Genetic risk for schizophrenia is associated with increased proportion of indirect connections in brain networks revealed by a semi-metric analysis: evidence from population sample stratified for polygenic risk.

Research studies based on tractography have revealed a prominent reduction of asymmetry in some key white-matter tracts in schizophrenia (SCZ). However, we know little about the influence of common genetic risk factors for SCZ on the efficiency of routing on structural brain networks (SBNs). Here, we use a novel recall-by-genotype approach, where we sample young adults from a population-based cohort (ALSPAC:N genotyped = 8,365) based on their burden of common SCZ risk alleles as defined by polygenic risk score (PRS). We compared 181 individuals at extremes of low (N = 91) or high (N = 90) SCZ-PRS under a robust diffusion MRI-based graph theoretical SBN framework. We applied a semi-metric analysis revealing higher SMR values for the high SCZ-PRS group compared with the low SCZ-PRS group in the left hemisphere. Furthermore, a hemispheric asymmetry index showed a higher leftward preponderance of indirect connections for the high SCZ-PRS group compared with the low SCZ-PRS group (PFDR < 0.05). These findings might indicate less efficient structural connectivity in the higher genetic risk group. This is the first study in a population-based sample that reveals differences in the efficiency of SBNs associated with common genetic risk variants for SCZ.

The dynamic interplay between sleep and mood: an intensive longitudinal study of individuals with bipolar disorder.

BACKGROUND: Sleep disturbances are important symptoms to monitor in people with bipolar disorder (BD) but the precise longitudinal relationships between sleep and mood remain unclear. We aimed to examine associations between stable and dynamic aspects of sleep and mood in people with BD, and assess individual differences in the strength of these associations. METHODS: Participants (N = 649) with BD-I (N = 400) and BD-II (N = 249) provided weekly self-reports of insomnia, depression and (hypo)mania symptoms using the True Colours online monitoring tool for 21 months. Dynamic structural equation models were used to examine the interplay between weekly reports of insomnia and mood. The effects of clinical and demographic characteristics on associations were also assessed. RESULTS: Increased variability in insomnia symptoms was associated with increased mood variability. In the sample as a whole, we found strong evidence of bidirectional relationships between insomnia and depressive symptoms but only weak support for bidirectional relationships between insomnia and (hypo)manic symptoms. We found substantial variability between participants in the strength of prospective associations between insomnia and mood, which depended on age, gender, bipolar subtype, and a history of rapid cycling. CONCLUSIONS: Our results highlight the importance of monitoring sleep in people with BD. However, researchers and clinicians investigating the association between sleep and mood should consider subgroup differences in this relationship. Advances in digital technology mean that intensive longitudinal data on sleep and mood are becoming increasingly available. Novel methods to analyse these data present an exciting opportunity for furthering our understanding of BD.

Genome-wide common and rare variant analysis provides novel insights into clozapine-associated neutropenia.

This corrects the article DOI: 10.1038/mp.2016.97.

Exome arrays capture polygenic rare variant contributions to schizophrenia.

Schizophrenia is a highly heritable disorder. Genome-wide association studies based largely on common alleles have identified over 100 schizophrenia risk loci, but it is also evident from studies of copy number variants (CNVs) and from exome-sequencing studies that rare alleles are also involved. Full characterization of the contribution of rare alleles to the disorder awaits the deployment of sequencing technology in very large sample sizes, meanwhile, as an interim measure, exome arrays allow rare non-synonymous variants to be sampled at a fraction of the cost. In an analysis of exome array data from 13 688 individuals (5585 cases and 8103 controls) from the UK, we found that rare (minor allele frequency < 0.1%) variant association signal was enriched among genes that map to autosomal loci that are genome-wide significant (GWS) in common variant studies of schizophrenia genome-wide association study (PGWAS = 0.01) as well as gene sets known to be enriched for rare variants in sequencing studies (PRARE = 0.026). We also identified the gene-wise equivalent of GWS support for WDR88 (WD repeat-containing protein 88), a gene of unknown function (P = 6.5 × 10(-7)). Rare alleles represented on exome chip arrays contribute to the genetic architecture of schizophrenia, but as is the case for GWAS, very large studies are required to reveal additional susceptibility alleles for the disorder.

Genetically predicted complement component 4A expression: effects on memory function and middle temporal lobe activation.

BACKGROUND: The longstanding association between the major histocompatibility complex (MHC) locus and schizophrenia (SZ) risk has recently been accounted for, partially, by structural variation at the complement component 4 (C4) gene. This structural variation generates varying levels of C4 RNA expression, and genetic information from the MHC region can now be used to predict C4 RNA expression in the brain. Increased predicted C4A RNA expression is associated with the risk of SZ, and C4 is reported to influence synaptic pruning in animal models. METHODS: Based on our previous studies associating MHC SZ risk variants with poorer memory performance, we tested whether increased predicted C4A RNA expression was associated with reduced memory function in a large (n = 1238) dataset of psychosis cases and healthy participants, and with altered task-dependent cortical activation in a subset of these samples. RESULTS: We observed that increased predicted C4A RNA expression predicted poorer performance on measures of memory recall (p = 0.016, corrected). Furthermore, in healthy participants, we found that increased predicted C4A RNA expression was associated with a pattern of reduced cortical activity in middle temporal cortex during a measure of visual processing (p < 0.05, corrected). CONCLUSIONS: These data suggest that the effects of C4 on cognition were observable at both a cortical and behavioural level, and may represent one mechanism by which illness risk is mediated. As such, deficits in learning and memory may represent a therapeutic target for new molecular developments aimed at altering C4's developmental role.

Schizophrenia copy number variants and associative learning.

Large-scale genomic studies have made major progress in identifying genetic risk variants for schizophrenia. A key finding from these studies is that there is an increased burden of genomic copy number variants (CNVs) in schizophrenia cases compared with controls. The mechanism through which these CNVs confer risk for the symptoms of schizophrenia, however, remains unclear. One possibility is that schizophrenia risk CNVs impact basic associative learning processes, abnormalities of which have long been associated with the disorder. To investigate whether genes in schizophrenia CNVs impact on specific phases of associative learning we combined human genetics with experimental gene expression studies in animals. In a sample of 11 917 schizophrenia cases and 16 416 controls, we investigated whether CNVs from patients with schizophrenia are enriched for genes expressed during the consolidation, retrieval or extinction of associative memories. We show that CNVs from cases are enriched for genes expressed during fear extinction in the hippocampus, but not genes expressed following consolidation or retrieval. These results suggest that CNVs act to impair inhibitory learning in schizophrenia, potentially contributing to the development of core symptoms of the disorder.

Genome-wide common and rare variant analysis provides novel insights into clozapine-associated neutropenia.

This corrects the article DOI: 10.1038/mp.2016.97.

Genome-wide common and rare variant analysis provides novel insights into clozapine-associated neutropenia.

The antipsychotic clozapine is uniquely effective in the management of schizophrenia; however, its use is limited by its potential to induce agranulocytosis. The causes of this, and of its precursor neutropenia, are largely unknown, although genetic factors have an important role. We sought risk alleles for clozapine-associated neutropenia in a sample of 66 cases and 5583 clozapine-treated controls, through a genome-wide association study (GWAS), imputed human leukocyte antigen (HLA) alleles, exome array and copy-number variation (CNV) analyses. We then combined associated variants in a meta-analysis with data from the Clozapine-Induced Agranulocytosis Consortium (up to 163 cases and 7970 controls). In the largest combined sample to date, we identified a novel association with rs149104283 (odds ratio (OR)=4.32, P=1.79 × 10-8), intronic to transcripts of SLCO1B3 and SLCO1B7, members of a family of hepatic transporter genes previously implicated in adverse drug reactions including simvastatin-induced myopathy and docetaxel-induced neutropenia. Exome array analysis identified gene-wide associations of uncommon non-synonymous variants within UBAP2 and STARD9. We additionally provide independent replication of a previously identified variant in HLA-DQB1 (OR=15.6, P=0.015, positive predictive value=35.1%). These results implicate biological pathways through which clozapine may act to cause this serious adverse effect.

Mental disorders of known aetiology and precision medicine in psychiatry: a promising but neglected alliance.

Personalized or precision medicine is predicated on the assumption that the average response to treatment is not necessarily representative of the response of each individual. A commitment to personalized medicine demands an effort to bring evidence-based medicine and personalized medicine closer together. The use of relatively homogeneous groups, defined using a priori criteria, may constitute a promising initial step for developing more accurate risk-prediction models with which to advance the development of personalized evidence-based medicine approaches to heterogeneous syndromes such as schizophrenia. However, this can lead to a paradoxical situation in the field of psychiatry. Since there has been a tendency to loosely define psychiatric disorders as ones without a known aetiology, the discovery of an aetiology for psychiatric syndromes (e.g. 22q11.2 deletion syndrome in some cases of schizophrenia), while offering a path toward more precise treatments, may also lead to their reclassification away from psychiatry. We contend that psychiatric disorders with a known aetiology should not be removed from the field of psychiatry. This knowledge should be used instead to guide treatment, inasmuch as psychotherapies, pharmacotherapies and other treatments can all be valid approaches to mental disorders. The translation of the personalized clinical approach inherent to psychiatry into evidence-based precision medicine can lead to the development of novel treatment options for mental disorders and improve outcomes.

Psychiatric gene discoveries shape evidence on ADHD's biology.

A strong motivation for undertaking psychiatric gene discovery studies is to provide novel insights into unknown biology. Although attention-deficit hyperactivity disorder (ADHD) is highly heritable, and large, rare copy number variants (CNVs) contribute to risk, little is known about its pathogenesis and it remains commonly misunderstood. We assembled and pooled five ADHD and control CNV data sets from the United Kingdom, Ireland, United States of America, Northern Europe and Canada. Our aim was to test for enrichment of neurodevelopmental gene sets, implicated by recent exome-sequencing studies of (a) schizophrenia and (b) autism as a means of testing the hypothesis that common pathogenic mechanisms underlie ADHD and these other neurodevelopmental disorders. We also undertook hypothesis-free testing of all biological pathways. We observed significant enrichment of individual genes previously found to harbour schizophrenia de novo non-synonymous single-nucleotide variants (SNVs; P=5.4 × 10(-4)) and targets of the Fragile X mental retardation protein (P=0.0018). No enrichment was observed for activity-regulated cytoskeleton-associated protein (P=0.23) or N-methyl-D-aspartate receptor (P=0.74) post-synaptic signalling gene sets previously implicated in schizophrenia. Enrichment of ADHD CNV hits for genes impacted by autism de novo SNVs (P=0.019 for non-synonymous SNV genes) did not survive Bonferroni correction. Hypothesis-free testing yielded several highly significantly enriched biological pathways, including ion channel pathways. Enrichment findings were robust to multiple testing corrections and to sensitivity analyses that excluded the most significant sample. The findings reveal that CNVs in ADHD converge on biologically meaningful gene clusters, including ones now established as conferring risk of other neurodevelopmental disorders.

Common alleles contribute to schizophrenia in CNV carriers.

The genetic architecture of schizophrenia is complex, involving risk alleles ranging from common alleles of weak effect to rare alleles of large effect, the best exemplar of the latter being large copy number variants (CNVs). It is currently unknown whether pathophysiology in those with defined rare mutations overlaps with that in other individuals with the disorder who do not share the same rare mutation. Under an extreme heterogeneity model, carriers of specific high-penetrance mutations form distinct subgroups. In contrast, under a polygenic threshold model, high-penetrance rare allele carriers possess many risk factors, of which the rare allele is the only one, albeit an important, factor. Under the latter model, cases with rare mutations can be expected to share some common risk alleles, and therefore pathophysiological mechanisms, with cases without the same mutation. Here we show that, compared with controls, individuals with schizophrenia who have known pathogenic CNVs carry an excess burden of common risk alleles (P=2.25 × 10(-17)) defined from a genome-wide association study largely based on individuals without known CNVs. Our finding is not consistent with an extreme heterogeneity model for CNV carriers, but does offer support for the polygenic threshold model of schizophrenia. That this is so provides support for the notion that studies aiming to model the effects of rare variation may uncover pathophysiological mechanisms of relevance to those with the disorder more widely.

Copy number variation in bipolar disorder.

Large (>100 kb), rare (<1% in the population) copy number variants (CNVs) have been shown to confer risk for schizophrenia (SZ), but the findings for bipolar disorder (BD) are less clear. In a new BD sample from the United Kingdom (n=2591), we have examined the occurrence of CNVs and compared this with previously reported samples of 6882 SZ and 8842 control subjects. When combined with previous data, we find evidence for a contribution to BD for three SZ-associated CNV loci: duplications at 1q21.1 (P=0.022), deletions at 3q29 (P=0.03) and duplications at 16p11.2 (P=2.3 × 10(-4)). The latter survives multiple-testing correction for the number of recurrent large CNV loci in the genome. Genes in 20 regions (total of 55 genes) were enriched for rare exonic CNVs among BD cases, but none of these survives correction for multiple testing. Finally, our data provide strong support for the hypothesis of a lesser contribution of very large (>500 kb) CNVs in BD compared with SZ, most notably for deletions >1 Mb (P=9 × 10(-4)).

Genome-wide analysis of over 106 000 individuals identifies 9 neuroticism-associated loci.

Neuroticism is a personality trait of fundamental importance for psychological well-being and public health. It is strongly associated with major depressive disorder (MDD) and several other psychiatric conditions. Although neuroticism is heritable, attempts to identify the alleles involved in previous studies have been limited by relatively small sample sizes. Here we report a combined meta-analysis of genome-wide association study (GWAS) of neuroticism that includes 91 370 participants from the UK Biobank cohort, 6659 participants from the Generation Scotland: Scottish Family Health Study (GS:SFHS) and 8687 participants from a QIMR (Queensland Institute of Medical Research) Berghofer Medical Research Institute (QIMR) cohort. All participants were assessed using the same neuroticism instrument, the Eysenck Personality Questionnaire-Revised (EPQ-R-S) Short Form's Neuroticism scale. We found a single-nucleotide polymorphism-based heritability estimate for neuroticism of ∼15% (s.e.=0.7%). Meta-analysis identified nine novel loci associated with neuroticism. The strongest evidence for association was at a locus on chromosome 8 (P=1.5 × 10(-15)) spanning 4 Mb and containing at least 36 genes. Other associated loci included interesting candidate genes on chromosome 1 (GRIK3 (glutamate receptor ionotropic kainate 3)), chromosome 4 (KLHL2 (Kelch-like protein 2)), chromosome 17 (CRHR1 (corticotropin-releasing hormone receptor 1) and MAPT (microtubule-associated protein Tau)) and on chromosome 18 (CELF4 (CUGBP elav-like family member 4)). We found no evidence for genetic differences in the common allelic architecture of neuroticism by sex. By comparing our findings with those of the Psychiatric Genetics Consortia, we identified a strong genetic correlation between neuroticism and MDD and a less strong but significant genetic correlation with schizophrenia, although not with bipolar disorder. Polygenic risk scores derived from the primary UK Biobank sample captured ∼1% of the variance in neuroticism in the GS:SFHS and QIMR samples, although most of the genome-wide significant alleles identified within a UK Biobank-only GWAS of neuroticism were not independently replicated within these cohorts. The identification of nine novel neuroticism-associated loci will drive forward future work on the neurobiology of neuroticism and related phenotypes.

Schizophrenia genetics: emerging themes for a complex disorder.

After two decades of frustration, genetic studies of schizophrenia have entered an era of spectacular success. Advances in genotyping technologies and high throughput sequencing, increasing analytic rigour and collaborative efforts on a global scale have generated a profusion of new findings. The broad conclusions from these studies are threefold: (1) schizophrenia is a highly polygenic disorder with a complex array of contributing risk loci across the allelic frequency spectrum; (2) many psychiatric illnesses share risk genes and alleles, specifically, schizophrenia has substantial overlaps with bipolar disorder, intellectual disability, major depressive disorder and autism spectrum disorders; and (3) some convergent biological themes are emerging from studies of schizophrenia and related disorders. In this commentary, we focus on the very recent findings that have emerged in the past 12 months, and in particular, the areas of convergence that are beginning to emerge from multiple study designs.

Evaluating historical candidate genes for schizophrenia.

Prior to the genome-wide association era, candidate gene studies were a major approach in schizophrenia genetics. In this invited review, we consider the current status of 25 historical candidate genes for schizophrenia (for example, COMT, DISC1, DTNBP1 and NRG1). The initial study for 24 of these genes explicitly evaluated common variant hypotheses about schizophrenia. Our evaluation included a meta-analysis of the candidate gene literature, incorporation of the results of the largest genomic study yet published for schizophrenia, ratings from informed researchers who have published on these genes, and ratings from 24 schizophrenia geneticists. On the basis of current empirical evidence and mostly consensual assessments of informed opinion, it appears that the historical candidate gene literature did not yield clear insights into the genetic basis of schizophrenia. A likely reason why historical candidate gene studies did not achieve their primary aims is inadequate statistical power. However, the considerable efforts embodied in these early studies unquestionably set the stage for current successes in genomic approaches to schizophrenia.

Genetic pleiotropy between multiple sclerosis and schizophrenia but not bipolar disorder: differential involvement of immune-related gene loci.

Converging evidence implicates immune abnormalities in schizophrenia (SCZ), and recent genome-wide association studies (GWAS) have identified immune-related single-nucleotide polymorphisms (SNPs) associated with SCZ. Using the conditional false discovery rate (FDR) approach, we evaluated pleiotropy in SNPs associated with SCZ (n=21,856) and multiple sclerosis (MS) (n=43,879), an inflammatory, demyelinating disease of the central nervous system. Because SCZ and bipolar disorder (BD) show substantial clinical and genetic overlap, we also investigated pleiotropy between BD (n=16,731) and MS. We found significant genetic overlap between SCZ and MS and identified 21 independent loci associated with SCZ, conditioned on association with MS. This enrichment was driven by the major histocompatibility complex (MHC). Importantly, we detected the involvement of the same human leukocyte antigen (HLA) alleles in both SCZ and MS, but with an opposite directionality of effect of associated HLA alleles (that is, MS risk alleles were associated with decreased SCZ risk). In contrast, we found no genetic overlap between BD and MS. Considered together, our findings demonstrate genetic pleiotropy between SCZ and MS and suggest that the MHC signals may differentiate SCZ from BD susceptibility.

Genetic overlap between Alzheimer's disease and Parkinson's disease at the MAPT locus.

We investigated the genetic overlap between Alzheimer's disease (AD) and Parkinson's disease (PD). Using summary statistics (P-values) from large recent genome-wide association studies (GWAS) (total n=89 904 individuals), we sought to identify single nucleotide polymorphisms (SNPs) associating with both AD and PD. We found and replicated association of both AD and PD with the A allele of rs393152 within the extended MAPT region on chromosome 17 (meta analysis P-value across five independent AD cohorts=1.65 × 10(-7)). In independent datasets, we found a dose-dependent effect of the A allele of rs393152 on intra-cerebral MAPT transcript levels and volume loss within the entorhinal cortex and hippocampus. Our findings identify the tau-associated MAPT locus as a site of genetic overlap between AD and PD, and extending prior work, we show that the MAPT region increases risk of Alzheimer's neurodegeneration.

Copy number variation in schizophrenia in Sweden.

Schizophrenia (SCZ) is a highly heritable neuropsychiatric disorder of complex genetic etiology. Previous genome-wide surveys have revealed a greater burden of large, rare copy number variations (CNVs) in SCZ cases and identified multiple rare recurrent CNVs that increase risk of SCZ although with incomplete penetrance and pleiotropic effects. Identification of additional recurrent CNVs and biological pathways enriched for SCZ CNVs requires greater sample sizes. We conducted a genome-wide survey for CNVs associated with SCZ using a Swedish national sample (4719 cases and 5917 controls). High-confidence CNV calls were generated using genotyping array intensity data, and their effect on risk of SCZ was measured. Our data confirm increased burden of large, rare CNVs in SCZ cases as well as significant associations for recurrent 16p11.2 duplications, 22q11.2 deletions and 3q29 deletions. We report a novel association for 17q12 duplications (odds ratio=4.16, P=0.018), previously associated with autism and mental retardation but not SCZ. Intriguingly, gene set association analyses implicate biological pathways previously associated with SCZ through common variation and exome sequencing (calcium channel signaling and binding partners of the fragile X mental retardation protein). We found significantly increased burden of the largest CNVs (>500 kb) in genes present in the postsynaptic density, in genomic regions implicated via SCZ genome-wide association studies and in gene products localized to mitochondria and cytoplasm. Our findings suggest that multiple lines of genomic inquiry--genome-wide screens for CNVs, common variation and exonic variation--are converging on similar sets of pathways and/or genes.

Evidence that duplications of 22q11.2 protect against schizophrenia.

A number of large, rare copy number variants (CNVs) are deleterious for neurodevelopmental disorders, but large, rare, protective CNVs have not been reported for such phenotypes. Here we show in a CNV analysis of 47 005 individuals, the largest CNV analysis of schizophrenia to date, that large duplications (1.5-3.0 Mb) at 22q11.2--the reciprocal of the well-known, risk-inducing deletion of this locus--are substantially less common in schizophrenia cases than in the general population (0.014% vs 0.085%, OR=0.17, P=0.00086). 22q11.2 duplications represent the first putative protective mutation for schizophrenia.

The ENCODE project: implications for psychiatric genetics.

The ENCyclopedia Of DNA Elements (ENCODE) project is a public research consortium that aims to identify all functional elements of the human genome sequence. The project comprised 1640 data sets, from 147 different cell type and the findings were released in a coordinated set of 34 publications across several journals. The ENCODE publications report that 80.4% of the human genome displays some functionality. These data have important implications for interpreting results from large-scale genetics studies. We reviewed some of the key findings from the ENCODE publications and discuss how they can influence or inform further investigations into the genetic factors contributing to neuropsychiatric disorders.