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

Comprehensive analysis of schizophrenia-associated loci highlights ion channel pathways and biologically plausible candidate causal genes

Over 100 associated genetic loci have been robustly associated with schizophrenia. Gene prioritization and pathway analysis have focused on a priori hypotheses and thus may have been unduly influenced by prior assumptions and missed important causal genes and pathways. Using a data-driven approach, we show that genes in associated loci: (1) are highly expressed in cortical brain areas; (2) are enriched for ion channel pathways (false discovery rates <0.05); and (3) contain 62 genes that are functionally related to each other and hence represent promising candidates for experimental follow up. We validate the relevance of the prioritized genes by showing that they are enriched for rare disruptive variants and de novo variants from schizophrenia sequencing studies (odds ratio 1.67, P = 0.039), and are enriched for genes encoding members of mouse and human postsynaptic density proteomes (odds ratio 4.56, P = 5.00 × 10(-4); odds ratio 2.60, P = 0.049).The authors wish it to be known that, in their opinion, the first 2 authors should be regarded as joint First Author.

Genetics of long-term treatment outcome in bipolar disorder

Bipolar disorder (BD) shows one of the strongest genetic predispositions among psychiatric disorders and the identification of reliable genetic predictors of treatment response could significantly improve the prognosis of the disease. The present study investigated genetic predictors of long-term treatment-outcome in 723 patients with BD type I from the STEP-BD (Systematic Treatment Enhancement Program for Bipolar Disorder) genome-wide dataset. BD I patients with >6months of follow-up and without any treatment restriction (reflecting a natural setting scenario) were included. Phenotypes were the total and depressive episode rates and the occurrence of one or more (hypo)manic/mixed episodes during follow-up. Quality control of genome-wide data was performed according to standard criteria and linear/logistic regression models were used as appropriate under an additive hypothesis. Top genes were further analyzed through a pathway analysis. Genes previously involved in the susceptibility to BD (DFNB31, SORCS2, NRXN1, CNTNAP2, GRIN2A, GRM4, GRIN2B), antidepressant action (DEPTOR, CHRNA7, NRXN1), and mood stabilizer or antipsychotic action (NTRK2, CHRNA7, NRXN1) may affect long-term treatment outcome of BD. Promising findings without previous strong evidence were TRAF3IP2-AS1, NFYC, RNLS, KCNJ2, RASGRF1, NTF3 genes. Pathway analysis supported particularly the involvement of molecules mediating the positive regulation of MAPK cascade and learning/memory processes. Further studies focused on the outlined genes may be helpful to provide validated markers of BD treatment outcome.

A significant risk locus on 19q13 for bipolar disorder identified using a combined genome-wide linkage and copy number variation analysis

Background

The genetic background to bipolar disorder (BPD) has been attributed to different genetic and genomic risk factors. In the present study we hypothesized that inherited copy number variations (CNVs) contribute to susceptibility of BPD. We screened 637 BP-pedigrees from the NIMH Genetic Initiative and gave priority to 46 pedigrees. In this subsample we performed parametric and non-parametric genome-wide linkage analyses using ~21,000 SNP-markers. We developed an algorithm to test for linkage restricted to regions with CNVs that are shared within and across families.

Results

For the combined CNV and linkage analysis, one region on 19q13 survived correction for multiple comparisons and replicates a previous BPD risk locus. The shared CNV map to the pregnancy-specific glycoprotein (PSG) gene, a gene-family not previously implicated in BPD etiology. Two SNPs in the shared CNV are likely transcription factor binding sites and are linked to expression of an F-box binding gene, a key regulator of neuronal pathways suggested to be involved in BPD etiology.

Conclusions

Our CNV-weighted linkage approach identifies a risk locus for BPD on 19q13 and forms a useful tool to future studies to unravel part of the genetic vulnerability to BPD.

Electronic supplementary material

The online version of this article (doi:10.1186/s13040-015-0076-y) contains supplementary material, which is available to authorized users.

Evidence for Association of Cell Adhesion Molecules Pathway and NLGN1 Polymorphisms with Schizophrenia in Chinese Han Population

Multiple risk variants of schizophrenia have been identified by Genome-wide association studies (GWAS). As a complement for GWAS, previous pathway-based analysis has indicated that cell adhesion molecules (CAMs) pathway might be involved in the pathogenesis of schizophrenia. However, less replication studies have been reported. Our objective was to investigate the association between CAMs pathway and schizophrenia in the Chinese Han population. We first performed a pathway analysis utilizing our previous GWAS data. The CAMs pathway (hsa04514) was significantly associated with schizophrenia using hybrid gene set-based test (P = 1.03×10⁻¹⁰) and hypergeometric test (P = 5.04×10⁻⁶). Moreover, 12 genes (HLA-A, HLA-C, HLA-DOB, HLA-DPB1, HLA-DQA2, HLA-DRB1, MPZ, CD276, NLGN1, NRCAM, CLDN1 and ICAM3) were modestly significantly associated with schizophrenia (P<0.01). Then, we selected one promising gene neuroligin 1 (NLGN1) to further investigate the association between eight significant SNPs and schizophrenia in an independent sample (1814 schizophrenia cases and 1487 healthy controls). Our study showed that seven SNPs of NLGN1 and two haplotype blocks were significantly associated with schizophrenia. This association was confirmed by the results of combined analysis. Among them, SNP rs9835385 had the most significant association with schizophrenia (P = 2.83×10⁻⁷). Furthermore, in silico analysis we demonstrated that NLGN1 is preferentially expressed in human brain and SNP rs1488547 was related to the expression level. We validated the association of CAMs pathway with schizophrenia in pathway-level and identified one susceptibility gene NLGN1. Further investigation of the roles of CAMs pathway in the pathogenesis of schizophrenia is warranted.

Neurodevelopmental origins of bipolar disorder: iPSC models

Bipolar disorder (BP) is a chronic neuropsychiatric condition characterized by pathological fluctuations in mood from mania to depression. Adoption, twin and family studies have consistently identified a significant hereditary component to BP, yet there is no clear genetic event or consistent neuropathology. BP has been suggested to have a developmental origin, although this hypothesis has been difficult to test since there are no viable neurons or glial cells to analyze, and research has relied largely on postmortem brain, behavioral and imaging studies, or has examined proxy tissues including saliva, olfactory epithelium and blood cells. Neurodevelopmental factors, particularly pathways related to nervous system development, cell migration, extracellular matrix, H3K4 methylation, and calcium signaling have been identified in large gene expression and GWAS studies as altered in BP. Recent advances in stem cell biology, particularly the ability to reprogram adult somatic tissues to a pluripotent state, now make it possible to interrogate these pathways in viable cell models. A number of induced pluripotent stem cell (iPSC) lines from BP patient and healthy control (C) individuals have been derived in several laboratories, and their ability to form cortical neurons examined. Early studies suggest differences in activity, calcium signaling, blocks to neuronal differentiation, and changes in neuronal, and possibly glial, lineage specification. Initial observations suggest that differentiation of BP patient-derived neurons to dorsal telencephalic derivatives may be impaired, possibly due to alterations in WNT, Hedgehog or Nodal pathway signaling. These investigations strongly support a developmental contribution to BP and identify novel pathways, mechanisms and opportunities for improved treatments.

Genetic Analysis of Association Between Calcium Signaling and Hippocampal Activation, Memory Performance in the Young and Old, and Risk for Sporadic Alzheimer Disease

IMPORTANCE

Human episodic memory performance is linked to the function of specific brain regions, including the hippocampus; declines as a result of increasing age; and is markedly disturbed in Alzheimer disease (AD), an age-associated neurodegenerative disorder that primarily affects the hippocampus. Exploring the molecular underpinnings of human episodic memory is key to the understanding of hippocampus-dependent cognitive physiology and pathophysiology.

OBJECTIVE

To determine whether biologically defined groups of genes are enriched in episodic memory performance across age, memory encoding-related brain activity, and AD.

DESIGN, SETTING, AND PARTICIPANTS

In this multicenter collaborative study, which began in August 2008 and is ongoing, gene set enrichment analysis was done by using primary and meta-analysis data from 57 968 participants. The Swiss cohorts consisted of 3043 healthy young adults assessed for episodic memory performance. In a subgroup (n = 1119) of one of these cohorts, functional magnetic resonance imaging was used to identify gene set-dependent differences in brain activity related to episodic memory. The German Study on Aging, Cognition, and Dementia in Primary Care Patients cohort consisted of 763 elderly participants without dementia who were assessed for episodic memory performance. The International Genomics of Alzheimer's Project case-control sample consisted of 54 162 participants (17 008 patients with sporadic AD and 37 154 control participants). Analyses were conducted between January 2014 and June 2015. Gene set enrichment analysis in all samples was done using genome-wide single-nucleotide polymorphism data.

MAIN OUTCOMES AND MEASURES

Episodic memory performance in the Swiss cohort and German Study on Aging, Cognition, and Dementia in Primary Care Patients cohort was quantified by picture and verbal delayed free recall tasks. In the functional magnetic resonance imaging experiment, activation of the hippocampus during encoding of pictures served as the phenotype of interest. In the International Genomics of Alzheimer's Project sample, diagnosis of sporadic AD served as the phenotype of interest.

RESULTS

In the discovery sample, we detected significant enrichment for genes constituting the calcium signaling pathway, especially those related to the elevation of cytosolic calcium (P = 2 × 10-4). This enrichment was replicated in 2 additional samples of healthy young individuals (P = .02 and .04, respectively) and a sample of healthy elderly participants (P = .004). Hippocampal activation (P = 4 × 10-4) and the risk for sporadic AD (P = .01) were also significantly enriched for genes related to the elevation of cytosolic calcium.

CONCLUSIONS AND RELEVANCE

By detecting consistent significant enrichment in independent cohorts of young and elderly participants, this study identified that calcium signaling plays a central role in hippocampus-dependent human memory processes in cognitive health and disease, contributing to the understanding and potential treatment of hippocampus-dependent cognitive pathology.

Converging models of schizophrenia--Network alterations of prefrontal cortex underlying cognitive impairments

The prefrontal cortex (PFC) and its connections with other brain areas are crucial for cognitive function. Cognitive impairments are one of the core symptoms associated with schizophrenia, and manifest even before the onset of the disorder. Altered neural networks involving PFC contribute to cognitive impairments in schizophrenia. Both genetic and environmental risk factors affect the development of the local circuitry within PFC as well as development of broader brain networks, and make the system vulnerable to further insults during adolescence, leading to the onset of the disorder in young adulthood. Since spared cognitive functions correlate with functional outcome and prognosis, a better understanding of the mechanisms underlying cognitive impairments will have important implications for novel therapeutics for schizophrenia focusing on cognitive functions. Multidisciplinary approaches, from basic neuroscience to clinical studies, are required to link molecules, circuitry, networks, and behavioral phenotypes. Close interactions among such fields by sharing a common language on connectomes, behavioral readouts, and other concepts are crucial for this goal.

Genetic disruption of voltage-gated calcium channels in psychiatric and neurological disorders

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Voltage-gated calcium channel classification—genes and proteins.

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Genetic analysis of neuropsychiatric syndromes.

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Calcium channel genes identified from GWA studies of psychiatric disorders.

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Rare mutations in calcium channel genes in psychiatric disorders.

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Pathophysiological sequelae of CACNA1C mutations and polymorphisms.

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Monogenic disorders resulting from harmful mutations in other voltage-gated calcium channel genes.

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Changes in calcium channel gene expression in disease.

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Involvement of voltage-gated calcium channels in early brain development.

This review summarises genetic studies in which calcium channel genes have been connected to the spectrum of neuropsychiatric syndromes, from bipolar disorder and schizophrenia to autism spectrum disorders and intellectual impairment. Among many other genes, striking numbers of the calcium channel gene superfamily have been implicated in the aetiology of these diseases by various DNA analysis techniques. We will discuss how these relate to the known monogenic disorders associated with point mutations in calcium channels. We will then examine the functional evidence for a causative link between these mutations or single nucleotide polymorphisms and the disease processes. A major challenge for the future will be to translate the expanding psychiatric genetic findings into altered physiological function, involvement in the wider pathology of the diseases, and what potential that provides for personalised and stratified treatment options for patients.

Computational dissection of human episodic memory reveals mental process-specific genetic profiles

Episodic memory performance is the result of distinct mental processes, such as learning, memory maintenance, and emotional modulation of memory strength. Such processes can be effectively dissociated using computational models. Here we performed gene set enrichment analyses of model parameters estimated from the episodic memory performance of 1,765 healthy young adults. We report robust and replicated associations of the amine compound SLC (solute-carrier) transporters gene set with the learning rate, of the collagen formation and transmembrane receptor protein tyrosine kinase activity gene sets with the modulation of memory strength by negative emotional arousal, and of the L1 cell adhesion molecule (L1CAM) interactions gene set with the repetition-based memory improvement. Furthermore, in a large functional MRI sample of 795 subjects we found that the association between L1CAM interactions and memory maintenance revealed large clusters of differences in brain activity in frontal cortical areas. Our findings provide converging evidence that distinct genetic profiles underlie specific mental processes of human episodic memory. They also provide empirical support to previous theoretical and neurobiological studies linking specific neuromodulators to the learning rate and linking neural cell adhesion molecules to memory maintenance. Furthermore, our study suggests additional memory-related genetic pathways, which may contribute to a better understanding of the neurobiology of human memory.

Two-dimensional Enrichment Analysis for Mining High-level Imaging Genetic Associations

Enrichment analysis has been widely applied in the genome-wide association studies (GWAS), where gene sets corresponding to biological pathways are examined for significant associations with a phenotype to help increase statistical power and improve biological interpretation. In this work, we expand the scope of enrichment analysis into brain imaging genetics, an emerging field that studies how genetic variation influences brain structure and function measured by neuroimaging quantitative traits (QT). Given the high dimensionality of both imaging and genetic data, we propose to study Imaging Genetic Enrichment Analysis (IGEA), a new enrichment analysis paradigm that jointly considers meaningful gene sets (GS) and brain circuits (BC) and examines whether any given GS-BC pair is enriched in a list of gene-QT findings. Using gene expression data from Allen Human Brain Atlas and imaging genetics data from Alzheimer's Disease Neuroimaging Initiative as test beds, we present an IGEA framework and conduct a proof-of-concept study. This empirical study identifies 12 significant high level two dimensional imaging genetics modules. Many of these modules are relevant to a variety of neurobiological pathways or neurodegenerative diseases, showing the promise of the proposal framework for providing insight into the mechanism of complex diseases.

Network-Based Analysis of Schizophrenia Genome-Wide Association Data to Detect the Joint Functional Association Signals

Schizophrenia is a common psychiatric disorder with high heritability and complex genetic architecture. Genome-wide association studies (GWAS) have identified several significant loci associated with schizophrenia. However, the explained heritability is still low. Growing evidence has shown schizophrenia is attributable to multiple genes with moderate effects. In-depth mining and integration of GWAS data is urgently expected to uncover disease-related gene combination patterns. Network-based analysis is a promising strategy to better interpret GWAS to identify disease-related network modules. We performed a network-based analysis on three independent schizophrenia GWASs by using a refined analysis framework, which included a more accurate gene P-value calculation, dynamic network module searching algorithm and detailed functional analysis for the obtained modules genes. The result generated 79 modules including 238 genes, which form a highly connected subnetwork with more statistical significance than expected by chance. The result validated several reported disease genes, such as MAD1L1, MCC, SDCCAG8, VAT1L, MAPK14, MYH9 and FXYD6, and also obtained several novel candidate genes and gene-gene interactions. Pathway enrichment analysis of the module genes suggested they were enriched in several neural and immune system related pathways/GO terms, such as neurotrophin signaling pathway, synaptosome, regulation of protein ubiquitination, and antigen processing and presentation. Further crosstalk analysis revealed these pathways/GO terms were cooperated with each other, and identified several important genes, which might play vital roles to connect these functions. Our network-based analysis of schizophrenia GWASs will facilitate the understanding of genetic mechanisms of schizophrenia.

Multivariate genetic determinants of EEG oscillations in schizophrenia and psychotic bipolar disorder from the BSNIP study

Schizophrenia (SZ) and psychotic bipolar disorder (PBP) are disabling psychiatric illnesses with complex and unclear etiologies. Electroencephalogram (EEG) oscillatory abnormalities in SZ and PBP probands are heritable and expressed in their relatives, but the neurobiology and genetic factors mediating these abnormalities in the psychosis dimension of either disorder are less explored. We examined the polygenic architecture of eyes-open resting state EEG frequency activity (intrinsic frequency) from 64 channels in 105 SZ, 145 PBP probands and 56 healthy controls (HCs) from the multisite BSNIP (Bipolar-Schizophrenia Network on Intermediate Phenotypes) study. One million single-nucleotide polymorphisms (SNPs) were derived from DNA. We assessed eight data-driven EEG frequency activity derived from group-independent component analysis (ICA) in conjunction with a reduced subset of 10,422 SNPs through novel multivariate association using parallel ICA (para-ICA). Genes contributing to the association were examined collectively using pathway analysis tools. Para-ICA extracted five frequency and nine SNP components, of which theta and delta activities were significantly correlated with two different gene components, comprising genes participating extensively in brain development, neurogenesis and synaptogenesis. Delta and theta abnormality was present in both SZ and PBP, while theta differed between the two disorders. Theta abnormalities were also mediated by gene clusters involved in glutamic acid pathways, cadherin and synaptic contact-based cell adhesion processes. Our data suggest plausible multifactorial genetic networks, including novel and several previously identified (DISC1) candidate risk genes, mediating low frequency delta and theta abnormalities in psychoses. The gene clusters were enriched for biological properties affecting neural circuitry and involved in brain function and/or development.

Integration of gene expression and GWAS results supports involvement of calcium signaling in Schizophrenia

The number of Genome Wide Association Studies (GWAS) of schizophrenia is rapidly growing. However, the small effect of individual genes limits the number of reliably implicated genes, which are too few and too diverse to perform reliable pathway analysis; hence the biological roles of the genes implicated in schizophrenia are unclear. To overcome these limitations we combine GWAS with genome-wide expression data from human post-mortem brain samples of schizophrenia patients and controls, taking these steps: 1) Identify 36 GWAS-based genes which are expressed in our dataset. 2) Find a cluster of 19 genes with highly correlated expression. We show that this correlation pattern is robust and statistically significant. 3) GO-enrichment analysis of these 19 genes reveals significant enrichment of ion channels and calcium-related processes. This finding (based on analyzing a small number of coherently expressed genes) is validated and enhanced in two ways: First, the emergence of calcium channels and calcium signaling is corroborated by identifying proteins that interact with those encoded by the cluster of 19. Second, extend the 19 cluster genes into 1028 genes, whose expression is highly correlated with the cluster's average profile. When GO-enrichment analysis is performed on this extended set, many schizophrenia related pathways appear, with calcium-related processes enriched with high statistical significance. Our results give further, expression-based validation to GWAS results, support a central role of calcium-signaling in the pathogenesis of schizophrenia, and point to additional pathways potentially related to the disease.

Genetic Sources of Subcomponents of Event-Related Potential in the Dimension of Psychosis Analyzed From the B-SNIP Study

OBJECTIVE

Biological risk factors underlying psychosis are poorly understood. Biological underpinnings of the dimension of psychosis can be derived using genetic associations with intermediate phenotypes such as subcomponents of auditory event-related potentials (ERPs). Various ERP subcomponent abnormalities in schizophrenia and psychotic bipolar disorder are heritable and are expressed in unaffected relatives, although studies investigating genetic contributions to ERP abnormalities are limited. The authors used a novel parallel independent component analysis (para-ICA) to determine which empirically derived gene clusters are associated with data-driven ERP subcomponents, assuming a complex etiology underlying psychosis.

METHOD

The authors examined the multivariate polygenic association of ERP subcomponents from 64-channel auditory oddball data in 144 individuals with schizophrenia, 210 psychotic bipolar disorder probands, and 95 healthy individuals from the multisite Bipolar-Schizophrenia Network on Intermediate Phenotypes study. Data were reduced by principal components analysis to two target and one standard ERP waveforms. Multivariate association of compressed ERP waveforms with a set of 20,329 single-nucleotide polymorphisms (SNPs) (reduced from a 1-million-SNP array) was examined using para-ICA. Genes associated with SNPs were further examined using pathway analysis tools.

RESULTS

Para-ICA identified four ERP components that were significantly correlated with three genetic components. Enrichment analysis revealed complement immune response pathway and multiple processes that significantly mediate ERP abnormalities in psychosis, including synaptic cell adhesion, axon guidance, and neurogenesis.

CONCLUSIONS

This study identified three genetic components comprising multiple genes mediating ERP subcomponent abnormalities in schizophrenia and psychotic bipolar disorder. The data suggest a possible polygenic structure comprising genes influencing key neurodevelopmental processes, neural circuitry, and brain function mediating biological pathways plausibly associated with psychosis.

Synaptic abnormalities and cytoplasmic glutamate receptor aggregates in contactin associated protein-like 2/Caspr2 knockout neurons

Central glutamatergic synapses and the molecular pathways that control them are emerging as common substrates in the pathogenesis of mental disorders. Genetic variation in the contactin associated protein-like 2 (CNTNAP2) gene, including copy number variations, exon deletions, truncations, single nucleotide variants, and polymorphisms have been associated with intellectual disability, epilepsy, schizophrenia, language disorders, and autism. CNTNAP2, encoded by Cntnap2, is required for dendritic spine development and its absence causes disease-related phenotypes in mice. However, the mechanisms whereby CNTNAP2 regulates glutamatergic synapses are not known, and cellular phenotypes have not been investigated in Cntnap2 knockout neurons. Here we show that CNTNAP2 is present in dendritic spines, as well as axons and soma. Structured illumination superresolution microscopy reveals closer proximity to excitatory, rather than inhibitory synaptic markers. CNTNAP2 does not promote the formation of synapses and cultured neurons from Cntnap2 knockout mice do not show early defects in axon and dendrite outgrowth, suggesting that CNTNAP2 is not required at this stage. However, mature neurons from knockout mice show reduced spine density and levels of GluA1 subunits of AMPA receptors in spines. Unexpectedly, knockout neurons show large cytoplasmic aggregates of GluA1. Here we characterize, for the first time to our knowledge, synaptic phenotypes in Cntnap2 knockout neurons and reveal a novel role for CNTNAP2 in GluA1 trafficking. Taken together, our findings provide insight into the biological roles of CNTNAP2 and into the pathogenesis of CNTNAP2-associated neuropsychiatric disorders.

The uniform-score gene set analysis for identifying common pathways associated with different diabetes traits

Background

Genetic heritability and expression study have shown that different diabetes traits have common genetic components and pathways. A computationally efficient pathway analysis of GWAS results will benefit post-GWAS study of SNP associations and identification of common genetic pathways from diabetes GWAS can help to improve understanding of the disease pathogenesis.

Results

We proposed a uniform-score gene-set analysis (USGSA) with implemented package to unify different gene measures by a uniform score for identifying pathways from GWAS data, and use a pre-generated permutation distribution table to quickly obtain multiple-testing adjusted p-value. Simulation studies of uniform score for four gene measures (minP, 2ndP, simP and fishP) have shown that USGSA has strictly controlled family-wise error rate. The power depends on types of gene measure. USGSA with a two-stage study strategy was applied to identify common pathways associated with diabetes traits based on public dbGaP GWAS results. The study identified 7 gene sets that contain binding motifs at promoter region of component genes for 5 transcription factors (TFs) of FOXO4, TCF3, NFAT, VSX1 and POU2F1, and 1 microRNA of mir-218. These gene sets include 25 common genes that are among top 5% of the gene associations over genome for all GWAS. Previous evidences showed that nearly all of these genes are mainly expressed in the brain.

Conclusions

USGSA is a computationally efficient approach for pathway analysis of GWAS data with promoted interpretability and comparability. The pathway analysis suggested that different diabetes traits share common pathways and component genes are potentially regulated by common TFs and microRNA. The result also indicated that the central nervous system has a critical role in diabetes pathogenesis. The findings will be important in formulating novel hypotheses for guiding follow-up studies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1515-3) contains supplementary material, which is available to authorized users.

Pathway analysis of genome-wide association datasets of personality traits

Although several genome-wide association (GWA) studies of human personality have been recently published, genetic variants that are highly associated with certain personality traits remain unknown, due to difficulty reproducing results. To further investigate these genetic variants, we assessed biological pathways using GWA datasets. Pathway analysis using GWA data was performed on 1089 Korean women whose personality traits were measured with the Revised NEO Personality Inventory for the 5-factor model of personality. A total of 1042 pathways containing 8297 genes were included in our study. Of these, 14 pathways were highly enriched with association signals that were validated in 1490 independent samples. These pathways include association of: Neuroticism with axon guidance [L1 cell adhesion molecule (L1CAM) interactions]; Extraversion with neuronal system and voltage-gated potassium channels; Agreeableness with L1CAM interaction, neurotransmitter receptor binding and downstream transmission in postsynaptic cells; and Conscientiousness with the interferon-gamma and platelet-derived growth factor receptor beta polypeptide pathways. Several genes that contribute to top-ranked pathways in this study were previously identified in GWA studies or by pathway analysis in schizophrenia or other neuropsychiatric disorders. Here we report the first pathway analysis of all five personality traits. Importantly, our analysis identified novel pathways that contribute to understanding the etiology of personality traits.

The molecular genetic architecture of attention deficit hyperactivity disorder

Attention deficit hyperactivity disorder (ADHD) is a common childhood behavioral condition which affects 2-10% of school age children worldwide. Although the underlying molecular mechanism for the disorder is poorly understood, familial, twin and adoption studies suggest a strong genetic component. Here we provide a state-of-the-art review of the molecular genetics of ADHD incorporating evidence from candidate gene and linkage designs, as well as genome-wide association (GWA) studies of common single-nucleotide polymorphisms (SNPs) and rare copy number variations (CNVs). Bioinformatic methods such as functional enrichment analysis and protein-protein network analysis are used to highlight biological processes of likely relevance to the aetiology of ADHD. Candidate gene associations of minor effect size have been replicated across a number of genes including SLC6A3, DRD5, DRD4, SLC6A4, LPHN3, SNAP-25, HTR1B, NOS1 and GIT1. Although case-control SNP-GWAS have had limited success in identifying common genetic variants for ADHD that surpass critical significance thresholds, quantitative trait designs suggest promising associations with Cadherin13 and glucose-fructose oxidoreductase domain 1 genes. Further, CNVs mapped to glutamate receptor genes (GRM1, GRM5, GRM7 and GRM8) have been implicated in the aetiology of the disorder and overlap with bioinformatic predictions based on ADHD GWAS SNP data regarding enriched pathways. Although increases in sample size across multi-center cohorts will likely yield important new results, we advocate that this must occur in parallel with a shift away from categorical case-control approaches that view ADHD as a unitary construct, towards dimensional approaches that incorporate endophenotypes and statistical classification methods.

Failed drug discovery in psychiatry: time for human genome-guided solutions

Our knowledge about the molecular and neural mechanisms of emotional and cognitive processes has increased exponentially in the past decades. Unfortunately, there has been no translation of this knowledge into the development of novel and improved pharmacological treatments for psychiatric disorders. We comment on some of the reasons for failed drug discovery in psychiatry, particularly on the use of ill-suited disease models and on the use of diagnostic constructs unrelated to the underlying biological mechanisms. Furthermore, we argue that the use of human genetic findings together with biologically informed phenotypes and advanced data-mining methodology will catalyze the identification of promising drug targets and, finally, will lead to improved therapeutic outcomes.

Genomic and network patterns of schizophrenia genetic variation in human evolutionary accelerated regions

The population persistence of schizophrenia despite associated reductions in fitness and fecundity suggests that the genetic basis of schizophrenia has a complex evolutionary history. A recent meta-analysis of schizophrenia genome-wide association studies offers novel opportunities for assessment of the evolutionary trajectories of schizophrenia-associated loci. In this study, we hypothesize that components of the genetic architecture of schizophrenia are attributable to human lineage-specific evolution. Our results suggest that schizophrenia-associated loci enrich in genes near previously identified human accelerated regions (HARs). Specifically, we find that genes near HARs conserved in nonhuman primates (pHARs) are enriched for schizophrenia-associated loci, and that pHAR-associated schizophrenia genes are under stronger selective pressure than other schizophrenia genes and other pHAR-associated genes. We further evaluate pHAR-associated schizophrenia genes in regulatory network contexts to investigate associated molecular functions and mechanisms. We find that pHAR-associated schizophrenia genes significantly enrich in a GABA-related coexpression module that was previously found to be differentially regulated in schizophrenia affected individuals versus healthy controls. In another two independent networks constructed from gene expression profiles from prefrontal cortex samples, we find that pHAR-associated schizophrenia genes are located in more central positions and their average path lengths to the other nodes are significantly shorter than those of other schizophrenia genes. Together, our results suggest that HARs are associated with potentially important functional roles in the genetic architecture of schizophrenia.

Psychiatric genome-wide association study analyses implicate neuronal, immune and histone pathways

Genome-wide association studies (GWAS) of psychiatric disorders have identified multiple genetic associations with such disorders, but better methods are needed to derive the underlying biological mechanisms that these signals indicate. We sought to identify biological pathways in GWAS data from over 60,000 participants from the Psychiatric Genomics Consortium. We developed an analysis framework to rank pathways that requires only summary statistics. We combined this score across disorders to find common pathways across three adult psychiatric disorders: schizophrenia, major depression and bipolar disorder. Histone methylation processes showed the strongest association, and we also found statistically significant evidence for associations with multiple immune and neuronal signaling pathways and with the postsynaptic density. Our study indicates that risk variants for psychiatric disorders aggregate in particular biological pathways and that these pathways are frequently shared between disorders. Our results confirm known mechanisms and suggest several novel insights into the etiology of psychiatric disorders.

Genome-wide pathway-based association study implicates complement system in the development of Kashin-Beck disease in Han Chinese

Kashin-Beck disease (KBD) is a chronic osteochondropathy. The pathogenesis of KBD remains unknown. To identify relevant biological pathways for KBD, we conducted a genome-wide pathway-based association study (GWPAS) following by replication analysis, totally using 2743 Chinese Han adults. A modified gene set enrichment algorithm was used to detect association between KBD and 963 biological pathways. Cartilage gene expression analysis and serum complement measurement were performed to evaluate the functional relevance of identified pathway with KBD. We found that the Complement and Coagulation Cascades (CACC) pathway was significantly associated with KBD (P value=3.09×10(-5), false-discovery rate=0.042). Within the CACC pathway, the most significant association was observed at rs1656966 (P value=1.97×10(-4)) of KNG1 gene. Further replication study observed that rs1656966 (P value=0.037) was significantly associated with KBD in an independent validation sample of 1026 subjects. Gene expression analysis observed that CFD (ratio=3.39±2.68), A2M (ratio=3.67±5.63), C5 (ratio=2.65±2.52) and CD46 (ratio=2.29±137) genes of the CACC pathway were up-regulated in KBD articular cartilage compared to healthy articular cartilage. The serum level of complement C5 in KBD patients were significantly higher than that in healthy controls (P value=0.038). Our study is the first to suggest that complement system-related CACC pathway contributed to the development of KBD.

Synapse assembly and neurodevelopmental disorders

In this review we examine the current understanding of how genetic deficits associated with neurodevelopmental disorders may impact synapse assembly. We then go on to discuss how the critical periods for these genetic deficits will shape the nature of future clinical interventions.

Genetic underpinnings of white matter 'connectivity': heritability, risk, and heterogeneity in schizophrenia

Schizophrenia is a highly heritable disorder. Thus, the combination of genetics and brain imaging may be a useful strategy to investigate the effects of risk genes on anatomical connectivity, and for gene discovery, i.e. discovering the genetic correlates of white matter phenotypes. Following a database search, I review evidence for heritability of white matter phenotypes. I also review candidate gene investigations, examining association of putative risk variants with white matter phenotypes, as well as the recent flurry of research exploring relationships of genome-wide significant risk loci with white matter phenotypes. Finally, I review multivariate and polygene approaches, which constitute a new wave of imaging-genetics research, including large collaborative initiatives aiming to discover new genes that may predict aspects of white matter microstructure. The literature supports the heritability of white matter phenotypes. Loci in genes intimately implicated in oligodendrocyte and myelin development, growth and maintenance, and neurotrophic systems are associated with white matter microstructure. GWAS variants have not yet sufficiently been explored using DTI-based evaluation of white matter to draw conclusions, although micro-RNA 137 is promising due to its potential regulation of other GWAS schizophrenia genes. Many imaging-genetic studies only include healthy participants, which, while helping control for certain confounds, cannot address questions related to disease heterogeneity or symptom expression, and thus more studies should include participants with schizophrenia. With sufficiently large sample sizes, the future of this field lies in polygene strategies aimed at risk prediction and heterogeneity dissection of schizophrenia that can translate to personalized interventions.

Genetics of complex traits in psychiatry

Virtually all psychiatric traits are genetically complex. This article discusses the genetics of complex traits in psychiatry. The complexity is accounted for by numerous factors, including multiple risk alleles, epistasis, and epigenetic effects such as methylation. Risk alleles can individually be common or rare, and can include, for example, single nucleotide polymorphisms and copy number variants that are transmitted or are new mutations, and other kinds of variation. Many different kinds of variation can be important for trait risk, either together in various proportions or as different factors in different subjects. Until more recently, approaches to complex traits were limited, and consequently only a few variants, usually of individually minor effect, were identified. At the present time, a much richer armamentarium exists that includes the routine application of genome-wide association studies and next-generation high-throughput sequencing and the combination of this information with other biologically relevant information, such as expression data. We have also seen the emergence of large meta-analysis and mega-analysis consortia. These developments are extremely important for psychiatric genetics, have advanced the field substantially, and promise formidable gains in the years to come as they are applied more widely.

Synaptic plasticity, neural circuits, and the emerging role of altered short-term information processing in schizophrenia

Synaptic plasticity alters the strength of information flow between presynaptic and postsynaptic neurons and thus modifies the likelihood that action potentials in a presynaptic neuron will lead to an action potential in a postsynaptic neuron. As such, synaptic plasticity and pathological changes in synaptic plasticity impact the synaptic computation which controls the information flow through the neural microcircuits responsible for the complex information processing necessary to drive adaptive behaviors. As current theories of neuropsychiatric disease suggest that distinct dysfunctions in neural circuit performance may critically underlie the unique symptoms of these diseases, pathological alterations in synaptic plasticity mechanisms may be fundamental to the disease process. Here we consider mechanisms of both short-term and long-term plasticity of synaptic transmission and their possible roles in information processing by neural microcircuits in both health and disease. As paradigms of neuropsychiatric diseases with strongly implicated risk genes, we discuss the findings in schizophrenia and autism and consider the alterations in synaptic plasticity and network function observed in both human studies and genetic mouse models of these diseases. Together these studies have begun to point toward a likely dominant role of short-term synaptic plasticity alterations in schizophrenia while dysfunction in autism spectrum disorders (ASDs) may be due to a combination of both short-term and long-term synaptic plasticity alterations.

Pathway analysis of genome-wide association study and transcriptome data highlights new biological pathways in colorectal cancer

Colorectal cancer (CRC) is a common malignancy that meets the definition of a complex disease. Genome-wide association study (GWAS) has identified several loci of weak predictive value in CRC, however, these do not fully explain the occurrence risk. Recently, gene set analysis has allowed enhanced interpretation of GWAS data in CRC, identifying a number of metabolic pathways as important for disease pathogenesis. Whether there are other important pathways involved in CRC, however, remains unclear. We present a systems analysis of KEGG pathways in CRC using (1) a human CRC GWAS dataset and (2) a human whole transcriptome CRC case-control expression dataset. Analysis of the GWAS dataset revealed significantly enriched KEGG pathways related to metabolism, immune system and diseases, cellular processes, environmental information processing, genetic information processing, and neurodegenerative diseases. Altered gene expression was confirmed in these pathways using the transcriptome dataset. Taken together, these findings not only confirm previous work in this area, but also highlight new biological pathways whose deregulation is critical for CRC. These results contribute to our understanding of disease-causing mechanisms and will prove useful for future genetic and functional studies in CRC.

A functional SNP catalog of overlapping miRNA-binding sites in genes implicated in prion disease and other neurodegenerative disorders

The involvement of SNPs in miRNA target sites remains poorly investigated in neurodegenerative disease. In addition to associations with disease risk, such genetic variations can also provide novel insight into mechanistic pathways that may be responsible for disease etiology and/or pathobiology. To identify SNPs associated specifically with degenerating neurons, we restricted our analysis to genes that are dysregulated in CA1 hippocampal neurons of mice during early, preclinical phase of Prion disease. The 125 genes chosen are also implicated in other numerous degenerative and neurological diseases and disorders and are therefore likely to be of fundamental importance. We predicted those SNPs that could increase, decrease, or have neutral effects on miRNA binding. This group of genes was more likely to possess DNA variants than were genes chosen at random. Furthermore, many of the SNPs are common within the human population, and could contribute to the growing awareness that miRNAs and associated SNPs could account for detrimental neurological states. Interestingly, SNPs that overlapped miRNA-binding sites in the 3'-UTR of GABA-receptor subunit coding genes were particularly enriched. Moreover, we demonstrated that SNP rs9291296 would strengthen miR-26a-5p binding to a highly conserved site in the 3'-UTR of gamma-aminobutyric acid receptor subunit alpha-4.

Genome-wide association study of sleep duration in the Finnish population

Sleep duration is genetically regulated, but the genetic variants are largely unknown. We aimed to identify such genes using a genome-wide association study (GWAS) combined with RNA expression at the population level, and with experimental verification. A GWAS was performed in a Finnish sample (n = 1941), and variants with suggestive association (P < 5 × 10(-5) ) were tested in a follow-up sample from the same population with sleep duration (n = 6834) and time in bed (n = 1720). Variants with pointwise association of P < 0.05 in the follow-up sample were analysed further. First, we correlated genotypes with transcript expression levels with sleep duration (n = 207). The expression levels of significant transcripts were further studied in experimental sleep restriction. Of the 31 variants with P < 5 × 10(-5) in the discovery sample, three variants showed nominal allelic association (P < 0.05) in the follow-up sample: rs10914351, near PTPRU (P = 0.049), rs1037079 in PCDH7-CENTD1 (P = 0.011) and rs2031573 near KLF6 (P = 0.044). The risk alleles for shorter sleep (rs2031573 and rs1037079) were also associated with higher KLF6 and PCDH7 expression levels (P < 0.05). Experimental sleep restriction increased the expression of KLF6 (P < 0.01). These data suggest that rs2031573 near KLF6 or related loci and rs1037079 between PCDH7-CENTD1 or related loci may contribute to the regulation of sleep duration via gene expression. These results illustrate the utility of combining different analytical approaches to identify genetic determinants for traits related to sleep physiology. However, additional studies are needed in order to understand the roles of KLF6 and PCDH7 in sleep regulation.

Excess of rare novel loss-of-function variants in synaptic genes in schizophrenia and autism spectrum disorders

Schizophrenia (SZ) and autism spectrum disorders (ASDs) are complex neurodevelopmental disorders that may share an underlying pathology suggested by shared genetic risk variants. We sequenced the exonic regions of 215 genes in 147 ASD cases, 273 SZ cases and 287 controls, to identify rare risk mutations. Genes were primarily selected for their function in the synapse and were categorized as: (1) Neurexin and Neuroligin Interacting Proteins, (2) Post-synaptic Glutamate Receptor Complexes, (3) Neural Cell Adhesion Molecules, (4) DISC1 and Interactors and (5) Functional and Positional Candidates. Thirty-one novel loss-of-function (LoF) variants that are predicted to severely disrupt protein-coding sequence were detected among 2 861 rare variants. We found an excess of LoF variants in the combined cases compared with controls (P=0.02). This effect was stronger when analysis was limited to singleton LoF variants (P=0.0007) and the excess was present in both SZ (P=0.002) and ASD (P=0.001). As an individual gene category, Neurexin and Neuroligin Interacting Proteins carried an excess of LoF variants in cases compared with controls (P=0.05). A de novo nonsense variant in GRIN2B was identified in an ASD case adding to the growing evidence that this is an important risk gene for the disorder. These data support synapse formation and maintenance as key molecular mechanisms for SZ and ASD.

The node of Ranvier in CNS pathology

Healthy nodes of Ranvier are crucial for action potential propagation along myelinated axons, both in the central and in the peripheral nervous system. Surprisingly, the node of Ranvier has often been neglected when describing CNS disorders, with most pathologies classified simply as being due to neuronal defects in the grey matter or due to oligodendrocyte damage in the white matter. However, recent studies have highlighted changes that occur in pathological conditions at the node of Ranvier, and at the associated paranodal and juxtaparanodal regions where neurons and myelinating glial cells interact. Lengthening of the node of Ranvier, failure of the electrically resistive seal between the myelin and the axon at the paranode, and retraction of myelin to expose voltage-gated K⁺ channels in the juxtaparanode, may contribute to altering the function of myelinated axons in a wide range of diseases, including stroke, spinal cord injury and multiple sclerosis. Here, we review the principles by which the node of Ranvier operates and its molecular structure, and thus explain how defects at the node and paranode contribute to neurological disorders.

The one and the many: effects of the cell adhesion molecule pathway on neuropsychological function in psychosis

BACKGROUND

Genetic studies of single gene variants have been criticized as providing a simplistic characterization of the genetic basis of illness risk that ignores the effects of other variants within the same biological pathways. Of candidate biological pathways for schizophrenia (SZ), the cell adhesion molecule (CAM) pathway has repeatedly been linked to both psychosis and neurocognitive dysfunction. Here we tested, using risk allele scores derived from the Schizophrenia Psychiatric Genome-Wide Association Study Consortium (PGC-SCZ), whether alleles within the CAM pathway were correlated with poorer neuropsychological function in patients.

METHOD

In total, 424 patients with psychosis were assessed in areas of cognitive ability typically found to be impaired in SZ: intelligence quotient, memory, working memory and attentional control. CAM pathway genes were identified using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Alleles within these genes identified as significantly associated with SZ risk in the PGC-SCZ were then used to calculate a CAM pathway-based polygenic risk allele score for each patient and these scores were tested for association with cognitive ability.

RESULTS

Increased CAM pathway polygenic risk scores were significantly associated with poorer performance on measures of memory and attention, explaining 1-3% of variation on these measures. Notably, the most strongly associated single nucleotide polymorphism (SNP) in the CAM pathway (rs9272105 within HLA-DQA1) explained a similar amount of variance in attentional control, but not memory, as the polygenic risk analysis.

CONCLUSIONS

These data support a role for the CAM pathway in cognitive function, both at the level of individual SNPs and the wider pathway. In so doing these data highlight the value of pathway-based polygenic risk score studies as well as single gene studies for understanding SZ-associated deficits in cognition.

Specific glial functions contribute to schizophrenia susceptibility

Schizophrenia is a highly polygenic brain disorder. The main hypothesis for disease etiology in schizophrenia primarily focuses on the role of dysfunctional synaptic transmission. Previous studies have therefore directed their investigations toward the role of neuronal dysfunction. However, recent studies have shown that apart from neurons, glial cells also play a major role in synaptic transmission. Therefore, we investigated the potential causal involvement of the 3 principle glial cell lineages in risk to schizophrenia. We performed a functional gene set analysis to test for the combined effects of genetic variants in glial type-specific genes for association with schizophrenia. We used genome-wide association data from the largest schizophrenia sample to date, including 13 689 cases and 18 226 healthy controls. Our results show that astrocyte and oligodendrocyte gene sets, but not microglia gene sets, are associated with an increased risk for schizophrenia. The astrocyte and oligodendrocyte findings are related to astrocyte signaling at the synapse, myelin membrane integrity, glial development, and epigenetic control. Together, these results show that genetic alterations underlying specific glial cell type functions increase susceptibility to schizophrenia and provide evidence that the neuronal hypothesis of schizophrenia should be extended to include the role of glia.

Genetic variants in CDC42 and NXPH1 as susceptibility factors for constipation and diarrhoea predominant irritable bowel syndrome

OBJECTIVE

The complex genetic aetiology underlying irritable bowel syndrome (IBS) needs to be assessed in large-scale genetic studies. Two independent IBS cohorts were genotyped to assess whether genetic variability in immune, neuronal and barrier integrity genes is associated with IBS.

DESIGN

384 single nucleotide polymorphisms (SNPs) covering 270 genes were genotyped in an exploratory cohort (935 IBS patients, 639 controls). 33 SNPs with Puncorrected<0.05 were validated in an independent set of 497 patients and 887 controls. Genotype distributions of single SNPs were assessed using an additive genetic model in IBS and clinical subtypes, IBS-C and IBS-D, both in individual and combined cohorts. Trait anxiety (N=614 patients, 533 controls), lifetime depression (N=654 patients, 533 controls) and mRNA expression in rectal biopsies (N=22 patients, 29 controls) were correlated with SNP genotypes.

RESULTS

Two SNPs associated independently in the exploratory and validation cohort: rs17837965-CDC42 with IBS-C (ORexploratory=1.59 (1.05 to 1.76); ORvalidation=1.76 (1.03 to 3.01)) and rs2349775-NXPH1 with IBS-D (ORexploratory=1.28 (1.06 to 1.56); ORvalidation=1.42 (1.08 to 1.88)). When combining both cohorts, the association of rs2349775 withstood post hoc correction for multiple testing in the IBS-D subgroup. Additionally, three SNPs in immune-related genes (rs1464510-LPP, rs1881457-IL13, rs2104286-IL2RA), one SNP in a neuronal gene (rs2349775-NXPH1) and two SNPs in epithelial genes (rs245051-SLC26A2, rs17837965-CDC42) were weakly associated with total-IBS (Puncorrected<0.05). At the functional level, rs1881457 increased IL13 mRNA levels, whereas anxiety and depression scores did not correlate with rs2349775-NXPH1.

CONCLUSIONS

Rs2349775 (NXPH1) and rs17837965 (CDC42) were associated with IBS-D and IBS-C, respectively, in two independent cohorts. Further studies are warranted to validate our findings and to determine the mechanisms underlying IBS pathophysiology.

Pathway analysis of cervical cancer genome-wide association study highlights the MHC region and pathways involved in response to infection

Cervical cancer is caused by infection with human papillomavirus (HPV). A genome-wide association study (GWAS) has identified several susceptibility loci for cervical cancer, but they explain only a small fraction of cervical cancer heritability. Other variants with weaker effect may be missed due to the stringent significance threshold. To identify important pathways in cervical carcinogenesis, we performed a two-stage pathway analysis in two independent GWASs in the Swedish population, using the single-nucleotide polymorphism (SNP) ratio test. The 565 predefined pathways from Kyoto Encyclopedia of Genes and Genomes and BioCarta databases were systematically evaluated in the discovery stage (1034 cases and 3948 controls with 632,668 SNPs) and the suggestive pathways were further validated in the replication stage (616 cases and 506 controls with 341,358 SNPs). We found 12 pathways that were significant in both stages, and these were further validated using set-based analysis. For 10 of these pathways, the effect was mainly due to genetic variation within the major histocompatibility complex (MHC) region. In addition, we identified a set of novel candidate genes outside the MHC region in the pathways denoted 'Staphylococcus aureus infection' and 'herpes simplex infection' that influenced susceptibility to cervical cancer (empirical P = 4.99 × 10(-5) and 4.99 × 10(-5) in the discovery study; empirical P = 8.98 × 10(-5) and 0.009 in the replication study, respectively). Staphylococcus aureus infection may evoke an inflammatory response that inadvertently enhances malignant progression caused by HPV infection, and Herpes simplex virus-2 infection may act in conjunction with HPV infection to increase the risk of cervical carcinoma development. These findings provide new insights into the etiology of cervical cancer.

Identification of gene ontologies linked to prefrontal-hippocampal functional coupling in the human brain

Functional interactions between the dorsolateral prefrontal cortex and hippocampus during working memory have been studied extensively as an intermediate phenotype for schizophrenia. Coupling abnormalities have been found in patients, their unaffected siblings, and carriers of common genetic variants associated with schizophrenia, but the global genetic architecture of this imaging phenotype is unclear. To achieve genome-wide hypothesis-free identification of genes and pathways associated with prefrontal-hippocampal interactions, we combined gene set enrichment analysis with whole-genome genotyping and functional magnetic resonance imaging data from 269 healthy German volunteers. We found significant enrichment of the synapse organization and biogenesis gene set. This gene set included known schizophrenia risk genes, such as neural cell adhesion molecule (NRCAM) and calcium channel, voltage-dependent, beta 2 subunit (CACNB2), as well as genes with well-defined roles in neurodevelopmental and plasticity processes that are dysfunctional in schizophrenia and have mechanistic links to prefrontal-hippocampal functional interactions. Our results demonstrate a readily generalizable approach that can be used to identify the neurogenetic basis of systems-level phenotypes. Moreover, our findings identify gene sets in which genetic variation may contribute to disease risk through altered prefrontal-hippocampal functional interactions and suggest a link to both ongoing and developmental synaptic plasticity.

A hypothesis-driven pathway analysis reveals myelin-related pathways that contribute to the risk of schizophrenia and bipolar disorder

Schizophrenia (SZ) and bipolar disorder (BD) are both severe neuropsychiatric disorders with a strong and potential overlapping genetic background. Multiple lines of evidence, including genetic studies, gene expression studies and neuroimaging studies, have suggested that both disorders are closely related to myelin and oligodendrocyte dysfunctions. In the current study, we hypothesized that the holistic effect of the myelin-related pathway contributes to the genetic susceptibility to both SZ and BD. We extracted pathway data from the canonical pathway database, Gene Ontology (GO), and selected a 'compiled' pathway based on previous literature. We then performed hypothesis-driven pathway analysis on GWAS data from the Psychiatric Genomics Consortium (PGC). As a result, we identified three myelin-related pathways with a joint effect significantly associated with both disorders: 'Myelin sheath' pathway (P(SZ) = 2.45E-7, P(BD) = 1.22E-3), 'Myelination' pathway (P(SZ) = 2.10E-4, P(BD) = 2.53E-24), and 'Compiled' pathway (P(SZ) = 4.57E-8, P(BD) = 2.61E-9). In comparing the SNPs and genes in these three pathways across the two diseases, we identified a substantial overlap in nominally associated SNPs and genes, which could be susceptibility SNPs and genes for both disorders. From these observations, we propose that myelin-related pathways may be involved in the etiologies of both SZ and BD.

Integrated pathway-based approach identifies association between genomic regions at CTCF and CACNB2 and schizophrenia

In the present study, an integrated hierarchical approach was applied to: (1) identify pathways associated with susceptibility to schizophrenia; (2) detect genes that may be potentially affected in these pathways since they contain an associated polymorphism; and (3) annotate the functional consequences of such single-nucleotide polymorphisms (SNPs) in the affected genes or their regulatory regions. The Global Test was applied to detect schizophrenia-associated pathways using discovery and replication datasets comprising 5,040 and 5,082 individuals of European ancestry, respectively. Information concerning functional gene-sets was retrieved from the Kyoto Encyclopedia of Genes and Genomes, Gene Ontology, and the Molecular Signatures Database. Fourteen of the gene-sets or pathways identified in the discovery dataset were confirmed in the replication dataset. These include functional processes involved in transcriptional regulation and gene expression, synapse organization, cell adhesion, and apoptosis. For two genes, i.e. CTCF and CACNB2, evidence for association with schizophrenia was available (at the gene-level) in both the discovery study and published data from the Psychiatric Genomics Consortium schizophrenia study. Furthermore, these genes mapped to four of the 14 presently identified pathways. Several of the SNPs assigned to CTCF and CACNB2 have potential functional consequences, and a gene in close proximity to CACNB2, i.e. ARL5B, was identified as a potential gene of interest. Application of the present hierarchical approach thus allowed: (1) identification of novel biological gene-sets or pathways with potential involvement in the etiology of schizophrenia, as well as replication of these findings in an independent cohort; (2) detection of genes of interest for future follow-up studies; and (3) the highlighting of novel genes in previously reported candidate regions for schizophrenia.

Identification of pathways for bipolar disorder: a meta-analysis

IMPORTANCE

Genome-wide investigations provide systematic information regarding the neurobiology of psychiatric disorders.

OBJECTIVE

To identify biological pathways that contribute to risk for bipolar disorder (BP) using genes with consistent evidence for association in multiple genome-wide association studies (GWAS).

DATA SOURCES

Four independent data sets with individual genome-wide data available in July 2011 along with all data sets contributed to the Psychiatric Genomics Consortium Bipolar Group by May 2012. A prior meta-analysis was used as a source for brain gene expression data.

STUDY SELECTION

The 4 published GWAS were included in the initial sample. All independent BP data sets providing genome-wide data in the Psychiatric Genomics Consortium were included as a replication sample.

DATA EXTRACTION AND SYNTHESIS

We identified 966 genes that contained 2 or more variants associated with BP at P < .05 in 3 of 4 GWAS data sets (n = 12,127 [5253 cases, 6874 controls]). Simulations using 10,000 replicates of these data sets corrected for gene size and allowed the calculation of an empirical P value for each gene; empirically significant genes were entered into a pathway analysis. Each of these pathways was then tested in the replication sample (n = 8396 [3507 cases, 4889 controls]) using gene set enrichment analysis for single-nucleotide polymorphisms. The 226 genes were also compared with results from a meta-analysis of gene expression in the dorsolateral prefrontal cortex.

MAIN OUTCOMES AND MEASURES

Empirically significant genes and biological pathways. RESULTS Among 966 genes, 226 were empirically significant (P < .05). Seventeen pathways were overrepresented in analyses of the initial data set. Six of the 17 pathways were associated with BP in both the initial and replication samples: corticotropin-releasing hormone signaling, cardiac β-adrenergic signaling, phospholipase C signaling, glutamate receptor signaling, endothelin 1 signaling, and cardiac hypertrophy signaling. Among the 226 genes, 9 differed in expression in the dorsolateral prefrontal cortex in patients with BP: CACNA1C, DTNA, FOXP1, GNG2, ITPR2, LSAMP, NPAS3, NCOA2, and NTRK3.

CONCLUSIONS AND RELEVANCE

Pathways involved in the genetic predisposition to BP include hormonal regulation, calcium channels, second messenger systems, and glutamate signaling. Gene expression studies implicate neuronal development pathways as well. These results tend to reinforce specific hypotheses regarding BP neurobiology and may provide clues for new approaches to treatment and prevention.

Multivariate analysis reveals genetic associations of the resting default mode network in psychotic bipolar disorder and schizophrenia

The brain's default mode network (DMN) is highly heritable and is compromised in a variety of psychiatric disorders. However, genetic control over the DMN in schizophrenia (SZ) and psychotic bipolar disorder (PBP) is largely unknown. Study subjects (n = 1,305) underwent a resting-state functional MRI scan and were analyzed by a two-stage approach. The initial analysis used independent component analysis (ICA) in 324 healthy controls, 296 SZ probands, 300 PBP probands, 179 unaffected first-degree relatives of SZ probands (SZREL), and 206 unaffected first-degree relatives of PBP probands to identify DMNs and to test their biomarker and/or endophenotype status. A subset of controls and probands (n = 549) then was subjected to a parallel ICA (para-ICA) to identify imaging-genetic relationships. ICA identified three DMNs. Hypo-connectivity was observed in both patient groups in all DMNs. Similar patterns observed in SZREL were restricted to only one network. DMN connectivity also correlated with several symptom measures. Para-ICA identified five sub-DMNs that were significantly associated with five different genetic networks. Several top-ranking SNPs across these networks belonged to previously identified, well-known psychosis/mood disorder genes. Global enrichment analyses revealed processes including NMDA-related long-term potentiation, PKA, immune response signaling, axon guidance, and synaptogenesis that significantly influenced DMN modulation in psychoses. In summary, we observed both unique and shared impairments in functional connectivity across the SZ and PBP cohorts; these impairments were selectively familial only for SZREL. Genes regulating specific neurodevelopment/transmission processes primarily mediated DMN disconnectivity. The study thus identifies biological pathways related to a widely researched quantitative trait that might suggest novel, targeted drug treatments for these diseases.

Genomic view of bipolar disorder revealed by whole genome sequencing in a genetic isolate

Bipolar disorder is a common, heritable mental illness characterized by recurrent episodes of mania and depression. Despite considerable effort to elucidate the genetic underpinnings of bipolar disorder, causative genetic risk factors remain elusive. We conducted a comprehensive genomic analysis of bipolar disorder in a large Old Order Amish pedigree. Microsatellite genotypes and high-density SNP-array genotypes of 388 family members were combined with whole genome sequence data for 50 of these subjects, comprising 18 parent-child trios. This study design permitted evaluation of candidate variants within the context of haplotype structure by resolving the phase in sequenced parent-child trios and by imputation of variants into multiple unsequenced siblings. Non-parametric and parametric linkage analysis of the entire pedigree as well as on smaller clusters of families identified several nominally significant linkage peaks, each of which included dozens of predicted deleterious variants. Close inspection of exonic and regulatory variants in genes under the linkage peaks using family-based association tests revealed additional credible candidate genes for functional studies and further replication in population-based cohorts. However, despite the in-depth genomic characterization of this unique, large and multigenerational pedigree from a genetic isolate, there was no convergence of evidence implicating a particular set of risk loci or common pathways. The striking haplotype and locus heterogeneity we observed has profound implications for the design of studies of bipolar and other related disorders.

Bipolar disorder is a common, heritable mental illness characterized by recurrent episodes of mania and depression. Despite considerable efforts genetic studies have yet to reveal the precise genetic underpinnings of the disorder. In this study we have analyzed a large extended pedigree of Old Order Amish that segregates bipolar disorder. Our study design integrates both dense genotype and whole-genome sequence data. In a combined linkage and association analysis we identify five chromosomal regions with nominally significant or suggestive evidence for linkage, several of which constitute replication of earlier linkage findings for bipolar disorder in non-Amish families. Association analysis of genetic variants in each of the linkage regions yielded a number of plausible candidate genes for bipolar disorder. The striking genetic heterogeneity we observed in this genetic isolate has profound implications for the study of bipolar disorder in the general population.

Converging genetic and functional brain imaging evidence links neuronal excitability to working memory, psychiatric disease, and brain activity

Working memory, the capacity of actively maintaining task-relevant information during a cognitive task, is a heritable trait. Working memory deficits are characteristic for many psychiatric disorders. We performed genome-wide gene set enrichment analyses in multiple independent data sets of young and aged cognitively healthy subjects (n = 2,824) and in a large schizophrenia case-control sample (n = 32,143). The voltage-gated cation channel activity gene set, consisting of genes related to neuronal excitability, was robustly linked to performance in working memory-related tasks across ages and to schizophrenia. Functional brain imaging in 707 healthy participants linked this gene set also to working memory-related activity in the parietal cortex and the cerebellum. Gene set analyses may help to dissect the molecular underpinnings of cognitive dimensions, brain activity, and psychopathology.

Protein-interaction-network-based analysis for genome-wide association analysis of schizophrenia in Han Chinese population

Schizophrenia is a severe neuropsychiatric disorder with a strong and complex genetic background. Recent genome-wide association studies (GWAS) have successfully identified several susceptibility loci of schizophrenia. In order to interpret the functional role of the genetic variants and detect the combined effects of some of these genes on schizophrenia, protein-interaction-network-based analysis (PINBA) has emerged as an effective approach. In the current study, we conducted a PINBA of our previous GWAS data taken from the Han Chinese population. In order to do so, we used dense module search (DMS), a method that locates densely connected modules for complex diseases by integrating the association signal from GWAS datasets into the human protein-protein interaction (PPI) network. As a result, we identified one gene set with a joint effect significantly associated with schizophrenia and gene expression profiling analysis suggested that they were mainly neuro- and immune-related genes, such as glutamatergic gene (GRM5), GABAergic genes (GABRB1, GABARAP) and genes located in the MHC region (HLA-C, TAP2, HIST1H1B). Further pathway enrichment analysis suggested that these genes are involved in processes related to neuronal and immune systems, such as the Adherens junction pathway, the Neurotrophin signaling pathway and the Toll-like receptor signaling pathway. In our study, we identified a set of susceptibility genes that had been missed in single-marker GWAS, and our findings could promote the study of the genetic mechanisms in schizophrenia.

Pathway analyses implicate glial cells in schizophrenia

BACKGROUND

The quest to understand the neurobiology of schizophrenia and bipolar disorder is ongoing with multiple lines of evidence indicating abnormalities of glia, mitochondria, and glutamate in both disorders. Despite high heritability estimates of 81% for schizophrenia and 75% for bipolar disorder, compelling links between findings from neurobiological studies, and findings from large-scale genetic analyses, are only beginning to emerge.

METHOD

Ten publically available gene sets (pathways) related to glia, mitochondria, and glutamate were tested for association to schizophrenia and bipolar disorder using MAGENTA as the primary analysis method. To determine the robustness of associations, secondary analyses were performed with: ALIGATOR, INRICH, and Set Screen. Data from the Psychiatric Genomics Consortium (PGC) were used for all analyses. There were 1,068,286 SNP-level p-values for schizophrenia (9,394 cases/12,462 controls), and 2,088,878 SNP-level p-values for bipolar disorder (7,481 cases/9,250 controls).

RESULTS

The Glia-Oligodendrocyte pathway was associated with schizophrenia, after correction for multiple tests, according to primary analysis (MAGENTA p = 0.0005, 75% requirement for individual gene significance) and also achieved nominal levels of significance with INRICH (p = 0.0057) and ALIGATOR (p = 0.022). For bipolar disorder, Set Screen yielded nominally and method-wide significant associations to all three glial pathways, with strongest association to the Glia-Astrocyte pathway (p = 0.002).

CONCLUSIONS

Consistent with findings of white matter abnormalities in schizophrenia by other methods of study, the Glia-Oligodendrocyte pathway was associated with schizophrenia in our genomic study. These findings suggest that the abnormalities of myelination observed in schizophrenia are at least in part due to inherited factors, contrasted with the alternative of purely environmental causes (e.g. medication effects or lifestyle). While not the primary purpose of our study, our results also highlight the consequential nature of alternative choices regarding pathway analysis, in that results varied somewhat across methods, despite application to identical datasets and pathways.

Widespread differences in cortex DNA methylation of the "language gene" CNTNAP2 between humans and chimpanzees

CNTNAP2, one of the largest genes in the human genome, has been linked to human-specific language abilities and neurodevelopmental disorders. Our hypothesis is that epigenetic rather than genetic changes have accelerated the evolution of the human brain. To compare the cortex DNA methylation patterns of human and chimpanzee CNTNAP2 at ultra-high resolution, we combined methylated DNA immunoprecipitation (MeDIP) with NimbleGen tiling arrays for the orthologous gene and flanking sequences. Approximately 1.59 Mb of the 2.51 Mb target region could be aligned and analyzed with a customized algorithm in both species. More than one fifth (0.34 Mb) of the analyzed sequence throughout the entire gene displayed significant methylation differences between six human and five chimpanzee cortices. One of the most striking interspecies differences with 28% methylation in human and 59% in chimpanzee cortex (by bisulfite pyrosequencing) lies in a region 300 bp upstream of human SNP rs7794745 which has been associated with autism and parent-of-origin effects. Quantitative real-time RT PCR revealed that the protein-coding splice variant CNTNAP2-201 is 1.6-fold upregulated in human cortex, compared with the chimpanzee. Transcripts CNTNAP2-001, -002, and -003 did not show skewed allelic expression, which argues against CNTNAP2 imprinting, at least in adult human brain. Collectively, our results suggest widespread cortex DNA methylation changes in CNTNAP2 since the human-chimpanzee split, supporting a role for CNTNAP2 fine-regulation in human-specific language and communication traits.

BDgene: a genetic database for bipolar disorder and its overlap with schizophrenia and major depressive disorder

BACKGROUND

Bipolar disorder (BD) is a common psychiatric disorder with complex genetic architecture. It shares overlapping genetic influences with schizophrenia (SZ) and major depressive disorder (MDD). Large numbers of genetic studies of BD and cross-disorder studies between BD and SZ/MDD have accumulated numerous genetic data. There is a growing need to integrate the data to provide a comprehensive data set to facilitate the genetic study of BD and its highly relevant diseases.

METHODS

BDgene database was developed to integrate BD-related genetic factors and shared ones with SZ/MDD from profound literature reading. On the basis of data from the literature, in-depth analyses were performed for further understanding of the data, including gene prioritization, pathway-based analysis, intersection analysis of multidisease candidate genes, and pathway enrichment analysis.

RESULTS

BDgene includes multiple types of literature-reported genetic factors of BD with both positive and negative results, including 797 genes, 3119 single nucleotide polymorphisms, and 789 regions. Shared genetic factors such as single nucleotide polymorphisms, genes, and regions from published cross-disorder studies among BD and SZ/MDD were also presented. In-depth data analyses identified 43 BD core genes; 70 BD candidate pathways; and 127, 79, and 107 new potential cross-disorder genes for BD-SZ, BD-MDD, and BD-SZ-MDD, respectively.

CONCLUSIONS

As a central genetic database for BD and the first cross-disorder database for BD and SZ/MDD, BDgene provides not only a comprehensive review of current genetic research but also high-confidence candidate genes and pathways for understanding of BD mechanism and shared etiology among its relevant diseases. BDgene is freely available at http://bdgene.psych.ac.cn.

Human genome-guided identification of memory-modulating drugs

In the last decade there has been an exponential increase in knowledge about the genetic basis of complex human traits, including neuropsychiatric disorders. It is not clear, however, to what extent this knowledge can be used as a starting point for drug identification, one of the central hopes of the human genome project. The aim of the present study was to identify memory-modulating compounds through the use of human genetic information. We performed a multinational collaborative study, which included assessment of aversive memory--a trait central to posttraumatic stress disorder--and a gene-set analysis in healthy individuals. We identified 20 potential drug target genes in two genomewide-corrected gene sets: the neuroactive ligand-receptor interaction and the long-term depression gene set. In a subsequent double-blind, placebo-controlled study in healthy volunteers, we aimed at providing a proof of concept for the genome-guided identification of memory modulating compounds. Pharmacological intervention at the neuroactive ligand-receptor interaction gene set led to significant reduction of aversive memory. The findings demonstrate that genome information, along with appropriate data mining methodology, can be used as a starting point for the identification of memory-modulating compounds.