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Memory consolidation involves discrete patterns of transcriptional events in the hippocampus. Despite the emergence of single-cell transcriptomic profiling techniques, defining learning-responsive gene expression across subregions of the hippocampus has remained challenging. Here, we utilized unbiased spatial sequencing to elucidate transcriptome-wide changes in gene expression in the hippocampus following learning, enabling us to define molecular signatures unique to each hippocampal subregion. We find that each subregion of the hippocampus exhibits distinct yet overlapping transcriptomic signatures. Although the CA1 region exhibited increased expression of genes related to transcriptional regulation, the DG showed upregulation of genes associated with protein folding. We demonstrate the functional relevance of subregion-specific gene expression by genetic manipulation of a transcription factor selectively in the CA1 hippocampal subregion, leading to long-term memory deficits. This work demonstrates the power of using spatial molecular approaches to reveal transcriptional events during memory consolidation.

Funding: Royal Society - UF150663, RGF\EA\180141; Wellcome Trust - 217065/Z/19/Z; H2020 European Research Council - 694189; NWO - 451-15-017; National Health and Medical Research Council - 1173896; Canadian Institute for Health Research - MOP-133440. Handedness has been studied for association with language-related disorders because of its link with language hemispheric dominance. No clear pattern has emerged, possibly because of small samples, publication bias, and heterogeneous criteria across studies. Non-right-handedness (NRH) frequency was assessed in N = 2503 cases with reading and/or language impairment and N = 4316 sex-matched controls identified from 10 distinct cohorts (age range 6–19 years old; European ethnicity) using a priori set criteria. A meta-analysis (Ncases = 1994) showed elevated NRH % in individuals with language/reading impairment compared with controls (OR = 1.21, CI = 1.06–1.39, p = .01). The association between reading/language impairments and NRH could result from shared pathways underlying brain lateralization, handedness, and cognitive functions. Publisher PDF

Objective To examine overlap and divergence of symptomatology in Autism Spectrum Disorder (ASD) with and without co-occurring Attention/Deficit Hyperactivity Disorder (ADHD) and/or Anxiety Disorder by age and sex. Method Participants included 25,078 individuals registered in the SPARK cohort, age 6-18 years. SPARK participation includes online consent and registration, as well as parent-reported ASD, ADHD, and Anxiety Disorder diagnoses, developmental, medical, and intervention history, and standardized rating scales. Individuals with ASD, ASD + ADHD, ASD + Anxiety, or ASD + ADHD + Anxiety were compared on measures assessing social communication, restricted and repetitive behaviors (RRBs), and motor functioning, and differences between male and female profiles were examined. Results Significant differences in symptom presentation between females/males, school-age/adolescent individuals, and by co-occurring conditions (ASD/ADHD/Anxiety) are apparent, and the impact of co-occurring conditions differed by age and sex. Most notably, school-age femaleswith ASD without co-occurring conditions present with significantly fewer concerns about social communication skills and have better motor skills, but have more prominent RRBs as compared to same-aged males with ASD alone; co-occurring conditions were associated with increased social communication problems and motor concerns, most consistently for school-age females. Conclusions School-age females with ASD are at highest risk for underestimation of autism-related symptoms, including underestimation of symptoms beyond core ASD features (motor skills). Further, across ages, particular consideration should be given when probing for social communication symptoms, RRBs, and motor skills in females with ASD alone, as well as with co-occurring ADHD and/or Anxiety. For females with co-occurring symptoms and conditions, use of symptom-specific measures in lieu of omnibus measures should be considered.

The complexity of autism’s phenotypic spectra is well-known, yet most genetic research uses case-control status as the target trait. It is undetermined if autistic symptom domain severity underlying this heterogeneity is heritable and pleiotropic with other psychiatric and behavior traits in the same manner as autism case-control status. In N = 6064 autistic children in the SPARK cohort, we investigated the common genetic properties of twelve subscales from three clinical autism instruments measuring autistic traits: the Social Communication Questionnaire (SCQ), the Repetitive Behavior Scale-Revised (RBS-R), and the Developmental Coordination Disorder Questionnaire (DCDQ). Educational attainment polygenic scores (PGS) were significantly negatively correlated with eleven subscales, while ADHD and major depression PGS were positively correlated with ten and eight of the autism subscales, respectively. Loneliness and neuroticism PGS were also positively correlated with many subscales. Significant PGS by sex interactions were found—surprisingly, the autism case-control PGS was negatively correlated in females and had no strong correlation in males. SNP-heritability of the DCDQ subscales ranged from 0.04 to 0.08, RBS-R subscales ranged from 0.09 to 0.24, and SCQ subscales ranged from 0 to 0.12. GWAS in SPARK followed by estimation of polygenic scores (PGS) in the typically-developing ABCD cohort (N = 5285), revealed significant associations of RBS-R subscale PGS with autism-related behavioral traits, with several subscale PGS more strongly correlated than the autism case-control PGS. Overall, our analyses suggest that the clinical autism subscale traits show variability in SNP-heritability, PGS associations, and significant PGS by sex interactions, underscoring the heterogeneity in autistic traits at a genetic level. Furthermore, of the three instruments investigated, the RBS-R shows the greatest evidence of genetic signal in both (1) autistic samples (greater heritability) and (2) general population samples (strongest PGS associations).

Neuronal activity-dependent transcription directs molecular processes that regulate synaptic plasticity, brain circuit development, behavioral adaptation, and long-term memory. Single cell RNA-sequencing technologies (scRNAseq) are rapidly developing and allow for the interrogation of activity-dependent transcription at cellular resolution. Here, we present NEUROeSTIMator, a deep learning model that integrates transcriptomic signals to estimate neuronal activation in a way that captures electrophysiological features and is robust against differences in species, cell type, and brain region. We demonstrate this method’s ability to accurately detect neuronal activity in previously published studies of single cell activity-induced gene expression. Further, we applied our model in a spatial transcriptomic study to identify unique patterns of learning-induced activity across different brain regions. Altogether, our findings establish NEUROeSTIMator as a powerful and broadly applicable tool for measuring neuronal activation, whether as a critical covariate or a primary readout of interest.

Worldwide, the majority of people prefer using the right hand for most motor tasks, including writing. Because of the link between handedness and language hemispheric dominance, handedness has been studied for association with language-related disorders. No clear pattern has emerged from these studies, and inconsistencies have been attributed to small sample sizes, publication bias, and heterogeneous criteria for the definition of handedness and disorders.Here, we assessed the frequency of non-right handedness (NRH) in 10 distinct cohorts not analysed before in this context. We identified N = 2,499 cases with reading and/or language impairment and N = 4,428 unique controls on the basis of a priori defined criteria. Overall, NRH was more frequent and more variable in the cases (8-24%) than in the controls (8-16%). Meta-analysis in the eight cohorts that met the inclusion criteria showed an increase of NRH in individuals with language/reading impairment compared to controls (OR = 1.21, CI = 1.06 - 1.37, p = 0.009). No moderator effects were detected for type of cohort (epidemiological versus clinical) and type of impairment (language versus reading). Our results support a genuine but modest association between NRH and reading and language impairments, suggesting shared biological pathways underlying brain lateralization, handedness, and cognitive functions.

Autism with co-occurring exceptional cognitive ability is often accompanied by severe internalizing symptoms and feelings of inadequacy. Whether cognitive ability also translates into greater risk for suicidal ideation is unclear. To investigate this urgent question, we examined two samples of high-ability individuals with autism for factors that were predictive of suicidal ideation. In the first sample (N=1,074 individuals seen at a clinic specializing in gifted/talented youth), we observed a striking excess of parent-reported suicidal ideation in autistic individuals with IQ≥120 (OR=5.9, p = 0.0007). In separate sample of N=1,983 SPARK participants, we confirmed higher rates of suicidal thoughts compared to non-autistic children from the ABCD cohort (OR=6.8, p < 2.2 × 10−16), and further that autistic children with suicidal thoughts had significantly higher cognitive ability (p < 2.2 × 10−16) than those without. Elevated polygenic scores (PGS) for cognitive performance were associated with increased suicidal thoughts (Z = 2.16, p = 0.03), with PGS for educational attainment trending in the same direction (Z = 1.4, p = 0.17). Notably, similar results were found in parents of these autistic youth, where higher PGS for educational attainment was associated with increasing thoughts of suicide (Z=2.28, p=0.02). Taken together, these results suggest that on a phenotypic and genetic level, increasing cognitive ability is an unexpected risk factor for suicidal ideation in individuals diagnosed with, or at risk for autism.

Autism with co-occurring exceptional cognitive ability is often accompanied by severe internalizing symptoms and feelings of inadequacy. Whether cognitive ability also translates into greater risk for suicidal ideation is unclear. To investigate this urgent question, we examined two samples of high-ability autistic individuals for factors that were predictive of suicidal ideation. In the first sample (N = 1,074 individuals seen at a clinic specializing in gifted/talented youth), we observed a striking excess of parent-reported suicidal ideation in autistic individuals with IQ ≥ 120 (Odds Ratio = 5.9, p=0.0007). In a separate sample of SPARK participants, we confirmed higher rates of suicidal thoughts compared to non-autistic children from the ABCD cohort (combined N = 16,049, Odds Ratio = 6.8, p2.2e-16), and further that autistic children with suicidal thoughts had significantly higher cognitive ability (p2.2e-16) than those without. Elevated polygenic scores (PGS) for cognitive performance were associated with increased suicidal thoughts (N = 1,983, Z=2.16,p=0.03), with PGS for educational attainment trending in the same direction (Z=1.4,p=0.17). Notably, similar results were found in parents of these autistic youth, where higher PGS for educational attainment was associated with increasing thoughts of suicide (N = 736, Z=2.28,p=0.02). Taken together, these results suggest that on a phenotypic and genetic level, increasing cognitive ability is an unexpected risk factor for suicidal ideation in individuals diagnosed with, or at risk for autism.

Gender diverse individuals are at higher risk for mental health problems. What remains unclear is whether this increased risk is attributable to environmental stressors (e.g., minority stress), innate pleiotropic effects on gender diversity and mental health, or gene-by-environment interactions. Here, we present two studies (N = 5,388 and N = 696, all from the SPARK autism cohort) investigating these questions. First, N = 696 independent adults (58% autistic) provided thorough information on their gender identities and expression using the Gender Self Report (GSR), a novel assessment for the continuous, multidimensional characterization of gender diversity. We tested 20 behavioral polygenic scores for association with the two GSR dimensions: Binary Gender Diversity (degree of identification with the gender opposite that implied by sex designated at birth) and Nonbinary Gender Diversity (degree of identification with a gender that is neither man/male nor woman/female). We found no evidence of association between gender diversity and polygenic risk for adult-onset psychiatric conditions (major depression, bipolar disorder, schizophrenia). Strikingly, we instead found that both gender diversity dimensions were positively associated with the cognitive performance polygenic score (Binaryρ= 0.09,p= 0.02 and Nonbinaryρ= 0.11,p= 0.003). We also found Binary Gender Diversity to be positively associated with polygenic scores for autism (ρ= 0.08,p= 0.045) and non-heterosexual sexual behavior (ρ= 0.09,p= 0.02). Additionally, we tested for interactions effects and found no association between increasing gender diversity and poorer mental health outcomes in the subsample with low genetic risk for these neuropsychiatric conditions. Only in the subsample with high genetic risk for major depression or schizophrenia did we observe a significant relationship between gender diversity and poor mental health outcomes. In the second study (N = 5,388), we used self-reported categorical gender identity and found that, in agreement with our first study, transgender and gender nonbinary individuals had significantly higher polygenic scores for cognitive performance (t= 3.90,p= 0.0001) and non-heterosexual sexual behavior (t= 2.0,p= 0.04), as well as risky behavior (t= 2.10,p= 0.04). In summary, our findings demonstrate gender diversity to have pleiotropic relationships with adaptive traits such as cognitive performance, implicate the environment (e.g., minority stress) as a key factor interacting with polygenic risk to generate poor mental health outcomes, and challenge a pathologizing view of gender diversity.

1AbstractLanguage is the foundation of human social interaction, education, commerce, and mental health. The heritability underlying language is well-established, but our understanding of its genetic basis — and how it compares to that of more general cognitive functioning— remains unclear. To illuminate the language-specific contributions of rare and common variation, we performed whole genome sequencing in N=350 individuals who were characterized with seven latent language phenotypes. We conducted region, gene, and gene set-based analyses to identify patterns of genetic burden that disproportionately explained these language factors compared to nonverbal IQ. These analyses identified language-specific associations with NDST4 and GRIN2A, with common variant replication of NDST4 in an independent sample. Rare variant burden analyses revealed three distinct functional profiles of genes that make contributions to language: a prenatally-expressed profile with enrichment for chromatin modifiers and broad neuropsychiatric risk, a postnatal cortex-expressed profile with enrichment for ion channels and cognitive/neuropsychiatric associations, and a postnatal, subcortically-expressed profile with enrichment of cilium-related proteins. Compared to a profile strongly associated with nonverbal IQ, these language-related profiles showed less intolerance to damaging variation, suggesting that the selection patterns acting on language differ from patterns linked to intellectual disability. Furthermore, we found evidence that rare potential reversions to an ancestral state are associated with poorer overall specific language ability. The breadth of these variant, gene, and profile associations suggest that while human-specific selection patterns do contribute to language, these are distributed broadly across numerous key mechanisms and developmental periods, and not in one or a few “language genes”.

The use of spoken and written language is a capacity that is unique to humans. Individual differences in reading- and language-related skills are influenced by genetic variation, with twin-based heritability estimates of 30-80%, depending on the trait. The relevant genetic architecture is complex, heterogeneous, and multifactorial, and yet to be investigated with well-powered studies. Here, we present a multicohort genome-wide association study (GWAS) of five traits assessed individually using psychometric measures: word reading, nonword reading, spelling, phoneme awareness, and nonword repetition, with total sample sizes ranging from 13,633 to 33,959 participants aged 5-26 years (12,411 to 27,180 for those with European ancestry, defined by principal component analyses). We identified a genome-wide significant association with word reading (rs11208009, p=1.098 × 10−8) independent of known loci associated with intelligence or educational attainment. All five reading-/language-related traits had robust SNP-heritability estimates (0.13–0.26), and genetic correlations between them were modest to high. Using genomic structural equation modelling, we found evidence for a shared genetic factor explaining the majority of variation in word and nonword reading, spelling, and phoneme awareness, which only partially overlapped with genetic variation contributing to nonword repetition, intelligence and educational attainment. A multivariate GWAS was performed to jointly analyse word and nonword reading, spelling, and phoneme awareness, maximizing power for follow-up investigation. Genetic correlation analysis of multivariate GWAS results with neuroimaging traits identified association with cortical surface area of the banks of the left superior temporal sulcus, a brain region with known links to processing of spoken and written language. Analysis of evolutionary annotations on the lineage that led to modern humans showed enriched heritability in regions depleted of Neanderthal variants. Together, these results provide new avenues for deciphering the biological underpinnings of these uniquely human traits.

BackgroundHigh cognitive ability is an almost universally positive prognostic indicator in the context of neurodevelopmental, neuropsychiatric, and neurodegenerative conditions. However, “twice-exceptional” individuals, those who demonstrate exceptionally high cognitive ability (gifted) and exhibit profound behavioral and mental health challenges, are a striking exception to this rule.MethodsWe digitized the clinical records of N=1,074 clients from a US-based specialty clinic serving gifted students. This included a broad array of diagnostic, cognitive, achievement, and behavioral data, including self, teacher, and parent reported items. We conducted both hypothesis-driven and unsupervised learning analyses to 1) identify characteristics whose association with full-scale IQ (FSIQ) was dependent on autism diagnosis and 2) identify cognitive archetypes associated with autism diagnosis and related behaviors. We tested the generalization of our findings using data from the SPARK (N=17,634) and ABCD studies (N=10,602).ResultsAutistic individuals with IQ >= 120 were nearly 15 times more likely to enter adulthood undiagnosed compared to lower-IQ (IQ < 70) counterparts. Self-reported sense of inadequacy was most strongly associated with increasing FSIQ specifically among autistic clients (beta=0.3, 95% CI:[0.15,0.45], p=7.1×10−5). Similarly, self, parent, and teacher reports of anxiety increased with FSIQ (all pConclusionsOur results suggest that autistic individuals with exceptional ability are underserved and suffer disproportionately from high anxiety and low self-worth. In addition, elevated IQ with a significant PS/VC discrepancy appears to be a clinically and genetically meaningful biotype linked to autism.

The mechanisms underlying memory loss associated with Alzheimer’s disease and related dementias (ADRD) remain unclear, and no effective treatments exist. Fundamental studies have shown that a set of transcriptional regulatory proteins of the nuclear receptor 4a (Nr4a) family serve as molecular switches for long-term memory. Here, we show that Nr4a proteins regulate the transcription of a group of genes encoding chaperones that localize to the endoplasmic reticulum (ER), which function to traffic plasticity-related proteins to the cell surface during long lasting forms of synaptic plasticity and memory. Nr4a transcription factors and ER chaperones are linked to ADRD in human samples as well as mouse models, and overexpressing Nr4a1 or the ER chaperone Hspa5 ameliorates the long-term memory deficits in a tau-based mouse model of ADRD, pointing towards novel therapeutic approaches for treating memory loss. Thus, our findings establish protein folding in the ER as a novel molecular concept underlying long-term memory, providing new insights into the mechanistic basis of cognitive deficits in dementia.One-Sentence SummaryMolecular approaches establish protein folding in the endoplasmic reticulum as a novel molecular concept underlying synaptic plasticity and memory, serving as a switch to regulate protein folding and trafficking, and driving cognitive deficits in neurodegenerative disorders.

Despite the known heritable nature of autism spectrum disorder (ASD), studies have primarily identified risk genes with de novo variants (DNVs). To capture the full spectrum of ASD genetic risk, we performed a two-stage analysis of rare de novo and inherited coding variants in 42,607 ASD cases, including 35,130 new cases recruited online by SPARK. In the first stage, we analyzed 19,843 cases with one or both biological parents and found that known ASD or neurodevelopmental disorder (NDD) risk genes explain nearly 70% of the genetic burden conferred by DNVs. In contrast, less than 20% of genetic risk conferred by rare inherited loss-of-function (LoF) variants are explained by known ASD/NDD genes. We selected 404 genes based on the first stage of analysis and performed a meta-analysis with an additional 22,764 cases and 236,000 population controls. We identified 60 genes with exome-wide significance (p < 2.5e-6), including five new risk genes (NAV3, ITSN1, MARK2, SCAF1, and HNRNPUL2). The association of NAV3 with ASD risk is entirely driven by rare inherited LoFs variants, with an average relative risk of 4, consistent with moderate effect. ASD individuals with LoF variants in the four moderate risk genes (NAV3, ITSN1, SCAF1, and HNRNPUL2, n = 95) have less cognitive impairment compared to 129 ASD individuals with LoF variants in well-established, highly penetrant ASD risk genes (CHD8, SCN2A, ADNP, FOXP1, SHANK3) (59% vs. 88%, p= 1.9e-06). These findings will guide future gene discovery efforts and suggest that much larger numbers of ASD cases and controls are needed to identify additional genes that confer moderate risk of ASD through rare, inherited variants.

To capture the full spectrum of genetic risk for autism, we performed a two-stage analysis of rare de novo and inherited coding variants in 42,607 autism cases, including 35,130 new cases recruited online by SPARK. We identified 60 genes with exome-wide significance (P 2.5 × 10

Significance COVID-19 is taking a major toll on personal health, healthcare systems, and the global economy. With three betacoronavirus epidemics in less than 20 y, there is an urgent need for therapies to combat new and existing coronavirus outbreaks. Our analysis of clinical data from over 300,000 patients in three major health systems demonstrates a 50% reduced risk of COVID-19 in patients taking lithium, a direct inhibitor of glycogen synthase kinase-3 (GSK-3). We further show that GSK-3 is essential for phosphorylation of the SARS-CoV-2 nucleocapsid protein and that GSK-3 inhibition blocks SARS-CoV-2 infection in human lung epithelial cells. These findings suggest an antiviral strategy for COVID-19 and new coronaviruses that may arise in the future., The coronaviruses responsible for severe acute respiratory syndrome (SARS-CoV), COVID-19 (SARS-CoV-2), Middle East respiratory syndrome-CoV, and other coronavirus infections express a nucleocapsid protein (N) that is essential for viral replication, transcription, and virion assembly. Phosphorylation of N from SARS-CoV by glycogen synthase kinase 3 (GSK-3) is required for its function and inhibition of GSK-3 with lithium impairs N phosphorylation, viral transcription, and replication. Here we report that the SARS-CoV-2 N protein contains GSK-3 consensus sequences and that this motif is conserved in diverse coronaviruses, raising the possibility that SARS-CoV-2 may be sensitive to GSK-3 inhibitors, including lithium. We conducted a retrospective analysis of lithium use in patients from three major health systems who were PCR-tested for SARS-CoV-2. We found that patients taking lithium have a significantly reduced risk of COVID-19 (odds ratio = 0.51 [0.35–0.74], P = 0.005). We also show that the SARS-CoV-2 N protein is phosphorylated by GSK-3. Knockout of GSK3A and GSK3B demonstrates that GSK-3 is essential for N phosphorylation. Alternative GSK-3 inhibitors block N phosphorylation and impair replication in SARS-CoV-2 infected lung epithelial cells in a cell-type–dependent manner. Targeting GSK-3 may therefore provide an approach to treat COVID-19 and future coronavirus outbreaks.

Summary: Proper gene regulation is critical for both neuronal development and maintenance as the brain matures. We previously demonstrated that Akirin2, an essential nuclear protein that interacts with transcription factors and chromatin remodeling complexes, is required for the embryonic formation of the cerebral cortex. Here we show that Akirin2 plays a mechanistically distinct role in maintaining healthy neurons during cortical maturation. Restricting Akirin2 loss to excitatory cortical neurons resulted in progressive neurodegeneration via necroptosis and severe cortical atrophy with age. Comparing transcriptomes from Akirin2-null postnatal neurons and cortical progenitors revealed that targets of the tumor suppressor p53, a regulator of both proliferation and cell death encoded by Trp53, were consistently upregulated. Reduction of Trp53 rescued neurodegeneration in Akirin2-null neurons. These data: (1) implicate Akirin2 as a critical neuronal maintenance protein, (2) identify p53 pathways as mediators of Akirin2 functions, and (3) suggest Akirin2 dysfunction may be relevant to neurodegenerative diseases.

Widespread sleep deprivation is a continuing public health problem in the United States and worldwide affecting adolescents and adults. Acute sleep deprivation results in decrements in spatial memory and cognitive impairments. The hippocampus is vulnerable to acute sleep deprivation with changes in gene expression, cell signaling, and protein synthesis. Sleep deprivation also has long lasting effects on memory and performance that persist after recovery sleep, as seen in behavioral studies from invertebrates to humans. Although previous research has shown that acute sleep deprivation impacts gene expression, the extent to which sleep deprivation affects gene regulation remains unknown. Using an unbiased deep RNA sequencing approach, we investigated the effects of acute sleep deprivation on gene expression in the hippocampus. We identified 1,146 genes that were significantly dysregulated following sleep deprivation with 507 genes upregulated and 639 genes downregulated, including protein coding genes and long non-coding RNAs not previously identified as impacted by sleep deprivation. Notably, genes significantly upregulated after sleep deprivation were associated with RNA splicing and the nucleus. In contrast, downregulated genes were associated with cell adhesion, dendritic localization, the synapse, and postsynaptic membrane. Furthermore, we found through independent experiments analyzing a subset of genes that three hours of recovery sleep following acute sleep deprivation was sufficient to normalize mRNA abundance for most genes, although exceptions occurred for some genes that may affect RNA splicing or transcription. These results clearly demonstrate that sleep deprivation differentially regulates gene expression on multiple transcriptomic levels to impact hippocampal function. Supplementary Information The online version contains supplementary material available at 10.1186/s13041-021-00835-1.

This study is the first genetically-informed investigation of avoidant/restrictive food intake disorder (ARFID), an eating disorder that profoundly impacts quality of life for those affected. ARFID is highly comorbid with autism, and we provide the first estimate of its prevalence in a large and phenotypically diverse autism cohort (a subsample of the SPARK study, N = 5,157 probands). This estimate, 21% (at a balanced accuracy 80%), is at the upper end of previous estimates from studies based on clinical samples, suggesting under-diagnosis and potentially lack of awareness among caretakers and clinicians. Although some studies suggest a decrease of disordered eating symptoms by age 6, our estimates indicate that up to 17% (at a balanced accuracy 87%) of parents of autistic children are also at heightened risk for ARFID, suggesting a lifelong risk for disordered eating. We were also able to provide the first estimates of narrow-sense heritability (h2) for ARFID risk, at 0.45. Genome-wide association revealed a single hit near ZSWIM6, a gene previously implicated in neurodevelopmental conditions. While, the current sample was not well-powered for GWAS, effect size and heritability estimates allowed us to project the sample sizes necessary to more robustly discover ARFID-linked loci via common variants. Further genetic analysis using polygenic risk scores (PRS) affirmed genetic links to autism as well as neuroticism and metabolic syndrome.

Background Neurodevelopmental disorders (NDDs) such as autism spectrum disorder (ASD) display a strong male bias. Androgen exposure is profoundly increased in typical male development, but it also varies within the sexes, and previous work has sought to connect morphological proxies of androgen exposure, including digit ratio and facial morphology, to neurodevelopmental outcomes. The results of these studies have been mixed, and the relationships between androgen exposure and behavior remain unclear. Methods Here, we measured both digit ratio masculinity (DRM) and facial landmark masculinity (FLM) in the same neurodevelopmental cohort (N = 763) and compared these proxies of androgen exposure to clinical and parent-reported features as well as polygenic risk scores. Results We found that FLM was significantly associated with NDD diagnosis (ASD, ADHD, ID; all $$p p < 0.05 ), while DRM was not. When testing for association with parent-reported problems, we found that both FLM and DRM were positively associated with concerns about social behavior ($$\rho =0.19$$ ρ = 0.19 , $$p=0.004$$ p = 0.004 ; $$\rho =0.2$$ ρ = 0.2 , $$p=0.004$$ p = 0.004 , respectively). Furthermore, we found evidence via polygenic risk scores (PRS) that DRM indexes masculinity via testosterone levels ($$t=4.0$$ t = 4.0 , $$p=8.8\times 10^{-5}$$ p = 8.8 × 10 - 5 ), while FLM indexes masculinity through a negative relationship with sex hormone binding globulin (SHBG) levels ($$t=-3.3$$ t = - 3.3 , $$p=0.001$$ p = 0.001 ). Finally, using the SPARK cohort (N = 9419) we replicated the observed relationship between polygenic estimates of testosterone, SHBG, and social functioning ($$t=-2.3$$ t = - 2.3 , $$p=0.02$$ p = 0.02 , and $$t=4.2$$ t = 4.2 , $$p={3.2\times 10^{-5}}$$ p = 3.2 × 10 - 5 for testosterone and SHBG, respectively). Remarkably, when considered over the extremes of each variable, these quantitative sex effects on social functioning were comparable to the effect of binary sex itself (binary male: $$-0.22\pm 0.05$$ - 0.22 ± 0.05 ; testosterone: $$-0.35\pm 0.15$$ - 0.35 ± 0.15 from 0.1%-ile to 99.9%-ile; SHBG: $$0.64\pm 0.15$$ 0.64 ± 0.15 from 0.1%-ile to 99.9%-ile). Limitations In the devGenes and SPARK cohorts, our analyses rely on indirect, rather than direct measurement of androgens and related molecules. Conclusions These findings and their replication in the large SPARK cohort lend support to the hypothesis that increasing net androgen exposure diminishes capacity for social functioning in both males and females.

Objective Epilepsy treatment falls short in ~30% of cases. A better understanding of epilepsy pathophysiology can guide rational drug development in this difficult to treat condition. We tested a low‐cost, drug‐repositioning strategy to identify candidate epilepsy drugs that are already FDA‐approved and might be immediately tested in epilepsy patients who require new therapies. Methods Biopsies of spiking and nonspiking hippocampal brain tissue from six patients with unilateral mesial temporal lobe epilepsy were analyzed by RNA‐Seq. These profiles were correlated with transcriptomes from cell lines treated with FDA‐approved drugs, identifying compounds which were tested for therapeutic efficacy in a zebrafish seizure assay. Results In spiking versus nonspiking biopsies, RNA‐Seq identified 689 differentially expressed genes, 148 of which were previously cited in articles mentioning seizures or epilepsy. Differentially expressed genes were highly enriched for protein–protein interactions and formed three clusters with associated GO‐terms including myelination, protein ubiquitination, and neuronal migration. Among the 184 compounds, a zebrafish seizure model tested the therapeutic efficacy of doxycycline, metformin, nifedipine, and pyrantel tartrate, with metformin, nifedipine, and pyrantel tartrate all showing efficacy. Interpretation This proof‐of‐principle analysis suggests our powerful, rapid, cost‐effective approach can likely be applied to other hard‐to‐treat diseases.

Most genes associated with neurodevelopmental disorders (NDDs) were identified with an excess of de novo mutations (DNMs) but the significance in case-control mutation burden analysis is unestablished. Here, we sequence 63 genes in 16,294 NDD cases and an additional 62 genes in 6,211 NDD cases. By combining these with published data, we assess a total of 125 genes in over 16,000 NDD cases and compare the mutation burden to nonpsychiatric controls from ExAC. We identify 48 genes (25 newly reported) showing significant burden of ultra-rare (MAF 0.01%) gene-disruptive mutations (FDR 5%), six of which reach family-wise error rate (FWER) significance (p 1.25E-06). Among these 125 targeted genes, we also reevaluate DNM excess in 17,426 NDD trios with 6,499 new autism trios. We identify 90 genes enriched for DNMs (FDR 5%; e.g., GABRG2 and UIMC1); of which, 61 reach FWER significance (p 3.64E-07; e.g., CASZ1). In addition to doubling the number of patients for many NDD risk genes, we present phenotype-genotype correlations for seven risk genes (CTCF, HNRNPU, KCNQ3, ZBTB18, TCF12, SPEN, and LEO1) based on this large-scale targeted sequencing effort.

BackgroundCREB-dependent transcription necessary for long-term memory is driven by interactions with CREB-binding protein (CBP), a multi-domain protein that binds numerous transcription factors potentially affecting expression of thousands of genes. Identifying specific domain functions for multi-domain proteins is essential to understand processes such as cognitive function and circadian clocks. We investigated the function of the CBP KIX domain in hippocampal memory and gene expression using CBPKIX/KIXmice with mutations that prevent phospho-CREB (Ser133) binding.ResultsWe found that CBPKIX/KIXmice were impaired in long-term memory, but not learning acquisition or short-term memory for the Morris water maze. Using an unbiased analysis of gene expression in the dorsal hippocampus after training in the Morris water maze or contextual fear conditioning, we discovered dysregulation of CREB, CLOCK, and BMAL1 target genes and downregulation of circadian genes in CBPKIX/KIXmice. Given our finding that the CBP KIX domain was important for transcription of circadian genes, we profiled circadian activity and phase resetting in CBPKIX/KIXmice. CBPKIX/KIXmice exhibited delayed activity peaks after light offset and longer free-running periods in constant dark. Interestingly, CBPKIX/KIXmice displayed phase delays and advances in response to photic stimulation comparable to wildtype littermates. Thus, this work delineates site-specific regulation of the circadian clock by a multi-domain protein.ConclusionsThese studies provide insight into the significance of the CBP KIX domain by defining targets of CBP transcriptional co-activation in memory and the role of the CBP KIX domain in vivo on circadian rhythms.Graphical abstract

As exome and whole-genome sequencing cohorts grow in size, the data they produce strains the limits of current tools and data structures. The Variant Call Format (VCF) was originally created as part of the 1,000 Genomes project. Flexible and concise enough to describe the genetic variations of thousands of samples in a single flat file, the VCF has become the standard for communicating the results of large-scale sequencing experiments. Because of its static and text-based structure, VCFs remain cumbersome to parse and filter in an interactive way, even with the aid of indexing. Iterating on previous concepts, we propose here a pipeline for converting VCFs to simple SQLite databases, which allow for rapid searching and filtering of genetic variants while minimizing memory overhead. Code can be found at https://github.com/tkoomar/VCFdbR

Neuroimaging research has begun adopting deep learning to model structural differences in the brain. This is a break from previous approaches that rely largely on anatomical volumetric or thickness-based features. Currently, most studies employ either convolutional deep learning based models or traditional machine learning models that use volumetric features. Because of this split, it is unclear which approach yields better predictive performance, or whether the two approaches will lead to different neuroanatomical conclusions, potentially even when applied to the same dataset. To address these questions, we present the largest single study of sex differences in the brain using 21,390 UK Biobank T1-weighted brain MRIs, which we analyzed through both traditional volumetric and 3D convolutional neural network models. Overall, we find that 3D-CNNs outperformed traditional machine learning models, with sex classification area under the ROC curve of 0.849 and 0.683, respectively. When performing sex classification using only single regions of the brain, we observed better performance from 3D-CNNs in all regions tested, indicating sex differences in the brain likely represent both structural and volumetric changes. In addition, we find little consensus in terms of brain region prioritization between the two approaches. In summary, we find that 3D-CNNs show exceptional sex classification performance, extract additional relevant structural information from brain regions beyond volume, and possibly because of this, prioritize sex differences in neuroanatomical regions differently than volume-based approaches.

To better understand the shared basis of language and mental health, this review examines the behavioral and neurobiological features of aberrant language in five major neuropsychiatric conditions. Special attention is paid to genes implicated in both language and neuropsychiatric disorders, as they reveal biological domains likely to underpin the processes controlling both. Abnormal language and communication are common manifestations of neuropsychiatric conditions, and children with impaired language are more likely to develop psychiatric disorders than their peers. Major themes in the genetics of both language and psychiatry include master transcriptional regulators, like FOXP2; key developmental regulators, like AUTS2; and mediators of neurotransmission, like GRIN2A and CACNA1C.

The Simons Foundation Autism Research Initiative (SFARI) has launched SPARKForAutism.org, a dynamic platform that is engaging thousands of individuals with autism spectrum disorder (ASD) and connecting them to researchers. By making all data accessible, SPARK seeks to increase our understanding of ASD and accelerate new supports and treatments for ASD.

Background NPAS3 has been established as a robust genetic risk factor in major mental illness. In mice, loss of neuronal PAS domain protein 3 (NPAS3) impairs postnatal hippocampal neurogenesis, while loss of the related protein NPAS1 promotes it. These and other findings suggest a critical role for NPAS proteins in neuropsychiatric functioning, prompting interest in the molecular pathways under their control. Methods We used RNA sequencing coupled with chromatin immunoprecipitation sequencing to identify genes directly regulated by NPAS1 and NPAS3 in the hippocampus of wild-type, Npas1 −/− , and Npas3 −/− mice. Computational integration with human genetic and expression data revealed the disease relevance of NPAS-regulated genes and pathways. Specific findings were confirmed at the protein level by Western blot. Results This is the first in vivo, transcriptome-scale investigation of genes regulated by NPAS1 and NPAS3. These transcription factors control an ensemble of genes that are themselves also major regulators of neuropsychiatric function. Specifically, Fmr1 (fragile X syndrome) and Ube3a (Angelman syndrome) are transcriptionally regulated by NPAS3, as is the neurogenesis regulator Notch . Dysregulation of these pathways was confirmed at the protein level. Furthermore, NPAS1/3 targets show increased human genetic burden for schizophrenia and intellectual disability. Conclusions Together, these data provide a clear, unbiased view of the full spectrum of genes regulated by NPAS1 and NPAS3 and show that these transcription factors are master regulators of neuropsychiatric function. These findings expose the molecular pathophysiology of NPAS1/3 mutations and provide a striking example of the shared, combinatorial nature of molecular pathways that underlie diagnostically distinct neuropsychiatric conditions.

Post-translational modification (PTM) is a covalent and enzymatic modification of proteins, which contributes to diversify the proteome. Despite many reported PTMs with essential roles in cellular functioning, lysine succinylation has emerged as a subject of particular interest. Because its experimental identification remains a costly and time-consuming process, computational predictors have been recently proposed for tackling this important issue. However, the performance of current predictors is still very limited. In this paper, we propose a new predictor called PSSM-Suc which employs evolutionary information of amino acids for predicting succinylated lysine residues. Here we described each lysine residue in terms of profile bigrams extracted from position specific scoring matrices. We compared the performance of PSSM-Suc to that of existing predictors using a widely used benchmark dataset. PSSM-Suc showed a significant improvement in performance over state-of-the-art predictors. Its sensitivity, accuracy and Matthews correlation coefficient were 0.8159, 0.8199 and 0.6396, respectively.