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

Integrated enrichment analysis of variants and pathways in genome-wide association studies indicates central role for IL-2 signaling genes in type 1 diabetes, and cytokine signaling genes in Crohn's disease

Pathway analyses of genome-wide association studies aggregate information over sets of related genes, such as genes in common pathways, to identify gene sets that are enriched for variants associated with disease. We develop a model-based approach to pathway analysis, and apply this approach to data from the Wellcome Trust Case Control Consortium (WTCCC) studies. Our method offers several benefits over existing approaches. First, our method not only interrogates pathways for enrichment of disease associations, but also estimates the level of enrichment, which yields a coherent way to promote variants in enriched pathways, enhancing discovery of genes underlying disease. Second, our approach allows for multiple enriched pathways, a feature that leads to novel findings in two diseases where the major histocompatibility complex (MHC) is a major determinant of disease susceptibility. Third, by modeling disease as the combined effect of multiple markers, our method automatically accounts for linkage disequilibrium among variants. Interrogation of pathways from eight pathway databases yields strong support for enriched pathways, indicating links between Crohn's disease (CD) and cytokine-driven networks that modulate immune responses; between rheumatoid arthritis (RA) and "Measles" pathway genes involved in immune responses triggered by measles infection; and between type 1 diabetes (T1D) and IL2-mediated signaling genes. Prioritizing variants in these enriched pathways yields many additional putative disease associations compared to analyses without enrichment. For CD and RA, 7 of 8 additional non-MHC associations are corroborated by other studies, providing validation for our approach. For T1D, prioritization of IL-2 signaling genes yields strong evidence for 7 additional non-MHC candidate disease loci, as well as suggestive evidence for several more. Of the 7 strongest associations, 4 are validated by other studies, and 3 (near IL-2 signaling genes RAF1, MAPK14, and FYN) constitute novel putative T1D loci for further study.

CNTNAP2 polymorphisms and structural brain connectivity: a diffusion-tensor imaging study

CNTNAP2 is a gene on chromosome 7 that has shown associations with autism and schizophrenia, and there is evidence that it plays an important role for neuronal synchronization and brain connectivity. In this study, we assessed the relationship between Diffusion Tensor Imaging (DTI), a putative marker of anatomical brain connectivity, and multiple single nucleotide polymorphisms (SNPs) spread out over this large gene. 81 healthy controls and 44 patients with schizophrenia (all Caucasian) underwent DTI and genotyping of 31 SNPs within CNTNAP2. We employed Tract-based Spatial Statistics (TBSS) for inter-subject brain registration and computed average diffusivity values for six major white matter tracts. Analyses of Covariance (ANCOVAs) were computed to test for possible associations with genotypes. The strongest association, which survived rigorous Bonferroni correction, was between rs2710126 genotype and Fractional Anisotropy (FA) in the uncinate fasciculus (p = .00003). This anatomical location is particularly interesting given the enriched fronto-temporal expression of CNTNAP2 in the developing brain. For this SNP, no phenotype association has been reported before. There were several further genotype-DTI associations that were nominally significant but did not survive Bonferroni correction, including an association between axial diffusivity in the dorsal cingulum bundle and a region in intron 13 (represented by rs2710102, rs759178, rs2538991), which has previously been reported to be associated with anterior-posterior functional connectivity. We present new evidence about the effects of CNTNAP2 on brain connectivity, whose disruption has been hypothesized to be central to schizophrenia pathophysiology.

What psychiatric genetics has taught us about the nature of psychiatric illness and what is left to learn

Psychiatric genetics has taught us a great deal about the nature of psychiatric disorders. Traditional family, twin and adoption studies have demonstrated the substantial role of genetic factors in their etiology, clarified the role of genetic factors in comorbidity, elucidated development pathways, and documented the importance of gene-environment correlation and interaction. We have also received some hard lessons when we were unable to detect replicable genes of large effect size and found that our much-valued candidate genes did not live up to their expected promise. With more mature molecular and statistical methods, we are entering now a different era. Statistical analyses of aggregate molecular signals are validating earlier heritability estimates. Replicated findings from genome-wide association studies are beginning to emerge, as are discoveries of large-effect size rare genomic variants. The number of such findings is likely to soon grow dramatically. The most pressing question facing the field is what biological picture these results will reveal. I articulate four possible scenarios that reflect (i) no, (ii) minimal, (iii) moderate and (iv) high biological coherence in the replicated molecular variant findings, which are soon likely to emerge. I discuss the factors that will likely influence these patterns, including the problems of etiological heterogeneity and multiple realizability. These findings could provide critical insights into the underlying biology of our psychiatric syndromes and potentially permit us to perceive, 'through a glass darkly,' the levels of the mind-brain system that are disordered.

Focal adhesion dynamics are altered in schizophrenia

BACKGROUND

Evidence from genetic association studies implicate genes involved in neural migration associated with schizophrenia risk. Neural stem/progenitor cell cultures (neurosphere-derived cells) from olfactory mucosa of schizophrenia patients have significantly dysregulated expression of genes in focal adhesion kinase (FAK) signaling, a key pathway regulating cell adhesion and migration. The aim of this study was to investigate whether olfactory neurosphere-derived cells from schizophrenia patients have altered cell adhesion, cell motility, and focal adhesion dynamics.

METHODS

Olfactory neurosphere-derived cells from nine male schizophrenia patients and nine male healthy control subjects were used. Cells were assayed for cell adhesion and cell motility and analyzed for integrins and FAK proteins. Focal adhesions were counted and measured in fixed cells, and time-lapse imaging was used to assess cell motility and focal adhesion dynamics.

RESULTS

Patient-derived cells were less adhesive and more motile than cells derived from healthy control subjects, and their motility was reduced to control cell levels by integrin-blocking antibodies and by inhibition of FAK. Vinculin-stained focal adhesion complexes were significantly smaller and fewer in patient cells. Time-lapse imaging of cells expressing FAK tagged with green fluorescent protein revealed that the disassembly of focal adhesions was significantly faster in patient cells.

CONCLUSIONS

The evidence for altered motility and focal adhesion dynamics in patient-derived cells is consistent with dysregulated gene expression in the FAK signaling pathway in these cells. Alterations in cell adhesion dynamics and cell motility could bias the trajectory of brain development in schizophrenia.

Decreased cerebrospinal fluid secretogranin II concentrations in severe forms of bipolar disorder

BACKGROUND

Bipolar disorder is a common psychiatric mood disorder that is defined by recurrent episodes of abnormally elevated mood and depression. Progressive structural brain changes in individuals with bipolar disorder have been suggested to be associated with defects in the secretion of neurotrophic factors. We sought to assess how the regulated secretory pathway in the brain is affected in patients with bipolar disorder by measuring chromogranin B and secretogranin II, which are 2 cerebrospinal fluid (CSF) biological markers for this process.

METHODS

We measured the concentrations of chromogranin B (peptide 439-451) and secretogranin II (peptide 154-165) in the CSF of patients with well-defined bipolar disorder and healthy controls. The lifetime severity of bipolar disorder was rated using the Clinical Global Impression (CGI) scale.

RESULTS

We included 126 patients with bipolar disorder and 71 healthy controls in our analysis. Concentrations of secretogranin II were significantly lower in patients with bipolar disorder type I than in healthy controls. The reduction was most pronounced in patients with high CGI scores (i.e., severe disease).

LIMITATIONS

The cross-sectional design of the current study limits the ability to pinpoint the causalities behind the observed associations.

CONCLUSION

This study shows that the CSF marker secretogranin II has the potential to act as a biological marker for severe forms of bipolar disorder. Our findings indicate that patients with bipolar disorder possess defects in the regulatory secretory pathway, which may be of relevance to the progressive structural brain changes seen in those with severe forms of the disease.

The genomic psychiatry cohort: partners in discovery

The Genomic Psychiatry Cohort (GPC) is a longitudinal resource designed to provide the necessary population-based sample for large-scale genomic studies, studies focusing on Research Domain Criteria (RDoC) and/or other alternate phenotype constructs, clinical and interventional studies, nested case-control studies, long-term disease course studies, and genomic variant-to-phenotype studies. We provide and will continue to encourage access to the GPC as an international resource. DNA and other biological samples and diagnostic data are available through the National Institute of Mental Health (NIMH) Repository. After appropriate review and approval by an advisory board, investigators are able to collaborate in, propose, and co-lead studies involving cohort participants.

"Selfish spermatogonial selection": a novel mechanism for the association between advanced paternal age and neurodevelopmental disorders

There is robust evidence from epidemiological studies that the offspring of older fathers have an increased risk of neurodevelopmental disorders, such as schizophrenia and autism. The authors present a novel mechanism that may contribute to this association. Because the male germ cell undergoes many more cell divisions across the reproductive age range, copy errors taking place in the paternal germline are associated with de novo mutations in the offspring of older men. Recently it has been recognized that somatic mutations in male germ cells that modify proliferation through dysregulation of the RAS protein pathway can lead to within-testis expansion of mutant clonal lines. First identified in association with rare disorders related to paternal age (e.g., Apert syndrome, achondroplasia), this process is known as "selfish spermatogonial selection." This mechanism favors propagation of germ cells carrying pathogenic mutations, increasingly skews the mutational profile of sperm as men age, and enriches de novo mutations in the offspring of older fathers that preferentially affect specific cellular signaling pathways. This mechanism not only offers a parsimonious explanation for the association between advanced paternal age and various neurodevelopmental disorders but also provides insights into the genetic architecture (role of de novo mutations), neurobiological correlates (altered cell cycle), and some epidemiological features of these disorders. The authors outline hypotheses to test this model. Given the secular changes for delayed parenthood in most societies, this hypothesis has important public health implications.

A comprehensive family-based replication study of schizophrenia genes

IMPORTANCE

Schizophrenia (SCZ) is a devastating psychiatric condition. Identifying the specific genetic variants and pathways that increase susceptibility to SCZ is critical to improve disease understanding and address the urgent need for new drug targets.

OBJECTIVE

To identify SCZ susceptibility genes.

DESIGN

We integrated results from a meta-analysis of 18 genome-wide association studies (GWAS) involving 1,085,772 single-nucleotide polymorphisms (SNPs) and 6 databases that showed significant informativeness for SCZ. The 9380 most promising SNPs were then specifically genotyped in an independent family-based replication study that, after quality control, consisted of 8107 SNPs.

SETTING

Linkage meta-analysis, brain transcriptome meta-analysis, candidate gene database, OMIM, relevant mouse studies, and expression quantitative trait locus databases.

PATIENTS

We included 11,185 cases and 10,768 control subjects from 6 databases and, after quality control 6298 individuals (including 3286 cases) from 1811 nuclear families.

MAIN OUTCOMES AND MEASURES

Case-control status for SCZ.

RESULTS

Replication results showed a highly significant enrichment of SNPs with small P values. Of the SNPs with replication values of P.01, the proportion of SNPs that had the same direction of effects as in the GWAS meta-analysis was 89% in the combined ancestry group (sign test, P < 2.20 x 10(-16) and 93% in subjects of European ancestry only (P < 2.20 < 10(-16)). Our results supported the major histocompatibility complex region showing a3.7-fold overall enrichment of replication values of P < .01 in subjects from European ancestry. We replicated SNPs in TCF4 (P = 2.53 x 10(-10)) and NOTCH4 (P = 3.16 x 10(-7)) that are among the most robust SCZ findings. More novel findings included POM121L2 (P = 3.51 x 10(-7)), AS3MT (P = 9.01 x 10(-7)), CNNM2 (P = 6.07 = 10(-7)), and NT5C2(P = 4.09 x 10(-7)). To explore the many small effects, we performed pathway analyses. The most significant pathways involved neuronal function (axonal guidance, neuronal systems, and L1 cell adhesion molecule interaction)and the immune system (antigen processing, cell adhesion molecules relevant to T cells, and translocation to immunological synapse).

CONCLUSIONS AND RELEVANCE

We replicated novel SCZ disease genes and pathogenic pathways. Better understanding the molecular and biological mechanisms involved with schizophrenia may improve disease management and may identify new drug targets.

White matter integrity as an intermediate phenotype: exploratory genome-wide association analysis in individuals at high risk of bipolar disorder

White matter integrity, as measured using diffusion tensor imaging (DTI), is reduced in individuals with bipolar disorder (BD), their unaffected relatives and carriers of specific risk-alleles. Fractional anisotropy (FA), an index of white matter integrity, is highly heritable but the genetic architecture of this trait has received little investigation. In this study we performed a genome-wide association study with FA as quantitative phenotype, in unaffected relatives of patients with BD (N=70) and a matched control group (N=80). Amongst our top results were SNPs located in genes involved in cell adhesion, white matter development and neuronal plasticity. Pathway analysis of the top associated polymorphisms and genes confirmed the enrichment of processes relevant to BD and white matter development, including axon guidance, ErbB-signalling neurotrophin signalling, phosphatidylinositol signalling, and cell adhesion. The majority of genes implicated in these pathways were differentially associated with FA in individuals at high familial risk, suggesting interactions with genetic background or environmental factors secondary to familial risk for BD. Although the present findings require independent replication, the results encourage the use of global FA as a quantitative phenotype in future large-scale studies which may help to identify the biological processes underlying reduced FA in BD and other psychiatric disorders.

Genome-wide gene-set analysis for identification of pathways associated with alcohol dependence

It is believed that multiple genetic variants with small individual effects contribute to the risk of alcohol dependence. Such polygenic effects are difficult to detect in genome-wide association studies that test for association of the phenotype with each single nucleotide polymorphism (SNP) individually. To overcome this challenge, gene-set analysis (GSA) methods that jointly test for the effects of pre-defined groups of genes have been proposed. Rather than testing for association between the phenotype and individual SNPs, these analyses evaluate the global evidence of association with a set of related genes enabling the identification of cellular or molecular pathways or biological processes that play a role in development of the disease. It is hoped that by aggregating the evidence of association for all available SNPs in a group of related genes, these approaches will have enhanced power to detect genetic associations with complex traits. We performed GSA using data from a genome-wide study of 1165 alcohol-dependent cases and 1379 controls from the Study of Addiction: Genetics and Environment (SAGE), for all 200 pathways listed in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Results demonstrated a potential role of the 'synthesis and degradation of ketone bodies' pathway. Our results also support the potential involvement of the 'neuroactive ligand-receptor interaction' pathway, which has previously been implicated in addictive disorders. These findings demonstrate the utility of GSA in the study of complex disease, and suggest specific directions for further research into the genetic architecture of alcohol dependence.

Genetic variation throughout the folate metabolic pathway influences negative symptom severity in schizophrenia

Low serum folate levels previously have been associated with negative symptom risk in schizophrenia, as has the hypofunctional 677C>T variant of the MTHFR gene. This study examined whether other missense polymorphisms in folate-regulating enzymes, in concert with MTHFR, influence negative symptoms in schizophrenia, and whether total risk allele load interacts with serum folate status to further stratify negative symptom risk. Medicated outpatients with schizophrenia (n = 219), all of European origin and some included in a previous report, were rated with the Positive and Negative Syndrome Scale. A subset of 82 patients also underwent nonfasting serum folate testing. Patients were genotyped for the MTHFR 677C>T (rs1801133), MTHFR 1298A>C (rs1801131), MTR 2756A>G (rs1805087), MTRR 203A>G (rs1801394), FOLH1 484T>C (rs202676), RFC 80A>G (rs1051266), and COMT 675G>A (rs4680) polymorphisms. All genotypes were entered into a linear regression model to determine significant predictors of negative symptoms, and risk scores were calculated based on total risk allele dose. Four variants, MTHFR 677T, MTR 2756A, FOLH1 484C, and COMT 675A, emerged as significant independent predictors of negative symptom severity, accounting for significantly greater variance in negative symptoms than MTHFR 677C>T alone. Total allele dose across the 4 variants predicted negative symptom severity only among patients with low folate levels. These findings indicate that multiple genetic variants within the folate metabolic pathway contribute to negative symptoms of schizophrenia. A relationship between folate level and negative symptom severity among patients with greater genetic vulnerability is biologically plausible and suggests the utility of folate supplementation in these patients.

Significant association of close homologue of L1 gene polymorphism rs2272522 with schizophrenia in Qatar

INTRODUCTION

Previous reports have found that polymorphisms in the close homologue of L1 (CHL1) gene located on chromosome 3p26 are associated with schizophrenia among different ethnic populations. The aim of this study was to examine the associations of single nucleotides polymorphisms (SNPs) of the CHL1 gene locus, including rs2055314 (C/T), rs2272522 (C/T) and rs331894 (A/G), with schizophrenia in the Qatari population.

METHODS

An association case control study was carried out on 86 Qatari schizophrenic patients from the Psychiatry Hospital, Hammed Medical Corporation, Qatar and 88 Qatari unrelated, healthy, control subjects. Schizophrenia was diagnosed according to the Diagnostic and Statistical Manual of Mental Disorders - Fourth Edition (DSM-IV) criteria for schizophrenia by two independent psychiatrists. Genotyping of the SNPs rs2055314 (C/T), rs2272522 (C/T) and rs331894 (A/G) was conducted using the 5' nuclease assay with the TaqMan MGB probe and an ABI 7500.

RESULTS

Individuals with the rs2272522 TT genotype had approximately 4.2 times greater risk of schizophrenia compared to individuals with the CC genotype (OR = 4.21; 95% CI: 1.12-15.53; P = 0.047). In addition, individuals carrying a T allele of the rs2272522 SNP had a significantly increased risk of schizophrenia (1.78 times) among the population (P = 0.028). SNPs rs2055314 and rs331894 had no significant association with schizophrenia. Pairwise linkage disequilibrium (LD) between the three polymorphisms was modest in the schizophrenic group.

DISCUSSION

The rs2272522 polymorphism was found to exhibit a highly significant association with schizophrenia in the Qatari population. This finding supports the hypothesis that cell adhesion molecules may be involved in the etiology of this disease among Qatari patients.

A missense mutation in the ITGA8 gene, a cell adhesion molecule gene, is associated with schizophrenia in Japanese female patients

BACKGROUND

Cell adhesion molecules (CAMs) play pivotal role in the development of the central nervous system (CNS) and have also been reported to play role in the pathophysiology of schizophrenia. Missense mutations in the CAMs genes might alter the binding of their ligands, increasing the vulnerability to develop schizophrenia.

METHODS

We selected 15 missense mutations in the CAMs genes of the CNS reported in the Kyoto Encyclopedia of Genes and Genomes (KEGG) and examined the association between these mutations and schizophrenia in 278 patients and 284 control subjects (first batch). We also genotyped the positive single nucleotide polymorphisms (SNPs) in 567 patients and 710 control subjects (second batch) and in 635 patients and 639 control subjects (replication samples).

RESULTS

Genotypic and allelic distributions of rs2298033 in the ITGA8 gene between the schizophrenia and control groups were significantly different in the first batch (p=0.005 and 0.007, respectively). Gender-based analysis revealed that the allelic and genotypic distributions of rs2298033 in the ITGA8 were significantly different between the schizophrenia and control groups among females in both batches (p=0.010, 0.011 and 0.0086, 0.010, respectively) but not among males. Combine analysis of rs2298033 with the replication samples revealed a more significant differences (p=0.0032; 0.0035 in the overall subjects and p=0.0024; 0.0025 in the female subjects, respectively). The significant differences for rs2802808 of the NFASC gene were only observed in the female subgroup of the first batch.

CONCLUSION

These results suggest that the ITGA8 gene might have gender-specific roles in the development of schizophrenia. Further replication and functional studies are required to confirm these findings.

Pathway analysis using information from allele-specific gene methylation in genome-wide association studies for bipolar disorder

Bipolar disorder (BPD) is a complex psychiatric trait with high heritability. Despite efforts through conducting genome-wide association (GWA) studies, the success of identifying susceptibility loci for BPD has been limited, which is partially attributed to the complex nature of its pathogenesis. Pathway-based analytic strategy is a powerful tool to explore joint effects of gene sets within specific biological pathways. Additionally, to incorporate other aspects of genomic data into pathway analysis may further enhance our understanding for the underlying mechanisms for BPD. Patterns of DNA methylation play important roles in regulating gene expression and function. A commonly observed phenomenon, allele-specific methylation (ASM) describes the associations between genetic variants and DNA methylation patterns. The present study aimed to identify biological pathways that are involve in the pathogenesis of BPD while incorporating brain specific ASM information in pathway analysis using two large-scale GWA datasets in Caucasian populations. A weighting scheme was adopted to take ASM information into consideration for each pathway. After multiple testing corrections, we identified 88 and 15 enriched pathways for their biological relevance for BPD in the Genetic Association Information Network (GAIN) and the Wellcome Trust Case Control Consortium dataset, respectively. Many of these pathways were significant only when applying the weighting scheme. Three ion channel related pathways were consistently identified in both datasets. Results in the GAIN dataset also suggest for the roles of extracellular matrix in brain for BPD. Findings from Gene Ontology (GO) analysis exhibited functional enrichment among genes of non-GO pathways in activity of gated channel, transporter, and neurotransmitter receptor. We demonstrated that integrating different data sources with pathway analysis provides an avenue to identify promising and novel biological pathways for exploring the underlying molecular mechanisms for bipolar disorder. Further basic research can be conducted to target the biological mechanisms for the identified genes and pathways.

The emerging spectrum of allelic variation in schizophrenia: current evidence and strategies for the identification and functional characterization of common and rare variants

After decades of halting progress, recent large genome-wide association studies (GWAS) are finally shining light on the genetic architecture of schizophrenia. The picture emerging is one of sobering complexity, involving large numbers of risk alleles across the entire allelic spectrum. The aims of this article are to summarize the key genetic findings to date and to compare and contrast methods for identifying additional risk alleles, including GWAS, targeted genotyping and sequencing. A further aim is to consider the challenges and opportunities involved in determining the functional basis of genetic associations, for instance using functional genomics, cellular models, animal models and imaging genetics. We conclude that diverse approaches will be required to identify and functionally characterize the full spectrum of risk variants for schizophrenia. These efforts should adhere to the stringent standards of statistical association developed for GWAS and are likely to entail very large sample sizes. Nonetheless, now more than any previous time, there are reasons for optimism and the ultimate goal of personalized interventions and therapeutics, although still distant, no longer seems unattainable.

TCF4 (e2-2; ITF2): a schizophrenia-associated gene with pleiotropic effects on human disease

Common SNPs in the transcription factor 4 (TCF4; ITF2, E2-2, SEF-2) gene, which encodes a basic Helix-Loop-Helix (bHLH) transcription factor, are associated with schizophrenia, conferring a small increase in risk. Other common SNPs in the gene are associated with the common eye disorder Fuch's corneal dystrophy, while rare, mostly de novo inactivating mutations cause Pitt-Hopkins syndrome. In this review, we present a systematic bioinformatics and literature review of the genomics, biological function and interactome of TCF4 in the context of schizophrenia. The TCF4 gene is present in all vertebrates, and although protein length varies, there is high conservation of primary sequence, including the DNA binding domain. Humans have a unique leucine-rich nuclear export signal. There are two main isoforms (A and B), as well as complex splicing generating many possible N-terminal amino acid sequences. TCF4 is highly expressed in the brain, where plays a role in neurodevelopment, interacting with class II bHLH transcription factors Math1, HASH1, and neuroD2. The Ca(2+) sensor protein calmodulin interacts with the DNA binding domain of TCF4, inhibiting transcriptional activation. It is also the target of microRNAs, including mir137, which is implicated in schizophrenia. The schizophrenia-associated SNPs are in linkage disequilibrium with common variants within putative DNA regulatory elements, suggesting that regulation of expression may underlie association with schizophrenia. Combined gene co-expression analyses and curated protein-protein interaction data provide a network involving TCF4 and other putative schizophrenia susceptibility genes. These findings suggest new opportunities for understanding the molecular basis of schizophrenia and other mental disorders.

RNA-Seq analysis implicates dysregulation of the immune system in schizophrenia

BACKGROUND

While genome-wide association studies identified some promising candidates for schizophrenia, the majority of risk genes remained unknown. We were interested in testing whether integration gene expression and other functional information could facilitate the identification of susceptibility genes and related biological pathways.

RESULTS

We conducted high throughput sequencing analyses to evaluate mRNA expression in blood samples isolated from 3 schizophrenia patients and 3 healthy controls. We also conducted pooled sequencing of 10 schizophrenic patients and matched controls. Differentially expressed genes were identified by t-test. In the individually sequenced dataset, we identified 198 genes differentially expressed between cases and controls, of them 19 had been verified by the pooled sequencing dataset and 21 reached nominal significance in gene-based association analyses of a genome wide association dataset. Pathway analysis of these differentially expressed genes revealed that they were highly enriched in the immune related pathways. Two genes, S100A8 and TYROBP, had consistent changes in expression in both individual and pooled sequencing datasets and were nominally significant in gene-based association analysis.

CONCLUSIONS

Integration of gene expression and pathway analyses with genome-wide association may be an efficient approach to identify risk genes for schizophrenia.

Pathway analysis of smoking quantity in multiple GWAS identifies cholinergic and sensory pathways

Cigarette smoking is a common addiction that increases the risk for many diseases, including lung cancer and chronic obstructive pulmonary disease. Genome-wide association studies (GWAS) have successfully identified and validated several susceptibility loci for nicotine consumption and dependence. However, the trait variance explained by these genes is only a small fraction of the estimated genetic risk. Pathway analysis complements single marker methods by including biological knowledge into the evaluation of GWAS, under the assumption that causal variants lie in functionally related genes, enabling the evaluation of a broad range of signals. Our approach to the identification of pathways enriched for multiple genes associated with smoking quantity includes the analysis of two studies and the replication of common findings in a third dataset. This study identified pathways for the cholinergic receptors, which included SNPs known to be genome-wide significant; as well as novel pathways, such as genes involved in the sensory perception of smell, that do not contain any single SNP that achieves that stringent threshold.

Multi-locus genome-wide association analysis supports the role of glutamatergic synaptic transmission in the etiology of major depressive disorder

Major depressive disorder (MDD) is a common psychiatric illness characterized by low mood and loss of interest in pleasurable activities. Despite years of effort, recent genome-wide association studies (GWAS) have identified few susceptibility variants or genes that are robustly associated with MDD. Standard single-SNP (single nucleotide polymorphism)-based GWAS analysis typically has limited power to deal with the extensive heterogeneity and substantial polygenic contribution of individually weak genetic effects underlying the pathogenesis of MDD. Here, we report an alternative, gene-set-based association analysis of MDD in an effort to identify groups of biologically related genetic variants that are involved in the same molecular function or cellular processes and exhibit a significant level of aggregated association with MDD. In particular, we used a text-mining-based data analysis to prioritize candidate gene sets implicated in MDD and conducted a multi-locus association analysis to look for enriched signals of nominally associated MDD susceptibility loci within each of the gene sets. Our primary analysis is based on the meta-analysis of three large MDD GWAS data sets (total N=4346 cases and 4430 controls). After correction for multiple testing, we found that genes involved in glutamatergic synaptic neurotransmission were significantly associated with MDD (set-based association P=6.9 × 10(-4)). This result is consistent with previous studies that support a role of the glutamatergic system in synaptic plasticity and MDD and support the potential utility of targeting glutamatergic neurotransmission in the treatment of MDD.

Candidate autism gene screen identifies critical role for cell-adhesion molecule CASPR2 in dendritic arborization and spine development

Mutations in the contactin-associated protein 2 (CNTNAP2) gene encoding CASPR2, a neurexin-related cell-adhesion molecule, predispose to autism, but the function of CASPR2 in neural circuit assembly remains largely unknown. In a knockdown survey of autism candidate genes, we found that CASPR2 is required for normal development of neural networks. RNAi-mediated knockdown of CASPR2 produced a cell-autonomous decrease in dendritic arborization and spine development in pyramidal neurons, leading to a global decline in excitatory and inhibitory synapse numbers and a decrease in synaptic transmission without a detectable change in the properties of these synapses. Our data suggest that in addition to the previously described role of CASPR2 in mature neurons, where CASPR2 organizes nodal microdomains of myelinated axons, CASPR2 performs an earlier organizational function in developing neurons that is essential for neural circuit assembly and operates coincident with the time of autism spectrum disorder (ASD) pathogenesis.

Functional gene group analysis identifies synaptic gene groups as risk factor for schizophrenia

Schizophrenia is a highly heritable disorder with a polygenic pattern of inheritance and a population prevalence of ~1%. Previous studies have implicated synaptic dysfunction in schizophrenia. We tested the accumulated association of genetic variants in expert-curated synaptic gene groups with schizophrenia in 4673 cases and 4965 healthy controls, using functional gene group analysis. Identifying groups of genes with similar cellular function rather than genes in isolation may have clinical implications for finding additional drug targets. We found that a group of 1026 synaptic genes was significantly associated with the risk of schizophrenia (P=7.6 × 10(-11)) and more strongly associated than 100 randomly drawn, matched control groups of genetic variants (P<0.01). Subsequent analysis of synaptic subgroups suggested that the strongest association signals are derived from three synaptic gene groups: intracellular signal transduction (P=2.0 × 10(-4)), excitability (P=9.0 × 10(-4)) and cell adhesion and trans-synaptic signaling (P=2.4 × 10(-3)). These results are consistent with a role of synaptic dysfunction in schizophrenia and imply that impaired intracellular signal transduction in synapses, synaptic excitability and cell adhesion and trans-synaptic signaling play a role in the pathology of schizophrenia.

Psychopathology and the human connectome: toward a transdiagnostic model of risk for mental illness

The panoply of cognitive, affective, motivational, and social functions that underpin everyday human experience requires precisely choreographed patterns of interaction between networked brain regions. Perhaps not surprisingly, diverse forms of psychopathology are characterized by breakdowns in these interregional relationships. Here, we discuss how functional brain imaging has provided insights into the nature of brain dysconnectivity in mental illness. Synthesizing work to date, we propose that genetic and environmental risk factors impinge upon systems-level circuits for several core dimensions of cognition, producing transdiagnostic symptoms. We argue that risk-associated disruption of these circuits mediates susceptibility to broad domains of psychopathology rather than discrete disorders.

Implications of genetic findings for understanding schizophrenia

From the perspective of those of us working on the genetics of schizophrenia, recent progress in identifying specific genetic risk factors at highly robust levels of statistical significance has been striking. However, the prevailing response among other schizophrenia researchers and some funders, families, and sufferers is often one of disappointment. In particular, it is often claimed that these discoveries explain only a small proportion of the genetic risk and hence tell us little about the nature of schizophrenia. The purpose of this article is to persuade you that recent genetic findings, while only revealing the tip of a complex genetic iceberg, already have profound implications for our general understanding of the classification and pathogenesis of schizophrenia and related disorders and that these have implications for schizophrenia research of all kinds.

Genome-wide association study in a Swedish population yields support for greater CNV and MHC involvement in schizophrenia compared with bipolar disorder

Schizophrenia (SCZ) and bipolar disorder (BD) are highly heritable psychiatric disorders with overlapping susceptibility loci and symptomatology. We conducted a genome-wide association study (GWAS) of these disorders in a large Swedish sample. We report a new and independent case-control analysis of 1507 SCZ cases, 836 BD cases and 2093 controls. No single-nucleotide polymorphisms (SNPs) achieved significance in these new samples; however, combining new and previously reported SCZ samples (2111 SCZ and 2535 controls) revealed a genome-wide significant association in the major histocompatibility complex (MHC) region (rs886424, P=4.54 × 10(-8)). Imputation using multiple reference panels and meta-analysis with the Psychiatric Genomics Consortium SCZ results underscored the broad, significant association in the MHC region in the full SCZ sample. We evaluated the role of copy number variants (CNVs) in these subjects. As in prior reports, deletions were enriched in SCZ, but not BD cases compared with controls. Singleton deletions were more frequent in both case groups compared with controls (SCZ: P=0.003, BD: P=0.013), whereas the largest CNVs (>500 kb) were significantly enriched only in SCZ cases (P=0.0035). Two CNVs with previously reported SCZ associations were also overrepresented in this SCZ sample: 16p11.2 duplications (P=0.0035) and 22q11 deletions (P=0.03). These results reinforce prior reports of significant MHC and CNV associations in SCZ, but not BD.

Coupling diffusion imaging with histological and gene expression analysis to examine the dynamics of cortical areas across the fetal period of human brain development

As a prominent component of the human fetal brain, the structure of the cerebral wall is characterized by its laminar organization which includes the radial glial scaffold during fetal development. Diffusion tensor imaging (DTI) is useful to quantitatively delineate the microstructure of the developing brain and to clearly identify transient fetal layers in the cerebral wall. In our study, the spatio-temporal microstructural changes in the developing human fetal cerebral wall were quantitatively characterized with high-resolution DTI data of postmortem fetal brains from 13 to 21 gestational weeks. Eleven regions of interest for each layer in the entire cerebral wall were included. Distinctive time courses of microstructural changes were revealed for 11 regions of the neocortical plate. A histological analysis was also integrated to elucidate the relationship between DTI fractional anisotropy (FA) and histology. High FA values correlated with organized radial architecture in histological image. Expression levels of 17565 genes were quantified for each of 11 regions of human fetal neocortex from 13 to 21 gestational weeks to identify transcripts showing significant correlation with FA change. These correlations suggest that the heterogeneous and regionally specific microstructural changes of the human neocortex are related to different gene expression patterns.

Mutations of ANK3 identified by exome sequencing are associated with autism susceptibility

Autism spectrum disorders (ASDs) are common neurodevelopmental disorders with a strong genetic etiology. However, due to the extreme genetic heterogeneity of ASDs, traditional approaches for gene discovery are challenging. Next-generation sequencing technologies offer an opportunity to accelerate the identification of the genetic causes of ASDs. Here, we report the results of whole-exome sequence in a cohort of 20 ASD patients. By extensive bioinformatic analysis, we identified novel mutations in seven genes that are implicated in synaptic function and neurodevelopment. After sequencing an additional 47 ASD samples, we identified three different missense mutations in ANK3 in four unrelated ASD patients, one of which, c.4705T>G (p.S1569A), is a de novo mutation. Given the fact that ANK3 has been shown to strongly associate with schizophrenia and bipolar disorder, our findings support an association between ANK3 mutations and ASD susceptibility and imply a shared molecular pathophysiology between ASDs and other neuropsychiatric disorders.

The relationship between Toxoplasma gondii infection and mood disorders in the third National Health and Nutrition Survey

BACKGROUND

Toxoplasma gondii (T. gondii) is a neurotropic protozoan parasite that causes persistent infection in humans. A substantial literature suggests that schizophrenia is associated with increased seroprevalence of T. gondii, but a possible link of the parasite with mood disorders has not been as thoroughly investigated.

METHODS

We examined the association of Toxoplasma-specific immunoglobulin G results with mood disorder outcomes in 7440 respondents from the third National Health and Nutrition Survey, which is a nationally representative sample of the United States noninstitutionalized civilian population. Regression models were adjusted for numerous potential confounders, including tobacco smoking and C-reactive protein levels.

RESULTS

No statistically significant associations were found between T. gondii seroprevalence and a history of major depression (n = 574; adjusted odds ratio [OR]: .8; 95% confidence interval [CI]: .5-1.2), severe major depression (n = 515; adjusted OR: .8; 95% CI: .6-1.2), dysthymia (n = 548; adjusted OR: 1.1; 95% CI: .7-1.8), or dysthymia with comorbid major depression (n = 242, adjusted OR: 1.2; 95% CI: .6-2.4), all p values were > .05, including analysis stratified by gender. However, there was a significant relationship between T. gondii seroprevalence and bipolar disorder type I for respondents in which both manic and major depression symptoms were reported (n = 41; adjusted OR: 2.4; 95% CI: 1.2-4.8; p < .05).

CONCLUSIONS

In a population-based sample, T. gondii seroprevalence is not elevated in unipolar mood disorders but is higher in a subset of respondents with a history of bipolar disorder type 1.

Common genetic variants and gene-expression changes associated with bipolar disorder are over-represented in brain signaling pathway genes

BACKGROUND

Despite high heritability, the genetic variants influencing bipolar disorder (BD) susceptibility remain largely unknown. Low statistical power to detect the small effect-size alleles believed to underlie much of the genetic risk and possible heterogeneity between cohorts are an increasing concern. Integrative biology approaches might offer advantages over genetic analysis alone by combining different genomic datasets at the higher level of biological processes rather than the level of specific genetic variants or genes. We employed this strategy to identify biological processes involved in BD etiopathology.

METHOD

Three genome-wide association studies and a brain gene-expression study were combined with the Human Protein Reference Database protein-protein interaction network data. We used bioinformatic analysis to search for biological networks with evidence of association on the basis of enrichment among both genetic and differential-expression associations with BD.

RESULTS

We identified association with gene networks involved in transmission of nerve impulse, Wnt, and Notch signaling. Three features stand out among these genes: 1) they localized to the human postsynaptic density, which is crucial for neuronal function; 2) their mouse knockouts present altered behavioral phenotypes; and 3) some are known targets of the pharmacological treatments for BD.

CONCLUSIONS

Genetic and gene-expression associations of BD cluster in discrete regions of the protein-protein interaction network. We found replicated evidence for association for networks involving several interlinked signaling pathways. These genes are promising candidates to generate animal models and pharmacological interventions. Our results demonstrate the potential advantage of integrative biology analyses of BD datasets.

Identifying the genetic variation of gene expression using gene sets: application of novel gene Set eQTL approach to PharmGKB and KEGG

Genetic variation underlying the regulation of mRNA gene expression in humans may provide key insights into the molecular mechanisms of human traits and complex diseases. Current statistical methods to map genetic variation associated with mRNA gene expression have typically applied standard linkage and/or association methods; however, when genome-wide SNP and mRNA expression data are available performing all pair wise comparisons is computationally burdensome and may not provide optimal power to detect associations. Consideration of different approaches to account for the high dimensionality and multiple testing issues may provide increased efficiency and statistical power. Here we present a novel approach to model and test the association between genetic variation and mRNA gene expression levels in the context of gene sets (GSs) and pathways, referred to as gene set - expression quantitative trait loci analysis (GS-eQTL). The method uses GSs to initially group SNPs and mRNA expression, followed by the application of principal components analysis (PCA) to collapse the variation and reduce the dimensionality within the GSs. We applied GS-eQTL to assess the association between SNP and mRNA expression level data collected from a cell-based model system using PharmGKB and KEGG defined GSs. We observed a large number of significant GS-eQTL associations, in which the most significant associations arose between genetic variation and mRNA expression from the same GS. However, a number of associations involving genetic variation and mRNA expression from different GSs were also identified. Our proposed GS-eQTL method effectively addresses the multiple testing limitations in eQTL studies and provides biological context for SNP-expression associations.

Genetic variability in the NMDA-dependent AMPA trafficking cascade is associated with alcohol dependence

Model studies in mice indicate that the severity of alcohol withdrawal is associated with polymorphic variation and expression of the MPDZ gene. Current knowledge about variation in the human MPDZ gene is limited; however, our data indicate its potential association with alcohol dependence. The multi-PDZ protein is an important part of the N-methyl-D-aspartate (NMDA)-dependent α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA) receptor trafficking cascade that controls glutamate-related excitatory neurotransmission. To investigate association of variation in the NMDA-dependent AMPA trafficking cascade with alcohol dependence, we performed a gene-set (pathway) analysis using single nucleotide polymorphism (SNP) data from the Study of Addiction: Genetic and Environment. Rather than testing for association with each SNP individually, which typically has low power to detect small effects of multiple SNPs, gene-set analysis applies a single statistical test to evaluate whether variation in a set of genes is associated with the phenotype of interest. Gene-set analysis of 988 SNPs in 13 genes in the pathway demonstrated a significant association with alcohol dependence, with P < 0.01 for the global effect of variation in this pathway. The statistically significant association of alcohol dependence with genetic variation in the NMDA-dependent AMPA receptor trafficking cascade indicates a need for further investigation of the role of this pathway in alcohol dependence.

Prevalence of autoimmune diseases in in-patients with schizophrenia: nationwide population-based study

BACKGROUND

The association between autoimmune diseases and schizophrenia has rarely been systematically investigated.

AIMS

To investigate the association between schizophrenia and a variety of autoimmune diseases and to explore possible gender variation in any such association.

METHOD

Taiwan's National Health Insurance Research Database was used to identify 10 811 hospital in-patients with schizophrenia and 108 110 age-matched controls. Univariate and multiple logistic regression analyses were performed, separately, to evaluate the association between autoimmune diseases and schizophrenia. We applied the false discovery rate to correct for multiple testing.

RESULTS

When compared with the control group, the in-patients with schizophrenia had an increased risk of Graves' disease (odds ratio (OR) = 1.32, 95% CI 1.04-1.67), psoriasis (OR = 1.48, 95% CI 1.07-2.04), pernicious anaemia (OR = 1.71, 95% CI 1.04-2.80), celiac disease (OR = 2.43, 95% CI 1.12-5.27) and hypersensitivity vasculitis (OR = 5.00, 95% CI 1.64-15.26), whereas a reverse association with rheumatoid arthritis (OR = 0.52, 95% CI 0.35-0.76) was also observed. Gender-specific variation was found for Sjögren syndrome, hereditary haemolytic anaemia, myasthenia gravis, polymyalgia rheumatica and dermatomyositis.

CONCLUSIONS

Schizophrenia was associated with a greater variety of autoimmune diseases than was anticipated. Further investigation is needed to gain a better understanding of the aetiology of schizophrenia and autoimmune diseases.

Dynamics of subcellular proteomes during brain development

Many neurological disorders are caused by perturbations during brain development, but these perturbations cannot be readily identified until there is comprehensive description of the development process. In this study, we performed mass spectrometry analysis of the synaptosomal and mitochondrial fractions from three rat brain regions at four postnatal time points. To quantitate our analysis, we employed (15)N labeled rat brains using a technique called SILAM (stable isotope labeling in mammals). We quantified 167429 peptides and identified over 5000 statistically significant changes during development including known disease-associated proteins. Global analysis revealed distinct trends between the synaptic and nonsynaptic mitochondrial proteomes and common protein networks between regions each consisting of a unique array of expression patterns. Finally, we identified novel regulators of neurodevelopment that possess the identical temporal pattern of known regulators of neurodevelopment. Overall, this study is the most comprehensive quantitative analysis of the developing brain proteome to date, providing an important resource for neurobiologists.

dbPTB: a database for preterm birth

Genome-wide association studies (GWAS) query the entire genome in a hypothesis-free, unbiased manner. Since they have the potential for identifying novel genetic variants, they have become a very popular approach to the investigation of complex diseases. Nonetheless, since the success of the GWAS approach varies widely, the identification of genetic variants for complex diseases remains a difficult problem. We developed a novel bioinformatics approach to identify the nominal genetic variants associated with complex diseases. To test the feasibility of our approach, we developed a web-based aggregation tool to organize the genes, genetic variations and pathways involved in preterm birth. We used semantic data mining to extract all published articles related to preterm birth. All articles were reviewed by a team of curators. Genes identified from public databases and archives of expression arrays were aggregated with genes curated from the literature. Pathway analysis was used to impute genes from pathways identified in the curations. The curated articles and collected genetic information form a unique resource for investigators interested in preterm birth. The Database for Preterm Birth exemplifies an approach that is generalizable to other disorders for which there is evidence of significant genetic contributions.

Database of genetic studies of bipolar disorder

This study describes the construction and preliminary analysis of a database of summary level genetic findings for bipolar disorder from the literature. The database is available for noncommercial use at http://bioprogramming.bsd.uchicago.edu/BDStudies/. This may be the first complete collection of published gene-specific linkage and association findings on bipolar disorder, including genome-wide association studies. Both the positive and negative findings have been incorporated so that the statistical and contextual significance of each finding may be compared semi-quantitatively and qualitatively across studies of mixed technologies. The database is appropriate for searching a literature populated by mainly underpowered studies, and if 'hits' are viewed as tentative knowledge for future hypothesis generation. It can serve as the basis for a mega-analysis of candidate genes. Herein, we discuss the most robust and best replicated gene findings to date in a contextual manner.

Genome-wide survey of large rare copy number variants in Alzheimer's disease among Caribbean hispanics

Recently genome-wide association studies have identified significant association between Alzheimer's disease (AD) and variations in CLU, PICALM, BIN1, CR1, MS4A4/MS4A6E, CD2AP, CD33, EPHA1, and ABCA7. However, the pathogenic variants in these loci have not yet been found. We conducted a genome-wide scan for large copy number variation (CNV) in a dataset of Caribbean Hispanic origin (554 controls and 559 AD cases that were previously investigated in a SNP-based genome-wide association study using Illumina HumanHap 650Y platform). We ran four CNV calling algorithms to obtain high-confidence calls for large CNVs (>100 kb) that were detected by at least two algorithms. Global burden analyses did not reveal significant differences between cases and controls in CNV rate, distribution of deletions or duplications, total or average CNV size; or number of genes affected by CNVs. However, we observed a nominal association between AD and a ∼470 kb duplication on chromosome 15q11.2 (P = 0.037). This duplication, encompassing up to five genes (TUBGCP5, CYFIP1, NIPA2, NIPA1, and WHAMML1) was present in 10 cases (2.6%) and 3 controls (0.8%). The dosage increase of CYFIP1 and NIPA1 genes was further confirmed by quantitative PCR. The current study did not detect CNVs that affect novel AD loci identified by recent genome-wide association studies. However, because the array technology used in our study has limitations in detecting small CNVs, future studies must carefully assess novel AD genes for the presence of disease-related CNVs.

Cell adhesion molecules contribute to Alzheimer's disease: multiple pathway analyses of two genome-wide association studies

Alzheimer's disease (AD) is a kind of complex neurological disorder. The complex genetic architecture of AD makes genetic analysis difficult. Fortunately, a pathway-based method to study the existing genome-wide association studies datasets has been applied into AD. However, no shared Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway was reported. In this study, we performed multiple pathway analyses of French AD genome-wide association studies dataset (discovery dataset, n = 7360, 2032 cases and 5328 controls) and Pfizer dataset (validation dataset, n = 2220, 1034 cases and 1186 controls). First, we performed multiple pathway analyses by Hypergeometric test, improved gene set enrichment analysis (IGSEA) and Z-statistic test in KEGG. Using Hypergeometric test, we identified 54 and 25 significant pathways (p < 0.05) in discovery dataset and validation dataset, respectively. Using IGSEA method, we identified three significant pathways in both discovery and validation datasets, respectively. Using Z-statistic test, we identified 19 significant pathways in validation dataset. Among the significant pathways, cell adhesion molecules (CAM) pathway was identified to be the only consistent signal emerging across multiple analyses in KEGG. After permutation and multiple testing corrections, CAM pathway was significant with p = 2.40E-05 (Hypergeometric test) and p = 3.00E-03 (IGSEA) in discovery dataset. In validation dataset, CAM pathway was significant with p = 1.84E-06 (Hypergeometric test), p = 1.00E-02 (IGSEA) and p = 2.81E-03 (Z-statistic test). We replicated the association by multiple pathway analyses in Gene Ontology using Hypergeometric test (WebGestalt), modified Fisher's exact test (DAVID) and Binomial test (PANTHER). Our findings provided further evidence on the association between CAM pathway and AD susceptibility, which would be helpful to study the genetic mechanisms of AD and may significantly assist in the development of therapeutic strategies.

Genome arrays for the detection of copy number variations in idiopathic mental retardation, idiopathic generalized epilepsy and neuropsychiatric disorders: lessons for diagnostic workflow and research

We review the contributions and limitations of genome-wide array-based identification of copy number variants (CNVs) in the clinical diagnostic evaluation of patients with mental retardation (MR) and other brain-related disorders. In unselected MR referrals a causative genomic gain or loss is detected in 14-18% of cases. Usually, such CNVs arise de novo, are not found in healthy subjects, and have a major impact on the phenotype by altering the dosage of multiple genes. This high diagnostic yield justifies array-based segmental aneuploidy screening as the initial genetic test in these patients. This also pertains to patients with autism (expected yield about 5-10% in nonsyndromic and 10-20% in syndromic patients) and schizophrenia (at least 5% yield). CNV studies in idiopathic generalized epilepsy, attention-deficit hyperactivity disorder, major depressive disorder and Tourette syndrome indicate that patients have, on average, a larger CNV burden as compared to controls. Collectively, the CNV studies suggest that a wide spectrum of disease-susceptibility variants exists, most of which are rare (<0.1%) and of variable and usually small effect. Notwithstanding, a rare CNV can have a major impact on the phenotype. Exome sequencing in MR and autism patients revealed de novo mutations in protein coding genes in 60 and 20% of cases, respectively. Therefore, it is likely that arrays will be supplanted by next-generation sequencing methods as the initial and perhaps ultimate diagnostic tool in patients with brain-related disorders, revealing both CNVs and mutations in a single test.

The shock of the new: progress in schizophrenia genomics

A growing list of common and rare genetic risk variants are being implicated in schizophrenia susceptibility. As with other complex genetic disorders most of the variance in genetic risk is still to be attributed. What can be learned from progress to date? The available data challenges how we conceptualize schizophrenia and suggests strong aetiological links with other psychiatric and developmental disorders. With the identification of rare copy number risk variants implicating specific genes (e.g. VIPR2 and NRXN1) it is increasingly possible to investigate molecular aetiology in patient subgroups to establish whether schizophrenia represents one or many different disease processes. This review summarizes recent research progress and suggests how the tools of modern genomics and neuroscience can be applied to best understand this devastating disorder.

RNA-Seq of human neurons derived from iPS cells reveals candidate long non-coding RNAs involved in neurogenesis and neuropsychiatric disorders

Genome-wide expression analysis using next generation sequencing (RNA-Seq) provides an opportunity for in-depth molecular profiling of fundamental biological processes, such as cellular differentiation and malignant transformation. Differentiating human neurons derived from induced pluripotent stem cells (iPSCs) provide an ideal system for RNA-Seq since defective neurogenesis caused by abnormalities in transcription factors, DNA methylation, and chromatin modifiers lie at the heart of some neuropsychiatric disorders. As a preliminary step towards applying next generation sequencing using neurons derived from patient-specific iPSCs, we have carried out an RNA-Seq analysis on control human neurons. Dramatic changes in the expression of coding genes, long non-coding RNAs (lncRNAs), pseudogenes, and splice isoforms were seen during the transition from pluripotent stem cells to early differentiating neurons. A number of genes that undergo radical changes in expression during this transition include candidates for schizophrenia (SZ), bipolar disorder (BD) and autism spectrum disorders (ASD) that function as transcription factors and chromatin modifiers, such as POU3F2 and ZNF804A, and genes coding for cell adhesion proteins implicated in these conditions including NRXN1 and NLGN1. In addition, a number of novel lncRNAs were found to undergo dramatic changes in expression, one of which is HOTAIRM1, a regulator of several HOXA genes during myelopoiesis. The increase we observed in differentiating neurons suggests a role in neurogenesis as well. Finally, several lncRNAs that map near SNPs associated with SZ in genome wide association studies also increase during neuronal differentiation, suggesting that these novel transcripts may be abnormally regulated in a subgroup of patients.

Combinations of SNPs related to signal transduction in bipolar disorder

Any given single nucleotide polymorphism (SNP) in a genome may have little or no functional impact. A biologically significant effect may possibly emerge only when a number of key SNP-related genotypes occur together in a single organism. Thus, in analysis of many SNPs in association studies of complex diseases, it may be useful to look at combinations of genotypes. Genes related to signal transmission, e.g., ion channel genes, may be of interest in this respect in the context of bipolar disorder. In the present study, we analysed 803 SNPs in 55 genes related to aspects of signal transmission and calculated all combinations of three genotypes from the 3×803 SNP genotypes for 1355 controls and 607 patients with bipolar disorder. Four clusters of patient-specific combinations were identified. Permutation tests indicated that some of these combinations might be related to bipolar disorder. The WTCCC bipolar dataset were use for replication, 469 of the 803 SNP were present in the WTCCC dataset either directly (n = 132) or by imputation (n = 337) covering 51 of our selected genes. We found three clusters of patient-specific 3×SNP combinations in the WTCCC dataset. Different SNPs were involved in the clusters in the two datasets. The present analyses of the combinations of SNP genotypes support a role for both genetic heterogeneity and interactions in the genetic architecture of bipolar disorder.

Genome-wide association study of the child behavior checklist dysregulation profile

OBJECTIVE

A potentially useful tool for understanding the distribution and determinants of emotional dysregulation in children is a Child Behavior Checklist profile, comprising the Attention Problems, Anxious/Depressed, and Aggressive Behavior clinical subscales (CBCL-DP). The CBCL-DP indexes a heritable trait that increases susceptibility for later psychopathology, including severe mood problems and aggressive behavior. We have conducted a genome-wide association study of the CBCL-DP in children with attention-deficit/hyperactivity disorder (ADHD).

METHOD

Families were ascertained at Massachusetts General Hospital and University of California, Los Angeles. Genotyping was conducted with the Illumina Human1M or Human1M-Duo BeadChip platforms. Genome-wide association analyses were conducted with the MQFAM multivariate extension of PLINK.

RESULTS

CBCL data were available for 341 ADHD offspring from 339 ADHD affected trio families from the UCLA (N = 128) and the MGH (N = 213) sites. We found no genome-wide statistically significant associations but identified several plausible candidate genes among findings at p < 5E-05: TMEM132D, LRRC7, SEMA3A, ALK, and STIP1.

CONCLUSIONS

We found suggestive evidence for developmentally expressed genes operant in hippocampal dependent memory and learning with the CBCL-DP.

Development of patient-specific neurons in schizophrenia using induced pluripotent stem cells

Induced pluripotent stem cell (iPSC) technology has the potential to transform regenerative medicine. It also offers a powerful tool for establishing in vitro models of disease, in particular, for neuropsychiatric disorders where live human neurons are essentially impossible to procure. Using iPSCs derived from three schizophrenia (SZ) patients, one of whom has 22q11.2del (velocardiofacial syndrome; VCFS), the authors developed a culture system to study SZ on a molecular and cellular level. SZ iPSCs were differentiated into functional, primarily glutamatergic neurons that were able to fire action potentials after ∼8 weeks in culture. Early differentiating neurons expressed a number of transcription factors/chromatin remodeling proteins and synaptic proteins relevant to SZ pathogenesis, including ZNF804A, RELN, CNTNAP2, CTNNA2, SMARCA2, and NRXN1. Although a small number of lines were developed in this preliminary study, the SZ line containing 22q11.2del showed a significant delay in the reduction of endogenous OCT4 and NANOG expression that normally occurs during differentiation. Constitutive expression of OCT4 has been observed in Dgcr8-deficient mouse embryonic stem cells (mESCs); DGCR8 maps to the 22q11.2-deleted region. These findings demonstrate that the method of inducing neural differentiation employed is useful for disease modeling in SZ and that the transition of iPSCs with 22q11.2 deletions towards a differentiated state may be marked by subtle changes in expression of pluripotency-associated genes.