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An understanding of how heterozygous loss-of-function mutations in autism spectrum disorder (ASD) risk genes, such as TBR1, contribute to ASD remains elusive. Conditional Tbr1 deletion during late mouse gestation in cortical layer 6 neurons (Tbr1layer6 mutants) provides novel insights into its function, including dendritic patterning, synaptogenesis, and cell-intrinsic physiology. These phenotypes occur in heterozygotes, providing insights into mechanisms that may underlie ASD pathophysiology. Restoring expression of Wnt7b largely rescues the synaptic deficit in Tbr1layer6 mutant neurons. Furthermore, Tbr1layer6 heterozygotes have increased anxiety-like behavior, a phenotype seen ASD. Integrating TBR1 chromatin immunoprecipitation sequencing (ChIP-seq) and RNA sequencing (RNA-seq) data from layer 6 neurons and activity of TBR1-bound candidate enhancers provides evidence for how TBR1 regulates layer 6 properties. Moreover, several putative TBR1 targets are ASD risk genes, placing TBR1 in a central position both for ASD risk and for regulating transcriptional circuits that control multiple steps in layer 6 development essential for the assembly of neural circuits.

We previously established the contribution of de novo damaging sequence variants to Tourette disorder (TD) through whole-exome sequencing of 511 trios. Here, we sequence an additional 291 TD trios and analyze the combined set of 802 trios. We observe an overrepresentation of de novo damaging variants in simplex, but not multiplex, families; we identify a high-confidence TD risk gene, CELSR3 (cadherin EGF LAG seven-pass G-type receptor 3); we find that the genes mutated in TD patients are enriched for those related to cell polarity, suggesting a common pathway underlying pathobiology; and we confirm a statistically significant excess of de novo copy number variants in TD. Finally, we identify significant overlap of de novo sequence variants between TD and obsessive-compulsive disorder and de novo copy number variants between TD and autism spectrum disorder, consistent with shared genetic risk.

Genomic association studies of common or rare protein-coding variation have established robust statistical approaches to account for multiple testing. Here we present a comparable framework to evaluate rare and de novo noncoding single-nucleotide variants, insertion/deletions, and all classes of structural variation from whole-genome sequencing (WGS). Integrating genomic annotations at the level of nucleotides, genes, and regulatory regions, we define 51,801 annotation categories. Analyses of 519 autism spectrum disorder families did not identify association with any categories after correction for 4,123 effective tests. Without appropriate correction, biologically plausible associations are observed in both cases and controls. Despite excluding previously identified gene-disrupting mutations, coding regions still exhibited the strongest associations. Thus, in autism, the contribution of de novo noncoding variation is probably modest in comparison to that of de novo coding variants. Robust results from future WGS studies will require large cohorts and comprehensive analytical strategies that consider the substantial multiple-testing burden.

Whole-exome sequencing (WES) and de novo variant detection have proven a powerful approach to gene discovery in complex neurodevelopmental disorders. We have completed WES of 325 Tourette disorder trios from the Tourette International Collaborative Genetics cohort and a replication sample of 186 trios from the Tourette Syndrome Association International Consortium on Genetics (511 total). We observe strong and consistent evidence for the contribution of de novo likely gene-disrupting (LGD) variants (rate ratio [RR] 2.32, p = 0.002). Additionally, de novo damaging variants (LGD and probably damaging missense) are overrepresented in probands (RR 1.37, p = 0.003). We identify four likely risk genes with multiple de novo damaging variants in unrelated probands: WWC1 (WW and C2 domain containing 1), CELSR3 (Cadherin EGF LAG seven-pass G-type receptor 3), NIPBL (Nipped-B-like), and FN1 (fibronectin 1). Overall, we estimate that de novo damaging variants in approximately 400 genes contribute risk in 12% of clinical cases. VIDEO ABSTRACT.

Analysis of de novo CNVs (dnCNVs) from the full Simons Simplex Collection (SSC) (N = 2,591 families) replicates prior findings of strong association with autism spectrum disorders (ASDs) and confirms six risk loci (1q21.1, 3q29, 7q11.23, 16p11.2, 15q11.2-13, and 22q11.2). The addition of published CNV data from the Autism Genome Project (AGP) and exome sequencing data from the SSC and the Autism Sequencing Consortium (ASC) shows that genes within small de novo deletions, but not within large dnCNVs, significantly overlap the high-effect risk genes identified by sequencing. Alternatively, large dnCNVs are found likely to contain multiple modest-effect risk genes. Overall, we find strong evidence that de novo mutations are associated with ASD apart from the risk for intellectual disability. Extending the transmission and de novo association test (TADA) to include small de novo deletions reveals 71 ASD risk loci, including 6 CNV regions (noted above) and 65 risk genes (FDR ≤ 0.1).

Whole-exome sequencing (WES) studies have demonstrated the contribution of de novo loss-of-function single-nucleotide variants (SNVs) to autism spectrum disorder (ASD). However, challenges in the reliable detection of de novo insertions and deletions (indels) have limited inclusion of these variants in prior analyses. By applying a robust indel detection method to WES data from 787 ASD families (2,963 individuals), we demonstrate that de novo frameshift indels contribute to ASD risk (OR = 1.6; 95% CI = 1.0-2.7; p = 0.03), are more common in female probands (p = 0.02), are enriched among genes encoding FMRP targets (p = 6 × 10(-9)), and arise predominantly on the paternal chromosome (p < 0.001). On the basis of mutation rates in probands versus unaffected siblings, we conclude that de novo frameshift indels contribute to risk in approximately 3% of individuals with ASD. Finally, by observing clustering of mutations in unrelated probands, we uncover two ASD-associated genes: KMT2E (MLL5), a chromatin regulator, and RIMS1, a regulator of synaptic vesicle release.

The genomic analyses of pediatric acute lymphoblastic leukemia (ALL) subtypes, particularly T-cell and B-cell lineages, have been pivotal in identifying potential therapeutic targets. Typical genomic analyses have directed attention toward the most commonly mutated genes. However, assessing the contribution of mutations to cancer phenotypes is crucial. Therefore, we estimated the cancer effects (scaled selection coefficients) for somatic substitutions in T-cell and B-cell cohorts, revealing key insights into mutation contributions. Cancer effects for well-known, frequently mutated genes like NRAS and KRAS in B-ALL were high, which underscores their importance as therapeutic targets. However, less frequently mutated genes IL7R, XBP1, and TOX also demonstrated high cancer effects, suggesting pivotal roles in the development of leukemia when present. In T-ALL, KRAS and NRAS are less frequently mutated than in B-ALL. However, their cancer effects when present are high in both subtypes. Mutations in PIK3R1 and RPL10 were not at high prevalence, yet exhibited some of the highest cancer effects in individual T-cell ALL patients. Even CDKN2A, with a low prevalence and relatively modest cancer effect, is potentially highly relevant for the epistatic effects that its mutated form exerts on other mutations. Prioritizing investigation into these moderately frequent but potentially high-impact targets not only presents novel personalized therapeutic opportunities but also enhances the understanding of disease mechanisms and advances precision therapeutics for pediatric ALL. [ABSTRACT FROM AUTHOR]

Cross-species evidence suggests that the ability to exert control over a stressor is a key dimension of stress exposure that may sensitize frontostriatal-amygdala circuitry to promote more adaptive responses to subsequent stressors. The present study examined neural correlates of stressor controllability in young adults. Participants (N = 56; M age = 23.74, range = 18–30 years) completed either the controllable or uncontrollable stress condition of the first of two novel stressor controllability tasks during functional magnetic resonance imaging (fMRI) acquisition. Participants in the uncontrollable stress condition were yoked to age- and sex-matched participants in the controllable stress condition. All participants were subsequently exposed to uncontrollable stress in the second task, which is the focus of fMRI analyses reported here. A whole-brain searchlight classification analysis revealed that patterns of activity in the right dorsal anterior insula (dAI) during subsequent exposure to uncontrollable stress could be used to classify participants' initial exposure to either controllable or uncontrollable stress with a peak of 73% accuracy. Previous experience of exerting control over a stressor may change the computations performed within the right dAI during subsequent stress exposure, shedding further light on the neural underpinnings of stressor controllability. [ABSTRACT FROM AUTHOR]

Key theoretical frameworks have proposed that examining the impact of exposure to specific dimensions of stress at specific developmental periods is likely to yield important insight into processes of risk and resilience. Utilizing a sample of N = 549 young adults who provided a detailed retrospective history of their lifetime exposure to numerous dimensions of traumatic stress and ratings of their current trauma-related symptomatology via completion of an online survey, here we test whether an individual's perception of their lifetime stress as either controllable or predictable buffered the impact of exposure on trauma-related symptomatology assessed in adulthood. Further, we tested whether this moderation effect differed when evaluated in the context of early childhood, middle childhood, adolescence, and young adulthood stress. Consistent with hypotheses, results highlight both stressor controllability and stressor predictability as buffering the impact of traumatic stress exposure on trauma-related symptomatology and suggest that the potency of this buffering effect varies across unique developmental periods. Leveraging dimensional ratings of lifetime stress exposure to probe heterogeneity in outcomes following stress - and, critically, considering interactions between dimensions of exposure and the developmental period when stress occurred - is likely to yield increased understanding of risk and resilience following traumatic stress.

Recent advances in the dimensional assessment of traumatic stress have initiated research examining correlates of exposure to specific features of stress. However, existing tools require intensive, in-person, clinician administration to generate the rich phenotypic data required for such analyses. These approaches are time consuming, costly, and substantially restrict the degree to which assessment tools can be disseminated in large-scale studies, constraining the refinement of existing dimensional models of early adversity. Here, we present an electronic adaptation of the Dimensional Inventory of Stress and Trauma Across the Lifespan (DISTAL), called the DISTAL-Electronic (DISTAL-E), present descriptive statistics drawn from a large sample of N = 500 young adult participants who completed the novel measure, and provide information about its psychometric properties. Results suggest that the DISTAL-E adequately assesses the following dimensional indices of traumatic stress exposure: type, chronicity, age of onset, severity, proximity, caregiver involvement, controllability, predictability, betrayal, threat, and deprivation and that it has excellent content and convergent validity and good test-retest reliability over a 7-11 day period. Although the development of the DISTAL-E facilitates the broad assessment of dimensions of stress exposure in large-scale datasets and has the potential to increase access to stress-related research to a wider group of participants who may not be able to access clinical research in traditional, in-person, clinic-based settings, the generalizability of results of the present study may be constrained by the fact that study participants were primarily White, educated, and with middle-to-high income. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Somatic nucleotide mutations can contribute to cancer cell survival, proliferation, and pathogenesis. Although research has focused on identifying which mutations are "drivers" versus "passengers," quantifying the proliferative effects of specific variants within clinically relevant contexts could reveal novel aspects of cancer biology. To enable researchers to estimate these cancer effects, we developed cancereffectsizeR, an R package that organizes somatic variant data, facilitates mutational signature analysis, calculates site-specific mutation rates, and tests models of selection. Built-in models support effect estimation from single nucleotides to genes. Users can also estimate epistatic effects between paired sets of variants, or design and test custom models. The utility of cancer effect was validated by showing in a pan-cancer dataset that somatic variants classified as likely pathogenic or pathogenic in ClinVar exhibit substantially higher effects than most other variants. Indeed, cancer effect was a better predictor of pathogenic status than variant prevalence or functional impact scores. In addition, the application of this approach toward pairwise epistasis in lung adenocarcinoma showed that driver mutations in BRAF, EGFR, or KRAS typically reduce selection for alterations in the other two genes. Companion reference data packages support analyses using the hg19 or hg38 human genome builds, and a reference data builder enables use with any species or custom genome build with available genomic and transcriptomic data. A reference manual, tutorial, and public source code repository are available at https://townsend-lab-yale.github.io/cancereffectsizeR. Comprehensive estimation of cancer effects of somatic mutations can provide insights into oncogenic trajectories, with implications for cancer prognosis and treatment., Significance: An R package provides streamlined, customizable estimation of underlying nucleotide mutation rates and of the oncogenic and epistatic effects of mutations in cancer cohorts., (©2022 The Authors; Published by the American Association for Cancer Research.)