TAN Classifiers Based on Decomposable Distributions

The original publication is available at www.springerlink.comIn this paper we present several Bayesian algorithms for learning Tree Augmented Naive Bayes (TAN) models. We extend the results in Meila & Jaakkola (2000a) to TANs by proving that accepting a prior decomposable distribution over TAN's, we can compute the exact Bayesian model averaging over TAN structures and parameters in polynomial time. Furthermore, we prove that the k-maximum a posteriori (MAP) TAN structures can also be computed in polynomial time. We use these results to correct minor errors in Meila & Jaakkola (2000a) and to construct several TAN based classifiers provide consistently better predictions over Irvine datasets and artificially generated data than TAN based classifiers proposed in the literature.Peer reviewe

Perampanel as precision therapy in rare genetic epilepsies

OBJECTIVE: Perampanel, an antiseizure drug with α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor antagonist properties, may have a targeted effect in genetic epilepsies with overwhelming glutamate receptor activation. Epilepsies with loss of γ-aminobutyric acid inhibition (e.g., SCN1A), overactive excitatory neurons (e.g., SCN2A, SCN8A), and variants in glutamate receptors (e.g., GRIN2A) hold special interest. We aimed to collect data from a large rare genetic epilepsy cohort treated with perampanel, to detect possible subgroups with high efficacy. METHODS: This multicenter project was based on the framework of NETRE (Network for Therapy in Rare Epilepsies), a web of pediatric neurologists treating rare epilepsies. Retrospective data from patients with genetic epilepsies treated with perampanel were collected. Outcome measures were responder rate (50% seizure reduction), and percentage of seizure reduction after 3 months of treatment. Subgroups of etiologies with high efficacy were identified. RESULTS: A total of 137 patients with 79 different etiologies, aged 2 months to 61 years (mean = 15.48 ± 9.9 years), were enrolled. The mean dosage was 6.45 ± 2.47 mg, and treatment period was 2.0 ± 1.78 years (1.5 months-8 years). Sixty-two patients (44.9%) were treated for >2 years. Ninety-eight patients (71%) were responders, and 93 (67.4%) chose to continue therapy. The mean reduction in seizure frequency was 56.61% ± 34.36%. Sixty patients (43.5%) sustained >75% reduction in seizure frequency, including 38 (27.5%) with >90% reduction in seizure frequency. The following genes showed high treatment efficacy: SCN1A, GNAO1, PIGA, PCDH19, SYNGAP1, POLG1, POLG2, and NEU1. Eleven of 17 (64.7%) patients with Dravet syndrome due to an SCN1A pathogenic variant were responders to perampanel treatment; 35.3% of them had >90% seizure reduction. Other etiologies remarkable for >90% reduction in seizures were GNAO1 and PIGA. Fourteen patients had a continuous spike and wave during sleep electroencephalographic pattern, and in six subjects perampanel reduced epileptiform activity. SIGNIFICANCE: Perampanel demonstrated high safety and efficacy in patients with rare genetic epilepsies, especially in SCN1A, GNAO1, PIGA, PCDH19, SYNGAP1, CDKL5, NEU1, and POLG, suggesting a targeted effect related to glutamate transmission

Perampanel as Precision Therapy in Rare Genetic Epilepsies

Objective: Perampanel, an antiseizure drug with AMPA-receptor antagonist properties, may have a targeted effect in genetic epilepsies with overwhelming glutamate receptor activation. Special interest holds epilepsies with loss of GABA inhibition (e.g. SCN1A), overactive excitatory neurons (e.g. SCN2A, SCN8A ), and variants in glutamate receptors (e.g. GRIN2A). We aimed to collect data from a large rare genetic epilepsy cohort treated with perampanel, to detect possible subgroups with high efficacy. Methods: A multicenter project based on the framework of NETRE (Network for Therapy in Rare Epilepsies), a web of pediatric neurologists treating rare epilepsies. Retrospective data from patients with genetic epilepsies treated with perampanel was collected. Outcome measures were responder rate (50% seizure reduction), and percentage of seizure reduction after 3 months of treatment. Subgroups of etiologies with high efficacy were identified. Results: 137 patients, with 79 different etiologies, aged 2 months-61 years (mean 15.48±9.9) were enrolled. The mean dosage was 6.45±2.47 mg, and treatment period was 2.0±1.78 years (1.5 months-8 years). 62 patients (44.9%) were treated for >2 years. 98 patients (71%) were responders, and 93 (67.4%) chose to continue therapy. The mean reduction in seizure frequency was 56.61±34.36%. 60 patients (43.5%) sustained over 75% reduction in seizure frequency, including 38 (27.5%) with > 90% reduction in seizure frequency. The following genes showed high treatment efficacy: SCN1A, GNAO1, PIGA, PCDH19, SYNGAP1, POLG1, POLG2, NEU1. 11/17 (64.7%) of patients with SCN1A, 35.3% of which had over 90% seizure reduction. Other etiologies remarkable for over 90% reduction in seizures were GNAO1 and PIGA. 14 patients had a CSWS EEG pattern and in 6 subjects perampanel reduced epileptiform activity. Significance: Perampanel demonstrated high safety and efficacy in patients with rare genetic epilepsies, especially in SCN1A, GNAO1, PIGA, PCDH19, SYNGAP1, CDKL5, NEU1 and POLG, suggesting a targeted effect related to glutamate transmission

Whole-exome and HLA sequencing in Febrile infection-related epilepsy syndrome

Febrile infection-related epilepsy syndrome (FIRES) is a devastating epilepsy characterized by new-onset refractory status epilepticus with a prior febrile infection. We performed exome sequencing in 50 individuals with FIRES, including 27 patient–parent trios and 23 single probands, none of whom had pathogenic variants in established genes for epilepsies or neurodevelopmental disorders. We also performed HLA sequencing in 29 individuals with FIRES and 529 controls, which failed to identify prominent HLA alleles. The genetic architecture of FIRES is substantially different from other developmental and epileptic encephalopathies, and the underlying etiology remains elusive, requiring novel approaches to identify the underlying causative factors

GWAS meta-analysis of over 29,000 people with epilepsy identifies 26 risk loci and subtype-specific genetic architecture

Epilepsy is a highly heritable disorder affecting over 50 million people worldwide, of which about one-third are resistant to current treatments. Here we report a multi-ancestry genome-wide association study including 29,944 cases, stratified into three broad categories and seven subtypes of epilepsy, and 52,538 controls. We identify 26 genome-wide significant loci, 19 of which are specific to genetic generalized epilepsy (GGE). We implicate 29 likely causal genes underlying these 26 loci. SNP-based heritability analyses show that common variants explain between 39.6% and 90% of genetic risk for GGE and its subtypes. Subtype analysis revealed markedly different genetic architectures between focal and generalized epilepsies. Gene-set analyses of GGE signals implicate synaptic processes in both excitatory and inhibitory neurons in the brain. Prioritized candidate genes overlap with monogenic epilepsy genes and with targets of current antiseizure medications. Finally, we leverage our results to identify alternate drugs with predicted efficacy if repurposed for epilepsy treatment

Genome-wide identification and phenotypic characterization of seizure-associated copy number variations in 741,075 individuals

Copy number variants (CNV) are established risk factors for neurodevelopmental disorders with seizures or epilepsy. With the hypothesis that seizure disorders share genetic risk factors, we pooled CNV data from 10,590 individuals with seizure disorders, 16,109 individuals with clinically validated epilepsy, and 492,324 population controls and identified 25 genome-wide significant loci, 22 of which are novel for seizure disorders, such as deletions at 1p36.33, 1q44, 2p21-p16.3, 3q29, 8p23.3-p23.2, 9p24.3, 10q26.3, 15q11.2, 15q12-q13.1, 16p12.2, 17q21.31, duplications at 2q13, 9q34.3, 16p13.3, 17q12, 19p13.3, 20q13.33, and reciprocal CNVs at 16p11.2, and 22q11.21. Using genetic data from additional 248,751 individuals with 23 neuropsychiatric phenotypes, we explored the pleiotropy of these 25 loci. Finally, in a subset of individuals with epilepsy and detailed clinical data available, we performed phenome-wide association analyses between individual CNVs and clinical annotations categorized through the Human Phenotype Ontology (HPO). For six CNVs, we identified 19 significant associations with specific HPO terms and generated, for all CNVs, phenotype signatures across 17 clinical categories relevant for epileptologists. This is the most comprehensive investigation of CNVs in epilepsy and related seizure disorders, with potential implications for clinical practice