Molecular pathways involved in neuronal cell adhesion and membrane scaffolding contribute to schizophrenia and bipolar disorder susceptibility

Progress in defining the biological causes of schizophrenia

Schizophrenia is a common mental illness resulting from a complex interplay of genetic and environmental risk factors. Establishing its primary molecular and cellular aetiopathologies has proved difficult. However, this is a vital step towards the rational development of useful disease biomarkers and new therapeutic strategies. The advent and large-scale application of genomic, transcriptomic, proteomic and metabolomic technologies are generating data sets required to achieve this goal. This discovery phase, typified by its objective and hypothesis-free approach, is described in the first part of the review. The accumulating biological information, when viewed as a whole, reveals a number of biological process and subcellular locations that contribute to schizophrenia causation. The data also show that each technique targets different aspects of central nervous system function in the disease state. In the second part of the review, key schizophrenia candidate genes are discussed more fully. Two higher-order processes - adult neurogenesis and inflammation - that appear to have pathological relevance are also described in detail. Finally, three areas where progress would have a large impact on schizophrenia biology are discussed: deducing the causes of schizophrenia in the individual, explaining the phenomenon of cross-disorder risk factors, and distinguishing causative disease factors from those that are reactive or compensatory.

Avoiding mouse traps in schizophrenia genetics: lessons and promises from current and emerging mouse models

Schizophrenia is one of the most common psychiatric disorders, but despite progress in identifying the genetic factors implicated in its development, the mechanisms underlying its etiology and pathogenesis remain poorly understood. Development of mouse models is critical for expanding our understanding of the causes of schizophrenia. However, translation of disease pathology into mouse models has proven to be challenging, primarily due to the complex genetic architecture of schizophrenia and the difficulties in the re-creation of susceptibility alleles in the mouse genome. In this review we highlight current research on models of major susceptibility loci and the information accrued from their analysis. We describe and compare the different approaches that are necessitated by diverse susceptibility alleles, and discuss their advantages and drawbacks. Finally, we discuss emerging mouse models, such as second-generation pathophysiology models based on innovative approaches that are facilitated by the information gathered from the current genetic mouse models.

Genetic regulation of Nrxn1 [corrected] expression: an integrative cross-species analysis of schizophrenia candidate genes

Neurexin 1 (NRXN1) is a large presynaptic transmembrane protein that has complex and variable patterns of expression in the brain. Sequence variants in NRXN1 are associated with differences in cognition, and with schizophrenia and autism. The murine Nrxn1 gene is also highly polymorphic and is associated with significant variation in expression that is under strong genetic control. Here, we use co-expression analysis, high coverage genomic sequence, and expression quantitative trait locus (eQTL) mapping to study the regulation of this gene in the brain. We profiled a family of 72 isogenic progeny strains of a cross between C57BL/6J and DBA/2J (the BXD family) using exon arrays and massively parallel RNA sequencing. Expression of most Nrxn1 exons have high genetic correlation (r>0.6) because of the segregation of a common trans eQTL on chromosome (Chr) 8 and a common cis eQTL on Chr 17. These two loci are also linked to murine phenotypes relevant to schizophrenia and to a novel human schizophrenia candidate gene with high neuronal expression (Pleckstrin and Sec7 domain containing 3). In both human and mice, NRXN1 is co-expressed with numerous synaptic and cell signaling genes, and known schizophrenia candidates. Cross-species co-expression and protein interaction network analyses identified glycogen synthase kinase 3 beta (GSK3B) as one of the most consistent and conserved covariates of NRXN1. By using the Molecular Genetics of Schizophrenia data set, we were able to test and confirm that markers in NRXN1 and GSK3B have epistatic interactions in human populations that can jointly modulate risk of schizophrenia.

Gene set analysis of genome-wide association studies: methodological issues and perspectives

Recent studies have demonstrated that gene set analysis, which tests disease association with genetic variants in a group of functionally related genes, is a promising approach for analyzing and interpreting genome-wide association studies (GWAS) data. These approaches aim to increase power by combining association signals from multiple genes in the same gene set. In addition, gene set analysis can also shed more light on the biological processes underlying complex diseases. However, current approaches for gene set analysis are still in an early stage of development in that analysis results are often prone to sources of bias, including gene set size and gene length, linkage disequilibrium patterns and the presence of overlapping genes. In this paper, we provide an in-depth review of the gene set analysis procedures, along with parameter choices and the particular methodology challenges at each stage. In addition to providing a survey of recently developed tools, we also classify the analysis methods into larger categories and discuss their strengths and limitations. In the last section, we outline several important areas for improving the analytical strategies in gene set analysis.

Neuronal cell adhesion genes: Key players in risk for schizophrenia, bipolar disorder and other neurodevelopmental brain disorders?

The major mental disorders, schizophrenia and bipolar disorder are substantially heritable. Recent genomic studies have identified a small number of common and rare risk genes contributing to both disorders and support epidemiological evidence that genetic susceptibility overlaps between them. Prompted by the question of whether risk genes cluster in specific molecular pathways or implicate discrete mechanisms we and others have developed hypothesis-free methods of investigating genome-wide association datasets at a pathway-level. The application of our method to the 212 experimentally-derived pathways in the Kyoto Encycolpaedia of Genes and Genomes (KEGG) database identified significant association between the cell adhesion molecule (CAM) pathway and both schizophrenia and bipolar disorder susceptibility across three GWAS datasets. Interestingly, a similar approach applied to an autistic spectrum disorders (ASDs) sample identified a similar pathway and involved many of the same genes. Disruption of a number of these genes (including NRXN1, CNTNAP2 and CASK) are known to cause diverse neurodevelopmental brain disorder phenotypes including schizophenia, autism, learning disability and specific language disorder. Taken together these studies bring the CAM pathway sharply into focus for more comprehensive DNA sequencing to identify the critical genes, and investigate their relationships and interaction with environmental risk factors in the expression of many seemingly different neurodevelopmental disorders.

Schizophrenia: a pathogenetic autoimmune disease caused by viruses and pathogens and dependent on genes

Many genes have been implicated in schizophrenia as have viral prenatal or adult infections and toxoplasmosis or Lyme disease. Several autoantigens also target key pathology-related proteins. These factors are interrelated. Susceptibility genes encode for proteins homologous to those of the pathogens while the autoantigens are homologous to pathogens' proteins, suggesting that the risk-promoting effects of genes and risk factors are conditional upon each other, and dependent upon protein matching between pathogen and susceptibility gene products. Pathogens' proteins may act as dummy ligands, decoy receptors, or via interactome interference. Many such proteins are immunogenic suggesting that antibody mediated knockdown of multiple schizophrenia gene products could contribute to the disease, explaining the immune activation in the brain and lymphocytes in schizophrenia, and the preponderance of immune-related gene variants in the schizophrenia genome. Schizophrenia may thus be a “pathogenetic” autoimmune disorder, caused by pathogens, genes, and the immune system acting together, and perhaps preventable by pathogen elimination, or curable by the removal of culpable antibodies and antigens.

A common genetic variant in the neurexin superfamily member CNTNAP2 is associated with increased risk for selective mutism and social anxiety-related traits

BACKGROUND

Selective mutism (SM), considered an early-onset variant of social anxiety disorder, shares features of impaired social interaction and communication with autism spectrum disorders (ASDs) suggesting a possible shared pathophysiology. We examined association of a susceptibility gene, contactin-associated protein-like 2 (CNTNAP2), for ASDs and specific language impairment with SM and social anxiety-related traits.

METHODS

Sample 1 subjects were 99 nuclear families including 106 children with SM. Sample 2 subjects were young adults who completed measures of social interactional anxiety (n = 1028) and childhood behavioral inhibition (n = 920). Five single nucleotide polymorphisms in CNTNAP2 (including rs7794745 and rs2710102, previously associated with ASDs) were genotyped.

RESULTS

Analyses revealed nominal significance (p = .018) for association of SM with rs2710102, which, with rs6944808, was part of a common haplotype associated with SM (permutation p = .022). Adjusting for sex and ancestral proportion, each copy of the rs2710102*a risk allele in the young adults was associated with increased odds of being >1 SD above the mean on the Social Interactional Anxiety Scale (odds ratio = 1.33, p = .015) and Retrospective Self-Report of Inhibition (odds ratio = 1.40, p = .010).

CONCLUSIONS

Although association was found with rs2710102, the risk allele (a) for the traits studied here is the nonrisk allele for ASD and specific language impairment. These findings suggest a partially shared etiology between ASDs and SM and raise questions about which aspects of these syndromes are potentially influenced by CNTNAP2 and mechanism(s) by which these influences may be conveyed.

Convergent functional genomic studies of ω-3 fatty acids in stress reactivity, bipolar disorder and alcoholism

Omega-3 fatty acids have been proposed as an adjuvant treatment option in psychiatric disorders. Given their other health benefits and their relative lack of toxicity, teratogenicity and side effects, they may be particularly useful in children and in females of child-bearing age, especially during pregnancy and postpartum. A comprehensive mechanistic understanding of their effects is needed. Here we report translational studies demonstrating the phenotypic normalization and gene expression effects of dietary omega-3 fatty acids, specifically docosahexaenoic acid (DHA), in a stress-reactive knockout mouse model of bipolar disorder and co-morbid alcoholism, using a bioinformatic convergent functional genomics approach integrating animal model and human data to prioritize disease-relevant genes. Additionally, to validate at a behavioral level the novel observed effects on decreasing alcohol consumption, we also tested the effects of DHA in an independent animal model, alcohol-preferring (P) rats, a well-established animal model of alcoholism. Our studies uncover sex differences, brain region-specific effects and blood biomarkers that may underpin the effects of DHA. Of note, DHA modulates some of the same genes targeted by current psychotropic medications, as well as increases myelin-related gene expression. Myelin-related gene expression decrease is a common, if nonspecific, denominator of neuropsychiatric disorders. In conclusion, our work supports the potential utility of omega-3 fatty acids, specifically DHA, for a spectrum of psychiatric disorders such as stress disorders, bipolar disorder, alcoholism and beyond.

Analysing biological pathways in genome-wide association studies

Genome-wide association (GWA) studies have typically focused on the analysis of single markers, which often lacks the power to uncover the relatively small effect sizes conferred by most genetic variants. Recently, pathway-based approaches have been developed, which use prior biological knowledge on gene function to facilitate more powerful analysis of GWA study data sets. These approaches typically examine whether a group of related genes in the same functional pathway are jointly associated with a trait of interest. Here we review the development of pathway-based approaches for GWA studies, discuss their practical use and caveats, and suggest that pathway-based approaches may also be useful for future GWA studies with sequencing data.

Genetic advances in the study of speech and language disorders

Developmental speech and language disorders cover a wide range of childhood conditions with overlapping but heterogeneous phenotypes and underlying etiologies. This characteristic heterogeneity hinders accurate diagnosis, can complicate treatment strategies, and causes difficulties in the identification of causal factors. Nonetheless, over the last decade, genetic variants have been identified that may predispose certain individuals to different aspects of speech and language difficulties. In this review, we summarize advances in the genetic investigation of stuttering, speech-sound disorder (SSD), specific language impairment (SLI), and developmental verbal dyspraxia (DVD). We discuss how the identification and study of specific genes and pathways, including FOXP2, CNTNAP2, ATP2C2, CMIP, and lysosomal enzymes, may advance our understanding of the etiology of speech and language disorders and enable us to better understand the relationships between the different forms of impairment across the spectrum.

RAPID detection of gene-gene interactions in genome-wide association studies

MOTIVATION

In complex disorders, independently evolving locus pairs might interact to confer disease susceptibility, with only a modest effect at each locus. With genome-wide association studies on large cohorts, testing all pairs for interaction confers a heavy computational burden, and a loss of power due to large Bonferroni-like corrections. Correspondingly, limiting the tests to pairs that show marginal effect at either locus, also has reduced power. Here, we describe an algorithm that discovers interacting locus pairs without explicitly testing all pairs, or requiring a marginal effect at each locus. The central idea is a mathematical transformation that maps 'statistical correlation between locus pairs' to 'distance between two points in a Euclidean space'. This enables the use of geometric properties to identify proximal points (correlated locus pairs), without testing each pair explicitly. For large datasets (∼ 10(6) SNPs), this reduces the number of tests from 10(12) to 10(6), significantly reducing the computational burden, without loss of power. The speed of the test allows for correction using permutation-based tests. The algorithm is encoded in a tool called RAPID (RApid Pair IDentification) for identifying paired interactions in case-control GWAS.

RESULTS

We validated RAPID with extensive tests on simulated and real datasets. On simulated models of interaction, RAPID easily identified pairs with small marginal effects. On the benchmark disease, datasets from The Wellcome Trust Case Control Consortium, RAPID ran in about 1 CPU-hour per dataset, and identified many significant interactions. In many cases, the interacting loci were known to be important for the disease, but were not individually associated in the genome-wide scan.

AVAILABILITY

http://bix.ucsd.edu/projects/rapid.

Common variants conferring risk of schizophrenia: a pathway analysis of GWAS data

Unlike the typical analysis of single markers in genome-wide association studies (GWAS), we incorporated Gene Set Enrichment Analysis (GSEA) and hypergeometric test and combined them using Fisher's combined method to perform pathway-based analysis in order to detect genes' combined effects on mediating schizophrenia. A few pathways were consistently found to be top ranked and likely associated with schizophrenia by these methods; they are related to metabolism of glutamate, the process of apoptosis, inflammation, and immune system (e.g., glutamate metabolism pathway, TGF-beta signaling pathway, and TNFR1 pathway). The genes involved in these pathways had not been detected by single marker analysis, suggesting this approach may complement the original analysis of GWAS dataset.

White matter neuron alterations in schizophrenia and related disorders

Increased density and altered spatial distribution of subcortical white matter neurons (WMNs) represents one of the more well replicated cellular alterations found in schizophrenia and related disease. In many of the affected cases, the underlying genetic risk architecture for these WMN abnormalities remains unknown. Increased density of neurons immunoreactive for Microtubule-Associated Protein 2 (MAP2) and Neuronal Nuclear Antigen (NeuN) have been reported by independent studies, though there are negative reports as well; additionally, group differences in some of the studies appear to be driven by a small subset of cases. Alterations in markers for inhibitory (GABAergic) neurons have also been described. For example, downregulation of neuropeptide Y (NPY) and nitric oxide synthase (NOS1) in inhibitory WMN positioned at the gray/white matter border, as well as altered spatial distribution, have been reported. While increased density of WMN has been suggested to reflect disturbance of neurodevelopmental processes, including neuronal migration, neurogenesis, and cell death, alternative hypotheses--such as an adaptive response to microglial activation in mature CNS, as has been described in multiple sclerosis--should also be considered. We argue that larger scale studies involving hundreds of postmortem specimens will be necessary in order to clearly establish the subset of subjects affected. Additionally, these larger cohorts could make it feasible to connect the cellular pathology to environmental and genetic factors implicated in schizophrenia, bipolar disorder, and autism. These could include the 22q11 deletion (Velocardiofacial/DiGeorge) syndrome, which in some cases is associated with neuronal ectopias in white matter.

Functional impact of global rare copy number variation in autism spectrum disorders

The autism spectrum disorders (ASDs) are a group of conditions characterized by impairments in reciprocal social interaction and communication, and the presence of restricted and repetitive behaviours. Individuals with an ASD vary greatly in cognitive development, which can range from above average to intellectual disability. Although ASDs are known to be highly heritable ( approximately 90%), the underlying genetic determinants are still largely unknown. Here we analysed the genome-wide characteristics of rare (<1% frequency) copy number variation in ASD using dense genotyping arrays. When comparing 996 ASD individuals of European ancestry to 1,287 matched controls, cases were found to carry a higher global burden of rare, genic copy number variants (CNVs) (1.19 fold, P = 0.012), especially so for loci previously implicated in either ASD and/or intellectual disability (1.69 fold, P = 3.4 x 10(-4)). Among the CNVs there were numerous de novo and inherited events, sometimes in combination in a given family, implicating many novel ASD genes such as SHANK2, SYNGAP1, DLGAP2 and the X-linked DDX53-PTCHD1 locus. We also discovered an enrichment of CNVs disrupting functional gene sets involved in cellular proliferation, projection and motility, and GTPase/Ras signalling. Our results reveal many new genetic and functional targets in ASD that may lead to final connected pathways.