Neuromuscular disease genetics in under-represented populations: increasing data diversity.

Neuromuscular diseases (NMDs) affect ∼15 million people globally. In high income settings DNA-based diagnosis has transformed care pathways and led to gene-specific therapies. However, most affected families are in low-to-middle income countries (LMICs) with limited access to DNA-based diagnosis. Most (86%) published genetic data is derived from European ancestry. This marked genetic data inequality hampers understanding of genetic diversity and hinders accurate genetic diagnosis in all income settings. We developed a cloud-based transcontinental partnership to build diverse, deeply-phenotyped and genetically characterized cohorts to improve genetic architecture knowledge, and potentially advance diagnosis and clinical management. We connected 18 centres in Brazil, India, South Africa, Turkey, Zambia, Netherlands and the UK. We co-developed a cloud-based data solution and trained 17 international neurology fellows in clinical genomic data interpretation. Single gene and whole exome data were analysed via a bespoke bioinformatics pipeline and reviewed alongside clinical and phenotypic data in global webinars to inform genetic outcome decisions. We recruited 6001 participants in the first 43 months. Initial genetic analyses 'solved' or 'possibly solved' ∼56% probands overall. In-depth genetic data review of the four commonest clinical categories (limb girdle muscular dystrophy, inherited peripheral neuropathies, congenital myopathy/muscular dystrophies and Duchenne/Becker muscular dystrophy) delivered a ∼59% 'solved' and ∼13% 'possibly solved' outcome. Almost 29% of disease causing variants were novel, increasing diverse pathogenic variant knowledge. Unsolved participants represent a new discovery cohort. The dataset provides a large resource from under-represented populations for genetic and translational research. In conclusion, we established a remote transcontinental partnership to assess genetic architecture of NMDs across diverse populations. It supported DNA-based diagnosis, potentially enabling genetic counselling, care pathways and eligibility for gene-specific trials. Similar virtual partnerships could be adopted by other areas of global genomic neurological practice to reduce genetic data inequality and benefit patients globally.

High diagnostic yield with algorithmic molecular approach on hereditary neuropathies.

OBJECTIVE: Charcot-Marie-Tooth disease covers a group of inherited peripheral neuropathies. The aim of this study was to investigate the effect of targeted next-generation sequencing panels on the molecular diagnosis of Charcot-Marie-Tooth disease and its subtypes in routine clinical practice, and also to show the limitations and importance of next-generation sequencing in the diagnosis of Charcot-Marie-Tooth diseases. METHODS: This is a retrospective study. Three different molecular methods (multiplex ligation probe amplification, next-generation sequencing, and whole-exome sequencing) were used to detect the mutations related to Charcot-Marie-Tooth disease. RESULTS: In total, 64 patients (33 males and 31 females) with suspected Charcot-Marie-Tooth disease were analyzed for molecular etiology. In all, 25 (39%) patients were diagnosed by multiplex ligation probe amplification. With an extra 11 patients with normal PMP22 multiplex ligation probe amplification results that were consulted to our laboratory for further genetic analysis, a total of 50 patients underwent next-generation sequencing for targeted gene panels associated with Charcot-Marie-Tooth disease. Notably, 18 (36%) patients had pathogenic/likely pathogenic variants. Whole-exome sequencing was performed on five patients with normal next-generation sequencing results; the diagnostic yield by whole-exome sequencing was 80% and it was higher in the childhood group. CONCLUSION: The molecular etiology in Charcot-Marie-Tooth disease patients can be determined according to pre-test evaluation, deciding the inheritance type with pedigree analysis, the clinical phenotype, and an algorithm for the genetic analysis. The presence of patients without a molecular diagnosis in all the literature suggests that there are new genes or mechanisms waiting to be discovered in the etiology of Charcot-Marie-Tooth disease.

High diagnostic yield of targeted next-generation sequencing panel as a first-tier molecular test for the patients with myopathy or muscular dystrophy.

Muscular dystrophies are a heterogeneous group of neuromuscular disorders with a wide range of the clinical and genetic spectrum. Whole-exome sequencing (WES) has been on the rise to become the usual method of choice for molecular diagnosis in patients presenting with muscular dystrophy or congenital or metabolic myopathy phenotype. Here, we used a panel with 47 genes including not only muscular dystrophy but also myopathy-associated genes that had been used as a first-tier approach. A total of 146 patients who were referred to our clinic with the prediagnosis of muscular dystrophy and/or myopathy were included in the study. Dystrophin gene deletion/duplication was ruled out on the patients with a preliminary diagnosis of Duchenne muscular dystrophy. In this study, the molecular etiology of 67 patients was proved with the gene panel with a diagnostic yield of 46%. Causal variants were identified in 23 genes including CAPN3(11), DYSF(9), DMD(8), SGCA(5), TTN(4), LAMA2(3), LMNA(3), SGCB(3), COL6A1(3), DES (2), CAV3(2), FKRP(2), FKTN(2), ANO5, COL6A2, CLCN1, GNE, POMGNT1, POMGNT2, POMT2, SYNE1, TCAP, and FLNC with 16 novel variants. There were 27 patients with uncertain molecular results including the ones who had a variant of uncertain significance, who had only one heterozygous variant for an autosomal recessive disease, and the ones who had two variants in different genes. Molecular diagnosis in muscular dystrophy is essential to plan clinical management and choosing treatment options. Also, the results will affect the reproduction options. Targeted next-generation sequencing is a cost-effective method that reduces the WES requirements with a significant diagnostic rate.

Risk of recurrence after antiepileptic withdrawal: Was it a good decision or not?

Background: The aim of this study was to identify the demographic-clinical variables affecting idiopathic epilepsy (IE) [called genetic generalized epilepsy (GGE)] recurrence and determine cut-off values that can be used in pediatric neurology practice for children with IE/GGE. Methods: A total of 250 children and adolescents with IE/GGE were included and retrospectively evaluated. The patients' hospital records were examined in order to identify possible electro-clinical features affecting epilepsy recurrence. Results: The overall rate of recurrence in the patients was 46%; the age at onset of seizures in recurrence group was lower (P = 0.040) and the age at last seizure was higher in the recurrence group (P < 0.001) than that in the non-recurrence group. Other factors found to be related to recurrence were the shorter duration of the seizure-free period (P = 0.030), shorter interval between the last seizure and antiepileptic drug (AED) withdrawal (P = 0.003), shorter duration of AED withdrawal (P = 0.005), and the existence of abnormalities on sleep electroencephalogram (EEG) during AED withdrawal (P = 0.010) and at the 6th month of withdrawal (P < 0.001). According to receiver operating characteristic (ROC) analysis, the risk of IE recurrence was higher in children who were younger than 3.6 years old (sensitivity: 65.6%, specificity: 62.7%), children with a seizure-free period that was shorter than 35.5 months (sensitivity: 89.6%, specificity: 32.8%), and children whose drug withdrawal period was shorter than 4.5 months (sensitivity: 56.3%, specificity: 71.6%). Conclusion: This study defined some electro-clinical factors that could guide clinicians when deciding to withdraw AEDs with regard to recurrence risk after evaluating a homogenous population of children with a diagnosis of IE/GGE.

Utility of estimated glucose disposal rate for predicting metabolic syndrome in children and adolescents with type-1 diabetes.

Objectives To determine the clinical utility of the estimated glucose disposal rate (eGDR) for predicting metabolic syndrome (MetS) in children and adolescents with type-1 diabetes (T1D). Methods Modified criteria of the International Diabetes Federation were used to determine MetS in children and adolescents between 10 and 18 years of age with T1D. The eGDR, a validated marker of insulin sensitivity, was calculated in two different ways using either the waist-to-hip ratio (WHR) or waist circumference (WC). Receiver operating characteristic (ROC) curve analysis was performed to ascertain cut-off levels of the eGDR to predict MetS. Results A total of 200 patients (52% male) with T1D were enrolled in the study. The prevalence of MetS was 10.5% (n: 21). Lower eGDR levels, indicating greater insulin resistance, were found in T1D patients with MetS when compared to those without (6.41 ± 1.86 vs. 9.50 ± 1.34 mg/kg/min) (p < 0.001). An eGDRWHR cut-off of 8.44 mg/kg/min showed 85.7% sensitivity and 82.6% specificity, while an eGDRWC cut-off of 8.16 mg/kg/min showed 76.1% sensitivity and 92.1% specificity for MetS diagnosis. The diagnostic odds ratio was 28.6 (7.3-131.0) for the eGDRWHR cut-off and 37.7 (10.8-140.8) for the eGDRWC cut-off. Conclusions The eGDR is a mathematical formula that can be used in clinical practice to detect the existence of MetS in children and adolescents with T1D using only the WC, existence of hypertension, and hemoglobin A1c levels. An eGDR calculated using the WC could be a preferred choice due to its higher diagnostic performance.

Benign epilepsy with centrotemporal spikes: Is there a thalamocortical network dysfunction present?

INTRODUCTION: Benign epilepsy of childhood with centrotemporal spikes (BECTS) is one of the most frequently seen epileptic syndromes in childhood. It is characterized by centrotemporal spikes (CTS) on electroencephalography (EEG) that are typically activated by drowsiness and stage N2 sleep. The location, frequency, and amplitude of the spikes may vary in different EEG records of the same patient, supporting the presence of a global pathology rather than a focal one. Despite the well-known relation between BECTS and stage N2 sleep, the results of sleep studies have been diverse and have mainly focused on sleep cycles. The characteristics of sleep spindles in the interictal periods have not been studied well. METHODS: A retrospective study involving patients with BECTS who were admitted to the Gazi University, Faculty of Medicine, Department of Pediatric Neurology from January 2017 to October 2018 was conducted herein. Patients with BECTS and age-matched controls who had stage N2 sleep records of 10 min were enrolled for spindle amplitude (peak-to-peak difference in spindle voltage), frequency (number of waveforms per second), and duration and density (number of spindle bursts/minute of stage N2 sleep). RESULTS: A total of 30 children with BECTS and 20 age-matched healthy peers were enrolled in the study. There were no significant differences between the age and sex of the patients. Statistically significant lower mean values of the amplitude, and duration and density of the spindle activity were observed in patients with BECTS when compared to the controls (P: 0.034, P: 0.016, and 0.020, respectively). Additionally, the risk of epilepsy was found to increase by 1.9 %, by the decrease of the mean amplitude of the spindles by 1 mV when compared to control group. CONCLUSION: The interictal records of stage N2 sleep differed in the patients with BECTS when compared to the controls. Findings related to the stage N2 sleep of the present study may suggest a network problem involving the thalamus and thalamocortical pathways in patients with BECTS.