Context
The hippocampus is strongly implicated in schizophrenia and, to a lesser degree, bipolar disorder. Proteomic investigations of the different regions of the hippocampus may help us to clarify the basis and the disease specificity of the changes.
Objective
To determine whether schizophrenia and bipolar disorder are associated with distinct patterns of differential protein expression in specific regions of the hippocampus.
Design, Setting, and Patients
A postmortem comparative proteomic study, including validation of differential expression, was performed. Midhippocampus samples from well-matched groups of 20 subjects with schizophrenia, 20 subjects with bipolar disorder, and 20 control cases from the Stanley Medical Research Institute Array Collection were analyzed.
Main Outcome Measures
We used laser-assisted microdissection to enrich for tissue from the hippocampal regions and 2-dimensional difference gel electrophoresis to compare protein profiles. Levels of differentially expressed proteins were confirmed by enzyme-linked immunosorbent assay and Western blotting. Hippocampi from haloperidol-treated mice were used to help discriminate drug-associated from disease-associated protein changes.
Results
Across all hippocampal regions, 108 protein spots in schizophrenia and 165 protein spots in bipolar disorder were differentially expressed compared with controls. Sixty-one proteins were differentially expressed in both disorders. One hundred fifty-two of these proteins were identified by mass spectrometry, and they implicated a range of different processes including cytoskeletal and metabolic functions. In both disorders, cornu ammonis regions 2 and 3 were affected to a significantly greater degree than other hippocampal regions. Additionally, numerous proteins showed expression changes in more than 1 region and more than 1 disorder. Validation work confirmed changes in septin 11 and in the expression of proteins involved in clathrin-mediated endocytosis in both schizophrenia and bipolar disorder.
Conclusions
Overall, similar protein changes were observed in schizophrenia and bipolar disorder and for the first time indicate that the most prominent proteomic changes occur within the hippocampus in cornu ammonis regions 2 and 3. The cytoskeletal protein septin 11 and the cellular trafficking process of clathrin-mediated endocytosis are implicated by our study.
Hippocampal abnormality is one of the most consistent findings in schizophrenia research.1 Hippocampal volume is reduced in chronic schizophrenia,2 first-episode psychosis,3 and the prodrome to psychotic illness.4 Two separate processes, a neurodevelopmental process and a progressive neuropathological process occurring after the onset of the illness,5,6 may contribute to these changes. The hippocampus is also implicated in bipolar disorder.7-9
The distinct subfields of the hippocampus, comprising the cornu ammonis (CA) regions 1 through 4 and the dentate gyrus (DG), differ anatomically, functionally,10,11 and in their vulnerability to neurological disorders.1 In schizophrenia, particular vulnerability has been suggested for regions CA2 and CA3,12-18 but a clear consensus is lacking.1,12,13 More generally, postmortem studies have shown reduced neuronal number,14 somal size,15,16 density of γ-aminobutyric acid (GABA)–ergic neurons,17,18 and dendritic arborization19 as well as evidence of glutamatergic dysfunction involving reduced N -methyl-D-aspartate (NMDA) and non-NMDA receptor expression.1,20 Synaptic changes are also described and involve alterations in the expression of several synaptic proteins.21-27
Unfortunately, our understanding of the molecular mechanisms underlying hippocampal alterations in schizophrenia and bipolar disorder is limited. While genomic investigations continue to contribute important insights28-31 and indeed point to a shared genetic basis,32,33 the core pathophysiology of these psychotic disorders remains elusive. A major limitation of genetic approaches is that analysis of nucleic acids alone cannot predict expression and function of the proteins they encode because proteins are undergoing a multitude of modifications from transcription to posttranslation.34 Equally, actual protein levels in cells do not reliably correlate with messenger RNA (mRNA) expression.35,36 Therefore, direct assessment of proteins, which represent the functional output of the cell, will be indispensable in the search for the molecular basis of psychotic disorders.
Proteomics is the study of the proteome of a particular biological system in a particular state.37 Using proteomic methods, it is possible to assess global differential protein expression between disease and control states and to obtain novel insights into disease (for reviews, see the articles by English et al,38 Görg et al,39 and Tannu and Hemby40). Proteomic studies of postmortem brain tissue from subjects with schizophrenia and from subjects with bipolar disorder have focused largely on the dorsolateral prefrontal cortex41-49 and the anterior cingulate cortex.50-53 They have demonstrated alterations in cytoskeletal, synaptic, metabolic, and mitochondrial proteins.42,44-46,48,50,54 To our knowledge, with regard to the hippocampus, there has been 1 previous proteomic study in schizophrenia54 and none in bipolar disorder.
Our investigation represents the first detailed proteomic study of the human hippocampus in schizophrenia and bipolar disorder. To account for anatomical and functional differences of hippocampal regions, we assessed 4 regions separately (CA1, CA2/3, CA4, and DG) using laser-assisted microdissection to achieve anatomical separation. The results of the study enhance our knowledge of the nature and extent of region-specific protein changes in psychotic disorders and may provide valuable information about the molecular mechanisms involved in these illnesses.
Human postmortem brain tissue from the midhippocampus at the level of the lateral geniculate nucleus was dissected by Maree J. Webster, PhD, anatomist, Stanley Medical Research Institute. The series consists of 105 subjects, including 35 subjects with schizophrenia, 35 subjects with bipolar disorder, and 35 control cases. Information on prescribed psychotropic medication is provided by the Stanley Medical Research Institute.
A subset of 20 samples from each of these 3 groups was selected to match as closely as possible for age and tissue pH.55,56Table 1 provides detailed demographic information on these 60 subjects. For a detailed breakdown of the main groups of prescribed psychotropic medications (eg, typical and atypical antipsychotics, mood stabilizers, antidepressants), see eTable 1. Investigators were blind to group identity until completion of the data analysis. Ethical approval was granted by the Royal College of Surgeons in Ireland Research Ethics Committee.
Laser-Assisted Microdissection
Frozen tissue sections were cut by the Stanley Medical Research Institute and mounted onto membrane-covered slides (PALM Microlaser Technologies AG, Bernried, Germany). From each case, 1 section was stained very briefly with cresyl violet and a detailed image was obtained to mark the boundaries between the different regions (Figure 1). Consecutive sections (25 sections for each case) were then stained with methyl green as this had previously been shown not to interfere with protein integrity in laser-assisted microdissection.57 The laser microdissector (PALM Microlaser Technologies) was used in the cut mode as previously described.58 Areas of DG, CA4, CA2/3, and CA1 were marked on each methyl green–stained section of each slide using the PALM software, cut using laser-assisted microdissection, collected in microtubes, and stored at −80°C.
Separation of proteins by 2-dimensional difference gel electrophoresis and image analysis
Samples were processed and separated by 2-dimensional difference gel electrophoresis (2D-DIGE) as described previously42,44,46,59 (for detailed methods, see the eAppendix and eTable 2). After electrophoresis, scanning of the gels with CyDye-labeled proteins was performed on a Typhoon 9410 image scanner (Amersham Biosciences, Little Chalfont, England). Prescans were performed to adjust the photomultiplier tube voltage to obtain images with a maximum intensity of 60 000 to 80 000 units. Images were cropped using ImageQuant software (Amersham Biosciences), and protein quantification across experimental groups was carried out with Progenesis software (Nonlinear Dynamics, Newcastle upon Tyne, England).
Network, functional, and pathway mapping
Ingenuity Pathways Analysis (Ingenuity Systems, Redwood City, California) was used to analyze the key biological relationships of all differentially expressed proteins (Table 2). Significant biological functions are categorized as of the signaling and metabolic pathways, molecular networks, and biological processes determined using Fisher exact test to compare the number of proteins that are most significantly perturbed in the data set.
Validation of differentially expressed proteins
We selected 9 proteins for validation based on their potential scientific interest, the fold changes, the number of hippocampal regions affected, and the availability of antibodies. For 3 of the proteins chosen, namely BCL2 inhibitor protein, cathepsin D, and N(G),N(G)-dimethylarginine dimethylaminohydrolase, enzyme-linked immunosorbent
assays or Western blots were not successfully optimized. However, validation work was successfully undertaken using enzyme-linked immunosorbent assay (protein-L-isoaspartate-O-methyltransferase [PCMT1]), Western blotting (spectrin, alpha, nonerythrocytic 1 [SPTAN1], armadillo repeat containing, X-linked 1 [ARMCX1], annexin A6 [ANXA6], and septin 11 [SEPT11]), and dot blot (fascin 1 [FSCN1]) in samples from the Stanley Medical Research Institute Array Collection (eAppendix) based on the suitability of the antibodies. Because the laser-captured material from hippocampal regions was very limited in quantity, for the proteins confirmed by Western blotting we were obliged to confirm differential protein expression on pooled samples such that every group was represented by 4 pools of 5 cases. Within each diagnostic group, subjects were randomly allocated to the 4 separate pools (eTable 3).
To assess the effects of psychotropic medication on the expression of candidate proteins, hippocampal tissue was harvested from mice treated with 0.5 mg/kg of haloperidol for 28 days (eAppendix). Western blotting was undertaken on mouse hippocampal tissue homogenates for ANXA6, FSCN1, PCMT1, SEPT11, and SPTAN1 (eAppendix).
Normalized spot volume data were extracted from the Progenesis software and log base 10 transformed prior to analysis to eliminate distributional skew and to give approximate normality. We chose, a priori, the covariates postmortem interval, refrigerator interval, and brain pH to be of interest as possible confounders of protein abundance, with the additional inclusion of drug use (antipsychotics, antidepressants, and mood stabilizers) as secondary analyses. Freezer time was not significantly different between groups and we did not include this variable as a potential confounder. Other covariates, which may also be considered as possible confounders, were highly correlated with our chosen set of covariates; for example, antipsychotic dose (included in secondary analysis), drug abuse, smoking history, and alcohol use were all highly correlated with each
other (correlation >0.7). Consequently, we did not make further adjustment for these.
Analysis of covariance (ANCOVA) was performed on the normalized spot volumes for each spot in each brain region, with age, postmortem interval, refrigerator interval, and brain pH included as covariates. Estimated differences between schizophrenia or bipolar disorder samples and controls were then obtained using linear contrasts and exponentiated to obtain fold changes. Significance testing was then performed at the 5% level using ANCOVA. Statistically significant protein spots, adjusted for the covariates, were identified by mass spectrometry. A false discovery rate60 of 5%, which incorporated data from the 4 brain regions in a single model (as a factor) while allowing different brain regions to differ in effect, was used to flag those spots statistically significant after adjustment for multiple comparisons.
A χ2 test of association was used to determine whether the frequency of statistically significant spots was different between the 4 hippocampal regions. The ANCOVA results for each region were then combined to assess the number of regions in which a spot was statistically significant and to determine the degree of overlap of statistically significant spots in adjacent hippocampal regions.
Two overall post hoc statistical approaches were undertaken to assess the effects of antipsychotropic medications, antidepressants, and mood stabilizers on the protein expression profiles. The patients with schizophrenia and bipolar disorder were combined into 1 group and the control subjects were excluded from this analysis. First, the effect of use of psychotropic medications at the time of death (on or off these medications) was analyzed using ANCOVA, adjusting for the covariates mentioned previously. Second, the cumulative effect of antipsychotic medications (fluphenazine equivalents in milligrams)61 on spot abundances was assessed. Lifetime antipsychotic dose was highly skewed; as a consequence, the combined group of subjects with schizophrenia and subjects with bipolar disorder was classified based on sample size into 1 of 6 categories as follows: (1) dose of 0 fluphenazine equivalents (n = 6); (2) dose of 5 to 3000 fluphenazine equivalents (n = 6); (3) dose of 4000 to 12 000 fluphenazine equivalents (n = 7); (4) dose of 15 000 to 25 000 fluphenazine equivalents (n = 7); (5) dose of 30 000 to 90 000 fluphenazine equivalents (n = 6); and (6) dose of 100 000 to 400 000 fluphenazine equivalents (n = 7).46 Note that the dose was unavailable for 1 patient, and this case was excluded from this analysis.
The management of data and statistical analyses were carried out with SAS version 9.1 statistical software (SAS Institute, Inc, Cary, North Carolina) and R version 9.1 statistical software (R Foundation for Statistical Computing, Vienna, Austria).
A total of 832 protein spots were identified on the master gel image, and these were matched across all gel images and statistically analyzed using ANCOVA (correcting for age, brain pH, postmortem interval, and refrigerator interval). Post hoc analysis investigating the effect of freezer time showed that including this variable in the analysis had no influence on our results. Across all hippocampal regions, 141 proteins (representing 108 individual protein spots) in schizophrenia and 203 proteins (representing 165 individual protein spots) in bipolar disorder were differentially expressed compared with controls.
Sixty-one of these proteins were altered in both disorders. Note that 1 protein can be represented by more than 1 spot and several spots were differentially expressed in more than 1 region.
Differential expression in the regions was observed as follows: DG, 23 spots in schizophrenia and 26 spots in bipolar disorder; CA4, 32 spots in schizophrenia and 30 spots in bipolar disorder; CA2/3, 53 spots in schizophrenia and 113 spots in bipolar disorder; and CA1, 33 spots in schizophrenia and 34 spots in bipolar disorder. Thirty-two proteins in schizophrenia and 38 proteins in bipolar disorder were altered across more than 1 hippocampal region.
Accounting for proteins altered in both disorders and across several regions, 213 protein spots in total were differentially expressed. Of these, 152 protein spots were successfully identified by mass spectrometry. eTable 4 and eTable 5 list these findings, including details of their functional ontology and significance after adjusting for multiple comparisons (false discovery rate <5%). Identified protein spots are also indicated on a representative 2D-DIGE gel in Figure 2.
Region-specific vulnerability
We found a significant association between the hippocampal regions and the number of protein spots differentially expressed between schizophrenia and controls (χ2 test, P = .002). In bipolar disorder, this effect was even more prominent, with 113 spots differentially expressed in CA2/3 (χ2 test, P < .001).
Protein spots differentially expressed in multiple regions
For schizophrenia, 141 spots were found to be differentially expressed in any brain region. This represented a set of 108 unique spots, of which 80 (74%) were unique
to a single brain region and the remaining 28 (26%) were differentially expressed in at least 2 brain regions. For bipolar disorder, a total of 203 spots were differentially expressed in any brain region. This represented a set of 165 unique spots, of which 131 (79%) were differentially expressed in a single brain region and 34 (21%) were expressed in 2 or more brain regions.
Post hoc statistical analysis of medication effects
The first post hoc analysis found 37 of the identified proteins to be affected by psychotropic medication status at the time of death. The second post hoc analysis (the linear regression model) of the effects of lifetime antipsychotic dose found that only 16 spots were influenced by antipsychotic dose. For most spots implicated by the post hoc analyses, the direction of the fold change associated with psychotropic medications (n = 29 of 37) and lifetime antipsychotic dose (n = 9 of 16) was influenced in the direction opposite to that observed in disease groups (eTable 5, “Post Hoc On/Off Medication and Antipsychotic Dose” column).
Validation of proteomic findings
Extensive validation to confirm the findings obtained using 2D-DIGE was undertaken. See Figure 3 for the details of this validation work.
Validation Using 60 Samples
Using Western blotting on subpooled samples and individual samples from CA2/3, no significant differences between groups were observed. Results from 2D-DIGE showed a reduced expression in CA2/3 in bipolar disorder (−1.65-fold; P = .01) and in schizophrenia (−1.59-fold; P = .009).
Dot blots from samples of CA2/3 showed trend reductions in protein levels for both diseases (ANCOVA, P = .07). Post hoc t tests confirmed reductions in schizophrenia (−6.3%; P = .03) but not in bipolar disorder (−5.4%; P = .11). Results from 2D-DIGE showed a reduced expression in CA4 for 2 spots in bipolar disorder (−1.11-fold [P = .04] and −1.13-fold [P = .03]) and in CA2/3 for 2 spots in bipolar disorder (−1.15-fold [P = .002] and −1.13-fold [P = .001]) and 1 spot in schizophrenia (−1.12-fold; P = .004).
Using enzyme-linked immunosorbent assay, reduced expression in disease groups in CA4 was confirmed (ANCOVA, P < .001). Post hoc t tests confirmed reductions in schizophrenia (−19.2%; P < .001) and bipolar disorder (−16.3%; P < .001). Results from 2D-DIGE showed a reduced expression in CA4 in schizophrenia (−1.34-fold; P = .005) and bipolar disorder (−1.23-fold; P = .02), in the DG in schizophrenia (−1.29-fold; P = .01), and in CA2/3 in bipolar disorder (−1.16-fold; P = .03).
Validation Using Pooled Samples
Using Western blotting on subpooled samples of CA2/3, reduced expression in disease groups was confirmed (ANCOVA, P < .001). Post hoc t tests confirmed reductions in bipolar disorder (−17.3%; P < .001) and schizophrenia (−10.8%; P = .004). Results from 2D-DIGE showed a reduced expression in CA2/3 only in bipolar disorder in 2 spots (−1.21-fold [P = .03] and –1.36-fold [P = .04]).
Using Western blotting on subpooled samples of CA2/3, reduced expression in disease groups was confirmed (ANCOVA, P = .006). Post hoc t tests confirmed reductions in bipolar disorder (−6.3%; P = .02) and schizophrenia (−7.8%; P = .002). Results from 2D-DIGE showed a reduced expression in CA2/3 only in bipolar disorder (−1.45-fold; P = .02).
Using Western blotting on subpooled samples of CA4, reduced expression in disease groups was confirmed (ANCOVA, P < .001). Post hoc t tests confirmed reductions in schizophrenia (−11.2%; P < .001) and bipolar disorder (−6.0%; P = .002). Results from 2D-DIGE showed a reduction in 2 spots in CA4 in schizophrenia (−1.14-fold [P = .04] and −1.20-fold [P = .01]) and in bipolar disorder (−1.12-fold; P = .04) as well as a reduction in CA2/3 in bipolar disorder (−1.17-fold; P = .01).
Candidate protein changes in haloperidol-treated mice
Western blot analysis demonstrated that ANXA6, FSCN1, PCMT1, SEPT11, and SPTAN1 were not significantly altered in mice treated with haloperidol (eFigure). This confirmed that our findings are disease related rather than drug related.
Our study has 3 main findings. First, we have shown that all hippocampal regions demonstrate disease-associated protein expression changes in schizophrenia and bipolar disorder, with the CA2/3 region showing the most prominent changes. Second, while changes are most prominent in bipolar disorder, they occur consistently in the same direction in both diseases and are in keeping with a shared common genetic basis.32,33 These changes particularly implicate cytoskeletal and metabolic changes. Finally, our results point to clathrin-mediated endocytosis (CME) as a novel contributor to the pathophysiology of psychotic disorders. Clathrin-mediated endocytosis is crucially involved in presynaptic and postsynaptic vesicle and receptor recycling and regulation, which have been proposed to be disturbed in psychosis.62
Previous studies have suggested that the CA2/3 region of the hippocampus may be particularly vulnerable to neuropathological changes in psychosis.18,63-68 This is particularly evident in relation to the pathology of GABAergic interneurons in schizophrenia15,18,69-72 but is less clear in relation to markers of synaptic and glutamatergic function72,73 and in relation to mood disorders.7,65,72,74,75 Using an unbiased proteomic approach to assess protein changes within different hippocampal fields, we have shown an excess of differential protein expression in disease within CA2/3 compared with the other regions. It has been suggested that this region shows a particular vulnerability in schizophrenia17 possibly owing to altered basolateral amygdala projections to CA2/3.17,76-79 The CA2/3 region has close functional connections to many other brain regions including the hypothalamus, septal nucleus,80 subiculum,81 and the CA1 region of the hippocampus.82 Thus, while we confirm and extend the knowledge implicating the hippocampus and the CA2/3 region in schizophrenia20,83 and bipolar disorder, changes in this region will have widespread consequences within the brain.
Our second main finding is that we have identified a total of 152 differentially expressed proteins in schizophrenia and bipolar disorder. Sixty-one proteins were altered in both disorders; without exception, the changes (where significant) occurred in the same direction in both conditions. Furthermore, among proteins showing significant changes in only 1 group, the direction of the fold change in the other disease group was in the same direction in more than 95% of cases (eTable 5). Perhaps surprisingly, the most prominent changes were found in bipolar disorder. Given the lack of hippocampal volume changes in bipolar disorder84 compared with schizophrenia,73 these findings might seem counterintuitive. However, functional hippocampal deficits exist in both disorders,85,86 and increasing evidence suggests that schizophrenia and bipolar disorder share common genetic vulnerabilities.87 Our findings therefore provide further support for a reappraisal of these disorders as distinct diagnostic entities,32 although other evidence for the distinct character must also be considered in any such reappraisal.32,49,88,89
In keeping with previous proteomic studies of schizophrenia and bipolar disorder,38 including one of the hippocampus in schizophrenia,90 our findings implicate proteins involved in cytoskeletal42,46,90 and metabolic42,45,46,48,58 cellular mechanisms and, specifically in bipolar disorder, cell death pathways.91,92 The results complement findings of transcriptomic investigations in these brain regions.9,93-98 In the cases of ANXA6, Bcl2 inhibitor protein BNIP3, N(G),N(G)-dimethylarginine dimethylaminohydrolase, galectin-1, and heat shock cognate 71-kDa protein, our findings are supported by recent genome-wide association studies.99 Ingenuity Pathways Analysis in our study notably identified cellular assembly and organization as one of the main categories of protein function altered in both schizophrenia and bipolar disorder (Table 2).
Abnormalities in cellular assembly and organization are illustrated by differential expression of SEPT11 and FSCN1, both of which contribute to this pathway. We observed prominent reductions in the expression of SEPT11 in both schizophrenia and bipolar disorder in CA2/3 and in CA4. We confirmed this reduction by Western blotting in CA4 in schizophrenia and bipolar disorder. We and others have previously found changes in SEPT11 in schizophrenia,100 although our previous study of the dorsolateral prefrontal cortex showed increased expression in schizophrenia and bipolar disorder.44 This contrast with our current findings may be explained by a region-specific effect and the possibility that SEPT11 is represented on the 2D-DIGE gel by more than 1 protein spot. Septin 11 has roles in myelination,101 dendrite spine morphology,102 and GABAergic synaptic connectivity,103 and alterations of SEPT11 are thus highly relevant to schizophrenia.73 We also observed reduced expression of FSCN1 in CA2/3 in schizophrenia and at trend level in bipolar disorder. Fascin 1 is an actin-bundling protein that has roles in neurite outgrowth.104 These findings are in keeping with the presence of altered cytoskeletal dynamics105 in these disorders.46
Our third main finding is that our study implicates the process of CME in psychotic disorders by showing altered expression of proteins involved in or regulating this pathway, namely synaptotagmin, heat shock cognate 71-kDa protein,106 cathepsin D,107 dynactin subunit 2,108,109 ANXA6, PCMT1, and SPTAN1. Clathrin-mediated endocytosis is a key cellular signaling process involved in the fine-tuning of neurotransmission,106,110-112 and we have previously demonstrated changes of protein members of the CME interactome,106 namely amphiphysin,46 clathrin adaptor protein complex 2,113 protein kinase C and casein kinase in neurons 1,44 syntaxin-binding protein 1,42 and dynamin-1.44 These changes are in keeping with studies that found similar changes in the expression of SPTAN1,45 heat shock cognate 71-kDa protein,114 cathepsin D,90 and the clathrin coat assembly protein AP180 in schizophrenia.49 Findings have not, however, been entirely consistent; for example, dynamin-1 expression changes have been observed in some45,49,51 but not all115,116 studies, and changes in dynactin subunit 2 were observed in the opposite direction in a previous proteomic study of the anterior cingulate cortex.51 Consequently, we focused some of our validation experiments on proteins involved in CME and we confirmed changes in ANXA6, PCMT1, and SPTAN1. Annexin 6, which was confirmed to be downregulated in CA2/3 in bipolar disorder and schizophrenia, is a component of clathrin-coated vesicles117,118 and binds clathrin adaptor protein complex 2 to mediate interaction between endocytosing plasma membrane proteins and clathrin.117 Spectrin, which was also confirmed to be downregulated in bipolar disorder in CA2/3, is enriched in neurons and together with actin contributes to endocytosis119-121 and NMDA receptor activity.122 Finally, we observed reduced expression of the enzyme PCMT1 in CA4 in schizophrenia and bipolar disorder. It is highly expressed in the brain and participates in the degradation and/or repair of damaged proteins, including the core CME protein clathrin.123 In keeping with this latter finding, previous work has shown a downregulation of PCMT1 mRNA in the hippocampus in bipolar disorder.9
These findings implicate CME in schizophrenia and bipolar disorder. They are important because NMDA receptor hypofunction is a potential key pathophysiological mechanism in schizophrenia (see the articles by Coyle124 and Labrie and Roder125 for review) and may be caused by altered NMDA recycling.126 Furthermore, antipsychotics and mood stabilizers modulate CME to various degrees. For example, antipsychotics antagonize the interaction of dopamine D2 receptors with the CME-associated protein β-arrestin-2,127 and chlorpromazine inhibits CME.112 Furthermore, lithium inhibits β-arrestin and may influence CME.128 Finally, in keeping with our findings implicating cytoskeletal function in schizophrenia, there is growing evidence for a role of the actin cytoskeleton in CME through the modulation of cell membrane tension and the invagination of clathrin-coated pits.129 Thus, our findings implicating cytoskeletal function and CME may be related. Future work will need to consider the functional aspects of CME within cellular domains such as within the postsynaptic density130 where CME changes would directly affect NMDA recycling.
Our study has significant advantages such as its quantitative nature, reliability, and sensitivity.40,131 There are also several potential limitations. Postmortem brain studies are potentially confounded by premortem and postmortem factors; thus, we statistically adjusted for the variation introduced by age, brain pH, postmortem interval, and refrigerator interval. We also carried out post hoc analyses within the disease groups for the effects of antipsychotic medication, mood stabilizers, and antidepressants (eTable 5). Forty-five proteins were implicated by these analyses, but most in the direction opposite to that observed in disease, thus arguing against our findings being due to medication effects. However, for 2 proteins relevant to our discussion, dynactin subunit 2 and FSCN1, alterations were in the same direction as that associated with mood stabilizers and may reflect treatment effects with mood stabilizers (although in the case of FSCN1, reduced expression was observed even after excluding subjects exposed to mood stabilizers [data not shown]). There was no evidence that the changes observed in any of the other validated proteins were due to psychotropic drug exposures. Furthermore, long-term exposure of mice to the antipsychotic drug haloperidol did not alter the expression of the proteins confirmed to be dysregulated in disease, suggesting that the changes observed in disease were not related to treatment with this antipsychotic agent. Nonetheless, while we can correct statistically for these potential confounders, such corrections are imperfect and it is possible that some of our findings are due in part to such confounders as drug exposure or environmental deprivation. Our findings should therefore be interpreted with some caution pending further information regarding the influence of these and other potential confounders. Finally, the 2D-DIGE method has some disadvantages such as the inability to resolve all proteins within a given proteome. Specific classes of proteins, particularly those with low abundance, exceptionally small or large proteins, and proteins that are highly hydrophobic or basic, remain difficult to visualize.39 For this reason, candidate transmembrane receptor proteins such as NMDA and GABA receptor proteins73 were not resolved in our gels and were not assessed. Our data should be viewed as complementary to rather than opposing this previous literature.
A challenge of proteomic analysis involves the necessity of assessing multiple spots and the possibility of type I error. At the 5% level of significance, there was an excess of statistically significant spots (up to 8% depending on brain region). While an excess of statistically significant spots was found, these corresponded to, at most, moderate changes in protein abundance and the realized P values were not on a small enough scale to offset any adjustment of false discovery rate when brain regions were analyzed separately. However, many spots remained significant using the 5% level of false discovery rate when all 4 brain regions were analyzed together in a single model (as a factor) while allowing different brain regions to differ in effect (eTable 4 and eTable 5). This was a consequence of the greater precision arising from a greater number of replicates effectively analyzed. To further compensate for potential false-positive results, we also selected a number of proteins for validation.
Our innovative use of pooled samples for the validation work is unusual and was necessitated by the unique and small amounts of available tissue dissected by laser-assisted microdissection. We confirmed altered expression of ANXA6, PCMT1, SEPT11, and SPTAN1 in schizophrenia and/or bipolar disorder, but we could not confirm the altered expression of ARMCX1. Changes in FSCN1 were confirmed only in schizophrenia and not in bipolar disorder. Further, while it was not technically feasible for us to validate all of our findings, many of our findings are consistent with previous studies where altered expressions of dynamin-1,44,45,51 neurofilament light polypeptide and neurofilament medium polypeptide,46,90 N(G),N(G)-dimethylarginine dimethylaminohydrolase 1,42,90 ubiquitin carboxyl-terminal hydrolase isozyme L1 and cathepsin D,90 α-internexin,44 dihydropyrimidinase-related protein 2,42 14-3-3 protein,46,90 stathmin,46,90 fructose bisphosphate aldolase C,46,50 peroxiredoxins42,45,90 and superoxide dismutase,51,90 α-enolase, and galectin-142,46 have been reported.
Our observation that a significant minority of proteins were differentially expressed in more than 1 hippocampal region in each disease offers reassurance that these latter changes are unlikely to represent chance findings. Thus, for 15 of 67 proteins shown to be differentially expressed in schizophrenia (eg, SEPT11, PCMT1, cathepsin D, adenosine triphosphate synthase, N(G),N(G)-dimethylarginine dimethylaminohydrolase 1) and 25 of 115 proteins for bipolar disorder (eg, PCMT1, adenosine triphosphate synthase, N(G),N(G)-dimethylarginine dimethylaminohydrolase 1, FSCN1, dynactin subunit 2), we also found similar significant changes in protein expression in 1 or more of the other hippocampal regions (eTable 4 and eTable 5). In the future, high-throughput validation methods such as multiple reaction monitoring,132 a label-free relative quantitative proteomic analysis, may allow us to confirm a greater number of proteins regardless of antibody availability.
In conclusion, our findings provide novel insights into the common disease pathogenesis of both schizophrenia and bipolar disorder. They also show a particular focus of altered protein expression changes in the CA2/3 region of these disorders.
Correspondence: David R. Cotter, MD, PhD, Department of Psychiatry, Royal College of Surgeons in Ireland, Education and Research Centre, Beaumont Hospital, Dublin 9, Ireland (drcotter@rcsi.ie).
Submitted for Publication: August 6, 2010; final revision received November 1, 2010; accepted December 16, 2010.
Financial Disclosure: None reported.
Funding/Support: This work was supported by the Wellcome Trust, NARSAD, and the Stanley Medical Research Institute.
Additional Contributions: Postmortem brains were donated by the Stanley Foundation Brain Bank Consortium courtesy of Llewellyn B. Bigelow, MD, Maree J. Webster, PhD, and staff. Koh-ichi Nagata, MD, PhD, donated the SEPT11 antibody. We thank the donors. Lance Hudson, BSc, Niamh Connolly, MSc, and Conn Hastings, BSc, shared their expertise in laser-assisted microdissection and animal work, Caitriona Scaife, BSc, provided technical assistance in 2D-DIGE image analysis, Peter Knief, PhD, helped with the figures, and Mary Cannon, MD, PhD, provided input into the final manuscript. Access to and use of mass spectrometry instrumentation of the Conway Institute is gratefully acknowledged; Giuliano Elia, PhD, Cathy Rooney, BSc, and Kasper Pedersen, BSc provided technical assistance in mass spectrometry.
1.Harrison
PJ The hippocampus in schizophrenia: a review of the neuropathological evidence and its pathophysiological implications.
Psychopharmacology (Berl) 2004;174
(1)
151- 162
PubMedGoogle Scholar 2.Wright
ICRabe-Hesketh
SWoodruff
PWDavid
ASMurray
RMBullmore
ET Meta-analysis of regional brain volumes in schizophrenia.
Am J Psychiatry 2000;157
(1)
16- 25
PubMedGoogle Scholar 3.Velakoulis
DWood
SJWong
MTMcGorry
PDYung
APhillips
LSmith
DBrewer
WProffitt
TDesmond
PPantelis
C Hippocampal and amygdala volumes according to psychosis stage and diagnosis: a magnetic resonance imaging study of chronic schizophrenia, first-episode psychosis, and ultra-high-risk individuals.
Arch Gen Psychiatry 2006;63
(2)
139- 149
PubMedGoogle Scholar 4.Lawrie
SMWhalley
HKestelman
JNAbukmeil
SSByrne
MHodges
ARimmington
JEBest
JJOwens
DGJohnstone
EC Magnetic resonance imaging of brain in people at high risk of developing schizophrenia.
Lancet 1999;353
(9146)
30- 33
PubMedGoogle Scholar 5.DeLisi
LESakuma
MTew
WKushner
MHoff
ALGrimson
R Schizophrenia as a chronic active brain process: a study of progressive brain structural change subsequent to the onset of schizophrenia.
Psychiatry Res 1997;74
(3)
129- 140
PubMedGoogle Scholar 6.Fornito
AYücel
MPantelis
C Reconciling neuroimaging and neuropathological findings in schizophrenia and bipolar disorder.
Curr Opin Psychiatry 2009;22
(3)
312- 319
PubMedGoogle Scholar 7.Harrison
PJ The neuropathology of primary mood disorder.
Brain 2002;125
(pt 7)
1428- 1449
PubMedGoogle Scholar 8.Savitz
JDrevets
WC Bipolar and major depressive disorder: neuroimaging the developmental-degenerative divide.
Neurosci Biobehav Rev 2009;33
(5)
699- 771
PubMedGoogle Scholar 9.Konradi
CEaton
MMacDonald
MLWalsh
JBenes
FMHeckers
S Molecular evidence for mitochondrial dysfunction in bipolar disorder.
Arch Gen Psychiatry 2004;61
(3)
300- 308
PubMedGoogle Scholar 10.Amaral
DGInsausti
R Hippocampal formation. Paxinos
Ged.
The Human Nervous System. San Diego, CA Academic Press1990;711- 735
Google Scholar 11.Duvernoy
HM The Human Hippocampus: Functional Anatomy, Vascularization and Serial Sections With MRI. 2nd Berlin, Germany Springer1998;
12.Cotter
DKerwin
Ral-Sarraji
SBrion
JPChadwich
ALovestone
SAnderton
BEverall
I Abnormalities of Wnt signalling in schizophrenia: evidence for neurodevelopmental abnormality.
Neuroreport 1998;9
(7)
1379- 1383
PubMedGoogle Scholar 13.Holinger
DPHarrison
PJ Cerebral asymmetry. Harrison
PJRoberts
GWeds.
The Neuropathology of Schizophrenia: Progress and Interpretation. Oxford, England Oxford University Press2000;151- 171
Google Scholar 14.Heckers
SHeinsen
HGeiger
BBeckmann
H Hippocampal neuron number in schizophrenia: a stereological study.
Arch Gen Psychiatry 1991;48
(11)
1002- 1008
PubMedGoogle Scholar 15.Benes
FMSorensen
IBird
ED Reduced neuronal size in posterior hippocampus of schizophrenic patients.
Schizophr Bull 1991;17
(4)
597- 608
PubMedGoogle Scholar 16.Falkai
PBogerts
B Cell loss in the hippocampus of schizophrenics.
Eur Arch Psychiatry Neurol Sci 1986;236
(3)
154- 161
PubMedGoogle Scholar 17.Benes
FM Amygdalocortical circuitry in schizophrenia: from circuits to molecules.
Neuropsychopharmacology 2010;35
(1)
239- 257
PubMedGoogle Scholar 18.Benes
FMKwok
EWVincent
SLTodtenkopf
MS A reduction of nonpyramidal cells in sector CA2 of schizophrenics and manic depressives.
Biol Psychiatry 1998;44
(2)
88- 97
PubMedGoogle Scholar 19.Rosoklija
GToomayan
GEllis
SPKeilp
JMann
JJLatov
NHays
APDwork
AJ Structural abnormalities of subicular dendrites in subjects with schizophrenia and mood disorders: preliminary findings.
Arch Gen Psychiatry 2000;57
(4)
349- 356
PubMedGoogle Scholar 20.Kerwin
RPatel
SMeldrum
B Quantitative autoradiographic analysis of glutamate binding sites in the hippocampal formation in normal and schizophrenic brain post mortem.
Neuroscience 1990;39
(1)
25- 32
PubMedGoogle Scholar 21.Law
AJWeickert
CSHyde
TMKleinman
JEHarrison
PJ Reduced spinophilin but not microtubule-associated protein 2 expression in the hippocampal formation in schizophrenia and mood disorders: molecular evidence for a pathology of dendritic spines.
Am J Psychiatry 2004;161
(10)
1848- 1855
PubMedGoogle Scholar 22.Harrison
PJEastwood
SL Neuropathological studies of synaptic connectivity in the hippocampal formation in schizophrenia.
Hippocampus 2001;11
(5)
508- 519
PubMedGoogle Scholar 23.Uezato
AMeador-Woodruff
JHMcCullumsmith
RE Vesicular glutamate transporter mRNA expression in the medial temporal lobe in major depressive disorder, bipolar disorder, and schizophrenia.
Bipolar Disord 2009;11
(7)
711- 725
PubMedGoogle Scholar 24.Eastwood
SLHarrison
PJ Decreased expression of vesicular glutamate transporter 1 and complexin II mRNAs in schizophrenia: further evidence for a synaptic pathology affecting glutamate neurons.
Schizophr Res 2005;73
(2-3)
159- 172
PubMedGoogle Scholar 25.Eastwood
SLHarrison
PJ Decreased mRNA expression of netrin-G1 and netrin-G2 in the temporal lobe in schizophrenia and bipolar disorder.
Neuropsychopharmacology 2008;33
(4)
933- 945
PubMedGoogle Scholar 26.Barr
AMYoung
CEPhillips
AGHoner
WG Selective effects of typical antipsychotic drugs on SNAP-25 and synaptophysin in the hippocampal trisynaptic pathway.
Int J Neuropsychopharmacol 2006;9
(4)
457- 463
PubMedGoogle Scholar 27.Sawada
KBarr
AMNakamura
MArima
KYoung
CEDwork
AJFalkai
PPhillips
AGHoner
WG Hippocampal complexin proteins and cognitive dysfunction in schizophrenia.
Arch Gen Psychiatry 2005;62
(3)
263- 272
PubMedGoogle Scholar 28.Shi
JLevinson
DFDuan
JSanders
ARZheng
YPe’er
IDudbridge
FHolmans
PAWhittemore
ASMowry
BJOlincy
AAmin
FCloninger
CRSilverman
JMBuccola
NGByerley
WFBlack
DWCrowe
RROksenberg
JRMirel
DBKendler
KSFreedman
RGejman
PV Common variants on chromosome 6p22.1 are associated with schizophrenia.
Nature 2009;460
(7256)
753- 757
PubMedGoogle Scholar 29.Stefansson
HOphoff
RASteinberg
SAndreassen
OACichon
SRujescu
DWerge
TPietiläinen
OPMors
OMortensen
PBSigurdsson
EGustafsson
ONyegaard
MTuulio-Henriksson
AIngason
AHansen
TSuvisaari
JLonnqvist
JPaunio
TBørglum
ADHartmann
AFink-Jensen
ANordentoft
MHougaard
DNorgaard-Pedersen
BBöttcher
YOlesen
JBreuer
RMöller
HJGiegling
IRasmussen
HBTimm
SMattheisen
MBitter
IRéthelyi
JMMagnusdottir
BBSigmundsson
TOlason
PMasson
GGulcher
JRHaraldsson
MFossdal
RThorgeirsson
TEThorsteinsdottir
URuggeri
MTosato
SFranke
BStrengman
EKiemeney
LAMelle
IDjurovic
SAbramova
LKaleda
VSanjuan
Jde Frutos
RBramon
EVassos
EFraser
GEttinger
UPicchioni
MWalker
NToulopoulou
TNeed
ACGe
DYoon
JLShianna
KVFreimer
NBCantor
RMMurray
RKong
AGolimbet
VCarracedo
AArango
CCostas
JJönsson
EGTerenius
LAgartz
IPetursson
HNöthen
MMRietschel
MMatthews
PMMuglia
PPeltonen
LSt Clair
DGoldstein
DBStefansson
KCollier
DAGenetic Risk and Outcome in Psychosis, Common variants conferring risk of schizophrenia.
Nature 2009;460
(7256)
744- 747
PubMedGoogle Scholar 30.Huffaker
SJChen
JNicodemus
KKSambataro
FYang
FMattay
VLipska
BKHyde
TMSong
JRujescu
DGiegling
IMayilyan
KProust
MJSoghoyan
ACaforio
GCallicott
JHBertolino
AMeyer-Lindenberg
AChang
JJi
YEgan
MFGoldberg
TEKleinman
JELu
BWeinberger
DR A primate-specific, brain isoform of KCNH2 affects cortical physiology, cognition, neuronal repolarization and risk of schizophrenia.
Nat Med 2009;15
(5)
509- 518
PubMedGoogle Scholar 31.Williams
HJNorton
NDwyer
SMoskvina
VNikolov
ICarroll
LGeorgieva
LWilliams
NMMorris
DWQuinn
EMGiegling
IIkeda
MWood
JLencz
THultman
CLichtenstein
PThiselton
DMaher
BSMalhotra
AKRiley
BKendler
KSGill
MSullivan
PSklar
PPurcell
SNimgaonkar
VLKirov
GHolmans
PCorvin
ARujescu
DCraddock
NOwen
MJO'Donovan
MCMolecular Genetics of Schizophrenia Collaboration (MGS) International Schizophrenia Consortium (ISC); SGENE-plus; GROUP, Fine mapping of ZNF804A and genome-wide significant evidence for its involvement in schizophrenia and bipolar disorder [published online April 6, 2010].
Mol Psychiatry PubMed10.1038/mp.2010.36
Google Scholar 32.Lichtenstein
PYip
BHBjörk
CPawitan
YCannon
TDSullivan
PFHultman
CM Common genetic determinants of schizophrenia and bipolar disorder in Swedish families: a population-based study.
Lancet 2009;373
(9659)
234- 239
PubMedGoogle Scholar 33.Owen
MJCraddock
N Diagnosis of functional psychoses: time to face the future.
Lancet 2009;373
(9659)
190- 191
PubMedGoogle Scholar 34.Baloyianni
NTsangaris
GT The audacity of proteomics: a chance to overcome current challenges in schizophrenia research.
Expert Rev Proteomics 2009;6
(6)
661- 674
PubMedGoogle Scholar 35.Anderson
LSeilhamer
J A comparison of selected mRNA and protein abundances in human liver.
Electrophoresis 1997;18
(3-4)
533- 537
PubMedGoogle Scholar 36.Paulson
LMartin
PPersson
ANilsson
CLLjung
EWestman-Brinkmalm
AEriksson
PSBlennow
KDavidsson
P Comparative genome- and proteome analysis of cerebral cortex from MK-801-treated rats.
J Neurosci Res 2003;71
(4)
526- 533
PubMedGoogle Scholar 37.Bayés
AGrant
SG Neuroproteomics: understanding the molecular organization and complexity of the brain.
Nat Rev Neurosci 2009;10
(9)
635- 646
PubMedGoogle Scholar 38.English
JAPennington
KDunn
MJCotter
DR The neuroproteomics of schizophrenia.
Biol Psychiatry 2011;69
(2)
163- 172
PubMedGoogle Scholar 39.Görg
AWeiss
WDunn
MJ Current two-dimensional electrophoresis technology for proteomics.
Proteomics 2004;4
(12)
3665- 3685
PubMedGoogle Scholar 40.Tannu
NSHemby
SE Two-dimensional fluorescence difference gel electrophoresis for comparative proteomics profiling.
Nat Protoc 2006;1
(4)
1732- 1742
PubMedGoogle Scholar 41.Martins-de-Souza
DGattaz
WFSchmitt
ARewerts
CMaccarrone
GDias-Neto
ETurck
CW Prefrontal cortex shotgun proteome analysis reveals altered calcium homeostasis and immune system imbalance in schizophrenia.
Eur Arch Psychiatry Clin Neurosci 2009;259
(3)
151- 163
PubMedGoogle Scholar 42.Behan
ATByrne
CDunn
MJCagney
GCotter
DR Proteomic analysis of membrane microdomain-associated proteins in the dorsolateral prefrontal cortex in schizophrenia and bipolar disorder reveals alterations in LAMP, STXBP1 and BASP1 protein expression.
Mol Psychiatry 2009;14
(6)
601- 613
PubMedGoogle Scholar 43.Martins-de-Souza
DGattaz
WFSchmitt
AMaccarrone
GHunyadi-Gulyás
EEberlin
MNSouza
GHMarangoni
SNovello
JCTurck
CWDias-Neto
E Proteomic analysis of dorsolateral prefrontal cortex indicates the involvement of cytoskeleton, oligodendrocyte, energy metabolism and new potential markers in schizophrenia.
J Psychiatr Res 2009;43
(11)
978- 986
PubMedGoogle Scholar 44.Pennington
KBeasley
CLDicker
PFagan
AEnglish
JPariante
CMWait
RDunn
MJCotter
DR Prominent synaptic and metabolic abnormalities revealed by proteomic analysis of the dorsolateral prefrontal cortex in schizophrenia and bipolar disorder.
Mol Psychiatry 2008;13
(12)
1102- 1117
PubMedGoogle Scholar 45.Prabakaran
SSwatton
JERyan
MMHuffaker
SJHuang
JTGriffin
JLWayland
MFreeman
TDudbridge
FLilley
KSKarp
NAHester
STkachev
DMimmack
MLYolken
RHWebster
MJTorrey
EFBahn
S Mitochondrial dysfunction in schizophrenia: evidence for compromised brain metabolism and oxidative stress.
Mol Psychiatry 2004;9
(7)
684- 697
PubMedGoogle Scholar 46.English
JADicker
PFöcking
MDunn
MJCotter
DR 2-D DIGE analysis implicates cytoskeletal abnormalities in psychiatric disease.
Proteomics 2009;9
(12)
3368- 3382
PubMedGoogle Scholar 47.Novikova
SIHe
FCutrufello
NJLidow
MS Identification of protein biomarkers for schizophrenia and bipolar disorder in the postmortem prefrontal cortex using SELDI-TOF-MS ProteinChip profiling combined with MALDI-TOF-PSD-MS analysis.
Neurobiol Dis 2006;23
(1)
61- 76
PubMedGoogle Scholar 48.Johnston-Wilson
NLSims
CDHofmann
JPAnderson
LShore
ADTorrey
EFYolken
RHStanley Neuropathology Consortium, Disease-specific alterations in frontal cortex brain proteins in schizophrenia, bipolar disorder, and major depressive disorder.
Mol Psychiatry 2000;5
(2)
142- 149
PubMedGoogle Scholar 49.Chan
MKTsang
TMHarris
LWGuest
PCHolmes
EBahn
S Evidence for disease and antipsychotic medication effects in post-mortem brain from schizophrenia patients [published online October 5, 2010].
Mol Psychiatry PubMed10.1038/mp.2010.100
Google Scholar 50.Beasley
CLPennington
KBehan
AWait
RDunn
MJCotter
D Proteomic analysis of the anterior cingulate cortex in the major psychiatric disorders: evidence for disease-associated changes.
Proteomics 2006;6
(11)
3414- 3425
PubMedGoogle Scholar 51.Clark
DDedova
ICordwell
SMatsumoto
I A proteome analysis of the anterior cingulate cortex gray matter in schizophrenia.
Mol Psychiatry 2006;11
(5)
459- 470
PubMedGoogle Scholar 52.Martins-de-Souza
DSchmitt
ARöder
RLebar
MSchneider-Axmann
TFalkai
PTurck
CW Sex-specific proteome differences in the anterior cingulate cortex of schizophrenia.
J Psychiatr Res 2010;44
(14)
989- 991
PubMedGoogle Scholar 53.Martins-de-Souza
DGattaz
WFSchmitt
ARewerts
CMarangoni
SNovello
JCMaccarrone
GTurck
CWDias-Neto
E Alterations in oligodendrocyte proteins, calcium homeostasis and new potential markers in schizophrenia anterior temporal lobe are revealed by shotgun proteome analysis.
J Neural Transm 2009;116
(3)
275- 289
PubMedGoogle Scholar 54.Edgar
PFDouglas
JECooper
GJDean
BKydd
RFaull
RL Comparative proteome analysis of the hippocampus implicates chromosome 6q in schizophrenia.
Mol Psychiatry 2000;5
(1)
85- 90
PubMedGoogle Scholar 55.Mexal
SBerger
RAdams
CERoss
RGFreedman
RLeonard
S Brain pH has a significant impact on human postmortem hippocampal gene expression profiles.
Brain Res 2006;1106
(1)
1- 11
PubMedGoogle Scholar 56.Vawter
MPTomita
HMeng
FBolstad
BLi
JEvans
SChoudary
PAtz
MShao
LNeal
CWalsh
DMBurmeister
MSpeed
TMyers
RJones
EGWatson
SJAkil
HBunney
WE Mitochondrial-related gene expression changes are sensitive to agonal-pH state: implications for brain disorders.
Mol Psychiatry 2006;11
(7)
615, 663- 679
PubMedGoogle Scholar 57.Shekouh
ARThompson
CCPrime
WCampbell
FHamlett
JHerrington
CSLemoine
NRCrnogorac-Jurcevic
TBuechler
MWFriess
HNeoptolemos
JPPennington
SRCostello
E Application of laser capture microdissection combined with two-dimensional electrophoresis for the discovery of differentially regulated proteins in pancreatic ductal adenocarcinoma.
Proteomics 2003;3
(10)
1988- 2001
PubMedGoogle Scholar 58.Pennington
KDicker
PDunn
MJCotter
DR Proteomic analysis reveals protein changes within layer 2 of the insular cortex in schizophrenia.
Proteomics 2008;8
(23-24)
5097- 5107
PubMedGoogle Scholar 59.Föcking
MBoersema
PJO’Donoghue
NLubec
GPennington
SRCotter
DRDunn
MJ 2-D DIGE as a quantitative tool for investigating the HUPO Brain Proteome Project mouse series.
Proteomics 2006;6
(18)
4914- 4931
PubMedGoogle Scholar 60.Benjamini
YHochberg
Y Controlling the false discovery rate: a practical and powerful approach to multiple testing.
J R Stat Soc Series B Stat Methodol 1995;57
(1)
289- 300
Google Scholar 61.Centorrino
FEakin
MBahk
WMKelleher
JPGoren
JSalvatore
PEgli
SBaldessarini
RJ Inpatient antipsychotic drug use in 1998, 1993, and 1989.
Am J Psychiatry 2002;159
(11)
1932- 1935
PubMedGoogle Scholar 62.Lau
CGZukin
RS NMDA receptor trafficking in synaptic plasticity and neuropsychiatric disorders.
Nat Rev Neurosci 2007;8
(6)
413- 426
PubMedGoogle Scholar 63.Benes
FMBerretta
S GABAergic interneurons: implications for understanding schizophrenia and bipolar disorder.
Neuropsychopharmacology 2001;25
(1)
1- 27
PubMedGoogle Scholar 64.Benes
FMKhan
YVincent
SLWickramasinghe
R Differences in the subregional and cellular distribution of GABAA receptor binding in the hippocampal formation of schizophrenic brain.
Synapse 1996;22
(4)
338- 349
PubMedGoogle Scholar 65.Benes
FMLim
BMatzilevich
DWalsh
JPSubburaju
SMinns
M Regulation of the GABA cell phenotype in hippocampus of schizophrenics and bipolars.
Proc Natl Acad Sci U S A 2007;104
(24)
10164- 10169
PubMedGoogle Scholar 66.Benes
FMTodtenkopf
MS Effect of age and neuroleptics on tyrosine hydroxylase-IR in sector CA2 of schizophrenic brain.
Neuroreport 1999;10
(17)
3527- 3530
PubMedGoogle Scholar 67.Pantazopoulos
HStone
DWalsh
JBenes
FM Differences in the cellular distribution of D1 receptor mRNA in the hippocampus of bipolars and schizophrenics.
Synapse 2004;54
(3)
147- 155
PubMedGoogle Scholar 68.Todtenkopf
MSBenes
FM Distribution of glutamate decarboxylase65 immunoreactive puncta on pyramidal and nonpyramidal neurons in hippocampus of schizophrenic brain.
Synapse 1998;29
(4)
323- 332
PubMedGoogle Scholar 69.Benes
FMBerretta
S Amygdalo-entorhinal inputs to the hippocampal formation in relation to schizophrenia.
Ann N Y Acad Sci 2000;911293- 304
PubMedGoogle Scholar 70.Berretta
SLange
NBhattacharyya
SSebro
RGarces
JBenes
FM Long-term effects of amygdala GABA receptor blockade on specific subpopulations of hippocampal interneurons.
Hippocampus 2004;14
(7)
876- 894
PubMedGoogle Scholar 71.Mizukami
KSasaki
MIshikawa
MIwakiri
MHidaka
SShiraishi
HIritani
S Immunohistochemical localization of gamma-aminobutyric acid(B) receptor in the hippocampus of subjects with schizophrenia.
Neurosci Lett 2000;283
(2)
101- 104
PubMedGoogle Scholar 72.Knable
MBBarci
BMWebster
MJMeador-Woodruff
JTorrey
EFStanley Neuropathology Consortium, Molecular abnormalities of the hippocampus in severe psychiatric illness: postmortem findings from the Stanley Neuropathology Consortium.
Mol Psychiatry 2004;9
(6)
609- 620
PubMedGoogle Scholar 73.Harrison
PJWeinberger
DR Schizophrenia genes, gene expression, and neuropathology: on the matter of their convergence.
Mol Psychiatry 2005;10
(1)
40- 68
PubMedGoogle Scholar 74.Dean
BScarr
EMcLeod
M Changes in hippocampal GABAA receptor subunit composition in bipolar 1 disorder.
Brain Res Mol Brain Res 2005;138
(2)
145- 155
PubMedGoogle Scholar 75.Benes
FMTodtenkopf
MSKostoulakos
P GluR5,6,7 subunit immunoreactivity on apical pyramidal cell dendrites in hippocampus of schizophrenics and manic depressives.
Hippocampus 2001;11
(5)
482- 491
PubMedGoogle Scholar 76.Cotter
DLandau
SBeasley
CStevenson
RChana
GMacMillan
LEverall
I The density and spatial distribution of GABAergic neurons, labelled using calcium binding proteins, in the anterior cingulate cortex in major depressive disorder, bipolar disorder, and schizophrenia.
Biol Psychiatry 2002;51
(5)
377- 386
PubMedGoogle Scholar 77.Woo
TUShrestha
KAmstrong
CMinns
MMWalsh
JPBenes
FM Differential alterations of kainate receptor subunits in inhibitory interneurons in the anterior cingulate cortex in schizophrenia and bipolar disorder.
Schizophr Res 2007;96
(1-3)
46- 61
PubMedGoogle Scholar 78.Benes
FMBird
ED An analysis of the arrangement of neurons in the cingulate cortex of schizophrenic patients.
Arch Gen Psychiatry 1987;44
(7)
608- 616
PubMedGoogle Scholar 79.Benes
FM Neural circuitry models of schizophrenia: is it dopamine, GABA, glutamate, or something else?
Biol Psychiatry 2009;65
(12)
1003- 1005
PubMedGoogle Scholar 80.Rosene
DLVan Hoesen
GW Hippocampal efferents reach widespread areas of cerebral cortex and amygdala in the rhesus monkey.
Science 1977;198
(4314)
315- 317
PubMedGoogle Scholar 81.Heckers
SKonradi
C Hippocampal neurons in schizophrenia.
J Neural Transm 2002;109
(5-6)
891- 905
PubMedGoogle Scholar 82.Schobel
SALewandowski
NMCorcoran
CMMoore
HBrown
TMalaspina
DSmall
SA Differential targeting of the CA1 subfield of the hippocampal formation by schizophrenia and related psychotic disorders.
Arch Gen Psychiatry 2009;66
(9)
938- 946
PubMedGoogle Scholar 83.Kolomeets
NSOrlovskaya
DDUranova
NA Decreased numerical density of CA3 hippocampal mossy fiber synapses in schizophrenia.
Synapse 2007;61
(8)
615- 621
PubMedGoogle Scholar 84.McDonald
CMarshall
NSham
PCBullmore
ETSchulze
KChapple
BBramon
EFilbey
FQuraishi
SWalshe
MMurray
RM Regional brain morphometry in patients with schizophrenia or bipolar disorder and their unaffected relatives.
Am J Psychiatry 2006;163
(3)
478- 487
PubMedGoogle Scholar 85.Ng
WXLau
IYGraham
SSim
K Neurobiological evidence for thalamic, hippocampal and related glutamatergic abnormalities in bipolar disorder: a review and synthesis.
Neurosci Biobehav Rev 2009;33
(3)
336- 354
PubMedGoogle Scholar 86.Bilder
RMBogerts
BAshtari
MWu
HAlvir
JMJody
DReiter
GBell
LLieberman
JA Anterior hippocampal volume reductions predict frontal lobe dysfunction in first episode schizophrenia.
Schizophr Res 1995;17
(1)
47- 58
PubMedGoogle Scholar 87.Owen
MJCraddock
NO’Donovan
MC Suggestion of roles for both common and rare risk variants in genome-wide studies of schizophrenia.
Arch Gen Psychiatry 2010;67
(7)
667- 673
PubMedGoogle Scholar 88.Birmaher
BAxelson
DMonk
KKalas
CGoldstein
BHickey
MBObreja
MEhmann
MIyengar
SShamseddeen
WKupfer
DBrent
D Lifetime psychiatric disorders in school-aged offspring of parents with bipolar disorder: the Pittsburgh Bipolar Offspring study.
Arch Gen Psychiatry 2009;66
(3)
287- 296
PubMedGoogle Scholar 89.Carpenter
WTBustillo
JRThaker
GKvan Os
JKrueger
RFGreen
MJ The psychoses: cluster 3 of the proposed meta-structure for
DSM-V and
ICD-11.
Psychol Med 2009;39
(12)
2025- 2042
PubMedGoogle Scholar 90.Nesvaderani
MMatsumoto
ISivagnanasundaram
S Anterior hippocampus in schizophrenia pathogenesis: molecular evidence from a proteome study.
Aust N Z J Psychiatry 2009;43
(4)
310- 322
PubMedGoogle Scholar 91.Benes
FMMatzilevich
DBurke
REWalsh
J The expression of proapoptosis genes is increased in bipolar disorder, but not in schizophrenia.
Mol Psychiatry 2006;11
(3)
241- 251
PubMedGoogle Scholar 92.Buttner
NBhattacharyya
SWalsh
JBenes
FM DNA fragmentation is increased in non-GABAergic neurons in bipolar disorder but not in schizophrenia.
Schizophr Res 2007;93
(1-3)
33- 41
PubMedGoogle Scholar 93.Mimmack
MLRyan
MBaba
HNavarro-Ruiz
JIritani
SFaull
RLMcKenna
PJJones
PBArai
HStarkey
MEmson
PCBahn
S Gene expression analysis in schizophrenia: reproducible up-regulation of several members of the apolipoprotein L family located in a high-susceptibility locus for schizophrenia on chromosome 22.
Proc Natl Acad Sci U S A 2002;99
(7)
4680- 4685
PubMedGoogle Scholar 94.Altar
CAJurata
LWCharles
VLemire
ALiu
PBukhman
YYoung
TABullard
JYokoe
HWebster
MJKnable
MBBrockman
JA Deficient hippocampal neuron expression of proteasome, ubiquitin, and mitochondrial genes in multiple schizophrenia cohorts.
Biol Psychiatry 2005;58
(2)
85- 96
PubMedGoogle Scholar 95.Shao
LVawter
MP Shared gene expression alterations in schizophrenia and bipolar disorder.
Biol Psychiatry 2008;64
(2)
89- 97
PubMedGoogle Scholar 96.Hemby
SEGinsberg
SDBrunk
BArnold
SETrojanowski
JQEberwine
JH Gene expression profile for schizophrenia: discrete neuron transcription patterns in the entorhinal cortex.
Arch Gen Psychiatry 2002;59
(7)
631- 640
PubMedGoogle Scholar 97.Ryan
MMLockstone
HEHuffaker
SJWayland
MTWebster
MJBahn
S Gene expression analysis of bipolar disorder reveals downregulation of the ubiquitin cycle and alterations in synaptic genes.
Mol Psychiatry 2006;11
(10)
965- 978
PubMedGoogle Scholar 98.Mirnics
KLevitt
PLewis
DA Critical appraisal of DNA microarrays in psychiatric genomics.
Biol Psychiatry 2006;60
(2)
163- 176
PubMedGoogle Scholar 99.Rietkerk
TBoks
MPSommer
IEde Jong
SKahn
RSOphoff
RA Network analysis of positional candidate genes of schizophrenia highlights myelin-related pathways.
Mol Psychiatry 2009;14
(4)
353- 355
PubMedGoogle Scholar 100.Ide
MLewis
DA Altered cortical CDC42 signaling pathways in schizophrenia: implications for dendritic spine deficits.
Biol Psychiatry 2010;68
(1)
25- 32
PubMedGoogle Scholar 101.Buser
AMErne
BWerner
HBNave
KASchaeren-Wiemers
N The septin cytoskeleton in myelinating glia.
Mol Cell Neurosci 2009;40
(2)
156- 166
PubMedGoogle Scholar 102.Xie
YVessey
JPKonecna
ADahm
RMacchi
PKiebler
MA The GTP-binding protein Septin 7 is critical for dendrite branching and dendritic-spine morphology.
Curr Biol 2007;17
(20)
1746- 1751
PubMedGoogle Scholar 103.Li
XSerwanski
DRMiralles
CPNagata
KDe Blas
AL Septin 11 is present in GABAergic synapses and plays a functional role in the cytoarchitecture of neurons and GABAergic synaptic connectivity.
J Biol Chem 2009;284
(25)
17253- 17265
PubMedGoogle Scholar 104.Kraft
REscobar
MMNarro
MLKurtis
JLEfrat
ABarnard
KRestifo
LL Phenotypes of
Drosophila brain neurons in primary culture reveal a role for fascin in neurite shape and trajectory.
J Neurosci 2006;26
(34)
8734- 8747
PubMedGoogle Scholar 105.Chang
LGoldman
RD Intermediate filaments mediate cytoskeletal crosstalk.
Nat Rev Mol Cell Biol 2004;5
(8)
601- 613
PubMedGoogle Scholar 106.Schmid
EMMcMahon
HT Integrating molecular and network biology to decode endocytosis.
Nature 2007;448
(7156)
883- 888
PubMedGoogle Scholar 107.Mills
IGPraefcke
GJVallis
YPeter
BJOlesen
LEGallop
JLButler
PJEvans
PRMcMahon
HT EpsinR: an AP1/clathrin interacting protein involved in vesicle trafficking.
J Cell Biol 2003;160
(2)
213- 222
PubMedGoogle Scholar 108.Zhao
YGaidarov
IKeen
JH Phosphoinositide 3-kinase C2alpha links clathrin to microtubule-dependent movement.
J Biol Chem 2007;282
(2)
1249- 1256
PubMedGoogle Scholar 109.Mead
CLKuzyk
MAMoradian
AWilson
GMHolt
RAMorin
GB Cytosolic protein interactions of the schizophrenia susceptibility gene dysbindin.
J Neurochem 2010;113
(6)
1491- 1503
PubMedGoogle Scholar 110.Traub
LM Tickets to ride: selecting cargo for clathrin-regulated internalization.
Nat Rev Mol Cell Biol 2009;10
(9)
583- 596
PubMedGoogle Scholar 112.Rodemer
CHaucke
V Clathrin/AP-2-dependent endocytosis: a novel playground for the pharmacological toolbox?
Handb Exp Pharmacol 2008;
(186)
105- 122
PubMedGoogle Scholar 113.Schubert
KOFöcking
MDicker
PDunn
MJCotter
DR Proteomic analysis of the basic sub-proteome (pH 6-11) in the hippocampus in schizophrenia and bipolar affective disorder.
Schizophr Res 2010;117
(2-3)
37210.1016/j.schres.2010.02.664
Google Scholar 114.Sivagnanasundaram
SCrossett
BDedova
ICordwell
SMatsumoto
I Abnormal pathways in the genu of the corpus callosum in schizophrenia pathogenesis: a proteome study.
Proteomics Clin Appl 2007;1
(10)
1291- 1305
PubMedGoogle Scholar 115.Gray
LJDean
BKronsbein
HCRobinson
PJScarr
E Region and diagnosis-specific changes in synaptic proteins in schizophrenia and bipolar I disorder.
Psychiatry Res 2010;178
(2)
374- 380
PubMedGoogle Scholar 116.Scarr
EGray
LKeriakous
DRobinson
PJDean
B Increased levels of SNAP-25 and synaptophysin in the dorsolateral prefrontal cortex in bipolar I disorder.
Bipolar Disord 2006;8
(2)
133- 143
PubMedGoogle Scholar 118.Grewal
THeeren
JMewawala
DSchnitgerhans
TWendt
DSalomon
GEnrich
CBeisiegel
UJäckle
S Annexin VI stimulates endocytosis and is involved in the trafficking of low density lipoprotein to the prelysosomal compartment.
J Biol Chem 2000;275
(43)
33806- 33813
PubMedGoogle Scholar 119.Kamal
AYing
YAnderson
RG Annexin VI-mediated loss of spectrin during coated pit budding is coupled to delivery of LDL to lysosomes.
J Cell Biol 1998;142
(4)
937- 947
PubMedGoogle Scholar 120.Doherty
GJMcMahon
HT Mediation, modulation, and consequences of membrane-cytoskeleton interactions.
Annu Rev Biophys 2008;3765- 95
PubMedGoogle Scholar 122.Wechsler
ATeichberg
VI Brain spectrin binding to the NMDA receptor is regulated by phosphorylation, calcium and calmodulin.
EMBO J 1998;17
(14)
3931- 3939
PubMedGoogle Scholar 123.Vigneswara
VLowenson
JDPowell
CDThakur
MBailey
KClarke
SRay
DECarter
WG Proteomic identification of novel substrates of a protein isoaspartyl methyltransferase repair enzyme.
J Biol Chem 2006;281
(43)
32619- 32629
PubMedGoogle Scholar 124.Coyle
JT Glutamate and schizophrenia: beyond the dopamine hypothesis.
Cell Mol Neurobiol 2006;26
(4-6)
365- 384
PubMedGoogle Scholar 125.Labrie
VRoder
JC The involvement of the NMDA receptor D-serine/glycine site in the pathophysiology and treatment of schizophrenia.
Neurosci Biobehav Rev 2010;34
(3)
351- 372
PubMedGoogle Scholar 126.Javitt
DCZukin
SR Recent advances in the phencyclidine model of schizophrenia.
Am J Psychiatry 1991;148
(10)
1301- 1308
PubMedGoogle Scholar 127.Masri
BSalahpour
ADidriksen
MGhisi
VBeaulieu
JMGainetdinov
RRCaron
MG Antagonism of dopamine D2 receptor/beta-arrestin 2 interaction is a common property of clinically effective antipsychotics.
Proc Natl Acad Sci U S A 2008;105
(36)
13656- 13661
PubMedGoogle Scholar 128.Clague
MJUrbé
Sde Lartigue
J Phosphoinositides and the endocytic pathway.
Exp Cell Res 2009;315
(9)
1627- 1631
PubMedGoogle Scholar 129.Galletta
BJMooren
OLCooper
JA Actin dynamics and endocytosis in yeast and mammals.
Curr Opin Biotechnol 2010;21
(5)
604- 610
PubMedGoogle Scholar 130.Hahn
CGBanerjee
AMacdonald
MLCho
DSKamins
JNie
ZBorgmann-Winter
KEGrosser
TPizarro
ACiccimaro
EArnold
SEWang
HYBlair
IA The post-synaptic density of human postmortem brain tissues: an experimental study paradigm for neuropsychiatric illnesses.
PLoS One 2009;4
(4)
e5251
PubMedGoogle Scholar 131.Marouga
RDavid
SHawkins
E The development of the DIGE system: 2D fluorescence difference gel analysis technology.
Anal Bioanal Chem 2005;382
(3)
669- 678
PubMedGoogle Scholar 132.Anderson
LHunter
CL Quantitative mass spectrometric multiple reaction monitoring assays for major plasma proteins.
Mol Cell Proteomics 2006;5
(4)
573- 588
PubMedGoogle Scholar