Gene expression in the etiology of schizophrenia

Whole transcriptome analysis reveals dysregulation of molecular networks in schizophrenia

To characterize the regulatory relationships between different types of transcripts and the altered molecular networks in schizophrenia (SCZ), we performed a whole transcriptome study by quantifying mRNAs, long noncoding RNAs (lncRNAs), miRNAs, and circular RNAs (circRNAs) in the same individuals simultaneously. A total of 807 dysregulated genes showed differential expression in SCZ cases compared with controls. Network-based analysis revealed dysregulation of molecular networks in SCZ. Finally, integration of the transcriptome data with published data identified promising SCZ candidate genes. Our study reveals that dysregulated molecular networks and regulatory relationships between different types of transcript may have a role in SCZ.

Candidates for drug repurposing to address the cognitive symptoms in schizophrenia

In the protein-protein interactome, we have previously identified a significant overlap between schizophrenia risk genes and genes associated with cognitive performance. Here, we further studied this overlap to identify potential candidate drugs for repurposing to treat the cognitive symptoms in schizophrenia. We first defined a cognition-related schizophrenia interactome from network propagation analyses, and identified drugs known to target more than one protein within this network. Thereafter, we used gene expression data to further select drugs that could counteract schizophrenia-associated gene expression perturbations. Additionally, we stratified these analyses by sex to identify sex-specific pharmacological treatment options for the cognitive symptoms in schizophrenia. After excluding drugs contraindicated in schizophrenia, we identified 12 drug repurposing candidates, most of which have anti-inflammatory and neuroprotective effects. Sex-stratified analyses showed that out of these 12 drugs, four were identified in females only, three were identified in males only, and five were identified in both sexes. Based on our bioinformatics analyses of disease genetics, we suggest 12 candidate drugs that warrant further examination for repurposing to treat the cognitive symptoms in schizophrenia, and suggest that these symptoms could be addressed by sex-specific pharmacological treatment options.

Evidence that a working memory cognitive phenotype within schizophrenia has a unique underlying biology

It is suggested studying phenotypes within the syndrome of schizophrenia will accelerate understanding the complex molecular pathology of the disorder. Supporting this hypothesis, we have identified a sub-group within schizophrenia with impaired working memory (WM) and have used Affymetrix™ Human Exon 1.0 ST Arrays to compare their blood RNA levels (n=16) to a group of with intact WM (n=18). Levels of 72 RNAs were higher in blood from patients with impaired WM, 11 of which have proven links to the maintenance of different aspects of working memory (cognition). Overall, changed gene expression in those with impaired WM could be linked to cognition through glutamatergic activity, olfaction, immunity, inflammation as well as energy and metabolism. Our data gives preliminary support to the hypotheses that there is a working memory deficit phenotype within the syndrome of schizophrenia with has a biological underpinning. In addition, our data raises the possibility that a larger study could show that the specific changes in gene expression we have identified could prove to be the biomarkers needed to develop a blood test to identify those with impaired WM; a significant step toward allowing the use of personalised medicine directed toward improving their impaired working memory.

What genes are differentially expressed in individuals with schizophrenia? A systematic review

Schizophrenia is a severe, complex mental disorder characterized by a combination of positive symptoms, negative symptoms, and impaired cognitive function. Schizophrenia is highly heritable (~80%) with multifactorial etiology and complex polygenic genetic architecture. Despite the large number of genetic variants associated with schizophrenia, few causal variants have been established. Gaining insight into the mechanistic influences of these genetic variants may facilitate our ability to apply these findings to prevention and treatment. Though there have been more than 300 studies of gene expression in schizophrenia over the past 15 years, none of the studies have yielded consistent evidence for specific genes that contribute to schizophrenia risk. The aim of this work is to conduct a systematic review and synthesis of case-control studies of genome-wide gene expression in schizophrenia. Comprehensive literature searches were completed in PubMed, EmBase, and Web of Science, and after a systematic review of the studies, data were extracted from those that met the following inclusion criteria: human case-control studies comparing the genome-wide transcriptome of individuals diagnosed with schizophrenia to healthy controls published between January 1, 2000 and June 30, 2020 in the English language. Genes differentially expressed in cases were extracted from these studies, and overlapping genes were compared to previous research findings from the genome-wide association, structural variation, and tissue-expression studies. The transcriptome-wide analysis identified different genes than those previously reported in genome-wide association, exome sequencing, and structural variation studies of schizophrenia. Only one gene, GBP2, was replicated in five studies. Previous work has shown that this gene may play a role in immune function in the etiology of schizophrenia, which in turn could have implications for risk profiling, prevention, and treatment. This review highlights the methodological inconsistencies that impede valid meta-analyses and synthesis across studies. Standardization of the use of covariates, gene nomenclature, and methods for reporting results could enhance our understanding of the potential mechanisms through which genes exert their influence on the etiology of schizophrenia. Although these results are promising, collaborative efforts with harmonization of methodology will facilitate the identification of the role of genes underlying schizophrenia.

Schizophrenia spectrum and other psychotic disorders

Since its earliest conceptualization, schizophrenia has been considered a disorder of "young men." Contemporary research suggests that there are sex differences in schizophrenia that are both transdiagnostic and representative of general sex/gender differences across the psychopathology spectrum. This chapter selectively summarizes representative sex/gender differences in clinical expression, epidemiology, risk factors, treatment, as well as course and outcome in schizophrenia. The consistent sex differences found, such as onset age, generic brain anomalies, and hormonal involvement, are not specific to schizophrenia or necessarily to psychopathology. It is suggested that in working with those diagnosed as meeting the current criteria for schizophrenia, clinicians adopt a transdiagnostic framework informed by sex and gender role processes.

Potentially repurposable drugs for schizophrenia identified from its interactome

We previously presented the protein-protein interaction network of schizophrenia associated genes, and from it, the drug-protein interactome which showed the drugs that target any of the proteins in the interactome. Here, we studied these drugs further to identify whether any of them may potentially be repurposable for schizophrenia. In schizophrenia, gene expression has been described as a measurable aspect of the disease reflecting the action of risk genes. We studied each of the drugs from the interactome using the BaseSpace Correlation Engine, and shortlisted those that had a negative correlation with differential gene expression of schizophrenia. This analysis resulted in 12 drugs whose differential gene expression (drug versus normal) had an anti-correlation with differential expression for schizophrenia (disorder versus normal). Some of these drugs were already being tested for their clinical activity in schizophrenia and other neuropsychiatric disorders. Several proteins in the protein interactome of the targets of several of these drugs were associated with various neuropsychiatric disorders. The network of genes with opposite drug-induced versus schizophrenia-associated expression profiles were significantly enriched in pathways relevant to schizophrenia etiology and GWAS genes associated with traits or diseases that had a pathophysiological overlap with schizophrenia. Drugs that targeted the same genes as the shortlisted drugs, have also demonstrated clinical activity in schizophrenia and other related disorders. This integrated computational analysis will help translate insights from the schizophrenia drug-protein interactome to clinical research - an important step, especially in the field of psychiatric drug development which faces a high failure rate.

Shared co-expression networks in frontal cortex of the normal aged brain and schizophrenia

Previous studies on the brain of people with schizophrenia have identified structural changes and gene expression changes, suggesting that brain aging maybe accelerated in people with schizophrenia. To better characterize gene expression profiles in schizophrenia and in the aged population we constructed co-expression networks using RNA-Seq data from frontal cortex. The first data set analysed was from 62 subjects with schizophrenia and 51 unaffected controls ranging in age from 19 to 63 years. The second separate data set was from normal control individuals ranging in age from 29 to 106 years. In the first data set, we found two co-expression modules significantly associated with schizophrenia. One was a downregulated co-expression module enriched for neuron function related genes and the other was an upregulated immune/inflammation-related module. In the second data set of normal individuals, we found seven co-expression modules significantly correlated with age. A comparison of the co-expression modules from the two data sets revealed a significant consensus in nodes associated with schizophrenia and those associated with normal aging. The results indicate that a co-expression module related to neuronal function is downregulated and an immune/inflammation related co-expression module is upregulated, and associated with cells of the blood vessels, in both schizophrenia and in normal aging. This finding adds further support to the hypothesis that there may be accelerated brain aging in schizophrenia.

Association of functional polymorphisms in 3'-untranslated regions of COMT, DISC1, and DTNBP1 with schizophrenia: a meta-analysis

INTRODUCTION

In recent years, various studies have accumulated evidence of the involvement of single nucleotide polymorphisms (SNPs) in introns and exons in schizophrenia. The association of functional SNPs in the 3'-untranslated regions with schizophrenia has been explored in a number of studies, but the results are inconclusive because of limited meta-analyses. To systematically analyze the association between SNPs in 3'-untranslated regions and schizophrenia, we conducted a meta-analysis by combining all available studies on schizophrenia candidate genes.

MATERIALS AND METHODS

We searched candidate genes from the schizophrenia database and performed a comprehensive meta-analysis using all the available data up to August 2017. The association between susceptible SNPs and schizophrenia was assessed by the pooled odds ratio with 95% confidence interval using fixed-effect and random-effect models.

RESULTS

A total of 21 studies including 8291 cases and 9638 controls were used for meta-analysis. Three investigated SNPs were rs165599, rs3737597, and rs1047631 of COMT, DISC1, and DTNBP1, respectively. Our results suggested that rs3737597 showed a significant association with schizophrenia in Europeans (odds ratio: 1.584, P: 0.002, 95% confidence interval: 1.176-2.134) under a random-effect framework.

CONCLUSION

This meta-analysis indicated that rs3737597 of DISC1 was significantly associated with schizophrenia in Europeans, and it can be suggested as an ethnic-specific risk genetic factor.

Can Peripheral Blood-Derived Gene Expressions Characterize Individuals at Ultra-high Risk for Psychosis?

The ultra-high risk (UHR) state was originally conceived to identify individuals at imminent risk of developing psychosis. Although recent studies have suggested that most individuals designated UHR do not, they constitute a distinctive group, exhibiting cognitive and functional impairments alongside multiple psychiatric morbidities. UHR characterization using molecular markers may improve understanding, provide novel insight into pathophysiology, and perhaps improve psychosis prediction reliability. Whole-blood gene expressions from 56 UHR subjects and 28 healthy controls are checked for existence of a consistent gene expression profile (signature) underlying UHR, across a variety of normalization and heterogeneity-removal techniques, including simple log-conversion, quantile normalization, gene fuzzy scoring (GFS), and surrogate variable analysis. During functional analysis, consistent and reproducible identification of important genes depends largely on how data are normalized. Normalization techniques that address sample heterogeneity are superior. The best performer, the unsupervised GFS, produced a strong and concise 12-gene signature, enriched for psychosis-associated genes. Importantly, when applied on random subsets of data, classifiers built with GFS are "meaningful" in the sense that the classifier models built using genes selected after other forms of normalization do not outperform random ones, but GFS-derived classifiers do. Data normalization can present highly disparate interpretations on biological data. Comparative analysis has shown that GFS is efficient at preserving signals while eliminating noise. Using this, we demonstrate confidently that the UHR designation is well correlated with a distinct blood-based gene signature.

Attempts to replicate genetic associations with schizophrenia in a cohort from north India

Schizophrenia is a chronic, severe, heritable disorder. Genome-wide association studies, conducted predominantly among Caucasians, have indicated > 100 risk alleles, with most significant SNPs on chromosome 6. There is growing interest as to whether these risk alleles are relevant in other ethnic groups as well. Neither an Indian genome-wide association studies nor a systematic replication of GWAS findings from other populations are reported. Thus, we analyzed 32 SNPs, including those associated in the Caucasian ancestry GWAS and other candidate gene studies, in a north Indian schizophrenia cohort (n = 1009 patients; n = 1029 controls) using a Sequenom mass array. Cognitive functioning was also assessed using the Hindi version of the Penn Computerized Neuropsychological Battery in a subset of the sample. MICB (rs6916394) a previously noted Caucasian candidate, was associated with schizophrenia at the p = 0.02 level. One SNP, rs2064430, AHI1 (6q23.3, SZ Gene database SNP) was associated at the p = 0.04 level. Other candidates had even less significance with rs6932590, intergenic (p = 0.07); rs3130615, MICB (p = 0.08); rs6916921, NFKBIL1 (p = 0.08) and rs9273012, HLA-DQA1 (p = 0.06) and haplotypic associations (p = 0.01-0.05) of 6p SNPs were detected. Of note, nominally significant associations with cognitive variables were identified, after covarying for age and diagnostic status. SNPs with p < 0.01 were: rs3130375, with working memory (p = 0.007); rs377763, with sensorimotor (p = 0.004); rs6916921, NFKBIL1 with emotion (p = 0.01). This relative lack of significant positive associations is likely influenced by the sample size and/or differences in the genetic architecture of schizophrenia across populations, encouraging population specific studies to identify shared and unique genetic risk factors for schizophrenia.

POPULATION GENETICS

CAUCASIANS AND INDIANS EXHIBIT GENETIC DISJUNCTION IN SCHIZOPHRENIA: A tenuous link between schizophrenia's genetic basis in Caucasians and Indians calls for more comprehensive research on the latter. Large-scale analyses of the human genome have identified over a hundred genetic variations associated with schizophrenia; however, these have focused largely on European and North American populations. Researchers led by the University of Delhi's BK Thelma, and Smita Deshpande of the Dr. Ram Manohar Lohia Hospital, India, selected 32 gene variations from past studies to look for similar associations in Indians. Many assays met limited success, though the team found significant correlations between certain variations and specific cognitive hallmarks of schizophrenia. Aside from differences in genetic architecture, the lack of adequate and comparable genetic data on schizophrenia in Indians may contribute to this apparent difference to schizophrenia in Caucasian patients. This shows a clear need for more schizophrenia genetic studies in India.

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.

Systematic Integration of Brain eQTL and GWAS Identifies ZNF323 as a Novel Schizophrenia Risk Gene and Suggests Recent Positive Selection Based on Compensatory Advantage on Pulmonary Function

Genome-wide association studies have identified multiple risk variants and loci that show robust association with schizophrenia. Nevertheless, it remains unclear how these variants confer risk to schizophrenia. In addition, the driving force that maintains the schizophrenia risk variants in human gene pool is poorly understood. To investigate whether expression-associated genetic variants contribute to schizophrenia susceptibility, we systematically integrated brain expression quantitative trait loci and genome-wide association data of schizophrenia using Sherlock, a Bayesian statistical framework. Our analyses identified ZNF323 as a schizophrenia risk gene (P = 2.22×10(-6)). Subsequent analyses confirmed the association of the ZNF323 and its expression-associated single nucleotide polymorphism rs1150711 in independent samples (gene-expression: P = 1.40×10(-6); single-marker meta-analysis in the combined discovery and replication sample comprising 44123 individuals: P = 6.85×10(-10)). We found that the ZNF323 was significantly downregulated in hippocampus and frontal cortex of schizophrenia patients (P = .0038 and P = .0233, respectively). Evidence for pleiotropic effects was detected (association of rs1150711 with lung function and gene expression of ZNF323 in lung: P = 6.62×10(-5) and P = 9.00×10(-5), respectively) with the risk allele (T allele) for schizophrenia acting as protective allele for lung function. Subsequent population genetics analyses suggest that the risk allele (T) of rs1150711 might have undergone recent positive selection in human population. Our findings suggest that the ZNF323 is a schizophrenia susceptibility gene whose expression may influence schizophrenia risk. Our study also illustrates a possible mechanism for maintaining schizophrenia risk variants in the human gene pool.

Genetic relationships between schizophrenia, bipolar disorder, and schizoaffective disorder

There is substantial evidence for partial overlap of genetic influences on schizophrenia and bipolar disorder, with family, twin, and adoption studies showing a genetic correlation between the disorders of around 0.6. Results of genome-wide association studies are consistent with commonly occurring genetic risk variants, contributing to both the shared and nonshared aspects, while studies of large, rare chromosomal structural variants, particularly copy number variants, show a stronger influence on schizophrenia than bipolar disorder to date. Schizoaffective disorder has been less investigated but shows substantial familial overlap with both schizophrenia and bipolar disorder. A twin analysis is consistent with genetic influences on schizoaffective episodes being entirely shared with genetic influences on schizophrenic and manic episodes, while association studies suggest the possibility of some relatively specific genetic influences on broadly defined schizoaffective disorder, bipolar subtype. Further insights into genetic relationships between these disorders are expected as studies continue to increase in sample size and in technical and analytical sophistication, information on phenotypes beyond clinical diagnoses are increasingly incorporated, and approaches such as next-generation sequencing identify additional types of genetic risk variant.

Sexually selected traits: a fundamental framework for studies on behavioral epigenetics

Emerging evidence suggests that epigenetic-based mechanisms contribute to various aspects of sex differences in brain and behavior. The major obstacle in establishing and fully understanding this linkage is identifying the traits that are most susceptible to epigenetic modification. We have proposed that sexual selection provides a conceptual framework for identifying such traits. These are traits involved in intrasexual competition for mates and intersexual choice of mating partners and generally entail a combination of male-male competition and female choice. These behaviors are programmed during early embryonic and postnatal development, particularly during the transition from the juvenile to adult periods, by exposure of the brain to steroid hormones, including estradiol and testosterone. We evaluate the evidence that endocrine-disrupting compounds, including bisphenol A, can interfere with the vital epigenetic and gene expression pathways and with the elaboration of sexually selected traits with epigenetic mechanisms presumably governing the expression of these traits. Finally, we review the evidence to suggest that these steroid hormones can induce a variety of epigenetic changes in the brain, including the extent of DNA methylation, histone protein alterations, and even alterations of noncoding RNA, and that many of the changes differ between males and females. Although much previous attention has focused on primary sex differences in reproductive behaviors, such as male mounting and female lordosis, we outline why secondary sex differences related to competition and mate choice might also trace their origins back to steroid-induced epigenetic programming in disparate regions of the brain.

22q11 deletion syndrome: a review of the neuropsychiatric features and their neurobiological basis

The 22q11.2 deletion syndrome (22q11DS) is caused by an autosomal dominant microdeletion of chromosome 22 at the long arm (q) 11.2 band. The 22q11DS is among the most clinically variable syndromes, with more than 180 features related with the deletion, and is associated with an increased risk of psychiatric disorders, accounting for up to 1%-2% of schizophrenia cases. In recent years, several genes located on chromosome 22q11 have been linked to schizophrenia, including those encoding catechol-O-methyltransferase and proline dehydrogenase, and the interaction between these and other candidate genes in the deleted region is an important area of research. It has been suggested that haploinsufficiency of some genes within the 22q11.2 region may contribute to the characteristic psychiatric phenotype and cognitive functioning of schizophrenia. Moreover, an extensive literature on neuroimaging shows reductions of the volumes of both gray and white matter, and these findings suggest that this reduction may be predictive of increased risk of prodromal psychotic symptoms in 22q11DS patients. Experimental and standardized cognitive assessments alongside neuroimaging may be important to identify one or more endophenotypes of schizophrenia, as well as a predictive prodrome that can be preventively treated during childhood and adolescence. In this review, we summarize recent data about the 22q11DS, in particular those addressing the neuropsychiatric and cognitive phenotypes associated with the deletion, underlining the recent advances in the studies about the genetic architecture of the syndrome.

A combined analysis of microarray gene expression studies of the human prefrontal cortex identifies genes implicated in schizophrenia

Small cohort sizes and modest levels of gene expression changes in brain tissue have plagued the statistical approaches employed in microarray studies investigating the mechanism of schizophrenia. To combat these problems a combined analysis of six prior microarray studies was performed to facilitate the robust statistical analysis of gene expression data from the dorsolateral prefrontal cortex of 107 patients with schizophrenia and 118 healthy subjects. Multivariate permutation tests identified 144 genes that were differentially expressed between schizophrenia and control groups. Seventy of these genes were identified as differentially expressed in at least one component microarray study but none of these individual studies had the power to identify the remaining 74 genes, demonstrating the utility of a combined approach. Gene ontology terms and biological pathways that were significantly enriched for differentially expressed genes were related to neuronal cell-cell signaling, mesenchymal induction, and mitogen-activated protein kinase signaling, which have all previously been associated with the etiopathogenesis of schizophrenia. The differential expression of BAG3, C4B, EGR1, MT1X, NEUROD6, SST and S100A8 was confirmed by real-time quantitative PCR in an independent cohort using postmortem human prefrontal cortex samples. Comparison of gene expression between schizophrenic subjects with and without detectable levels of antipsychotics in their blood suggests that the modulation of MT1X and S100A8 may be the result of drug exposure. In conclusion, this combined analysis has resulted in a statistically robust identification of genes whose dysregulation may contribute to the mechanism of schizophrenia.

New frontiers in animal research of psychiatric illness

Alterations in neurodevelopment are thought to modify risk of numerous psychiatric disorders, including schizophrenia, autism, ADHD, mood and anxiety disorders, and substance abuse. However, little is known about the cellular and molecular changes that guide these neurodevelopmental changes and how they contribute to mental illness. In this review, we suggest that elucidating this process in humans requires the use of model organisms. Furthermore, we advocate that such translational work should focus on the role that genes and/or environmental factors play in the development of circuits that regulate specific physiological and behavioral outcomes in adulthood. This emphasis on circuit development, as a fundamental unit for understanding behavior, is distinct from current approaches of modeling psychiatric illnesses in animals in two important ways. First, it proposes to replace the diagnostic and statistical manual of mental disorders (DSM) diagnostic system with measurable endophenotypes as the basis for modeling human psychopathology in animals. We argue that a major difficulty in establishing valid animal models lies in their reliance on the DSM/International Classification of Diseases conceptual framework, and suggest that the Research Domain Criteria project, recently proposed by the NIMH, provides a more suitable system to model human psychopathology in animals. Second, this proposal emphasizes the developmental origin of many (though clearly not all) psychiatric illnesses, an issue that is often glossed over in current animal models of mental illness. We suggest that animal models are essential to elucidate the mechanisms by which neurodevelopmental changes program complex behavior in adulthood. A better understanding of this issue, in animals, is the key for defining human psychopathology, and the development of earlier and more effective interventions for mental illness.

RT-qPCR study on post-mortem brain samples from patients with major psychiatric disorders: reference genes and specimen characteristics

BACKGROUND

Gene expression studies conducted in post-mortem human brain samples have the potential to identify relevant genes implicated in psychiatric disorders. Although reverse transcription quantitative real-time PCR (RT-qPCR) has emerged as the method of choice for specific gene expression studies, it requires the use of stable reference genes, and it is necessary to control for pre- and post-mortem factors to obtain reliable data.

OBJECTIVE

The aim of this study was to identify suitable reference genes and specimen characteristics that can be taken into account when comparing mRNA expression data between post-mortem brain specimens from psychiatric patients and controls.

METHOD

We used a selection of suitably matched occipital cortex specimens from subjects in each of the following groups: schizophrenia (N = 15), bipolar disorder (N = 13), major depressive disorder (N = 15), and control (N = 15). Quantitative and qualitative RNA analyses were performed prior to RT-qPCR and gene expression stability was evaluated with geNorm and NormFinder.

RESULTS

We identified GAPDH, RPS17, RPL30, RPLP0, and TFRC as potential reference genes from a sample plate containing 32 candidates commonly used as reference genes. Further analyses of these 5 genes highlighted that 1) they are suitable reference genes for RT-qPCR studies in these post-mortem brain samples from psychiatric patients, and 2) the RNA quality index is highly correlated with gene expression values (r = -0.681, p < 0.0001).

CONCLUSIONS

In addition to controlling for pre- and post-mortem factors and selecting stable reference genes for normalization, sample sets should be matched with regard to RNA quality.

Personalized medicine: progress and promise

Personalized medicine is a broad and rapidly advancing field of health care that is informed by each person's unique clinical, genetic, genomic, and environmental information. Personalized medicine depends on multidisciplinary health care teams and integrated technologies (e.g., clinical decision support) to utilize our molecular understanding of disease in order to optimize preventive health care strategies. Human genome information now allows providers to create optimized care plans at every stage of a disease, shifting the focus from reactive to preventive health care. The further integration of personalized medicine into the clinical workflow requires overcoming several barriers in education, accessibility, regulation, and reimbursement. This review focuses on providing a comprehensive understanding of personalized medicine, from scientific discovery at the laboratory bench to integration of these novel ways of understanding human biology at the bedside.

Genome-wide analysis shows increased frequency of copy number variation deletions in Dutch schizophrenia patients

BACKGROUND

Since 2008, multiple studies have reported on copy number variations (CNVs) in schizophrenia. However, many regions are unique events with minimal overlap between studies. This makes it difficult to gain a comprehensive overview of all CNVs involved in the etiology of schizophrenia. We performed a systematic CNV study on the basis of a homogeneous genome-wide dataset aiming at all CNVs ≥ 50 kilobase pair. We complemented this analysis with a review of cytogenetic and chromosomal abnormalities for schizophrenia reported in the literature with the purpose of combining classical genetic findings and our current understanding of genomic variation.

METHODS

We investigated 834 Dutch schizophrenia patients and 672 Dutch control subjects. The CNVs were included if they were detected by QuantiSNP (http://www.well.ox.ac.uk/QuantiSNP/) as well as PennCNV (http://www.neurogenome.org/cnv/penncnv/) and contain known protein coding genes. The integrated identification of CNV regions and cytogenetic loci indicates regions of interest (cytogenetic regions of interest [CROIs]).

RESULTS

In total, 2437 CNVs were identified with an average number of 2.1 CNVs/subject for both cases and control subjects. We observed significantly more deletions but not duplications in schizophrenia cases versus control subjects. The CNVs identified coincide with loci previously reported in the literature, confirming well-established schizophrenia CROIs 1q42 and 22q11.2 as well as indicating a potentially novel CROI on chromosome 5q35.1.

CONCLUSIONS

Chromosomal deletions are more prevalent in schizophrenia patients than in healthy subjects and therefore confer a risk factor for pathogenicity. The combination of our CNV data with previously reported cytogenetic abnormalities in schizophrenia provides an overview of potentially interesting regions for positional candidate genes.

Characterizing brain cortical plasticity and network dynamics across the age-span in health and disease with TMS-EEG and TMS-fMRI

Brain plasticity can be conceptualized as nature's invention to overcome limitations of the genome and adapt to a rapidly changing environment. As such, plasticity is an intrinsic property of the brain across the lifespan. However, mechanisms of plasticity may vary with age. The combination of transcranial magnetic stimulation (TMS) with electroencephalography (EEG) or functional magnetic resonance imaging (fMRI) enables clinicians and researchers to directly study local and network cortical plasticity, in humans in vivo, and characterize their changes across the age-span. Parallel, translational studies in animals can provide mechanistic insights. Here, we argue that, for each individual, the efficiency of neuronal plasticity declines throughout the age-span and may do so more or less prominently depending on variable 'starting-points' and different 'slopes of change' defined by genetic, biological, and environmental factors. Furthermore, aberrant, excessive, insufficient, or mistimed plasticity may represent the proximal pathogenic cause of neurodevelopmental and neurodegenerative disorders such as autism spectrum disorders or Alzheimer's disease.

Identification of a functional rare variant in autism using genome-wide screen for monoallelic expression

Recent work has led to the identification of several susceptibility genes for autism spectrum disorder (ASD) and an increased appreciation of the importance of rare and de novo mutations. Some of the mutations may be very hard to detect using current strategies, especially if they are located in regulatory regions. We present a new approach to identify functional mutations that exploit the fact that many rare mutations disrupt the expression of genes from a single parental chromosome. The method incorporates measurement of the relative expression of the two copies of a gene across the genome using single nucleotide polymorphism arrays. Allelic expression has been successfully used to study common regulatory polymorphisms; however, it has not been implemented as a screening tool for rare mutation. We tested the potential of this approach by screening for monoallelic expression in lymphoblastoid cell lines derived from a small ASD cohort. After filtering regions shared across multiple samples, we identified genes showing monoallelic expression in specific ASD samples. Validation by quantitative sequencing demonstrated that the genes (or only part of them) are monoallelic expressed. The genes included both previously suspected risk factors for ASD and novel candidates. In one gene, named autism susceptibility candidate 2 (AUTS2), we identified a rare duplication that is likely to be the cause of monoallelic expression. Our results demonstrate the ability to identify rare regulatory mutations using genome-wide allelic expression screens, capabilities that could be expanded to other diseases, especially those with suspected involvement of rare dominantly acting mutations.

Modulating Gene Expression through Psychotherapy: The Contribution of Noninvasive Somatic Interventions

Mapping the relationship between gene expression and psychopathology is proving to be among the most promising new frontiers for advancing the understanding, treatment, and prevention of mental disorders. Each cell in the human body contains some 23,688 genes, yet only a tiny fraction of a cell's genes are active or “expressed” at any given moment. The interactions of biochemical, psychological, and environmental factors influencing gene expression are complex yet relatively accessible technologies for assessing gene expression have allowed the identification of specific genes implicated in a range of psychiatric disorders, including depression, anxiety, and schizophrenia. Moreover, successful psychotherapeutic interventions have been shown to shift patterns of gene expression. Five areas of biological change in successful psychotherapy that are dependent upon precise shifts in gene expression are identified in this article. Psychotherapy ameliorates (a) exaggerated limbic system responses to innocuous stimuli, (b) distortions in learning and memory, (c) imbalances between sympathetic and parasympathetic nervous system activity, (d) elevated levels of cortisol and other stress hormones, and (e) impaired immune functioning. The thesis of this article is that psychotherapies that utilize noninvasive somatic interventions may yield greater precision and power in bringing about therapeutically beneficial shifts in gene expression that control these biological markers. The article examines the manual stimulation of acupuncture points during psychological exposure as an example of such a somatic intervention. For each of the five areas, a testable proposition is presented to encourage research that compares acupoint protocols with conventional therapies in catalyzing advantageous shifts in gene expression.

MicroRNA expression profiling in the prefrontal cortex of individuals affected with schizophrenia and bipolar disorders

MicroRNAs (miRNAs) are a large family of small non-coding RNAs which negatively control gene expression at both the mRNA and protein levels. The number of miRNAs identified is growing rapidly and approximately one-third is expressed in the brain where they have been shown to affect neuronal differentiation, synaptosomal complex localization and synapse plasticity, all functions thought to be disrupted in schizophrenia. Here we investigated the expression of 667 miRNAs (miRBase v.13) in the prefrontal cortex of individuals with schizophrenia (SZ, N = 35) and bipolar disorder (BP, N = 35) using a real-time PCR-based Taqman Low Density Array (TLDA). After extensive QC steps, 441 miRNAs were included in the final analyses. At a FDR of 10%, 22 miRNAs were identified as being differentially expressed between cases and controls, 7 dysregulated in SZ and 15 in BP. Using in silico target gene prediction programs, the 22miRNAs were found to target brain specific genes contained within networks overrepresented for neurodevelopment, behavior, and SZ and BP disease development. In an initial attempt to corroborate some of these predictions, we investigated the extent of correlation between the expressions of hsa-mir-34a, -132 and -212 and their predicted gene targets. mRNA expression of tyrosine hydroxylase (TH), phosphogluconate dehydrogenase (PGD) and metabotropic glutamate receptor 3 (GRM3) was measured in the SMRI sample. Hsa-miR-132 and -212 were negatively correlated with TH (p = 0.0001 and 0.0017) and with PGD (p = 0.0054 and 0.017, respectively).

Evidence for cis-acting regulation of ANK3 and CACNA1C gene expression

OBJECTIVES

Genome-wide association studies (GWAS) have identified Ankyrin-G (ANK3) and the alpha-1C subunit of the L-type voltage-gated calcium channel (CACNA1C) as susceptibility genes for bipolar disorder. Available biological information on these genes suggests a potential molecular mechanism involving ion channel dysfunction. The associated single nucleotide polymorphisms (SNPs) at ANK3 (rs10994336) and CACNA1C (rs1006737) are both intronic with no obvious impact on gene function. We investigated whether, instead of affecting protein function, these risk variants might impact on gene regulation affecting expression.

METHODS

We have done this by testing for allelic expression imbalance (AEI) to identify cis-acting regulatory polymorphisms.

RESULTS

We identified evidence of cis-acting variation at both loci in HapMap Caucasian Europeans from Utah (CEU) lymphoblastoid cell lines. There was considerable evidence of AEI at ANK3 with more than half of all heterozygous samples (21 out of 34) for marker SNP rs3750800 showing AEI and a small number of samples showing near monoallelic expression. The AEI at either gene could not be attributed to the GWAS-associated SNPs.

CONCLUSIONS

These data indicate that there is genetic variation local to both genes affecting their expression, but that this variation is not responsible for increasing risk of bipolar disorder.

New Genetic Findings in Schizophrenia: Is there Still Room for the Dopamine Hypothesis of Schizophrenia?

Schizophrenia is a highly heritable disorder, but the identification of specific genes has proven to be a difficult endeavor. Genes involved in the dopaminergic system are considered to be major candidates since the “dopamine hypothesis” of impairment in dopaminergic neurotransmission is one of the most widely accepted hypotheses of the etiology of schizophrenia. The overall findings from candidate studies do provide some support for the “dopamine hypothesis.” However, results from the first systematic genome-wide association (GWA) studies have implicated variants within ZNF804A, NRGN, TCF4, and variants in the MHC region on chromosome 6p22.1. Although these genes may not immediately impact on dopaminergic neurotransmission, it remains possible that downstream impairments in dopaminergic function are caused. Furthermore, only a very small fraction of all truly associated genetic variants have been detected and many more associated variants will be identified in the future by GWA studies and alternative approaches. The results of these studies may allow a more comprehensive re-evaluation of the dopamine hypothesis.

An integrated genomic analysis of gene-function correlation on schizophrenia susceptibility genes

Schizophrenia is a highly complex inheritable disease characterized by numerous genetic susceptibility elements, each contributing a modest increase in risk for the disease. Although numerous linkage or association studies have identified a large set of schizophrenia-associated loci, many are controversial. In addition, only a small portion of these loci overlaps with the large cumulative pool of genes that have shown changes of expression in schizophrenia. Here, we applied a genomic gene-function approach to identify susceptibility loci that show direct effect on gene expression, leading to functional abnormalities in schizophrenia. We carried out an integrated analysis by cross-examination of the literature-based susceptibility loci with the schizophrenia-associated expression gene list obtained from our previous microarray study (Journal of Human Genetics (2009) 54: 665-75) using bioinformatic tools, followed by confirmation of gene expression changes using qPCR. We found nine genes (CHGB, SLC18A2, SLC25A27, ESD, C4A/C4B, TCP1, CHL1 and CTNNA2) demonstrate gene-function correlation involving: synapse and neurotransmission; energy metabolism and defense mechanisms; and molecular chaperone and cytoskeleton. Our findings further support the roles of these genes in genetic influence and functional consequences on the development of schizophrenia. It is interesting to note that four of the nine genes are located on chromosome 6, suggesting a special chromosomal vulnerability in schizophrenia.

A novel microRNA and transcription factor mediated regulatory network in schizophrenia

Background

Schizophrenia is a complex brain disorder with molecular mechanisms that have yet to be elucidated. Previous studies have suggested that changes in gene expression may play an important role in the etiology of schizophrenia, and that microRNAs (miRNAs) and transcription factors (TFs) are primary regulators of this gene expression. So far, several miRNA-TF mediated regulatory modules have been verified. We hypothesized that miRNAs and TFs might play combinatory regulatory roles for schizophrenia genes and, thus, explored miRNA-TF regulatory networks in schizophrenia.

Results

We identified 32 feed-forward loops (FFLs) among our compiled schizophrenia-related miRNAs, TFs and genes. Our evaluation revealed that these observed FFLs were significantly enriched in schizophrenia genes. By converging the FFLs and mutual feedback loops, we constructed a novel miRNA-TF regulatory network for schizophrenia. Our analysis revealed EGR3 and hsa-miR-195 were core regulators in this regulatory network. We next proposed a model highlighting EGR3 and miRNAs involved in signaling pathways and regulatory networks in the nervous system. Finally, we suggested several single nucleotide polymorphisms (SNPs) located on miRNAs, their target sites, and TFBSs, which may have an effect in schizophrenia gene regulation.

Conclusions

This study provides many insights on the regulatory mechanisms of genes involved in schizophrenia. It represents the first investigation of a miRNA-TF regulatory network for a complex disease, as demonstrated in schizophrenia.

Recent advances in the genetics of obsessive-compulsive disorder

This article reviews recent developments in understanding the genetic etiology of obsessive-compulsive disorder (OCD). Family studies provide further support for the familial aggregation of OCD. Genome-wide linkage studies indicate that specific chromosomal regions are linked to OCD. Moreover, results from recent molecular genetic studies suggest that several candidate genes are associated with OCD. However, specific genes causing OCD have not been conclusively identified, and the molecular pathogenesis of the disorder has not been elucidated. The search for genes is complicated by the clinical and etiologic heterogeneity of OCD, as well as the possibility of gene-gene and gene-environment interactions. Despite this complexity, further refinement of the phenotype and developments in molecular and statistical genetics hold promise for further deepening our genetic understanding of OCD in the future.

The DISC1 pathway modulates expression of neurodevelopmental, synaptogenic and sensory perception genes

BACKGROUND

Genetic and biological evidence supports a role for DISC1 across a spectrum of major mental illnesses, including schizophrenia and bipolar disorder. There is evidence for genetic interplay between variants in DISC1 and in biologically interacting loci in psychiatric illness. DISC1 also associates with normal variance in behavioral and brain imaging phenotypes.

METHODOLOGY

Here, we analyze public domain datasets and demonstrate correlations between variants in the DISC1 pathway genes and levels of gene expression. Genetic variants of DISC1, NDE1, PDE4B and PDE4D regulate the expression of cytoskeletal, synaptogenic, neurodevelopmental and sensory perception proteins. Interestingly, these regulated genes include existing targets for drug development in depression and psychosis.

CONCLUSIONS

Our systematic analysis provides further evidence for the relevance of the DISC1 pathway to major mental illness, identifies additional potential targets for therapeutic intervention and establishes a general strategy to mine public datasets for insights into disease pathways.

Recent advances in postmortem pathology and neurochemistry in schizophrenia

PURPOSE OF REVIEW

This is a review examining recent data from the study of the postmortem central nervous system (CNS) of patients with schizophrenia.

RECENT FINDINGS

Studies on the human CNS transcriptome suggest changes in pro-inflammatory pathways and myelination in schizophrenia, whereas changes in the proteome suggest that pathways involved in energy and metabolism may be particularly stressed. There appear to be complex changes in the expression of proposed candidate genes for schizophrenia such as NRG1, DISC1, RGS4 and DTNB1, and there are continued reports of alterations in central gamma-aminobutyric acidergic, dopaminergic, glutamatergic and cholinergic pathways in patients with the disorder. Data on epigenetic mechanisms and transcriptome regulation suggest that at least some changes in gene expression may be due to changes in levels of gene promoter methylation or microRNAs in the CNS of patients with schizophrenia.

SUMMARY

Postmortem CNS studies have begun to unravel changes in the epigenetic regulation of gene expression that may be central to how gene-environment interactions contribute to the onset of schizophrenia. In addition, a recent study indicates that it is possible to use biomarkers to segregate the syndrome of schizophrenia into more biologically homogeneous populations, which should decrease the biological complexity observed within that group within the schizophrenia syndrome.

Putative psychosis genes in the prefrontal cortex: combined analysis of gene expression microarrays

BACKGROUND

Recent studies have shown similarities between schizophrenia and bipolar disorder in phenotypes and in genotypes, and those studies have contributed to an ongoing re-evaluation of the traditional dichotomy between schizophrenia and bipolar disorder. Bipolar disorder with psychotic features may be closely related to schizophrenia and therefore, psychosis may be an alternative phenotype compared to the traditional diagnosis categories.

METHODS

We performed a cross-study analysis of 7 gene expression microarrays that include both psychosis and non-psychosis subjects. These studies include over 400 microarray samples (163 individual subjects) on 3 different Affymetrix microarray platforms.

RESULTS

We found that 110 transcripts are differentially regulated (p < 0.001) in psychosis after adjusting for confounding variables with a multiple regression model. Using a quantitative PCR, we validated a set of genes such as up-regulated metallothioneins (MT1E, MT1F, MT1H, MT1K, MT1X, MT2A and MT3) and down-regulated neuropeptides (SST, TAC1 and NPY) in the dorsolateral prefrontal cortex of psychosis patients.

CONCLUSION

This study demonstrates the advantages of cross-study analysis in detecting consensus changes in gene expression across multiple microarray studies. Differential gene expression between individuals with and without psychosis suggests that psychosis may be a useful phenotypic variable to complement the traditional diagnosis categories.