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Abstract

Objective: The purpose of the present study was to identify differentially expressed proteins in the anterior and posterior hippocampus of brains of schizophrenia patients compared to neurologically healthy controls.

Method: Proteins extracted from fresh frozen post-mortem posterior and anterior hippocampus for nine schizophrenia and nine control individuals, and seven schizophrenia and seven control individuals, respectively, were screened for differential expression using 2-D gel electrophoresis and mass spectrometry.

Results: A significantly larger number of protein spots were differentially expressed in the anterior (n = 43) compared to the posterior (n = 16) hippocampus, representing 34 and 14 unique proteins, respectively. These proteins are involved in cytoskeleton structure and function, neurotransmission and mitochondrial function.

Conclusion: Based on the aberrant protein expression profiles, the anterior hippocampus appears to be more involved in schizophrenia pathogenesis than the posterior hippocampus. Furthermore, consistent with previous findings, we found molecular evidence to support abnormal neuronal cytoarchitecture and function, neurotransmission and mitochondrial function in the schizophrenia hippocampus.

Keywords

Cytoskeleton hippocampus neurotransmitters proteomics schizophrenia

Neuroimaging and neuropathological studies implicate the hippocampus in schizophrenia pathogenesis [1]. Magnetic resonance imaging studies found decreased hippocampus volume in schizophrenia, which precedes onset of illness [2, 3]. A greater volume reduction in the anterior hippocampus (AH) compared to the posterior hippocampus (PH) has also been reported [4, 5]. A review of the neuropathological findings in the hippocampus of schizophrenia brains suggests subtle morphological alterations such as size, organization and shape of the neurons [6]. Molecular findings of decreased levels of synaptic proteins [7, 8] and dendritic indices [9] are consistent with findings of subtle morphological alterations suggesting a disturbance of connectivity within and between the hippocampus and other brain regions. Furthermore decreased levels of signalling proteins such as glutamate [10, 11], decreased γ-aminobutyric acid (GABA) interneurons [12] and serotonin and muscarinic receptor density [13, 14], decreased glucose metabolism [15], which has been associated with severity of positive symptoms [15–17] have also been reported. Finally, a large-scale microarray study has found the hippocampus to be one of the regions with the highest number of altered gene transcripts in schizophrenia [18] and an earlier proteomics study found 16 proteins altered in expression [19]. Because proteins are essential for cellular function, it is important to assess the changes in the proteome of the schizophrenia hippocampus in order to characterize in detail the molecular pathways responsible for abnormalities of this region in schizophrenia. Additionally, because the AH and PH are known to carry out different functions and also connect to different regions of the brain [5], it would be important to investigate the protein expression profiles in these two regions separately because this may provide a more detailed picture of the role of the hippocampus in schizophrenia. We hypothesize that the protein profiles of the AH are different to the PH based on the differences in the function and connectivity of each of these regions in the brain and we expect to find a larger number of alterations in the proteome of the AH compared to the PH based on the degree of pathology that has been reported for the AH in schizophrenia.

In the present study 2-D gel electrophoresis (2DGE) and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) were used to investigate protein expression differences in the AH and PH in schizophrenia subjects compared to matched controls in an unbiased manner. Distinct protein expression profiles of the schizophrenia brains are expected to consist of a mixture of proteins that may be altered as a result of causative pathogenesis of the disease, the effects of neuroleptic medication and secondary changes induced during the course of this long-lasting illness. The aims of this investigation were twofold: to clarify the extent of involvement of the AH and PH in schizophrenia pathogenesis at the level of protein expression; and to identify schizophrenia-related molecular mechanisms in the AH and PH that may explain some of the observed subtle neuropathology and functional impairment in these regions.

Methods

Human brain tissue samples

Fresh frozen post-mortem brain tissues from the AH and PH were provided by the NSW Tissue Resource Centre (University of Sydney, Sydney, NSW, Australia) from seven schizophrenia and seven control subjects, and nine schizophrenia and nine control subjects, respectively. AH was defined as where the amygdala ends and the ventral lateral thalamic nucleus appears. PH was defined as the region spanning the pulvinar thalami. Tissue was sectioned in the coronal plane and included all cornu ammonis regions and dentate gyrus. Subtle variations were expected in the proportion of neuronal populations sampled for each region from each case due to slight variations in the coronal blocks from which the hippocampus was sampled and from the sampling itself. The impact of these differences on protein analysis was minimized using biological replicates and a selection criterion that excluded from further analysis protein spots present in <30% of the cases examined. All schizophrenia subjects fulfilled DSM-IV criteria [20]. Subjects were determined to be free of significant neuropathology, and controls had no history of major psychiatric, neurological illnesses or drug abuse. All subjects were of Caucasian origin and were matched for gender, age, hemisphere, post-mortem interval (PMI) and brain pH, where possible. No significant difference was present between the schizophrenia and control groups in age, PMI or pH (p > 0.05). Information regarding schizophrenia subtype, duration of illness (DOI), neuroleptic dose and cause of death was provided for each subject (Table 1). Patients were treated with a range of typical neuroleptics except schizophrenia subject 4, who was treated with both typical and atypical neuroleptics. An estimated total amount of medication administered to each patient was determined by multiplying the DOI (days) with the median dose of medication (mg day⁻¹ chlorpromazine equivalent units, because the medication information provided by the NSW Tissue Resource Centre (TRC, University of Sydney, NSW, Australia) was the lifetime range from the lowest to the highest prescribed dose). Approval from the Central Sydney Area Health Service (Protocol Number X03-00285) was obtained for the use of human post-mortem brain tissue in the present study.

Table 1.

Subject details

Case no.	Gender	Age (years)	PMI (h)	PH	H	Cause of death	Type of schizophrenia	DOI (years)	CpzeEq (mg day⁻¹)
Anterior hippocampus
Control subjects
1	M	60	28	6.8	L	Ischaemic heart disease: coronary artery atherosclerosis
2	M	46	29	6.1	L	Acute myocardial infarction
3	F	60	21	6.8	L	Ischaemic heart disease
4	M	28	28	6.7	L	Doxepin toxicity
5	M	54	29	6.8	R	Coronary artery atheroma
6	F	71	16	6.2	L	Adenocarcinoma of the pancreas
7	M	78	6.5	6.2	L	Adenocarcinoma lung
Mean±SD		57±16.5	22.5±8.62	6.51±0.33

Schizophrenia subjects
1	M	57	48	6.7	R	Atherosclerotic cardiovascular disease	Paranoid (chronic)	17	225–975
2	M	40	21.5	6.2	L	Dihydrocodeine toxicity and obstructive sleep apnoea	Paranoid (chronic)	23	225–1800
3	F	58	19	6.1	L	Sepsis and chronic renal failure	Paranoid (episodic)	39	300–400
4	M	30	24	6.6	L	CO poisoning: suicide	Paranoid (episodic)	3.5	130–975
5	M	54	27.5	6.2	R	Coronary artery thrombosis	Paranoid (episodic)	35	50–600
6	F	66	12.5	6.5	R	Faecaloid peritonitis	Paranoid (chronic)	47	1200–2500
7	M	75	36	6.4	L	Ischaemic heart disease	Paranoid (continuous)	44	200–1200
Mean±SD		54±15.2	26.9±11.8	6.39±0.23			Paranoid (chronic)	17	225–975

Posterior hippocampus
Controls subjects
1	M	56	24	6.5	R	Coronary artery atheroma
2	M	37	24	6.4	R	Electrocution
3	F	60	21	6.8	L	Ischaemic heart disease
4	M	34	21	6.7	L	Acute exacerbation of asthma
5	M	53	16	6.8	R	Dilated cardiomyopathy
6	M	60	25	6.7	R	Bacterial peritonitis, ascites, carcinomatosis, gastrointestinal stomach tumour
7^†	F	60	21	6.8	L	Ischaemic heart disease
8	F	71	16	6.2	L	Adenocarcinoma of the pancreas
9	M	78	6.5	6.2	L	Adenocarcinoma lung
Mean±SD		57±14.2	19.39±5.82	6.57±0.25

Schizophrenia subjects
1	M	57	48	6.7	R	Atherosclerotic cardiovascular disease	Paranoid (chronic)	17	225–975
2	M	40	21.5	6.2	L	Dihydrocodeine toxicity and obstructive sleep apnoea	Paranoid (chronic)	23	225–1800
3	F	58	19	6.1	L	Sepsis and chronic renal failure	Paranoid (episodic)	39	300–400
4	M	30	24	6.6	L	CO poisoning: suicide	Paranoid (episodic)	3.5	130–975
5	M	57	18	6.6	R	Ischaemic heart disease	Paranoid (continuous)	30	300–1300
6	M	54	27.5	6.2	R	Coronary artery thrombosis	Paranoid (episodic)	35	50–600
7	F	56	39	6.6	R	Undetermined	Paranoid (chronic)	32	100–600
8	F	66	12.5	6.5	R	Faecaloid peritonitis	Paranoid (chronic)	47	1200–2500
9	M	75	36	6.4	L	Ischaemic heart disease	Paranoid (continuous)	44	200–1200
Mean±SD		55±13.2	27.22±11.5	6.43±0.22

CpzeEq, chlorpromazine equivalent; DOI, duration of illness; H, hemisphere; PMI, post-mortem interval; ^†Same individual as subject 3.

Two-dimensional gel electrophoresis

2DGE analysis was performed as described in detail in Sivagnanasundaram et al. [21]. Briefly, proteins were extracted and protein concentration determined by the Bradford method using a complex human brain protein mixture as a standard. A total of 350 µg of each protein sample was profiled in duplicate in the first dimension on precast immobilized 11 cm pH 4–7 gradient strips and in the second dimension on precast 8–16% Tris-HCl sodium dodecylsulfide–polyacrylamide gel electrophoresis. The protein profile of each gel was visualized by colloidal Coomassie Blue staining [22].

Image acquisition and analysis

Gels were scanned using Phoretix Powerscan software (Nonlinear Dynamics, Newcastle-upon-Tyne, UK) with a UMAX flatbed scanner (light path: transmissive, brightness: 40.55, contrast: 80.12, 400 dots per inch). Intensity calibration was performed prior to gel scanning using a 25×125 mm AGFA strip (Ridgefield, NJ, USA). The resulting gel images were analysed using Phoretix 2D Expression software (Nonlinear Dynamics), which allows spot detection, spot matching between different gels, and spot quantification. Spots detected automatically by the software were checked manually to ensure consistency across all gels. Mode of non-spot background subtraction was applied, in order to remove background intensity present in the gels, which would otherwise artificially raise spot volume. Total spot volume normalization was then applied, which corrects for the differences in protein loading concentration between gels, by dividing the volume of each spot by the total volume of all spots in the gel and multiplying the resulting figure by 100. A reference gel was created consisting of all protein spots detected on all subgels within the schizophrenia and control groups and all protein spots detected on the subgels were matched to the reference gel.

Statistical analysis

Average gels were created for each group, to assist comparison and reduce variations within subgels of a group. Averaging parameter was set to 70%, that is, a protein spot had to be present in at least 70% of the subgels within a group to be represented in the average gel for subsequent statistical analysis. Protein spots showing statistically significant difference in expression between schizophrenia and control average gels, generated with an averaging parameter set at 70%, were assessed initially for significant difference using t-test and then verified using two-level nested ANOVA (http://udel.edu/∼mcdonald/statnested.html). Nested ANOVA analysis is suitable for equal and unequal sample sizes and takes into consideration technical versus biological replicates [23]. Significant outliers (p < 0.05) of protein spot intensity for each sample within the groups were assessed using Grubbs’ test (http://www.graphpad.com/quickcalcs/Grubbs1.cfm) and removed prior to nested ANOVA analysis. Pearson's correlation analyses were performed to examine whether protein expression levels differed as a function of either, age, PMI, DOI, brain pH or medication. Values were calculated using the average normalized volumes from each subject for each statistically significant protein.

Mass spectrometry and identification of protein spots

The differentially expressed protein spots were excised for identification by mass spectrometry, using spot picker tips (1.5 mm tips for PDN 1.5 spot picker; The Gel Company, San Francisco, CA, USA) and subjected to in-gel trypsin digestion (Porcine trypsin; Promega, Sydney, NSW, Ausralia). The digested peptides were desalted and concentrated using C₁₈ Perfect Pure Tips (Eppendorf, Sydney, NSW, Ausralia) as described in Clark et al. [24]. The mass spectrometry was performed using a QSTAR XL mass spectrometer with an oMALDI ion source (Applied Biosystems, Scoresby, Victoria, Australia). The monoisotopic peptide mass data were generated manually or automatically using the oMALDI Xpert software (version 2.0; threshold was set to 10, exclusion window of 3 amu and maximum of 50 peaks were generated; Applied Biosystems) and was used to perform searches of the mammalian SWISS-PROT, NCBI and TrEMBL databases using the programs Aldente (www.expasy.ch) and MASCOT (version 2.0, www.matrixscience.com). For MASCOT, identification parameters were set to allow one possible missed tryptic cleavage per peptide, peptide mass accuracy within ±0.15 Da and variable oxidation of methionine checked. For MASCOT a minimum of four matched peptides and a MOWSE probability score of >64, which corresponds to p < 0.05, was required for confidence in identification. For Aldente, peptide mass accuracy was allowed within ±0.2 Da. If the programs returned more than one protein match, the best match was chosen based on the observed isoelectric point (pI) and molecular weight values of the protein, the number of matching peptide masses, the percentage sequence coverage and the agreement between matches returned by the two programs.

Results

Proteins isolated from the AH and PH from each schizophrenia and control sample was assessed for differential expression in duplicate. In total the AH and PH reference gels consisted of 979 and 1042 protein spots, respectively, representing protein spots identified in both schizophrenia and control gels. Among these, 919 and 936 protein spots were identified in both schizophrenia and control samples in the AH and PH, respectively. Of these, the control samples showed greater variability in the AH when all 919 protein spots were assessed on standard deviation (SD_controls=0.93 compared to SD_{schizophrenia}=0.33), and the schizophrenia samples showed greater variability in the PH when all 936 protein spots were assessed (SD_{schizophrenia}=0.095 compared to SD_control=0.052). A total of 518 and 490 protein spots were assessed for differential expression in the AH and PH, respectively, using an averaging parameter of 70%. Significant changes in the relative abundance of 43 and 16 protein spots were found between the control and schizophrenia groups in the AH and PH, respectively, using two-level nested ANOVA, taking into consideration the technical (in-duplicate) and biological (schizophrenia and control samples) replicates (p < 0.05; Tables 2 and 3; Figure 1).

Figure 1.

2-D gel electrophoresis of the (a) anterior hippocampus and (b) posterior hippocampus proteome showing the protein spots differentially expressed in schizophrenia brains compared to controls and their corresponding spot numbers.

Table 2.

Proteins differentially expressed in the anterior hippocampus of schizophrenia brains

Spot no.	Protein	Accesssion no.^†	FC	p^‡	Fs^§	p^§	PM (%SC)	pI/mass (kDa)	MS	CS loci
Energy metabolism
4304	CKB: creatine kinase chain B	P12277	−1.96	0.001442	7.78	0.0164	11/14 (35)	5.3/43	151
4303	CKB	P12277	−2.05	0.000461	10.05	0.008078	9/12 (32)	5.3/43	135
2841	NDUFA5: NADH dehydrogenase (ubiquinone) 1 alpha subcomplex subunit 5	Q16718	1.8	0.01419	6.68	0.0254	9/19 (63)	5.8/13	131	7q32
4039	LDHB: l-lactate dehydrogenase B chain	P07195	−2.5	0.000895	18.58	0.001536	10/18 (25)	5.7/37	117
2715	NDKA: nucleoside diphosphate kinase A	P15531	1.425	0.01931	4.99	0.0472	7/13 (40)	5.8/17	93	17q21.3
2310	ATP5H: ATP synthase d chain, mitochondrial	O75947	1.65	0.0174	7.39	0.0186	7/24 (55)	5.2/18	76	17q25
2307	ATP5H Correlated with medication: r = − 0.81, p < 0.05	O75947	1.84	0.00000177	23.55	0.000397	6/18 (54)	5.2/18	76
4504	COX5A: cytochrome c oxidase subunit Va	P20674	1.9	0.0000896	22.94	0.000441	6/13 (28)	4.9/13	76	15q25
4100	COX6B1: cytochrome c oxidase subunit Vib	P14854	−1.5	0.00999	5.81	0.0366	4/9 (44)	6.8/10	69	19q13.1

Oxidative stress response
4065	SOD1: superoxide dismutase 1, soluble	P00441	−1.892	0.001676	7.46	0.0182	4/8 (32)	5.7/16	66	21q22.11
4453	PRDX2: peroxiredoxin 2	P32119	−3.2	0.000165	20.45	0.000699	8/9 (41)	5.7/22	153	19q13.2
4769	PRDX2	P32119	2.928	0.0000527	14.44	0.003484	8/10 (36)	5.7/22	148
3992	PRDX6: peroxiredoxin 6	P30041	1.902	0.00000373	37.6852	0.000110	5/9 (23)	6/25	76	1q25.1
4003	PRDX6	P30041	2.1	0.000223	25.8883	0.000267	6/9 (29)	6/25	97

Protein metabolism
4488	CTSD: cathepsin D heavy chain	P07339	−1.4	0.008683	5.2185	0.0413	9/20 (25)	5.6/27	88	11p15.5
4771	UCHL1: ubiquitin carboxyl-terminal esterase L1	P09936	−4.29	0.001216	9.5658	0.0102	8/12 (43)	5.3/25	114	4p14
4459	UCHL1	P09936	−3.388	0.007187	5.9355	0.0351	11/19 (36)	5.3/25	102
4473	UCHL1	P09936	1.72	0.000348	17.9755	0.001717	8/17 (24)	5.3/25	67
2716	UBE2N: ubiquitin-conjugating enzyme E2 N	P61088	2.05	0.000248	10.5235	0.007818	6/10 (46)	6.1/17	102	12q22
2068	PHB: prohibitin	P35232	1.52	0.001208	8.5568	0.0127	8/9 (35)	5.6/30	140	17q21

Heat shock protein
3697	HSPA9B: heat shock 70 kDa protein 9B	P38646	−1.466	0.008456	7.5207	0.0207	8/11 (13)	5.5/69	81
3724	HSPA1B: heat shock 70 kDa protein 1	P08107	−1.22	0.002982	18.5519	0.001544	12/18 (19)	5.5/70	136	6p21.3

Cell growth and/or maintenance
4296	ACTB: actin, beta	P60709	−2.069	0.006131	5.4781	0.0413	5/9 (18)	5.3/42	67
4241	VIM: vimentin Correlated with medication: r = 0.76, p < 0.05	P08670	1.739	0.003953	6.0033	0.0306	9/12 (23)	5.1/54	118	10p13
4551	CAPZA2: F-actin capping protein α-2 subunit	P47755	−2.0	0.001532	12.8652	0.004267	5/10 (23)	5.6/33	70	7q31.2-q31.3
4284	NEFM: neurofilament medium polypeptide	P07197	−1.71	0.03628	6.0979	0.0331	11/23 (15)	4.9/102	99	8p21

Cell growth and/or maintenance, cell communication/signal transduction
4538	STMN1: stathmin	P16949	1.512	0.02741	5.1889	0.0437	6/16 (28)	5.8/17	70	1p36.1-p35

Cell communication/signal transduction
4406	RHOGDI: rho GDP-dissociation inhibitor 1	P52565	1.429	0.0034	6.0552	0.0300	12/26 (47)	5/23	135	17q25.3
4433	GNB2: guanine nucleotide binding protein G(I)/G(S)/G(T), beta subunit 2	P62879	−2.259	0.000128	16.0953	0.001724	5/5 (11)	5.6/37	69	7q22
4497	GNB2	P62879	−1.87	0.000172	19.7032	0.000997	4/4 (13)	5.6/37	69
4621	GNB2	P62879	−1.7	0.003003	5.6670	0.0347	5/5 (11)	5.6/37	69
2340	RAB2: Ras-related protein Rab-2	P61019	1.439	0.02198	6.2602	0.0278	11/17 (55)	6.1/24	156	8q12.1
1933	ANXA5: annexin A5	P08758	1.629	0.002477	6.0160	0.0304	10/14 (36)	4.9/36	146	4q26-q28
2611	VSNL1: visinin-like protein 1	P62760	2.356	0.02188	7.0779	0.0324	9/18 (40)	5/22	89	2p24.3

Cell communication/signal transduction, apoptosis
3405	YWHAG: 14-3-3 protein gamma	P61981	1.735	0.0000000742	45.4958	0.000021	11/13 (28)	4.8/28	118	7q11.23
3390	YWHAE: 14-3-3 protein epsilon	P62258	1.372	0.0000271	16.1623	0.001699	6/9 (18)	4.6/29	70	17p13.3
2131	YWHAZ: 14-3-3 protein zeta	P63104	1.886	0.000117	14.8858	0.002276	7/13 (34)	4.7/28	86	8q23.1
2126	YWHAZ	P63104	1.954	0.000012	19.2206	0.000890	10/14 (31)	4.7/28	142

Cell differentiation/cell proliferation
4517	FABP7: fatty acid-binding protein, brain	O15540	−1.587	0.001604	6.8015	0.0229	7/20 (38)	5.4/15	68	6q22-q23
2627	GMF: glia maturation factor, beta	P60983	1.572	0.004569	7.1418	0.0217	8/19 (46)	5.2/17	112	14q22.2

Hormone metabolism
1751	CRYM: crystallin, mu	Q14894	2.165	0.000104	14.7862	0.002330	5/8 (15)	5.1/34	72	16p13.11-p12.3

Vesicular trafficking
3647	ATP6V1A: vacuolar ATP synthase catalytic subunit A, ubiquitous isoform	P38606	−1.4	0.02713	5.7400	0.0402	11/20 (18)	5.4/68	92	3q13.2-q13.31

Nitric oxide generation
4640	DDAH1: dimethylarginine dimethylaminohydrolase 1	O94760	−1.598	0.004346	7.9280	0.0156	4/5 (17)	5.5/31	66	1p22

CS loci, human chromosomal localization of the gene encoding the respective protein; FC, fold change observed in schizophrenia brains; pI, soelectric point; PM (%SC), no. peptides matched out of the total number searched in the database and percentage sequence coverage; MS, MASCOT probability based Mowse score, in which a score of ≥64 are significant hits; Spot no., assigned by the Phoretix software. ^†SwissProt or UniProtKB (http://au.expasy.org/sprot/) accession number of protein identified; ^‡t-test; ^§nested ANOVA. Bold, protein spots that displayed strong correlation with pre- and post-mortem factors.

Table 3.

Proteins differentially expressed in the posterior hippocampus of schizophrenia brains

Spot no.	Protein	Accession no.^†	FC	p^‡	Fs^§	p^§	PM (% SC)	pI/mass (kDa)	MS	CS loci
Energy metabolism
6523	PGAM1: phosphoglycerate mutase 1	P18669	1.353	0.01005	9.2705	0.007723	7/15 (28)	6.8/29	93	10q25.3
6221	NDUFV2: NADH dehydrogenase (ubiquinone) flavoprotein 2, 24kDa	P19404	1.261	0.005218	9.6559	0.007718	10/25 (40)	5.7/24	146	18p11.3-p11.2
1457	CKB: creatine kinase chain B	P12277	2.04	0.01398	16.4571	0.003650	9/23 (32)	5.3/43	113	14q32

Energy metabolism, oxidative stress response
4571	TALDO1: transaldolase 1	P37837	1.1	0.03841	7.0694	0.0187	8/11 (18)	6.3/38	64	11p15.5-p15.4

Protein metabolism
5233	CCT5: T-complex protein 1 subunit epsilon	P48643	−1.389	0.005639	12.3158	0.002905	13/32 (26)	5.5/60	78	5p15.2
843	GARS: glycyl-tRNA synthetase	P41250	1.27	0.01566	5.1387	0.0446	8/12 (12)	6.6/83	78	7p15

Cell communication/signal transduction
4713	GNAO1: guanine nucleotide-binding protein G(o) alpha subunit 1	P09471	−1.665	0.008714	7.1538	0.0166	8/23 (26)	5.3/40	88	16q13
1475	GNAO1	P09471	−1.767	0.03384	6.9136	0.0220	5/9 (16)	5.3/40	64

Cell growth and/or maintenance
3460	GSN: gelsolin	P06396	1.41	0.01527	6.6236	0.0212	7/10 (13)	5.9/86	87	9q33
648	GSN	P06396	1.525	0.000211	20.1364	0.000434	7/10 (13)	5.9/86	85
6535	ACTB: actin, beta	P60709	1.197	0.01388	7.4467	0.0149	8/16 (23)	5.3/42	85	7p15-p12
4532	TUBB4: tubulin β-4 chain	P04350	−2.0	0.006327	7.3068	0.0157	11/26 (24)	4.8/50	102	19p13.3
5188	TUBA1: tubulin α-1 chain	P68366	−1.242	0.01947	7.0544	0.0209	6/11 (18)	5/50	77	2q35

Cell growth and/or maintenance, cell communication/signal transduction
4043	STMN1: stathmin Correlated with PMI: r = 0.71, p < 0.05	P16949	1.475	0.000338	12.1444	0.003643	5/8 (30)	5.8/17	78	1p36.1 p35

Regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism, apoptosis
5176	HNRPK: heterogeneous nuclear ribonucleoprotein K	P61978	−1.1	0.0349	8.8200	0.0208	9/25 (17)	5.4/51	68	9q21.32-q21.33

Porphyrin metabolism
6580	HEPB1: heme-binding protein 1	Q9NRV9	1.427	0.02661	5.2977	0.0361	6/21 (37)	5.7/21	83	12p13.1

CS loci, human chromosomal localization of the gene encoding the respective protein; FC, fold change observed in schizophrenia brains; pI, isoelectric point; PM (%SC), no. peptides matched out of the total number searched in the database and percentage sequence coverage; MS, MASCOT probability based Mowse score, in which a score of ≥64 are significant hits; Spot no., assigned by the Phoretix software. ^†SwissProt or UniProtKB (http://au.expasy.org/sprot/) accession number of protein identified; ^‡t-test; ^§nested ANOVA. Bold, protein spots that displayed strong correlation with pre- and post-mortem factors.

The 43 differentially expressed protein spots in the AH represent 34 unique proteins involved in a number of functions (Table 2), classified using the Human Protein Reference Database (http://www.hprd.org). Seven unique proteins were identified in more than one protein spot, reflecting either different isoforms or post-translation modification such as phosphorylation or glycosylation. Similarly the 14 unique proteins differentially expressed in the PH are involved in a number of functions (Table 3).

Variation in protein expression levels caused by post-mortem factors, brain pH and PMI and pre-mortem factors, age, DOI and medication were assessed using Pearson correlation test. The expression levels of two protein spots, 2307 and 4241 (Table 2), displayed strong correlation with medication (r = − 0.81, p < 0.05 and r = 0.76, p < 0.05, respectively). Protein spot 4043, identified as differentially expressed in the PH, showed strong correlation with PMI (Table 3, r = 0.71, p < 0.05). The difference in expression of spot 4043 between schizophrenia and controls remained significant (ANCOVA p = 0.032) after co-varying for PMI.

Discussion

2DGE is a proteomics tool that enables the investigation of high-abundance, hydrophilic components of a protein mixture 10–120 kDa in size [25]. In the present study we used 2DGE and MALDI-TOF-MS to profile the brain proteome of the AH and PH and identify differentially expressed proteins between schizophrenia and control brains. Proteomic analysis indicated that the AH and PH display different protein profiles (Figure 1), which may be explained by the different connectivity and functions of the two regions of the hippocampus [5]. Importantly, the larger number of molecular changes in the AH (n = 43) compared to the PH (n = 16) reflect greater perturbation in the AH in schizophrenia. Of these changes in protein expression levels, the measured intensity of protein spot adenosine triphosphate (ATP) synthase d chain (mitochondrial) was inversely correlated with antipsychotic medication, while vimentin (VIM) was positively correlated with medication. The difference in expression levels of these two proteins in the AH could be due to a change in response to medication.

Previous findings of altered protein and mRNA expression in the schizophrenia hippocampus of creatine kinase chain B (CKB), ubiquitin carboxyl-terminal esterase L1 and visinin-like protein 1 (VSNL1) were replicated in the present study in the AH [26–29]. Furthermore single nucleotide polymorphisms in the genes encoding superoxide dismutase 1, heat shock 70 kDa protein 1 and 14-3-3 zeta (YWHAZ) identified as differentially expressed in the present study, have been reported to show association with schizophrenia in previous studies [30–32]. Three abnormal pathways identified in both the AH and PH: altered glutamatergic and GABAergic neurotransmission, mitochondrial dysfunction and abnormal neuronal and glial cytoarchitecture, are discussed in the following section.

Altered glutamatergic excitatory and GABAergic inhibitory neurotransmission in the AH, consistent with previous findings in schizophrenia [33–35], were indicated by decreased expression of vacuolar ATP synthase catalytic subunit; increased expression of annexin V, proteins involved in uptake and release of neurotransmitters into the synaptic cleft [36, 37] and increased expression of YWHAZ, a protein that interacts directly with GABA_B receptor 1 [38]. Abnormal neurotransmission and signal transduction was also indicated by decreased expression of guanine nucleotide-binding protein G(o) alpha subunit 1 in the PH, a protein that plays an important role in mediating GABAergic, cholinergic and dopaminergic neurotransmission [39], systems that have been implicated in schizophrenia pathogenesis [40]. Increased expression of VSNL1, thought to contribute to processes of synaptic plasticity, is suggestive of altered hippocampal circuitry [41–43].

Consistent with decreased energy metabolism in schizophrenia hippocampus [15, 44] altered expression of CKB, l-lactate dehydrogenase B chain, phosphoglycerate mutase 1 and nicotinamide adenine dinucleotide H (NADH) dehydrogenase (ubiquinone) flavoprotein 2, 24 kDa were observed in both the AH and PH. Among the abnormal activities of the various mitochondrial complexes of oxidative phosphorylation in schizophrenia, the activities of complex I and IV are reported to be most affected [45]. The present findings of increased expression of NADH dehydrogenase (ubiquinone) 1 alpha subcomplex subunit 5, a subunit of complex I [46] and altered expression of cytochrome c oxidase subunit Va and subunit VIb isoform 1, subunits of the cytochrome oxidase complex IV, a rate-limiting enzyme in oxidative phosphorylation, are consistent with that report.

Altered expression of proteins of neuron and glial cytoarchitecture in the AH and PH (beta actin, neurofilament medium polypeptide protein, VIM, nucleoside diphosphate kinase A, F-actin capping protein α-2 subunit, rho GDP-dissociation inhibitor 1, stathmin, 14-3-3 gamma, 14-3-3 epsilon, YWHAZ, gelsolin, tubulin β-4 chain, tubulin α-1 chain and T-complex protein 1 subunit epsilon), some of which if developmental in origin, may give rise to reduction in the extent of axonal or dendritic arborization, resulting in small neuron size and decreased neuropil volume in the hippocampus [4, 47–58]. The altered expression of these proteins is consistent with a previous study showing altered expression of microtubule-associated proteins in specific subfields of the hippocampal formation [59] and reduced neuron size in the PH in schizophrenia [60]. These changes are consistent with abnormal cytoarchitecture, diminished synaptic plasticity and connectivity in the hippocampus, and reports of reduced synaptic proteins and decreased density of mitochondria in axon terminal and dendrites [1, 5, 61, 62].

Altered expression of the proteins discussed here are consistent with the hypothesis that abnormal synaptic circuitry or ‘wiring’ within the AH and its extrinsic connections, especially with the prefrontal cortex (PFC), underlie cognitive dysfunction in schizophrenia [5, 6]. In support of this view a similar network of abnormal pathways and altered protein expression was also reported in the anterior cingulate cortex (ACC) grey matter [24], ACC white matter [63] and the genu of the corpus callosum [21]. Mitochondrial dysfunction and compromised oxidative stress response processes as identified in the present study were also reported in previous studies of the PFC and ACC [64–67]. The abnormal processes identified in the AH can lead to altered neuronal plasticity and brain connectivity, processes that are presently thought to be the core pathology of schizophrenia [68].

It should be noted that although some of these changes may be causative factors, others may be a consequence of the illness or compensatory such as response to medication, as we have shown. Genetic screening of the genes encoding these proteins for potential disease causing mutations, together with assessment of alterations in transcription and translation regulatory processes, may help to distinguish the causative factors. Future follow-up studies in addition to genetic screening, include assessment of the protein changes at the transcript level using quantitative polymerase chain reaction in a larger population and identification of the cellular and subcellular localization of the altered proteins using immunohistochemistry. Changes identified in the level of expressed transcripts will be followed up using quantitative in situ hybridization.

Footnotes

Acknowledgements

This work was supported by Schizophrenia Research Institute (SRI), utilizing infrastructure funding from NSW Health (SS) and the NSW Government BioFirst Award (IM). AH and PH tissues were provided by the NSW Tissue Resource Centre, which is supported by the University of Sydney, SRI, National Institute of Alcohol Abuse and Alcoholism (National Institutes of Health, USA) and NSW Department of Health and NHMRC. Mass spectrometry for the present study was carried out at the Biomedical Node of the Australian Proteome Analysis Facility and was supported in part by grants from the Major National Research Facilities Program and the University of Sydney. Note: Schizophrenia Research Institute was formally known as the Neuroscience Institute of Schizophrenia and Allied Disorders (NISAD)

References

1. Harrison

Eastwood

. Neuropathological studies of synaptic connectivity in the hippocampal formation in schizophrenia. Hippocampus 2001; 11: 508–519.

2. Lawrie

Whalley

Kestelman

. Magnetic resonance imaging of brain in people at high risk of developing schizophrenia. Lancet 1999; 353: 30–33.

3. Antonova

Sharma

Morris

Kumari

. The relationship between brain structure and neurocognition in schizophrenia: a selective review. Schizophr Res 2004; 70: 117–145.

4. Szeszko

Goldberg

Gunduz-Bruce

. Smaller anterior hippocampal formation volume in antipsychotic-naive patients with first-episode schizophrenia. Am J Psychiatry 2003; 160: 2190–2197.

5. Goldman

Mitchell

. What is the functional significance of hippocampal pathology in schizophrenia?. Schizophr Bull 2004; 30: 367–392.

6. Harrison

. The hippocampus in schizophrenia: a review of the neuropathological evidence and its pathophysiological implications. Psychopharmacology (Berl) 2004; 174: 151–162.

7. Harrison

Eastwood

. Preferential involvement of excitatory neurons in medial temporal lobe in schizophrenia. Lancet 1998; 352: 1669–1673.

8. Eastwood

Harrison

. Decreased synaptophysin in the medial temporal lobe in schizophrenia demonstrated using immunoautoradiography. Neuroscience 1995; 69: 339–343.

9. Rosoklija

Toomayan

Ellis

. Structural abnormalities of subicular dendrites in subjects with schizophrenia and mood disorders: preliminary findings. Arch Gen Psychiatry 2000; 57: 349–356.

10.

10. Kerwin

Patel

Meldrum

. Quantitative autoradiographic analysis of glutamate binding sites in the hippocampal formation in normal and schizophrenic brain post mortem. Neuroscience 1990; 39: 25–32.

11.

11. Deakin

Slater

Simpson

. Frontal cortical and left temporal glutamatergic dysfunction in schizophrenia. J Neurochem 1989; 52: 1781–1786.

12.

12. Zhang

Reynolds

. A selective decrease in the relative density of parvalbumin-immunoreactive neurons in the hippocampus in schizophrenia. Schizophr Res 2002; 55: 1–10.

13.

13. Scarr

Pavey

Copolov

Dean

. Hippocampal 5-hydroxytryptamine receptors: abnormalities in postmortem brain from schizophrenic subjects. Schizophr Res 2004; 71: 383–392.

14.

14. Crook

Tomaskovic-Crook

Copolov

Dean

. Decreased muscarinic receptor binding in subjects with schizophrenia: a study of the human hippocampal formation. Biol Psychiatry 2000; 48: 381–388.

15.

15. Tamminga

Thaker

Buchanan

. Limbic system abnormalities identified in schizophrenia using positron emission tomography with fluorodeoxyglucose and neocortical alterations with deficit syndrome. Arch Gen Psychiatry 1992; 49: 522–530.

16.

16. Tamminga

Holcomb

. Phenotype of schizophrenia: a review and formulation. Mol Psychiatry 2005; 10: 27–39.

17.

17. Tamminga

Vogel

Gao

Lahti

Holcomb

. The limbic cortex in schizophrenia: focus on the anterior cingulate. Brain Res Brain Res Rev 2000; 31: 364–370.

18.

18. Katsel

Davis

Gorman

Haroutunian

. Variations in differential gene expression patterns across multiple brain regions in schizophrenia. Schizophr Res 2005; 77: 241–252.

19.

19. Edgar

Schonberger

Dean

Faull

Kydd

Cooper

. A comparative proteome analysis of hippocampal tissue from schizophrenic and Alzheimer's disease individuals. Mol Psychiatry 1999; 4: 173–178.

20.

20. American

. Diagnostic and statistical manual of mental disorders4th edn. American Psychiatric Association, Washington, DC 1994.

21.

21. Sivagnanasundaram

Crossett

Dedova

Cordwell

Matsumoto

. Abnormal pathways in the genu of the corpus callosum in schizophrenia pathogenesis: a proteome study. Proteomics Clin App 2007; 1: 1291–1305.

22.

22. Miller

Crawford

Gianazza

. Protein stains for proteomic applications: which, when, why?. Proteomics 2006; 6: 5385–5408.

23.

23. Karp

Spencer

Lindsay

O'Dell

Lilley

. Impact of replicate types on proteomic expression analysis. J Proteome Res 2005; 4: 1867–1871.

24.

24. Clark

Dedova

Cordwell

Matsumoto

. A proteome analysis of the anterior cingulate cortex gray matter in schizophrenia. Mol Psychiatry 2006; 11: 459–470,423.

25.

25. Fountoulakis

. Application of proteomics technologies in the investigation of the brain. Mass Spectrom Rev 2004; 23: 231–258.

26.

26. Burbaeva

Savushkina

Boksha

. Creatine kinase BB in brain in schizophrenia. World J Biol Psychiatry 2003; 4: 177–183.

27.

27. Aksenova

Karaseva

Burbaeva

. Creatine phosphokinase distribution in the brain in schizophrenia and Alzheimer's disease]. Zh Nevropatol Psikhiatr Im S S Korsakova 1993; 93: 35–36.

28.

28. Altar

Jurata

Charles

. Deficient hippocampal neuron expression of proteasome, ubiquitin, and mitochondrial genes in multiple schizophrenia cohorts. Biol Psychiatry 2005; 58: 85–96.

29.

29. Bernstein

Braunewell

Spilker

. Hippocampal expression of the calcium sensor protein visinin-like protein-1 in schizophrenia. Neuroreport 2002; 13: 393–396.

30.

30. Akyol

Yanik

Elyas

. Association between Ala-9Val polymorphism of Mn-SOD gene and schizophrenia. Prog Neuropsychopharmacol Biol Psychiatry 2005; 29: 123–131.

31.

31. Pae

Kim

Kwon

. Polymorphisms of heat shock protein 70 gene (HSPA1A, HSPA1B and HSPA1L) and schizophrenia. Neurosci Res 2005; 53: 8–13.

32.

32. Jia

Zhang

. An association study between polymorphisms in three genes of 14-3-3 (tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein) family and paranoid schizophrenia in northern Chinese population. Eur Psychiatry 2004; 19: 377–379.

33.

33. Tamminga

Lahti

Medoff

Gao

Holcomb

. Evaluating glutamatergic transmission in schizophrenia. Ann N Y Acad Sci 2003; 1003: 113–118.

34.

34. Harrison

Law

Eastwood

. Glutamate receptors and transporters in the hippocampus in schizophrenia. Ann N Y Acad Sci 2003; 1003: 94–101.

35.

35. Costa

Davis

Dong

. A GABAergic cortical deficit dominates schizophrenia pathophysiology. Crit Rev Neurobiol 2004; 16: 1–23.

36.

36. Morel

. Neurotransmitter release: the dark side of the vacuolar-H + ATPase. Biol Cell 2003; 95: 453–457.

37.

37. Gotow

Sakata

Funakoshi

Uchiyama

. Preferential localization of annexin V to the axon terminal. Neuroscience 1996; 75: 507–521.

38.

38. Couve

Kittler

Uren

. Association of GABA(B) receptors and members of the 14-3-3 family of signaling proteins. Mol Cell Neurosci 2001; 17: 317–328.

39.

39. Hubbard

Hepler

. Cell signalling diversity of the Gqalpha family of heterotrimeric G proteins. Cell Signal 2006; 18: 135–150.

40.

40. Harrison

, Weinberger

. Schizophrenia genes, gene expression, and neuropathology: on the matter of their convergence. Mol Psychiatry 2005; 10:40–68; image 45.

41.

41. Brackmann

Schuchmann

Anand

Braunewell

. Neuronal Ca2+ sensor protein VILIP-1 affects cGMP signalling of guanylyl cyclase B by regulating clathrin-dependent receptor recycling in hippocampal neurons. J Cell Sci 2005; 118: 2495–2505.

42.

42. Lin

Jeanclos

Treuil

Braunewell

Gundelfinger

Anand

. The calcium sensor protein visinin-like protein-1 modulates the surface expression and agonist sensitivity of the alpha 4beta 2 nicotinic acetylcholine receptor. J Biol Chem 2002; 277: 41 872–41 878.

43.

43. Spilker

Gundelfinger

Braunewell

. Evidence for different functional properties of the neuronal calcium sensor proteins VILIP-1 and VILIP-3: from subcellular localization to cellular function. Biochim Biophys Acta 2002; 1600: 118–127.

44.

44. Potkin

Alva

Fleming

. A PET study of the pathophysiology of negative symptoms in schizophrenia. Positron emission tomography. Am J Psychiatry 2002; 159: 227–237.

45.

45. Ben-Shachar

. Mitochondrial dysfunction in schizophrenia: a possible linkage to dopamine. J Neurochem 2002; 83: 1241–1251.

46.

46. Smeitink

van den Heuvel

. Human mitochondrial complex I in health and disease. Am J Hum Genet 1999; 64: 1505–1510.

47.

47. Lariviere

Julien

. Functions of intermediate filaments in neuronal development and disease. J Neurobiol 2004; 58: 131–148.

48.

48. Matus

. Actin-based plasticity in dendritic spines. Science 2000; 290: 754–758.

49.

49. dos Remedios

Chhabra

Kekic

. Actin binding proteins: regulation of cytoskeletal microfilaments. Physiol Rev 2003; 83: 433–473.

50.

50. Leffers

Nielsen

Andersen

. Identification of two human Rho GDP dissociation inhibitor proteins whose overexpression leads to disruption of the actin cytoskeleton. Exp Cell Res 1993; 209: 165–174.

51.

51. Curmi

Gavet

Charbaut

. Stathmin and its phosphoprotein family: general properties, biochemical and functional interaction with tubulin. Cell Struct Funct 1999; 24: 345–357.

52.

52. Satoh

Yamamura

Arima

. The 14-3-3 protein epsilon isoform expressed in reactive astrocytes in demyelinating lesions of multiple sclerosis binds to vimentin and glial fibrillary acidic protein in cultured human astrocytes. Am J Pathol 2004; 165: 577–592.

53.

53. Li

Guo

Teng

Ding

Chen

. 14-3-3gamma affects dynamics and integrity of glial filaments by binding to phosphorylated GFAP. J Cell Sci 2006; 119: 4452–4461.

54.

54. Matthews

Johnson

. 14-3-3Zeta does not increase GSK3beta-mediated tau phosphorylation in cell culture models. Neurosci Lett 2005; 384: 211–216.

55.

55. Ge

Volkening

Leystra-Lantz

Jaffe

Strong

. 14-3-3 protein binds to the low molecular weight neurofilament (NFL) mRNA 3′ UTR. Mol Cell Neurosci 2007; 34: 80–87.

56.

56. Tanaka

Sobue

. Localization and characterization of gelsolin in nervous tissues: gelsolin is specifically enriched in myelin-forming cells. J Neurosci 1994; 14: 1038–1052.

57.

57. Laferriere

MacRae

Brown

. Tubulin synthesis and assembly in differentiating neurons. Biochem Cell Biol 1997; 75: 103–117.

58.

58. Lewis

Tian

Vainberg

Cowan

. Chaperonin-mediated folding of actin and tubulin. J Cell Biol 1996; 132: 1–4.

59.

59. Arnold

Lee

Gur

Trojanowski

. Abnormal expression of two microtubule-associated proteins (MAP2 and MAP5) in specific subfields of the hippocampal formation in schizophrenia. Proc Natl Acad Sci U S A 1991; 88: 10 850–10 854.

60.

60. Benes

Sorensen

Bird

. Reduced neuronal size in posterior hippocampus of schizophrenic patients. Schizophr Bull 1991; 17: 597–608.

61.

61. Harrison

. The neuropathology of schizophrenia. A critical review of the data and their interpretation. Brain 1999; 122(Pt 4)593–624.

62.

62. Arnold

Franz

Gur

. Smaller neuron size in schizophrenia in hippocampal subfields that mediate cortical-hippocampal interactions. Am J Psychiatry 1995; 152: 738–748.

63.

63. Clark

Dedova

Cordwell

Matsumoto

. Altered proteins of the anterior cingulate cortex white matter proteome in schizophrenia. Proteomics Clin App 2007; 1: 157–166.

64.

64. Novikova

Cutrufello

Lidow

. 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: 61–76.

65.

65. Beasley

Pennington

Behan

Wait

Dunn

Cotter

. Proteomic analysis of the anterior cingulate cortex in the major psychiatric disorders: evidence for disease-associated changes. Proteomics 2006; 6: 3414–3425.

66.

66. Prabakaran

Swatton

Ryan

. Mitochondrial dysfunction in schizophrenia: evidence for compromised brain metabolism and oxidative stress. Mol Psychiatry 2004; 9: 684–697, 643.

67.

67. Pennington

Beasley

Dicker

. Prominent synaptic and metabolic abnormalities revealed by proteomic analysis of the dorsolateral prefrontal cortex in schizophrenia and bipolar disorder. Mol Psychiatry 2008; 13: 1102–1117.

68.

68. Stephan

Baldeweg

Friston

. Synaptic plasticity and dysconnection in schizophrenia. Biol Psychiatry 2006; 59: 929–939.

Anterior Hippocampus in Schizophrenia Pathogenesis: Molecular Evidence from a Proteome Study

Abstract

Keywords

Methods

Human brain tissue samples

Two-dimensional gel electrophoresis

Image acquisition and analysis

Statistical analysis

Mass spectrometry and identification of protein spots

Results

Discussion

Footnotes

Acknowledgements

References