A comparison of machine learning classifiers for pediatric epilepsy using resting-state functional MRI latency data

Epilepsy affects 1 in 150 children under the age of 10 and is the most common chronic pediatric neurological condition; poor seizure control can irreversibly disrupt normal brain development. The present study compared the ability of different machine learning algorithms trained with resting-state functional MRI (rfMRI) latency data to detect epilepsy. Preoperative rfMRI and anatomical MRI scans were obtained for 63 patients with epilepsy and 259 healthy controls. The normal distribution of latency z-scores from the epilepsy and healthy control cohorts were analyzed for overlap in 36 seed regions. In these seed regions, overlap between the study cohorts ranged from 0.44-0.58. Machine learning features were extracted from latency z-score maps using principal component analysis. Extreme Gradient Boosting (XGBoost), Support Vector Machines (SVM), and Random Forest algorithms were trained with these features. Area under the receiver operating characteristics curve (AUC), accuracy, sensitivity, specificity and F1-scores were used to evaluate model performance. The XGBoost model outperformed all other models with a test AUC of 0.79, accuracy of 74%, specificity of 73%, and a sensitivity of 77%. The Random Forest model performed comparably to XGBoost across multiple metrics, but it had a test sensitivity of 31%. The SVM model did not perform \u3e70% in any of the test metrics. The XGBoost model had the highest sensitivity and accuracy for the detection of epilepsy. Development of machine learning algorithms trained with rfMRI latency data could provide an adjunctive method for the diagnosis and evaluation of epilepsy with the goal of enabling timely and appropriate care for patients

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

Splits in fruitfly Hox gene complexes

The homeotic genes are strikingly conserved between invertebrates and vertebrates. There is conservation, not only of the homeobox sequences, but also of their collinear order on the chromosome. The genes are found in clusters or 'complexes', and are arranged on the chromosome in the order of their function along the anteroposterior body axis (for review, see ref. 1). In the fruitfly Drosophila melanogaster, the homeotic genes are split into two separate clusters, the Antennapedia complex (ANTP-C) and the Bithorax complex (BX-C), which direct development of the anterior and posterior segments, respectively. We show that in Drosophila virilis, a closely related species, the homeotic genes are also in two clusters, but the split occurs within the BX-C. The existence of two independent splits in the Drosophila lineage suggests that these flies lack the molecular constraint responsible for the ordered clusters in other animals

An individual data-driven virtual resection model based on epileptic network dynamics in children with intractable epilepsy: a magnetoencephalography interictal activity application

Epilepsy surgery continues to be a recommended treatment for intractable (medication-resistant) epilepsy; however, 30–70% of epilepsy surgery patients can continue to have seizures. Surgical failures are often associated with incomplete resection or inaccurate localization of the epileptogenic zone. This retrospective study aims to improve surgical outcome through in silico testing of surgical hypotheses through a personalized computational neurosurgery model created from individualized patient’s magnetoencephalography recording and MRI. The framework assesses the extent of the epileptic network and evaluates underlying spike dynamics, resulting in identification of one single brain volume as a candidate for resection. Dynamic-locked networks were utilized for virtual cortical resection. This in silico protocol was tested in a cohort of 24 paediatric patients with focal drug-resistant epilepsy who underwent epilepsy surgery. Of 24 patients who were included in the analysis, 79% (19 of 24) of the models agreed with the patient's clinical surgery outcome and 21% (5 of 24) were considered as model failures (accuracy 0.79, sensitivity 0.77, specificity 0.82). Patients with unsuccessful surgery outcome typically showed a model cluster outside of the resected cavity, while those with successful surgery showed the cluster model within the cavity. Two of the model failures showed the cluster in the vicinity of the resected tissue and either a functional disconnection or lack of precision of the magnetoencephalography–MRI overlapping could explain the results. Two other cases were seizure free for 1 year but developed late recurrence. This is the first study that provides in silico personalized protocol for epilepsy surgery planning using magnetoencephalography spike network analysis. This model could provide complementary information to the traditional pre-surgical assessment methods and increase the proportion of patients achieving seizure-free outcome from surgery.Depto. de Radiología, Rehabilitación y FisioterapiaFac. de MedicinaTRUEpu

Indications for Inpatient Magnetoencephalography in Children - An Institution's Experience

Magnetoencephalography (MEG) is recognized as a valuable non-invasive clinical method for localization of the epileptogenic zone and critical functional areas, as part of a pre-surgical evaluation for patients with pharmaco-resistant epilepsy. MEG is also useful in localizing functional areas as part of pre-surgical planning for tumor resection. MEG is usually performed in an outpatient setting, as one part of an evaluation that can include a variety of other testing modalities including 3-Tesla MRI and inpatient video-electroencephalography monitoring. In some clinical circumstances, however, completion of the MEG as an inpatient can provide crucial ictal or interictal localization data during an ongoing inpatient evaluation, in order to expedite medical or surgical planning. Despite well-established clinical indications for performing MEG in general, there are no current reports that discuss indications or considerations for completion of MEG on an inpatient basis. We conducted a retrospective institutional review of all pediatric MEGs performed between January 2012 and December 2020, and identified 34 cases where MEG was completed as an inpatient. We then reviewed all relevant medical records to determine clinical history, all associated diagnostic procedures, and subsequent treatment plans including epilepsy surgery and post-surgical outcomes. In doing so, we were able to identify five indications for completing the MEG on an inpatient basis: (1) super-refractory status epilepticus (SRSE), (2) intractable epilepsy with frequent electroclinical seizures, and/or frequent or repeated episodes of status epilepticus, (3) intractable epilepsy with infrequent epileptiform discharges on EEG or outpatient MEG, or other special circumstances necessitating inpatient monitoring for successful and safe MEG data acquisition, (4) MEG mapping of eloquent cortex or interictal spike localization in the setting of tumor resection or other urgent neurosurgical intervention, and (5) international or long-distance patients, where outpatient MEG is not possible or practical. MEG contributed to surgical decision-making in the majority of our cases (32 of 34). Our clinical experience suggests that MEG should be considered on an inpatient basis in certain clinical circumstances, where MEG data can provide essential information regarding the localization of epileptogenic activity or eloquent cortex, and be used to develop a treatment plan for surgical management of children with complicated or intractable epilepsy

Mutations in Histone Acetylase Modifier BRPF1 Cause an Autosomal-Dominant Form of Intellectual Disability with Associated Ptosis

Intellectual disability (ID) is a common neurodevelopmental disorder exhibiting extreme genetic heterogeneity, and more than 500 genes have been implicated in Mendelian forms of ID. We performed exome sequencing in a large family affected by an autosomal-dominant form of mild syndromic ID with ptosis, growth retardation, and hypotonia, and we identified an inherited 2 bp deletion causing a frameshift in BRPF1 (c.1052_1053del) in five affected family members. BRPF1 encodes a protein modifier of two histone acetyltransferases associated with ID: KAT6A (also known as MOZ or MYST3) and KAT6B (MORF or MYST4). The mRNA transcript was not significantly reduced in affected fibroblasts and most likely produces a truncated protein (p.Val351Glyfs(∗)8). The protein variant shows an aberrant cellular location, loss of certain protein interactions, and decreased histone H3K23 acetylation. We identified BRPF1 deletions or point mutations in six additional individuals with a similar phenotype. Deletions of the 3p25 region, containing BRPF1 and SETD5, cause a defined ID syndrome where most of the clinical features are attributed to SETD5 deficiency. We compared the clinical symptoms of individuals carrying mutations or small deletions of BRPF1 alone or SETD5 alone with those of individuals with deletions encompassing both BRPF1 and SETD5. We conclude that both genes contribute to the phenotypic severity of 3p25 deletion syndrome but that some specific features, such as ptosis and blepharophimosis, are mostly driven by BRPF1 haploinsufficienc

Mutations in Histone Acetylase Modifier BRPF1 Cause an Autosomal-Dominant Form of Intellectual Disability with Associated Ptosis

Intellectual disability (ID) is a common neurodevelopmental disorder exhibiting extreme genetic heterogeneity, and more than 500 genes have been implicated in Mendelian forms of ID. We performed exome sequencing in a large family affected by an autosomal-dominant form of mild syndromic ID with ptosis, growth retardation, and hypotonia, and we identified an inherited 2 bp deletion causing a frameshift in BRPF1 (c.1052_1053del) in five affected family members. BRPF1 encodes a protein modifier of two histone acetyltransferases associated with ID: KAT6A (also known as MOZ or MYST3) and KAT6B (MORF or MYST4). The mRNA transcript was not significantly reduced in affected fibroblasts and most likely produces a truncated protein (p.Val351Glyfs*8). The protein variant shows an aberrant cellular location, loss of certain protein interactions, and decreased histone H3K23 acetylation. We identified BRPF1 deletions or point mutations in six additional individuals with a similar phenotype. Deletions of the 3p25 region, containing BRPF1 and SETD5, cause a defined ID syndrome where most of the clinical features are attributed to SETD5 deficiency. We compared the clinical symptoms of individuals carrying mutations or small deletions of BRPF1 alone or SETD5 alone with those of individuals with deletions encompassing both BRPF1 and SETD5. We conclude that both genes contribute to the phenotypic severity of 3p25 deletion syndrome but that some specific features, such as ptosis and blepharophimosis, are mostly driven by BRPF1 haploinsufficiency