Specificity of polygenic signatures across symptom dimensions in bipolar disorder: an analysis of UK Bipolar Disorder Research Network data.

BACKGROUND: Current definitions and clinical heterogeneity in bipolar disorder are major concerns as they obstruct aetiological research and impede drug development. Therefore, stratification of bipolar disorder is a high priority. To inform stratification, our analysis aimed to examine the patterns and relationships between polygenic liability for bipolar disorder, major depressive disorder (MDD), and schizophrenia with multidimensional symptom representations of bipolar disorder. METHODS: In this analysis, data from the UK Bipolar Disorder Research Network (BDRN) were assessed with the Operational Checklist for Psychotic Disorders. Individuals with bipolar disorder as defined in DSM-IV, of European ancestry (self-reported), aged 18 years or older at time of interview, living in the UK, and registered with the BDRN were eligible for inclusion. Psychopathological variables obtained via interview by trained research psychologists or psychiatrists and psychiatric case notes were used to identify statistically distinct symptom dimensions, calibrated with exploratory factor analysis and validated with confirmatory factor analysis (CFA). CFA was extended to include three polygenic risk scores (PRSs) indexing liability for bipolar disorder, MDD, and schizophrenia in a multiple indicator multiple cause (MIMIC) structural equation model to estimate PRS relationships with symptom dimensions. FINDINGS: Of 4198 individuals potentially eligible for inclusion, 4148 (2804 [67·6%] female individuals and 1344 [32·4%] male individuals) with a mean age at interview of 45 years (SD 12·03) were available for analysis. Three reliable dimensions (mania, depression, and psychosis) were identified. The MIMIC model fitted the data well (root mean square error of approximation 0·021, 90% CI 0·019-0·023; comparative fit index 0·99) and suggests statistically distinct symptom dimensions also have distinct polygenic profiles. The PRS for MDD was strongly associated with the depression dimension (standardised ß 0·125, 95% CI 0·080-0·171) and the PRS for schizophrenia was strongly associated with the psychosis dimension (0·108, 0·082-0·175). For the mania dimension, the PRS for bipolar disorder was weakly associated (0·050, 0·002-0·097). INTERPRETATION: Our findings support the hypothesis that genetic heterogeneity underpins clinical heterogeneity, suggesting that different symptom dimensions within bipolar disorder have partly distinct causes. Furthermore, our results suggest that a specific symptom dimension has a similar cause regardless of the primary psychiatric diagnosis, supporting the use of symptom dimensions in precision psychiatry. FUNDING: Wellcome Trust and UK Medical Research Council.

The relationship between case-control differential gene expression from brain tissue and genetic associations in schizophrenia.

Large numbers of genetic loci have been identified that are known to contain common risk alleles for schizophrenia, but linking associated alleles to specific risk genes remains challenging. Given that most alleles that influence liability to schizophrenia are thought to do so by altered gene expression, intuitively, case-control differential gene expression studies should highlight genes with a higher probability of being associated with schizophrenia and could help identify the most likely causal genes within associated loci. Here, we test this hypothesis by comparing transcriptome analysis of the dorsolateral prefrontal cortex from 563 schizophrenia cases and 802 controls with genome-wide association study (GWAS) data from the third wave study of the Psychiatric Genomics Consortium. Genes differentially expressed in schizophrenia were not enriched for common allelic association statistics compared with other brain-expressed genes, nor were they enriched for genes within associated loci previously reported to be prioritized by genetic fine-mapping. Genes prioritized by Summary-based Mendelian Randomization were underexpressed in cases compared to other genes in the same GWAS loci. However, the overall strength and direction of expression change predicted by SMR were not related to that observed in the differential expression data. Overall, this study does not support the hypothesis that genes identified as differentially expressed from RNA sequencing of bulk brain tissue are enriched for those that show evidence for genetic associations. Such data have limited utility for prioritizing genes in currently associated loci in schizophrenia.

Genetic Liabilities Differentiating Bipolar Disorder, Schizophrenia, and Major Depressive Disorder, and Phenotypic Heterogeneity in Bipolar Disorder.

Importance: Understanding the origins of clinical heterogeneity in bipolar disorder (BD) will inform new approaches to stratification and studies of underlying mechanisms. Objective: To identify components of genetic liability that are shared between BD, schizophrenia, and major depressive disorder (MDD) and those that differentiate each disorder from the others and to examine associations between heterogeneity for key BD symptoms and each component. Design, Setting, and Participants: Using data from the Bipolar Disorder Research Network in the United Kingdom, components of liability were identified by applying genomic structural equation modeling to genome-wide association studies of schizophrenia, BD, and MDD. Polygenic risk scores (PRS) representing each component were tested for association with symptoms in an independent BD data set. Adults with DSM-IV BD or schizoaffective disorder, bipolar type, were included. Data were collected from January 2000 to December 2013, and data were analyzed from June 2020 to February 2022. Main Outcomes and Measures: PRS representing the components of liability were tested for association with mania and depression, psychosis, and mood incongruence of psychosis in participants with BD, measured using the Bipolar Affective Disorder Dimensional Scale. Results: Of 4429 included participants, 3012 (68.0%) were female, and the mean (SD) age was 46.2 (12.3) years. Mania and psychosis were associated with the shared liability component (mania ß = 0.29; 95% CI, 0.23-0.34; P = 3.04 × 10-25; psychosis ß = 0.05; 95% CI, 0.04-0.07; P = 2.33 × 10-13) and the components that differentiate each of schizophrenia (mania ß = 0.08; 95% CI, 0.03-0.14; P = .002; psychosis ß = 0.03; 95% CI, 0.01-0.04; P = 1.0 × 10-4) and BD (mania ß = 0.14; 95% CI, 0.09-0.20; P = 1.99 × 10-7; psychosis ß = 0.02; 95% CI, 0.01-0.03; P = .006) from the other disorders. The BD differentiating component was associated with mania independently of effects on psychosis (ß = 0.14; 95% CI, 0.08-0.20; P = 4.32 × 10-6) but not with psychosis independently of mania. Conversely, the schizophrenia differentiating component was associated with psychosis independently of effects on mania (ß = 0.01; 95% CI, 0.003-0.03; P = .02), but not with mania independently of psychosis. Mood incongruence of psychosis was associated only with the schizophrenia differentiating component (ß = 0.03; 95% CI, 0.01-0.05; P = .005). Depression was associated with higher MDD differentiating component (ß = 0.07; 95% CI, 0.01-0.12; P = .01) but lower BD differentiating component (ß = -0.11; 95% CI, -0.17 to -0.06; P = 7.06 × 10-5). Conclusions and Relevance: In this study of BD, clinical heterogeneity reflected the burden of liability to BD and the contribution of alleles that have differentiating effects on risk for other disorders; mania, psychosis, and depression were associated with the components of genetic liability differentiating BD, MDD, and schizophrenia, respectively. Understanding the basis of this etiological heterogeneity will be critical for identifying the different pathophysiological processes underlying BD, stratifying patients, and developing precision therapeutics.

Developmental disruption to the cortical transcriptome and synaptosome in a model of SETD1A loss-of-function.

Large-scale genomic studies of schizophrenia implicate genes involved in the epigenetic regulation of transcription by histone methylation and genes encoding components of the synapse. However, the interactions between these pathways in conferring risk to psychiatric illness are unknown. Loss-of-function (LoF) mutations in the gene encoding histone methyltransferase, SETD1A, confer substantial risk to schizophrenia. Among several roles, SETD1A is thought to be involved in the development and function of neuronal circuits. Here, we employed a multi-omics approach to study the effects of heterozygous Setd1a LoF on gene expression and synaptic composition in mouse cortex across five developmental timepoints from embryonic day 14 to postnatal day 70. Using RNA sequencing, we observed that Setd1a LoF resulted in the consistent downregulation of genes enriched for mitochondrial pathways. This effect extended to the synaptosome, in which we found age-specific disruption to both mitochondrial and synaptic proteins. Using large-scale patient genomics data, we observed no enrichment for genetic association with schizophrenia within differentially expressed transcripts or proteins, suggesting they derive from a distinct mechanism of risk from that implicated by genomic studies. This study highlights biological pathways through which SETD1A LOF may confer risk to schizophrenia. Further work is required to determine whether the effects observed in this model reflect human pathology.

New insights into the genetic etiology of Alzheimer's disease and related dementias.

Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele.

Interaction Testing and Polygenic Risk Scoring to Estimate the Association of Common Genetic Variants With Treatment Resistance in Schizophrenia.

IMPORTANCE: About 20% to 30% of people with schizophrenia have psychotic symptoms that do not respond adequately to first-line antipsychotic treatment. This clinical presentation, chronic and highly disabling, is known as treatment-resistant schizophrenia (TRS). The causes of treatment resistance and their relationships with causes underlying schizophrenia are largely unknown. Adequately powered genetic studies of TRS are scarce because of the difficulty in collecting data from well-characterized TRS cohorts. OBJECTIVE: To examine the genetic architecture of TRS through the reassessment of genetic data from schizophrenia studies and its validation in carefully ascertained clinical samples. DESIGN, SETTING, AND PARTICIPANTS: Two case-control genome-wide association studies (GWASs) of schizophrenia were performed in which the case samples were defined as individuals with TRS (n = 10 501) and individuals with non-TRS (n = 20 325). The differences in effect sizes for allelic associations were then determined between both studies, the reasoning being such differences reflect treatment resistance instead of schizophrenia. Genotype data were retrieved from the CLOZUK and Psychiatric Genomics Consortium (PGC) schizophrenia studies. The output was validated using polygenic risk score (PRS) profiling of 2 independent schizophrenia cohorts with TRS and non-TRS: a prevalence sample with 817 individuals (Cardiff Cognition in Schizophrenia [CardiffCOGS]) and an incidence sample with 563 individuals (Genetics Workstream of the Schizophrenia Treatment Resistance and Therapeutic Advances [STRATA-G]). MAIN OUTCOMES AND MEASURES: GWAS of treatment resistance in schizophrenia. The results of the GWAS were compared with complex polygenic traits through a genetic correlation approach and were used for PRS analysis on the independent validation cohorts using the same TRS definition. RESULTS: The study included a total of 85 490 participants (48 635 [56.9%] male) in its GWAS stage and 1380 participants (859 [62.2%] male) in its PRS validation stage. Treatment resistance in schizophrenia emerged as a polygenic trait with detectable heritability (1% to 4%), and several traits related to intelligence and cognition were found to be genetically correlated with it (genetic correlation, 0.41-0.69). PRS analysis in the CardiffCOGS prevalence sample showed a positive association between TRS and a history of taking clozapine (r2 = 2.03%; P = .001), which was replicated in the STRATA-G incidence sample (r2 = 1.09%; P = .04). CONCLUSIONS AND RELEVANCE: In this GWAS, common genetic variants were differentially associated with TRS, and these associations may have been obscured through the amalgamation of large GWAS samples in previous studies of broadly defined schizophrenia. Findings of this study suggest the validity of meta-analytic approaches for studies on patient outcomes, including treatment resistance.

Developmental Profile of Psychiatric Risk Associated With Voltage-Gated Cation Channel Activity.

BACKGROUND: Recent breakthroughs in psychiatric genetics have implicated biological pathways onto which genetic risk for psychiatric disorders converges. However, these studies do not reveal the developmental time point(s) at which these pathways are relevant. METHODS: We aimed to determine the relationship between psychiatric risk and developmental gene expression relating to discrete biological pathways. We used postmortem RNA sequencing data (BrainSeq and BrainSpan) from brain tissue at multiple prenatal and postnatal time points, with summary statistics from recent genome-wide association studies of schizophrenia, bipolar disorder, and major depressive disorder. We prioritized gene sets for overall enrichment of association with each disorder and then tested the relationship between the association of their constituent genes with their relative expression at each developmental stage. RESULTS: We observed relationships between the expression of genes involved in voltage-gated cation channel activity during early midfetal, adolescence, and early adulthood time points and association with schizophrenia and bipolar disorder, such that genes more strongly associated with these disorders had relatively low expression during early midfetal development and higher expression during adolescence and early adulthood. The relationship with schizophrenia was strongest for the subset of genes related to calcium channel activity, while for bipolar disorder, the relationship was distributed between calcium and potassium channel activity genes. CONCLUSIONS: Our results indicate periods during development when biological pathways related to the activity of calcium and potassium channels may be most vulnerable to the effects of genetic variants conferring risk for psychiatric disorders. Furthermore, they indicate key time points and potential targets for disorder-specific therapeutic interventions.

Genetic association of FMRP targets with psychiatric disorders.

Genes encoding the mRNA targets of fragile X mental retardation protein (FMRP) are enriched for genetic association with psychiatric disorders. However, many FMRP targets possess functions that are themselves genetically associated with psychiatric disorders, including synaptic transmission and plasticity, making it unclear whether the genetic risk is truly related to binding by FMRP or is alternatively mediated by the sampling of genes better characterised by another trait or functional annotation. Using published common variant, rare coding variant and copy number variant data, we examined the relationship between FMRP binding and genetic association with schizophrenia, major depressive disorder and bipolar disorder. High-confidence targets of FMRP, derived from studies of multiple tissue types, were enriched for common schizophrenia risk alleles, as well as rare loss-of-function and de novo nonsynonymous variants in schizophrenia cases. Similarly, through common variation, FMRP targets were associated with major depressive disorder, and we present novel evidence of association with bipolar disorder. These relationships could not be explained by other functional annotations known to be associated with psychiatric disorders, including those related to synaptic structure and function. This study reinforces the evidence that targeting by FMRP captures a subpopulation of genes enriched for genetic association with a range of psychiatric disorders.

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 (GWAS) 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. We identify a significant correlation between schizophrenia risk and expression at 89 genes in the dorsolateral prefrontal cortex (P ≤ 9.43 × 10-6), including 20 novel genes. Genes whose expression correlate with schizophrenia were enriched for those involved in abnormal CNS synaptic transmission (PFDR = 0.02) and antigen processing and presentation of peptide antigen via MHC class I (PFDR = 0.02). Within the CNS synaptic transmission set, we identify individual significant candidate genes to which we assign direction of expression changes in schizophrenia. The findings provide strong candidates for experimentally probing the molecular basis of synaptic pathology in schizophrenia.

Novel Insight Into the Etiology of Autism Spectrum Disorder Gained by Integrating Expression Data With Genome-wide Association Statistics.

BACKGROUND: A recent genome-wide association study (GWAS) of autism spectrum disorder (ASD) (ncases = 18,381, ncontrols = 27,969) has provided novel opportunities for investigating the etiology of ASD. Here, we integrate the ASD GWAS summary statistics with summary-level gene expression data to infer differential gene expression in ASD, an approach called transcriptome-wide association study (TWAS). METHODS: Using FUSION software, ASD GWAS summary statistics were integrated with predictors of gene expression from 16 human datasets, including adult and fetal brains. A novel adaptation of established statistical methods was then used to test for enrichment within candidate pathways and specific tissues and at different stages of brain development. The proportion of ASD heritability explained by predicted expression of genes in the TWAS was estimated using stratified linkage disequilibrium score regression. RESULTS: This study identified 14 genes as significantly differentially expressed in ASD, 13 of which were outside of known genome-wide significant loci (±500 kb). XRN2, a gene proximal to an ASD GWAS locus, was inferred to be significantly upregulated in ASD, providing insight into the functional consequence of this associated locus. One novel transcriptome-wide significant association from this study is the downregulation of PDIA6, which showed minimal evidence of association in the GWAS, and in gene-based analysis using MAGMA. Predicted gene expression in this study accounted for 13.0% of the total ASD single nucleotide polymorphism heritability. CONCLUSIONS: This study has implicated several genes as significantly up/downregulated in ASD, providing novel and useful information for subsequent functional studies. This study also explores the utility of TWAS-based enrichment analysis and compares TWAS results with a functionally agnostic approach.

Genome-wide association study identifies 30 loci associated with bipolar disorder.

Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study (GWAS) including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P < 1 × 10-4 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (P < 5 × 10-8) in the discovery GWAS were not genome-wide significant in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis, 30 loci were genome-wide significant, including 20 newly identified loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene sets, including regulation of insulin secretion and endocannabinoid signaling. Bipolar I disorder is strongly genetically correlated with schizophrenia, driven by psychosis, whereas bipolar II disorder is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential biological mechanisms for bipolar disorder.

Dynamic expression of genes associated with schizophrenia and bipolar disorder across development.

Common 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 the two disorders. 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 genetic association with schizophrenia is positively correlated with expression in the prefrontal cortex during early midfetal development and early infancy, and negatively correlated with expression during late childhood, which stabilises in adolescence. In contrast, risk-associated genes for bipolar disorder did not exhibit a bias towards expression at any prenatal stage, although the pattern of postnatal expression was similar to that of schizophrenia. These results highlight the dynamic expression of genes harbouring risk for schizophrenia and bipolar disorder across prefrontal cortex development and support the hypothesis that prenatal neurodevelopmental events are more strongly associated with schizophrenia than bipolar disorder.

Genetic modifiers of Mendelian disease: Huntington's disease and the trinucleotide repeat disorders.

In the decades since the genes and mutations associated with the commoner Mendelian disorders were first discovered, technological advances in genetic analysis have made finding genomic variation a much less onerous task. Recently, the global efforts to collect subjects with Mendelian disorders, to better define the disorders and to empower appropriate clinical trials, along with improved genetic technologies, have allowed the identification of genetic variation that does not cause disease, but substantially modifies disease presentation. The advantage of this is it identifies biological pathways and molecules, that, if modified in people, might alter disease presentation. In Huntington's disease (HD), caused by an expanded CAG repeat tract in HTT, genetic variation has been uncovered that is associated with change in the onset or progression of disease. Some of this variation lies in genes that are part of the DNA damage response, previously suggested to be important in modulating expansion of the repeat tract in germline and somatic cells. The genetic evidence implicates a DNA damage response-related pathway in modulating the pathogenicity of the repeat tracts in HD, and possibly, in other trinucleotide repeat disorders. These findings offer new targets for drug development in these currently intractable disorders.

Treating the placenta to prevent adverse effects of gestational hypoxia on fetal brain development.

Some neuropsychiatric disease, including schizophrenia, may originate during prenatal development, following periods of gestational hypoxia and placental oxidative stress. Here we investigated if gestational hypoxia promotes damaging secretions from the placenta that affect fetal development and whether a mitochondria-targeted antioxidant MitoQ might prevent this. Gestational hypoxia caused low birth-weight and changes in young adult offspring brain, mimicking those in human neuropsychiatric disease. Exposure of cultured neurons to fetal plasma or to secretions from the placenta or from model trophoblast barriers that had been exposed to altered oxygenation caused similar morphological changes. The secretions and plasma contained altered microRNAs whose targets were linked with changes in gene expression in the fetal brain and with human schizophrenia loci. Molecular and morphological changes in vivo and in vitro were prevented by a single dose of MitoQ bound to nanoparticles, which were shown to localise and prevent oxidative stress in the placenta but not in the fetus. We suggest the possibility of developing preventative treatments that target the placenta and not the fetus to reduce risk of psychiatric disease in later life.

Mutation intolerant genes and targets of FMRP are enriched for nonsynonymous alleles in schizophrenia.

Risk of schizophrenia is conferred by alleles occurring across the full spectrum of frequencies from common SNPs of weak effect through to ultra rare alleles, some of which may be moderately to highly penetrant. Previous studies have suggested that some of the risk of schizophrenia is attributable to uncommon alleles represented on Illumina exome arrays. Here, we present the largest study of exomic variation in schizophrenia to date, using samples from the United Kingdom and Sweden (10,011 schizophrenia cases and 13,791 controls). Single variants, genes, and gene sets were analyzed for association with schizophrenia. No single variant or gene reached genome-wide significance. Among candidate gene sets, we found significant enrichment for rare alleles (minor allele frequency [MAF] < 0.001) in genes intolerant of loss-of-function (LoF) variation and in genes whose messenger RNAs bind to fragile X mental retardation protein (FMRP). We further delineate the genetic architecture of schizophrenia by excluding a role for uncommon exomic variants (0.01 ≤ MAF ≥ 0.001) that confer a relatively large effect (odds ratio [OR] > 4). We also show risk alleles within this frequency range exist, but confer smaller effects and should be identified by larger studies.

Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects.

Copy number variants (CNVs) have been strongly implicated in the genetic etiology of schizophrenia (SCZ). However, genome-wide investigation of the contribution of CNV to risk has been hampered by limited sample sizes. We sought to address this obstacle by applying a centralized analysis pipeline to a SCZ cohort of 21,094 cases and 20,227 controls. A global enrichment of CNV burden was observed in cases (odds ratio (OR) = 1.11, P = 5.7 × 10-15), which persisted after excluding loci implicated in previous studies (OR = 1.07, P = 1.7 × 10-6). CNV burden was enriched for genes associated with synaptic function (OR = 1.68, P = 2.8 × 10-11) and neurobehavioral phenotypes in mouse (OR = 1.18, P = 7.3 × 10-5). Genome-wide significant evidence was obtained for eight loci, including 1q21.1, 2p16.3 (NRXN1), 3q29, 7q11.2, 15q13.3, distal 16p11.2, proximal 16p11.2 and 22q11.2. Suggestive support was found for eight additional candidate susceptibility and protective loci, which consisted predominantly of CNVs mediated by nonallelic homologous recombination.

Similar striatal gene expression profiles in the striatum of the YAC128 and HdhQ150 mouse models of Huntington's disease are not reflected in mutant Huntingtin inclusion prevalence.

BACKGROUND: The YAC128 model of Huntington's disease (HD) shows substantial deficits in motor, learning and memory tasks and alterations in its transcriptional profile. We examined the changes in the transcriptional profile in the YAC128 mouse model of HD at 6, 12 and 18 months and compared these with those seen in other models and human HD caudate. RESULTS: Differential gene expression by genotype showed that genes related to neuronal function, projection outgrowth and cell adhesion were altered in expression. A Time-course ANOVA revealed that genes downregulated with increased age in wild-type striata were likely to be downregulated in the YAC128 striata. There was a substantial overlap of concordant gene expression changes in the YAC128 striata compared with those in human HD brain. Changes in gene expression over time showed fewer striatal YAC128 RNAs altered in abundance than in the HdhQ150 striata but there was a very marked overlap in transcriptional changes at all time points. Despite the similarities in striatal expression changes at 18 months the HdhQ150 mice showed widespread mHTT and ubiquitin positive inclusion staining in the striatum whereas this was absent in the YAC128 striatum. CONCLUSIONS: The gene expression changes in YAC128 striata show a very closely matched profile to that of HdhQ150 striata and are already significantly different between genotypes by six months of age, implying that the temporal molecular gene expression profiles of these models match very closely, despite differences in the prevalence of brain inclusion formation between the models. The YAC128 gene expression changes appear to correlate well with gene expression differences caused by ageing. A relatively small number of genes showed significant differences in expression between the striata of the two models and these could explain some of the phenotypic differences between the models.

Pathway analyses implicate glial cells in schizophrenia.

BACKGROUND: The quest to understand the neurobiology of schizophrenia and bipolar disorder is ongoing with multiple lines of evidence indicating abnormalities of glia, mitochondria, and glutamate in both disorders. Despite high heritability estimates of 81% for schizophrenia and 75% for bipolar disorder, compelling links between findings from neurobiological studies, and findings from large-scale genetic analyses, are only beginning to emerge. METHOD: Ten publically available gene sets (pathways) related to glia, mitochondria, and glutamate were tested for association to schizophrenia and bipolar disorder using MAGENTA as the primary analysis method. To determine the robustness of associations, secondary analyses were performed with: ALIGATOR, INRICH, and Set Screen. Data from the Psychiatric Genomics Consortium (PGC) were used for all analyses. There were 1,068,286 SNP-level p-values for schizophrenia (9,394 cases/12,462 controls), and 2,088,878 SNP-level p-values for bipolar disorder (7,481 cases/9,250 controls). RESULTS: The Glia-Oligodendrocyte pathway was associated with schizophrenia, after correction for multiple tests, according to primary analysis (MAGENTA p = 0.0005, 75% requirement for individual gene significance) and also achieved nominal levels of significance with INRICH (p = 0.0057) and ALIGATOR (p = 0.022). For bipolar disorder, Set Screen yielded nominally and method-wide significant associations to all three glial pathways, with strongest association to the Glia-Astrocyte pathway (p = 0.002). CONCLUSIONS: Consistent with findings of white matter abnormalities in schizophrenia by other methods of study, the Glia-Oligodendrocyte pathway was associated with schizophrenia in our genomic study. These findings suggest that the abnormalities of myelination observed in schizophrenia are at least in part due to inherited factors, contrasted with the alternative of purely environmental causes (e.g. medication effects or lifestyle). While not the primary purpose of our study, our results also highlight the consequential nature of alternative choices regarding pathway analysis, in that results varied somewhat across methods, despite application to identical datasets and pathways.

Genome-wide association study of clinical dimensions of schizophrenia: polygenic effect on disorganized symptoms.

OBJECTIVE: Multiple sources of evidence suggest that genetic factors influence variation in clinical features of schizophrenia. The authors present the first genome-wide association study (GWAS) of dimensional symptom scores among individuals with schizophrenia. METHOD: Based on the Lifetime Dimensions of Psychosis Scale ratings of 2,454 case subjects of European ancestry from the Molecular Genetics of Schizophrenia (MGS) sample, three symptom factors (positive, negative/disorganized, and mood) were identified with exploratory factor analysis. Quantitative scores for each factor from a confirmatory factor analysis were analyzed for association with 696,491 single-nucleotide polymorphisms (SNPs) using linear regression, with correction for age, sex, clinical site, and ancestry. Polygenic score analysis was carried out to determine whether case and comparison subjects in 16 Psychiatric GWAS Consortium (PGC) schizophrenia samples (excluding MGS samples) differed in scores computed by weighting their genotypes by MGS association test results for each symptom factor. RESULTS: No genome-wide significant associations were observed between SNPs and factor scores. Most of the SNPs producing the strongest evidence for association were in or near genes involved in neurodevelopment, neuroprotection, or neurotransmission, including genes playing a role in Mendelian CNS diseases, but no statistically significant effect was observed for any defined gene pathway. Finally, polygenic scores based on MGS GWAS results for the negative/disorganized factor were significantly different between case and comparison subjects in the PGC data set; for MGS subjects, negative/disorganized factor scores were correlated with polygenic scores generated using case-control GWAS results from the other PGC samples. CONCLUSIONS: The polygenic signal that has been observed in cross-sample analyses of schizophrenia GWAS data sets could be in part related to genetic effects on negative and disorganized symptoms (i.e., core features of chronic schizophrenia).