Evidence for rare and common genetic risk variants for schizophrenia at protein kinase C, alpha

Secondary metabolites and their bioactivities from Paecilomyces gunnii YMF1.00003

Four new polyketides (1-4) and seven known compounds (5-11) including three polyketides and four sterols were isolated from the fermented extracts of Paecilomyces gunnii YMF1.00003. The new chemical structures were determined through the analysis of the nuclear magnetic resonance and high-resolution electrospray ionization mass spectrometry, and their configurations were subsequently confirmed by nuclear overhauser effect spectroscopy, the calculated electronic circular dichroism (ECD) spectra, and quantum chemical calculations of the NMR data (qcc NMR). Based on the results of pre-activity screening and compound structure target prediction, certain metabolites were assayed to evaluate their cytotoxic and protein kinase Cα inhibitory activities. Results indicated that 3β-hydroxy-7α-methoxy-5α,6α-epoxy-8(14),22E-dien-ergosta (8) exhibited potent cytotoxic activity, with half-maximal inhibitory concentration values of 3.00 ± 0.27 to 15.69 ± 0.61 μM against five tumor cells, respectively. The new compound gunniiol A (1) showed weak cytotoxic activity at a concentration of 40 μM. At a concentration of 20 μg/mL, compounds 1, 6, and 7 exhibited protein kinase Cα inhibition by 43.63, 40.93, and 57.66%, respectively. This study is the first to report steroids demonstrating good cytotoxicity and polyketides exhibiting inhibitory activity against protein kinase Cα from the extracts of P. gunnii.

Dysfunction of Prkcaa Links Social Behavior Defects with Disturbed Circadian Rhythm in Zebrafish

Protein kinase Cα (PKCα/PRKCA) is a crucial regulator of circadian rhythm and is associated with human mental illnesses such as autism spectrum disorders and schizophrenia. However, the roles of PRKCA in modulating animal social behavior and the underlying mechanisms remain to be explored. Here we report the generation and characterization of prkcaa-deficient zebrafish (Danio rerio). The results of behavioral tests indicate that a deficiency in Prkcaa led to anxiety-like behavior and impaired social preference in zebrafish. RNA-sequencing analyses revealed the significant effects of the prkcaa mutation on the expression of the morning-preferring circadian genes. The representatives are the immediate early genes, including egr2a, egr4, fosaa, fosab and npas4a. The downregulation of these genes at night was attenuated by Prkcaa dysfunction. Consistently, the mutants demonstrated reversed day-night locomotor rhythm, which are more active at night than in the morning. Our data show the roles of PRKCA in regulating animal social interactions and link the social behavior defects with a disturbed circadian rhythm.

The machine learning algorithm for the diagnosis of schizophrenia on the basis of gene expression in peripheral blood

BACKGROUND

Schizophrenia (SCZ) is a highly heritable mental disorder with a substantial disease burden. Machine learning (ML) method can be used to identify individuals with SCZ on the basis of blood gene expression data with high accuracy.

METHODS

This study aimed to differentiate patients with SCZ from healthy individuals by using the messenger RNA expression level in peripheral blood of 48 patients with SCZ and 50 controls via ML algorithms, namely, artificial neural networks, extreme gradient boosting, support vector machine (SVM), decision tree, and random forest. The expression of six mRNAs was detected using quantitative real-time polymerase chain reaction (qRT-PCR).

RESULTS

The relative expression levels of GNAI1 (P < 0.001), PRKCA (P < 0.001), and PRKCB (P = 0.021) increased in the SCZ group, whereas those of FYN (P < 0.001), LYN (P = 0.022), and YWHAZ (P < 0.001) decreased in the SCZ group. We generated models with various combinations of genes based on five ML algorithms. The SVM model with six factors (GNAI1, FYN, PRKCA, YWHAZ, PRKCB, and LYN genes) was the best model for distinguishing patients with SCZ from healthy individuals (AUC = 0.993, sensitivity = 1.000, specificity = 0.895, and Youden index = 0.895).

CONCLUSIONS

This study suggested that the combination of genes using the ML method is better than the use of a single gene to discriminate patients with SCZ from healthy individuals. The combination of GNAI1, FYN, PRKCA, YWHAZ, PRKCB, and LYN under the SVM model can be used as a diagnostic biomarker for SCZ.

The Gene Polymorphism of VMAT2 Is Associated with Risk of Schizophrenia in Male Han Chinese

OBJECTIVE

To investigate the association between gene polymorphism of vesicular monoamine transporter type 2(VMAT2) and schizophrenia in Han Chinese population.

METHODS

430 patients with schizophrenia and 470 age-sex matched controls were recruited from four mental health centers. All patients were diagnosed by two psychiatrists based on the Structured Clinical Interview for DSM Disorders (SCID). The ligase detection reactions (LDR) method was used to assess the polymorphism of the two SNPs (rs363371 and rs363324) of VMAT2.

RESULTS

No associations of two SNPs with schizophrenia was found. When we stratified males and females for the analysis, we found that that in the recessive model of rs363371, there was an obvious significant association between rs363371 and schizophrenia in males (OR=0.564, 95% CI=0.357-0.892, p=0.014) but not females. For the association between rs363324 and schizophrenia, no association was found in either males or females. No association was found when stratifying early-onset schizophrenia and late-onset schizophrenia.

CONCLUSION

Our findings indicate that both rs363371 and rs363324 were not associated with schizophrenia, while it seemed that the AA genotype of rs363371 plays a protective effect in male Chinese in developing schizophrenia.

Assessment of complementarity of WGCNA and NERI results for identification of modules associated to schizophrenia spectrum disorders

Psychiatric disorders involve both changes in multiple genes as well different types of variations. As such, gene co-expression networks allowed the comparison of different stages and parts of the brain contributing to an integrated view of genetic variation. Two methods based on co-expression networks presents appealing results: Weighted Gene Correlation Network Analysis (WGCNA) and Network-Medicine Relative Importance (NERI). By selecting two different gene expression databases related to schizophrenia, we evaluated the biological modules selected by both WGCNA and NERI along these databases as well combining both WGCNA and NERI results (WGCNA-NERI). Also we conducted a enrichment analysis for the identification of partial biological function of each result (as well a replication analysis). To appraise the accuracy of whether both algorithms (as well our approach, WGCNA-NERI) were pointing to genes related to schizophrenia and its complex genetic architecture we conducted the MSET analysis, based on a reference gene list of schizophrenia database (SZDB) related to DNA Methylation, Exome, GWAS as well as copy number variation mutation studies. The WGCNA results were more associated with inflammatory pathways and immune system response; NERI obtained genes related with cellular regulation, embryological pathways e cellular growth factors. Only NERI were able to provide a statistical meaningful results to the MSET analysis (for Methylation and de novo mutations data). However, combining WGCNA and NERI provided a much more larger overlap in these two categories and additionally on Transcriptome database. Our study suggests that using both methods in combination is better for establishing a group of modules and pathways related to a complex disease than using each method individually. NERI is available at: https://bitbucket.org/sergionery/neri.

High Incidence of Copy Number Variants in Adults with Intellectual Disability and Co-morbid Psychiatric Disorders

A genetic analysis of unexplained mild-moderate intellectual disability and co-morbid psychiatric or behavioural disorders is not systematically conducted in adults. A cohort of 100 adult patients affected by both phenotypes were analysed in order to identify the presence of copy number variants (CNVs) responsible for their condition identifying a yield of 12.8% of pathogenic CNVs (19% when including clinically recognizable microdeletion syndromes). Moreover, there is a detailed clinical description of an additional 11% of the patients harbouring possible pathogenic CNVs—including a 7q31 deletion (IMMP2L) in two unrelated patients and duplications in 3q29, 9p24.2p24.1 and 15q14q15.1—providing new evidence of its contribution to the phenotype. This study adds further proof of including chromosomal microarray analysis (CMA) as a mandatory test to improve the diagnosis in the adult patients in psychiatric services.

A Genome-Wide Association Study and Complex Network Identify Four Core Hub Genes in Bipolar Disorder

Bipolar disorder is a common and severe mental illness with unsolved pathophysiology. A genome-wide association study (GWAS) has been used to find a number of risk genes, but it is difficult for a GWAS to find genes indirectly associated with a disease. To find core hub genes, we introduce a network analysis after the GWAS was conducted. Six thousand four hundred fifty eight single nucleotide polymorphisms (SNPs) with p < 0.01 were sifted out from Wellcome Trust Case Control Consortium (WTCCC) dataset and mapped to 2045 genes, which are then compared with the protein–protein network. One hundred twelve genes with a degree >17 were chosen as hub genes from which five significant modules and four core hub genes (FBXL13, WDFY2, bFGF, and MTHFD1L) were found. These core hub genes have not been reported to be directly associated with BD but may function by interacting with genes directly related to BD. Our method engenders new thoughts on finding genes indirectly associated with, but important for, complex diseases.

Role of Protein Kinase C in Bipolar Disorder: A Review of the Current Literature

Bipolar disorder (BD) is a major health problem. It causes significant morbidity and imposes a burden on the society. Available treatments help a substantial proportion of patients but are not beneficial for an estimated 40-50%. Thus, there is a great need to further our understanding the pathophysiology of BD to identify new therapeutic avenues. The preponderance of evidence pointed towards a role of protein kinase C (PKC) in BD. We reviewed the literature pertinent to the role of PKC in BD. We present recent advances from preclinical and clinical studies that further support the role of PKC. Moreover, we discuss the role of PKC on synaptogenesis and neuroplasticity in the context of BD. The recent development of animal models of BD, such as stimulant-treated and paradoxical sleep deprivation, and the ability to intervene pharmacologically provide further insights into the involvement of PKC in BD. In addition, the effect of PKC inhibitors, such as tamoxifen, in the resolution of manic symptoms in patients with BD further points in that direction. Furthermore, a wide variety of growth factors influence neurotransmission through several molecular pathways that involve downstream effects of PKC. Our current understanding identifies the PKC pathway as a potential therapeutic avenue for BD.

Regulatory Variants Modulate Protein Kinase C α (PRKCA) Gene Expression in Human Heart

PURPOSE

Protein kinase C α (PRKCA) is involved in multiple functions and has been implicated in heart failure risks and treatment outcomes. This study aims to identify regulatory variants affecting PRKCA expression in human heart, and evaluate attributable risk of heart disease.

METHODS

mRNA expression quantitative trait loci (eQTLs) were extracted from the Genotype and Tissue Expression Project (GTEx). Allelic mRNA ratios were measured in 51 human heart tissues to identify cis-acting regulatory variants. Potential regulatory regions were tested with luciferase reporter gene assays and further evaluated in GTEx and genome-wide association studies.

RESULTS

Located in a region with robust enhancer activity in luciferase reporter assays, rs9909004 (T > C, minor allele frequency =0.47) resides in a haplotype displaying strong eQTLs for PRKCA in heart (p = 1.2 × 10-23). The minor C allele is associated with both decreased PRKCA mRNA expression and decreased risk of phenotypes characteristic of heart failure in GWAS analyses (QT interval p = 3.0 × 10-14). While rs9909004 is the likely regulatory variant, other variants in high linkage disequilibrium cannot be excluded. Distinct regulatory variants appear to affect expression in other tissues.

CONCLUSIONS

The haplotype carrying rs9909004 influences PRKCA expression in the heart and is associated with traits linked to heart failure, potentially affecting therapy of heart failure.

miR-634 is a Pol III-dependent intronic microRNA regulating alternative-polyadenylated isoforms of its host gene PRKCA

BACKGROUND

The protein kinase C alpha (PRKCA) gene, coding for a Th17-cell-selective kinase, shows a complex splicing pattern, with at least 2 stable alternative transcripts characterized by an alternative upstream polyadenylation site. Polymorphisms in this gene were associated with several conditions, including multiple sclerosis, asthma, schizophrenia, and cancer. The presence of a microRNA (miRNA), i.e. miR-634, within intron 15 of the PRKCA gene, suggests the intriguing possibility that this miRNA might play a role in the susceptibility to these pathologies.

METHODS

Here, we characterized miR-634 expression profile and searched for its putative targets using a combination of RT-PCR and gene reporter assays.

RESULTS

The quantitative analysis of PRKCA and miR-634 transcripts in a panel of human tissues and cell lines revealed discordant expression profiles, suggesting the presence of an independent miR-634 promoter and/or a possible direct role of miR-634 in modulating PRKCA expression. Functional studies demonstrated the existence of a miRNA-specific promoter, which was shown to be Pol-III-dependent. Furthermore, transfection experiments showed that miR-634 is able to target its host gene by specifically down-regulating the shorter alternative-polyadenylated isoforms.

CONCLUSIONS

MiR-634 is a Pol III-dependent intronic miRNA, which could target its host gene through a "first-order" negative feedback.

GENERAL SIGNIFICANCE

MiR-634 is one of the few characterized examples of Pol-III-dependent intronic miRNAs. Its independent transcription from the host gene suggests caution in using expression profiles of host genes as proxies for the expression of the corresponding intronic miRNAs.

Obesity and genomics: role of technology in unraveling the complex genetic architecture of obesity

Obesity is a complex and multifactorial disease that occurs as a result of the interaction between "obesogenic" environmental factors and genetic components. Although the genetic component of obesity is clear from the heritability studies, the genetic basis remains largely elusive. Successes have been achieved in identifying the causal genes for monogenic obesity using animal models and linkage studies, but these approaches are not fruitful for polygenic obesity. The developments of genome-wide association approach have brought breakthrough discovery of genetic variants for polygenic obesity where tens of new susceptibility loci were identified. However, the common SNPs only accounted for a proportion of heritability. The arrival of NGS technologies and completion of 1000 Genomes Project have brought other new methods to dissect the genetic architecture of obesity, for example, the use of exome genotyping arrays and deep sequencing of candidate loci identified from GWAS to study rare variants. In this review, we summarize and discuss the developments of these genetic approaches in human obesity.

Sex differences in the genetic risk for schizophrenia: history of the evidence for sex-specific and sex-dependent effects

Although there is a long history to examinations of sex differences in the familial (and specifically, genetic) transmission of schizophrenia, there have been few investigators who have systematically and rigorously studied this issue. This is true even in light of population and clinical studies identifying significant sex differences in incidence, expression, neuroanatomic and functional brain abnormalities, and course of schizophrenia. This review highlights the history of work in this arena from studies of family transmission patterns, linkage and twin studies to the current molecular genetic strategies of large genome-wide association studies. Taken as a whole, the evidence supports the presence of genetic risks of which some are sex-specific (i.e., presence in one sex and not the other) or sex-dependent (i.e., quantitative differences in risk between the sexes). Thus, a concerted effort to systematically investigate these questions is warranted and, as we argue here, necessary in order to fully understand the etiology of schizophrenia.

Are dopamine D2 receptors out of control in psychosis?

It is known that schizophrenia patients are behaviorally supersensitive to dopamine-like drugs (amphetamine, methylphenidate). There is evidence for an increased release of dopamine, a slight increase of dopamine D2 receptors and an increase of dopamine D2High receptors in schizophrenia, all possibly explaining the clinical supersensitivity to dopamine. The elevation in apparent D2High receptors in vivo in schizophrenia matches the elevation in D2High receptors in many animal models of psychosis. The increased amounts of D2High receptors in psychotic-like behavior in animals may result from a loss of control of D2 by various factors. These factors include the rate of phosphorylation and desensitization of D2 receptors by kinases, the attachment of arrestin to D2 receptors, internalization of D2 receptors, the rate of receptor de-phosphorylation, formation of D2 receptor dimers, and GTP regulation by various GTPases. While at present there are no statistically significant associations of any of these controlling factors and their genes with schizophrenia, investigation of D2High receptors in schizophrenia will require a new radioligand in order to selectively label D2High receptors in vivo in patients. Finally, haloperidol reduces the number of D2High receptors that are elevated by amphetamine, indicating that this therapeutic effect may occur clinically.

The DAO gene is associated with schizophrenia and interacts with other genes in the Taiwan Han Chinese population

BACKGROUND

Schizophrenia is a highly heritable disease with a polygenic mode of inheritance. Many studies have contributed to our understanding of the genetic underpinnings of schizophrenia, but little is known about how interactions among genes affect the risk of schizophrenia. This study aimed to assess the associations and interactions among genes that confer vulnerability to schizophrenia and to examine the moderating effect of neuropsychological impairment.

METHODS

We analyzed 99 SNPs from 10 candidate genes in 1,512 subject samples. The permutation-based single-locus, multi-locus association tests, and a gene-based multifactorial dimension reduction procedure were used to examine genetic associations and interactions to schizophrenia.

RESULTS

We found that no single SNP was significantly associated with schizophrenia. However, a risk haplotype, namely A-T-C of the SNP triplet rsDAO7-rsDAO8-rsDAO13 of the DAO gene, was strongly associated with schizophrenia. Interaction analyses identified multiple between-gene and within-gene interactions. Between-gene interactions including DAO*DISC1 , DAO*NRG1 and DAO*RASD2 and a within-gene interaction for CACNG2 were found among schizophrenia subjects with severe sustained attention deficits, suggesting a modifying effect of impaired neuropsychological functioning. Other interactions such as the within-gene interaction of DAO and the between-gene interaction of DAO and PTK2B were consistently identified regardless of stratification by neuropsychological dysfunction. Importantly, except for the within-gene interaction of CACNG2, all of the identified risk haplotypes and interactions involved SNPs from DAO.

CONCLUSIONS

These results suggest that DAO, which is involved in the N-methyl-d-aspartate receptor regulation, signaling and glutamate metabolism, is the master gene of the genetic associations and interactions underlying schizophrenia. Besides, the interaction between DAO and RASD2 has provided an insight in integrating the glutamate and dopamine hypotheses of schizophrenia.

Exploring the pathogenetic association between schizophrenia and type 2 diabetes mellitus diseases based on pathway analysis

BACKGROUND

Schizophrenia (SCZ) and type 2 diabetes mellitus (T2D) are both complex diseases. Accumulated studies indicate that schizophrenia patients are prone to present the type 2 diabetes symptoms, but the potential mechanisms behind their association remain unknown. Here we explored the pathogenetic association between SCZ and T2D based on pathway analysis and protein-protein interaction.

RESULTS

With sets of prioritized susceptibility genes for SCZ and T2D, we identified significant pathways (with adjusted p-value < 0.05) specific for SCZ or T2D and for both diseases based on pathway enrichment analysis. We also constructed a network to explore the crosstalk among those significant pathways. Our results revealed that some pathways are shared by both SCZ and T2D diseases through a number of susceptibility genes. With 382 unique susceptibility proteins for SCZ and T2D, we further built a protein-protein interaction network by extracting their nearest interacting neighbours. Among 2,104 retrieved proteins, 364 of them were found simultaneously interacted with susceptibility proteins of both SCZ and T2D, and proposed as new candidate risk factors for both diseases. Literature mining supported the potential association of partial new candidate proteins with both SCZ and T2D. Moreover, some proteins were hub proteins with high connectivity and interacted with multiple proteins involved in both diseases, implying their pleiotropic effects for the pathogenic association. Some of these hub proteins are the components of our identified enriched pathways, including calcium signaling, g-secretase mediated ErbB4 signaling, adipocytokine signaling, insulin signaling, AKT signaling and type II diabetes mellitus pathways. Through the integration of multiple lines of information, we proposed that those signaling pathways, which contain susceptibility genes for both diseases, could be the key pathways to bridge SCZ and T2D. AKT could be one of the important shared components and may play a pivotal role to link both of the pathogenetic processes.

CONCLUSIONS

Our study is the first network and pathway-based systematic analysis for SCZ and T2D, and provides the general pathway-based view of pathogenetic association between two diseases. Moreover, we identified a set of candidate genes potentially contributing to the linkage between these two diseases. This research offers new insights into the potential mechanisms underlying the co-occurrence of SCZ and T2D, and thus, could facilitate the inference of novel hypotheses for the co-morbidity of the two diseases. Some etiological factors that exert pleiotropic effects shared by the significant pathways of two diseases may have important implications for the diseases and could be therapeutic intervention targets.

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.

An environmental analysis of genes associated with schizophrenia: hypoxia and vascular factors as interacting elements in the neurodevelopmental model

Investigating and understanding gene-environment interaction (G × E) in a neurodevelopmentally and biologically plausible manner is a major challenge for schizophrenia research. Hypoxia during neurodevelopment is one of several environmental factors related to the risk of schizophrenia, and links between schizophrenia candidate genes and hypoxia regulation or vascular expression have been proposed. Given the availability of a wealth of complex genetic information on schizophrenia in the literature without knowledge on the connections to environmental factors, we now systematically collected genes from candidate studies (using SzGene), genome-wide association studies (GWAS) and copy number variation (CNV) analyses, and then applied four criteria to test for a (theoretical) link to ischemia-hypoxia and/or vascular factors. In all, 55% of the schizophrenia candidate genes (n=42 genes) met the criteria for a link to ischemia-hypoxia and/or vascular factors. Genes associated with schizophrenia showed a significant, threefold enrichment among genes that were derived from microarray studies of the ischemia-hypoxia response (IHR) in the brain. Thus, the finding of a considerable match between genes associated with the risk of schizophrenia and IHR and/or vascular factors is reproducible. An additional survey of genes identified by GWAS and CNV analyses suggested novel genes that match the criteria. Findings for interactions between specific variants of genes proposed to be IHR and/or vascular factors with obstetric complications in patients with schizophrenia have been reported in the literature. Therefore, the extended gene set defined here may form a reasonable and evidence-based starting point for hypothesis-based testing of G × E interactions in clinical genetic and translational neuroscience studies.

Convergent functional genomics of schizophrenia: from comprehensive understanding to genetic risk prediction

We have used a translational convergent functional genomics (CFG) approach to identify and prioritize genes involved in schizophrenia, by gene-level integration of genome-wide association study data with other genetic and gene expression studies in humans and animal models. Using this polyevidence scoring and pathway analyses, we identify top genes (DISC1, TCF4, MBP, MOBP, NCAM1, NRCAM, NDUFV2, RAB18, as well as ADCYAP1, BDNF, CNR1, COMT, DRD2, DTNBP1, GAD1, GRIA1, GRIN2B, HTR2A, NRG1, RELN, SNAP-25, TNIK), brain development, myelination, cell adhesion, glutamate receptor signaling, G-protein-coupled receptor signaling and cAMP-mediated signaling as key to pathophysiology and as targets for therapeutic intervention. Overall, the data are consistent with a model of disrupted connectivity in schizophrenia, resulting from the effects of neurodevelopmental environmental stress on a background of genetic vulnerability. In addition, we show how the top candidate genes identified by CFG can be used to generate a genetic risk prediction score (GRPS) to aid schizophrenia diagnostics, with predictive ability in independent cohorts. The GRPS also differentiates classic age of onset schizophrenia from early onset and late-onset disease. We also show, in three independent cohorts, two European American and one African American, increasing overlap, reproducibility and consistency of findings from single-nucleotide polymorphisms to genes, then genes prioritized by CFG, and ultimately at the level of biological pathways and mechanisms. Finally, we compared our top candidate genes for schizophrenia from this analysis with top candidate genes for bipolar disorder and anxiety disorders from previous CFG analyses conducted by us, as well as findings from the fields of autism and Alzheimer. Overall, our work maps the genomic and biological landscape for schizophrenia, providing leads towards a better understanding of illness, diagnostics and therapeutics. It also reveals the significant genetic overlap with other major psychiatric disorder domains, suggesting the need for improved nosology.

17q24.2 microdeletions: a new syndromal entity with intellectual disability, truncal obesity, mood swings and hallucinations

Although microdeletions of the long arm of chromosome 17 are being reported with increasing frequency, deletions of chromosome band 17q24.2 are rare. Here we report four patients with a microdeletion encompassing chromosome band 17q24.2 with a smallest region of overlap of 713 kb containing five Refseq genes and one miRNA. The patients share the phenotypic characteristics, such as intellectual disability (4/4), speech delay (4/4), truncal obesity (4/4), seizures (2/4), hearing loss (3/4) and a particular facial gestalt. Hallucinations and mood swings were also noted in two patients. The PRKCA gene is a very interesting candidate gene for many of the observed phenotypic features, as this gene plays an important role in many cellular processes. Deletion of this gene might explain the observed truncal obesity and could also account for the hallucinations and mood swings seen in two patients, whereas deletion of a CACNG gene cluster might be responsible for the seizures observed in two patients. In one of the patients, the PRKAR1A gene responsible for Carney Complex and the KCNJ2 gene causal for Andersen syndrome are deleted. This is the first report of a patient with a whole gene deletion of the KCNJ2 gene.

Next-generation sequencing approaches for genetic mapping of complex diseases

The advent of next generation sequencing technologies has opened new possibilities in the analysis of human disease. In this review we present the main next-generation sequencing technologies, with their major contributions and possible applications to the study of the genetic etiology of complex diseases.

Phenotype evaluation and genomewide linkage study of clinical variables in schizophrenia

Genetic factors are likely to influence clinical variation in schizophrenia, but it is unclear which variables are most suitable as phenotypes and which molecular genetic loci are involved. We evaluated clinical variable phenotypes and applied suitable phenotypes in genome-wide covariate linkage analysis. We ascertained 170 affected relative pairs (168 sibling-pairs and two avuncular pairs) with DSM-IV schizophrenia or schizoaffective disorder from the United Kingdom. We defined psychotic symptom dimensions, age at onset (AAO), and illness course using the OPCRIT checklist. We evaluated phenotypes using within sibling-pair correlations and applied suitable phenotypes in multipoint covariate linkage analysis based on 372 microsatellite markers at ∼10 cM intervals. The statistical significance of linkage results was assessed by simulation. The positive and disorganized symptom dimensions, AAO, and illness course qualified as suitable phenotypes. There were no genome-wide significant linkage results. There was suggestive evidence of linkage for the positive dimension on chromosomes 2q32, 10q26, and 20q12; the disorganized dimension on 8p21 and 17q21; and illness course on 2q33 and 22q11. The linkage peak for disorganization on 17q21 remained suggestive after correction for multiple testing. To our knowledge, this is the first study to integrate phenotype evaluation and genome-wide covariate linkage analysis for symptom dimensions and illness history variables in sibling-pairs with schizophrenia. The significant within-pair correlations strengthen the evidence that some clinical variables within schizophrenia are suitable phenotypes for molecular genetic investigations. At present there are no genome-wide significant linkage results for these phenotypes, but a number of suggestive findings warrant further investigation.

A genome-wide study of panic disorder suggests the amiloride-sensitive cation channel 1 as a candidate gene

Panic disorder (PD) is a mental disorder with recurrent panic attacks that occur spontaneously and are not associated to any particular object or situation. There is no consensus on what causes PD. However, it is recognized that PD is influenced by environmental factors, as well as genetic factors. Despite a significant hereditary component, genetic studies have only been modestly successful in identifying genes of importance for the development of PD. In this study, we conducted a genome-wide scan using microsatellite markers and PD patients and control individuals from the isolated population of the Faroe Islands. Subsequently, we conducted a fine mapping, which revealed the amiloride-sensitive cation channel 1 (ACCN1) located on chromosome 17q11.2-q12 as a potential candidate gene for PD. The further analyses of the ACCN1 gene using single-nucleotide polymorphisms (SNPs) revealed significant association with PD in an extended Faroese case-control sample. However, analyses of a larger independent Danish case-control sample yielded no substantial significant association. This suggests that the possible risk alleles associated in the isolated population are not those involved in the development of PD in a larger outbred population.

Comprehensive family-based association study of the glutamate transporter gene SLC1A1 in obsessive-compulsive disorder

SLC1A1 encodes a neuronal glutamate transporter and is a promising candidate gene for obsessive-compulsive disorder (OCD). Several independent research groups have reported significant associations between OCD and single nucleotide polymorphisms (SNPs) in this gene. Previously, we evaluated 13 SNPs in, or near, SLC1A1 and reported a strong association signal with rs301443, a SNP 7.5 kb downstream of the gene [Shugart et al. (2009); Am J Med Genet Part B 150B:886–892]. The aims of the current study were first, to further investigate this finding by saturating the region around rs301443; and second, to explore the entire gene more thoroughly with a dense panel of SNP markers. We genotyped an additional 111 SNPs in or near SLC1A1, covering from 9 kb upstream to 84 kb downstream of the gene at average spacing of 1.7 kb per SNP, and conducted family-based association analyses in 1,576 participants in 377 families.We found that none of the surrounding markers were in linkage disequilibrium with rs301443, nor were any associated with OCD. We also found that SNP rs4740788, located about 8.8 kb upstream of the gene, was associated with OCD in all families (P = 0.003) and in families with male affecteds (P = 0.002). A three-SNP haplotype (rs4740788–rs10491734–rs10491733) was associated with OCD in the total sample (P = 0.00015) and in families with male affecteds (P = 0.0007). Although of nominal statistical significance considering the number of comparisons, these findings provide further support for the involvement of SLC1A1 in the pathogenesis of OCD.

Association of CHRNA4 polymorphisms with smoking behavior in two populations

CHRNA4, the gene that encodes the nicotinic acetylcholine receptor α(4) subunit, is a potential candidate gene for nicotine dependence (ND). However, studies of the association of CHNRA4 with smoking behavior have shown inconsistent results. Our meta-analysis of linkage studies of smoking behavior identified a genome-wide significant linkage of the phenotype maximum number of cigarettes smoked in a 24-hour period to a region (20q13.12-q13.32) harboring CHRNA4. This motivated us to examine the association of CHRNA4 with smoking behavior in two independent samples. In this study, we examined five single nucleotide polymorphisms (SNPs) within CHRNA4 and three smoking-related behaviors: one quantitative trait [cigarettes smoked per day (CPD)], and two binary traits [DSM-IV diagnosis of ND and dichotomized Fagerstrom test of ND (FTND)], in 1,249 unrelated European-Americans (EAs) and 1,790 unrelated African-Americans (AAs). Using the combined sample with sex, age, and race as covariates, the synonymous SNP rs1044394 was significantly associated with ND (P = 0.001) and FTND (P = 0.01). Rs2236196, which has a low correlation with rs1044394, was also significantly associated with CPD (P = 0.003). The pattern of association for these SNPs was similar in AAs and EAs. After correction for multiple testing, the association between rs1044394 and ND in the combined sample remained significant (P = 0.033). In summary, our study supports association between CHRNA4 common variation and ND in AA and EA samples. Additional studies will be necessary to evaluate the role of rare variants at CHRNA4 for ND.

Polymorphisms associated with normal memory variation also affect memory impairment in schizophrenia

Neurocognitive dysfunction is a core feature of schizophrenia with particularly prominent deficits in verbal episodic memory. The molecular basis of this memory impairment is poorly understood and its relatedness to normal variation in memory performance is unclear. In this study, we explore, in a sample of cognitively impaired schizophrenia patients, the role of polymorphisms in seven genes recently reported to modulate episodic memory in normal subjects. Three polymorphisms (GRIN2B rs220599, GRM3 rs2189814 and PRKCA rs8074995) were associated with episodic verbal memory in both control and patients with cognitive deficit, but not in cognitively spared patients or the pooled schizophrenia sample. GRM3 and PRKCA acted in opposite directions in patients compared to controls, possibly reflecting an abnormal brain milieu and/or adverse environmental effects in schizophrenia. The encoded proteins balance glutamate signalling vs. excitotoxicity in complex interactions involving the excitatory amino acid transporter 2 (EAAT2), implicated in the dysfunctional glutamatergic signalling in schizophrenia. Double carrier status of the GRM3 and PRKCA minor alleles was associated with lower memory test scores and with increased risk of schizophrenia. Single nucleotide polymorphism (SNP) rs8074995 lies within the PRKCA region spanned by a rare haplotype associated with schizophrenia in a recent UK study and provides further evidence of PRKCA contribution to memory impairment and susceptibility to schizophrenia. Our study supports the utility of parsing the broad phenotype of schizophrenia into component cognitive endophenotypes that reduce heterogeneity and enable the capture of potentially important genetic associations.

Genetics in schizophrenia: where are we and what next?

Understanding the genetic basis of schizophrenia continues to be major challenge. The research done during the last two decades has provided several candidate genes which unfortunately have not been consistently replicated across or within a population. The recent genome-wide association studies (GWAS) and copy number variation (CNV) studies have provided important evidence suggesting a role of both common and rare large CNVs in schizophrenia genesis. The burden of rare copy number variations appears to be increased in schizophrenia patients. A consistent observation among the GWAS studies is the association with schizophrenia of genetic markers in the major histocompatibility complex (6p22.1)-containing genes including NOTCH4 and histone protein loci. Molecular genetic studies are also demonstrating that there is more overlap between the susceptibility genes for schizophrenia and bipolar disorder than previously suspected. In this review we summarize the major findings of the past decade and suggest areas of future research.

Disease gene characterization through large-scale co-expression analysis

BACKGROUND

In the post genome era, a major goal of biology is the identification of specific roles for individual genes. We report a new genomic tool for gene characterization, the UCLA Gene Expression Tool (UGET).

RESULTS

Celsius, the largest co-normalized microarray dataset of Affymetrix based gene expression, was used to calculate the correlation between all possible gene pairs on all platforms, and generate stored indexes in a web searchable format. The size of Celsius makes UGET a powerful gene characterization tool. Using a small seed list of known cartilage-selective genes, UGET extended the list of known genes by identifying 32 new highly cartilage-selective genes. Of these, 7 of 10 tested were validated by qPCR including the novel cartilage-specific genes SDK2 and FLJ41170. In addition, we retrospectively tested UGET and other gene expression based prioritization tools to identify disease-causing genes within known linkage intervals. We first demonstrated this utility with UGET using genetically heterogeneous disorders such as Joubert syndrome, microcephaly, neuropsychiatric disorders and type 2 limb girdle muscular dystrophy (LGMD2) and then compared UGET to other gene expression based prioritization programs which use small but discrete and well annotated datasets. Finally, we observed a significantly higher gene correlation shared between genes in disease networks associated with similar complex or Mendelian disorders.

DISCUSSION

UGET is an invaluable resource for a geneticist that permits the rapid inclusion of expression criteria from one to hundreds of genes in genomic intervals linked to disease. By using thousands of arrays UGET annotates and prioritizes genes better than other tools especially with rare tissue disorders or complex multi-tissue biological processes. This information can be critical in prioritization of candidate genes for sequence analysis.