Burden of variants for different CVS thresholds across epilepsy phenotypes with only individuals of European descent.

Odds ratios and p-value were calculated using a binomial logistic regression for variants of different Constraint Violation Score (CVS) thresholds. Lines represent 95% confidence intervals. Comparisons were made for cases and controls (A), Genetic Generalized Epilepsy (GGE) and controls (B), Non-Acquired Focal Epilepsy (NAFE) and controls (C) and GGE and NAFE (D). (TIF)</p

Accuracy of predictions’ directionality on known GTEx eQTLs.

Directionality accuracy was computed according to ExPecto’s predicted magnitude in natural log fold change. (TIF)</p

Burden of variants for different CVS thresholds across epilepsy phenotypes when using non-neurological tissues.

Odds ratios and p-value were calculated using a binomial logistic regression for variants of different Constraint Violation Score (CVS) thresholds. Lines represent 95% confidence intervals. Comparisons were made for cases and controls (A), Genetic Generalized Epilepsy (GGE) and controls (B), Non-Acquired Focal Epilepsy (NAFE) and controls (C) and GGE and NAFE (D). Tissues that were used are artery aorta, colon transverse and skin of body. (TIF)</p

UMAP of ethnicity for the epilepsy patients and controls.

The UMAP was made with ‘umap-learn v0.5.1’ and based on the first 5 principal components. (TIF)</p

STROBE statement—checklist of items that should be included in reports of observational studies.

STROBE statement—checklist of items that should be included in reports of observational studies.</p

List of variants included in the final analysis.

The discovery of new variants has leveled off in recent years in epilepsy studies, despite the use of very large cohorts. Consequently, most of the heritability is still unexplained. Rare non-coding variants have been largely ignored in studies on epilepsy, although non-coding single nucleotide variants can have a significant impact on gene expression. We had access to whole genome sequencing (WGS) from 247 epilepsy patients and 377 controls. To assess the functional impact of non-coding variants, ExPecto, a deep learning algorithm was used to predict expression change in brain tissues. We compared the burden of rare non-coding deleterious variants between cases and controls. Rare non-coding highly deleterious variants were significantly enriched in Genetic Generalized Epilepsy (GGE), but not in Non-Acquired Focal Epilepsy (NAFE) or all epilepsy cases when compared with controls. In this study we showed that rare non-coding deleterious variants are associated with epilepsy, specifically with GGE. Larger WGS epilepsy cohort will be needed to investigate those effects at a greater resolution. Nevertheless, we demonstrated the importance of studying non-coding regions in epilepsy, a disease where new discoveries are scarce.</div

Burden of variants for different CVS thresholds across epilepsy phenotypes.

Odds ratios and p-value were calculated using a binomial logistic regression for variants of different Constraint Violation Score (CVS) thresholds. Lines represent 95% confidence intervals. Comparisons were made for cases and controls (A), Genetic Generalized Epilepsy (GGE) and controls (B), Non-Acquired Focal Epilepsy (NAFE) and controls (C) and GGE and NAFE (D).</p

X-Linked <i>MTMR8</i> Diversity and Evolutionary History of Sub-Saharan Populations

<div><p>The genetic diversity within an 11 kb segment of the <i>MTMR8</i> gene in a sample of 111 sub-Saharan and 49 non-African X chromosomes was investigated to assess the early evolutionary history of sub-Saharan Africans and the out-of-Africa expansion. The analyses revealed a complex genetic structure of the Africans that contributed to the emergence of modern humans. We observed partitioning of two thirds of old lineages among southern, west/central and east African populations indicating ancient population stratification predating the out of Africa migration. Age estimates of these lineages, older than coalescence times of uniparentally inherited markers, raise the question whether contemporary humans originated from a single population or as an amalgamation of different populations separated by years of independent evolution, thus suggesting a greater antiquity of our species than generally assumed. While the oldest sub-Saharan lineages, ∼500 thousand years, are found among Khoe-San from southern-Africa, a distinct haplotype found among Biaka is likely due to admixture from an even older population. An East African population that gave rise to non-Africans underwent a selective sweep affecting the subcentromeric region where <i>MTMR8</i> is located. This and similar sweeps in four other regions of the X chromosome, documented in the literature, effectively reduced genetic diversity of non-African chromosomes and therefore may have exacerbated the effect of the demographic bottleneck usually ascribed to the out of Africa migration. Our data is suggestive, however, that a bottleneck, occurred in Africa before range expansion.</p></div

<i>MTMR8</i> segment haplotypes.

<p>The haplotype spans 11 Kb of the <i>MTMR8</i> gene, starting in intron 3 and ending in intron 5; the location of its polymorphic sites within the hg 19 genome reference sequence are shown in the third line. New alleles appear on the background of ancestral (chimpanzee) alleles, which are also shared with Neandertal and Denisova sequences, except for the polymorphic site 6 (highlighted in grey) where the derived allele is the same as that found in the Neandertal genome. The polymorphic sites 25 and 31, involving CpG-dinucleotides, are assumed to have mutated twice, indicated by asterisk, to create separate haplotypes 5 and 2, respectively (both found among Khoe-San).</p

Number of individuals for each phenotype.

The discovery of new variants has leveled off in recent years in epilepsy studies, despite the use of very large cohorts. Consequently, most of the heritability is still unexplained. Rare non-coding variants have been largely ignored in studies on epilepsy, although non-coding single nucleotide variants can have a significant impact on gene expression. We had access to whole genome sequencing (WGS) from 247 epilepsy patients and 377 controls. To assess the functional impact of non-coding variants, ExPecto, a deep learning algorithm was used to predict expression change in brain tissues. We compared the burden of rare non-coding deleterious variants between cases and controls. Rare non-coding highly deleterious variants were significantly enriched in Genetic Generalized Epilepsy (GGE), but not in Non-Acquired Focal Epilepsy (NAFE) or all epilepsy cases when compared with controls. In this study we showed that rare non-coding deleterious variants are associated with epilepsy, specifically with GGE. Larger WGS epilepsy cohort will be needed to investigate those effects at a greater resolution. Nevertheless, we demonstrated the importance of studying non-coding regions in epilepsy, a disease where new discoveries are scarce.</div