Ion channels and schizophrenia: a gene set-based analytic approach to GWAS data for biological hypothesis testing

Unraveling multi-scale neuroimaging biomarkers and molecular foundations for schizophrenia: A combined multivariate pattern analysis and transcriptome-neuroimaging association study

AIMS

Schizophrenia is characterized by alterations in resting-state spontaneous brain activity; however, it remains uncertain whether variations at diverse spatial scales are capable of effectively distinguishing patients from healthy controls. Additionally, the genetic underpinnings of these alterations remain poorly elucidated. We aimed to address these questions in this study to gain better understanding of brain alterations and their underlying genetic factors in schizophrenia.

METHODS

A cohort of 103 individuals with diagnosed schizophrenia and 110 healthy controls underwent resting-state functional MRI scans. Spontaneous brain activity was assessed using the regional homogeneity (ReHo) metric at four spatial scales: voxel-level (Scale 1) and regional-level (Scales 2-4: 272, 53, 17 regions, respectively). For each spatial scale, multivariate pattern analysis was performed to classify schizophrenia patients from healthy controls, and a transcriptome-neuroimaging association analysis was performed to establish connections between gene expression data and ReHo alterations in schizophrenia.

RESULTS

The ReHo metrics at all spatial scales effectively discriminated schizophrenia from healthy controls. Scale 2 showed the highest classification accuracy at 84.6%, followed by Scale 1 (83.1%) and Scale 3 (78.5%), while Scale 4 exhibited the lowest accuracy (74.2%). Furthermore, the transcriptome-neuroimaging association analysis showed that there were not only shared but also unique enriched biological processes across the four spatial scales. These related biological processes were mainly linked to immune responses, inflammation, synaptic signaling, ion channels, cellular development, myelination, and transporter activity.

CONCLUSIONS

This study highlights the potential of multi-scale ReHo as a valuable neuroimaging biomarker in the diagnosis of schizophrenia. By elucidating the complex molecular basis underlying the ReHo alterations of this disorder, this study not only enhances our understanding of its pathophysiology, but also pave the way for future advancements in genetic diagnosis and treatment of schizophrenia.

When rare meets common: Treatable genetic diseases are enriched in the general psychiatric population

Mental illnesses are one of the biggest contributors to the global disease burden. Despite the increased recognition, diagnosis and ongoing research of mental health disorders, the etiology and underlying molecular mechanisms of these disorders are yet to be fully elucidated. Moreover, despite many treatment options available, a large subset of the psychiatric patient population is nonresponsive to standard medications and therapies. There has not been a comprehensive study to date examining the burden and impact of treatable genetic disorders (TGDs) that can present with neuropsychiatric features in psychiatric patient populations. In this study, we test the hypothesis that TGDs that present with psychiatric symptoms are more prevalent within psychiatric patient populations compared to the general population by performing targeted next-generation sequencing of 129 genes associated with 108 TGDs in a cohort of 2301 psychiatric patients. In total, 48 putative affected and 180 putative carriers for TGDs were identified, with known or likely pathogenic variants in 79 genes. Despite screening for only 108 genetic disorders, this study showed a two-fold (2.09%) enrichment for genetic disorders within the psychiatric population relative to the estimated 1% cumulative prevalence of all single gene disorders globally. This strongly suggests that the prevalence of these, and most likely all, genetic diseases is greatly underestimated in psychiatric populations. Increasing awareness and ensuring accurate diagnosis of TGDs will open new avenues to targeted treatment for a subset of psychiatric patients.

SCN5A channelopathy: arrhythmia, cardiomyopathy, epilepsy and beyond

Influx of sodium ions through voltage-gated sodium channels in cardiomyocytes is essential for proper electrical conduction within the heart. Both acquired conditions associated with sodium channel dysfunction (myocardial ischaemia, heart failure) as well as inherited disorders secondary to mutations in the gene SCN5A encoding for the cardiac sodium channel Nav1.5 are associated with life-threatening arrhythmias. Research in the last decade has uncovered the complex nature of Nav1.5 distribution, function, in particular within distinct subcellular subdomains of cardiomyocytes. Nav1.5-based channels furthermore display previously unrecognized non-electrogenic actions and may impact on cardiac structural integrity, leading to cardiomyopathy. Moreover, SCN5A and Nav1.5 are expressed in cell types other than cardiomyocytes as well as various extracardiac tissues, where their functional role in, e.g. epilepsy, gastrointestinal motility, cancer and the innate immune response is increasingly investigated and recognized. This review provides an overview of these novel insights and how they deepen our mechanistic knowledge on SCN5A channelopathies and Nav1.5 (dys)function. This article is part of the theme issue 'The heartbeat: its molecular basis and physiological mechanisms'.

A human iPSC-astroglia neurodevelopmental model reveals divergent transcriptomic patterns in schizophrenia

While neurodevelopmental abnormalities have been associated with schizophrenia (SCZ), the role of astroglia in disease pathophysiology remains poorly understood. In the present study, we used a human induced pluripotent stem cell (iPSC)-derived astrocyte model to investigate the temporal patterns of astroglia differentiation during developmental stages critical for SCZ using RNA sequencing. The model generated astrocyte-specific gene expression patterns during differentiation that corresponded well to astroglia-specific expression signatures of in vivo cortical fetal development. Using this model we identified SCZ-specific expression dynamics, and found that SCZ-associated differentially expressed genes were significantly enriched in the medial prefrontal cortex, striatum, and temporal lobe, targeting VWA5A and ADAMTS19. In addition, SCZ astrocytes displayed alterations in calcium signaling, and significantly decreased glutamate uptake and metalloproteinase activity relative to controls. These results implicate novel transcriptional dynamics in astrocyte differentiation in SCZ together with functional changes that are potentially important biological components of SCZ pathology.

Two-Pore Domain Potassium Channel in Neurological Disorders

K2P channel is the leaky potassium channel that is critical to keep up the negative resting membrane potential for legitimate electrical conductivity of the excitable tissues. Recently, many substances and medication elements are discovered that could either straightforwardly or in a roundabout way influence the 15 distinctive K⁺ ion channels including TWIK, TREK, TASK, TALK, THIK, and TRESK. Opening and shutting of these channels or any adjustment in their conduct is thought to alter the pathophysiological condition of CNS. There is no document available till now to explain in detail about the molecular mechanism of agents acting on K2P channel. Accordingly, in this review we cover the current research and mechanism of action of these channels, we have also tried to mention the detailed effect of drugs and how the channel behavior changes by focusing on recent advances regarding activation and modulation of ion channels.

The Translational Machine: A novel machine-learning approach to illuminate complex genetic architectures

The Translational Machine (TM) is a machine learning (ML)-based analytic pipeline that translates genotypic/variant call data into biologically contextualized features that richly characterize complex variant architectures and permit greater interpretability and biological replication. It also reduces potentially confounding effects of population substructure on outcome prediction. The TM consists of three main components. First, replicable but flexible feature engineering procedures translate genome-scale data into biologically informative features that appropriately contextualize simple variant calls/genotypes within biological and functional contexts. Second, model-free, nonparametric ML-based feature filtering procedures empirically reduce dimensionality and noise of both original genotype calls and engineered features. Third, a powerful ML algorithm for feature selection is used to differentiate risk variant contributions across variant frequency and functional prediction spectra. The TM simultaneously evaluates potential contributions of variants operative under polygenic and heterogeneous models of genetic architecture. Our TM enables integration of biological information (e.g., genomic annotations) within conceptual frameworks akin to geneset-/pathways-based and collapsing methods, but overcomes some of these methods' limitations. The full TM pipeline is executed in R. Our approach and initial findings from its application to a whole-exome schizophrenia case-control data set are presented. These TM procedures extend the findings of the primary investigation and yield novel results.

Association of Candidate Single Nucleotide Polymorphisms Related to Candidate Genes in Patients With Schizophrenia

Introduction:

Schizophrenia is a chronic heterogenic neurodevelopment disorder. Many genes interfere in the development of SCZ. All four genes, NrCAM, PRODH, ANK3, and ANKK1, which were evaluated in this study, were previously reported to be associated with Schizophrenia. The NrCAM contributes to creating cognitive deficiencies through the CAM’s signaling pathway. PRODH plays a vital role in creating SCZ negative symptoms through the signaling pathway of glutamatergic and NMDA receptors. ANK3 affects ion channel and molecular adhesion in Ranvier and initial segments of axons, leading to mental retardation, sleep disorder, and SCZ. ANKK1 encodes a protein kinase and was reported to be associated with alcohol addiction, Attention Deficit Hyperactivity Disorder (ADHD), and SCZ.

Methods:

The subjects were selected from Schizophrenic patients referring to the Psychiatric Ward of Imam-Hussein Hospital and Schizophrenic Patients Support Institution (AHEBBA). 95 (30 Schizoaffective patients, 57 Paranoid patients, and 8 disorganized) patients were recruited as the subjects in the present case-control association study. 120 healthy subjects were recruited from the Tehran Medical Genetics Laboratory staff and a group of students from the Islamic Azad University of Science and Research in Tehran. The genotypes were determined with molecular genotyping techniques of PCR-RFLP, ARMS-PCR, and Cycle sequencing. Results were analyzed by the Chi-Square test using SPSS V. 24 and R, SNP STATE Package to investigate significant differences between cases and controls.

Results:

The incidence of schizophrenia was 68% and 32% among men and women, respectively. The evaluation of the allelic association between schizophrenia and all the candidate SNPs showed a significant association between NrCAM’s SNP rs10235968 and SCZ (P=0.001). Haplotype T, T, C in rs10235968, rs6967368, rs3763463, respectively, within the NrCAM gene, showed significant association with schizophrenia disorder (P=0.0001).

Conclusion:

No association was found between other candidate SNPs and SCZ among the subjects.

Glycogen synthase kinase-3: The missing link to aberrant circuit function in disorders of cognitive dysfunction?

Elevated GSK-3 activity has been implicated in cognitive dysfunction associated with various disorders including Alzheimer's disease, schizophrenia, type 2 diabetes, traumatic brain injury, major depressive disorder and bipolar disorder. Further, aberrant neural oscillatory activity in, and between, cortical regions and the hippocampus is consistently present within these same cognitive disorders. In this review, we will put forth the idea that increased GSK-3 activity serves as a pathological convergence point across cognitive disorders, inducing similar consequent impacts on downstream signaling mechanisms implicated in the maintenance of processes critical to brain systems communication and normal cognitive functioning. In this regard we suggest that increased activation of GSK-3 and neuronal oscillatory dysfunction are early pathological changes that may be functionally linked. Mechanistic commonalities between these disorders of cognitive dysfunction will be discussed and potential downstream targets of GSK-3 that may contribute to neuronal oscillatory dysfunction identified.

Large epigenome-wide association study of childhood ADHD identifies peripheral DNA methylation associated with disease and polygenic risk burden

Epigenetic variation in peripheral tissues is being widely studied as a molecular biomarker of complex disease and disease-related exposures. To date, few studies have examined differences in DNA methylation associated with attention-deficit hyperactivity disorder (ADHD). In this study, we profiled genetic and methylomic variation across the genome in saliva samples from children (age 7-12 years) with clinically established ADHD (N = 391) and nonpsychiatric controls (N = 213). We tested for differentially methylated positions (DMPs) associated with both ADHD diagnosis and ADHD polygenic risk score, by using linear regression models including smoking, medication effects, and other potential confounders in our statistical models. Our results support previously reported associations between ADHD and DNA methylation levels at sites annotated to VIPR2, and identify several novel disease-associated DMPs (p < 1e-5), although none of them were genome-wide significant. The two top-ranked, ADHD-associated DMPs (cg17478313 annotated to SLC7A8 and cg21609804 annotated to MARK2) are also significantly associated with nearby SNPs (p = 1.2e-46 and p = 2.07e-59), providing evidence that disease-associated DMPs are under genetic control. We also report a genome-wide significant association between ADHD polygenic risk and variable DNA methylation at a site annotated to the promoter of GART and SON (p = 6.71E-8). Finally, we show that ADHD-associated SNPs colocalize with SNPs associated with methylation levels in saliva. This is the first large-scale study of DNA methylation in children with ADHD. Our results represent novel epigenetic biomarkers for ADHD that may be useful for patient stratification, reinforce the importance of genetic effects on DNA methylation, and provide plausible molecular mechanisms for ADHD risk variants.

A Method for Analyzing Two-locus Epistasis of Complex Diseases based on Decision Tree and Mutual Entropy

Background:

Epistasis makes complex diseases difficult to understand, especially when heterogeneity also exists. Heterogeneity of complex diseases makes the distribution of case population more confused. However, the traditional methods proposed to detect epistasis often ignore heterogeneity, resulting in low power of association studies.

Methods:

In this study, we firstly use rank information in the Classification Decision Tree and Mutual Entropy (CTME) to construct two different evaluation scores, namely multiple objectives. In addition, we improve the calculation of joint entropy between SNPs and disease label, which elevates the efficiency of CTME. Then, the ant colony algorithm is applied to search two-locus epistatic combination space. To handle the potential heterogeneity, all candidate two-locus SNPs are merged to recognize multiple different epistatic combinations. Finally, all these solutions are tested by χ2 test.

Results and Conclusion:

Experiments show that our method CTME improves the power of association study. More importantly, CTME also detects multiple epistatic SNPs contributing to heterogeneity. The experimental results show that CTME has advantages on power and efficiency.

A molecule-based genetic association approach implicates a range of voltage-gated calcium channels associated with schizophrenia

Traditional genome-wide association studies (GWAS) have successfully detected genetic variants associated with schizophrenia. However, only a small fraction of heritability can be explained. Gene-set/pathway-based methods can overcome limitations arising from single nucleotide polymorphism (SNP)-based analysis, but most of them place constraints on size which may exclude highly specific and functional sets, like macromolecules. Voltage-gated calcium (Ca_v ) channels, belonging to macromolecules, are composed of several subunits whose encoding genes are located far away or even on different chromosomes. We combined information about such molecules with GWAS data to investigate how functional channels associated with schizophrenia. We defined a biologically meaningful SNP-set based on channel structure and performed an association study by using a validated method: SNP-set (sequence) kernel association test. We identified eight subtypes of Ca_v channels significantly associated with schizophrenia from a subsample of published data (N = 56,605), including the L-type channels (Ca_v 1.1, Ca_v 1.2, Ca_v 1.3), P-/Q-type Ca_v 2.1, N-type Ca_v 2.2, R-type Ca_v 2.3, T-type Ca_v 3.1, and Ca_v 3.3. Only genes from Ca_v 1.2 and Ca_v 3.3 have been implicated by the largest GWAS (N = 82,315). Each subtype of Ca_v channels showed relatively high chip heritability, proportional to the size of its constituent gene regions. The results suggest that abnormalities of Ca_v channels may play an important role in the pathophysiology of schizophrenia and these channels may represent appropriate drug targets for therapeutics. Analyzing subunit-encoding genes of a macromolecule in aggregate is a complementary way to identify more genetic variants of polygenic diseases. This study offers the potential of power for discovery the biological mechanisms of schizophrenia.

Identifying novel genes and biological processes relevant to the development of cancer therapy-induced mucositis: An informative gene network analysis

Mucositis is a complex, dose-limiting toxicity of chemotherapy or radiotherapy that leads to painful mouth ulcers, difficulty eating or swallowing, gastrointestinal distress, and reduced quality of life for patients with cancer. Mucositis is most common for those undergoing high-dose chemotherapy and hematopoietic stem cell transplantation and for those being treated for malignancies of the head and neck. Treatment and management of mucositis remain challenging. It is expected that multiple genes are involved in the formation, severity, and persistence of mucositis. We used Ingenuity Pathway Analysis (IPA), a novel network-based approach that integrates complex intracellular and intercellular interactions involved in diseases, to systematically explore the molecular complexity of mucositis. As a first step, we searched the literature to identify genes that harbor or are close to the genetic variants significantly associated with mucositis. Our literature review identified 27 candidate genes, of which ERCC1, XRCC1, and MTHFR were the most frequently studied for mucositis. On the basis of this 27-gene list, we used IPA to generate gene networks for mucositis. The most biologically significant novel molecules identified through IPA analyses included TP53, CTNNB1, MYC, RB1, P38 MAPK, and EP300. Additionally, uracil degradation II (reductive) and thymine degradation pathways (p = 1.06-08) were most significant. Finally, utilizing 66 SNPs within the 8 most connected IPA-derived candidate molecules, we conducted a genetic association study for oral mucositis in the head and neck cancer patients who were treated using chemotherapy and/or radiation therapy (186 head and neck cancer patients with oral mucositis vs. 699 head and neck cancer patients without oral mucositis). The top ranked gene identified through this association analysis was RB1 (rs2227311, p-value = 0.034, odds ratio = 0.67). In conclusion, gene network analysis identified novel molecules and biological processes, including pathways related to inflammation and oxidative stress, that are relevant to mucositis development, thus providing the basis for future studies to improve the management and treatment of mucositis in patients with cancer.

Network-assisted analysis of GWAS data identifies a functionally-relevant gene module for childhood-onset asthma

The number of genetic factors associated with asthma remains limited. To identify new genes with an undetected individual effect but collectively influencing asthma risk, we conducted a network-assisted analysis that integrates outcomes of genome-wide association studies (GWAS) and protein-protein interaction networks. We used two GWAS datasets, each consisting of the results of a meta-analysis of nine childhood-onset asthma GWASs (5,924 and 6,043 subjects, respectively). We developed a novel method to compute gene-level P-values (fastCGP), and proposed a parallel dense-module search and cross-selection strategy to identify an asthma-associated gene module. We identified a module of 91 genes with a significant joint effect on childhood-onset asthma (P < 10⁻⁵). This module contained a core subnetwork including genes at known asthma loci and five peripheral subnetworks including relevant candidates. Notably, the core genes were connected to APP (encoding amyloid beta precursor protein), a major player in Alzheimer’s disease that is known to have immune and inflammatory components. Functional analysis of the module genes revealed four gene clusters involved in innate and adaptive immunity, chemotaxis, cell-adhesion and transcription regulation, which are biologically meaningful processes that may underlie asthma risk. Our findings provide important clues for future research into asthma aetiology.

MAPK1/ERK2 as novel target genes for pain in head and neck cancer patients

Background

Genetic susceptibility plays an important role in the risk of developing pain in individuals with cancer. As a complex trait, multiple genes underlie this susceptibility. We used gene network analyses to identify novel target genes associated with pain in patients newly diagnosed with squamous cell carcinoma of the head and neck (HNSCC).

Results

We first identified 36 cancer pain-related genes (i.e., focus genes) from 36 publications based on a literature search. The Ingenuity Pathway Analysis (IPA) analysis identified additional genes that are functionally related to the 36 focus genes through pathway relationships yielding a total of 82 genes. Subsequently, 800 SNPs within the 82 IPA-selected genes on the Illumina HumanOmniExpress-12v1 platform were selected from a large-scale genotyping effort. Association analyses between the 800 candidate SNPs (covering 82 genes) and pain in a patient cohort of 1368 patients with HNSCC (206 patients with severe pain vs. 1162 with non-severe pain) showed the highest significance for MAPK1/ERK2, a gene belonging to the MAP kinase family (rs8136867, p value = 8.92 × 10⁻⁴; odds ratio [OR] = 1.33, 95 % confidence interval [CI]: 1.13–1.58). Other top genes were PIK3C2G (a member of PI3K [complex], rs10770367, p value = 1.10 × 10⁻³; OR = 1.46, 95 % CI: 1.16–1.82), TCRA (the alpha chain of T-cell receptor, rs6572493, p value = 2.84 × 10⁻³; OR = 0.70, 95 % CI: 0.55–0.88), PDGFC (platelet-derived growth factor C, rs6845322, p value = 4.88 × 10⁻³; OR = 1.32, 95 % CI: 1.09–1.60), and CD247 (a member of CD3, rs2995082, p value = 7.79 × 10⁻³; OR = 0.76, 95 % CI: 0.62–0.93).

Conclusions

Our findings provide novel candidate genes and biological pathways underlying pain in cancer patients. Further study of the variations of these candidate genes could inform clinical decision making when treating cancer pain.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-016-0348-7) contains supplementary material, which is available to authorized users.

SK3 Channel Overexpression in Mice Causes Hippocampal Shrinkage Associated with Cognitive Impairments

The dysfunction of the small-conductance calcium-activated K⁺ channel SK3 has been described as one of the factors responsible for the progress of psychoneurological diseases, but the molecular basis of this is largely unknown. This report reveals through use of immunohistochemistry and computational tomography that long-term increased expression of the SK3 small-conductance calcium-activated potassium channel (SK3-T/T) in mice induces a notable bilateral reduction of the hippocampal area (more than 50 %). Histological analysis showed that SK3-T/T mice have cellular disarrangements and neuron discontinuities in the hippocampal formation CA1 and CA3 neuronal layer. SK3 overexpression resulted in cognitive loss as determined by the object recognition test. Electrophysiological examination of hippocampal slices revealed that SK3 channel overexpression induced deficiency of long-term potentiation in hippocampal microcircuits. In association with these results, there were changes at the mRNA levels of some genes involved in Alzheimer’s disease and/or linked to schizophrenia, epilepsy, and autism. Taken together, these features suggest that augmenting the function of SK3 ion channel in mice may present a unique opportunity to investigate the neural basis of central nervous system dysfunctions associated with schizophrenia, Alzheimer’s disease, or other neuropsychiatric/neurodegenerative disorders in this model system. As a more detailed understanding of the role of the SK3 channel in brain disorders is limited by the lack of specific SK3 antagonists and agonists, the results observed in this study are of significant interest; they suggest a new approach for the development of neuroprotective strategies in neuropsychiatric/neurodegenerative diseases with SK3 representing a potential drug target.

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.

EpilepsyGene: a genetic resource for genes and mutations related to epilepsy

Epilepsy is one of the most prevalent chronic neurological disorders, afflicting about 3.5–6.5 per 1000 children and 10.8 per 1000 elderly people. With intensive effort made during the last two decades, numerous genes and mutations have been published to be associated with the disease. An organized resource integrating and annotating the ever-increasing genetic data will be imperative to acquire a global view of the cutting-edge in epilepsy research. Herein, we developed EpilepsyGene (http://61.152.91.49/EpilepsyGene). It contains cumulative to date 499 genes and 3931 variants associated with 331 clinical phenotypes collected from 818 publications. Furthermore, in-depth data mining was performed to gain insights into the understanding of the data, including functional annotation, gene prioritization, functional analysis of prioritized genes and overlap analysis focusing on the comorbidity. An intuitive web interface to search and browse the diversified genetic data was also developed to facilitate access to the data of interest. In general, EpilepsyGene is designed to be a central genetic database to provide the research community substantial convenience to uncover the genetic basis of epilepsy.

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.

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.

Brugada syndrome ECG is highly prevalent in schizophrenia

BACKGROUND

The causes of increased risk of sudden cardiac death in schizophrenia are not resolved. We aimed to establish (1) whether ECG markers of sudden cardiac death risk, in particular Brugada-ECG pattern, are more prevalent among patients with schizophrenia, and (2) whether increased prevalence of these ECG markers in schizophrenia is explained by confounding factors, notably sodium channel-blocking medication.

METHODS AND RESULTS

In a cross-sectional study, we analyzed ECGs of a cohort of 275 patients with schizophrenia, along with medication use. We determined whether Brugada-ECG was present and assessed standard ECG measures (heart rate, PQ-, QRS-, and QT-intervals). We compared the findings with nonschizophrenic individuals of comparable age (the Netherlands Study of Depression and Anxiety [NESDA] cohort; N=179) and, to account for assumed increased aging rate in schizophrenia, with individuals 20 years older (Hoorn cohort; n=1168), using multivariate regression models. Brugada-ECG was significantly more prevalent in the schizophrenia cohort (11.6%) compared with NESDA controls (1.1%) or Hoorn controls (2.4%). Moreover, patients with schizophrenia had longer QT-intervals (410.9 versus 393.1 and 401.9 ms; both P<0.05), increased proportion of mild or severe QTc prolongation (13.1% and 5.8% versus 3.4% and 0.0% [NESDA], versus 5.1 and 2.8% [Hoorn]), and higher heart rates (80.8 versus 61.7 and 68.0 beats per minute; both P<0.05). The prevalence of Brugada-ECG was still increased (9.6%) when patients with schizophrenia without sodium channel-blocking medication were compared with either of the control cohorts.

CONCLUSIONS

Brugada-ECG has increased prevalence among patients with schizophrenia. This association is not explained by the use of sodium channel-blocking medication.

Network.assisted analysis to prioritize GWAS results: principles, methods and perspectives

Genome-wide association studies (GWAS) have rapidly become a powerful tool in genetic studies of complex diseases and traits. Traditionally, single marker-based tests have been used prevalently in GWAS and have uncovered tens of thousands of disease-associated SNPs. Network-assisted analysis (NAA) of GWAS data is an emerging area in which network-related approaches are developed and utilized to perform advanced analyses of GWAS data in order to study various human diseases or traits. Progress has been made in both methodology development and applications of NAA in GWAS data, and it has already been demonstrated that NAA results may enhance our interpretation and prioritization of candidate genes and markers. Inspired by the strong interest in and high demand for advanced GWAS data analysis, in this review article, we discuss the methodologies and strategies that have been reported for the NAA of GWAS data. Many NAA approaches search for subnetworks and assess the combined effects of multiple genes participating in the resultant subnetworks through a gene set analysis. With no restriction to pre-defined canonical pathways, NAA has the advantage of defining subnetworks with the guidance of the GWAS data under investigation. In addition, some NAA methods prioritize genes from GWAS data based on their interconnections in the reference network. Here, we summarize NAA applications to various diseases and discuss the available options and potential caveats related to their practical usage. Additionally, we provide perspectives regarding this rapidly growing research area.

Disruption of dopamine neuron activity pattern regulation through selective expression of a human KCNN3 mutation

The calcium-activated small conductance potassium channel SK3 plays an essential role in the regulation of dopamine neuron activity patterns. Here we demonstrate that expression of a human disease-related SK3 mutation (hSK3Δ) in dopamine neurons of mice disrupts the balance between tonic and phasic dopamine neuron activity. Expression of hSK3Δ suppressed endogenous SK currents, reducing coupling between SK channels and NMDA receptors (NMDARs) and increasing permissiveness for burst firing. Consistent with enhanced excitability of dopamine neurons, hSK3Δ increased evoked calcium signals in dopamine neurons in vivo and potentiated evoked dopamine release. Specific expression of hSK3Δ led to deficits in attention and sensory gating and heightened sensitivity to a psychomimetic drug. Sensory-motor alterations and psychomimetic sensitivity were recapitulated in a mouse model of transient, reversible dopamine neuron activation. These results demonstrate the cell-autonomous effects of a human ion channel mutation on dopamine neuron physiology and the impact of activity pattern disruption on behavior.

Role of DISC1 interacting proteins in schizophrenia risk from genome-wide analysis of missense SNPs

A balanced translocation affecting DISC1 cosegregates with several psychiatric disorders, including schizophrenia, in a Scottish family. DISC1 is a hub protein of a network of protein-protein interactions involved in multiple developmental pathways within the brain. Gene set-based analysis has been proposed as an alternative to individual analysis of single nucleotide polymorphisms (SNPs) to get information from genome-wide association studies. In this work, we tested for an overrepresentation of the DISC1 interacting proteins within the top results of our ranked list of genes based on our previous genome-wide association study of missense SNPs in schizophrenia. Our data set consisted of 5100 common missense SNPs genotyped in 476 schizophrenic patients and 447 control subjects from Galicia, NW Spain. We used a modification of the Gene Set Enrichment Analysis adapted for SNPs, as implemented in the GenGen software. The analysis detected an overrepresentation of the DISC1 interacting proteins (permuted P-value=0.0158), indicative of the role of this gene set in schizophrenia risk. We identified seven leading-edge genes, MACF1, UTRN, DST, DISC1, KIF3A, SYNE1, and AKAP9, responsible for the overrepresentation. These genes are involved in neuronal cytoskeleton organization and intracellular transport through the microtubule cytoskeleton, suggesting that these processes may be impaired in schizophrenia.

Major channels involved in neuropsychiatric disorders and therapeutic perspectives

Voltage-gated ion channels are important mediators of physiological functions in the central nervous system. The cyclic activation of these channels influences neurotransmitter release, neuron excitability, gene transcription, and plasticity, providing distinct brain areas with unique physiological and pharmacological response. A growing body of data has implicated ion channels in the susceptibility or pathogenesis of psychiatric diseases. Indeed, population studies support the association of polymorphisms in calcium and potassium channels with the genetic risk for bipolar disorders (BPDs) or schizophrenia. Moreover, point mutations in calcium, sodium, and potassium channel genes have been identified in some childhood developmental disorders. Finally, antibodies against potassium channel complexes occur in a series of autoimmune psychiatric diseases. Here we report recent studies assessing the role of calcium, sodium, and potassium channels in BPD, schizophrenia, and autism spectrum disorders, and briefly summarize promising pharmacological strategies targeted on ion channels for the therapy of mental illness and related genetic tests.

Gene ontology analysis of pairwise genetic associations in two genome-wide studies of sporadic ALS

BACKGROUND

It is increasingly clear that common human diseases have a complex genetic architecture characterized by both additive and nonadditive genetic effects. The goal of the present study was to determine whether patterns of both additive and nonadditive genetic associations aggregate in specific functional groups as defined by the Gene Ontology (GO).

RESULTS

We first estimated all pairwise additive and nonadditive genetic effects using the multifactor dimensionality reduction (MDR) method that makes few assumptions about the underlying genetic model. Statistical significance was evaluated using permutation testing in two genome-wide association studies of ALS. The detection data consisted of 276 subjects with ALS and 271 healthy controls while the replication data consisted of 221 subjects with ALS and 211 healthy controls. Both studies included genotypes from approximately 550,000 single-nucleotide polymorphisms (SNPs). Each SNP was mapped to a gene if it was within 500 kb of the start or end. Each SNP was assigned a p-value based on its strongest joint effect with the other SNPs. We then used the Exploratory Visual Analysis (EVA) method and software to assign a p-value to each gene based on the overabundance of significant SNPs at the α = 0.05 level in the gene. We also used EVA to assign p-values to each GO group based on the overabundance of significant genes at the α = 0.05 level. A GO category was determined to replicate if that category was significant at the α = 0.05 level in both studies. We found two GO categories that replicated in both studies. The first, 'Regulation of Cellular Component Organization and Biogenesis', a GO Biological Process, had p-values of 0.010 and 0.014 in the detection and replication studies, respectively. The second, 'Actin Cytoskeleton', a GO Cellular Component, had p-values of 0.040 and 0.046 in the detection and replication studies, respectively.

CONCLUSIONS

Pathway analysis of pairwise genetic associations in two GWAS of sporadic ALS revealed a set of genes involved in cellular component organization and actin cytoskeleton, more specifically, that were not reported by prior GWAS. However, prior biological studies have implicated actin cytoskeleton in ALS and other motor neuron diseases. This study supports the idea that pathway-level analysis of GWAS data may discover important associations not revealed using conventional one-SNP-at-a-time approaches.

Integration of biological networks and pathways with genetic association studies

Millions of genetic variants have been assessed for their effects on the trait of interest in genome-wide association studies (GWAS). The complex traits are affected by a set of inter-related genes. However, the typical GWAS only examine the association of a single genetic variant at a time. The individual effects of a complex trait are usually small, and the simple sum of these individual effects may not reflect the holistic effect of the genetic system. High-throughput methods enable genomic studies to produce a large amount of data to expand the knowledge base of the biological systems. Biological networks and pathways are built to represent the functional or physical connectivity among genes. Integrated with GWAS data, the network- and pathway-based methods complement the approach of single genetic variant analysis, and may improve the power to identify trait-associated genes. Taking advantage of the biological knowledge, these approaches are valuable to interpret the functional role of the genetic variants, and to further understand the molecular mechanism influencing the traits. The network- and pathway-based methods have demonstrated their utilities, and will be increasingly important to address a number of challenges facing the mainstream GWAS.

Pathway analysis of genomic data: concepts, methods, and prospects for future development

Genome-wide data sets are increasingly being used to identify biological pathways and networks underlying complex diseases. In particular, analyzing genomic data through sets defined by functional pathways offers the potential of greater power for discovery and natural connections to biological mechanisms. With the burgeoning availability of next-generation sequencing, this is an opportune moment to revisit strategies for pathway-based analysis of genomic data. Here, we synthesize relevant concepts and extant methodologies to guide investigators in study design and execution. We also highlight ongoing challenges and proposed solutions. As relevant analytical strategies mature, pathways and networks will be ideally placed to integrate data from diverse -omics sources to harness the extensive, rich information related to disease and treatment mechanisms.