Context GAD67 regulation involves a network of genes implicated in schizophrenia and bipolar disorder. We have studied the copy number intensities of these genes in specific hippocampal subregions to clarify whether abnormalities of genomic integrity covary with gene expression in a circuitry-based manner.
Objective To compare the copy number intensities of genes associated with GAD67 regulation in the stratum oriens of sectors CA3/2 and CA1 in patients with schizophrenia, patients with bipolar disorder, and healthy controls.
Design Samples of sectors CA3/2 and CA1 were obtained from patients with schizophrenia, patients with bipolar disorder, and healthy controls. Genomic integrity was analyzed using microarrays, and the copy number intensities identified were correlated with the gene expression profile from a subset of these cases previously reported.
Setting Harvard Brain Tissue Resource Center at McLean Hospital, Belmont, Massachusetts.
Patients A total of 15 patients with schizophrenia, 15 patients with bipolar disorder, and 15 healthy controls.
Main Outcome Measures The copy number intensities for 28 target genes were individually examined using single-nucleotide polymorphism microarrays and correlated with homologous messenger RNA (mRNA) fold changes.
Results The copy number intensities examined using both microarrays and quantitative real-time polymerase chain reaction for the GAD67 gene were significantly decreased in sector CA3/2 of patients with schizophrenia and patients with bipolar disorder. Other genes associated with GAD67 regulation also showed changes in copy number intensities, and these changes were similar in magnitude and direction to those previously reported for mRNA fold changes in sector CA3/2 but not sector CA1. Moreover, the copy number intensities and mRNA fold changes were significantly correlated for both patients with schizophrenia (r = 0.649; P = .0003) and patients with bipolar disorder (r = 0.772; P = .0002) in sector CA3/2 but not in sector CA1.
Conclusion Insertions and deletions of genomic DNA in γ-aminobutyric acid cells at a key locus of the hippocampal circuit are reflected in transcriptional changes in GAD67 regulation that are circuitry-based and diagnosis-specific.
Copy number abnormalities have been found in genomic material from patients with many different brain disorders.1-11 However, their significance for understanding the heritability and/or pathophysiology of such illnesses is not understood. The present study has attempted to explore this question by analyzing copy number intensities in laser-microdissected samples of the hippocampus from patients with schizophrenia and patients with bipolar disorder. In both disorders, dysfunction of γ-aminobutyric acid (GABA)–ergic cells has been inferred from the finding of decreased expression of the glutamic acid decarboxylase 67 kD isoform (GAD67), a key marker for GABAergic function.12-15 There is a network of genes associated with the regulation of GAD67.16 This network appears to interact with other functional gene clusters, such as neurogenesis, cell cycle regulation, and the DNA damage response.17 Together, the latter 3 clusters play a critical role in maintaining genomic integrity, by detecting and repairing insertions, deletions, or perhaps even sequence rearrangements. If not repaired, such changes could theoretically result in the abnormal transcriptional regulation of genes associated with the regulation of GAD67.
In our study, samples have been obtained from the stratum oriens of sectors CA3/2 and CA1 (eFigure 1), a layer of the hippocampus in which GABA cells are the exclusive neuronal cell type. A preponderance of postmortem abnormalities in patients with schizophrenia and in patients with bipolar disorder have been found in sector CA3/2.18,19 These samples have been subjected to a microarray-based analysis of copy number intensities for 28 candidate genes involved in GAD67 regulation, neurogenesis, cell cycle regulation, and the DNA damage response. The results presented demonstrate that there are highly significant changes in the magnitude and direction of copy number intensities for specific target genes associated with GAD67 regulation in patients with schizophrenia and patients with bipolar disorder. Additionally, these copy number intensities show parallel variations in the expression of the respective messenger RNAs (mRNAs) for these target genes. To our knowledge, this is the first demonstration that disturbances in genomic integrity may contribute to GABA cell dysfunction in schizophrenia and bipolar disorder. Changes in copy number intensities vary in accordance with the disturbances in the expression of mRNAs associated with GAD67 regulation, but the patterns seen are fundamentally different for patients with schizophrenia and patients with bipolar disorder, suggesting that these changes occur in a circuitry-based and diagnosis-specific manner.
For the analyses of copy number intensities, postmortem samples of hippocampi from 15 healthy controls, 15 patients with schizophrenia, and 15 patients with bipolar disorder were obtained from the Harvard Brain Tissue Resource Center at McLean Hospital in Belmont, Massachusetts. The cases were group-matched for age, postmortem disorder, hemisphere, sex, and tissue pH (eTable). A subset of these cases (7 in each group) were described in an earlier microarray-based study,16 and the data from these cases were used to associate gene expression changes for the target genes with the respective copy number intensities obtained in the present study. Psychiatric diagnoses were established using a retrospective review of medical records and an extensive family questionnaire that includes information about medical history, psychiatric condition, and social demographics. The diagnosis of schizophrenia was made using the criteria of Feighner et al,20 whereas the diagnosis of bipolar disorder was made according to DSM-III-R criteria.
Sections (20 μm) were cut from a paraffin block using with a Jung RM2025 microtome and mounted on Leica frame slides. The sections were then deparaffinized and rehydrated in a graded series of xylene and ethanol. Nissl-stained sections were examined microscopically to ensure that each was cut in a transverse plane through the hippocampus and that all of the typical cytoarchitectonic features were present. A laser-microdissected apparatus was used to sample the stratum oriens of sectors CA2/3 and CA1. Because of the hypothesis-driven design of our study, we chose to contrast the findings in the stratum oriens of CA3/2 with those of sector CA1, which is also a layer in which GABA cells are the exclusive neuronal cell type.21 This layer in CA1 is, however, uniquely different from its homologue in CA3/2 in terms of its cytoarchitectonic detail, connectivity,22 functional integration,23 and gene expression patterns.17,21,24 For these reasons, we chose the stratum oriens of sector CA1 as a comparison site for changes in genomic integrity and mRNA expression in hippocampal GABA cells. There are approximately 3 times as many glial nuclei than neuronal nuclei in the stratum oriens of both sectors. Neurons are readily distinguishable from glia by their Nissl-positive cytoplasm and dendrites, their euchromatin content, and the size of their cell bodies, which are typically much larger. Glial nuclei show a predominance of heterochromatin, which is associated with gene silencing.25 These observations, together with our in situ hybridization studies of this layer, have suggested that very little gene expression is occurring in the glial cells at this locus.
Dna extraction and array hybridization
A QIAamp DNA FFPE Tissue Kit (Qiagen) was used to extract genomic DNA from formalin-fixed, paraffin-embedded tissue. After extraction, the whole genome was amplified with a REPLI-g kit (Qiagen). DNA digestion, labeling, and hybridization were performed according to the manufacturer's instructions. In brief, genomic DNA (500 ng) is digested with Nsp I and Sty I restriction enzymes and ligated to adaptors that recognize the cohesive 4–base pair (bp) overhangs. All fragments resulting from restriction enzyme digestion were substrates for adaptor ligation. A generic primer that recognizes the adaptor sequence was used to amplify adaptor-ligated DNA fragments. Polymerase chain reaction (PCR) conditions were optimized to preferentially amplify fragments in the 200- to 1100-bp size range. The PCR amplification products for each restriction enzyme digest were combined and purified using polystyrene beads. The amplified DNA was then fragmented, labeled, and hybridized to Affymetrix Genome-Wide Human SNP Array 6.0. After the arrays were washed and stained, the copy number intensities were analyzed.
The scanned images of single-nucleotide polymorphism (SNP) arrays were analyzed using the Affymetrix Genotyping Console 2.0 and the Affymetrix Genotyping Tools software. Although copy number variants are commonly used as an end point in genetic studies of large populations or in searches for risk genes, copy number intensities provide greater sensitivity and more robust findings than the rounded-off ratios that result from analyses of copy number variants. The copy number intensities were determined according to the hybridization intensity data generated from each SNP probe using dChip software.26 To calculate mean copy number values for selected regions, the output of the SNP probe intensities were exported to Excel (Microsoft). Copy number intensity changes were measured by comparing the hybridization intensities of healthy controls with those of the patients with schizophrenia or bipolar disorder.
Verification of gene copy numbers by quantitative real-time pcr
To validate copy number intensity changes identified by SNP arrays, we performed quantitative real-time PCR for GAD67 using genomic DNA (gDNA) from 6 controls, 6 patients with schizophrenia, and 6 patients with bipolar disorder. GAD67 gene probes was purchased from Applied Biosystems (the probes' identification numbers are Hs 01242242_cn and Hs 01602806_cn). Each 20-μL assay contained 10 ng of gDNA, 900nM each of forward and reverse primers for the reference gene (RNaseP) and for the target gene, 250nM each of the VIC dye (reference)–labeled and FAM dye (target)–labeled gene-specific probe in 1× TaqMan Gene Expression Master Mix. Individual samples were run in triplicate. Real-time data were collected by the OPTICON software. Quantitative real-time PCR data were analyzed using the relative quantification or ΔΔCt method27 based on DNA copy number ratio of a target gene vs reference gene in a given patient sample relative to matched healthy control sample. Relative quantity (RQ) is 2−ΔΔCt, and the copy number is 2 × RQ.
GraphPad Prism version 4.0 software was used for statistical analysis. The Fisher exact test and the 1-way analysis of variance with the Tukey post hoc test were used to evaluate differences in copy number for each target gene in the healthy control, schizophrenia, and bipolar disorder groups. Copy number intensities were also correlated with microarray-based gene expression data obtained in an earlier study16 in which an identical subset of cases was included.
Copy number intensities in patients with schizophrenia or bipolar disorder
Genomic copy numbers were determined by calculating the median signal intensities of the healthy controls, the patients with schizophrenia, and the patients with bipolar disorder with respect to normal reference DNAs. As shown in Figure 1, the GAD67- containing segment at the 2q24.3-2q31.1 chromosomal locus spanned approximately 14.2 megabases. The mean copy number intensity at the GAD67 -containing locus was 28% lower in the patients with schizophrenia than in the healthy controls. Similarly, lower numbers (15%) also occurred in the CA1 sector of the patients with schizophrenia at the same locus. Patients with bipolar disorder did not show differences in copy number intensities at the 2q24.3-2q31.1 locus in either sector (Figure 1).
Copy number intensities and specific target genes
The analysis of copy number intensities for 28 different target genes associated with the GAD67 regulatory network (n = 14), neurogenesis (n = 4), cell cycle regulation (n = 5), and the DNA damage response (n = 5) for sectors CA3/2 and CA1 are shown in Table 1 and Table 2, respectively. The overall sequence and its specific chromosomal locus are indicated for each gene in Tables 1 and 2. The genes that were chosen as targets for our study satisfied 2 criteria: (1) they must have shown significant differences in gene expression (fold changes),17,21,24 and (2) the genes must be associated directly or indirectly with the GAD67 regulatory network that was derived from a network association analysis.21 Some of the genes that are associated with this network (such as DLX1 and DLX2)28 and that play an important role in the development and function of GABA cells were not included because they did not show expression changes, and fell below the level of detection because of their very low abundance in the stratum oriens of sectors CA3/2 and CA1 of the human hippocampus.
Significant changes in copy number intensity in GAD67 regulatory genes were observed in 9 of 14 patients with schizophrenia (64%) and in 7 of 14 patients with bipolar disorder (50%) (Tables 1 and 2). The mean CNI for this gene was also decreased by 22% and 25%, respectively, in patients with schizophrenia and patients with bipolar disorder. In sector CA1, however, 50% of patients with schizophrenia showed significant CNI changes in GAD67 regulatory genes, whereas the patients with bipolar disorder showed no changes (Tables 1 and 2).
Heat maps of copy number intensities for specific chromosomal loci were plotted for several genes in the GAD67 regulatory network (Figure 1). As suggested by our earlier gene expression profile (GEP) study,21GAD67 expression was significantly decreased in sector CA3/2 of patients with schizophrenia and patients with bipolar disorder (Table 1). As shown in Figure 2A, the SNP arrays for GAD67, HDAC11, DAXX, PAX5, RUNX2, and CCND2 showed changes in copy number intensities in patients with schizophrenia and patients with bipolar disorder that are remarkably similar to those previously reported for a GEP study21 at this same locus of CA3/2. For example, GAD67 expression is reduced in both patients with schizophrenia and patients with bipolar disorder, HDAC11 and DAXX expression increased only in patients with schizophrenia, and both PAX5 and RUNX2 expression significantly decreased in patients with bipolar disorder. Two exceptions are PAX5, for which expression was only significantly lower in patients with bipolar disorder, and CCND2, for which transcripts were increased in patients with schizophrenia at this locus (Figure 2A). In the CA1 sector, copy number intensities for GAD67 are significantly decreased only for patients with schizophrenia, not for patients with bipolar disorder (Figure 2B), but this pattern is virtually identical to that seen for the GEP findings previously reported for the same cases.16 Copy number intensities for HDAC11 increased by 78% (Table 2), but the copy number intensities for the other genes do not show significant changes.
Copy number intensities for GAD65 (GAD2), GRIK1, RUNX2, PAX5, and SMAD4 were also decreased in the CA3/2 sector of patients with schizophrenia, whereas GRIK2, GRIK3, HDAC11, and DAXX all had higher copy number intensities. As shown in Table 3, the copy number intensity changes for these target genes in the CA3/2 sector of patients with schizophrenia were similar in direction to those reported with a GEP.16,21 In the CA3/2 sector of patients with bipolar disorder (Table 1), the copy numbers of GRIK1, GRIK2, GAD65, LEF1, DAXX, RUNX2, and PAX5 were also decreased, and most showed a direction of change consistent with the earlier GEP data for these same genes21 (Table 3).
The 4 genes in the neurogenesis cluster were chosen because they had shown significant changes in their GEPs, and our modeling suggested that they are probably important to the regulation of the cell cycle.19FGF3,29FGF9,30,31VEGF,32 and NRG133 are key players in the growth and differentiation of a wide variety of cells and tissues, including the hippocampus,34 and are believed to increase the risk for schizophrenia.35,36 In CA3/2 sector of patients with bipolar disorder, these genes showed significant decreases in copy number intensity, and these changes occurred in the same direction as those observed when a GEP was undertaken (Table 3). In the patients with schizophrenia, VEGF showed increases of copy number intensity in the CA3/2 sector, and this direction of change is similar to that seen in the GEPs for the same genes. NRG1 showed significant reductions in copy number intensity; however, the transcripts for this gene were significantly changed in the opposite direction for the GEP data (Table 3).
Cell Cycle and DNA Damage Response
Copy number intensities for cell cycle regulation and the DNA damage response showed significant changes in the CA3/2 sector of patients with schizophrenia and patients with bipolar disorder (Table 1). The copy number intensity of E2F3 in patients with schizophrenia was significantly reduced, and this change was in the same direction as that observed for transcripts in the GEP study.21 The patients with bipolar disorder showed only 1 gene (MBD4) with significant changes in copy number intensity and gene expression, both of which were increased; however, this similar change was seen for this gene in sectors CA3/2 and CA1 of both groups of patients. Overall, the changes observed for copy number intensities in the cell cycle and DNA damage response categories showed much less consistency when compared with the GEP data for these same genes.
To validate the copy number intensity changes identified by SNP array, we performed quantitative PCR analysis for the candidate gene GAD67 using gDNA from microdissected tissues (obtained from 6 patients with schizophrenia, 6 patients with bipolar disorder, and 6 healthy controls). In sector CA3/2, the copy number for the GAD67 gene also decreased by 34% and 37%, respectively, in patients with schizophrenia and patients with bipolar disorder, which is in complete agreement with the SNP data. In sector CA1, the copy number for the GAD67 gene decreased by 59% in patients with schizophrenia, although there was only a 10% decrease in patients with bipolar disorder (eFigure 2). These results have demonstrated the overall validity of the copy number status determined by SNP microarrays, and they also establish that GAD67 is the gene with one of the most frequent genetic alterations in schizophrenia and bipolar disorder.
Association analysis between copy number intensities and gene expression
Do DNA copy number intensities reflect gene expression patterns that we have identified in patients with schizophrenia and patients with bipolar disorder within the loci of interest? In sector CA3/2 of both the schizophrenia and bipolar disorder groups, the majority of target genes showed abnormally high or low levels of mRNA expression, whereas in sector CA1, both groups showed a paucity of significant expression changes (Table 3). When decreases or increases of copy numbers are observed, the changes seen could be related to either deletions or duplications, respectively, of chromatin material. The genes showing significant correlations between copy number intensities and gene expression for the GAD67 regulatory genes (Figure 3) were generally quite different for the schizophrenia and bipolar disorder groups. As shown in Table 3, the patients with bipolar disorder showed no expression changes for GRIK3, DAXX, HDAC11, TGFB2, and TGFBR1, whereas all of the other genes showed significant expression changes. In patients with schizophrenia, RUNX2, LEF1, PAX5, and SMAD4 did not show expression changes. Overall, there was a diagnostic selectivity for the target genes associated with decreased GAD67 expression in schizophrenia vs bipolar disorder.21
When the GEP data and the copy number intensity data (Table 3) were analyzed using linear regression analyses (Figure 3), a robust correlation was observed when both groups of patients were combined (r = 0.692; P = .0001) or when the patients with schizophrenia (r = 0.649; P = .0003) and the patients with bipolar disorder (r = 0.772; P = .0002) were separately compared with the healthy controls (Figure 3). For a majority of the target genes, the changes in copy number intensities and the fold changes tended to occur in the same direction, although the magnitudes of the respective changes were, in some instances, dramatically different. For example, mRNA expression for FGF9 was decreased 11-fold in patients with bipolar disorder, whereas the loss of copy number intensity for this gene was only 20%. Disparities of this type contributed to the variance in the data and resulted in a reduction in the r correlation coefficient, even when the correlations were statistically significant.
As shown in Table 4 and Figure 4, when the target genes were separated according to those directly related to the GAD67 regulatory network and those not related to it (ie, genes associated with growth factors, cell cycle, and DNA repair), much higher correlations between copy number intensity changes and mRNA levels were observed in the former (r = 0.712; P = .0001) than in the latter (r = 0.492; P = .008) of sector CA3/2 but not sector CA1 (r = 0.067 and r = 0.225, respectively). These data suggest that the expression of genes in the GAD67 network in the CA3/2 sector is tightly linked to the status of genomic integrity at this locus.
The linear regression analyses of target genes in sector CA1 did not reveal any correlation between gene expression and copy number intensity changes. There are many genes showing notable expression changes but no copy number intensity changes, suggesting that a dissociation between copy number intensities and gene expression changes may occur in sector CA1. As with sector CA3/2, however, a subset of genes in sector CA1 not related to GAD67 regulation did not show correlations with copy number intensities (Figure 4). These results demonstrate a striking subregional difference in the association of copy number intensities with gene expression changes.
There is increasing evidence supporting the involvement of copy number variants in the etiology of schizophrenia,9,37-39 although it is not clear what mechanisms may be related to these changes. Most of these reports have employed genome-wide screening for copy number variants, and only a few have concentrated on specific target genes.40 Although there have been preliminary attempts at linking copy number variants with expression data for specific genes in cancer research,41,42 to date, no study of the brain has attempted to associate the occurrence of copy number intensities for specific target genes with the expression of their respective mRNAs. The results described herein suggest that copy number intensity changes for specific target genes and their associated mRNAs vary not only in a diagnosis-specific way but also in a circuitry-based manner.
GAD67 plays an important role in the activity of GABA neurons and their dysfunction in schizophrenia. Although one association study37 concluded that there was a link between the GAD67 gene and childhood-onset schizophrenia, another study,43 using a Danish cohort, provides evidence that, in this sample, there is no link to schizophrenia but, possibly, a link to bipolar disorder. Another gene, neuregulin 1 (NRG1), may be functionally involved in the regulation of GAD67 activity.44 Interestingly, NRG1 also showed significant changes in both copy number intensity and gene expression, in patients with schizophrenia and patients with bipolar disorder. This gene appears to have a weak association with schizophrenia when haplotype-based P values were included in the analyses, and there was no evidence of between-study heterogeneity.45 These studies underscore the difficulties inherently present when attempting to relate copy number intensities derived from blood samples in population studies to copy number intensities obtained from brain tissue in studies of the molecular regulation of neural circuitry. Generally speaking, the genes included in the present study cannot be thought of as genetically transmitted risk factors, even when both copy number intensities and mRNA expression show robust changes, because the study design is fundamentally different from that used in association studies. The information gathered in our study is most useful in identifying the ways in which the molecular regulation of complex circuits may be abnormal, particularly when combined with parallel rodent modeling.46
The target genes examined in our study are involved in the functional maintenance of hippocampal GABA cells that show abnormal expression of GAD67 in schizophrenia and bipolar disorder.17,21 They include networks that regulate GAD67 expression, neurogenesis, the cell cycle, and the DNA damage response. In the present study, most of these genes showed significant increases or decreases of copy number intensities at their respective chromosomal loci. The largely robust nature of these copy number intensities and their correlation with the respective expression changes suggest that they may be linked to the regulation of functional differentiation and genomic integrity in hippocampal GABA cells. Widespread deletions along the GAD67 -encompassing segment of chromosome 2q (ie, 2q24.3-2q31.1), where GAD67 is encoded,47 have been identified in patients with schizophrenia but not in patients with bipolar disorder. The fact that GAD67 expression is significantly reduced in sector CA3/2 of both disorders suggests that these broad-based deletions on the 2q chromosome may be only one of the many mechanisms involved in the decrease of GAD67 expression.
The results from quantitative PCR showed a decreased copy number intensity of GAD67 in patients with schizophrenia or bipolar disorder, which was consistent with the results from SNP arrays. These findings demonstrate that a decreased copy number intensity of GAD67 in the hippocampus could be a prevalent genetic change in the majority of patients with schizophrenia or bipolar disorder. More importantly, there was a significant correlation between DNA loss and RNA underexpression of the GAD67 gene, suggesting that the transcript level of this gene may be regulated by its DNA copy number.
In sector CA3/2, the direction of change for copy number intensities showed a high degree of correspondence with the expression changes for the respective target genes. For example, in patients with schizophrenia, HDAC11 and DAXX both showed increased copy number intensities and expression changes. In patients with bipolar disorder, however, these parameters for PAX5 and RUNX2 were both decreased. Indeed, the regression analyses provide compelling evidence to support the idea that these 2 variables are interrelated. The relationship between copy number intensities and gene expression changes was most striking for the genes directly involved in GAD67 regulation compared with the genes more indirectly involved in neurogenesis, cell cycle regulation, and the DNA damage response.
The fact that the nature of the changes in copy number intensity and gene expression for the target genes was quite different for the 2 disorders may reflect the fundamentally different nature of the molecular abnormalities found in the GABA cells of sector CA3/2 for each disorder. It seems unlikely that psychotropic medications are responsible for these differences because the 2 groups showed similar drug exposure histories (eTable). It seems more likely that the unique changes in copy number intensity and gene expression in sector CA3/2 might be related to differences in “risk genes” for the 2 respective disorders.
Unlike the copy number intensities in sector CA3/2, those in sector CA1 of patients with schizophrenia or bipolar disorder did not show any correlation with gene expression changes. Only 20% to 30% of the target genes associated with cell cycle regulation and DNA repair in sector CA1 of patients with schizophrenia or bipolar disorder showed significant changes in expression (Table 3).
This obvious difference between the findings in sector CA3/2 and the findings in sector CA1 is consistent with the idea that the local tissue environment surrounding a cell may play a critical role in influencing its profile of transcriptional activity. In the hippocampus of patients with schizophrenia or bipolar disorder, the concentration of significant findings in the stratum oriens of sector CA3/2, but not sector CA1, can potentially be explained by differences in the molecular activity within neurons that comprise the microcircuitry at these 2 respective sites.24 For example, the stratum oriens of sector CA3/2, but not sector CA1, receives a rich glutamatergic projection from the basolateral amygdala, and these fibers are believed to play an important role in the integration of emotion and cognition, particularly in relation to stressful events.48 Other systems that are unique to this locus include GABAergic fibers that originate in the septal nuclei49 and contribute to the regulation of oscillatory rhythms.50
The stratum oriens is unique because the exclusive neuronal cell type in this layer is the GABAergic interneuron. These latter cells receive a robust and specific projection from the basolateral amygdala,51 which exerts an important influence on membrane properties and the action potential firing rate in fast-spiking inhibitory cells.46 Based on the present findings, basolateral amygdala projections to the stratum oriens of the CA3/2 locus may contribute to the functional and genomic integrity of GABAergic interneurons at this locus, presumably through synaptic or modulatory mechanisms. The GAD67 regulatory network includes 3 kainate-sensitive glutamate receptor (KAR) genes (GRIK1, GRIK2, and GRIK3) that encode the GluR5, 6, and 7 subunits, respectively, for this receptor. Abnormal expression and activity of KAR in the hippocampus are believed to play an important role in schizophrenia.52,53 Because the GAD67 regulatory network is linked to the canonical clusters associated with the cell cycle and the DNA damage response, the synaptically mediated influence of electrical activity generated within the trisynaptic pathway could contribute, at least theoretically, to parallel changes in copy number intensity and gene expression for the target genes associated with the regulation of GAD67 in GABA cells at this locus. These changes could include either deletions or duplications of genomic sequences in these target genes.
Most of our knowledge regarding the relationship between the sensing and repair of DNA has come from proliferating cell populations, like those active during embryogenesis.54 Little or nothing is known about the regulation of the cell cycle or the DNA damage response in postmitotic cells in the adult brain. Many believe that terminal differentiation involves an extensive reprogramming of the genome, so that genes that are relevant to interneuron function, like those associated with GAD67 regulation, are transcribed, while other genes are permanently silenced.55
The mechanisms associated with the repair of damaged DNA include pivotal target genes, such as CCND2, E2F3, MBD4, and HDAC, that may help to link the differentiation of mature GABA cells to their ability (or inability) to repair damaged DNA and preserve their genomic and functional integrity. To our knowledge, the present study provides the first evidence that deletions and/or duplications are present in terminally differentiated neurons in the adult hippocampus and that such changes may also contribute to the aberrant expression of key genes involved in the normal and abnormal functioning of hippocampal GABA cells.
In summary, the analyses reported herein demonstrate that there is considerable overlap between copy number intensities and mRNA expression for target genes associated with GAD67 regulation at a key locus within the hippocampi of patients with schizophrenia or bipolar disorder. Elucidating cell type–specific and locus-specific associations of genes comprising the GAD67 regulatory network in hippocampal GABA cells with those associated with the cell cycle and DNA repair could help to explain the presence of unique cellular endophenotypes in each of these 2 disorders.56 The genomic integrity and differentiation of tissue-specific functions in postmitotic GABA cells, and their potential relationship with age-related changes in health and disease,54 are issues that will require further study in many different forms of neuropsychiatric disease.
Correspondence: Francine M. Benes, MD, PhD, McLean Hospital, 115 Mill St, Belmont, MA 02478 (fbenes@mclean.harvard.edu).
Submitted for Publication: July 15, 2011; final revision received November 3, 2011; accepted November 15, 2011.
Published Online: February 6, 2012. doi:10.1001/archgenpsychiatry.2011.1882
Financial Disclosure: None reported.
Funding/Support: This study was supported by National Institutes of Health grants MH077175, MH42261-08, and MH/NS 077550 and the William P. and Henry B. Test Endowment (Harvard University).
Additional Contributions: We thank Cheng Li, PhD, Associate Professor of Biostatistics and Computational Biology, Harvard Medical School, for his extraordinary generosity and patience in helping us to organize our SNP database for copy number intensities and their analyses using the most appropriate statistics. We also thank Deborah L. Levy, PhD, for her expertise in genetics studies of blood samples from live subjects and her insights into how copy number variants and risk genes may interact in psychiatric disorders.
2.Sebat J, Lakshmi B, Malhotra D, Troge J, Lese-Martin C, Walsh T, Yamrom B, Yoon S, Krasnitz A, Kendall J, Leotta A, Pai D, Zhang R, Lee YH, Hicks J, Spence SJ, Lee AT, Puura K, Lehtimäki T, Ledbetter D, Gregersen PK, Bregman J, Sutcliffe JS, Jobanputra V, Chung W, Warburton D, King MC, Skuse D, Geschwind DH, Gilliam TC, Ye K, Wigler M. Strong association of de novo copy number mutations with autism.
Science. 2007;316(5823):445-44917363630
PubMedGoogle ScholarCrossref 3.Marshall CR, Noor A, Vincent JB, Lionel AC, Feuk L, Skaug J, Shago M, Moessner R, Pinto D, Ren Y, Thiruvahindrapduram B, Fiebig A, Schreiber S, Friedman J, Ketelaars CE, Vos YJ, Ficicioglu C, Kirkpatrick S, Nicolson R, Sloman L, Summers A, Gibbons CA, Teebi A, Chitayat D, Weksberg R, Thompson A, Vardy C, Crosbie V, Luscombe S, Baatjes R, Zwaigenbaum L, Roberts W, Fernandez B, Szatmari P, Scherer SW. Structural variation of chromosomes in autism spectrum disorder.
Am J Hum Genet. 2008;82(2):477-48818252227
PubMedGoogle ScholarCrossref 4.Morrow EM, Yoo SY, Flavell SW, Kim TK, Lin Y, Hill RS, Mukaddes NM, Balkhy S, Gascon G, Hashmi A, Al-Saad S, Ware J, Joseph RM, Greenblatt R, Gleason D, Ertelt JA, Apse KA, Bodell A, Partlow JN, Barry B, Yao H, Markianos K, Ferland RJ, Greenberg ME, Walsh CA. Identifying autism loci and genes by tracing recent shared ancestry.
Science. 2008;321(5886):218-22318621663
PubMedGoogle ScholarCrossref 5.Polymeropoulos MH, Higgins JJ, Golbe LI, Johnson WG, Ide SE, Di Iorio G, Sanges G, Stenroos ES, Pho LT, Schaffer AA, Lazzarini AM, Nussbaum RL, Duvoisin RC. Mapping of a gene for Parkinson's disease to chromosome 4q21-q23.
Science. 1996;274(5290):1197-11998895469
PubMedGoogle ScholarCrossref 6.Rovelet-Lecrux A, Hannequin D, Raux G, Le Meur N, Laquerrière A, Vital A, Dumanchin C, Feuillette S, Brice A, Vercelletto M, Dubas F, Frebourg T, Campion D. APP locus duplication causes autosomal dominant early-onset Alzheimer disease with cerebral amyloid angiopathy.
Nat Genet. 2006;38(1):24-2616369530
PubMedGoogle ScholarCrossref 7.Helbig I, Mefford HC, Sharp AJ, Guipponi M, Fichera M, Franke A, Muhle H, de Kovel C, Baker C, von Spiczak S, Kron KL, Steinich I, Kleefuss-Lie AA, Leu C, Gaus V, Schmitz B, Klein KM, Reif PS, Rosenow F, Weber Y, Lerche H, Zimprich F, Urak L, Fuchs K, Feucht M, Genton P, Thomas P, Visscher F, de Haan GJ, Møller RS, Hjalgrim H, Luciano D, Wittig M, Nothnagel M, Elger CE, Nürnberg P, Romano C, Malafosse A, Koeleman BP, Lindhout D, Stephani U, Schreiber S, Eichler EE, Sander T. 15q13.3 microdeletions increase risk of idiopathic generalized epilepsy.
Nat Genet. 2009;41(2):160-16219136953
PubMedGoogle ScholarCrossref 8.Erez A, Patel AJ, Wang X, Xia Z, Bhatt SS, Craigen W, Cheung SW, Lewis RA, Fang P, Davenport SL, Stankiewicz P, Lalani SR. Alu-specific microhomology-mediated deletions in CDKL5 in females with early-onset seizure disorder.
Neurogenetics. 2009;10(4):363-36919471977
PubMedGoogle ScholarCrossref 9.Stefansson H, Rujescu D, Cichon S, Pietiläinen OP, Ingason A, Steinberg S, Fossdal R, Sigurdsson E, Sigmundsson T, Buizer-Voskamp JE, Hansen T, Jakobsen KD, Muglia P, Francks C, Matthews PM, Gylfason A, Halldorsson BV, Gudbjartsson D, Thorgeirsson TE, Sigurdsson A, Jonasdottir A, Jonasdottir A, Bjornsson A, Mattiasdottir S, Blondal T, Haraldsson M, Magnusdottir BB, Giegling I, Möller HJ, Hartmann A, Shianna KV, Ge D, Need AC, Crombie C, Fraser G, Walker N, Lonnqvist J, Suvisaari J, Tuulio-Henriksson A, Paunio T, Toulopoulou T, Bramon E, Di Forti M, Murray R, Ruggeri M, Vassos E, Tosato S, Walshe M, Li T, Vasilescu C, Mühleisen TW, Wang AG, Ullum H, Djurovic S, Melle I, Olesen J, Kiemeney LA, Franke B, Sabatti C, Freimer NB, Gulcher JR, Thorsteinsdottir U, Kong A, Andreassen OA, Ophoff RA, Georgi A, Rietschel M, Werge T, Petursson H, Goldstein DB, Nöthen MM, Peltonen L, Collier DA, St Clair D, Stefansson K.GROUP. Large recurrent microdeletions associated with schizophrenia.
Nature. 2008;455(7210):232-23618668039
PubMedGoogle ScholarCrossref 10.Kirov G, Gumus D, Chen W, Norton N, Georgieva L, Sari M, O’Donovan MC, Erdogan F, Owen MJ, Ropers HH, Ullmann R. Comparative genome hybridization suggests a role for NRXN1 and APBA2 in schizophrenia.
Hum Mol Genet. 2008;17(3):458-46517989066
PubMedGoogle ScholarCrossref 11.Vrijenhoek T, Buizer-Voskamp JE, van der Stelt I, Strengman E, Sabatti C, Geurts van Kessel A, Brunner HG, Ophoff RA, Veltman JA.Genetic Risk and Outcome in Psychosis (GROUP) Consortium. Recurrent CNVs disrupt three candidate genes in schizophrenia patients.
Am J Hum Genet. 2008;83(4):504-51018940311
PubMedGoogle ScholarCrossref 12.Akbarian S, Huang HS. Molecular and cellular mechanisms of altered GAD1/GAD67 expression in schizophrenia and related disorders.
Brain Res Rev. 2006;52(2):293-30416759710
PubMedGoogle ScholarCrossref 13.Volk DW, Austin MC, Pierri JN, Sampson AR, Lewis DA. Decreased glutamic acid decarboxylase67 messenger RNA expression in a subset of prefrontal cortical gamma-aminobutyric acid neurons in subjects with schizophrenia.
Arch Gen Psychiatry. 2000;57(3):237-24510711910
PubMedGoogle ScholarCrossref 14.Guidotti A, Auta J, Davis JM, Di-Giorgi-Gerevini V, Dwivedi Y, Grayson DR, Impagnatiello F, Pandey G, Pesold C, Sharma R, Uzunov D, Costa E. Decrease in reelin and glutamic acid decarboxylase67 (GAD67) expression in schizophrenia and bipolar disorder: a postmortem brain study [published correction appears in
Arch Gen Psychiatry 2002;59(1):12].
Arch Gen Psychiatry. 2000;57(11):1061-106911074872
PubMedGoogle ScholarCrossref 15.Duncan CE, Webster MJ, Rothmond DA, Bahn S, Elashoff M, Shannon Weickert C. Prefrontal GABA(A) receptor alpha-subunit expression in normal postnatal human development and schizophrenia.
J Psychiatr Res. 2010;44(10):673-68120100621
PubMedGoogle ScholarCrossref 16.Benes FM. Searching for unique endophenotypes for schizophrenia and bipolar disorder within neural circuits and their molecular regulatory mechanisms.
Schizophr Bull. 2007;33(4):932-93617575303
PubMedGoogle ScholarCrossref 17.Benes FM, Lim B, Subburaju S. Site-specific regulation of cell cycle and DNA repair in post-mitotic GABA cells in schizophrenic versus bipolars.
Proc Natl Acad Sci U S A. 2009;106(28):11731-1173619564623
PubMedGoogle ScholarCrossref 18.Benes FM, Khan Y, Vincent SL, Wickramasinghe R. Differences in the subregional and cellular distribution of GABAA receptor binding in the hippocampal formation of schizophrenic brain.
Synapse. 1996;22(4):338-3498867028
PubMedGoogle ScholarCrossref 19.Benes FM. Amygdalocortical circuitry in schizophrenia: from circuits to molecules.
Neuropsychopharmacology. 2010;35(1):239-25719727065
PubMedGoogle ScholarCrossref 20.Feighner JP, Robins E, Guze SB, Woodruff RA Jr, Winokur G, Munoz R. Diagnostic criteria for use in psychiatric research.
Arch Gen Psychiatry. 1972;26(1):57-635009428
PubMedGoogle ScholarCrossref 21.Benes FM, Lim B, Matzilevich D, Walsh JP, Subburaju S, Minns M. Regulation of the GABA cell phenotype in hippocampus of schizophrenics and bipolars.
Proc Natl Acad Sci U S A. 2007;104(24):10164-1016917553960
PubMedGoogle ScholarCrossref 22.Rosene DL, Van Hoesen GW. The hippocampal formation of the primate brain. In: Peters A, Jones EG, eds. Cerebral Cortex: Vol 6: Further Aspects of Cortical Function, Including Hippocampus. New York, NY: Plenum Press; 1987:345-456
24.Benes FM, Lim B, Matzilevich D, Subburaju S, Walsh JP. Circuitry-based gene expression profiles in GABA cells of the trisynaptic pathway in schizophrenics versus bipolars.
Proc Natl Acad Sci U S A. 2008;105(52):20935-2094019104056
PubMedGoogle ScholarCrossref 25.Dillon N, Festenstein R. Unravelling heterochromatin: competition between positive and negative factors regulates accessibility.
Trends Genet. 2002;18(5):252-25812047950
PubMedGoogle ScholarCrossref 26.Li C, Wong WH. Model-based analysis of oligonucleotide arrays: expression index computation and outlier detection.
Proc Natl Acad Sci U S A. 2001;98(1):31-3611134512
PubMedGoogle ScholarCrossref 27.Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.
Methods. 2001;25(4):402-40811846609
PubMedGoogle ScholarCrossref 28.Mao R, Page DT, Merzlyak I, Kim C, Tecott LH, Janak PH, Rubenstein JL, Sur M. Reduced conditioned fear response in mice that lack Dlx1 and show subtype-specific loss of interneurons.
J Neurodev Disord. 2009;1(3):224-23619816534
PubMedGoogle ScholarCrossref 29.Li JJ, Friedman-Kien AE, Cockerell C, Nicolaides A, Liang SL, Huang YQ. Evaluation of the tumorigenic and angiogenic potential of human fibroblast growth factor FGF3 in nude mice.
J Cancer Res Clin Oncol. 1998;124(5):259-2649645456
PubMedGoogle ScholarCrossref 30.Miyamoto M, Naruo K, Seko C, Matsumoto S, Kondo T, Kurokawa T. Molecular cloning of a novel cytokine cDNA encoding the ninth member of the fibroblast growth factor family, which has a unique secretion property.
Mol Cell Biol. 1993;13(7):4251-42598321227
PubMedGoogle Scholar 31.Nakamura S, Todo T, Haga S, Aizawa T, Motoi Y, Ueki A, Kurokawa T, Ikeda K. Motor neurons in human and rat spinal cord synthesize fibroblast growth factor-9.
Neurosci Lett. 1997;221(2-3):181-1849121694
PubMedGoogle ScholarCrossref 33.Fazzari P, Paternain AV, Valiente M, Pla R, Luján R, Lloyd K, Lerma J, Marín O, Rico B. Control of cortical GABA circuitry development by Nrg1 and ErbB4 signalling.
Nature. 2010;464(7293):1376-138020393464
PubMedGoogle ScholarCrossref 34.Blumberg HP, Wang F, Chepenik LG, Kalmar JH, Edmiston E, Duman RS, Gelernter J. Influence of vascular endothelial growth factor variation on human hippocampus morphology.
Biol Psychiatry. 2008;64(10):901-90318707678
PubMedGoogle ScholarCrossref 35.Nicodemus KK, Law AJ, Radulescu E, Luna A, Kolachana B, Vakkalanka R, Rujescu D, Giegling I, Straub RE, McGee K, Gold B, Dean M, Muglia P, Callicott JH, Tan HY, Weinberger DR. Biological validation of increased schizophrenia risk with NRG1, ERBB4, and AKT1 epistasis via functional neuroimaging in healthy controls.
Arch Gen Psychiatry. 2010;67(10):991-100120921115
PubMedGoogle ScholarCrossref 36.Terwisscha van Scheltinga AF, Bakker SC, Kahn RS. Fibroblast growth factors in schizophrenia.
Schizophr Bull. 2010;36(6):1157-116619429845
PubMedGoogle ScholarCrossref 37.Walsh T, McClellan JM, McCarthy SE, Addington AM, Pierce SB, Cooper GM, Nord AS, Kusenda M, Malhotra D, Bhandari A, Stray SM, Rippey CF, Roccanova P, Makarov V, Lakshmi B, Findling RL, Sikich L, Stromberg T, Merriman B, Gogtay N, Butler P, Eckstrand K, Noory L, Gochman P, Long R, Chen Z, Davis S, Baker C, Eichler EE, Meltzer PS, Nelson SF, Singleton AB, Lee MK, Rapoport JL, King MC, Sebat J. Rare structural variants disrupt multiple genes in neurodevelopmental pathways in schizophrenia.
Science. 2008;320(5875):539-54318369103
PubMedGoogle ScholarCrossref 38.International Schizophrenia Consortium. Rare chromosomal deletions and duplications increase risk of schizophrenia.
Nature. 2008;455(7210):237-24118668038
PubMedGoogle ScholarCrossref 39.Xu B, Roos JL, Levy S, van Rensburg EJ, Gogos JA, Karayiorgou M. Strong association of de novo copy number mutations with sporadic schizophrenia.
Nat Genet. 2008;40(7):880-88518511947
PubMedGoogle ScholarCrossref 40.Amar S, Ovadia O, Maier W, Ebstein R, Belmaker RH, Mishmar D, Agam G. Copy number variation of the SELENBP1 gene in schizophrenia.
Behav Brain Funct. 2010;6:4020615253
PubMedGoogle ScholarCrossref 41.Cahan P, Li Y, Izumi M, Graubert TA. The impact of copy number variation on local gene expression in mouse hematopoietic stem and progenitor cells.
Nat Genet. 2009;41(4):430-43719270704
PubMedGoogle ScholarCrossref 42.Gorlov IP, Gallick GE, Gorlova OY, Amos C, Logothetis CJ. GWAS meets microarray: are the results of genome-wide association studies and gene-expression profiling consistent? prostate cancer as an example.
PLoS One. 2009;4(8):e651119652704
PubMedGoogle ScholarCrossref 43.Lundorf MD, Buttenschøn HN, Foldager L, Blackwood DH, Muir WJ, Murray V, Pelosi AJ, Kruse TA, Ewald H, Mors O. Mutational screening and association study of glutamate decarboxylase 1 as a candidate susceptibility gene for bipolar affective disorder and schizophrenia.
Am J Med Genet B Neuropsychiatr Genet. 2005;135B(1):94-10115806582
PubMedGoogle ScholarCrossref 44.Harrison PJ, Law AJ. Neuregulin 1 and schizophrenia: genetics, gene expression, and neurobiology.
Biol Psychiatry. 2006;60(2):132-14016442083
PubMedGoogle ScholarCrossref 45.Munafò MR, Thiselton DL, Clark TG, Flint J. Association of the NRG1 gene and schizophrenia: a meta-analysis.
Mol Psychiatry. 2006;11(6):539-54616520822
PubMedGoogle ScholarCrossref 46.Gisabella B, Cunningham MG, Bolshakov VY, Benes FM. Amygdala-dependent regulation of electrical properties of hippocampal interneurons in a model of schizophrenia.
Biol Psychiatry. 2009;65(6):464-47219027103
PubMedGoogle ScholarCrossref 47.Bacchelli E, Blasi F, Biondolillo M, Lamb JA, Bonora E, Barnby G, Parr J, Beyer KS, Klauck SM, Poustka A, Bailey AJ, Monaco AP, Maestrini E.International Molecular Genetic Study of Autism Consortium (IMGSAC). Screening of nine candidate genes for autism on chromosome 2q reveals rare nonsynonymous variants in the cAMP-GEFII gene.
Mol Psychiatry. 2003;8(11):916-92414593429
PubMedGoogle ScholarCrossref 48.Richardson MP, Strange BA, Dolan RJ. Encoding of emotional memories depends on amygdala and hippocampus and their interactions.
Nat Neurosci. 2004;7(3):278-28514758364
PubMedGoogle ScholarCrossref 49.Bland BH, Oddie SD, Colom LV. Mechanisms of neural synchrony in the septohippocampal pathways underlying hippocampal theta generation.
J Neurosci. 1999;19(8):3223-323710191335
PubMedGoogle Scholar 50.Tóth K, Freund TF, Miles R. Disinhibition of rat hippocampal pyramidal cells by GABAergic afferents from the septum.
J Physiol. 1997;500(pt 2):463-4749147330
PubMedGoogle Scholar 51.Berretta S, Munno DW, Benes FM. Amygdalar activation alters the hippocampal GABA system: “partial” modelling for postmortem changes in schizophrenia.
J Comp Neurol. 2001;431(2):129-13811169995
PubMedGoogle ScholarCrossref 52.Porter RH, Eastwood SL, Harrison PJ. Distribution of kainate receptor subunit mRNAs in human hippocampus, neocortex and cerebellum, and bilateral reduction of hippocampal GluR6 and KA2 transcripts in schizophrenia.
Brain Res. 1997;751(2):217-2319099808
PubMedGoogle ScholarCrossref 53.Eastwood SL, McDonald B, Burnet PW, Beckwith JP, Kerwin RW, Harrison PJ. Decreased expression of mRNAs encoding non-NMDA glutamate receptors GluR1 and GluR2 in medial temporal lobe neurons in schizophrenia.
Brain Res Mol Brain Res. 1995;29(2):211-2237609609
PubMedGoogle ScholarCrossref 54.Simonatto M, Latella L, Puri PL. DNA damage and cellular differentiation: more questions than responses.
J Cell Physiol. 2007;213(3):642-64817894406
PubMedGoogle ScholarCrossref 55.Forcales SV, Puri PL. Signaling to the chromatin during skeletal myogenesis: novel targets for pharmacological modulation of gene expression.
Semin Cell Dev Biol. 2005;16(4-5):596-61116129633
PubMedGoogle ScholarCrossref 56.Benes FM. Regulation of cell cycle and DNA repair in post-mitotic GABA neurons in psychotic disorders.
Neuropharmacology. 2011;60(7-8):1232-124221184762
PubMedGoogle ScholarCrossref