Publications
46 results found
Coleman JRI, Bryois J, Gaspar HA, et al., 2019, Biological annotation of genetic loci associated with intelligence in a meta-analysis of 87,740 individuals, MOLECULAR PSYCHIATRY, Vol: 24, Pages: 182-197, ISSN: 1359-4184
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- Citations: 30
Komiyama NH, van de Lagemaat LN, Stanford LE, et al., 2018, Synaptic combinatorial molecular mechanisms generate repertoires of innate and learned behavior
<jats:title>Abstract</jats:title><jats:p>Although molecular mechanisms underpinning specific behaviors have been described, whether there are mechanisms that orchestrate a behavioral repertoire is unknown. To test if the postsynaptic proteome of excitatory synapses could impart such a mechanism we conducted the largest genetic study of mammalian synapses yet undertaken. A repertoire of sixteen innate and learned behaviors was assessed from 290,850 measures in 55 lines of mutant mice carrying targeted mutations in the principal classes of postsynaptic proteins. Each innate and learned behavior used a different combination of proteins. These combinations were comprised of proteins that amplified or attenuated the magnitude of each behavioral response. All behaviors required proteins found in PSD95 supercomplexes. We show the vertebrate increase in proteome complexity drove an expansion in behavioral repertoires and generated susceptibility to a wide range of diseases. Our results reveal a molecular mechanism that generates a versatile and complex behavioral repertoire that is central to human behavioral disorders.</jats:p>
Nguyen HT, Dobbyn A, Charney AW, et al., 2018, Integrative analysis of rare variants and pathway information shows convergent results between immune pathways, drug targets and epilepsy genes
<jats:title>Abstract</jats:title><jats:p>Trio family and case-control studies of next-generation sequencing data have proven integral to understanding the contribution of rare inherited and<jats:italic>de novo</jats:italic>single-nucleotide variants to the genetic architecture of complex disease. Ideally, such studies should identify individual risk genes of moderate to large effect size to generate novel treatment hypotheses for further follow-up. However, due to insufficient power, gene set enrichment analyses have come to be relied upon for detecting differences between cases and controls, implicating sets of hundreds of genes rather than specific targets for further investigation. Here, we present a Bayesian statistical framework, termed gTADA, that integrates gene-set membership information with gene-level<jats:italic>de novo</jats:italic>and rare inherited case-control counts, to prioritize risk genes with excess rare variant burden within enriched gene sets. Applying gTADA to available whole-exome sequencing datasets for several neuropsychiatric conditions, we replicated previously reported gene set enrichments and identified novel risk genes. For epilepsy, gTADA prioritized 40 risk genes (posterior probabilities > 0.95), 6 of which replicate in an independent whole-genome sequencing study. In addition, 30/40 genes are novel genes. We found that epilepsy genes had high protein-protein interaction (PPI) network connectivity, and show specific expression during human brain development. Some of the top prioritized EPI genes were connected to a PPI subnetwork of immune genes and show specific expression in prenatal microglia. We also identified multiple enriched drug-target gene sets for EPI which included immunostimulants as well as known antiepileptics. Immune biology was supported specifically by case-control variants from familial epilepsies rather than do novo mutations in generalized encephalitic epilepsy.<
Zhu F, Cizeron M, Qiu Z, et al., 2018, Architecture of the mouse brain synaptome, Neuron, Vol: 99, Pages: 781-799.e10, ISSN: 0896-6273
Synapses are found in vast numbers in the brain and contain complex proteomes. We developed genetic labeling and imaging methods to examine synaptic proteins in individual excitatory synapses across all regions of the mouse brain. Synapse catalogs were generated from the molecular and morphological features of a billion synapses. Each synapse subtype showed a unique anatomical distribution and each brain region showed a distinct signature of synapse subtypes. Whole brain synaptome cartography revealed spatial architecture from dendritic to global systems levels and previously unknown anatomical features. Synaptome mapping of circuits showed correspondence between synapse diversity and structural and functional connectomes. Behaviorally relevant patterns of neuronal activity trigger spatio-temporal postsynaptic responses sensitive to the structure of synaptome maps. Areas controlling higher cognitive function contain greatest synapse diversity and mutations causing cognitive disorders reorganized synaptome maps. Synaptome technology and resources have wide-ranging application in studies of the normal and diseased brain.
Munoz-Manchado AB, Gonzales CB, Zeisel A, et al., 2018, Diversity of interneurons in the dorsal striatum revealed by single-cell RNA sequencing and PatchSeq, Cell Reports, Vol: 24, Pages: 2179-2190.e1-e7, ISSN: 2211-1247
Striatal locally projecting neurons, or interneurons, act on nearby circuits and shape functional output to the rest of the basal ganglia. We performed single-cell RNA sequencing of striatal cells enriching for interneurons. We find seven discrete interneuron types, six of which are GABAergic. In addition to providing specific markers for the populations previously described, including those expressing Sst/Npy, Th, Npy without Sst, and Chat, we identify two small populations of cells expressing Cck with or without Vip. Surprisingly, the Pvalb-expressing cells do not constitute a discrete cluster but rather are part of a larger group of cells expressing Pthlh with a spatial gradient of Pvalb expression. Using PatchSeq, we show that Pthlh cells exhibit a continuum of electrophysiological properties correlated with expression of Pvalb. Furthermore, we find significant molecular differences that correlate with differences in electrophysiological properties between Pvalb-expressing cells of the striatum and those of the cortex.
Zeisel A, Hochgerner H, Lönnerberg P, et al., 2018, Molecular architecture of the mouse nervous system, Cell, Vol: 174, Pages: 999-1014.e22, ISSN: 0092-8674
The mammalian nervous system executes complex behaviors controlled by specialized, precisely positioned, and interacting cell types. Here, we used RNA sequencing of half a million single cells to create a detailed census of cell types in the mouse nervous system. We mapped cell types spatially and derived a hierarchical, data-driven taxonomy. Neurons were the most diverse and were grouped by developmental anatomical units and by the expression of neurotransmitters and neuropeptides. Neuronal diversity was driven by genes encoding cell identity, synaptic connectivity, neurotransmission, and membrane conductance. We discovered seven distinct, regionally restricted astrocyte types that obeyed developmental boundaries and correlated with the spatial distribution of key glutamate and glycine neurotransmitters. In contrast, oligodendrocytes showed a loss of regional identity followed by a secondary diversification. The resource presented here lays a solid foundation for understanding the molecular architecture of the mammalian nervous system and enables genetic manipulation of specific cell types.
Nagel M, Jansen PR, Stringer S, et al., 2018, Meta-analysis of genome-wide association studies for neuroticism in 449,484 individuals identifies novel genetic loci and pathways, NATURE GENETICS, Vol: 50, Pages: 920-+, ISSN: 1061-4036
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- Citations: 317
Savage JE, Jansen PR, Stringer S, et al., 2018, Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence, Nature Genetics, Vol: 50, Pages: 912-919, ISSN: 1061-4036
Intelligence is highly heritable1 and a major determinant of human health and well-being. Recent genome-wide meta-analyses have identified 24 genomic loci linked to variation in intelligence, but much about its genetic underpinnings remains to be discovered. Here, we present a large-scale genetic association study of intelligence (n = 269,867), identifying 205 associated genomic loci (190 new) and 1,016 genes (939 new) via positional mapping, expression quantitative trait locus (eQTL) mapping, chromatin interaction mapping, and gene-based association analysis. We find enrichment of genetic effects in conserved and coding regions and associations with 146 nonsynonymous exonic variants. Associated genes are strongly expressed in the brain, specifically in striatal medium spiny neurons and hippocampal pyramidal neurons. Gene set analyses implicate pathways related to nervous system development and synaptic structure. We confirm previous strong genetic correlations with multiple health-related outcomes, and Mendelian randomization analysis results suggest protective effects of intelligence for Alzheimer’s disease and ADHD and bidirectional causation with pleiotropic effects for schizophrenia. These results are a major step forward in understanding the neurobiology of cognitive function as well as genetically related neurological and psychiatric disorders.
Harris KD, Hochgerner H, Skene NG, et al., 2018, Classes and continua of hippocampal CA1 inhibitory neurons revealed by single-cell transcriptomics, PLoS Biology, Vol: 16, ISSN: 1544-9173
Understanding any brain circuit will require a categorization of its constituent neurons. In hippocampal area CA1, at least 23 classes of GABAergic neuron have been proposed to date. However, this list may be incomplete; additionally, it is unclear whether discrete classes are sufficient to describe the diversity of cortical inhibitory neurons or whether continuous modes of variability are also required. We studied the transcriptomes of 3,663 CA1 inhibitory cells, revealing 10 major GABAergic groups that divided into 49 fine-scale clusters. All previously described and several novel cell classes were identified, with three previously described classes unexpectedly found to be identical. A division into discrete classes, however, was not sufficient to describe the diversity of these cells, as continuous variation also occurred between and within classes. Latent factor analysis revealed that a single continuous variable could predict the expression levels of several genes, which correlated similarly with it across multiple cell types. Analysis of the genes correlating with this variable suggested it reflects a range from metabolically highly active faster-spiking cells that proximally target pyramidal cells to slower-spiking cells targeting distal dendrites or interneurons. These results elucidate the complexity of inhibitory neurons in one of the simplest cortical structures and show that characterizing these cells requires continuous modes of variation as well as discrete cell classes.
Skene NG, Bryois JD, Bakken TE, et al., 2018, Genetic identification of brain cell types underlying schizophrenia, Nature Genetics, Vol: 50, Pages: 825-833, ISSN: 1061-4036
With few exceptions, the marked advances in knowledge about the genetic basis of schizophrenia have not converged on findings that can be confidently used for precise experimental modeling. By applying knowledge of the cellular taxonomy of the brain from single-cell RNA sequencing, we evaluated whether the genomic loci implicated in schizophrenia map onto specific brain cell types. We found that the common-variant genomic results consistently mapped to pyramidal cells, medium spiny neurons (MSNs) and certain interneurons, but far less consistently to embryonic, progenitor or glial cells. These enrichments were due to sets of genes that were specifically expressed in each of these cell types. We also found that many of the diverse gene sets previously associated with schizophrenia (genes involved in synaptic function, those encoding mRNAs that interact with FMRP, antipsychotic targets, etc.) generally implicated the same brain cell types. Our results suggest a parsimonious explanation: the common-variant genetic results for schizophrenia point at a limited set of neurons, and the gene sets point to the same cells. The genetic risk associated with MSNs did not overlap with that of glutamatergic pyramidal cells and interneurons, suggesting that different cell types have biologically distinct roles in schizophrenia.
Savage JE, Jansen PR, Stringer S, et al., 2018, GWAS meta-analysis (N=279,930) identifies new genes and functional links to general cognitive ability, Publisher: BIOMED CENTRAL LTD, ISSN: 1473-9542
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- Citations: 1
Roy M, Sorokina O, Skene N, et al., 2018, Proteomic analysis of postsynaptic proteins in regions of the human neocortex, Nature Neuroscience, Vol: 21, Pages: 130-138, ISSN: 1097-6256
The postsynaptic proteome of excitatory synapses comprises ~1,000 highly conserved proteins that control the behavioral repertoire, and mutations disrupting their function cause >130 brain diseases. Here, we document the composition of postsynaptic proteomes in human neocortical regions and integrate it with genetic, functional and structural magnetic resonance imaging, positron emission tomography imaging, and behavioral data. Neocortical regions show signatures of expression of individual proteins, protein complexes, biochemical and metabolic pathways. We characterized the compositional signatures in brain regions involved with language, emotion and memory functions. Integrating large-scale GWAS with regional proteome data identifies the same cortical region for smoking behavior as found with fMRI data. The neocortical postsynaptic proteome data resource can be used to link genetics to brain imaging and behavior, and to study the role of postsynaptic proteins in localization of brain functions.
Skene NG, Roy M, Grant SGN, 2017, A genomic lifespan program that reorganises the young adult brain is targeted in schizophrenia, eLife, Vol: 6, ISSN: 2050-084X
The genetic mechanisms regulating the brain and behaviour across the lifespan are poorly understood. We found that lifespan transcriptome trajectories describe a calendar of gene regulatory events in the brain of humans and mice. Transcriptome trajectories defined a sequence of gene expression changes in neuronal, glial and endothelial cell-types, which enabled prediction of age from tissue samples. A major lifespan landmark was the peak change in trajectories occurring in humans at 26 years and in mice at 5 months of age. This species-conserved peak was delayed in females and marked a reorganization of expression of synaptic and schizophrenia-susceptibility genes. The lifespan calendar predicted the characteristic age of onset in young adults and sex differences in schizophrenia. We propose a genomic program generates a lifespan calendar of gene regulation that times age-dependent molecular organization of the brain and mutations that interrupt the program in young adults cause schizophrenia.
Skene NG, Grant SGN, 2016, Identification of vulnerable cell types in major brain disorders using single cell transcriptomes and expression weighted cell type enrichment, Frontiers in Neuroscience, Vol: 10, Pages: 1-11, ISSN: 1662-453X
The cell types that trigger the primary pathology in many brain diseases remain largely unknown. One route to understanding the primary pathological cell type for a particular disease is to identify the cells expressing susceptibility genes. Although this is straightforward for monogenic conditions where the causative mutation may alter expression of a cell type specific marker, methods are required for the common polygenic disorders. We developed the Expression Weighted Cell Type Enrichment (EWCE) method that uses single cell transcriptomes to generate the probability distribution associated with a gene list having an average level of expression within a cell type. Following validation, we applied EWCE to human genetic data from cases of epilepsy, Schizophrenia, Autism, Intellectual Disability, Alzheimer's disease, Multiple Sclerosis and anxiety disorders. Genetic susceptibility primarily affected microglia in Alzheimer's and Multiple Sclerosis; was shared between interneurons and pyramidal neurons in Autism and Schizophrenia; while intellectual disabilities and epilepsy were attributable to a range of cell-types, with the strongest enrichment in interneurons. We hypothesized that the primary cell type pathology could trigger secondary changes in other cell types and these could be detected by applying EWCE to transcriptome data from diseased tissue. In Autism, Schizophrenia and Alzheimer's disease we find evidence of pathological changes in all of the major brain cell types. These findings give novel insight into the cellular origins and progression in common brain disorders. The methods can be applied to any tissue and disorder and have applications in validating mouse models.
Skrzypiec AE, Shah RS, Schiavon E, et al., 2013, Stress-induced lipocalin-2 controls dendritic spine formation and neuronal activity in the amygdala, PLoS ONE, Vol: 8, ISSN: 1932-6203
Behavioural adaptation to psychological stress is dependent on neuronal plasticity and dysfunction at this cellular level may underlie the pathogenesis of affective disorders such as depression and post-traumatic stress disorder. Taking advantage of genome-wide microarray assay, we performed detailed studies of stress-affected transcripts in the amygdala – an area which forms part of the innate fear circuit in mammals. Having previously demonstrated the role of lipocalin-2 (Lcn-2) in promoting stress-induced changes in dendritic spine morphology/function and neuronal excitability in the mouse hippocampus, we show here that the Lcn-2 gene is one of the most highly upregulated transcripts detected by microarray analysis in the amygdala after acute restraint-induced psychological stress. This is associated with increased Lcn-2 protein synthesis, which is found on immunohistochemistry to be predominantly localised to neurons. Stress-naïve Lcn-2−/− mice show a higher spine density in the basolateral amygdala and a 2-fold higher rate of neuronal firing rate compared to wild-type mice. Unlike their wild-type counterparts, Lcn-2−/− mice did not show an increase in dendritic spine density in response to stress but did show a distinct pattern of spine morphology. Thus, amygdala-specific neuronal responses to Lcn-2 may represent a mechanism for behavioural adaptation to psychological stress.
Coba MP, Komiyama NH, Nithianantharajah J, et al., 2012, TNiK Is Required for Postsynaptic and Nuclear Signaling Pathways and Cognitive Function, JOURNAL OF NEUROSCIENCE, Vol: 32, Pages: 13987-13999, ISSN: 0270-6474
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- Citations: 65
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