High Rate of Recurrent De Novo Mutations in Developmental and Epileptic Encephalopathies.

Developmental and epileptic encephalopathy (DEE) is a group of conditions characterized by the co-occurrence of epilepsy and intellectual disability (ID), typically with developmental plateauing or regression associated with frequent epileptiform activity. The cause of DEE remains unknown in the majority of cases. We performed whole-genome sequencing (WGS) in 197 individuals with unexplained DEE and pharmaco-resistant seizures and in their unaffected parents. We focused our attention on de novo mutations (DNMs) and identified candidate genes containing such variants. We sought to identify additional subjects with DNMs in these genes by performing targeted sequencing in another series of individuals with DEE and by mining various sequencing datasets. We also performed meta-analyses to document enrichment of DNMs in candidate genes by leveraging our WGS dataset with those of several DEE and ID series. By combining these strategies, we were able to provide a causal link between DEE and the following genes: NTRK2, GABRB2, CLTC, DHDDS, NUS1, RAB11A, GABBR2, and SNAP25. Overall, we established a molecular diagnosis in 63/197 (32%) individuals in our WGS series. The main cause of DEE in these individuals was de novo point mutations (53/63 solved cases), followed by inherited mutations (6/63 solved cases) and de novo CNVs (4/63 solved cases). De novo missense variants explained a larger proportion of individuals in our series than in other series that were primarily ascertained because of ID. Moreover, these DNMs were more frequently recurrent than those identified in ID series. These observations indicate that the genetic landscape of DEE might be different from that of ID without epilepsy.

When "bad" is good: How evaluative judgments eliminate the standard anchoring effect.

Early accounts of judgmental anchoring attribute the effect to a deliberate, but insufficient, adjustment process; more recent theories point to automatic, priming-based processes as the underlying cause. In this article we introduce a novel anchor assessment manipulation and a decompositional analysis of the standard anchoring effect to determine the extent to which anchoring is driven by automatic versus deliberate processes. Prior to providing a target estimate, participants indicated whether the target was greater or less than the anchor, or whether the anchor would make a good or bad target estimate. Contrary to predictions of priming-based accounts, the decomposition of the anchoring effect revealed that participants generally provided estimates consistent with their prior assessment; in particular, anchoring was eliminated when participants considered the anchor to be a bad target estimate. These findings challenge the view of anchoring as an inevitable bias of numerical judgment and indicate that people have significant control over how they manage numerical information in judgments under uncertainty. (PsycInfo Database Record (c) 2021 APA, all rights reserved).