A large fraction of rare and severe neurodevelopmental disorders are caused by sporadic de novo variants. Epidemiological disease estimates are not available for the vast majority of these de novo monogenic neurodevelopmental disorders because of phenotypic heterogeneity and the absence of large-scale genomic screens. Yet, knowledge of disease incidence is important for clinicians and researchers to guide health policy planning. Here, we adjusted a statistical method based on genetic data to predict, for the first time, the incidences of 101 known de novo variant-associated neurodevelopmental disorders as well as 3106 putative monogenic disorders. Two corroboration analyses supported the validity of the calculated estimates. First, greater predicted gene-disorder incidences positively correlated with larger numbers of pathogenic variants collected from patient variant databases (Kendall’s τ = 0.093, P-value = 6.9 × 10−6). Second, for six of seven (86%) de novo variant associated monogenic disorders for which epidemiological estimates were available (SCN1A, SLC2A1, SALL1, TBX5, KCNQ2, and CDKL5), the predicted incidence estimates matched the reported estimates. We conclude that in the absence of epidemiological data, our catalogue of 3207 incidence estimates for disorders caused by de novo variants can guide patient advocacy groups, clinicians, researchers, and policymakers in strategic decision-making.
Understanding the exact molecular mechanisms involved in the etiology of epileptogenic pathologies with or without tumor activity is essential for improving treatment of drug-resistant focal epilepsy. Here, we characterize the landscape of somatic genetic variants in resected brain specimens from 474 individuals with drug-resistant focal epilepsy using deep whole-exome sequencing (>350×) and whole-genome genotyping. Across the exome, we observe a greater number of somatic single-nucleotide variants (SNV) in low-grade epilepsy-associated tumors (LEAT; 7.92 ± 5.65 SNV) than in brain tissue from malformations of cortical development (MCD; 6.11 ± 4 SNV) or hippocampal sclerosis (HS; 5.1 ± 3.04 SNV). Tumor tissues also had the largest number of likely pathogenic variant carrying cells. LEAT had the highest proportion of samples with one or more somatic copy number variants (CNV; 24.7%), followed by MCD (5.4%) and HS (4.1%). Recurring somatic whole chromosome duplications affecting Chromosome 7 (16.8%), chromosome 5 (10.9%), and chromosome 20 (9.9%) were observed among LEAT. For germline variant-associated MCD genes such as TSC2, DEPDC5, and PTEN, germline SNV were frequently identified within large loss of heterozygosity regions, supporting the recently proposed ‘second hit’ disease mechanism in these genes. We detect somatic variants in twelve established lesional epilepsy genes and demonstrate exome-wide statistical support for three of these in the etiology of LEAT (e.g., BRAF) and MCD (e.g., SLC35A2 and MTOR). We also identify novel significant associations for PTPN11 with LEAT and NRAS Q61 mutated protein with a complex MCD characterized by polymicrogyria and nodular heterotopia. The variants identified in NRAS are known from cancer studies to lead to hyperactivation of NRAS, which can be targeted pharmacologically. We identify large recurrent 1q21-q44 duplication including AKT3 in association with focal cortical dysplasia type 2a with hyaline astrocytic inclusions, another rare and possibly under-recognized brain lesion. The clinical genetic analyses showed that the numbers of somatic SNV across the exome and the fraction of affected cells were positively correlated with the age at seizure onset and surgery in individuals with LEAT. In summary, our comprehensive genetic screen sheds light on the genome-scale landscape of genetic variants in epileptic brain lesions, informs the design of gene panels for clinical diagnostic screening, and guides future directions for clinical implementation of epilepsy surgery genetics.
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