Schizophrenia gene networks and pathways and their applications for novel candidate gene selection

Network-based drug repurposing for schizophrenia

Despite recent progress, the challenges in drug discovery for schizophrenia persist. However, computational drug repurposing has gained popularity as it leverages the wealth of expanding biomedical databases. Network analyses provide a comprehensive understanding of transcription factor (TF) regulatory effects through gene regulatory networks, which capture the interactions between TFs and target genes by integrating various lines of evidence. Using the PANDA algorithm, we examined the topological variances in TF-gene regulatory networks between individuals with schizophrenia and healthy controls. This algorithm incorporates binding motifs, protein interactions, and gene co-expression data. To identify these differences, we subtracted the edge weights of the healthy control network from those of the schizophrenia network. The resulting differential network was then analysed using the CLUEreg tool in the GRAND database. This tool employs differential network signatures to identify drugs that potentially target the gene signature associated with the disease. Our analysis utilised a large RNA-seq dataset comprising 532 post-mortem brain samples from the CommonMind project. We constructed co-expression gene regulatory networks for both schizophrenia cases and healthy control subjects, incorporating 15,831 genes and 413 overlapping TFs. Through drug repurposing, we identified 18 promising candidates for repurposing as potential treatments for schizophrenia. The analysis of TF-gene regulatory networks revealed that the TFs in schizophrenia predominantly regulate pathways associated with energy metabolism, immune response, cell adhesion, and thyroid hormone signalling. These pathways represent significant targets for therapeutic intervention. The identified drug repurposing candidates likely act through TF-targeted pathways. These promising candidates, particularly those with preclinical evidence such as rimonabant and kaempferol, warrant further investigation into their potential mechanisms of action and efficacy in alleviating the symptoms of schizophrenia.

Potential Roles for the GluN2D NMDA Receptor Subunit in Schizophrenia

Glutamate N-methyl-D-aspartate receptor (NMDAR) hypofunction has been proposed to underlie schizophrenia symptoms. This theory arose from the observation that administration of NMDAR antagonists, which are compounds that inhibit NMDAR activity, reproduces behavioural and molecular schizophrenia-like phenotypes, including hallucinations, delusions and cognitive impairments in healthy humans and animal models. However, the role of specific NMDAR subunits in these schizophrenia-relevant phenotypes is largely unknown. Mounting evidence implicates the GluN2D subunit of NMDAR in some of these symptoms and pathology. Firstly, genetic and post-mortem studies show changes in the GluN2D subunit in people with schizophrenia. Secondly, the psychosis-inducing effects of NMDAR antagonists are blunted in GluN2D-knockout mice, suggesting that the GluN2D subunit mediates NMDAR-antagonist-induced psychotomimetic effects. Thirdly, in the mature brain, the GluN2D subunit is relatively enriched in parvalbumin (PV)-containing interneurons, a cell type hypothesized to underlie the cognitive symptoms of schizophrenia. Lastly, the GluN2D subunit is widely and abundantly expressed early in development, which could be of importance considering schizophrenia is a disorder that has its origins in early neurodevelopment. The limitations of currently available therapies warrant further research into novel therapeutic targets such as the GluN2D subunit, which may help us better understand underlying disease mechanisms and develop novel and more effective treatment options.

Emerging evidence for astrocyte dysfunction in schizophrenia

Schizophrenia is a complex, chronic mental health disorder whose heterogeneous genetic and neurobiological background influences early brain development, and whose precise etiology is still poorly understood. Schizophrenia is not characterized by gross brain pathology, but involves subtle pathological changes in neuronal populations and glial cells. Among the latter, astrocytes critically contribute to the regulation of early neurodevelopmental processes, and any dysfunctions in their morphological and functional maturation may lead to aberrant neurodevelopmental processes involved in the pathogenesis of schizophrenia, such as mitochondrial biogenesis, synaptogenesis, and glutamatergic and dopaminergic transmission. Studies of the mechanisms regulating astrocyte maturation may therefore improve our understanding of the cellular and molecular mechanisms underlying the pathogenesis of schizophrenia.

Preservation Analysis on Spatiotemporal Specific Co-expression Networks Suggests the Immunopathogenesis of Alzheimer's Disease

The occurrence and development of Alzheimer’s disease (AD) is a continuous clinical and pathophysiological process, molecular biological, and brain functional change often appear before clinical symptoms, but the detailed underlying mechanism is still unclear. The expression profiling of postmortem brain tissue from AD patients and controls provides evidence about AD etiopathogenesis. In the current study, we used published AD expression profiling data to construct spatiotemporal specific coexpression networks in AD and analyzed the network preservation features of each brain region in different disease stages to identify the most dramatically changed coexpression modules and obtained AD-related biological pathways, brain regions and circuits, cell types and key genes based on these modules. As result, we constructed 57 spatiotemporal specific networks (19 brain regions by three disease stages) in AD and observed universal expression changes in all 19 brain regions. The eight most dramatically changed coexpression modules were identified in seven brain regions. Genes in these modules are mostly involved in immune response-related pathways and non-neuron cells, and this supports the immune pathology of AD and suggests the role of blood brain barrier (BBB) injuries. Differentially expressed genes (DEGs) meta-analysis and protein–protein interaction (PPI) network analysis suggested potential key genes involved in AD development that might be therapeutic targets. In conclusion, our systematical network analysis on published AD expression profiling data suggests the immunopathogenesis of AD and identifies key brain regions and genes.

MetaGSCA: A tool for meta-analysis of gene set differential coexpression

Analyses of gene set differential coexpression may shed light on molecular mechanisms underlying phenotypes and diseases. However, differential coexpression analyses of conceptually similar individual studies are often inconsistent and underpowered to provide definitive results. Researchers can greatly benefit from an open-source application facilitating the aggregation of evidence of differential coexpression across studies and the estimation of more robust common effects. We developed Meta Gene Set Coexpression Analysis (MetaGSCA), an analytical tool to systematically assess differential coexpression of an a priori defined gene set by aggregating evidence across studies to provide a definitive result. In the kernel, a nonparametric approach that accounts for the gene-gene correlation structure is used to test whether the gene set is differentially coexpressed between two comparative conditions, from which a permutation test p-statistic is computed for each individual study. A meta-analysis is then performed to combine individual study results with one of two options: a random-intercept logistic regression model or the inverse variance method. We demonstrated MetaGSCA in case studies investigating two human diseases and identified pathways highly relevant to each disease across studies. We further applied MetaGSCA in a pan-cancer analysis with hundreds of major cellular pathways in 11 cancer types. The results indicated that a majority of the pathways identified were dysregulated in the pan-cancer scenario, many of which have been previously reported in the cancer literature. Our analysis with randomly generated gene sets showed excellent specificity, indicating that the significant pathways/gene sets identified by MetaGSCA are unlikely false positives. MetaGSCA is a user-friendly tool implemented in both forms of a Web-based application and an R package "MetaGSCA". It enables comprehensive meta-analyses of gene set differential coexpression data, with an optional module of post hoc pathway crosstalk network analysis to identify and visualize pathways having similar coexpression profiles.

Rewired Pathways and Disrupted Pathway Crosstalk in Schizophrenia Transcriptomes by Multiple Differential Coexpression Methods

Transcriptomic studies of mental disorders using the human brain tissues have been limited, and gene expression signatures in schizophrenia (SCZ) remain elusive. In this study, we applied three differential co-expression methods to analyze five transcriptomic datasets (three RNA-Seq and two microarray datasets) derived from SCZ and matched normal postmortem brain samples. We aimed to uncover biological pathways where internal correlation structure was rewired or inter-coordination was disrupted in SCZ. In total, we identified 60 rewired pathways, many of which were related to neurotransmitter, synapse, immune, and cell adhesion. We found the hub genes, which were on the center of rewired pathways, were highly mutually consistent among the five datasets. The combinatory list of 92 hub genes was generally multi-functional, suggesting their complex and dynamic roles in SCZ pathophysiology. In our constructed pathway crosstalk network, we found "Clostridium neurotoxicity" and "signaling events mediated by focal adhesion kinase" had the highest interactions. We further identified disconnected gene links underlying the disrupted pathway crosstalk. Among them, four gene pairs (PAK1:SYT1, PAK1:RFC5, DCTN1:STX1A, and GRIA1:MAP2K4) were normally correlated in universal contexts. In summary, we systematically identified rewired pathways, disrupted pathway crosstalk circuits, and critical genes and gene links in schizophrenia transcriptomes.

Zbtb16 regulates social cognitive behaviors and neocortical development

Zinc finger and BTB domain containing 16 (ZBTB16) play the roles in the neural progenitor cell proliferation and neuronal differentiation during development, however, how the function of ZBTB16 is involved in brain function and behaviors unknown. Here we show the deletion of Zbtb16 in mice leads to social impairment, repetitive behaviors, risk-taking behaviors, and cognitive impairment. To elucidate the mechanism underlying the behavioral phenotypes, we conducted histological analyses and observed impairments in thinning of neocortical layer 6 (L6) and a reduction of TBR1+ neurons in Zbtb16 KO mice. Furthermore, we found increased dendritic spines and microglia, as well as developmental defects in oligodendrocytes and neocortical myelination in the prefrontal cortex (PFC) of Zbtb16 KO mice. Using genomics approaches, we identified the Zbtb16 transcriptome that includes genes involved in neocortical maturation such as neurogenesis and myelination, and both autism spectrum disorder (ASD) and schizophrenia (SCZ) pathobiology. Co-expression networks further identified Zbtb16-correlated modules that are unique to ASD or SCZ, respectively. Our study provides insight into the novel roles of ZBTB16 in behaviors and neocortical development related to the disorders.

Schizophrenia in a genomic era: a review from the pathogenesis, genetic and environmental etiology to diagnosis and treatment insights

Schizophrenia is a common multigenic and debilitating neurological disorder characterized by chronic psychotic symptoms and psychosocial impairment. Complex interactions of genetics and environmental factors have been implicated in etiology of schizophrenia. There is no central pathophysiology mechanism, diagnostic neuropathology, or biological markers have been defined for schizophrenia. However, a number of different hypotheses including neurodevelopmental and neurochemical hypotheses have been proposed to explain the neuropathology of schizophrenia. This review provides an overview of pathogenesis, genetic and environmental etiologies to diagnosis and treatment insights in clinical management of schizophrenia in light of the recent discoveries of genetic loci associated with susceptibility to schizophrenia.

Expression correlation attenuates within and between key signaling pathways in chronic kidney disease

BACKGROUND

Compared to the conventional differential expression approach, differential coexpression analysis represents a different yet complementary perspective into diseased transcriptomes. In particular, global loss of transcriptome correlation was previously observed in aging mice, and a most recent study found genetic and environmental perturbations on human subjects tended to cause universal attenuation of transcriptome coherence. While methodological progresses surrounding differential coexpression have helped with research on several human diseases, there has not been an investigation of coexpression disruptions in chronic kidney disease (CKD) yet.

METHODS

RNA-seq was performed on total RNAs of kidney tissue samples from 140 CKD patients. A combination of differential coexpression methods were employed to analyze the transcriptome transition in CKD from the early, mild phase to the late, severe kidney damage phase.

RESULTS

We discovered a global expression correlation attenuation in CKD progression, with pathway Regulation of nuclear SMAD2/3 signaling demonstrating the most remarkable intra-pathway correlation rewiring. Moreover, the pathway Signaling events mediated by focal adhesion kinase displayed significantly weakened crosstalk with seven pathways, including Regulation of nuclear SMAD2/3 signaling. Well-known relevant genes, such as ACTN4, were characterized with widespread correlation disassociation with partners from a wide array of signaling pathways.

CONCLUSIONS

Altogether, our analysis reported a global expression correlation attenuation within and between key signaling pathways in chronic kidney disease, and presented a list of vanishing hub genes and disrupted correlations within and between key signaling pathways, illuminating on the pathophysiological mechanisms of CKD progression.

Computational medicine: quantitative modeling of complex diseases

Biological complex systems are composed of numerous components that interact within and across different scales. The ever-increasing generation of high-throughput biomedical data has given us an opportunity to develop a quantitative model of nonlinear biological systems having implications in health and diseases. Multidimensional molecular data can be modeled using various statistical methods at different scales of biological organization, such as genome, transcriptome and proteome. I will discuss recent advances in the application of computational medicine in complex diseases such as network-based studies, genome-scale metabolic modeling, kinetic modeling and support vector machines with specific examples in the field of cancer, psychiatric disorders and type 2 diabetes. The recent advances in translating these computational models in diagnosis and identification of drug targets of complex diseases are discussed, as well as the challenges researchers and clinicians are facing in taking computational medicine from the bench to bedside.

Schizophrenia-associated MicroRNA-Gene Interactions in the Dorsolateral Prefrontal Cortex

Schizophrenia-associated anomalies in gene expression in postmortem brain can be attributed to a combination of genetic and environmental influences. Given the small effect size of common variants, it is likely that we may only see the combined impact of some of these at the pathway level in small postmortem studies. At the gene level, however, there may be more impact from common environmental exposures mediated by influential epigenomic modifiers, such as microRNA (miRNA). We hypothesise that dysregulation of miRNAs and their alteration of gene expression have significant implications in the pathophysiology of schizophrenia. In this study, we integrate changes in cortical gene and miRNA expression to identify regulatory interactions and networks associated with the disorder. Gene expression analysis in post-mortem prefrontal dorsolateral cortex (BA 46) (n = 74 matched pairs of schizophrenia, schizoaffective, and control samples) was integrated with miRNA expression in the same cohort to identify gene-miRNA regulatory networks. A significant gene-miRNA interaction network was identified, including miR-92a, miR-495, and miR-134, which converged with differentially expressed genes in pathways involved in neurodevelopment and oligodendrocyte function. The capacity for miRNA to directly regulate gene expression through respective binding sites in BCL11A, PLP1, and SYT11 was also confirmed to support the biological relevance of this integrated network model. The observations in this study support the hypothesis that miRNA dysregulation is an important factor in the complex pathophysiology of schizophrenia.

Interactome Analyses implicated CAMK2A in the genetic predisposition and pharmacological mechanism of Bipolar Disorder

Bipolar disorder (BPD) is a severe mental illness characterized by fluctuations in mood states, behaviors and energy levels. Growing evidence suggests that genes associated with specific illnesses tend to interact together and encode a tight protein-protein interaction (PPI) network, providing valuable information for understanding their pathogenesis. To gain insights into the genetic and physiological foundation of BPD, we conduct the physical PPI analysis of 184 BPD risk genes distilled from genome-wide association studies and exome sequencing studies. We have identified several hub genes (CAMK2A, HSP90AA1 and PLCG1) among those risk genes, and observed significant enrichment of the BPD risk genes in certain pathways such as calcium signaling, oxytocin signaling and circadian entrainment. Furthermore, while none of the 184 genetic risk genes are "well established" BPD drug targets, our PPI analysis showed that αCaMKII (encoded by CAMK2A) had direct physical PPIs with targets (HRH1, SCN5A and CACNA1E) of clinically used anti-manic BPD drugs, such as carbamazepine. We thus speculated that αCaMKII might be involved in the cellular pharmacological actions of those drugs. Using cultured rat primary cortical neurons, we found that carbamazepine treatment induced phosphorylation of αCaMKII in dose-dependent manners. Intriguingly, previous study showed that CAMK2A heterozygous knockout (CAMK2A^+/-) mice exhibited infradian oscillation of locomotor activities that can be rescued by carbamazepine. Our data, in combination with previous studies, provide convergent evidence for the involvement of CAMK2A in the risk of BPD.

Mega-analysis of Odds Ratio: A Convergent Method for a Deep Understanding of the Genetic Evidence in Schizophrenia

Numerous high-throughput omics studies have been conducted in schizophrenia, providing an accumulated catalog of susceptible variants and genes. The results from these studies, however, are highly heterogeneous. The variants and genes nominated by different omics studies often have limited overlap with each other. There is thus a pressing need for integrative analysis to unify the different types of data and provide a convergent view of schizophrenia candidate genes (SZgenes). In this study, we collected a comprehensive, multidimensional dataset, including 7819 brain-expressed genes. The data hosted genome-wide association evidence in genetics (eg, genotyping data, copy number variations, de novo mutations), epigenetics, transcriptomics, and literature mining. We developed a method named mega-analysis of odds ratio (MegaOR) to prioritize SZgenes. Application of MegaOR in the multidimensional data resulted in consensus sets of SZgenes (up to 530), each enriched with dense, multidimensional evidence. We proved that these SZgenes had highly tissue-specific expression in brain and nerve and had intensive interactions that were significantly stronger than chance expectation. Furthermore, we found these SZgenes were involved in human brain development by showing strong spatiotemporal expression patterns; these characteristics were replicated in independent brain expression datasets. Finally, we found the SZgenes were enriched in critical functional gene sets involved in neuronal activities, ligand gated ion signaling, and fragile X mental retardation protein targets. In summary, MegaOR analysis reported consensus sets of SZgenes with enriched association evidence to schizophrenia, providing insights into the pathophysiology underlying schizophrenia.

Prenatal Exposure to Benzophenone-3 Impairs Autophagy, Disrupts RXRs/PPARγ Signaling, and Alters Epigenetic and Post-Translational Statuses in Brain Neurons

The UV absorber benzophenone-3 (BP-3) is the most extensively used chemical substance in various personal care products. Despite that BP-3 exposure is widespread, knowledge about the impact of BP-3 on the brain development is negligible. The present study aimed to explore the mechanisms of prenatal exposure to BP-3 in neuronal cells, with particular emphasis on autophagy and nuclear receptors signaling as well as the epigenetic and post-translational modifications occurring in response to BP-3. To observe the impact of prenatal exposure to BP-3, we administered BP-3 to pregnant mice, and next, we isolated brain tissue from pretreated embryos for primary cell neocortical culture. Our study revealed that prenatal exposure to BP-3 (used in environmentally relevant doses) impairs autophagy in terms of BECLIN-1, MAP1LC3B, autophagosomes, and autophagy-related factors; disrupts the levels of retinoid X receptors (RXRs) and peroxisome proliferator-activated receptor gamma (PPARγ); alters epigenetic status (i.e., attenuates HDAC and sirtuin activities); inhibits post-translational modifications in terms of global sumoylation; and dysregulates expression of neurogenesis- and neurotransmitter-related genes as well as miRNAs involved in pathologies of the nervous system. Our study also showed that BP-3 has good permeability through the BBB. We strongly suggest that BP-3-evoked effects may substantiate a fetal basis of the adult onset of neurological diseases, particularly schizophrenia and Alzheimer’s disease.

Non-coding RNA dysregulation in the amygdala region of schizophrenia patients contributes to the pathogenesis of the disease

Schizophrenia (SCZ) is a neuropsychiatric disorder with a complex genetic etiology. The redundancy of the gene networks underlying SCZ indicates that many gene combinations have the potential to cause a system dysfunction that can manifest as SCZ or a related neurodevelopmental disorder. Recent studies show that small non-coding microRNA (miRNA) and long non-coding RNA (lncRNA) are important factors in shaping these networks and are dynamically regulated by neuronal activation. We investigated the genome-wide transcription profiles of 46 human amygdala samples obtained from 22 SCZ patients and 24 healthy controls. Using RNA sequencing (RNA-seq), we determined lncRNA expression levels in all samples and generated miRNA profiles for 27 individuals (13 cases and 14 controls). Previous studies have identified differentially expressed miRNAs in SCZ, including miR-132, miR-212, and miR-34a/miR-34c. Here we report differential expression of a novel miRNA, miR1307, in SCZ. Notably, miR1307 maps to a locus previously associated with SCZ through GWAS. Additionally, one lncRNA that was overexpressed in SCZ, AC005009.2, also maps to a region previously associated with SCZ based on GWAS and overlapped SCZ-related genes. The results were replicated in a large independent data set of 254 dorsolateral prefrontal cortex samples from the CommonMind consortium. Taken together, these results suggest that miRNA and lncRNAs are important contributors to the pathogenesis of SCZ.

A Biomolecular Network Driven Proteinic Interaction in HCV Clearance

Hepatitis C virus infection causes chronic liver disease that leads to cancer-related mortality. Presently around 30% of the HCV (infected) affected population get rid of the infection through spontaneous disease clearance. This phenomenon is conducted by a set of reported immune candidate genes. Hence, this study focuses only on these immune-response related genes with aid of network approach, where the idea is to disseminate the network for better understanding of key functional genes and their transcription control activity. Based on the network analysis the IFNG, TNF, IFNB1, STAT1, NFKB1, STAT3, SOCS1, and MYD88 genes are prioritized as hub genes along with their common transcription factors (TFs), IRF9, NFKB1, and STAT1. The dinucleotide frequency of TF binding elements indicated GG-rich motifs in these regulatory elements. On the other hand, gene enrichment report suggests the regulation of response to interferon gamma signaling pathway, which plays central role in the spontaneous HCV clearance. Therefore, our study tends to prioritize the genes, TFs, and their regulatory pathway towards HCV clearance. Even so, the resultant hub genes and their TFs and TF binding elements could be crucial in underscoring the clearance activity in specific populations.

Induced Pluripotent Stem Cells Reveal Common Neurodevelopmental Genome Deprograming in Schizophrenia

Schizophrenia is a neurodevelopmental disorder characterized by complex aberrations in the structure, wiring, and chemistry of multiple neuronal systems. The abnormal developmental trajectory of the brain is established during gestation, long before clinical manifestation of the disease. Over 200 genes and even greater numbers of single nucleotide polymorphisms and copy number variations have been linked with schizophrenia. How does altered function of such a variety of genes lead to schizophrenia? We propose that the protein products of these altered genes converge on a common neurodevelopmental pathway responsible for the development of brain neural circuit and neurotransmitter systems. The results of a multichanneled investigation using induced pluripotent stem cell (iPSCs)- and embryonic stem cell (ESCs)-derived neuronal committed cells (NCCs) indicate an early (preneuronal) developmental-genomic etiology of schizophrenia and that the dysregulated developmental gene networks are common to genetically unrelated cases of schizophrenia. The results support a "watershed" mechanism in which mutations within diverse signaling pathways affect the common pan-ontogenic mechanism, integrative nuclear (n)FGFR1 signaling (INFS). Dysregulation of INFS in schizophrenia NCCs deconstructs coordinated gene networks and leads to formation of new networks by the dysregulated genes. This genome deprograming affects critical gene programs and pathways for neural development and functions. Studies show that the genomic deprograming reflect an altered nFGFR1-genome interactions and deregulation of miRNA genes by nFGFR1. In addition, changes in chromatin topology imposed by nFGFR1 may play a role in coordinate gene dysregulation in schizophrenia.

Common module analysis reveals prospective targets and mechanisms of pediatric adrenocortical adenoma and carcinoma

Pediatric adrenocortical carcinoma and adrenocortical adenoma are two rare diseases affecting children. Molecular analyses were performed to identify commonalities in gene expression between the diseases. Differentially expressed genes were identified for the pediatric adrenocortical adenoma and carcinoma tissues, as compared with normal tissues, using the expression dataset. Protein-protein interaction (PPI) networks were constructed for adenoma and carcinoma disease models, and common modules among the diseases were identified. A total of two common modules with 14 nodes and 20 nodes were revealed among the adenoma and carcinoma networks, respectively. Genes of the common modules were also identified to be the common hub genes of the disease models. Enrichment of the genes of the common modules suggested associations with steroid biosynthesis, the proteasome, cell cycle and metabolic pathways. Modularity, topological and functional analysis of the PPI networks revealed common modules among pediatric adenoma and carcinoma disease models, which provided insight into the underlying disease mechanisms and suggesting prospective targets for future study.

Evidence of a Conserved Molecular Response to Selection for Increased Brain Size in Primates

The adaptive significance of human brain evolution has been frequently studied through comparisons with other primates. However, the evolution of increased brain size is not restricted to the human lineage but is a general characteristic of primate evolution. Whether or not these independent episodes of increased brain size share a common genetic basis is unclear. We sequenced and de novo assembled the transcriptome from the neocortical tissue of the most highly encephalized nonhuman primate, the tufted capuchin monkey (Cebus apella). Using this novel data set, we conducted a genome-wide analysis of orthologous brain-expressed protein coding genes to identify evidence of conserved gene–phenotype associations and species-specific adaptations during three independent episodes of brain size increase. We identify a greater number of genes associated with either total brain mass or relative brain size across these six species than show species-specific accelerated rates of evolution in individual large-brained lineages. We test the robustness of these associations in an expanded data set of 13 species, through permutation tests and by analyzing how genome-wide patterns of substitution co-vary with brain size. Many of the genes targeted by selection during brain expansion have glutamatergic functions or roles in cell cycle dynamics. We also identify accelerated evolution in a number of individual capuchin genes whose human orthologs are associated with human neuropsychiatric disorders. These findings demonstrate the value of phenotypically informed genome analyses, and suggest at least some aspects of human brain evolution have occurred through conserved gene–phenotype associations. Understanding these commonalities is essential for distinguishing human-specific selection events from general trends in brain evolution.

Mechanism and properties of positive allosteric modulation of N-methyl-d-aspartate receptors by 6-alkyl 2-naphthoic acid derivatives

The theory that N-methyl-d-aspartate receptor (NMDAR) hypofunction is responsible for the symptoms of schizophrenia is well supported by many pharmacological and genetic studies. Accordingly, positive allosteric modulators (PAMs) that augment NMDAR signaling may be useful for treating schizophrenia. Previously we have identified several NMDAR PAMs containing a carboxylic acid attached to naphthalene, phenanthrene, or coumarin ring systems. In this study, we describe several functional and mechanistic properties of UBP684, a 2-naphthoic acid derivative, which robustly potentiates agonist responses at each of the four GluN1a/GluN2 receptors and at neuronal NMDARs. UBP684 increases the maximal l-glutamate/glycine response while having minor subunit-specific effects on agonist potency. PAM binding is independent of agonist binding, and PAM activity is independent of membrane voltage, redox state, and the GluN1 exon 5 N-terminal insert. UBP684 activity is, however, markedly pH-dependent, with greater potentiation occurring at lower pHs and inhibitory activity at pH 8.4. UBP684 increases channel open probability (P_o) and slows receptor deactivation time upon removal of l-glutamate, but not glycine. The structurally related PAM, UBP753, reproduced most of these findings, but did not prolong agonist removal deactivation time. Studies using cysteine mutants to lock the GluN1 and GluN2 ligand-binding domains (LBDs) in the agonist-bound states indicate that PAM potentiation requires GluN2 LBD conformational flexibility. Together, these findings suggest that UBP684 and UBP753 stabilize the GluN2 LBD in an active conformation and thereby increase P_o. Thus, UBP684 and UBP753 may serve as lead compounds for developing agents to enhance NMDAR activity in disorders associated with NMDAR hypofunction.

Pathway-wide association study identifies five shared pathways associated with schizophrenia in three ancestral distinct populations

Genome-wide association studies have confirmed the polygenic nature of schizophrenia and suggest that there are hundreds or thousands of alleles associated with increased liability for the disorder. However, the generalizability of any one allelic marker of liability is remarkably low and has bred the notion that schizophrenia may be better conceptualized as a pathway(s) disorder. Here, we empirically tested this notion by conducting a pathway-wide association study (PWAS) encompassing 255 experimentally validated Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways among 5033 individuals diagnosed with schizophrenia and 5332 unrelated healthy controls across three distinct ethnic populations; European-American (EA), African-American (AA) and Han Chinese (CH). We identified 103, 74 and 87 pathways associated with schizophrenia liability in the EA, CH and AA populations, respectively. About half of these pathways were uniquely associated with schizophrenia liability in each of the three populations. Five pathways (serotonergic synapse, ubiquitin mediated proteolysis, hedgehog signaling, adipocytokine signaling and renin secretion) were shared across all three populations and the single-nucleotide polymorphism sets representing these five pathways were enriched for single-nucleotide polymorphisms with regulatory function. Our findings provide empirical support for schizophrenia as a pathway disorder and suggest schizophrenia is not only a polygenic but likely also a poly-pathway disorder characterized by both genetic and pathway heterogeneity.

Epigenetic profiling of human brain differential DNA methylation networks in schizophrenia

Background

Epigenetics of schizophrenia provides important information on how the environmental factors affect the genetic architecture of the disease. DNA methylation plays a pivotal role in etiology for schizophrenia. Previous studies have focused mostly on the discovery of schizophrenia-associated SNPs or genetic variants. As postmortem brain samples became available, more and more recent studies surveyed transcriptomics of the diseases. In this study, we constructed protein-protein interaction (PPI) network using the disease associated SNP (or genetic variants), differentially expressed disease genes and differentially methylated disease genes (or promoters). By combining the different datasets and topological analyses of the PPI network, we established a more comprehensive understanding of the development and genetics of this devastating mental illness.

Results

We analyzed the previously published DNA methylation profiles of prefrontal cortex from 335 healthy controls and 191 schizophrenic patients. These datasets revealed 2014 CpGs identified as GWAS risk loci with the differential methylation profile in schizophrenia, and 1689 schizophrenic differential methylated genes (SDMGs) identified with predominant hypomethylation. These SDMGs, combined with the PPIs of these genes, were constructed into the schizophrenic differential methylation network (SDMN). On the SDMN, there are 10 hypermethylated SDMGs, including GNA13, CAPNS1, GABPB2, GIT2, LEFTY1, NDUFA10, MIOS, MPHOSPH6, PRDM14 and RFWD2. The hypermethylation to differential expression network (HyDEN) were constructed to determine how the hypermethylated promoters regulate gene expression. The enrichment analyses of biochemical pathways in HyDEN, including TNF alpha, PDGFR-beta signaling, TGF beta Receptor, VEGFR1 and VEGFR2 signaling, regulation of telomerase, hepatocyte growth factor receptor signaling, ErbB1 downstream signaling and mTOR signaling pathway, suggested that the malfunctioning of these pathways contribute to the symptoms of schizophrenia.

Conclusions

The epigenetic profiles of DNA differential methylation from schizophrenic brain samples were investigated to understand the regulatory roles of SDMGs. The SDMGs interplays with SCZCGs in a coordinated fashion in the disease mechanism of schizophrenia. The protein complexes and pathways involved in SDMN may be responsible for the etiology and potential treatment targets. The SDMG promoters are predominantly hypomethylated. Increasing methylation on these promoters is proposed as a novel therapeutic approach for schizophrenia.

Electronic supplementary material

The online version of this article (doi:10.1186/s12920-016-0229-y) contains supplementary material, which is available to authorized users.

Integrative approach for inference of gene regulatory networks using lasso-based random featuring and application to psychiatric disorders

Background

Inferring gene regulatory networks is one of the most interesting research areas in the systems biology. Many inference methods have been developed by using a variety of computational models and approaches. However, there are two issues to solve. First, depending on the structural or computational model of inference method, the results tend to be inconsistent due to innately different advantages and limitations of the methods. Therefore the combination of dissimilar approaches is demanded as an alternative way in order to overcome the limitations of standalone methods through complementary integration. Second, sparse linear regression that is penalized by the regularization parameter (lasso) and bootstrapping-based sparse linear regression methods were suggested in state of the art methods for network inference but they are not effective for a small sample size data and also a true regulator could be missed if the target gene is strongly affected by an indirect regulator with high correlation or another true regulator.

Results

We present two novel network inference methods based on the integration of three different criteria, (i) z-score to measure the variation of gene expression from knockout data, (ii) mutual information for the dependency between two genes, and (iii) linear regression-based feature selection.

Based on these criterion, we propose a lasso-based random feature selection algorithm (LARF) to achieve better performance overcoming the limitations of bootstrapping as mentioned above.

Conclusions

In this work, there are three main contributions. First, our z score-based method to measure gene expression variations from knockout data is more effective than similar criteria of related works. Second, we confirmed that the true regulator selection can be effectively improved by LARF. Lastly, we verified that an integrative approach can clearly outperform a single method when two different methods are effectively jointed. In the experiments, our methods were validated by outperforming the state of the art methods on DREAM challenge data, and then LARF was applied to inferences of gene regulatory network associated with psychiatric disorders.

Biomarkers in schizophrenia: A focus on blood based diagnostics and theranostics

Identifying biomarkers that can be used as diagnostics or predictors of treatment response (theranostics) in people with schizophrenia (Sz) will be an important step towards being able to provide personalized treatment. Findings from the studies in brain tissue have not yet been translated into biomarkers that are practical in clinical use because brain biopsies are not acceptable and neuroimaging techniques are expensive and the results are inconclusive. Thus, in recent years, there has been search for blood-based biomarkers for Sz as a valid alternative. Although there are some encouraging preliminary data to support the notion of peripheral biomarkers for Sz, it must be acknowledged that Sz is a complex and heterogeneous disorder which needs to be further dissected into subtype using biological based and clinical markers. The scope of this review is to critically examine published blood-based biomarker of Sz, focusing on possible uses for diagnosis, treatment response, or their relationship with schizophrenia-associated phenotype. We sorted the studies into six categories which include: (1) brain-derived neurotrophic factor; (2) inflammation and immune function; (3) neurochemistry; (4) oxidative stress response and metabolism; (5) epigenetics and microRNA; and (6) transcriptome and proteome studies. This review also summarized the molecules which have been conclusively reported as potential blood-based biomarkers for Sz in different blood cell types. Finally, we further discusses the pitfall of current blood-based studies and suggest that a prediction model-based, Sz specific, blood oriented study design as well as standardize blood collection conditions would be useful for Sz biomarker development.

Evidence-Based Theory for Integrated Genome Regulation of Ontogeny--An Unprecedented Role of Nuclear FGFR1 Signaling

Genetic experiments have positioned the fgfr1 gene at the top of the gene hierarchy that governs gastrulation, as well as the subsequent development of the major body axes, nervous system, muscles, and bones, by affecting downstream genes that control the cell cycle, pluripotency, and differentiation, as well as microRNAs. Studies show that this regulation is executed by a single protein, the nuclear isoform of FGFR1 (nFGFR1), which integrates signals from development‐initiating factors, such as retinoic acid (RA), and operates at the interface of genomic and epigenomic information. nFGFR1 cooperates with a multitude of transcriptional factors (TFs), and targets thousands of genes encoding for mRNAs, as well as miRNAs in top ontogenic networks. nFGFR1 binds to the promoters of ancient proto‐oncogenes and tumor suppressor genes, in addition to binding to metazoan morphogens that delineate body axes, and construct the nervous system, as well as mesodermal and endodermal tissues. The discovery of pan‐ontogenic gene programming by integrative nuclear FGFR1 signaling (INFS) impacts our understanding of ontogeny, as well as developmental pathologies, and holds new promise for reconstructive medicine, and cancer therapy. J. Cell. Physiol. 231: 1199–1218, 2016. © 2016 The Authors. Journal of Cellular Physiology published by Wiley Periodicals, Inc.

Sex/gender differences in the brain and cognition in schizophrenia

The early conceptualizations of schizophrenia have noted some sex/gender differences in epidemiology and clinical expression of the disorder. Over the past few decades, the interest in differences between male and female patients has expanded to encompass brain morphology and neurocognitive function. Despite some variability and methodological shortcomings, a few patterns emerge from the available literature. Most studies of gross neuroanatomy show more enlarged ventricles and smaller frontal lobes in men than in women with schizophrenia; finding reflecting normal sexual dimorphism. In comparison, studies of brain asymmetry and specific corticolimbic structures, suggest a disturbance in normal sexual dimorphism. The neurocognitive findings are somewhat consistent with this picture. Studies of cognitive functions mediated by the lateral frontal network tend to show sex differences in patients which are in the same direction as those observed in the general population, whereas studies of processes mediated by the corticolimbic system more frequently reveal reversal of normal sexual dimorphisms. These trends are faint and future research would need to delineate neurocognitive differences between men and women with various subtypes of schizophrenia (e.g., early versus late onset), while taking into consideration hormonal status and gender of tested participants.

NERI: network-medicine based integrative approach for disease gene prioritization by relative importance

Background

Complex diseases are characterized as being polygenic and multifactorial, so this poses a challenge regarding the search for genes related to them. With the advent of high-throughput technologies for genome sequencing, gene expression measurements (transcriptome), and protein-protein interactions, complex diseases have been sistematically investigated. Particularly, Protein-Protein Interaction (PPI) networks have been used to prioritize genes related to complex diseases according to its topological features. However, PPI networks are affected by ascertainment bias, in which more studied proteins tend to have more connections, degrading the results quality. Additionally, methods using only PPI networks can provide only static and non-specific results, since the topologies of these networks are not specific of a given disease.

Results

The goal of this work is to develop a methodology that integrates PPI networks with disease specific data sources, such as GWAS and gene expression, to find genes more specific of a given complex disease. After the integration of PPI networks and gene expression data, the resulting network is used to connect genes related to the disease through the shortest paths that have the greatest concordance between their gene expressions. Both case and control expression data are used separately and, at the end, the most altered genes between the two conditions are selected. To evaluate the method, schizophrenia was adopted as case study.

Conclusion

Results show that the proposed method successfully retrieves differentially coexpressed genes in two conditions, while avoiding the bias from literature. Moreover we were able to achieve a greater concordance in the selection of important genes from different microarray studies of the same disease and to produce a more specific gene set related to the studied disease.

GluN2D N-Methyl-d-Aspartate Receptor Subunit Contribution to the Stimulation of Brain Activity and Gamma Oscillations by Ketamine: Implications for Schizophrenia

The dissociative anesthetic ketamine elicits symptoms of schizophrenia at subanesthetic doses by blocking N-methyl-d-aspartate receptors (NMDARs). This property led to a variety of studies resulting in the now well-supported theory that hypofunction of NMDARs is responsible for many of the symptoms of schizophrenia. However, the roles played by specific NMDAR subunits in different symptom components are unknown. To evaluate the potential contribution of GluN2D NMDAR subunits to antagonist-induced cortical activation and schizophrenia symptoms, we determined the ability of ketamine to alter regional brain activity and gamma frequency band neuronal oscillations in wild-type (WT) and GluN2D-knockout (GluN2D-KO) mice. In WT mice, ketamine (30 mg/kg, i.p.) significantly increased [(14)C]-2-deoxyglucose ([(14)C]-2DG) uptake in the medial prefrontal cortex (mPFC), entorhinal cortex and other brain regions, and decreased activity in the somatosensory cortex and inferior colliculus. In GluN2D-KO mice, however, ketamine did not significantly increase [(14)C]-2DG uptake in any brain region examined, yet still decreased [(14)C]-2DG uptake in the somatosensory cortex and inferior colliculus. Ketamine also increased locomotor activity in WT mice but not in GluN2D-KO mice. In electrocorticographic analysis, ketamine induced a 111% ± 16% increase in cortical gamma-band oscillatory power in WT mice, but only a 15% ± 12% increase in GluN2D-KO mice. Consistent with GluN2D involvement in schizophrenia-related neurologic changes, GluN2D-KO mice displayed impaired spatial memory acquisition and reduced parvalbumin (PV)-immunopositive staining compared with control mice. These results suggest a critical role of GluN2D-containing NMDARs in neuronal oscillations and ketamine's psychotomimetic, dissociative effects and hence suggests a critical role for GluN2D subunits in cognition and perception.

Two-stage comprehensive evaluation of genetic susceptibility of common variants in FBXO38, AP3B2 and WHAMM to severe chronic periodontitis

Chronic periodontitis is an oral disorder characterized with gingival inflammation and bone destruction. As the sixth-most prevalent condition affecting more than 743 million people around the world, it is classified as one of the seven destructive oral disorders. Early genetic epidemiological evidence indicated a major role for genetics in periodontal disease development. In this study, we conducted a two-stage comprehensive evaluation of the genetic susceptibility of FBXO38, AP3B2 and WHAMM with the diagnosis of severe chronic periodontitis. A total of 5,065 study subjects from the Han Chinese population consisting of 1,264 cases and 3,801 healthy controls were recruited, and 65 single nucleotide markers related to the three candidate genes were genotyped to investigate the susceptibility of patients with these polymorphisms to severe chronic periodontitis. To increase the coverage of genetic markers, we implemented imputation techniques to extend the number of tested makers to 416. Single marker and haplotype-based analyses were performed, and significant results were obtained for FBXO38 (rs10043775, P = 0.0009) and AP3B2 (rs11631963-rs11637433, CA, P = 9.98 × 10(-5); rs1864699-rs2099259-rs2278355, ATC, P = 3.84 × 10(-8)). Our findings provide direct evidence for the association of FBXO38 and AP3B2 with severe chronic periodontitis in the Han Chinese population.

Inhibition of 14-3-3 Proteins Leads to Schizophrenia-Related Behavioral Phenotypes and Synaptic Defects in Mice

BACKGROUND

The 14-3-3 family of proteins is implicated in the regulation of several key neuronal processes. Previous human and animal studies suggested an association between 14-3-3 dysregulation and schizophrenia.

METHODS

We characterized behavioral and functional changes in transgenic mice that express an isoform-independent 14-3-3 inhibitor peptide in the brain.

RESULTS

We recently showed that 14-3-3 functional knockout mice (FKO) exhibit impairments in associative learning and memory. We report here that these 14-3-3 FKO mice display other behavioral deficits that correspond to the core symptoms of schizophrenia. These behavioral deficits may be attributed to alterations in multiple neurotransmission systems in the 14-3-3 FKO mice. In particular, inhibition of 14-3-3 proteins results in a reduction of dendritic complexity and spine density in forebrain excitatory neurons, which may underlie the altered synaptic connectivity in the prefrontal cortical synapse of the 14-3-3 FKO mice. At the molecular level, this dendritic spine defect may stem from dysregulated actin dynamics secondary to a disruption of the 14-3-3-dependent regulation of phosphorylated cofilin.

CONCLUSIONS

Collectively, our data provide a link between 14-3-3 dysfunction, synaptic alterations, and schizophrenia-associated behavioral deficits.

Distilling a Visual Network of Retinitis Pigmentosa Gene-Protein Interactions to Uncover New Disease Candidates

Background

Retinitis pigmentosa (RP) is a highly heterogeneous genetic visual disorder with more than 70 known causative genes, some of them shared with other non-syndromic retinal dystrophies (e.g. Leber congenital amaurosis, LCA). The identification of RP genes has increased steadily during the last decade, and the 30% of the cases that still remain unassigned will soon decrease after the advent of exome/genome sequencing. A considerable amount of genetic and functional data on single RD genes and mutations has been gathered, but a comprehensive view of the RP genes and their interacting partners is still very fragmentary. This is the main gap that needs to be filled in order to understand how mutations relate to progressive blinding disorders and devise effective therapies.

Methodology

We have built an RP-specific network (RPGeNet) by merging data from different sources: high-throughput data from BioGRID and STRING databases, manually curated data for interactions retrieved from iHOP, as well as interactions filtered out by syntactical parsing from up-to-date abstracts and full-text papers related to the RP research field. The paths emerging when known RP genes were used as baits over the whole interactome have been analysed, and the minimal number of connections among the RP genes and their close neighbors were distilled in order to simplify the search space.

Conclusions

In contrast to the analysis of single isolated genes, finding the networks linking disease genes renders powerful etiopathological insights. We here provide an interactive interface, RPGeNet, for the molecular biologist to explore the network centered on the non-syndromic and syndromic RP and LCA causative genes. By integrating tissue-specific expression levels and phenotypic data on top of that network, a more comprehensive biological view will highlight key molecular players of retinal degeneration and unveil new RP disease candidates.

Functional genomics indicate that schizophrenia may be an adult vascular-ischemic disorder

In search for the elusive schizophrenia pathway, candidate genes for the disorder from a discovery sample were localized within the energy-delivering and ischemia protection pathway. To test the adult vascular-ischemic (AVIH) and the competing neurodevelopmental hypothesis (NDH), functional genomic analyses of practically all available schizophrenia-associated genes from candidate gene, genome-wide association and postmortem expression studies were performed. Our results indicate a significant overrepresentation of genes involved in vascular function (P < 0.001), vasoregulation (that is, perivascular (P < 0.001) and shear stress (P < 0.01), cerebral ischemia (P < 0.001), neurodevelopment (P < 0.001) and postischemic repair (P < 0.001) among schizophrenia-associated genes from genetic association studies. These findings support both the NDH and the AVIH. The genes from postmortem studies showed an upregulation of vascular-ischemic genes (P = 0.020) combined with downregulated synaptic (P = 0.005) genes, and ND/repair (P = 0.003) genes. Evidence for the AVIH and the NDH is critically discussed. We conclude that schizophrenia is probably a mild adult vascular-ischemic and postischemic repair disorder. Adult postischemic repair involves ND genes for adult neurogenesis, synaptic plasticity, glutamate and increased long-term potentiation of excitatory neurotransmission (i-LTP). Schizophrenia might be caused by the cerebral analog of microvascular angina.

Network analysis reveals a stress-affected common gene module among seven stress-related diseases/systems which provides potential targets for mechanism research

Chronic stress (CS) was reported to associate with many complex diseases and stress-related diseases show strong comorbidity; however, molecular analyses have not been performed to date to evaluate common stress-induced biological processes across these diseases. We utilized networks constructed by genes from seven genetic databases of stress-related diseases or systems to explore the common mechanisms. Genes were connected based on the interaction information of proteins they encode. A common sub-network constructed by 561 overlapping genes and 8863 overlapping edges among seven networks was identified and it provides a common gene module among seven stress-related diseases/systems. This module is significantly overlapped with network that constructed by genes from the CS gene database. 36 genes with high connectivity (hub genes) were identified from seven networks as potential key genes in those diseases/systems, 33 of hub genes were included in the common module. Genes in the common module were enriched in 190 interactive gene ontology (GO) functional clusters which provide potential disease mechanism. In conclusion, by analyzing gene networks we revealed a stress-affected common gene module among seven stress-related diseases/systems which provides insight into the process of stress induction of disease and suggests potential gene and pathway candidates for further research.

Functional genomics indicate that schizophrenia may be an adult vascular-ischemic disorder

In search for the elusive schizophrenia pathway, candidate genes for the disorder from a discovery sample were localized within the energy-delivering and ischemia protection pathway. To test the adult vascular-ischemic (AVIH) and the competing neurodevelopmental hypothesis (NDH), functional genomic analyses of practically all available schizophrenia-associated genes from candidate gene, genome-wide association and postmortem expression studies were performed. Our results indicate a significant overrepresentation of genes involved in vascular function (P < 0.001), vasoregulation (that is, perivascular (P < 0.001) and shear stress (P < 0.01), cerebral ischemia (P < 0.001), neurodevelopment (P < 0.001) and postischemic repair (P < 0.001) among schizophrenia-associated genes from genetic association studies. These findings support both the NDH and the AVIH. The genes from postmortem studies showed an upregulation of vascular-ischemic genes (P = 0.020) combined with downregulated synaptic (P = 0.005) genes, and ND/repair (P = 0.003) genes. Evidence for the AVIH and the NDH is critically discussed. We conclude that schizophrenia is probably a mild adult vascular-ischemic and postischemic repair disorder. Adult postischemic repair involves ND genes for adult neurogenesis, synaptic plasticity, glutamate and increased long-term potentiation of excitatory neurotransmission (i-LTP). Schizophrenia might be caused by the cerebral analog of microvascular angina.

A Systematic Analysis of Candidate Genes Associated with Nicotine Addiction

Nicotine, as the major psychoactive component of tobacco, has broad physiological effects within the central nervous system, but our understanding of the molecular mechanism underlying its neuronal effects remains incomplete. In this study, we performed a systematic analysis on a set of nicotine addiction-related genes to explore their characteristics at network levels. We found that NAGenes tended to have a more moderate degree and weaker clustering coefficient and to be less central in the network compared to alcohol addiction-related genes or cancer genes. Further, clustering of these genes resulted in six clusters with themes in synaptic transmission, signal transduction, metabolic process, and apoptosis, which provided an intuitional view on the major molecular functions of the genes. Moreover, functional enrichment analysis revealed that neurodevelopment, neurotransmission activity, and metabolism related biological processes were involved in nicotine addiction. In summary, by analyzing the overall characteristics of the nicotine addiction related genes, this study provided valuable information for understanding the molecular mechanisms underlying nicotine addiction.

Oncogenes and tumor suppressor genes: comparative genomics and network perspectives

BACKGROUND

Defective tumor suppressor genes (TSGs) and hyperactive oncogenes (OCGs) heavily contribute to cell proliferation and apoptosis during cancer development through genetic variations such as somatic mutations and deletions. Moreover, they usually do not perform their cellular functions individually but rather execute jointly. Therefore, a comprehensive comparison of their mutation patterns and network properties may provide a deeper understanding of their roles in the cancer development and provide some clues for identification of novel targets.

RESULTS

In this study, we performed a comprehensive survey of TSGs and OCGs from the perspectives of somatic mutations and network properties. For comparative purposes, we choose five gene sets: TSGs, OCGs, cancer drug target genes, essential genes, and other genes. Based on the data from Pan-Cancer project, we found that TSGs had the highest mutation frequency in most tumor types and the OCGs second. The essential genes had the lowest mutation frequency in all tumor types. For the network properties in the human protein-protein interaction (PPI) network, we found that, relative to target proteins, essential proteins, and other proteins, the TSG proteins and OCG proteins both tended to have higher degrees, higher betweenness, lower clustering coefficients, and shorter shortest-path distances. Moreover, the TSG proteins and OCG proteins tended to have direct interactions with cancer drug target proteins. To further explore their relationship, we generated a TSG-OCG network and found that TSGs and OCGs connected strongly with each other. The integration of the mutation frequency with the TSG-OCG network offered a network view of TSGs, OCGs, and their interactions, which may provide new insights into how the TSGs and OCGs jointly contribute to the cancer development.

CONCLUSIONS

Our study first discovered that the OCGs and TSGs had different mutation patterns, but had similar and stronger protein-protein characteristics relative to the essential proteins or control proteins in the whole human interactome. We also found that the TSGs and OCGs had the most direct interactions with cancer drug targets. The results will be helpful for cancer drug target identification, and ultimately, understanding the etiology of cancer and treatment at the network level.

Co-expression network of neural-differentiation genes shows specific pattern in schizophrenia

Background

Schizophrenia is a neurodevelopmental disorder with genetic and environmental factors contributing to its pathogenesis, although the mechanism is unknown due to the difficulties in accessing diseased tissue during human neurodevelopment. The aim of this study was to find neuronal differentiation genes disrupted in schizophrenia and to evaluate those genes in post-mortem brain tissues from schizophrenia cases and controls.

Methods

We analyzed differentially expressed genes (DEG), copy number variation (CNV) and differential methylation in human induced pluripotent stem cells (hiPSC) derived from fibroblasts from one control and one schizophrenia patient and further differentiated into neuron (NPC). Expression of the DEG were analyzed with microarrays of post-mortem brain tissue (frontal cortex) cohort of 29 schizophrenia cases and 30 controls. A Weighted Gene Co-expression Network Analysis (WGCNA) using the DEG was used to detect clusters of co-expressed genes that werenon-conserved between adult cases and controls brain samples.

Results

We identified methylation alterations potentially involved with neuronal differentiation in schizophrenia, which displayed an over-representation of genes related to chromatin remodeling complex (adjP = 0.04). We found 228 DEG associated with neuronal differentiation. These genes were involved with metabolic processes, signal transduction, nervous system development, regulation of neurogenesis and neuronal differentiation. Between adult brain samples from cases and controls there were 233 DEG, with only four genes overlapping with the 228 DEG, probably because we compared single cell to tissue bulks and more importantly, the cells were at different stages of development. The comparison of the co-expressed network of the 228 genes in adult brain samples between cases and controls revealed a less conserved module enriched for genes associated with oxidative stress and negative regulation of cell differentiation.

Conclusion

This study supports the relevance of using cellular approaches to dissect molecular aspects of neurogenesis with impact in the schizophrenic brain. We showed that, although generated by different approaches, both sets of DEG associated to schizophrenia were involved with neocortical development. The results add to the hypothesis that critical metabolic changes may be occurring during early neurodevelopment influencing faulty development of the brain and potentially contributing to further vulnerability to the illness.

Electronic supplementary material

The online version of this article (doi:10.1186/s12920-015-0098-9) contains supplementary material, which is available to authorized users.

Pathways and networks-based analysis of candidate genes associated with nicotine addiction

Nicotine is the addictive substance in tobacco and it has a broad impact on both the central and peripheral nervous systems. Over the past decades, an increasing number of genes potentially involved in nicotine addiction have been identified by different technical approaches. However, the molecular mechanisms underlying nicotine addiction remain largely unclear. Under such situation, a comprehensive analysis focusing on the overall functional characteristics of these genes, as well as how they interact with each other will provide us valuable information to understand nicotine addiction. In this study, we presented a systematic analysis on nicotine addiction-related genes to identify the major underlying biological themes. Functional analysis revealed that biological processes and biochemical pathways related to neurodevelopment, immune system and metabolism were significantly enriched in the nicotine addiction-related genes. By extracting the nicotine addiction-specific subnetwork, a number of novel genes associated with addiction were identified. Moreover, we constructed a schematic molecular network for nicotine addiction via integrating the pathways and network, providing an intuitional view to understand the development of nicotine addiction. Pathway and network analysis indicated that the biological processes related to nicotine addiction were complex. Results from our work may have important implications for understanding the molecular mechanism underlying nicotine addiction.

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.

An overview of the neurobiology of suicidal behaviors as one meta-system

Suicidal behaviors (SB) may be regarded as the outmost consequence of mental illnesses, or as a distinct entity per se. Regardless, the consequences of SB are very large to both society and affected individuals. The path leading to SB is clearly a complex one involving interactions between the subject's biology and environmental influences throughout life. With the aim to generate a representative and diversified overview of the different neurobiological components hypothesized or shown implicated across the entire SB field up to date by any approach, we selected and compiled a list of 212 gene symbols from the literature. An increasing number of novel gene (products) have been introduced as candidates, with half being implicated in SB in only the last 4 years. These candidates represent different neuro systems and functions and might therefore be regarded as competing or redundant explanations. We then adopted a unifying approach by treating them all as parts of the same meta-system, using bioinformatic tools. We present a network of all components connected by physical protein-protein interactions (the SB interactome). We proceeded by exploring the differences between the highly connected core (~30% of the candidate genes) and its peripheral parts, observing more functional homogeneity at the core, with multiple signal transduction pathways and actin-interacting proteins connecting a subset of receptors in nerve cell compartments as well as development/morphology phenotypes and the stress-sensitive synaptic plasticity processes of long term potentiation/depression. We suggest that SB neurobiology might also be viewed as one meta-system and perhaps be explained as intrinsic unbalances acting within the core or as imbalances arising between core and specific peripheral components.

Network analysis of gene expression in peripheral blood identifies mTOR and NF-κB pathways involved in antipsychotic-induced extrapyramidal symptoms

To identify the candidate genes for pharmacogenetic studies of antipsychotic (AP)-induced extrapyramidal symptoms (EPS), we propose a systems biology analytical approach, based on protein-protein interaction network construction and functional annotation analysis, of changes in gene expression (Human Genome U219 Array Plate) induced by treatment with risperidone or paliperidone in peripheral blood. 12 AP-naïve patients with first-episode psychosis participated in the present study. Our analysis revealed that, in response to AP treatment, constructed networks were enriched for different biological processes in patients without EPS (ubiquitination, protein folding and adenosine triphosphate (ATP) metabolism) compared with those presenting EPS (insulin receptor signaling, lipid modification, regulation of autophagy and immune response). Moreover, the observed differences also involved specific pathways, such as anaphase promoting complex /cdc20, prefoldin/CCT/triC and ATP synthesis in no-EPS patients, and mammalian target of rapamycin and NF-κB kinases in patients with EPS. Our results showing different patterns of gene expression in EPS patients, offer new and valuable markers for pharmacogenetic studies.

Genetic Variants of Interleukin-10 Gene Promoter are Associated with Schizophrenia in Saudi Patients: A Case-Control Study

BACKGROUND

Interleukin-10 (IL-10) gene is considered as a potential candidate gene in schizophrenia association studies. The polymorphisms on IL-10 gene have been reported to be linked with susceptibility to the development of schizophrenia within consistent results.

AIMS

The aim of this case-control study was to examine whether the -1082A/G, -819T/C, and -592A/C polymorphisms in IL-10 gene are implicated in schizophrenia development in the Saudi population.

MATERIALS AND METHODS

Molecular genotyping of IL-10 gene polymorphisms was performed to analyze the genotypes and alleles distribution of three single-nucleotide polymorphisms (SNPs) in patients (n = 181) and healthy individuals as control group (n = 211).

RESULTS

The frequencies of GA genotype at -1082, and CC genotype at positions -592 and -819 were significantly higher in schizophrenia patients compared to healthy subjects suggesting that GA, CC, and CC genotypes are susceptible to schizophrenia. The ACC haplotype known to be associated with intermediate production of IL-10 are more prevalent in our schizophrenia patients. On the other hand, genotypes -1082 GG, -819 CT, and -592 CA of IL-10 were more prevalent in healthy controls suggesting protective effects of GA, CT, and CA genotypes against schizophrenia. There was no significant association of IL-10 polymorphisms with sex or positive or negative symptoms of schizophrenia.

CONCLUSION

This study indicates that the IL-10 gene polymorphisms play a significant role in the etiology of schizophrenia in Saudi Arabians patients.

Transcriptome alterations of mitochondrial and coagulation function in schizophrenia by cortical sequencing analysis

Background

Transcriptome sequencing of brain samples provides detailed enrichment analysis of differential expression and genetic interactions for evaluation of mitochondrial and coagulation function of schizophrenia. It is implicated that schizophrenia genetic and protein interactions may give rise to biological dysfunction of energy metabolism and hemostasis. These findings may explain the biological mechanisms responsible for negative and withdraw symptoms of schizophrenia and antipsychotic-induced venous thromboembolism.

We conducted a comparison of schizophrenic candidate genes from literature reviews and constructed the schizophrenia-mediator network (SCZMN) which consists of schizophrenic candidate genes and associated mediator genes by applying differential expression analysis to BA22 RNA-Seq brain data. The network was searched against pathway databases such as PID, Reactome, HumanCyc, and Cell-Map. The candidate complexes were identified by MCL clustering using CORUM for potential pathogenesis of schizophrenia.

Results

Published BA22 RNA-Seq brain data of 9 schizophrenic patients and 9 controls samples were analyzed. The differentially expressed genes in the BA22 brain samples of schizophrenia are proposed as schizophrenia candidate marker genes (SCZCGs). The genetic interactions between mitochondrial genes and many under-expressed SCZCGs indicate the genetic predisposition of mitochondria dysfunction in schizophrenia. The biological functions of SCZCGs, as listed in the Pathway Interaction Database (PID), indicate that these genes have roles in DNA binding transcription factor, signal and cancer-related pathways, coagulation and cell cycle regulation and differentiation pathways.

In the query-query protein-protein interaction (QQPPI) network of SCZCGs, TP53, PRKACA, STAT3 and SP1 were identified as the central "hub" genes. Mitochondrial function was modulated by dopamine inhibition of respiratory complex I activity. The genetic interaction between mitochondria function and schizophrenia may be revealed by DRD2 linked to NDUFS7 through protein-protein interactions of FLNA and ARRB2.

The biological mechanism of signaling pathway of coagulation cascade was illustrated by the PPI network of the SCZCGs and the coagulation-associated genes. The relationship between antipsychotic target genes (DRD2/3 and HTR2A) and coagulation factor genes (F3, F7 and F10) appeared to cascade the following hemostatic process implicating the bottleneck of coagulation genetic network by the bridging of actin-binding protein (FLNA).

Conclusions

It is implicated that the energy metabolism and hemostatic process have important roles in the pathogenesis for schizophrenia. The cross-talk of genetic interaction by these co-expressed genes and reached candidate genes may address the key network in disease pathology. The accuracy of candidate genes evaluated from different quantification tools could be improved by crosstalk analysis of overlapping genes in genetic networks.

Genome-Wide Analyses of Working-Memory Ability: A Review

Working memory, a theoretical construct from the field of cognitive psychology, is crucial to everyday life. It refers to the ability to temporarily store and manipulate task-relevant information. The identification of genes for working memory might shed light on the molecular mechanisms of this important cognitive ability and-given the genetic overlap between, for example, schizophrenia risk and working-memory ability-might also reveal important candidate genes for psychiatric illness. A number of genome-wide searches for genes that influence working memory have been conducted in recent years. Interestingly, the results of those searches converge on the mediating role of neuronal excitability in working-memory performance, such that the role of each gene highlighted by genome-wide methods plays a part in ion channel formation and/or dopaminergic signaling in the brain, with either direct or indirect influence on dopamine levels in the prefrontal cortex. This result dovetails with animal models of working memory that highlight the role of dynamic network connectivity, as mediated by dopaminergic signaling, in the dorsolateral prefrontal cortex. Future work, which aims to characterize functional variants influencing working-memory ability, might choose to focus on those genes highlighted in the present review and also those networks in which the genes fall. Confirming gene associations and highlighting functional characterization of those associations might have implications for the understanding of normal variation in working-memory ability and also for the development of drugs for mental illness.

Prediction of disease-related genes based on weighted tissue-specific networks by using DNA methylation

BACKGROUND

Predicting disease-related genes is one of the most important tasks in bioinformatics and systems biology. With the advances in high-throughput techniques, a large number of protein-protein interactions are available, which make it possible to identify disease-related genes at the network level. However, network-based identification of disease-related genes is still a challenge as the considerable false-positives are still existed in the current available protein interaction networks (PIN).

RESULTS

Considering the fact that the majority of genetic disorders tend to manifest only in a single or a few tissues, we constructed tissue-specific networks (TSN) by integrating PIN and tissue-specific data. We further weighed the constructed tissue-specific network (WTSN) by using DNA methylation as it plays an irreplaceable role in the development of complex diseases. A PageRank-based method was developed to identify disease-related genes from the constructed networks. To validate the effectiveness of the proposed method, we constructed PIN, weighted PIN (WPIN), TSN, WTSN for colon cancer and leukemia, respectively. The experimental results on colon cancer and leukemia show that the combination of tissue-specific data and DNA methylation can help to identify disease-related genes more accurately. Moreover, the PageRank-based method was effective to predict disease-related genes on the case studies of colon cancer and leukemia.

CONCLUSIONS

Tissue-specific data and DNA methylation are two important factors to the study of human diseases. The same method implemented on the WTSN can achieve better results compared to those being implemented on original PIN, WPIN, or TSN. The PageRank-based method outperforms degree centrality-based method for identifying disease-related genes from WTSN.

Advanced fault diagnosis methods in molecular networks

Analysis of the failure of cell signaling networks is an important topic in systems biology and has applications in target discovery and drug development. In this paper, some advanced methods for fault diagnosis in signaling networks are developed and then applied to a caspase network and an SHP2 network. The goal is to understand how, and to what extent, the dysfunction of molecules in a network contributes to the failure of the entire network. Network dysfunction (failure) is defined as failure to produce the expected outputs in response to the input signals. Vulnerability level of a molecule is defined as the probability of the network failure, when the molecule is dysfunctional. In this study, a method to calculate the vulnerability level of single molecules for different combinations of input signals is developed. Furthermore, a more complex yet biologically meaningful method for calculating the multi-fault vulnerability levels is suggested, in which two or more molecules are simultaneously dysfunctional. Finally, a method is developed for fault diagnosis of networks based on a ternary logic model, which considers three activity levels for a molecule instead of the previously published binary logic model, and provides equations for the vulnerabilities of molecules in a ternary framework. Multi-fault analysis shows that the pairs of molecules with high vulnerability typically include a highly vulnerable molecule identified by the single fault analysis. The ternary fault analysis for the caspase network shows that predictions obtained using the more complex ternary model are about the same as the predictions of the simpler binary approach. This study suggests that by increasing the number of activity levels the complexity of the model grows; however, the predictive power of the ternary model does not appear to be increased proportionally.

Schizophrenia: an integrated sociodevelopmental-cognitive model

Schizophrenia remains a major burden on patients and society. The dopamine hypothesis attempts to explain the pathogenic mechanisms of the disorder, and the neurodevelopmental hypothesis the origins. In the past 10 years an alternative, the cognitive model, has gained popularity. However, the first two theories have not been satisfactorily integrated, and the most influential iteration of the cognitive model makes no mention of dopamine, neurodevelopment, or indeed the brain. In this Review we show that developmental alterations secondary to variant genes, early hazards to the brain, and childhood adversity sensitise the dopamine system, and result in excessive presynaptic dopamine synthesis and release. Social adversity biases the cognitive schema that the individual uses to interpret experiences towards paranoid interpretations. Subsequent stress results in dysregulated dopamine release, causing the misattribution of salience to stimuli, which are then misinterpreted by the biased cognitive processes. The resulting paranoia and hallucinations in turn cause further stress, and eventually repeated dopamine dysregulation hardwires the psychotic beliefs. Finally, we consider the implications of this model for understanding and treatment of schizophrenia.