Schizophrenia (SZ) is a complex disorder resulting from both genetic and environmental causes with a lifetime prevalence world-wide of 1%; however, there are no specific, sensitive and validated biomarkers for SZ. A general unifying hypothesis has been put forward that disease-associated single nucleotide polymorphisms (SNPs) from genome-wide association study (GWAS) are more likely to be associated with gene expression quantitative trait loci (eQTL). We will describe this hypothesis and review primary methodology with refinements for testing this paradigmatic approach in SZ. We will describe biomarker studies of SZ and testing enrichment of SNPs that are associated both with eQTLs and existing GWAS of SZ. SZ-associated SNPs that overlap with eQTLs can be placed into gene–gene expression, protein–protein and protein–DNA interaction networks. Further, those networks can be tested by reducing/silencing the gene expression levels of critical nodes. We present pilot data to support these methods of investigation such as the use of eQTLs to annotate GWASs of SZ, which could be applied to the field of biomarker discovery. Those networks that have association with SNP markers, especially cis-regulated expression, might lead to a more clear understanding of important candidate genes that predispose to disease and alter expression. This method has general application to many complex disorders.
expression quantitative trait loci; cis-regulatory SNPs; GWAS; gene expression; lymphoblastoid cell lines
Schizophrenia and bipolar disorder together affect approximately 2.5% of the world population, and their etiologies are thought to involve multiple genetic variants and environmental influences. The analysis of gene expression patterns in brain may provide a characteristic signature for each disorder.
RNA samples from the dorsolateral prefrontal cortex (Brodmann area 46) consisting of individuals with schizophrenia (SZ), bipolar disorder (BPD), and control subjects were tested on the Codelink Human 20K Bioarray platform. Selected transcripts were validated by quantitative real-time polymerase chain reaction (PCR). The strong effects of age, gender, and pH in the analysis of differential gene expression were controlled by analysis of covariance (ANCOVA). Criteria for differential gene expression were 1) a gene was significantly dysregulated in both BPD and SZ compared with control subjects and 2) significant in ANCOVA analysis with samples that have a pH above the median of the sample.
A list of 78 candidate genes passed these two criteria in BPD and SZ and was overrepresented for functional categories of nervous system development, immune system development and response, and cell death. Five dysregulated genes were confirmed with quantitative Q-PCR in both BPD and SZ. Three genes were highly enriched in brain expression (AGXT2L1, SLC1A2, and TU3A). The distribution of AGXT2L1 expression in control subjects versus BPD and SZ was highly significant (Fisher’s Exact Test, p < 10−06).
These results suggest a partially shared molecular profile for both disorders and offer a window into discovery of common pathophysiology that might lead to core treatments.
AGXT2L1; antipsychotic medication; apoptosis; bipolar disorder; BUB1B; dorsolateral prefrontal cortex; EMX2; ERBB2; FGF2; FTH1; IL2RA; LGALS3; MAFG; microarray; neurogenesis; NFATC1; PVR; quantitative PCR; RERG; schizophrenia; SLC1A2; SMCY; SMO; SOX9; TU3A; TXNIP
Klinefelter’s Syndrome (KS) is a chromosomal karyotype with one or more extra X chromosomes. KS individuals often show language impairment and the phenotype might be due to overexpression of genes on the extra X chromosome(s). We profiled mRNA derived from lymphoblastoid cell lines from males with documented KS and control males using the Affymetrix U133P microarray platform. There were 129 differentially expressed genes (DEGs) in KS group compared with controls after Benjamini–Hochberg false discovery adjustment. The DEGs included 14 X chromosome genes which were significantly over-represented. The Y chromosome had zero DEGs. In exploratory analysis of gene expression–cognition relationships, 12 DEGs showed significant correlation of expression with measures of verbal cognition in KS. Overexpression of one pseudoautosomal gene, GTPBP6 (GTP binding protein 6, putative) was inversely correlated with verbal IQ (r = −0.86, P < 0.001) and four other measures of verbal ability. Overexpression of XIST was found in KS compared to XY controls suggesting that silencing of many genes on the X chromosome might occur in KS similar to XX females. The microarray findings for eight DEGs were validated by quantitative PCR. The 14 X chromosome DEGs were not differentially expressed in prior studies comparing female and male brains suggesting a dysregulation profile unique to KS. Examination of X-linked DEGs, such as GTPBP6, TAF9L, and CXORF21, that show verbal cognition–gene expression correlations may establish a causal link between these genes, neurodevelopment, and language function. A screen of candidate genes may serve as biomarkers of KS for early diagnosis.
XXY; XY; brain; lymphocytes; microarray; XIST; GTPBP6; TAF9L; CXORF21
The neural cell adhesion molecule (NCAM1) is a multifunction transmembrane protein involved in synaptic plasticity, neurodevelopment, and neurogenesis. Multiple NCAM1 proteins were differentially altered in bipolar disorder and schizophrenia. Single nucleotide polymorphisms (SNPs) in the NCAM1 gene were significantly associated with bipolar disorder in the Japanese population. Bipolar disorder and schizophrenia may share common vulnerability or susceptibility risk factors for shared features in each disorder.
Both SNPs and splice variants in the NCAM1 gene were analysed in bipolar disorder and schizophrenia. A case-control study design for association of SNPs and differential exon expression in the NCAM1 gene was used.
A genotypic association between bipolar disorder and SNP b (rs2303377 near mini-exon b) and a suggestive association between schizophrenia and SNP 9 (rs646558) were found. Three of the two marker haplotypes for SNP 9 and SNP b showed varying frequencies between bipolar and controls (P < 0.0001) as well as between schizophrenia and controls (P < 0.0001). There were nine NCAM1 transcripts present in postmortem brain samples that involve alternative splicing of NCAM1 mini-exons (a, b, c) and the secreted (SEC) exon. Significant differences in the amounts of four alternatively spliced isoforms were found between NCAM1 SNP genotypes. In exploratory analysis, the c—SEC alternative spliced isoform was significantly decreased in bipolar disorder compared to controls for NCAM1 SNP b heterozygotes (P = 0.013).
Diverse NCAM1 transcripts were found with possibly different functions. The results suggest that SNPs within NCAM1 contribute differential risk for both bipolar disorder and schizophrenia possibly by alternative splicing of the gene. Psychiatr Genet 17:55−67 © 2007 Lippincott Williams & Wilkins.
alternative splicing; association; bipolar disorder; genetics; neural cell adhesion molecule 1; schizophrenia; secreted-neural cell adhesion molecule 1; single nucleotide polymorphism; variable alternative spliced exon–secreted-neural cell adhesion molecule 1
Mood disorders and schizophrenia are common and complex disorders with consistent evidence of genetic and environmental influences on predisposition. It is generally believed that the consequences of disease, gene expression, and allelic heterogeneity may be partly the explanation for the variability observed in treatment response. Correspondingly, while effective treatments are available for some patients, approximately half of the patients fail to respond to current neuropsychiatric treatments. A number of peripheral gene expression studies have been conducted to understand these brain-based disorders and mechanisms of treatment response with the aim of identifying suitable biomarkers and perhaps subgroups of patients based upon molecular fingerprint. In this review, we summarize the results from blood-derived gene expression studies implemented with the aim of discovering biomarkers for treatment response and classification of disorders. We include data from a biomarker study conducted in first-episode subjects with schizophrenia, where the results provide insight into possible individual biological differences that predict antipsychotic response. It is concluded that, while peripheral studies of expression are generating valuable results in pathways involving immune regulation and response, larger studies are required which hopefully will lead to robust biomarkers for treatment response and perhaps underlying variations relevant to these complex disorders.
Gene expression changes in brains of individuals with schizophrenia (SZ) have been hypothesized to reflect possible pathways related to pathophysiology and/or medication. Other factors have robust effects on gene expression profiling in brain and possibly influence the schizophrenia transcriptome such as age and pH are examined. Pathways of curated gene expression or gene correlation networks reported in SZ (white matter, apoptosis, neurogenesis, synaptic plasticity, glutamatergic and GABAergic neurotransmission, immune and stress-response, mitochondrial, and neurodevelopment) are not unique to SZ and have been associated with other psychiatric disorders. Suggestions going forward to improve the next decade of profiling: consider multiple brain regions that are carefully dissected, release large datasets from multiple brain regions in controls to better understand neurocircuitry, integrate genetics and gene expression, measure expression variants on genome wide level, peripheral biomarker studies, and analyze the transcriptome across a developmental series of brains. Gene expression, while an important feature of the genomic landscape, requires further systems biology to advance from control brains to a more precise definition of the schizophrenia interactome.
microarray; gene expression; schizophrenia; bipolar disorder; psychiatry; gene-based biomarker discovery; next generation sequencing; allele specific expression; copy number variation
A missense polymorphism in the NRG1 gene, Val > Leu in exon 11, was reported to increase the risk of schizophrenia in selected families from the Central Valley region of Costa Rica (CVCR). The present study investigated the relationship between three NRG1 genetic variants, rs6994992, rs3924999, and Val > Leu missense polymorphism in exon 11, in cases and selected controls from an isolated population from the CVCR. Isolated populations can have less genetic heterogeneity and increase power to detect risk variants in candidate genes. Subjects with bipolar disorder (BD, n = 358), schizophrenia (SZ, n = 273), or unrelated controls (CO, n = 479) were genotyped for three NRG1 variants. The NRG1 promoter polymorphism (rs6994992) was related to altered expression of NRG1 Type IV in other studies. The expression of NRG1 type IV in the dorsolateral prefrontal cortex (DLPFC) and the effect of the rs6994992 genotype on expression were explored in a postmortem cohort of BD, SZ, major depressive disorder (MDD) cases, and controls. The missense polymorphism Val > Leu in exon 11 was not significantly associated with schizophrenia as previously reported in a family sample from this population, the minor allele frequency is 4%, thus our sample size is not large enough to detect an association. We observed however an association of rs6994992 with NRG1 type IV expression in DLPFC and a significantly decreased expression in MDD compared to controls. The present results while negative do not rule out a genetic association of these SNPs with BD and SZ in CVCR, perhaps due to small risk effects that we were unable to detect and potential intergenic epistasis. The previous genetic relationship between expression of a putative brain specific isoform of NRG1 type IV and SNP variation was replicated in postmortem samples in our preliminary study.
neuregulin 1 isoform expression; schizophrenia; isolated population; Costa Rica; bipolar disorder; major depressive disorder; hippocampus; dorsolateral prefrontal cortex
Mitochondrial deficiencies with unknown causes have been observed in schizophrenia (SZ) and bipolar disorder (BD) in imaging and postmortem studies. Polymorphisms and somatic mutations in mitochondrial DNA (mtDNA) were investigated as potential causes with next generation sequencing of mtDNA (mtDNA-Seq) and genotyping arrays in subjects with SZ, BD, major depressive disorder (MDD), and controls. The common deletion of 4,977 bp in mtDNA was compared between SZ and controls in 11 different vulnerable brain regions and in blood samples, and in dorsolateral prefrontal cortex (DLPFC) of BD, SZ, and controls. In a separate analysis, association of mitochondria SNPs (mtSNPs) with SZ and BD in European ancestry individuals (n = 6,040) was tested using Genetic Association Information Network (GAIN) and Wellcome Trust Case Control Consortium 2 (WTCCC2) datasets. The common deletion levels were highly variable across brain regions, with a 40-fold increase in some regions (nucleus accumbens, caudate nucleus and amygdala), increased with age, and showed little change in blood samples from the same subjects. The common deletion levels were increased in the DLPFC for BD compared to controls, but not in SZ. Full mtDNA genome resequencing of 23 subjects, showed seven novel homoplasmic mutations, five were novel synonymous coding mutations. By logistic regression analysis there were no significant mtSNPs associated with BD or SZ after genome wide correction. However, nominal association of mtSNPs (p < 0.05) to SZ and BD were found in the hypervariable region of mtDNA to T195C and T16519C. The results confirm prior reports that certain brain regions accumulate somatic mutations at higher levels than blood. The study in mtDNA of common polymorphisms, somatic mutations, and rare mutations in larger populations may lead to a better understanding of the pathophysiology of psychiatric disorders.
mitochondria; homoplasmy; common deletion; novel mutations; schizophrenia; bipolar disorder
The imaging genetics approach to studying the genetic basis of disease leverages the individual strengths of both neuroimaging and genetic studies by visualizing and quantifying the brain activation patterns in the context of genetic background. Brain imaging as an intermediate phenotype can help clarify the functional link among genes, the molecular networks in which they participate, and brain circuitry and function. Integrating genetic data from a genome-wide association study (GWAS) with brain imaging as a quantitative trait (QT) phenotype can increase the statistical power to identify risk genes. A QT analysis using brain imaging (DLPFC activation during a working memory task) as a quantitative trait has identified unanticipated risk genes for schizophrenia. Several of these genes (RSRC1, ARHGAP18, ROBO1-ROBO2, GPC1, CTXN3-SLC12A2) have functions related to progenitor cell proliferation, migration, and differentiation, axonal connectivity, and development of forebrain structures. These genes, however, do not function in isolation but rather through gene regulatory networks. To obtain a deeper understanding how the GWAS-identified genes participate in larger gene regulatory networks, we measured correlations among transcript levels in the mouse and human postmortem tissue, and performed a gene set enrichment analysis (GSEA). The results of such computational approaches can be further validated in animal experiments in which the networks are experimentally studied and perturbed with specific compounds. Glypican 1 and FGF17 mouse models can be used to study such gene regulatory networks. The model demonstrates epistatic interactions between FGF and glypican on brain development and may be a useful model of negative symptom schizophrenia.
Gender differences in brain development and in the prevalence of neuropsychiatric disorders such as depression have been reported. Gender differences in human brain might be related to patterns of gene expression. Microarray technology is one useful method for investigation of gene expression in brain. We investigated gene expression, cell types, and regional expression patterns of differentially expressed sex chromosome genes in brain. We profiled gene expression in male and female dorsolateral prefrontal cortex, anterior cingulate cortex, and cerebellum using the Affymetrix oligonucleotide microarray platform. Differentially expressed genes between males and females on the Y chromosome (DBY, SMCY, UTY, RPS4Y, and USP9Y) and X chromosome (XIST) were confirmed using real-time PCR measurements. In situ hybridization confirmed the differential expression of gender-specific genes and neuronal expression of XIST, RPS4Y, SMCY, and UTY in three brain regions examined. The XIST gene, which silences gene expression on regions of the X chromosome, is expressed in a subset of neurons. Since a subset of neurons express gender-specific genes, neural subpopulations may exhibit a subtle sexual dimorphism at the level of differences in gene regulation and function. The distinctive pattern of neuronal expression of XIST, RPS4Y, SMCY, and UTY and other sex chromosome genes in neuronal subpopulations may possibly contribute to gender differences in prevalence noted for some neuropsychiatric disorders. Studies of the protein expression of these sex- chromosome-linked genes in brain tissue are required to address the functional consequences of the observed gene expression differences.
RPS4Y; UTY; SMCY; XIST; DBY; USP9Y; VCX; VCY
The consistency of peripheral gene expression data and the overlap with brain expression has not been evaluated in biomarker discovery, nor has it been reported in multiple tissues from the same subjects on a genome wide transcript level. The effects of processing whole blood, transformation, and passaged cell lines on gene expression profiling was studied in healthy subjects using Affymetrix arrays. Ficoll extracted peripheral blood mononuclear cells (PBMCs), Epstein-Barr virus (EBV) transformed lymphocytes, passaged lymphoblastic cell lines (LCLs), and whole blood from Tempus tubes were compared. There were 6,813 transcripts differentially expressed between different methods of blood preparation. Principal component analysis resolved two partitions involving pre- and post-transformation EBV effects.
Combining results from Affymetrix arrays, postmortem subjects' brain and PBMC profiles showed co-expression levels of summarized transcripts for 4,103 of 17,859 (22.9%) RefSeq transcripts. In a control experiment, rat hemi-brain and blood showed similar expression levels for 19% of RefSeq transcripts. After filtering transcripts that were not significantly different in abundance between human cerebellum and PBMCs from the Affymetrix exon array the correlation in mean transcript abundance was high as expected (r = 0.98). Differences in the alternative splicing index in brain and blood were found for about 90% of all transcripts examined. This study demonstrates over 4,100 brain transcripts co-expressed in blood samples can be further examined by in vitro and in vivo experimental studies of blood and cell lines from patients with psychiatric disorders.
biomarker; gene expression; whole genome
Recent findings of mitochondrial abnormalities in brains from subjects with neurological disorders have led to a renewed search for mitochondrial abnormalities in psychiatric disorders. A growing body of evidence suggests that there is mitochondrial dysfunction in schizophrenia, bipolar disorder, and major depressive disorder, including evidence from electron microscopy, imaging, gene expression, genotyping, and sequencing studies. Specific evidence of dysfunction such as increased common deletion and decreased gene expression in mitochondria in psychiatric illnesses suggests that direct examination of mitochondrial DNA from postmortem brain cells may provide further details of mitochondrial alterations in psychiatric disorders.
Bipolar disorder; major depressive disorder; mitochondria; mtDNA; schizophrenia
There are major concerns that specific agonal conditions, including coma and hypoxia, might affect ribonucleic acid (RNA) integrity in postmortem brain studies. We report that agonal factors significantly affect RNA integrity and have a major impact on gene expression profiles in microarrays. In contrast to agonal factors, gender, age, and postmortem factors have less effect on gene expression profiles. The Average Correlation Index is proposed as a method for evaluating RNA integrity on the basis of similarity of microarray profiles. Reducing the variance due to agonal factors is critical in investigating small but validated gene expression differences in messenger RNA levels between psychiatric patients and control subjects.
Adenine; Uracil-rich elements; bipolar disorder; freezer interval; iron-responsive element; major depressive disorder; postmortem interval
Even though nicotine has been shown to modulate mRNA expression of a variety of genes, a comprehensive high-throughput study of the effects of nicotine on the tissue-specific gene expression profiles has been lacking in the literature. In this study, cDNA microarrays containing 1117 genes and ESTs were used to assess the transcriptional response to chronic nicotine treatment in rat, based on four brain regions, i.e. prefrontal cortex (PFC), nucleus accumbens (NAs), ventral tegmental area (VTA), and amygdala (AMYG). On the basis of a non-parametric resampling method, an index (called jackknifed reliability index, JRI) was proposed, and employed to determine the inherent measurement error across multiple arrays used in this study. Upon removal of the outliers, the mean correlation coefficient between duplicate measurements increased to 0.978±0.0035 from 0.941 ±0.045. Results from principal component analysis and pairwise correlations suggested that brain regions studied were highly similar in terms of their absolute expression levels, but exhibited divergent transcriptional responses to chronic nicotine administration. For example, PFC and NAs were significantly more similar to each other (r=0.7; P<10−14) than to either VTA or AMYG. Furthermore, we confirmed our microarray results for two representative genes, i.e. the weak inward rectifier K+ channel (TWIK-1), and phosphate and tensin homolog (PTEN) by using real-time quantitative RT-PCR technique. Finally, a number of genes, involved in MAPK, phosphatidylinositol, and EGFR signaling pathways, were identified and proposed as possible targets in response to nicotine administration. © 2001 Elsevier Science B.V. All rights reserved.
Microarray; Normalization; mRNA expression; Brain; Nicotine; Pathway
Abnormalities in the circadian clockwork often characterize patients with major depressive and bipolar disorders. Circadian clock genes are targets of interest in these patients. CRY2 is a circadian gene that participates in regulation of the evening oscillator. This is of interest in mood disorders where a lack of switch from evening to morning oscillators has been postulated.
We observed a marked diurnal variation in human CRY2 mRNA levels from peripheral blood mononuclear cells and a significant up-regulation (P = 0.020) following one-night total sleep deprivation, a known antidepressant. In depressed bipolar patients, levels of CRY2 mRNA were decreased (P = 0.029) and a complete lack of increase was observed following sleep deprivation. To investigate a possible genetic contribution, we undertook SNP genotyping of the CRY2 gene in two independent population-based samples from Sweden (118 cases and 1011 controls) and Finland (86 cases and 1096 controls). The CRY2 gene was significantly associated with winter depression in both samples (haplotype analysis in Swedish and Finnish samples: OR = 1.8, P = 0.0059 and OR = 1.8, P = 0.00044, respectively).
We propose that a CRY2 locus is associated with vulnerability for depression, and that mechanisms of action involve dysregulation of CRY2 expression.
Most studies investigating the neurobiology of depression and suicide have focused on the serotonergic system. While it seems clear that serotonergic alterations play a role in the pathogenesis of these major public health problems, dysfunction in additional neurotransmitter systems and other molecular alterations may also be implicated. Microarray expression studies are excellent screening tools to generate hypotheses about additional molecular processes that may be at play. In this study we investigated brain regions that are known to be implicated in the neurobiology of suicide and major depression are likely to represent valid global molecular alterations.
We performed gene expression analysis using the HG-U133AB chipset in 17 cortical and subcortical brain regions from suicides with and without major depression and controls. Total mRNA for microarray analysis was obtained from 663 brain samples isolated from 39 male subjects, including 26 suicide cases and 13 controls diagnosed by means of psychological autopsies. Independent brain samples from 34 subjects and animal studies were used to control for the potential confounding effects of comorbidity with alcohol. Using a Gene Ontology analysis as our starting point, we identified molecular pathways that may be involved in depression and suicide, and performed follow-up analyses on these possible targets. Methodology included gene expression measures from microarrays, Gene Score Resampling for global ontological profiling, and semi-quantitative RT-PCR. We observed the highest number of suicide specific alterations in prefrontal cortical areas and hippocampus. Our results revealed alterations of synaptic neurotransmission and intracellular signaling. Among these, Glutamatergic (GLU) and GABAergic related genes were globally altered. Semi-quantitative RT-PCR results investigating expression of GLU and GABA receptor subunit genes were consistent with microarray data.
The observed results represent the first overview of global expression changes in brains of suicide victims with and without major depression and suggest a global brain alteration of GLU and GABA receptor subunit genes in these conditions.
Gene expression changes in neuropsychiatric and neurodegenerative disorders, and gene responses to therapeutic drugs, provide new ways to identify central nervous system (CNS) targets for drug discovery. This review summarizes gene and pathway targets replicated in expression profiling of human postmortem brain, animal models, and cell culture studies. Analysis of isolated human neurons implicates targets for Alzheimer’s disease and the cognitive decline associated with normal aging and mild cognitive impairment. In addition to τ, amyloid-β precursor protein, and amyloid-β peptides (Aβ), these targets include all three high-affinity neurotrophin receptors and the fibroblast growth factor (FGF) system, synapse markers, glutamate receptors (GluRs) and transporters, and dopamine (DA) receptors, particularly the D2 subtype. Gene-based candidates for Parkinson’s disease (PD) include the ubiquitin–proteosome system, scavengers of reactive oxygen species, brain-derived neurotrophic factor (BDNF), its receptor, TrkB, and downstream target early growth response 1, Nurr-1, and signaling through protein kinase C and RAS pathways. Increasing variability and decreases in brain mRNA production from middle age to old age suggest that cognitive impairments during normal aging may be addressed by drugs that restore antioxidant, DNA repair, and synaptic functions including those of DA to levels of younger adults. Studies in schizophrenia identify robust decreases in genes for GABA function, including glutamic acid decarboxylase, HINT1, glutamate transport and GluRs, BDNF and TrkB, numerous 14-3-3 protein family members, and decreases in genes for CNS synaptic and metabolic functions, particularly glycolysis and ATP generation. Many of these metabolic genes are increased by insulin and muscarinic agonism, both of which are therapeutic in psychosis. Differential genomic signals are relatively sparse in bipolar disorder, but include deficiencies in the expression of 14-3-3 protein members, implicating these chaperone proteins and the neurotransmitter pathways they support as possible drug targets. Brains from persons with major depressive disorder reveal decreased expression for genes in glutamate transport and metabolism, neurotrophic signaling (eg, FGF, BDNF and VGF), and MAP kinase pathways. Increases in these pathways in the brains of animals exposed to electroconvulsive shock and antidepressant treatments identify neurotrophic and angiogenic growth factors and second messenger stimulation as therapeutic approaches for the treatment of depression.
microarray; gene expression; schizophrenia; bipolar disorder; depression; Alzheimer’s disease; Parkinson’s disease
Mitochondria provide most of the energy for brain cells by the process of oxidative phosphorylation. Mitochondrial abnormalities and deficiencies in oxidative phosphorylation have been reported in individuals with schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD) in transcriptomic, proteomic, and metabolomic studies. Several mutations in mitochondrial DNA (mtDNA) sequence have been reported in SZ and BD patients.
Dorsolateral prefrontal cortex (DLPFC) from a cohort of 77 SZ, BD, and MDD subjects and age-matched controls (C) was studied for mtDNA sequence variations and heteroplasmy levels using Affymetrix mtDNA resequencing arrays. Heteroplasmy levels by microarray were compared to levels obtained with SNaPshot and allele specific real-time PCR. This study examined the association between brain pH and mtDNA alleles. The microarray resequencing of mtDNA was 100% concordant with conventional sequencing results for 103 mtDNA variants. The rate of synonymous base pair substitutions in the coding regions of the mtDNA genome was 22% higher (p = 0.0017) in DLPFC of individuals with SZ compared to controls. The association of brain pH and super haplogroup (U, K, UK) was significant (p = 0.004) and independent of postmortem interval time.
Focusing on haplogroup and individual susceptibility factors in psychiatric disorders by considering mtDNA variants may lead to innovative treatments to improve mitochondrial health and brain function.
Multiple linkage regions have been reported in schizophrenia, and some appear to harbor susceptibility genes that are differentially expressed in postmortem brain tissue derived from unrelated individuals. We combined traditional genome-wide linkage analysis in a multiplex family with lymphocytic genome-wide expression analysis. A genome scan suggested linkage to a chromosome 4q marker (D4S1530, LOD 2.17, θ=0) using a dominant model. Haplotype analysis using flanking microsatellite markers delineated a 14 Mb region that cosegregated with all those affected. Subsequent genome-wide scan with SNP genotypes supported the evidence of linkage to 4q33−35.1 (LOD=2.39) using a dominant model. Genome-wide microarray analysis of five affected and five unaffected family members identified two differentially expressed genes within the haplotype AGA and GALNT7 (aspartylglucosaminidase and UDP-N-acetyl-alpha-d-galactosamine: polypeptide N-acetylgalactosaminyltransferase 7) with nominal significance; however, these genes did not remain significant following analysis of covariance. We carried out genome-wide linkage analyses between the quantitative expression phenotype and genetic markers. AGA expression levels showed suggestive linkage to multiple markers in the haplotype (maximum LOD=2.37) but to no other genomic region. GALNT7 expression levels showed linkage to regulatory loci at 4q28.1 (maximum LOD=3.15) and in the haplotype region at 4q33−35.1 (maximum LOD=2.37). ADH1B (alcohol dehydrogenase IB) was linked to loci at 4q21–q23 (maximum LOD=3.08) and haplotype region at 4q33−35.1 (maximum LOD=2.27). Seven differentially expressed genes were validated with RT-PCR. Three genes in the 4q33−35.1 haplotype region were also differentially expressed in schizophrenia in postmortem dorsolateral prefrontal cortex: AGA, HMGB2, and SCRG1. These results indicate that combining differential gene expression with linkage analysis may help in identifying candidate genes and potential regulatory sites. Moreover, they also replicate recent findings of complex trans- and cis- regulation of genes.
Gene expression patterns in the brain are strongly influenced by the severity and duration of physiological stress at the time of death. This agonal effect, if not well controlled, can lead to spurious findings and diminished statistical power in case-control comparisons. While some recent studies match samples by tissue pH and clinically recorded agonal conditions, we found that these indicators were sometimes at odds with observed stress-related gene expression patterns, and that matching by these criteria still sometimes results in identifying case-control differences that are primarily driven by residual agonal effects. This problem is analogous to the one encountered in genetic association studies, where self-reported race and ethnicity are often imprecise proxies for an individual's actual genetic ancestry.
We developed an Agonal Stress Rating (ASR) system that evaluates each sample's degree of stress based on gene expression data, and used ASRs in post hoc sample matching or covariate analysis. While gene expression patterns are generally correlated across different brain regions, we found strong region-region differences in empirical ASRs in many subjects that likely reflect inter-individual variabilities in local structure or function, resulting in region-specific vulnerability to agonal stress.
Variation of agonal stress across different brain regions differs between individuals, revealing a new level of complexity for gene expression studies of brain tissues. The Agonal Stress Ratings quantitatively assess each sample's extent of regulatory response to agonal stress, and allow a strong control of this important confounder.
CNS-focused cDNA microarrays were used to examine gene expression profiles in dorsolateral prefrontal cortex (dlPFC, Area 46) from seven sets of individually age- and postmortem interval-5 matched male cocaine abusers and controls. The presence of cocaine and related metabolites was confirmed by gas chromatography-mass spectrometry.
Sixty-five transcripts were differentially expressed, indicating alterations in energy metabolism, mitochondria and oligodendrocyte function, cytoskeleton and related signaling, and neuronal plasticity. There was evidence for two distinct states of transcriptional regulation, with increases 10 in gene expression predominating in subjects testing positive for a metabolite indicative of recent "crack" cocaine abuse and decreased expression profiles in the remaining cocaine subjects. This pattern was confirmed by quantitative PCR for select transcripts.
These data suggest that cocaine abuse targets a distinct subset of genes in the dlPFC, resulting in either a state of acute activation in which increased gene expression predominates, or a relatively 15 de-stimulated, refractory phase.
addiction; expression patterns; gene profiling; neuroplasticity; psychostimulants
Whole-genome and exome sequencing have already proven to be essential and powerful methods to identify genes responsible for simple Mendelian inherited disorders. These methods can be applied to complex disorders as well, and have been adopted as one of the current mainstream approaches in population genetics. These achievements have been made possible by next generation sequencing (NGS) technologies, which require substantial bioinformatics resources to analyze the dense and complex sequence data. The huge analytical burden of data from genome sequencing might be seen as a bottleneck slowing the publication of NGS papers at this time, especially in psychiatric genetics. We review the existing methods for processing NGS data, to place into context the rationale for the design of a computational resource. We describe our method, the Graphical Pipeline for Computational Genomics (GPCG), to perform the computational steps required to analyze NGS data. The GPCG implements flexible workflows for basic sequence alignment, sequence data quality control, single nucleotide polymorphism analysis, copy number variant identification, annotation, and visualization of results. These workflows cover all the analytical steps required for NGS data, from processing the raw reads to variant calling and annotation. The current version of the pipeline is freely available at http://pipeline.loni.ucla.edu. These applications of NGS analysis may gain clinical utility in the near future (e.g., identifying miRNA signatures in diseases) when the bioinformatics approach is made feasible. Taken together, the annotation tools and strategies that have been developed to retrieve information and test hypotheses about the functional role of variants present in the human genome will help to pinpoint the genetic risk factors for psychiatric disorders.
Next Generation Sequencing (NGS); LONI pipeline; SNPs; CNVs; workflow; bioinformatics
Rapid cycling is a severe form of bipolar disorder with an increased rate of episodes that is particularly treatment-responsive to chronotherapy and stable sleep-wake cycles. We hypothesized that the P2RX7 gene would be affected by sleep deprivation and be implicated in rapid cycling.
To assess whether P2RX7 expression is affected by total sleep deprivation and if variation in P2RX7 is associated with rapid cycling in bipolar patients.
Gene expression analysis in peripheral blood mononuclear cells (PBMCs) from healthy volunteers and case-case and case-control SNP/haplotype association analyses in patients.
Healthy volunteers at the sleep research center, University of California, Irvine Medical Center (UCIMC), USA (n = 8) and Swedish outpatients recruited from specialized psychiatric clinics for bipolar disorder, diagnosed with bipolar disorder type 1 (n = 569; rapid cycling: n = 121) and anonymous blood donor controls (n = 1,044).
P2RX7 RNA levels were significantly increased during sleep deprivation in PBMCs from healthy volunteers (p = 2.3*10−9). The P2RX7 rs2230912 _A allele was more common (OR = 2.2, p = 0.002) and the ACGTTT haplotype in P2RX7 (rs1718119 to rs1621388) containing the protective rs2230912_G allele (OR = 0.45–0.49, p = 0.003–0.005) was less common, among rapid cycling cases compared to non-rapid cycling bipolar patients and blood donor controls.
Sleep deprivation increased P2RX7 expression in healthy persons and the putatively low-activity P2RX7 rs2230912 allele A variant was associated with rapid cycling in bipolar disorder. This supports earlier findings of P2RX7 associations to affective disorder and is in agreement with that particularly rapid cycling patients have a more vulnerable diurnal system.
Suicidal behaviors are frequent in mood disorders patients but only a subset of them ever complete suicide. Understanding predisposing factors for suicidal behaviors in high risk populations is of major importance for the prevention and treatment of suicidal behaviors. The objective of this project was to investigate gene expression changes associated with suicide in brains of mood disorder patients by microarrays (Affymetrix HG-U133 Plus2.0) in the dorsolateral prefrontal cortex (DLPFC: 6 Non-suicides, 15 suicides), the anterior cingulate cortex (ACC: 6NS, 9S) and the nucleus accumbens (NAcc: 8NS, 13S). ANCOVA was used to control for age, gender, pH and RNA degradation, with P≤0.01 and fold change±1.25 as criteria for significance. Pathway analysis revealed serotonergic signaling alterations in the DLPFC and glucocorticoid signaling alterations in the ACC and NAcc. The gene with the lowest p-value in the DLPFC was the 5-HT2A gene, previously associated both with suicide and mood disorders. In the ACC 6 metallothionein genes were down-regulated in suicide (MT1E, MT1F, MT1G, MT1H, MT1X, MT2A) and three were down-regulated in the NAcc (MT1F, MT1G, MT1H). Differential expression of selected genes was confirmed by qPCR, we confirmed the 5-HT2A alterations and the global down-regulation of members of the metallothionein subfamilies MT 1 and 2 in suicide completers. MTs 1 and 2 are neuro-protective following stress and glucocorticoid stimulations, suggesting that in suicide victims neuroprotective response to stress and cortisol may be diminished. Our results thus suggest that suicide-specific expression changes in mood disorders involve both glucocorticoids regulated metallothioneins and serotonergic signaling in different regions of the brain.
Major mood disorders have been linked to abnormalities in circadian rhythms, leading to disturbances in sleep, mood, temperature, and hormonal levels. We provide evidence that ketamine, a drug with rapid antidepressant effects, influences the function of the circadian molecular machinery. Ketamine modulates CLOCK:BMAL1-mediated transcriptional activation when these regulators are ectopically expressed in NG108-15 neuronal cells. Inhibition occurs in a dose-dependent manner and is attenuated after treatment with the GSK3β antagonist SB21673. We analyzed the effect of ketamine on circadian gene expression and observed a dose-dependent reduction in the amplitude of circadian transcription of the Bmal1, Per2, and Cry1 genes. Finally, chromatin-immunoprecipitation analyses revealed that ketamine altered the recruitment of the CLOCK:BMAL1 complex on circadian promoters in a time-dependent manner. Our results reveal a yet unsuspected molecular mode of action of ketamine and thereby may suggest possible pharmacological antidepressant strategies.