribution of common genetic variation to drug-resistant focal epilepsy. These findings provide insights into possible mechanisms underlying drug response variability in epilepsy, offering potential targets for personalised treatment approaches