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BackgroundRisk factors associated with sporadic non-amnestic and early-onset Alzheimer’s disease remain underexamined. We investigated a large, clinically heterogeneous Alzheimer’s disease cohort for frequencies of established Alzheimer’s disease risk factors (hypertension, hyperlipidemia, diabetes mellitus,APOE-ɛ4 frequency, and years of education), alongside a suite of novel factors with historical theoretical association (non-right-handedness, learning disability, seizures, and autoimmune disease).MethodsIn this case-control study, we screened the demographic and health histories of 750 consecutive early-onset and 750 late-onset Alzheimer’s disease patients from the University of California San Francisco Memory and Aging Center for the prevalence of conventional risk and novel Alzheimer’s disease factors and compared these results with 8,859 Alzheimer’s disease individuals from the National Alzheimer’s Coordinating Center, Amsterdam University Medical Center, Amsterdam, and Mayo Clinic, Jacksonville.ResultsEarly-onset Alzheimer’s disease was associated with significantly lower frequencies of established risk factors (hypertension, hyperlipidemia, diabetes mellitus, allpAPOE-ɛ4,p=0.03) and significantly higher frequencies of novel factors (non-right-handedness, learning disability, active seizure, allpp=0.002, and autoimmune disease,p=0.007). Logistic regressions predicting EOAD vs. LOAD controlling for sex, education,APOE-ɛ4 status, typical, and novel risk factors, produced findings consistent with the above. Principal component analysis loaded novel factors into two components, non-right-handedness and learning disability versus seizure and autoimmune disease, and the combination of factors from both components resulted in an exponential decrease in age at onset from any single factor alone.APOE-ɛ4 provided no additional contribution to age at onset decreases within the non-amnestic Alzheimer’s disease cohort but shifted the age of onset 3 years earlier within amnestic presentations (p=0.013).ConclusionsWe identified non-right-handedness, learning disability, seizures, and autoimmune disease as novel factors that affect both the age at onset and phenotypical targeting of Alzheimer’s disease. Together these results support a new theoretical framework of neurodegenerative disease susceptibility and that through the collection of detailed developmental and health history, neurodegenerative disease risk in some may be highly predictable, offering new opportunities towards early detection, monitoring, therapeutic intervention, and ultimately disease prevention.

Non-enhancing (NE) infiltrating tumor cells beyond the contrast-enhancing (CE) bulk of tumor are potential propagators of recurrence after gross total resection of high-grade glioma. We leveraged single-nucleus RNA-sequencing to compare prospectively identified biopsy specimens from CE and NE regions. Recurrent gliomas recapitulate the previously reported glioma cellular states of primary gliomas. Tumor cells in NE regions are enriched in oligodendrocyte progenitor cell-like and neural progenitor cell-like cellular states, while CE regions are enriched for astrocyte-like and mesenchymal-like states. These NE glioma cells have similar copy number alterations and proportions of proliferative and putative glioma stem cells relative to CE regions. Tumor cells in NE regions exhibit upregulation of genes previously associated with lower grade gliomas. Cell-, gene-, and pathway-level analyses of the tumor microenvironment in the NE region reveal relative downregulation of tumor-mediated neovascularization and cell-mediated immune response, but increased glioma-to-neuron interactions. This comprehensive analysis illustrates differing tumor and non-tumor landscapes of CE and NE regions in high-grade gliomas, highlighting the NE region as an area harboring likely initiators of recurrence in a pro-tumor microenvironment and identifying possible targets for future design of NE-specific adjuvant therapy.

IMPORTANCEThe neurological substrates of visual creativity are unknown. We demonstrate the role of dorsomedial visual cortex in emergence of visual artistic creativity (VAC) in the setting of dementia. Our findings illuminate neural substrates of human creativity and suggest that hyperactivation of specific brain areas may manifest as enhanced cognitive or behavioral capacities.OBJECTIVETo determine the anatomical and physiological underpinnings of VAC in dementia.DESIGN, SETTING, AND PARTICIPANTSAs part of a prospective, longitudinal cohort study focused on frontotemporal dementia (FTD), 734 patients met research criteria for an FTD spectrum disorder between 2002 and 2019. Of these, seventeen showed emergence of visual artistic creativity (VAC-FTD). Two control groups (n = 51 each) were matched to VAC-FTD based on demographic and clinical parameters: (1) Not Visually Artistic FTD (NVA-FTD) and (2) Healthy Controls (HC).MAIN OUTCOMES AND MEASURESClinical, neuropsychological, genetic and neuroimaging data were analyzed to characterize VAC-FTD and compare VAC-FTD to control groups.RESULTSEmergence of VAC occurred around the time of onset of symptoms, and was disproportionately seen in patients with temporal lobe predominant degeneration (n = 8/17). Atrophy network mapping identified a dorsomedial occipital region whose activity inversely correlated, in healthy brains, with activity in the patient-specific atrophy patterns in VAC-FTD (n = 17/17) and NVA-FTD (n = 45/51). Structural covariance analysis revealed that volume of this dorsal occipital region was strongly correlated, in VAC-FTD, but not in NVA-FTD or HC, with a volume in the primary motor cortex corresponding to the right hand representation. One patient, who underwent fluorodeoxyglucose positron emission tomography before and after VAC onset, showed increasing glucose metabolism in the dorsal occipital region over the interval when creativity emerged.CONCLUSIONS AND RELEVANCEFTD lesion-induced intensification of dorsal visual association cortex structure and function predisposes to emergence of VAC in certain environmental or genetic conditions. Paradoxical gains of function are early manifestations of neurodegenerative disease, and this study delineates a specific brain region associated with the emergence of VAC.

Autism Spectrum Disorder (ASD) has a complex genetic architecture involving contributions from de novo and inherited variation. Few studies have been designed to address the role of rare inherited variation, or its interaction with polygenic risk in ASD. Here, we performed whole genome sequencing of the largest cohort of multiplex families to date, consisting of 4,551 individuals in 1,004 families having 2 or more affected children with ASD. Using this study design, we identify seven novel risk genes supported primarily by rare inherited variation, finding support for a total of 74 genes in our cohort and a total of 152 genes after combining with other studies. Probands demonstrated an increased burden of mutations in 2 or more known risk genes (KARGs) — in three families both probands inherited protein truncating variants in two KARGs. We also find that polygenic risk is over transmitted from unaffected parents to affected children with rare inherited variants, consistent with combinatorial effects in the offspring, which may explain the reduced penetrance of these rare variants in parents. We also observe that in addition to social dysfunction, language delay is associated with ASD polygenic risk over-transmission. These results are consistent with an additive complex genetic risk architecture of ASD involving rare and common variation and further suggest that language delay is a core biological feature of ASD.

The UCLA ATLAS Community Health Initiative (ATLAS) has an initial target to recruit 150,000 participants from across the UCLA Health system, with the goal of creating a genomic database to accelerate precision medicine efforts in California. This initiative includes a biobank embedded within the UCLA Health system that comprises de-identified genomic data linked to electronic health records (EHR). The first freeze of data from September 2020 contains 27,987 genotyped samples imputed to 7.9 million SNPs across the genome and is linked with a de-identified EHR extract. This database enables the study of numerous clinically-related phenotypes within the same medical system. Here we describe a centralized repository of the genotype data and provide tools and pipelines to perform genome-wide and phenome-wide association studies across a wide range of EHR-derived phenotypes and genetic ancestry groups. We demonstrate the utility of this resource through the analysis of 7 well-studied traits and recapitulate many previous genetic and phenotypic associations.

SUMMARYNeurodegenerative diseases are characterized by neuronal death and regenerative failure. However, gene regulatory programs governing how initial neuronal injuries lead to neuronal death remain poorly understood. In adult mice, optic nerve crush (ONC) injury, which severs all axons of retinal ganglion cells (RGCs), results in massive death of axotomized RGCs and regenerative failure of survivors. We performed an in vivo CRISPR/Cas9-based genome-wide screen of 1893 transcription factors (TFs) to seek repressors of RGC survival and axon regeneration following ONC. In parallel, we profiled the epigenetic and transcriptional landscapes of injured RGCs by ATAC-seq and RNA-seq to identify critical injury responsive TFs and their targets. Remarkably, these independent analyses converged on a set of four ATF/CEBP transcription factors – ATF3, ATF4, C/EBPγ and CHOP (Ddit3) – as critical regulators of survival. Further studies indicate that these TFs contribute to two pro-death transcriptional programs: ATF3/CHOP preferentially regulate pathways activated by cytokines and innate immunity, whereas ATF4/C/EBPγ regulate pathways engaged by intrinsic neuronal stressors. Manipulation of these TFs also protects RGCs in an experimental model of glaucoma, a prevalent disease in which RGCs die. Together, our results reveal core transcription programs that transform an initial axonal insult into a degenerative result and suggest novel strategies for treating neurodegenerative diseases.

SummaryBiobanks are being established across the world to understand the genetic, environmental, and epidemiological basis of human diseases with the goal of better prevention and treatments. Genome-wide association studies (GWAS) have been very successful at mapping genomic loci for a wide range of human diseases and traits, but in general, lack appropriate representation of diverse ancestries - with most biobanks and preceding GWAS studies composed of individuals of European ancestries. Here, we introduce the Global Biobank Meta-analysis Initiative (GBMI) -- a collaborative network of 19 biobanks from 4 continents representing more than 2.1 million consented individuals with genetic data linked to electronic health records. GBMI meta-analyzes summary statistics from GWAS generated using harmonized genotypes and phenotypes from member biobanks. GBMI brings together results from GWAS analysis across 6 main ancestry groups: approximately 33,000 of African ancestry either from Africa or from admixed-ancestry diaspora (AFR), 18,000 admixed American (AMR), 31,000 Central and South Asian (CSA), 341,000 East Asian (EAS), 1.4 million European (EUR), and 1,600 Middle Eastern (MID) individuals. In this flagship project, we generated GWASs from across 14 exemplar diseases and endpoints, including both common and less prevalent diseases that were previously understudied. Using the genetic association results, we validate that GWASs conducted in biobanks worldwide can be successfully integrated despite heterogeneity in case definitions, recruitment strategies, and baseline characteristics between biobanks. We demonstrate the value of this collaborative effort to improve GWAS power for diseases, increase representation, benefit understudied diseases, and improve risk prediction while also enabling the nomination of disease genes and drug candidates by incorporating gene and protein expression data and providing insight into the underlying biology of the studied traits.

SummaryCNS neurons do not regenerate after injury, leading to permanent functional deficits. Although sensory and motor neuron axons do regrow after peripheral nerve injury, functional outcome is limited due to the incomplete and slow regrowth. The lack of human-relevant assays suitable for large-scale drug screens has limited neuro-repair therapy discovery. To address this we developed a phenotypic screening strategy using human induced pluripotent stem cell-derived motor neurons to identify axon-regeneration promoting compounds and targets. The screens involve both re-plating human motor neurons on chondroitin sulfate proteoglycans and measuring regeneration responses to laser axotomy in spot cultures, and from them we identified multiple hits that promote injured axon regrowth. The top hit blebbistatin, a non-muscle myosin II inhibitor, accelerated axon regeneration and functional recovery after sciatic nerve injury in vivo. Human “injury in a dish” assays are suitable, therefore, to screen for therapeutic interventions that can induce or accelerate axon regeneration.

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.

Large medical centers located in urban areas such as Los Angeles care for a diverse patient population and offer the potential to study the interplay between genomic ancestry and social determinants of health within a single medical system. Here, we introduce the UCLA ATLAS Community Health Initiative – a biobank of genomic data linked with de-identified electronic health records (EHRs) of UCLA Health patients. We leverage the unique genomic diversity of the patient population in ATLAS to explore the interplay between self-reported race/ethnicity and genetic ancestry within a disease context using phenotypes extracted from the EHR. First, we identify an extensive amount of continental and subcontinental genomic diversity within the ATLAS data that is consistent with the global diversity of Los Angeles; this includes clusters of ATLAS individuals corresponding to individuals with Korean, Japanese, Filipino, and Middle Eastern genomic ancestries. Most importantly, we find that common diseases and traits stratify across genomic ancestry clusters, thus suggesting their utility in understanding disease biology across diverse individuals. Next, we showcase the power of genetic data linked with EHR to perform ancestry-specific genome and phenome-wide scans to identify genetic factors for a variety of EHR-derived phenotypes (phecodes). For example, we find ancestry-specific associations for liver disease, and link the genetic variants with neurological and neoplastic phenotypes primarily within individuals of admixed ancestries. Overall, our results underscore the utility of studying the genomes of diverse individuals through biobank-scale genotyping efforts linked with EHR-based phenotyping.

The prevalence of Alzheimer’s disease (AD), the leading cause of dementia, shows a strict age-dependency, but why ageing constitutes the main risk factor for this disease is still poorly understood. Brain ageing affects oligodendrocytes1 and the structural integrity of myelin sheaths2, the latter associated with secondary neuroinflammation3. Since oligodendrocytes support axonal and neuronal health4–7, we hypothesised that ageing-associated loss of myelin integrity could be an upstream risk factor for neuronal amyloid-β (Aβ) deposition, the primary neuropathological hallmark of AD. Here, we show that in AD mouse models different genetically induced defects of myelin integrity or demyelinating injuries are indeed potent drivers of amyloid deposition in vivo, quantified by whole brain light sheet microscopy. Conversely, the lack of myelin in the forebrain provides protection against plaque deposition. Mechanistically, we find that myelin dysfunction causes the accumulation of the Aβ producing machinery within axonal swellings and increases cortical amyloid precursor protein (APP) cleavage. Surprisingly, AD mice with dysfunctional myelin lack plaque-corralling microglia but show a disease-associated microglia (DAM)-like signature as revealed by bulk and single cell transcriptomics. These activated microglia, however, are primarily engaged with myelin, preventing the protective reactions of microglia to Aβ plaques. Our data suggest a working model, in which age-dependent structural defects of myelin promote plaque formation, directly and indirectly, and are thus an upstream AD risk factor. Improving oligodendrocyte health and myelin integrity could be a promising target to delay AD.g

Attention deficit hyperactivity disorder (ADHD) is a complex disorder with heterogeneous clinical presentations that manifest variability in long-term outcomes. The genetic contributions to this clinical heterogeneity, however, are not well understood. Here, we study 14 084 individuals diagnosed with ADHD to identify several genetic factors underlying clinical heterogeneity. One genome-wide significant locus was specifically associated with an autism spectrum disorder (ASD) diagnosis among individuals diagnosed with ADHD and it was not previously associated with ASD nor ADHD, individually. We used a novel approach to compare profiles of polygenic scores for groups of individuals diagnosed with ADHD and uncovered robust evidence that biology is an important factor in on-going clinical debates. Specifically, individuals diagnosed with ASD and ADHD, substance use disorder (SUD) and ADHD, or first diagnosed with ADHD in adulthood had different profiles of polygenic scores for ADHD and multiple other psychiatric, cognitive, and socio-behavioral traits. A polygene overlap between an ASD diagnosis in ADHD and cognitive performance was replicated in an independent, typically developing cohort. Our unique approach uncovered evidence of genetic heterogeneity in a widely studied complex disorder, allowing for timely contributions to the understanding of ADHD etiology and providing a model for similar studies of other disorders.

SUMMARYTau (MAPT) drives neuronal dysfunction in Alzheimer’s disease (AD) and other tauopathies. To dissect the underlying mechanisms, we combined an engineered ascorbic acid peroxidase (APEX) approach with quantitative affinity purification mass spectrometry (AP-MS) followed by proximity ligation assay (PLA) to characterize Tau interactomes modified by neuronal activity and mutations that cause frontotemporal dementia (FTD) in human induced pluripotent stem cell (iPSC)-derived neurons. We established activity-dependent interactions of Tau with presynaptic vesicle proteins during Tau secretion and mapped the exact APEX-tau-induced biotinylated tyrosines to the cytosolic domains of the interacting vesicular proteins. We showed that FTD mutations impair bioenergetics and markedly diminished Tau’s interaction with mitochondria proteins, which were downregulated in AD brains of multiple cohorts and correlated with disease severity. These multi-modal and dynamic Tau interactomes with unprecedented spatiotemporal resolution shed novel insights into Tau’s role in neuronal function and disease-related processes with potential therapeutic targets to block Tau-mediated pathogenesis.

Predicting functionality of noncoding variation is one of the major challenges in modern genetics. We employed massively parallel reporter assays to screen 5,706 variants from genome-wide association studies for both Alzheimer’s disease (AD) and Progressive Supranuclear Palsy (PSP). We identified 320 functional regulatory polymorphisms (SigVars) comprising 27 of 34 unique tested loci, including multiple independent signals across the complex 17q21.31 region. We identify novel risk genes includingPLEKHM1in PSP andAPOC1in AD, and perform gene-editing to validate four distinct causal loci, confirming complement 4 (C4A) as a novel genetic risk factor for AD. Moreover, functional variants preferentially disrupt transcription factor binding sites that converge on enhancers with differential cell-type specific activity in PSP and AD, implicating a neuronalSP1-driven regulatory network in PSP pathogenesis. These analyses support a novel mechanism underlying noncoding genetic risk, whereby common genetic variants drive disease risk via their aggregate activity on specific transcriptional programs.One Sentence SummaryHigh-throughput functional analysis of GWAS loci reveals cell-type specific regulatory networks that mediate genetic risk for dementia.

SUMMARYDefects in interneuron migration during forebrain development can disrupt the assembly of cortical circuits and have been associated with neuropsychiatric disease. The molecular and cellular bases of such deficits have been particularly difficult to study in humans due to limited access to functional forebrain tissue from patients. We previously developed a human forebrain assembloid model of Timothy Syndrome (TS), caused by a gain-of-function mutation in CACNA1C which encodes the L-type calcium channel (LTCC) Cav1.2. By functionally integrating human induced pluripotent stem cell (hiPSC)-derived organoids resembling the dorsal and ventral forebrain from patients and control individuals, we uncovered that migration is disrupted in TS cortical interneurons. Here, we dissect the molecular underpinnings of this phenotype and report that acute pharmacological modulation of Cav1.2 can rescue the saltation length but not the saltation frequency of TS migrating interneurons. Furthermore, we find that the defect in saltation length in TS interneurons is associated with aberrant actomyosin function and is rescued by pharmacological modulation of MLC phosphorylation, whereas the saltation frequency phenotype in TS interneurons is driven by enhanced GABA sensitivity and can be restored by GABA receptor antagonism. Overall, these findings uncover multi-faceted roles of LTCC function in human cortical interneuron migration in the context of disease and suggest new strategies to restore interneuron migration deficits.

It has been proposed that focal anterior temporal lobe (ATL) degeneration is a specific, unitary FTLD-TDP-related disease that initially preferentially affects the left or right hemisphere. Patients with early left ATL (lATL) atrophy show severe anomia and verbal semantic deficits and meet criteria for semantic variant primary progressive aphasia (svPPA) and semantic dementia, prompting appropriate neurological care. There is less consensus regarding the symptoms in right ATL (rATL) predominant cases, who most often present with behavioral and emotional changes leading to a misdiagnosis of a psychiatric disorder, and later of behavioral variant frontotemporal dementia (bvFTD). Uncertainties regarding early symptoms and lack of an overarching framework continues to hinder proper diagnosis and care of patients with rATL disease. Here, we present symptom chronology, cognitive and socioemotional profiles of a large, well-characterized, longitudinally followed cohort of patients with rATL-predominant degeneration and propose new criteria and nosology for the syndrome.We identified individuals with a clinical diagnosis of bvFTD or svPPA and a structural MRI (n=478). Based on neuroimaging criteria, we identified three groups: patients with rATL-predominant atrophy with relative sparing of the frontal lobes (n=46), patients with frontal-predominant atrophy with relative sparing of the rATL (n=79), and patients with lATL-predominant atrophy with relative sparing of the frontal lobes (n=75). Seventy-eight patients had undergone autopsy. We analyzed patients’ clinical, neuropsychological, genetic, anatomical, and pathological profiles.In the rATL-predominant group, the earliest symptoms were loss of empathy (27%), person-specific semantic impairment (23%), and complex compulsions and rigid thought process (18%). On testing, this group exhibited greater impairments in emotional theory of mind, identifying famous people from names and face, and facial affect naming (despite preserved face perception) than the lATL- and frontal-predominant groups. The clinical features were highly sensitive (81%) and specific (84%) in differentiating rATL from bvFTD in the first three years of the disease. FTLD-TDP (84%) was the most common pathology.Our results suggest that rATL-predominant degeneration is characterized by early loss of empathy and person-specific knowledge, deficits that are caused by progressive loss of semantic memory for concepts of social-emotional relevance. Although this syndrome exists along a clinical, anatomical, and pathological continuum with svPPA, patients present with progressive behavioral changes. To facilitate early identification and care in clinical and research settings, we propose specific diagnostic criteria and the term “emotional semantic variant frontotemporal dementia” to distinguish this syndrome from other forms of frontotemporal dementia.

Treatment-refractory glioma stem and tumor cells exhibit phenotypic plasticity driving recurrence, but the underlying molecular mechanisms remain to be elucidated. Here, we employed single-cell and whole transcriptomic analyses to discover that radiation induces a dynamic shift in functional states of glioma cells allowing for acquisition of vascular endothelial-like and pericyte-like cell phenotypes. These vascular-like cells provide a trophic niche to promote proliferation of irradiated glioma cells, and their selective depletion results in reduced tumor growth post-treatment in vivo. Mechanistically, the acquisition of vascular-like phenotype is driven by increased chromatin accessibility and H3K27 acetylation in specific vascular gene regions post-treatment. Blocking P300 histone acetyltransferase activity reverses the epigenetic changes induced by radiation, and inhibits the phenotypic transition and tumor growth. Our findings highlight an important role for P300 histone acetyltransferase in treatment-induced plasticity and opens a new therapeutic avenue for preventing glioma recurrence.SignificanceOur study demonstrates that radiation therapy promotes glioma resistance by inducing vascular-like phenotypes in GSC that, in turn, aid in proliferation of the remaining tumor cells. This phenotype switch is mediated by P300 HAT, and inhibition of this enzyme is a potential therapeutic target for preventing glioma recurrence following radiation.

The microenvironments of the brain consist of specialized cell types that together influence physiological functions in health and pathological outcomes in disease. Despite apparent differences in the density of neurons and oligodendrocytes in various milieus, such as gray matter (GM) and white matter (WM), the extent of structural and functional heterogeneity of other resident cells remains unclear. We profiled RNA in ~500,000 nuclei from 19 tissue types across the central nervous system of the healthy adult common marmoset (Callithrix jacchus) and mapped 87 identified subclusters (including neurons, glia, and vasculature) spatially onto a 3D MRI atlas. We performed cross-species comparison, explored regulatory pathways, surveyed cellular determinants of neurological disorders, and modeled regional intercellular communication. We found spatially segregated microglia, oligodendrocyte lineage cells, and astrocytes in WM and GM. WM-glia are diverse, are enriched with genes involved in stimulus response and biomolecule modification, and interact with other resident cells more extensively than their GM counterparts. GM-glia preserve the expression of developmental morphogens into adulthood and share 6 differentially enriched transcription factors that restrict the transcriptome complexity. Our work in marmoset, an experimentally tractable animal model with >5 times more WM volume and complexity than mouse, identifies novel WM-glia subtypes and their contributions to different neurological disorders. A companion Callithrix jacchus Primate Cell Atlas (CjPCA) is available through an online portal https://cjpca.ninds.nih.gov to facilitate data exploration.

Gene expression covaries with brain activity as measured by resting state functional magnetic resonance imaging (MRI). However, it is unclear how genomic differences driven by disease state can affect this relationship. Here, we integrate from the ABIDE I and II imaging cohorts with datasets of gene expression in brains of neurotypical individuals and individuals with autism spectrum disorder (ASD) with regionally matched brain activity measurements from fMRI datasets. We identify genes linked with brain activity whose association is disrupted in ASD. We identified a subset of genes that showed a differential developmental trajectory in individuals with ASD compared with controls. These genes are enriched in voltage-gated ion channels and inhibitory neurons, pointing to excitation-inhibition imbalance in ASD. We further assessed differences at the regional level showing that the primary visual cortex is the most affected region in ASD. Our results link disrupted brain expression patterns of individuals with ASD to brain activity and show developmental, cell type, and regional enrichment of activity linked genes.

Classically, psychiatric disorders have been considered to lack defining pathology, but recent work has demonstrated consistent disruption at the molecular level, characterized by transcriptomic and epigenetic alterations.1–3 In ASD, upregulation of microglial, astrocyte, and immune signaling genes, downregulation of specific synaptic genes, and attenuation of regional gene expression differences are observed.1,2,4–6 However, whether these changes are limited to the cortical association areas profiled is unknown. Here, we perform RNA-sequencing (RNA-seq) on 725 brain samples spanning 11 distinct cortical areas in 112 ASD cases and neurotypical controls. We identify substantially more genes and isoforms that differentiate ASD from controls than previously observed. These alterations are pervasive and cortex-wide, but vary in magnitude across regions, roughly showing an anterior to posterior gradient, with the strongest signal in visual cortex, followed by parietal cortex and the temporal lobe. We find a notable enrichment of ASD genetic risk variants among cortex-wide downregulated synaptic plasticity genes and upregulated protein folding gene isoforms. Finally, using snRNA-seq, we determine that regional variation in the magnitude of transcriptomic dysregulation reflects changes in cellular proportion and cell-type-specific gene expression, particularly impacting L3/4 excitatory neurons. These results highlight widespread, genetically-driven neuronal dysfunction as a major component of ASD pathology in the cerebral cortex, extending beyond association cortices to involve primary sensory regions.

MEF2C has been shown to be a critical transcription factor for neurodevelopment, whose loss-of-function mutation in humans results in MEF2C haploinsufficiency syndrome (MHS), a severe form of autism spectrum disorder (ASD)/intellectual disability (ID). Here, we use patient hiPSC-derived cerebrocortical neurons and cerebral organoids to characterize MHS deficits. Unexpectedly, we found an aberrant micro-RNA-mediated gliogenesis pathway that contributes to decreased neurogenesis. We also demonstrate network-level hyperexcitability in neurons, as evidenced by excessive synaptic and extrasynaptic activity contributing to excitatory/inhibitory (E/I) imbalance. Notably, the extrasynaptic NMDA receptor antagonist, NitroSynapsin, corrects this aberrant electrical activity associated with abnormal phenotypes. During neurodevelopment, MEF2C regulates many ASD-associated gene networks suggesting that our approach may lead to personalized therapy for multiple forms of ASD.One sentence summaryAutism-like MEF2C+/- patient hiPSC models show miRNA-mediated overproduction of astrocytes and hyperactivity of neurons.

Interpretation of the function of non-coding risk loci for neuropsychiatric disorders and brain-relevant traits via gene expression and alternative splicing is generally performed in bulk post-mortem adult tissue. However, genetic risk loci are enriched in regulatory elements active during neocortical differentiation, and regulatory effects of risk variants may be masked by heterogeneity in bulk tissue. Here, we map expression quantitative trait loci (eQTLs), splicing QTLs (sQTLs), and allele specific expression in primary human neural progenitors (n=85) and their sorted neuronal progeny (n=74), identifying numerous loci not detected in either bulk developing cortical wall or adult cortex. Using colocalization and genetic imputation via transcriptome wide association, we uncover cell-type specific regulatory mechanisms underlying risk for brain-relevant traits that are active during neocortical differentiation. Specifically, we identified a progenitor-specific eQTL for CENPW co-localized with common variant associations of cortical area and educational attainment.

SummaryWith the continuing coronavirus disease 2019 (COVID-19) pandemic coupled with phased reopening, it is critical to identify risk factors associated with susceptibility and severity of disease in a diverse population to help shape government policies, guide clinical decision making, and prioritize future COVID-19 research. In this retrospective case-control study, we used de-identified electronic health records (EHR) from the University of California Los Angeles (UCLA) Health System between March 9th, 2020 and June 14th, 2020 to identify risk factors for COVID-19 susceptibility (severe acute respiratory distress syndrome coronavirus 2 (SARS-CoV-2) PCR test positive), inpatient admission, and severe outcomes (treatment in an intensive care unit or intubation). Of the 26,602 individuals tested by PCR for SARS-CoV-2, 992 were COVID-19 positive (3.7% of Tested), 220 were admitted in the hospital (22% of COVID-19 positive), and 77 had a severe outcome (35% of Inpatient). Consistent with previous studies, males and individuals older than 65 years old had increased risk of inpatient admission. Notably, individuals self-identifying as Hispanic or Latino constituted an increasing percentage of COVID-19 patients as disease severity escalated, comprising 24% of those testing positive, but 40% of those with a severe outcome, a disparity that remained after correcting for medical co-morbidities. Cardiovascular disease, hypertension, and renal disease were premorbid risk factors present before SARS-CoV-2 PCR testing associated with COVID-19 susceptibility. Less well-established risk factors for COVID-19 susceptibility included pre-existing dementia (odds ratio (OR) 5.2 [3.2-8.3], p=2.6 × 10−10), mental health conditions (depression OR 2.1 [1.6-2.8], p=1.1 × 10−6) and vitamin D deficiency (OR 1.8 [1.4-2.2], p=5.7 × 10−6). Renal diseases including end-stage renal disease and anemia due to chronic renal disease were the predominant premorbid risk factors for COVID-19 inpatient admission. Other less established risk factors for COVID-19 inpatient admission included previous renal transplant (OR 9.7 [2.8-39], p=3.2×10−4) and disorders of the immune system (OR 6.0 [2.3, 16], p=2.7×10−4). Prior use of oral steroid medications was associated with decreased COVID-19 positive testing risk (OR 0.61 [0.45, 0.81], p=4.3×10−4), but increased inpatient admission risk (OR 4.5 [2.3, 8.9], p=1.8×10−5). We did not observe that prior use of angiotensin converting enzyme inhibitors or angiotensin receptor blockers increased the risk of testing positive for SARS-CoV-2, being admitted to the hospital, or having a severe outcome. This study involving direct EHR extraction identified known and less well-established demographics, and prior diagnoses and medications as risk factors for COVID-19 susceptibility and inpatient admission. Knowledge of these risk factors including marked ethnic disparities observed in disease severity should guide government policies, identify at-risk populations, inform clinical decision making, and prioritize future COVID-19 research.

BackgroundHuman epidemiologic studies have implicated exposure to infectious or inflammatory insults during gestation in the etiology of neurodevelopmental disorders. Rodent models of maternal immune activation (MIA) have identified the maternal immune response as the critical link between maternal infection and aberrant brain and behavior development in offspring. The nonhuman primate MIA model provides an opportunity to maximize the translational utility of this model in a species more closely related to humans.MethodsHere we evaluate the effects of MIA on brain and behavioral development in the rhesus monkey (Macaca mulatta). A modified form of the viral mimic, Polyinosinic-polycytidylic acid (PolyIC), was delivered to pregnant rhesus monkeys (n=14) in the late first trimester to stimulate a maternal immune response. Control dams received saline injections at the same gestational time points (n=10) or were untreated (n=4).ResultsMIA-treated dams exhibited a strong immune response as indexed by transient increases in sickness behavior, temperature and inflammatory cytokines. MIA-exposed offspring developed species typical milestones and demonstrate subtle changes in early in social development. However, magnetic resonance imaging demonstrated significant gray matter volume reductions in prefrontal and frontal cortices at 6, 12 and 24 months of age.ConclusionsThese findings provide new insights into the emergence of neuropathology in MIA-exposed primates and have implications for the pathophysiology of human psychiatric disorders associated with maternal gestational infection.

Mouse models have allowed for the direct interrogation of genetic effects on molecular, physiological and behavioral brain phenotypes. However, it is unknown to what extent neurological or psychiatric traits may be human or primate-specific and therefore, which components can be faithfully recapitulated in mouse models. We identify robust co-expression modules reflecting whole brain and regional patterns of gene expression and compare conservation of co-expression in 116 independent data sets derived from human, mouse and non-human primate representing more than 15,000 total samples. We observe greater co-expression changes occurring on the human lineage than mouse, and substantial regional variation that highlights cerebral cortex as the most diverged region. Cell type specific modules are the most divergent across the brain, compared with those that represent basic metabolic processes. Among these, glia are the most divergent, three times that of neurons. We show that regulatory sequence divergence explains a significant fraction of co-expression divergence. Similarly, protein coding sequence constraint parallels co-expression conservation, such that genes with loss of function intolerance are enriched in neuronal, rather than glial modules. We also identify dozens of human disease risk genes, such as COMT, PSEN-1, LRRK2, and SNCA, with highly divergent co-expression between mouse and primates or human. We show that 3D human brain organoids recapitulate in vivo co-expression modules representing several human cell types, which along with our analysis of human-mouse disease gene divergence, serve as a foundational resource to guide disease modeling and its interpretation.

Cellular heterogeneity in the human brain obscures the identification of robust cellular regulatory networks. Here we integrated genome-wide chromosome conformation in purified neurons and glia with transcriptomic and enhancer profiles to build the gene regulatory landscape of two major cell classes in the human brain. Within glutamatergic and GABAergic neurons, we were able to link enhancers to their cognate genes via neuronal chromatin interaction profiles. These cell-type-specific regulatory landscapes were then leveraged to gain insight into the cellular etiology of several brain disorders. We found that Alzheimer’s disease (AD)-associated epigenetic dysregulation was linked to neurons and oligodendrocytes, whereas genetic risk factors for AD highlighted microglia as a central cell type, suggesting that different cell types may confer risk to the disease via different genetic mechanisms. Moreover, neuronal subtype-specific annotation of genetic risk factors for schizophrenia and bipolar disorder identified shared (parvalbumin-expressing interneurons) and distinct cellular etiology (upper layer neurons for bipolar and deeper layer projection neurons for schizophrenia) between these two closely related psychiatric illnesses. Collectively, these findings shed new light on cell-type-specific gene regulatory networks in brain disorders.

Gene networks have proven their utility for elucidating transcriptome structure in the brain, yielding numerous biological insights. Most analyses have focused on expression relationships within a circumspect number of regions – how these relationships vary across a broad array of brain regions is largely unknown. By leveraging RNA-sequencing in 864 samples representing 12 brain regions in a cohort of 131 phenotypically normal individuals, we identify 12 brain-wide, 114 region-specific, and 50 cross-regional co-expression modules. We replicate the majority (81%) of modules in regional microarray datasets. Nearly 40% of expressed genes fall into brain-wide modules corresponding to major cell classes and conserved biological processes. Region-specific modules comprise 25% of expressed genes and correspond to region-specific cell types and processes, such as oxytocin signaling in the hypothalamus, or addiction pathways in the nucleus accumbens. We further leverage these modules to capture cell-type-specific lncRNA and gene isoforms, both of which contribute substantially to regional synaptic diversity. We identify enrichment of neuropsychiatric disease risk variants in brain wide and multi-regional modules, consistent with their broad impact on cell classes, and highlight specific roles in neuronal proliferation and activity-dependent processes. Finally, we examine the manner in which gene co-expression and gene regulatory networks reflect genetic risk, including the recently framed omnigenic model of disease architecture.

SummaryCommon genetic risk for neuropsychiatric disorders is enriched in regulatory elements active during cortical neurogenesis. However, the mechanisms mediating the effects of genetic variants on gene regulation are poorly understood. To determine the functional impact of common genetic variation on the non-coding genome longitudinally during human cortical development, we performed a chromatin accessibility quantitative trait loci (caQTL) analysis in neural progenitor cells and their differentiated neuronal progeny from 92 donors. We identified 8,111 caQTLs in progenitors and 3,676 caQTLs in neurons, with highly temporal, cell-type specific effects. A subset (∼20%) of caQTLs were also associated with changes in gene expression. Motif-disrupting alleles of transcriptional activators generally led to decreases in chromatin accessibility, whereas motif-disrupting alleles of repressors led to increases in chromatin accessibility. By integrating cell-type specific caQTLs and brain-relevant genome-wide association data, we were able to fine-map loci and identify regulatory mechanisms underlying non-coding neuropsychiatric disorder risk variants.HighlightsGenetic variation alters chromatin architecture during human cortical developmentGenetic effects on chromatin accessibility are highly cell-type specificAlleles disrupting TF motifs generally decrease accessibility, except for repressorscaQTLs facilitate fine-mapping and inference of regulatory mechanisms of GWAS loci

Genetic risk for psychiatric illness is complex, so identification of shared molecular pathways where distinct forms of genetic risk might coincide is of substantial interest. A growing body of genetic and genomic studies suggest that such shared molecular pathways exist across disorders with different clinical presentations, such as schizophrenia and autism spectrum disorder (ASD). But how this relates to specific genetic risk factors is unknown. Further, whether some of the molecular changes identified in brain relate to potentially confounding antemortem or post-mortem factors is difficult to prove. We analyzed the transcriptome from the cortex and hippocampus of three mouse lines modeling human copy number variants (CNVs) associated with schizophrenia and ASD: Df(h15q13)/+, Df(h22q11)/+, and Df(h1q21)/+ which carry the 15q13.3 deletion, 22q11.2 deletion, and 1q21.1 deletion, respectively. Although we found very little overlap of differential expression at the level of individual genes, gene network analysis identified two modules of co-expressed genes that were dysregulated across all three mouse models. One module observed in both cortex and hippocampus was associated with neuronal energetics and firing rate, and overlapped with changes identified in post mortem human brain from SCZ and ASD patients. These data highlight aspects of convergent gene expression in mouse models harboring major risk alleles, and strengthen the connection between neuronal energetic dysfunction and neuropsychiatric disorders in humans.

An emerging challenge in neurodegenerative dementia is understanding how immune-associated genes and pathways contribute to disease. To achieve a refined view of neuroinflammatory signaling across neurodegeneration, we took an integrative functional genomics approach to consider neurodegeneration from the perspective of microglia and their interactions with other cells. Using large-scale gene expression and perturbation data, regulatory motif analysis, and gene knockout studies, we identify and characterize a microglial-centric network involving distinct gene co-expression modules associated with progressive stages of neurodegeneration. These modules, which are conserved from mouse to human, differentially incorporate specific immune sensors of cellular damage and pathways that are predicted to eventually tune the immune response toward chronic inflammation and immune suppression. Notably, common genetic risk for Alzheimer’s disease (AD), Frontotemporal dementia (FTD) and Progressive Supranuclear Palsy (PSP) resides in specific modules that distinguish between the disorders, but also show convergence on pathways related to anti-viral defense mechanisms. These results suggest a model wherein combinatorial microglial-immune signaling integrate specific immune activators and disease genes that lead to the establishment of chronic states of simultaneous inflammation and immunosuppression involving type 1 interferon in these dementias.

Neurodevelopmental disorders are highly heritable and associated with spatially-selective disruptions of brain anatomy. The logic that translates genetic risks into spatially patterned brain vulnerabilities remains unclear but is a fundamental question in disease pathogenesis. Here, we approach this question by integrating (i)in vivoneuroimaging data from patient subgroups with known causal genomic copy number variations (CNVs), and (ii) bulk and single-cell gene expression data from healthy cortex. First, for each of six different CNV disorders, we show that spatial patterns of cortical anatomy change in youth are correlated with spatial patterns of expression for CNV region genes in bulk cortical tissue from typically-developing adults. Next, by transforming normative bulk-tissue cortical expression data into cell-type expression maps, we further link each disorder’s anatomical change map to specific cell classes and specific CNV-region genes that these cells express. Finally, we establish convergent validity of this “transcriptional vulnerability model” by inter-relating patient neuroimaging data with measures of altered gene expression in both brain and blood-derived patient tissue. Our work clarifies general biological principles that govern the mapping of genetic risks onto regional brain disruption in neurodevelopmental disorders. We present new methods that can harness these principles to screen for potential cellular and molecular determinants of disease from readily available patient neuroimaging data.

Background22q11.2 copy number variants (CNVs) are among the most highly penetrant genetic risk variants for developmental neuropsychiatric disorders such as schizophrenia (SCZ) and autism spectrum disorder (ASD). However, the specific mechanisms through which they confer risk remain unclear.MethodsUsing a functional genomics approach, we integrated transcriptomic data from the developing human brain, genome-wide association findings for SCZ and ASD, protein interaction data, and pathophysiological signatures of SCZ and ASD to: 1) organize genes into the developmental cellular and molecular systems within which they operate; 2) identify neurodevelopmental processes associated with polygenic risk for SCZ and ASD across the allelic frequency spectrum; and 3) elucidate pathways and individual genes through which 22q11.2 CNVs may confer risk for each disorder.ResultsPolygenic risk for SCZ and ASD converged on partially overlapping gene networks involved in synaptic function and transcriptional regulation, with ASD risk variants additionally enriched for networks involved in neuronal differentiation during fetal development. The 22q11.2 locus formed a large protein network that disproportionately affected SCZ- and ASD-associated neurodevelopmental networks, including loading highly onto synaptic and gene regulatory pathways.SEPT5, PI4KA, andSNAP29genes are candidate drivers of 22q11.2 synaptic pathology relevant to SCZ and ASD, andDGCR8andHIRAare candidate drivers of disease-relevant alterations in gene regulation.ConclusionsThe current approach provides a powerful framework to identify neurodevelopmental processes affected by diverse risk variants for SCZ and ASD, and elucidate the mechanisms through which highly penetrant multi-gene CNVs contribute to disease risk.

SummaryWe present the largest exome sequencing study of autism spectrum disorder (ASD) to date (n=35,584 total samples, 11,986 with ASD). Using an enhanced Bayesian framework to integrate de novo and case-control rare variation, we identify 102 risk genes at a false discovery rate ≤ 0.1. Of these genes, 49 show higher frequencies of disruptive de novo variants in individuals ascertained for severe neurodevelopmental delay, while 53 show higher frequencies in individuals ascertained for ASD; comparing ASD cases with mutations in these groups reveals phenotypic differences. Expressed early in brain development, most of the risk genes have roles in regulation of gene expression or neuronal communication (i.e., mutations effect neurodevelopmental and neurophysiological changes), and 13 fall within loci recurrently hit by copy number variants. In human cortex single-cell gene expression data, expression of risk genes is enriched in both excitatory and inhibitory neuronal lineages, consistent with multiple paths to an excitatory/inhibitory imbalance underlying ASD.

Author(s): Walker, Rebecca | Advisor(s): Geschwind, Daniel H | Abstract: Neurodevelopmental and neuropsychiatric diseases, such as autism spectrum disorder (ASD) and schizophrenia (SCZ), are highly heritable, with hundreds of risk loci contributing to disease risk identified through large-scale genomic studies. The ability to interpret these susceptibility variants and their contributions to disease has been difficult due to the fact that many of these variants fall in non-coding regions of the genome, or in regions of high linkage disequilibrium. Given the non-coding nature of the majority of these variants, as well as their enrichment in known enhancers, many of these variants are predicted to regulate gene expression, which is known to be dependent on tissue, cell type and developmental stage. Here, I have characterized functional genetic variation controlling transcriptional regulation in developing human brain to dissect common variation contributing to neurodevelopmental and early onset neuropsychiatric diseases, characterized by phenotypes originating in utero or early postnatal life. I have comprehensively profiled expression and splicing levels by RNA sequencing and high-density genotyping in 201 mid-gestational human brains and have performed expression and splicing quantitative trait loci analysis, which is currently the largest eQTL study in the developing brain. I identified 7962 expression QTL (eQTL) and 4635 splice QTL (sQTL), including several thousand fetal-specific regulatory regions when compared to published QTL studies of the adult brain. I leveraged these eQTL and sQTL to identify splicing and transcriptional drivers affected by human genetic variation, by significant enrichment in experimentally determined transcription factor, DNA binding proteins, and RNA bringing proteins binding sides. Further integration with experimental transcription factor knockdown data provide evidence that the regulatory regions identified through the eQTL and sQTL analysis are functional and validate that the changes seen in gene expression levels and/or splicing are likely due to the transcription factor’s role in regulating that gene. By integration with GWAS, I characterized the genes and isoforms contributing to specific neuropsychiatric disorders, including SCZ and ASD, as well as other cognitive or behavioral-related phenotypes. Specifically showing prenatal brain regulatory regions are significantly enriched for SCZ GWAS risk in a complimentary and additive manner to adult brain regulatory regions. I then perform gene co-expression network analysis and identify co-expressed modules of genes representing distinct biological processes in the developing brain. By integrating the QTL identified gene regulatory regions with co-expression modules and GWAS risk loci, I find SCZ and ASD impact distinct developmental gene co-expression modules. Yet, in both disorders, common and rare genetic variation converge. In ASD this convergence also implicates a specific cell type as well, superficial cortical neurons. Additionally, integration of eQTL and sQTL with GWAS via transcriptome wide association identified dozens of novel candidate risk genes, highlighting shared and stage-specific mechanisms in SCZ. These analyses demonstrate the highly distinctive effects of transcriptional control, as well as divergent age-related contributions to disease. More broadly, these findings demonstrate the genetic mechanisms by which early developmental events have a striking and widespread influence on adult anatomical and behavioral phenotypes.

Autism spectrum disorder (ASD) is a genetically complex, clinically heterogeneous neurodevelopmental disease. Recently, our understanding of the molecular abnormalities in ASD has been expanded through transcriptomic analyses of postmortem brains. However, a crucial molecular pathway involved in synaptic development, RNA editing, has not yet been studied on a genome-wide scale. Here, we profiled the global patterns of adenosine-to-inosine (A-to-I) editing in a large cohort of post-mortem ASD brains. Strikingly, we observed a global bias of hypo-editing in ASD brains, common to different brain regions and involving many genes with known neurobiological functions. Through genome-wide protein-RNA binding analyses and detailed molecular assays, we show that the Fragile X proteins, FMRP and FXR1P, interact with ADAR proteins and modulate A-to-I editing. Furthermore, we observed convergent patterns of RNA editing alterations in ASD and Fragile X syndrome, thus establishing RNA editing as a molecular link underlying these two highly related diseases. Our findings support a role for RNA editing dysregulation in ASD and highlight novel mechanisms for RNA editing regulation.

During organogenesis, patterns and gradients of gene expression underlie organization and diversified cell specification to generate complex tissue architecture. While the cerebral cortex is organized into six excitatory neuronal layers, it is unclear whether glial cells are diversified to mimic neuronal laminae or show distinct layering. To determine the molecular architecture of the mammalian cortex, we developed a high content pipeline that can quantify single-cell gene expression in situ. The Large-area Spatial Transcriptomic (LaST) map confirmed expected cortical neuron layer organization and also revealed a novel neuronal identity signature. Screening 46 candidate genes for astrocyte diversity across the cortex, we identified grey matter superficial, mid and deep astrocyte identities in gradient layer patterns that were distinct from neurons. Astrocyte layers formed in early postnatal cortex and mostly persisted in adult mouse and human cortex. Mutations that shifted neuronal post-mitotic identity or organization were sufficient to alter glial layering, indicating an instructive role for neuronal cues. In normal mouse cortex, astrocyte layer patterns showed area diversity between functionally distinct cortical regions. These findings indicate that excitatory neurons and astrocytes cells are organized into distinct lineage-associated laminae, which give rise to higher order neuroglial complexity of cortical architecture.

Defining the number, proportion, or lineage of distinct cell types in the developing human brain is an important goal of modern brain research. We defined single cell transcriptomic profiles for 40,000 cells at mid-gestation to identify cell types in the developing human neocortex. We define expression profiles corresponding to all known major cell types at this developmental period and identify multiple transcription factors and co-factors expressed in specific cell types, providing an unprecedented resource for understanding human neocortical development including the first single-cell characterization of human subplate neurons. We characterize major developmental trajectories during early neurogenesis, showing that cell type differentiation occurs on a continuum that involves transitions that tie cell cycle progression with early cell fate decisions. We use these data to deconvolute regulatory networks and map neuropsychiatric disease genes to specific cell types, implicating dysregulation of specific cell types, as the mechanistic underpinnings of several neurodevelopmental disorders. Together these results provide an extensive catalog of cell types in human neocortex and extend our understanding of early cortical development, human brain evolution and the cellular basis of neuropsychiatric disease.One Sentence SummaryComprehensive single cell transcriptomes in developing human cortex inform models of cell diversity, differentiation and disease risk.

Autism spectrum disorder (ASD) encompasses a collection of complex neuropsychiatric disorders characterized by deficits in social functioning, communication and repetitive behavior. Building on recent studies supporting a role for developmentally moderated regulatory genomic variation in the molecular etiology of ASD, we quantified genome-wide patterns of DNA methylation in 233 post-mortem tissues samples isolated from three brain regions (prefrontal cortex, temporal cortex and cerebellum) dissected from 43 ASD patients and 38 non-psychiatric control donors. We identified widespread differences in DNA methylation associated with idiopathic ASD (iASD), with consistent signals in both cortical regions that were distinct to those observed in the cerebellum. Individuals carrying a duplication on chromosome 15q (dup15q), representing a genetically-defined subtype of ASD, were characterized by striking differences in DNA methylation across a discrete domain spanning an imprinted gene cluster within the duplicated region. In addition to the dramatic cis-effects on DNA methylation observed in dup15q carriers, we identified convergent methylomic signatures associated with both iASD and dup15q, reflecting the findings from previous studies of gene expression and H3K27ac. Cortical co-methylation network analysis identified a number of co-methylated modules significantly associated with ASD that are enriched for genomic regions annotated to genes involved in the immune system, synaptic signalling and neuronal regulation. Our study represents the first systematic analysis of DNA methylation associated with ASD across multiple brain regions, providing novel evidence for convergent molecular signatures associated with both idiopathic and syndromic autism.

Genetic studies of autism spectrum disorder (ASD) have revealed a complex, heterogeneous architecture, in which the contribution of rare inherited variation remains relatively un-explored. We performed whole-genome sequencing (WGS) in 2,308 individuals from families containing multiple affected children, including analysis of single nucleotide variants (SNV) and structural variants (SV). We identified 16 new ASD-risk genes, including many supported by inherited variation, and provide statistical support for 69 genes in total, including previously implicated genes. These risk genes are enriched in pathways involving negative regulation of synaptic transmission and organelle organization. We identify a significant protein-protein interaction (PPI) network seeded by inherited, predicted damaging variants disrupting highly constrained genes, including members of the BAF complex and established ASD risk genes. Analysis of WGS also identified SVs effecting non-coding regulatory regions in developing human brain, implicating NR3C2 and a recurrent 2.5Kb deletion within the promoter of DLG2. These data lend support to studying multiplex families for identifying inherited risk for ASD. We provide these data through the Hartwell Autism Research and Technology Initiative (iHART), an open access cloud-computing repository for ASD genetics research.

Loss of function mutations in CNTNAP2 cause a syndromic form of autism spectrum disorder (ASD) in humans and produce social deficits, repetitive behaviors, and seizures in mice. Yet, the functional effects of these mutations at the cellular and circuit level remain elusive. Using laser scanning photostimulation, whole-cell recordings, and electron microscopy, we found a dramatic decrease in functional excitatory and inhibitory synaptic inputs in L2/3 medial prefrontal cortex (mPFC) of Cntnap2 knock-out (KO) mice. In accordance with decreased synaptic input, KO mice displayed reduced spine and synapse densities, despite normal intrinsic excitability and dendritic complexity. To determine how this decrease in synaptic inputs alters coordination of neuronal firing patterns in vivo, we recorded mPFC local field potentials (LFP) and unit spiking in head-fixed mice during locomotion and rest. In KO mice, LFP power was not significantly altered at all tested frequencies, but inhibitory neurons showed delayed phase-firing and reduced phase-locking to delta and theta oscillations during locomotion. Excitatory neurons showed similar changes but only to delta oscillations. These findings suggest that profound ASD-related alterations in synaptic inputs can yield perturbed temporal coordination of cortical ensembles.

Identification of mechanisms underlying the incidence of psychiatric disorders has been hampered by the difficulty in discovering highly-predictive environmental risk factors. For example, prior efforts have failed to establish environmental effects predicting geospatial clustering of schizophrenia incidence beyond urban-rural differences. Here, we employ a novel statistical framework for decomposing the geospatial risk for schizophrenia based on locale of upbringing (place of residence, ages 0-7 years) and its synergistic effects with genetic liabilities (polygenic risk for schizophrenia). We use this statistical framework to analyze unprecedented geolocation and genotyping data in a case-cohort study of n=24,028 subjects, drawn from the 1.47 million Danish persons born between 1981 and 2005. Using this framework we estimate the effects of upbringing locale (E) and gene-by-locale interactions (GxE). After controlling for potential confounding variables, upbringing at high-risk locales increases the risk for schizophrenia on average by 122%, while GxE modulates genetic risk for schizophrenia on average by 78%. Within the boundaries of Copenhagen (the largest and most densely populated city of Denmark) specific locales vary substantially in their E and GxE effects, with hazard ratios ranging from 0.26 to 9.26 for E and from 0.20 to 5.95 for GxE. This study provides insight into the degree of geospatial clustering of schizophrenia risk, and our novel analytic procedure provides a framework for decomposing variation in geospatial risk into G, E, and GxE components.

Autism spectrum disorder (ASD) is a highly heritable and heterogeneous group of neurodevelopmental phenotypes diagnosed in more than 1% of children. Common genetic variants contribute substantially to ASD susceptibility, but to date no individual variants have been robustly associated with ASD. With a marked sample size increase from a unique Danish population resource, we report a genome-wide association meta-analysis of 18,381 ASD cases and 27,969 controls that identifies five genome-wide significant loci. Leveraging GWAS results from three phenotypes with significantly overlapping genetic architectures (schizophrenia, major depression, and educational attainment), seven additional loci shared with other traits are identified at equally strict significance levels. Dissecting the polygenic architecture we find both quantitative and qualitative polygenic heterogeneity across ASD subtypes, in contrast to what is typically seen in other complex disorders. These results highlight biological insights, particularly relating to neuronal function and corticogenesis and establish that GWAS performed at scale will be much more productive in the near term in ASD, just as it has been in a broad range of important psychiatric and diverse medical phenotypes.

SummaryDe novo mutations in hundreds of different genes collectively cause 25-42% of severe developmental disorders (DD). The cause in the remaining cases is largely unknown. The role of de novo mutations in regulatory elements affecting known DD associated genes or other genes is essentially unexplored. We identified de novo mutations in three classes of putative regulatory elements in almost 8,000 DD patients. Here we show that de novo mutations in highly conserved fetal-brain active elements are significantly and specifically enriched in neurodevelopmental disorders. We identified a significant two-fold enrichment of recurrently mutated elements. We estimate that, genome-wide, de novo mutations in fetaLbrain active elements are likely to be causal for 1-3% of patients without a diagnostic coding variant and that only a small fraction (de novo mutations in these elements are pathogenic. Our findings represent a robust estimate of the contribution of de novo mutations in regulatory elements to this genetically heterogeneous set of disorders, and emphasise the importance of combining functional and evolutionary evidence to delineate regulatory causes of genetic disorders.

ImportanceThe genetic relationship between cognition, autism, and schizophrenia is complex. It is unclear how genes that contribute to cognition also contribute to risk for autism and schizophrenia.ObjectiveTo investigate the interaction between genes related to cognition (measured via proxy through educational attainment, which we call ‘edu genes’) and genes/biological pathways that are atypical in autism and schizophrenia.DesignGenetic correlation and enrichment analysis were conducted to identify the interaction between edu genes and risk genes and biological pathways for autism or schizophrenia.ResultsFirst, edu genes are enriched in a specific developmental co-expression module that is also enriched for high confidence autism risk genes. Second, modules enriched for genes that are dysregulated in autism and schizophrenia are also enriched for edu genes. Finally, genes that overlap between the two above modules and educational attainment are significantly enriched for genes that flank human accelerated regions, suggesting increased positive selection for the overlapping gene sets.ConclusionOur results identify distinct co-expression modules where risk genes for the two psychiatric conditions interact with edu genes. This suggests specific pathways that contribute to both cognitive deficits and cognitive talents, in individuals with schizophrenia or autism.Key PointsQuestionHow do genes for educational attainment interact with risk genes for autism and schizophrenia?FindingsWe show that genes for educational attainment (edu genes) are significantly likely to be mutated in autism and intellectual disability. We further show that edu genes also interact with co-expression modules that are associated with autism or schizophrenia and are enriched for differentially expressed genes in autism or schizophrenia. Finally, we identify that the enrichment between risk genes for autism and schizophrenia and human accelerated regions are driven, in part, by their overlap with edu genes.MeaningEdu genes interact with schizophrenia and autism risk genes in specific pathways, contributing to both cognitive deficits and talents.

SummaryWe apply transcriptome-wide RNA sequencing in postmortem autism spectrum disorder (ASD) brain and controls and identify convergent alterations in the noncoding transcriptome, including primate specific lncRNA, and transcript splicing in ASD cerebral cortex, but not cerebellum. We characterize an attenuation of patterning between frontal and temporal cortex in ASD and identify SOX5, a transcription factor involved in cortical neuron fate specification, as a likely driver of this pattern. We further show that a genetically defined subtype of ASD, Duplication 15q Syndrome, shares the core transcriptomic signature of idiopathic ASD, indicating that observed molecular convergence in autism brain is the likely consequence of manifold genetic alterations. Using co-expression network analysis, we show that diverse forms of genetic risk for ASD affect convergent, independently replicated, biological pathways and provide an unprecedented resource for understanding the molecular alterations associated with ASD in humans.

Recent large-scale studies have identified multiple genetic risk factors for mental illness and indicate a complex, polygenic, and pleiotropic genetic architecture for neuropsychiatric disease. However, little is known about how genetic variants yield brain dysfunction or pathology. We use transcriptomic profiling as an unbiased, quantitative readout of molecular phenotypes across 5 major psychiatric disorders, including autism (ASD), schizophrenia (SCZ), bipolar disorder (BD), depression (MDD), and alcoholism (AAD), compared with carefully matched controls. We identify a clear pattern of shared and distinct gene-expression perturbations across these conditions, identifying neuronal gene co-expression modules downregulated across ASD, SCZ, and BD, and astrocyte related modules most prominently upregulated in ASD and SCZ. Remarkably, the degree of sharing of transcriptional dysregulation was strongly related to polygenic (SNP-based) overlap across disorders, indicating a significant genetic component. These findings provide a systems-level view of the neurobiological architecture of major neuropsychiatric illness and demonstrate pathways of molecular convergence and specificity.

Neurodegenerative dementias are clinically heterogeneous, progressive diseases with frequently overlapping symptoms, such as cognitive impairments and behavior and movement deficits. Although a majority of cases appear to be sporadic, there is a large genetic component that has yet to be fully explained. Here, we review the recent genetic and genomic findings pertaining to Alzheimer’s disease, frontotemporal dementia, Lewy body dementia, and prion dementia. In this review, we describe causal and susceptibility genes identified for these dementias and discuss recent research pertaining to the molecular function of these genes. Of particular interest, there is a large overlap in clinical phenotypes, genes, and/or aggregating protein products involved in these diseases, as well as frequent comorbid presentation, indicating that these dementias may represent a continuum of syndromes rather than individual diseases.