Biology subjects

Owen, M. J.

Publications and source records attributed to Owen, M. J..

11 recordsLinked to original sources

bioRxiv2018

Haploinsufficiency of the schizophrenia risk gene Cyfip1 causes abnormal postnatal hippocampal neurogenesis through a novel microglia dependent mechanism

Genetic risk factors can significantly increase chances of developing psychiatric disorders, but the underlying biological processes through which this risk is effected remain largely unknown. Here we show that haploinsufficiency of Cyfip1, a candidate risk gene present in the pathogenic 15q11.2(BP1-BP2) deletion may impact on psychopathology via abnormalities in cell survival and migration of newborn neurons during postnatal hippocampal neurogenesis. We demonstrate that haploinsufficiency of Cyfip1 leads to increased numbers of adult born hippocampal neurons due to reduced apoptosis, without altering proliferation. We confirm this is due to a cell autonomous failure of microglia to induce apoptosis through the secretion of the appropriate factors. Furthermore, we show an abnormal migration of adult-born neurons due to altered Arp2/3 mediated actin dynamics. Together, our findings throw new light on how the genetic risk candidate Cyfip1 may influence the hippocampus, a brain region with strong evidence for involvement in psychopathology.

neuroscience↗

bioRxiv2018

A Transcriptome Wide Association Study implicates specific pre- and post-synaptic abnormalities in Schizophrenia

Schizophrenia is a complex highly heritable disorder. Genome-wide association studies have identified multiple loci that influence the risk of developing schizophrenia, although the causal variants driving these associations and their impacts on specific genes are largely unknown. Here we link genetic findings to gene expression in the human brain by performing a transcriptome-wide association study (TWAS) in which we integrate the largest published genome-wide association dataset of schizophrenia, with publically available post mortem expression data from the dorsolateral prefrontal cortex (DLPFC). We identify a significant correlation between schizophrenia risk and expression at eighty-nine genes in DLPFC, including forty-two genes not identified in earlier TWAS of this transcriptomic resource. Genes whose expression correlate with schizophrenia were enriched for those involved in nervous system development, abnormal synaptic transmission, reduced long term potentiation, and calcium-dependent cell-cell adhesion. Previous genetic studies have implicated post-synaptic glutamatergic and gabaergic processes in schizophrenia; here we extend this to include molecules that regulate presynaptic transmitter release. We identify specific candidate genes to which we assign predicted directions of effect in terms of expression level, facilitating downstream experimental studies geared towards a better mechanistic understanding of schizophrenia pathogenesis.

genetics↗

bioRxiv2018

The role of rare copy number variants in depression

The role of large, rare copy number variants (CNVs) in neurodevelopmental disorders is well-established,1-5 but their contribution to common psychiatric disorders, such as depression, remains unclear. We have previously shown that a substantial proportion of CNV enrichment in schizophrenia is explained by CNVs associated with neurodevelopmental disorders.6, 7 Depression shares genetic risk with schizophrenia8, 9 and is frequently comorbid with neurodevelopmental disorders10, 11, suggesting to us the hypothesis that if CNVs play a role in depression, neurodevelopmental CNVs are those most likely to be associated. We confirmed this in UK Biobank by showing that neurodevelopmental CNVs were associated with depression (24,575 cases, 5.87%; OR=1.36, 95% CI 1.22-1.51, p=1.61x10-8), whilst finding no evidence implicating other CNVs. Four individual neurodevelopmental CNVs increased risk of depression (1q21.1 duplication, PWS duplication, 16p13.11 deletion, 16p11.2 duplication). The association between neurodevelopmental CNVs and depression was partially explained by social deprivation but not by education attainment or physical illness.

neuroscience↗

bioRxiv2018

Effects of pathogenic CNVs on physical traits in participants of the UK Biobank

BackgroundCopy number variants (CNVs) have been shown to increase risk for physical anomalies, developmental, psychiatric and medical disorders. Some of them have been associated with changes in weight, height, and other physical traits. As most studies have been performed on children and young people, these effects of CNVs in adulthood are not well established.\n\nMethodsThe UK Biobank recruited half a million adults who provided a variety of physical measurements. We called all CNVs from the Affymetrix microarrays and selected a set of 54 CNVs implicated as pathogenic (including their reciprocal deletions/duplications) and that were present in five or more persons. Linear regression analysis was used to establish their association with 16 physical traits, relevant to human health.\n\nResults396,725 participants of white British or Irish descent (excluding first-degree relatives) passed our quality control filters. There were 214 CNV/trait associations significant at a false discovery rate of 0.1, most of them novel. These traits are associated with adverse health outcomes: e.g. increased weight, waist-to-hip ratio, pulse rate and body fat composition. Deletions at 16p11.2, 16p12.1, NRXN1 and duplications at 16p13.11 and 22q11.2 produced the highest numbers of significant associations. CNVs at 1q21.1, 2q13, 16p11.2, 16p11.2 distal, 16p12.1, 17p12 and 17q12 demonstrated one or more mirror image effects of deletions versus duplications.\n\nConclusionsCarriers of many CNVs should be monitored for physical traits that increase morbidity and mortality. Genes within these CNVs can give insights into biological processes and therapeutic interventions.

genetics↗

bioRxiv2018

Dynamic expression of risk genes for schizophrenia and bipolar disorder across development

AO_SCPCAPBSTRACTC_SCPCAPCommon genetic variation contributes a substantial proportion of risk for both schizophrenia and bipolar disorder. Furthermore, there is evidence of significant, but not complete, overlap in genetic risk between schizophrenia and bipolar disorder. It has been hypothesised that genetic variants conferring risk for these disorders do so by influencing brain development, leading to the later emergence of symptoms. The comparative profile of risk gene expression for schizophrenia and bipolar disorder across development over different brain regions however remains unclear. Using genotypes derived from genome wide associations studies of the largest available cohorts of patients and control subjects, we investigated whether genes enriched for schizophrenia and bipolar disorder association show a bias for expression across any of 13 developmental stages in prefrontal cortical and subcortical brain regions. We show that genes associated with schizophrenia have a strong bias towards increased expression in the prefrontal cortex during early midfetal development and early infancy, and decreased expression during late childhood which normalises in adolescence. Risk-associated genes for bipolar disorder shared this postnatal expression profile but did not exhibit a bias towards expression at any prenatal stage. These results emphasise the dynamic expression of genes harbouring risk for schizophrenia and bipolar disorder across prefrontal cortex development and support the view that prenatal neurodevelopmental events are more strongly associated with schizophrenia than bipolar disorder.

neuroscience↗

bioRxiv2018

Genetic risk for schizophrenia and developmental delay is associated with shape and microstructure of midline white matter structures

Genomic copy number variants (CNVs) are amongst the most highly penetrant genetic risk factors for neuropsychiatric disorders. The scarcity of carriers of individual CNVs and their phenotypical heterogeneity limits investigations of the associated neural mechanisms and endophenotypes. We applied a novel design based on CNV penetrance for schizophrenia and developmental delay that allows us to identify structural sequelae that are most relevant to neuropsychiatric disorders. Our focus on brain structural abnormalities was based on the hypothesis that convergent mechanisms contributing to neurodevelopmental disorders would likely manifest in the macro- and microstructure of white matter and cortical and subcortical grey matter. 21 adult participants carrying neuropsychiatric risk CNVs (including those located at 22q11.2, 15q11.2, 1q21.1, 16p11.2, and 17q12) and 15 age- and gender matched controls underwent T1-weighted structural, diffusion and quantitative T1 relaxometry MRI.\n\nThe macro- and microstructural properties of the cingulum bundles were associated with penetrance for both developmental delay and schizophrenia, in particular curvature along the anterior-posterior axis (Sz: pcorr=0.026; DD: pcorr=0.035) and intracellular volume fraction (Sz: pcorr=0.019; DD: pcorr=0.064) Further principal component analysis showed alterations in the interrelationships between the volumes of several mid-line white matter structures (Sz: pcorr=0.055; DD, pcorr=0.027). In particular, the ratio of volumes in the splenium and body of the corpus callosum was significantly associated with both penetrance scores (Sz: p=0.037; DD; p=0.006). Our results are consistent with the notion that a significant alteration in developmental trajectories of mid-line white-matter structures constitutes a common neurodevelopmental aberration contributing to risk for schizophrenia and intellectual disability.

neuroscience↗

bioRxiv2018

Medical consequences of pathogenic CNVs in adults: Analysis of the UK Biobank.

BackgroundGenomic copy number variants (CNVs) increase risk for early-onset neurodevelopmental disorders but their impact on medical outcomes in later life is poorly understood. The UK Biobank, with half a million well-phenotyped adults, presents an opportunity to study the medical consequences of CNV in middle and old age.\n\nMethodsWe called 54 CNVs associated with clinical phenotypes or genomic disorders, including their reciprocal deletions or duplications, in all Biobank participants. We used logistic regression analysis to test CNVs for associations with 58 common medical phenotypes.\n\nFindingsCNV carriers had an increased risk of developing 37 of the 58 phenotypes at nominal levels of statistical significance, with 19 associations surviving Bonferroni correction (p<8{middle dot}6x10-4). Tests of each of the 54 CNVs for association with each of the 58 phenotypes identified 18 associations that survived Bonferroni correction (p<1{middle dot}6x10-5) and a further 57 that were associated at a false discovery rate (FDR) threshold of 0{middle dot}1. Thirteen CNVs had three or more significant associations at FDR=0{middle dot}1, with the largest number of phenotypes (N=15) found for deletions at 16p11{middle dot}2. The most common CNVs (frequency 0{middle dot}5-0{middle dot}7%) have no or minimal impact on medical outcomes in adults.\n\nInterpretationSome of the 54 tested CNVs have profound effects on physical health, even in people who have largely escaped early neurodevelopmental outcomes. Our work provides clinicians with a morbidity map of potential outcomes among carriers of these CNVs.\n\nFundingMRC UK, Wellcome Trust UK

genomics↗

bioRxiv2018

Association between schizophrenia and both loss of function and missense mutations in paralog conserved sites of voltage-gated sodium channels

Sequencing studies have highlighted candidate sets of genes involved in schizophrenia, including activity-regulated cytoskeleton-associated protein (ARC) and N-methyl-d-aspartate receptor (NMDAR) complexes. Two genes, SETD1A and RBM12, have also been associated with robust statistical evidence. Larger samples and novel methods for identifying disease-associated missense variants are needed to reveal novel genes and biological mechanisms associated with schizophrenia. We sequenced 187 genes, selected for prior evidence of association with schizophrenia, in a new dataset of 5,207 cases and 4,991 controls. Included were members of ARC and NMDAR post-synaptic protein complexes, as well as voltage-gated sodium and calcium channels. We observed a significant case excess of rare (<0.1% in frequency) loss-of-function (LoF) mutations across all 187 genes (OR = 1.36; Pcorrected = 0.0072) but no individual gene was associated with schizophrenia after correcting for multiple testing. We found novel evidence that LoF and missense variants at paralog conserved sites were enriched in sodium channels (OR = 1.26; P = 0.0035). Meta-analysis of our new data with published sequencing data (11,319 cases, 15,854 controls and 1,136 trios) supported and refined this association to sodium channel alpha subunits (P = 0.0029). Meta-analysis also confirmed association between schizophrenia and rare variants in ARC (P = 4.0 x 10-4) and NMDAR (P = 1.7 x 10-5) synaptic genes. No association was found between rare variants in calcium channels and schizophrenia.\n\nIn one of the largest sequencing studies of schizophrenia to date, we provide novel evidence that multiple voltage-gated sodium channels are involved in schizophrenia pathogenesis, and increase the evidence for association between rare variants in ARC and NMDAR post-synaptic complexes and schizophrenia. Larger samples are required to identify specific genes and variants driving these associations.\n\nAuthor SummaryCommon and rare genetic variations are known to play a substantial role in the development of schizophrenia. Recently, sequencing studies have started to highlight specific sets of genes that are enriched for rare variation in schizophrenia, such as the synaptic gene sets ARC and NMDAR, as well as voltage-gated sodium and calcium channels. To confirm the role of these gene sets in schizophrenia, and identify specific risk genes, we sequenced 187 genes in a new sample of 5,207 schizophrenia cases and 4,991 controls. We find an excess of protein truncating mutations with a frequency <0.1% in all 187 targeted genes, and provide novel evidence that mutations altering amino acids conserved across sodium channel proteins are risk factors for schizophrenia. Through meta-analysing our new data with previously published sequencing data sets, for a total of 11,319 cases, 15,854 controls and 1,136 trios, we increase the evidence for association between rare coding variants and schizophrenia in voltage-gated sodium channels, as well as in synaptic gene sets ARC and NMDAR. Although no individual gene was associated with schizophrenia, these findings suggest larger studies will identify the specific genes driving these associations.

genetics↗

bioRxiv2017

Psychosis and the level of mood incongruence in Bipolar Disorder are related to genetic liability for Schizophrenia

ImportanceBipolar disorder (BD) overlaps schizophrenia in its clinical presentation and genetic liability. Alternative approaches to patient stratification beyond current diagnostic categories are needed to understand the underlying disease processes/mechanisms.\n\nObjectivesTo investigate the relationship between common-variant liability for schizophrenia, indexed by polygenic risk scores (PRS) and psychotic presentations of BD, using clinical descriptions which consider both occurrence and level of mood-incongruent psychotic features.\n\nDesignCase-control design: using multinomial logistic regression, to estimate differential associations of PRS across categories of cases and controls.\n\nSettings & Participants4399 BDcases, mean [sd] age-at-interview 46[12] years, of which 2966 were woman (67%) from the BD Research Network (BDRN) were included in the final analyses, with data for 4976 schizophrenia cases and 9012 controls from the Type-1 diabetes genetics consortium and Generation Scotland included for comparison.\n\nExposureStandardised PRS, calculated using alleles with an association p-value threshold < 0.05 in the second Psychiatric Genomics Consortium genome-wide association study of schizophrenia, adjusted for the first 10 population principal components and genotyping-platform.\n\nMain outcome measureMultinomial logit models estimated PRS associations with BD stratified by (1) Research Diagnostic Criteria (RDC) BD subtypes (2) Lifetime occurrence of psychosis.(3) Lifetime mood-incongruent psychotic features and (4) ordinal logistic regression examined PRS associations across levels of mood-incongruence. Ratings were derived from the Schedule for Clinical Assessment in Neuropsychiatry interview (SCAN) and the Bipolar Affective Disorder Dimension Scale (BADDS).\n\nResultsAcross clinical phenotypes, there was an exposure-response gradient with the strongest PRS association for schizophrenia (RR=1.94, (95% C.1.1.86, 2.01)), then schizoaffective BD (RR=1.37, (95% C.I. 1.22, 1.54)), BD I (RR= 1.30, (95% C.I. 1.24, 1.36)) and BD II (RR=1.04, (95% C.1. 0.97, 1.11)). Within BD cases, there was an effect gradient, indexed by the nature of psychosis, with prominent mood-incongruent psychotic features having the strongest association (RR=1.46, (95% C.1.1.36, 1.57)), followed by mood-congruent psychosis (RR= 1.24, (95% C.1. 1.17, 1.33)) and lastly, BD cases with no history of psychosis (RR= 1.09, (95% C.1. 1.04, 1.15)).\n\nConclusionWe show for the first time a polygenic-risk gradient, across schizophrenia and bipolar disorder, indexed by the occurrence and level of mood-incongruent psychotic symptoms.

genetics↗

bioRxiv2017

Genetic Identification Of Brain Cell Types Underlying Schizophrenia

With few exceptions, the marked advances in knowledge about the genetic basis for schizophrenia have not converged on findings that can be confidently used for precise experimental modeling. 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. The common variant genomic results consistently mapped to pyramidal cells, medium spiny neurons, and certain interneurons but far less consistently to embryonic, progenitor, or glial cells. These enrichments were due to distinct sets of genes specifically expressed in each of these cell types. Many of the diverse gene sets associated with schizophrenia (including antipsychotic targets) implicate the same brain cell types. Our results provide 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. While some of the genetic risk is associated with GABAergic interneurons, this risk largely does not overlap with that from projecting cells.

genomics↗

bioRxiv2017

Causal Analyses, Statistical Efficiency And Phenotypic Precision Through Recall-By-Genotype Study Design

Genome-wide association studies have been useful in identifying common genetic variants related to a variety of complex traits and diseases; however, they are often limited in their ability to inform about underlying biology. Whilst bioinformatics analyses, studies of cells, animal models and applied genetic epidemiology have provided some understanding of genetic associations or causal pathways, there is a need for new genetic studies that elucidate causal relationships and mechanisms in a cost-effective, precise and statistically efficient fashion. We discuss the motivation for and the characteristics of the Recall-by-Genotype (RbG) study design, an approach that enables genotype-directed deep-phenotyping and improvement in drawing causal inferences. Specifically, we present RbG designs using single and multiple variants and discuss the inferential properties, analytical approaches and applications of both. We consider the efficiency of the RbG approach, the likely value of RbG studies for the causal investigation of disease aetiology and the practicalities of incorporating genotypic data into population studies in the context of the RbG study design. Finally, we provide a catalogue of the UK-based resources for such studies, an online tool to aid the design of new RbG studies and discuss future developments of this approach.

genetics↗