Schizophrenia genetics: where next?

Unlocking the Therapeutic Potential of Exosomes Derived From Nasal Olfactory Mucosal Mesenchymal Stem Cells: Restoring Synaptic Plasticity, Neurogenesis, and Neuroinflammation in Schizophrenia

BACKGROUND AND HYPOTHESIS

Schizophrenia (SCZ) is a multifaceted mental disorder marked by a spectrum of symptoms, including hallucinations, delusions, cognitive deficits, and negative symptoms. Its etiology involves intricate interactions between genetic and environmental factors, posing significant challenges for effective treatment. We hypothesized that intranasal administration of exosomes derived from nasal olfactory mucosal mesenchymal stem cells (OM-MSCs-exos) could alleviate SCZ-like behaviors in a murine model induced by methylazoxymethanol (MAM).

STUDY DESIGN

We conducted a comprehensive investigation to assess the impact of intranasally delivered OM-MSC-exos on SCZ-like behaviors in MAM-induced mice. This study encompassed behavioral assessments, neuroinflammatory markers, glial activation, synaptic protein expression, and neurogenesis within the hippocampus.

STUDY RESULTS

Our findings demonstrated that intranasal administration of OM-MSC-exos effectively ameliorated SCZ-like behaviors, specifically addressing social withdrawal and sensory gating deficits in the MAM-induced murine model. Furthermore, OM-MSC-exos intervention yielded a reduction in neuroinflammatory markers and a suppression of microglial activation within the hippocampus. Simultaneously, we observed an upregulation of key synaptic protein expression, including PSD95 and TH, the rate-limiting enzyme for dopamine biosynthesis.

CONCLUSIONS

Our study underscores the therapeutic potential of OM-MSC-exos in mitigating SCZ-like behavior. The OM-MSC-exos have the capacity to modulate glial cell activation, diminish neuroinflammation, and promote BDNF-associated synaptic plasticity and neurogenesis, thus ameliorating SCZ-like behaviors. In summary, intranasal administration of OM-MSC-exos offers a multifaceted approach to address SCZ mechanisms, promising innovative treatments for this intricate disorder.

Schizophrenia in the genetic era: a review from development history, clinical features and genomic research approaches to insights of susceptibility genes

Schizophrenia is a devastating neuropsychiatric disorder affecting 1% of the world population and ranks as one of the disorders providing the most severe burden for society. Schizophrenia etiology remains obscure involving multi-risk factors, such as genetic, environmental, nutritional, and developmental factors. Complex interactions of genetic and environmental factors have been implicated in the etiology of schizophrenia. This review provides an overview of the historical origins, pathophysiological mechanisms, diagnosis, clinical symptoms and corresponding treatment of schizophrenia. In addition, as schizophrenia is a polygenic, genetic disorder caused by the combined action of multiple micro-effective genes, we further detail several approaches, such as candidate gene association study (CGAS) and genome-wide association study (GWAS), which are commonly used in schizophrenia genomics studies. A number of GWASs about schizophrenia have been performed with the hope to identify novel, consistent and influential risk genetic factors. Finally, some schizophrenia susceptibility genes have been identified and reported in recent years and their biological functions are also listed. This review may serve as a summary of past research on schizophrenia genomics and susceptibility genes (NRG1, DISC1, RELN, BDNF, MSI2), which may point the way to future schizophrenia genetics research. In addition, depending on the above discovery of susceptibility genes and their exact function, the development and application of antipsychotic drugs will be promoted in the future.

Common and rare variant associations with latent traits underlying depression, bipolar disorder, and schizophrenia

Genetic studies in psychiatry have primarily focused on the effects of common genetic variants, but few have investigated the role of rare genetic variants, particularly for major depression. In order to explore the role of rare variants in the gap between estimates of single nucleotide polymorphism (SNP) heritability and twin study heritability, we examined the contribution of common and rare genetic variants to latent traits underlying psychiatric disorders using high-quality imputed genotype data from the UK Biobank. Using a pre-registered analysis, we used items from the UK Biobank Mental Health Questionnaire relevant to three psychiatric disorders: major depression (N = 134,463), bipolar disorder (N = 117,376) and schizophrenia (N = 130,013) and identified a general hierarchical factor for each that described participants' responses. We calculated participants' scores on these latent traits and conducted single-variant genetic association testing (MAF > 0.05%), gene-based burden testing and pathway association testing associations with these latent traits. We tested for enrichment of rare variants (MAF 0.05-1%) in genes that had been previously identified by common variant genome-wide association studies, and genes previously associated with Mendelian disorders having relevant symptoms. We found moderate genetic correlations between the latent traits in our study and case-control phenotypes in previous genome-wide association studies, and identified one common genetic variant (rs72657988, minor allele frequency = 8.23%, p = 1.01 × 10^-9) associated with the general factor of schizophrenia, but no other single variants, genes or pathways passed significance thresholds in this analysis, and we did not find enrichment in previously identified genes.

Identifying the Common Genetic Basis of Antidepressant Response

Background

Antidepressants are a first-line treatment for depression. However, only a third of individuals experience remission after the first treatment. Common genetic variation, in part, likely regulates antidepressant response, yet the success of previous genome-wide association studies has been limited by sample size. This study performs the largest genetic analysis of prospectively assessed antidepressant response in major depressive disorder to gain insight into the underlying biology and enable out-of-sample prediction.

Methods

Genome-wide analysis of remission (n remit = 1852, n nonremit = 3299) and percentage improvement (n = 5218) was performed. Single nucleotide polymorphism-based heritability was estimated using genome-wide complex trait analysis. Genetic covariance with eight mental health phenotypes was estimated using polygenic scores/AVENGEME. Out-of-sample prediction of antidepressant response polygenic scores was assessed. Gene-level association analysis was performed using MAGMA and transcriptome-wide association study. Tissue, pathway, and drug binding enrichment were estimated using MAGMA.

Results

Neither genome-wide association study identified genome-wide significant associations. Single nucleotide polymorphism-based heritability was significantly different from zero for remission (h 2 = 0.132, SE = 0.056) but not for percentage improvement (h 2 = -0.018, SE = 0.032). Better antidepressant response was negatively associated with genetic risk for schizophrenia and positively associated with genetic propensity for educational attainment. Leave-one-out validation of antidepressant response polygenic scores demonstrated significant evidence of out-of-sample prediction, though results varied in external cohorts. Gene-based analyses identified ETV4 and DHX8 as significantly associated with antidepressant response.

Conclusions

This study demonstrates that antidepressant response is influenced by common genetic variation, has a genetic overlap schizophrenia and educational attainment, and provides a useful resource for future research. Larger sample sizes are required to attain the potential of genetics for understanding and predicting antidepressant response.

Bioinformatics and Network-based Approaches for Determining Pathways, Signature Molecules, and Drug Substances connected to Genetic Basis of Schizophrenia etiology

Knowledge of heterogeneous etiology and pathophysiology of schizophrenia (SZP) is reasonably inadequate and non-deterministic due to its inherent complexity and underlying vast dynamics related to genetic mechanisms. The evolution of large-scale transcriptome-wide datasets and subsequent development of relevant, robust technologies for their analyses show promises toward elucidating the genetic basis of disease pathogenesis, its early risk prediction, and predicting drug molecule targets for therapeutic intervention. In this research, we have scrutinized the genetic basis of SZP through functional annotation and network-based system biology approaches. We have determined 96 overlapping differentially expressed genes (DEGs) from 2 microarray datasets and subsequently identified their interconnecting networks to reveal transcriptome signatures like hub proteins (FYN, RAD51, SOCS3, XIAP, AKAP13, PIK3C2A, CBX5, GATA3, EIF3K, and CDKN2B), transcription factors and miRNAs. In addition, we have employed gene set enrichment to highlight significant gene ontology (e.g., positive regulation of microglial cell activation) and relevant pathways (such as axon guidance and focal adhesion) interconnected to the genes associated with SZP. Finally, we have suggested candidate drug substances like Luteolin HL60 UP as a possible therapeutic target based on these key molecular signatures.

Polygenic association with severity and long-term outcome in eating disorder cases

About 20% of individuals with anorexia nervosa (AN) remain chronically ill. Therefore, early identification of poor outcome could improve care. Genetic research has identified regions of the genome associated with AN. Patients with anorexia nervosa were identified via the Swedish eating disorder quality registers Stepwise and Riksät and invited to participate in the Anorexia Nervosa Genetics Initiative. First, we associated genetic information longitudinally with eating disorder severity indexed by scores on the Clinical Impairment Assessment (CIA) in 2843 patients with lifetime AN with or without diagnostic migration to other forms of eating disorders followed for up to 16 years (mean = 5.3 years). Second, we indexed the development of a severe and enduring eating disorder (SEED) by a high CIA score plus a follow-up time ≥5 years. We associated individual polygenic scores (PGSs) indexing polygenic liability for AN, schizophrenia, and body mass index (BMI) with severity and SEED. After multiple testing correction, only the BMI PGS when calculated with traditional clumping and p value thresholding was robustly associated with disorder severity (β_PGS = 1.30; 95% CI: 0.72, 1.88; p = 1.2 × 10^-5) across all p value thresholds at which we generated the PGS. However, using the alternative PGS calculation method PRS-CS yielded inconsistent results for all PGS. The positive association stands in contrast to the negative genetic correlation between BMI and AN. Larger discovery GWASs to calculate PGS will increase power, and it is essential to increase sample sizes of the AN GWASs to generate clinically meaningful PGS as adjunct risk prediction variables. Nevertheless, this study provides the first evidence of potential clinical utility of PGSs for eating disorders.

Schizophrenia risk candidate protein ZNF804A interacts with STAT2 and influences interferon-mediated gene transcription in mammalian cells

Previously evidence was presented that the single-nucleotide polymorphism rs1344706 located in an intronic region of the ZNF804A gene is associated with reduced transcript levels in fetal brains. This genetic variation in the gene encoding the zinc-finger protein ZNF804A is associated with schizophrenia (SZ) and bipolar disorder. Currently, the molecular and cellular function of ZNF804A is unclear. Here, we generated a high-confidence protein-protein interaction (PPI) network for ZNF804A using a combination of yeast two-hybrid and bioluminescence-based PPI detection assays, directly linking 12 proteins to the disease-associated target protein. Among the top hits was the signal transducer and activator of transcription 2 (STAT2), an interferon-regulated transcription factor. Detailed mechanistic studies revealed that STAT2 binds to the unstructured N-terminus of ZNF804A. This interaction is mediated by multiple short amino acid motifs in ZNF804A but not by the conserved C2H2 zinc-finger domain, which is also located at the N-terminus. Interestingly, investigations in HEK293 cells demonstrated that ZNF804A and STAT2 both co-translocate from the cytoplasm into the nucleus upon interferon (IFN) treatment. Furthermore, a concentration-dependent effect of ZNF804A overproduction on STAT2-mediated gene expression was observed using a luciferase reporter, which is under the control of an IFN-stimulated response element (ISRE). Together these results indicate the formation of ZNF804A:STAT2 protein complex and its translocation from the cytoplasm into the nucleus upon IFN stimulation, suggesting that it may function as a signal transducer that activates IFN-mediated gene expression programs.

Decreased interhemispheric connectivity and increased cortical excitability in unmedicated schizophrenia: A prefrontal interleaved TMS fMRI study

BACKGROUND

Prefrontal abnormalities in schizophrenia have consistently emerged from resting state and cognitive neuroimaging studies. However, these correlative findings require causal verification via combined imaging/stimulation approaches. To date, no interleaved transcranial magnetic stimulation and functional magnetic resonance imaging study (TMS fMRI) has probed putative prefrontal cortex abnormalities in schizophrenia.

OBJECTIVE

/Hypothesis: We hypothesized that subjects with schizophrenia would show significant hyperexcitability at the site of stimulation (BA9) and decreased interhemispheric functional connectivity.

METHODS

We enrolled 19 unmedicated subjects with schizophrenia and 22 controls. All subjects underwent brain imaging using a 3T MRI scanner with a SENSE coil. They also underwent a single TMS fMRI session involving motor threshold (rMT) determination, structural imaging, and a parametric TMS fMRI protocol with 10 Hz triplet pulses at 0, 80, 100 and 120% rMT. Scanning involved a surface MR coil optimized for bilateral prefrontal cortex image acquisition.

RESULTS

Of the original 41 enrolled subjects, 8 subjects with schizophrenia and 11 controls met full criteria for final data analyses. At equal TMS intensity, subjects with schizophrenia showed hyperexcitability in left BA9 (p = 0.0157; max z-score = 4.7) and neighboring BA46 (p = 0.019; max z-score = 4.47). Controls showed more contralateral functional connectivity between left BA9 and right BA9 through increased activation in right BA9 (p = 0.02; max z-score = 3.4). GM density in subjects with schizophrenia positively correlated with normalized prefrontal to motor cortex ratio of the corresponding distance from skull to cortex ratio (S-BA9/S-MC) (r = 0.83, p = 0.004).

CONCLUSIONS

Subjects with schizophrenia showed hyperexcitability in left BA9 and impaired interhemispheric functional connectivity compared to controls. Interleaved TMS fMRI is a promising tool to investigate prefrontal dysfunction in schizophrenia.

Expression analysis and genotyping of DGKZ: a GWAS-derived risk gene for schizophrenia

Schizophrenia (SCZ) is a disabling and severe mental illness characterized by abnormal social behavior and disrupted emotions. Similar to other neuropsychological disorders, both genetics and environmental factors interplay so as to develop SCZ. It is acknowledged that genes such as DGKZ are involved in lipid signaling pathways that are the basis of neural activities, memory, and learning and are considered as candidate loci for SCZ. The aim of the present study was to evaluate the expression level and genotypes of DGKZ in patients with SCZ and controls. We used q-PCR to measure the relative expression of DGKZ in blood. To determine DGKZ-rs7951870 genotypes, tetra-ARMS PCR was used. Our results showed a significant difference in DGKZ mRNA ratio between SCZ patients and healthy controls (P = 2 × 10^-4). Also, we showed that rs7951870-TT genotype was strongly associated with increased DGKZ expression level (P = 0.038). In conclusion, our findings revealed dysregulation of DGKZ in SCZ patients and a significant correction between the gene expression and DGKZ variant rs7951870.

Female gender specific association of the Reelin (RELN) gene rs7341475 variant with schizophrenia

RELN gene encodes a large extracellular matrix protein which is critical for neuronal migration, cell positioning and cell-cell interactions. It also controls the synaptic plasticity of neurons for initiation and maintenance of long term potentiation. The aim of this study is to investigate the association of RELN rs7341475 variant with schizophrenia. Genomic DNA isolation was performed from 105 schizophrenic patients and 137 healthy controls to determine RELN rs7341475 genotypes. Genotype and allele frequencies were determined by a polymerase chain reaction-restriction fragment length polymorphism method developed in our laboratory. Statistical analysis was performed using χ² test. The frequencies for G allele were 79.5% in cases and 81.0% in controls, for A allele 20.5% in cases and 19.0% in controls in the overall population. The genotype frequencies of the RELN gene rs7341475 variant were GG; 63.8%, GA; 31.4% and AA; 4.8% in cases, GG; 63.5%, GA; 35.0% and AA; 1.5% in controls in the overall population. There was no statistically significant association between the rs7341475 variant of RELN gene and schizophrenia in the overall population (χ² = 2.473, p = 0.290). In the gender specific analysis, female gender specific association was only found. The RELN rs7341475 variant GG genotype was significantly associated with schizophrenia (p = 0.034, OR 2.760, 95% CI 1.058-7.197) and A allele was protective against schizophrenia (p = 0.034, OR 0.362, 95% CI 0.139-0.945). All cases and controls were in Hardy-Weinberg equilibrium (p > 0.05). Population size can be increased to improve the statistical power. Moreover, other RELN gene variants which are especially involved in neuronal migration and epigenetic regulation may be analyzed for revealing the complex genetic architecture of schizophrenia. In conclusion, there was only association between the RELN rs7341475 variant and schizophrenia in the female gender in a Turkish population.

Discovery of rare variants implicated in schizophrenia using next-generation sequencing

Schizophrenia is a highly heritable psychiatric disorder that affects 1% of the population. Genome-wide association studies have identified common variants in candidate genes associated with schizophrenia, but the genetics mechanisms of this disorder have not yet been elucidated. The discovery of rare genetic variants that contribute to schizophrenia symptoms promises to help explain the missing heritability of the disease. Next generation sequencing techniques are revolutionizing the field of psychiatric genetics. Various statistical approaches have been developed for rare variant association testing in case-control and family studies. Targeted resequencing, whole exome sequencing and whole genome sequencing combined with these computational tools are used for the discovery of rare genetic variations in schizophrenia. The findings provide useful information for characterizing the rare mutations and elucidating the genetic mechanisms by which the variants cause schizophrenia.

TPH2 polymorphisms across the spectrum of psychiatric morbidity: A systematic review and meta-analysis

Tryptophan hydroxylase 2 (TPH2) is the rate-limiting enzyme in brain serotonin synthesis. The TPH2 gene has frequently been investigated in relation to psychiatric morbidity. The aim of the present review is to integrate results from association studies between TPH2 single nucleotide polymorphisms (SNPs) and various psychiatric disorders, which we furthermore quantified with meta-analysis. We reviewed 166 studies investigating 69 TPH2 SNPs in a broad range of psychiatric disorders, including over 30,000 patients. According to our meta-analysis, TPH2 polymorphisms show strongest associations with mood disorders, suicide (attempt) and schizophrenia. Despite small effect sizes, we conclude that TPH2 SNPs in the coding and non-coding areas (rs4570625, rs11178997, rs11178998, rs10748185, rs1843809, rs4290270, rs17110747) are each associated with one or more psychopathological conditions. Our findings highlight the possible common serotonergic mechanisms of the investigated psychiatric disorders. Yet, the functional relevance of most TPH2 polymorphisms is unclear. Characterizing how exactly the different TPH2 variants influence the serotonergic neurotransmission is a next necessary step in understanding the psychiatric disorders where serotonin is implicated.

Method to estimate the approximate samples size that yield a certain number of significant GWAS signals in polygenic traits

To argue for increased sample collection for disorders without significant findings, researchers resorted to plotting, for multiple traits, the number of significant findings as a function of the sample size. However, for polygenic traits, the prevalence of the disorder confounds the relationship between the number of significant findings and the sample size. To adjust the number of significant findings for prevalence, we develop a method that uses the expected noncentrality of the contrast between liabilities of cases and controls. We empirically find that, when compared to the sample size, this measure is a better predictor of number of significant findings. Even more, we show that the sample size effect on the number of signals is explained by the noncentrality measure. Finally, we provide an R script to estimate the required sample size (noncentrality) needed to yield a prespecified number of significant findings, along with the converse.

Novel functional variants at the GWAS-implicated loci might confer risk to major depressive disorder, bipolar affective disorder and schizophrenia

BACKGROUND

A challenge of understanding the mechanisms underlying cognition including neurodevelopmental and neuropsychiatric disorders is mainly given by the potential severity of cognitive disorders for the quality of life and their prevalence. However, the field has been focused predominantly on protein coding variation until recently. Given the importance of tightly controlled gene expression for normal brain function, the goal of the study was to assess the functional variation including non-coding variation in human genome that is likely to play an important role in cognitive functions. To this end, we organized and utilized available genome-wide datasets from genomic, transcriptomic and association studies into a comprehensive data corpus. We focused on genomic regions that are enriched in regulatory activity-overlapping transcriptional factor binding regions and repurpose our data collection especially for identification of the regulatory SNPs (rSNPs) that showed associations both with allele-specific binding and allele-specific expression. We matched these rSNPs to the nearby and distant targeted genes and then selected the variants that could implicate the etiology of cognitive disorders according to Genome-Wide Association Studies (GWAS). Next, we use DeSeq 2.0 package to test the differences in the expression of the certain targeted genes between the controls and the patients that were diagnosed bipolar affective disorder and schizophrenia. Finally, we assess the potential biological role for identified drivers of cognition using DAVID and GeneMANIA.

RESULTS

As a result, we selected fourteen regulatory SNPs locating within the loci, implicated from GWAS for cognitive disorders with six of the variants unreported previously. Grouping of the targeted genes according to biological functions revealed the involvement of processes such as 'posttranscriptional regulation of gene expression', 'neuron differentiation', 'neuron projection development', 'regulation of cell cycle process' and 'protein catabolic processes'. We identified four rSNP-targeted genes that showed differential expression between patient and control groups depending on brain region: NRAS-in schizophrenia cohort, CDC25B, DDX21 and NUCKS1-in bipolar disorder cohort.

CONCLUSIONS

Overall, our findings are likely to provide the keys for unraveling the mechanisms that underlie cognitive functions including major depressive disorder, bipolar disorder and schizophrenia etiopathogenesis.

Blood assessment of the expression levels of matrix metalloproteinase 9 (MMP9) and its natural inhibitor, TIMP1 genes in Iranian schizophrenic patients

Schizophrenia (SCZ) is the most severe chronic mental disorder characterized by abnormal social behavior and disrupted emotions and thought. Like other complex neuropsychological disease, SCZ is caused by a combination of genetic and environmental factors but with a high concordance rate. So far, different genetic factors are revealed to be associated with increased risk of developing SCZ. One of the best ways to investigate the genetic basis of the complex disease is to discover the genetic underlying mechanisms of the defective clinical aspects of the patients. In this regard, genes involved in the developmental mechanisms of the brain such as long-term potentiation (LTP) process that is the basis of synaptic plasticity, memory and learning are considered as strong candidates for SCZ. The aim of the present study was to evaluate the expression levels of two genes that are involved in the LTP regulation in the developing and adult brain, Matrix metallopeptidase9 (MMP9) and TIMP metallopeptidase inhibitor 1 (TIMP1) genes in a blood assessment of schizophrenic patients in comparison to healthy controls by means of quantitative real time PCR. The results of the study showed a significant difference in MMP9/TIPM1 ratio between SCZ patients and healthy controls (P = 0.01). However, no significant difference was detected in the expression level of individual MMP9 and TIMP1 genes in SCZ patients versus healthy controls either in total numbers of subject or in sex based subgroups. Considering the relatively small sample size of the current study, there is a need to replicate this study with further investigations about the mechanism of association of these genes and their functions in the pathogenesis of the SCZ.

The recurrence risk of genetic complex diseases

Complex inherited diseases affected by an interaction between collective effects of the genotype at one or multiple loci either to increase or to lower susceptibility to disease, combined with a variety of environmental exposures that may trigger, accelerate, exacerbate, or protect against the disease process. The new aspects of genetic techniques have been opened for diagnosis and analysis of inherited disorders. While appropriate Mendelian laws is applied to estimate the recurrence risk of single gene diseases, using empirical recurrence risks are the most important and available method to evaluate pedigree of complex (multifactorial), chromosomal, and unknown etiology disorders. Although, generally, empirical recurrent risks are not accurate, either because of the difference of gene frequencies and environmental factors among populations or heterogeneity of disease; using results of plenty family population studies, computerized estimating programs, genotyping technologies, and Genome-wide association studies (GWASs) of single nucleotide polymorphisms (SNPs), can make it possible nowadays to estimate these risks. The specific family situation and importance recurrence risks of some common complex genetic diseases will be presented in this review and some important multifactorial disorders’ recurrence risks will be summarized to help genetic counselors for supporting families and representing better view of genetic disorders.

The Future is The Past: Methylation QTLs in Schizophrenia

Genome-wide association studies (GWAS) have remarkably advanced insight into the genetic basis of schizophrenia (SCZ). Still, most of the functional variance in disease risk remains unexplained. Hence, there is a growing need to map genetic variability-to-genes-to-functions for understanding the pathophysiology of SCZ and the development of better treatments. Genetic variation can regulate various cellular functions including DNA methylation, an epigenetic mark with important roles in transcription and the mediation of environmental influences. Methylation quantitative trait loci (meQTLs) are derived by mapping levels of DNA methylation in genetically different, genotyped individuals and define loci at which DNA methylation is influenced by genetic variation. Recent evidence points to an abundance of meQTLs in brain tissues whose functional contributions to development and mental diseases are still poorly understood. Interestingly, fetal meQTLs reside in regulatory domains affecting methylome reconfiguration during early brain development and are enriched in loci identified by GWAS for SCZ. Moreover, fetal meQTLs are preserved in the adult brain and could trace early epigenomic deregulation during vulnerable periods. Overall, these findings highlight the role of fetal meQTLs in the genetic risk for and in the possible neurodevelopmental origin of SCZ.

Prediction of alcohol drinking in adolescents: Personality-traits, behavior, brain responses, and genetic variations in the context of reward sensitivity

Adolescence is a time that can set the course of alcohol abuse later in life. Sensitivity to reward on multiple levels is a major factor in this development. We examined 736 adolescents from the IMAGEN longitudinal study for alcohol drinking during early (mean age=14.37) and again later (mean age=16.45) adolescence. Conducting structural equation modeling we evaluated the contribution of reward-related personality traits, behavior, brain responses and candidate genes. Personality seems to be most important in explaining alcohol drinking in early adolescence. However, genetic variations in ANKK1 (rs1800497) and HOMER1 (rs7713917) play an equal role in predicting alcohol drinking two years later and are most important in predicting the increase in alcohol consumption. We hypothesize that the initiation of alcohol use may be driven more strongly by personality while the transition to increased alcohol use is more genetically influenced.

Overview of genetic research in anorexia nervosa: The past, the present and the future

BACKGROUND

Even though the evidence supporting the presence of a heritable component in the aetiology of anorexia nervosa (AN) is strong, the underlying genetic mechanisms remain poorly understood. The recent publication of a genome-wide association study (GWAS) of AN (Boraska, Mol Psychiatry, 2014) was an important step in genetic research in AN.

OBJECTIVE

To briefly sum up strengths and weaknesses of candidate-gene and genome-wide approaches, to discuss the genome-wide association studies of AN and to make predictions about the genetic architecture of AN by comparing it to that of schizophrenia (since the diseases share some similarities and genetic research in schizophrenia is more advanced).

METHOD

Descriptive literature review.

RESULTS

Despite remarkable efforts, the gene-association studies in AN did not advance our knowledge as much as had been hoped, although some results still await replication.

DISCUSSION

Continuous effort of participants, clinicians and researchers remains necessary to ensure that genetic research in AN follows a similarly successful path as in schizophrenia. Identification of genetic susceptibility loci provides a basis for follow-up studies.

Genetic variants in long non-coding RNA MIAT contribute to risk of paranoid schizophrenia in a Chinese Han population

The heritability of schizophrenia has been reported to be as high as ~80%, but the contribution of genetic variants identified to this heritability remains to be estimated. Long non-coding RNAs (LncRNAs) are involved in multiple processes critical to normal cellular function and dysfunction of lncRNA MIAT may contribute to the pathophysiology of schizophrenia. However, the genetic evidence of lncRNAs involved in schizophrenia has not been documented. Here, we conducted a two-stage association analysis on 8 tag SNPs that cover the whole MIAT locus in two independent Han Chinese schizophrenia case-control cohorts (discovery sample from Shanxi Province: 1093 patients with paranoid schizophrenia and 1180 control subjects; replication cohort from Jilin Province: 1255 cases and 1209 healthy controls). In discovery stage, significant genetic association with paranoid schizophrenia was observed for rs1894720 (χ(2)=74.20, P=7.1E-18), of which minor allele (T) had an OR of 1.70 (95% CI=1.50-1.91). This association was confirmed in the replication cohort (χ(2)=22.66, P=1.9E-06, OR=1.32, 95%CI 1.18-1.49). Besides, a weak genotypic association was detected for rs4274 (χ(2)=4.96, df=2, P=0.03); the AA carriers showed increased disease risk (OR=1.30, 95%CI=1.03-1.64). No significant association was found between any haplotype and paranoid schizophrenia. The present studies showed that lncRNA MIAT was a novel susceptibility gene for paranoid schizophrenia in the Chinese Han population. Considering that most lncRNAs locate in non-coding regions, our result may explain why most susceptibility loci for schizophrenia identified by genome wide association studies were out of coding regions.

Influence of NRGN rs12807809 polymorphism on symptom severity in individuals with schizophrenia in the Han population but not the Zhuang population of south China

BACKGROUND

NRGN is one of the most promising candidate genes for schizophrenia based on function and position. Therefore, this study aimed to examine the genetic association of this polymorphism with schizophrenia in the Zhuang and Han populations of south China. Subjects and methods A total of 282 patients (188 Han and 94 Zhuang) and 282 healthy subjects (188 Han and 94 Zhuang) were recruited. Of these, 246 schizophrenia patients underwent an assessment of psychotic symptoms using the Positive and Negative Syndrome Scale (PANSS). A TaqMan genotyping assay method was used to determine the genotypes.

RESULTS

We did not find a significant association of rs12807809 polymorphism with schizophrenia in the total pooled samples, or in the separate ethnic groups. However, in Han schizophrenia patients, quantitative data analyses showed that the CC genotype of the rs12807809 polymorphism was associated with PANSS aggression subscale score and activation subscale score. Furthermore, carriers of the C allele of rs12807809 polymorphism among Han schizophrenia patients had higher scores of general, activation, depression, aggression, and global symptoms than the T allele carriers.

CONCLUSION

In conclusion rs12807809 polymorphism may not contribute to the risk of schizophrenia but influence the clinical symptoms of schizophrenia in the Han population.

Understanding complex transcriptome dynamics in schizophrenia and other neurological diseases using RNA sequencing

How the human brain develops and adapts with its trillions of functionally integrated synapses remains one of the greatest mysteries of life. With tremendous advances in neuroscience, genetics, and molecular biology, we are beginning to appreciate the scope of this complexity and define some of the parameters of the systems that make it possible. These same tools are also leading to advances in our understanding of the pathophysiology of neurocognitive and neuropsychiatric disorders. Like the substrate for these problems, the etiology is usually complex-involving an array of genetic and environmental influences. To resolve these influences and derive better interventions, we need to reveal every aspect of this complexity and model their interactions and define the systems and their regulatory structure. This is particularly important at the tissue-specific molecular interface between the underlying genetic and environmental influence defined by the transcriptome. Recent advances in transcriptome analysis facilitated by RNA sequencing (RNA-Seq) can provide unprecedented insight into the functional genomics of neurological disorders. In this review, we outline the advantages of this approach and highlight some early application of this technology in the investigation of the neuropathology of schizophrenia. Recent progress of RNA-Seq studies in schizophrenia has shown that there is extraordinary transcriptome dynamics with significant levels of alternative splicing. These studies only scratch the surface of this complexity and therefore future studies with greater depth and samples size will be vital to fully explore transcriptional diversity and its underlying influences in schizophrenia and provide the basis for new biomarkers and improved treatments.

Genetic risk for schizophrenia: convergence on synaptic pathways involved in plasticity

Recent large-scale genomic studies have revealed two broad classes of risk alleles for schizophrenia: a polygenic component of risk mediated through multiple common risk variants and rarer more highly penetrant submicroscopic chromosomal deletions and duplications, known as copy number variants. The focus of this review is on the emerging findings from the latter and subsequent exome sequencing data of smaller, deleterious single nucleotide variants and indels. In these studies, schizophrenia patients were found to have enriched de novo mutations in genes belonging to the postsynaptic density at glutamatergic synapses, particularly components of the N-methyl-D-aspartate receptor signaling complex, including the PSD-95 complex, activity-regulated cytoskeleton-associated protein interactors, the fragile X mental retardation protein complex, voltage-gated calcium channels, and genes implicated in actin cytoskeletal dynamics. The convergence of these implicated genes onto a coherent biological pathway at the synapse, with a specific role in plasticity, provides a significant advance in understanding pathogenesis and points to new targets for biological investigation. We consider the implications of these studies in the context of existing genetic data and the potential need to reassess diagnostic boundaries of neuropsychiatric disorders before discussing ways forward for more directed mechanistic studies to develop stratified, novel therapeutic approaches in the future.

RNA Sequencing in Schizophrenia

Schizophrenia (SCZ) is a serious psychiatric disorder that affects 1% of general population and places a heavy burden worldwide. The underlying genetic mechanism of SCZ remains unknown, but studies indicate that the disease is associated with a global gene expression disturbance across many genes. Next-generation sequencing, particularly of RNA sequencing (RNA-Seq), provides a powerful genome-scale technology to investigate the pathological processes of SCZ. RNA-Seq has been used to analyze the gene expressions and identify the novel splice isoforms and rare transcripts associated with SCZ. This paper provides an overview on the genetics of SCZ, the advantages of RNA-Seq for transcriptome analysis, the accomplishments of RNA-Seq in SCZ cohorts, and the applications of induced pluripotent stem cells and RNA-Seq in SCZ research.

Sleep and plasticity in schizophrenia

Schizophrenia is a devastating mental illness with a worldwide prevalence of approximately 1%. Although the clinical features of the disorder were described over one hundred years ago, its neurobiology is still largely elusive despite several decades of research. Schizophrenia is associated with marked sleep disturbances and memory impairment. Above and beyond altered sleep architecture, sleep rhythms including slow waves and spindles are disrupted in schizophrenia. In the healthy brain, these rhythms reflect and participate in plastic processes during sleep. This chapter discusses evidence that schizophrenia patients exhibit dysfunction of sleep-mediated plasticity on a behavioral, cellular, and molecular level and offers suggestions on how the study of sleeping brain activity can shed light on the pathophysiological mechanisms of the disorder.

Targeted multiplexed selected reaction monitoring analysis evaluates protein expression changes of molecular risk factors for major psychiatric disorders

BACKGROUND

Extensive research efforts have generated genomic, transcriptomic, proteomic, and functional data hoping to elucidate psychiatric pathophysiology. Selected reaction monitoring, a recently developed targeted proteomic mass spectrometric approach, has made it possible to evaluate previous findings and hypotheses with high sensitivity, reproducibility, and quantitative accuracy.

METHODS

Here, we have developed a labelled multiplexed selected reaction monitoring assay, comprising 56 proteins previously implicated in the aetiology of major psychiatric disorders, including cell type markers or targets and effectors of known psychopharmacological interventions. We analyzed postmortem anterior prefrontal cortex (Brodmann area 10) tissue of patients diagnosed with schizophrenia (n=22), bipolar disorder (n=23), and major depressive disorder with (n=11) and without (n=11) psychotic features compared with healthy controls (n=22).

RESULTS

Results agreed with several previous studies, with the finding of alterations of Wnt-signalling and glutamate receptor abundance predominately in bipolar disorder and abnormalities in energy metabolism across the neuropsychiatric disease spectrum. Calcium signalling was predominantly affected in schizophrenia and affective psychosis. Interestingly, we were able to show a decrease of all 4 tested oligodendrocyte specific proteins (MOG, MBP, MYPR, CNPase) in bipolar disorder and to a lesser extent in schizophrenia and affective psychosis. Finally, we provide new evidence linking ankyrin 3 specifically to affective psychosis and the 22q11.2 deletion syndrome-associated protein septin 5 to schizophrenia.

CONCLUSIONS

Our study highlights the potential of selected reaction monitoring to evaluate the protein abundance levels of candidate markers of neuropsychiatric spectrum disorders, providing a high throughput multiplex platform for validation of putative disease markers and drug targets.

5-Hydroxytryptamine (serotonin) 2A receptor gene polymorphism is associated with schizophrenia

BACKGROUND & OBJECTIVES

Schizophrenia, the debilitating neuropsychiatric disorder, is known to be heritable, involving complex genetic mechanisms. Several chromosomal regions associated with schizophrenia have been identified during the past; putative gene (s) in question, to be called the global signature for the pathophysiology of the disease, however, seems to evade us. The results obtained from the several population-wise association-non association studies have been diverse. w0 e therefore, undertook the present study on Tamil speaking population in south India to examine the association between the single nucleotide polymorphisms (SNPs) at the serotonin receptor gene (5HT2A) and the occurrence of the disease.

METHODS

Blood samples collected from 266 cases and 272 controls were subjected to genotyping (PCR amplification of candidate SNPs, RFLP and sequencing). The data on the SNPs were subjected to statistical analysis for assessing the gene frequencies in both the cases and the controls.

RESULTS

The study revealed significant association between the genotypic frequencies of the serotonin receptor polymorphism and schizophrenia. SNP analysis revealed that the frequencies of GG (30%, rs6311) and CC genotypes (32%, rs6313), were higher in patients (P<0.05) than in controls. The study also showed presence of G and C alleles in patients. s0 ignificant levels of linkage disequilibrium (LD) were found to exist between the genotype frequencies of rs6311 and rs6313.

INTERPRETATION & CONCLUSIONS

This study indicated an association between the SNPs (rs6311 and rs6313) of the serotonin receptor 5HT2A and schizophrenia. HapMap analysis revealed that in its genotype distribution, the Tamil speaking population was different from several other populations across the world, signifying the importance of such ethnicity-based studies to improve our understanding of this complex disease.

Research review: Polygenic methods and their application to psychiatric traits

BACKGROUND

Despite evidence from twin and family studies for an important contribution of genetic factors to both childhood and adult onset psychiatric disorders, identifying robustly associated specific DNA variants has proved challenging. In the pregenomics era the genetic architecture (number, frequency and effect size of risk variants) of complex genetic disorders was unknown. Empirical evidence for the genetic architecture of psychiatric disorders is emerging from the genetic studies of the last 5 years.

METHODS AND SCOPE

We review the methods investigating the polygenic nature of complex disorders. We provide mini-guides to genomic profile (or polygenic) risk scoring and to estimation of variance (or heritability) from common SNPs; a glossary of key terms is also provided. We review results of applications of the methods to psychiatric disorders and related traits and consider how these methods inform on missing heritability, hidden heritability and still-missing heritability.

FINDINGS

Genome-wide genotyping and sequencing studies are providing evidence that psychiatric disorders are truly polygenic, that is they have a genetic architecture of many genetic variants, including risk variants that are both common and rare in the population. Sample sizes published to date are mostly underpowered to detect effect sizes of the magnitude presented by nature, and these effect sizes may be constrained by the biological validity of the diagnostic constructs.

CONCLUSIONS

Increasing the sample size for genome wide association studies of psychiatric disorders will lead to the identification of more associated genetic variants, as already found for schizophrenia. These loci provide the starting point of functional analyses that might eventually lead to new prevention and treatment options and to improved biological validity of diagnostic constructs. Polygenic analyses will contribute further to our understanding of complex genetic traits as sample sizes increase and as sample resources become richer in phenotypic descriptors, both in terms of clinical symptoms and of nongenetic risk factors.

Carbonyl stress and schizophrenia

Appropriate biological treatment and psychosocial support are essential to achieve and maintain recovery for patients with schizophrenia. Despite extensive efforts to clarify the underlying disease mechanisms, the main cause and pathophysiology of schizophrenia remain unclear. This is due in large part to disease heterogeneity, which results in biochemical differences within a single disease entity. Other factors include variability across clinical symptoms and disease course, along with varied risk factors and treatment responses. Although schizophrenia's positive symptoms are largely managed through treatment with atypical antipsychotics, new classes of drugs are needed to address the unmet medical need for improving cognitive dysfunction and promoting recovery of negative symptoms in these patients. Accumulation of toxic reactive dicarbonyls, such as methylglyoxal, are typical indicators of carbonyl stress, and result in the modification of proteins and the formation of advanced glycation end products, such as pentosidine. In June 2010, we reported on idiopathic carbonyl stress in a subpopulation of schizophrenia patients, leading to a failure of metabolic systems with plasma pentosidine accumulation and serum pyridoxal depletion. Our findings suggest two markers, pentosidine and pyridoxal, as beneficial for distinguishing a specific subgroup of schizophrenics. We believe that this information, derived from in vitro and in vivo studies, is beneficial in the search for personalized and hopefully more effective treatment regimens in schizophrenia. Here, we define a subtype of schizophrenia based on carbonyl stress and the potential for using carbonyl stress as a biomarker in the challenge of overcoming heterogeneity in schizophrenia treatment.

Technological advances for deciphering the complexity of psychiatric disorders: merging proteomics with cell biology

Proteomic studies have increased our understanding of the molecular pathways affected in psychiatric disorders. Mass spectrometry and two-dimensional gel electrophoresis analyses of post-mortem brain samples from psychiatric patients have revealed effects on synaptic, cytoskeletal, antioxidant and mitochondrial protein networks. Multiplex immunoassay profiling studies have found alterations in hormones, growth factors, transport and inflammation-related proteins in serum and plasma from living first-onset patients. Despite these advances, there are still difficulties in translating these findings into platforms for improved treatment of patients and for discovery of new drugs with better efficacy and side effect profiles. This review describes how the next phase of proteomic investigations in psychiatry should include stringent replication studies for validation of biomarker candidates and functional follow-up studies which can be used to test the impact on physiological function. All biomarker candidates should now be tested in series with traditional and emerging cell biological approaches. This should include investigations of the effects of post-translational modifications, protein dynamics and network analyses using targeted proteomic approaches. Most importantly, there is still an urgent need for development of disease-relevant cellular models for improved translation of proteomic findings into a means of developing novel drug treatments for patients with these life-altering disorders.

Pro-inflammatory cytokine levels are raised in female schizophrenia patients treated with clozapine

BACKGROUND

We have previously shown that the neurotrophic factor, S100B, is raised in serum samples of female patients with schizophrenia, but not male patients, compared to controls, and this may be associated with raised BMI. Here we analysed the levels of additional proinflammatory cytokines in patients with schizophrenia to further investigate these gender differences.

METHODS

The levels of six cytokines (IL1β, IL6, IL8, IL17, IL23, TNFα) were measured in serum samples obtained from patients with schizophrenia, treated with clozapine (n=91) and compared with healthy controls (n=50). Individual cytokine levels were measured using dot-immunoblotting methods and a 'cytokine signature' was also generated by summing all 6 cytokines. Treatment time, patient age, gender, illness severity and metabolic parameters were also measured.

RESULTS

The levels of proinflammatory cytokines and BMI were significantly raised in female, but not male, patients treated with clozapine compared to healthy controls. Compared to individual cytokines, the 'cytokine signature' analysis showed less scatter of data although this 'cytokine signature' method did not improve separation of individual patients and controls.

CONCLUSIONS

This study supports previous findings that raised BMI, which is likely associated with increased number of adipocytes, may contribute to increased cytokine serum concentrations in females.

The contribution of genetic and environmental factors to the duration of pregnancy

This review describes how improvements in biometric-genetic studies of twin kinships, half-sibships, and cousinships have now demonstrated a sizeable fetal genetic and maternal genetic contribution to the spontaneous onset of labor. This is an important development because previous literature for the most part reports only an influence of the maternal genome. Current estimates of the percent of variation that is attributable to fetal genetic factors range from 11-35%; the range for the maternal genetic contribution is 13-20%. These same studies demonstrate an even larger influence of environmental sources over and above the influence of genetic sources and previously identified environmental risk factors. With these estimates in hand, a major goal for research on pregnancy duration is to identify specific allelic variation and environmental risk to account for this estimated genetic and environmental variation. A review of the current literature can serve as a guide for future research efforts.

Genome-wide association studies: findings at the major histocompatibility complex locus in psychosis

The major histocompatibility complex (MHC) is one of the most intensively investigated, genetically diverse regions of the genome. In its extended form, it encodes more than 400 genes critical to immunity but is also involved in many other functions. In 2009, three simultaneously published genome-wide association studies (GWAS) reported the first compelling evidence for involvement of the MHC in schizophrenia susceptibility. In this review, we describe the structure and function of the MHC, discuss some of the challenges for genetic analysis of the region, and provide an update on findings from GWAS studies before describing potential approaches to interpreting the role of the locus in schizophrenia etiology. The GWAS literature supports involvement of the MHC locus in schizophrenia susceptibility. Current evidence suggests that the MHC plays a more significant role in schizophrenia susceptibility than in other psychiatric disorders. Because of the substantial diversity at the locus, there are differences in the implicated risk variants between ancestral groups, as there are for many other disorders. This is somewhat different than the pattern emerging at other loci. The association findings presently capture large genomic regions, with at least some evidence to suggest that multiple signals may be involved. Based on notable successes in other disorders, we suggest approaches to refining association signals at the locus. Finally, we discuss that these genetic data may be used to understand how the MHC contributes to the complex etiology of schizophrenia.

Multimodal voxel-based meta-analysis of structural and functional magnetic resonance imaging studies in those at elevated genetic risk of developing schizophrenia

Computational brain-imaging studies of individuals at familial high risk for psychosis have provided interesting results, but interpreting these findings can be a challenge due to a number of factors. We searched the literature for studies reporting whole brain voxel-based morphometry (VBM) or functional magnetic resonance imaging (fMRI) findings in people at familial high risk for schizophrenia compared with a control group. A voxel-wise meta-analysis with the effect-size version of Signed Differential Mapping (ES-SDM) identified regional abnormalities of functional brain response. Similarly, an ES-SDM meta-analysis was conducted on VBM studies. A multi-modal imaging meta-analysis was used to highlight brain regions with both structural and functional abnormalities. Nineteen studies met the inclusion criteria, in which a total of 815 familial high-risk individuals were compared to 685 controls. Our fMRI results revealed a number of regions of altered activation. VBM findings demonstrated both increases and decreases in grey matter density of relatives in a variety of brain regions. The multimodal analysis revealed relatives had decreased grey matter with hyper-activation in the left inferior frontal gyrus/amygdala, and decreased grey matter with hypo-activation in the thalamus. We found several regions of altered activation or structure in familial high-risk individuals. Reliable fMRI findings in the right posterior superior temporal gyrus further confirm that alteration in this area is a potential marker of risk.

Genome-wide association analysis identifies 13 new risk loci for schizophrenia

Schizophrenia is an idiopathic mental disorder with a heritable component and a substantial public health impact. We conducted a multi-stage genome-wide association study (GWAS) for schizophrenia beginning with a Swedish national sample (5,001 cases and 6,243 controls) followed by meta-analysis with previous schizophrenia GWAS (8,832 cases and 12,067 controls) and finally by replication of SNPs in 168 genomic regions in independent samples (7,413 cases, 19,762 controls and 581 parent-offspring trios). We identified 22 loci associated at genome-wide significance; 13 of these are new, and 1 was previously implicated in bipolar disorder. Examination of candidate genes at these loci suggests the involvement of neuronal calcium signaling. We estimate that 8,300 independent, mostly common SNPs (95% credible interval of 6,300-10,200 SNPs) contribute to risk for schizophrenia and that these collectively account for at least 32% of the variance in liability. Common genetic variation has an important role in the etiology of schizophrenia, and larger studies will allow more detailed understanding of this disorder.

New findings in the genetics of schizophrenia

New findings in schizophrenia genetics are based on genome-wide association studies (GWAS), research into DNA copy number variations (CNVs), and endophenotypes. More than 70 genes have recently been suspected to be involved in the genetic background of schizophrenia based on the GWAS´s results. They are typically related to neurodevelopment/neuroplasticity, immunology and neuroendocrinology. Nevertheless, for many detected genes their possible relationship to schizophrenia etiopathogenesis is still unknown. The CNVs at genome loci 1q21.1 (candidate gene e.g., PRKAB2), 2p16.3 (candidate gene e.g., NRXN1), 3q29 (candidate genes e.g., BDH1, DLG1, PAK2 or TFRC), 15q11.2 (candidate gene e.g., CYFIP1), 15q13.3 (candidate gene e.g., CHRNA7), 16p13.1 (candidate genes e.g.,NTAN1 or NDE1) and 22q11.2 (candidate genes e.g., COMT, GSTT2 or PRODH) were associated with schizophrenia most frequently. Genetic research of schizophrenia endophenotypes, usually neurophysiological, neuromotoric, neurocognitive, neuroanatomical, neurological or personality-related, will help us to discover the role of relevant genes in the pathogenesis of schizophrenia. It is also necessary to integrate knowledge from other research platforms in schizophrenia, like epigenetics, studies of gene-environment interactions, transcriptomics, proteomics, metabolomics, neuroimaging and psychopathology. A better knowledge of the genetic background of schizophrenia can lead to changes in the treatment, prevention and genetic counselling. It may also reduce stigma in this severe mental disorder.

DISC1-ATF4 transcriptional repression complex: dual regulation of the cAMP-PDE4 cascade by DISC1

Disrupted-In-Schizophrenia 1 (DISC1), a risk factor for major mental illnesses, has been studied extensively in the context of neurodevelopment. However, the role of DISC1 in neuronal signaling, particularly in conjunction with intracellular cascades that occur in response to dopamine, a neurotransmitter implicated in numerous psychiatric disorders, remains elusive. Previous data suggest that DISC1 interacts with numerous proteins that impact neuronal function, including activating transcription factor 4 (ATF4). In this study, we identify a novel DISC1 and ATF4 binding region in the genomic locus of phosphodiesterase 4D (PDE4D), a gene implicated in psychiatric disorders. We found that the loss of function of either DISC1 or ATF4 increases PDE4D9 transcription, and that the association of DISC1 with the PDE4D9 locus requires ATF4. We also show that PDE4D9 is increased by D1-type dopamine receptor dopaminergic stimulation. We demonstrate that the mechanism for this increase is due to DISC1 dissociation from the PDE4D locus in mouse brain. We further characterize the interaction of DISC1 with ATF4 to show that it is regulated via protein kinase A-mediated phosphorylation of DISC1 serine-58. Our results suggest that the release of DISC1-mediated transcriptional repression of PDE4D9 acts as feedback inhibition to regulate dopaminergic signaling. Furthermore, as DISC1 loss-of-function leads to a specific increase in PDE4D9, PDE4D9 itself may represent an attractive target for therapeutic approaches in psychiatric disorders.

A population-based association study of 2q32.3 and 8q21.3 loci with schizophrenia in Han Chinese

It has been reported that two new schizophrenia susceptibility loci (2q32.3 and 8q21.3) containing two single-nucleotide polymorphisms (SNPs; rs17662626 and rs7004633) have been identified in Europeans by a genome-wide association study. To determine if the two regions are associated with schizophrenia in Han Chinese, which are distinct from Europeans, we analyzed 9 SNPs, including rs17662626 and rs7004633, within 2 regions involving 1430 cases and 1570 controls from the Han population. Single SNP association, haplotype association, and gender-specific association analyses were performed. Single SNP analyses revealed that there was no association with schizophrenia in the region of 2q32.3, but rs7004633 mapping to the region of 8q21.3 was significantly associated with schizophrenia (p = 5.1 × 10(-5); OR = 1.274; 95% CI, 1.134-1.429). Further genotype and haplotype association analyses for the region of 8q21.3 suggested a similar pattern. Additionally, analyses by haplotypes indicated that a haplotype block in the region of 8q21.3 highly associated with schizophrenia and one haplotype in this haploblock had a 1.5-fold increase in the cases. Our results provide further evidence regarding the association of the region of 8q21.3 with schizophrenia in Han Chinese, as well as Europeans, which confirmed the previous report that 8q21.3 may play important roles in the etiology of schizophrenia.

Interpreting the role of de novo protein-coding mutations in neuropsychiatric disease

Pedigree, linkage and association studies are consistent with heritable variation for complex disease due to the segregation of genetic factors in families and in the population. In contrast, de novo mutations make only minor contributions to heritability estimates for complex traits. Nonetheless, some de novo variants are known to be important in disease etiology. The identification of risk-conferring de novo variants will contribute to the discovery of etiologically relevant genes and pathways and may help in genetic counseling. There is considerable interest in the role of such mutations in complex neuropsychiatric disease, largely driven by new genotyping and sequencing technologies. An important role for large de novo copy number variations has been established. Recently, whole-exome sequencing has been used to extend the investigation of de novo variation to point mutations in protein-coding regions. Here, we consider several challenges for the interpretation of such mutations in the context of their role in neuropsychiatric disease.

The power of meta-analysis in genome-wide association studies

Meta-analysis of multiple genome-wide association (GWA) studies has become common practice over the past few years. The main advantage of this technique is the maximization of power to detect subtle genetic effects for common traits. Moreover, one can use meta-analysis to probe and identify heterogeneity in the effect sizes across the combined studies. In this review, we systematically appraise and evaluate the characteristics of GWA meta-analyses with 10,000 or more subjects published up to June 2012. We provide an overview of the current landscape of variants discovered by GWA meta-analyses, and we discuss and assess with extrapolations from empirical data the value of larger meta-analyses for the discovery of additional genetic associations and new biology in the future. Finally, we discuss some emerging logistical and practical issues related to the conduct of meta-analysis of GWA studies.

Genes and environments in schizophrenia: The different pieces of a manifold puzzle

Genetic research targeting schizophrenia has undergone tremendous development during recent years. Supported by recently developed high-throughput genotyping technologies, both rare and common genetic variants have been identified that show consistent association with schizophrenia. These results have been replicated by independent studies and refined in meta-analyses. The genetic variation uncovered consists of common alleles, i.e. single nucleotide polymorphisms (SNPs) conveying small effects (odds ratios below 1.1) on disease risk. The source of rare variants is copy number variations (CNVs), only detectable in a small proportion of patients (3-5% for all known CNVs) with schizophrenia, furthermore extremely rare de novo mutations captured by next generation sequencing, the most recent technological advancement in the field. Despite these findings, the search for the genetic architecture underlying schizophrenia continues since these variants explain only a small proportion of the overall phenotypic variance. Gene-environment interactions provide a compelling model for resolving this paradox and interpreting the risk factors of schizophrenia. Epidemiologically proven risk factors, such as prenatal infection, obstetric complications, urbanicity, cannabis, and trauma have been demonstrated to interact with genetic risk, giving rise to higher prevalence rates or more severe symptomatology in individuals with direct or indirect genetic predisposition for schizophrenia. Further research will have to explain how the different forms of genetic variation interact and how environmental factors modulate their effects. Moreover, the challenging question lying ahead of us is how genetic and environmental factors translate to molecular disease pathways. New approaches, including animal studies and in vitro disease modeling, as well as innovative real-world environment assessment methods, will help to understand the complex etiology of schizophrenia.

Rare variants in complex traits: novel identification strategies and the role of de novo mutations

Following the limited success of linkage and association studies aimed at identifying the genetic causes of common neurodevelopmental syndromes like autism and schizophrenia, complex traits such as these have recently been considered under the 'common disease-rare variant' hypothesis. Prior to this hypothesis, the study of candidate genes has enabled the discovery of rare variants in complex disorders, and in turn some of these variants have highlighted the genetic contribution of de novo variants. De novo variants belong to a subcategory of spontaneous rare variants that are largely associated with sporadic diseases, which include some complex psychiatric disorders where the affected individuals do not transmit the genetic defects they carry because of their reduced reproductive fitness. Interestingly, recent studies have demonstrated the rate of germline de novo mutations to be higher in individuals with complex psychiatric disorders by comparison to what is seen in unaffected control individuals; moreover, de novo mutations carried by affected individuals have generally been more deleterious than those observed in control individuals. Advanced sequencing technologies have recently enabled the undertaking of massive parallel sequencing projects that can cover the entire coding sequences (exome) or genome of several individuals at once. Such advances have thus fostered the emergence of novel genetic hypotheses and ideas to investigate disease-causative genetic variations. The genetic underpinnings of a number of sporadic complex diseases is now becoming partly explained and more major breakthroughs for complex traits genomics should be expected in the near future.

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

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

Cortical circuit dysfunction and cognitive deficits in schizophrenia--implications for preemptive interventions

Schizophrenia is a devastating disorder that is common, usually chronic, frequently associated with substantial co-morbidity for addictive and medical disorders and, as a consequence, very costly in both personal and economic terms. At present, no proven means for preventing or modifying the course of the illness exist. This review discusses evidence supporting the ideas that: (i) impairments in certain cognitive processes are the core feature of schizophrenia; (ii) these cognitive impairments reflect abnormalities in specific cortical circuits; and (iii) these circuitry abnormalities arise during childhood-adolescence. The implications of these findings for the development and implementation of safe, preemptive, disease-modifying interventions in individuals at high risk for a clinical diagnosis of schizophrenia are considered.