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ORIGINAL PAPER
Daniel Martins-de-Souza ÆWagner F. Gattaz ÆAndrea Schmitt ÆChristiane Rewerts
Giuseppina Maccarrone ÆEmmanuel Dias-Neto ÆChristoph W. Turck
Prefrontal cortex shotgun proteome analysis reveals
altered calcium homeostasis and immune system
imbalance in schizophrenia
Received: 27 June 2008 / Accepted: 19 September 2008 / Published online: 22 January 2009
jAbstract Schizophrenia is a complex disease,
likely to be caused by a combination of serial altera-
tions in a number of genes and environmental factors.
The dorsolateral prefrontal cortex (Brodmann’s Area
46) is involved in schizophrenia and executes high-
level functions such as working memory, differentia-
tion of conflicting thoughts, determination of right
and wrong concepts and attitudes, correct social
behavior and personality expression. Global proteo-
mic analysis of post-mortem dorsolateral prefrontal
cortex samples from schizophrenia patients and
non-schizophrenic individuals was performed using
stable isotope labeling and shotgun proteomics. The
analysis resulted in the identification of 1,261 proteins,
84 of which showed statistically significant differential
expression, reinforcing previous data supporting the
involvement of the immune system, calcium homeo-
stasis, cytoskeleton assembly, and energy metabolism
in schizophrenia. In addition a number of new
potential markers were found that may contribute to
the understanding of the pathogenesis of this complex
disease.
jKey words schizophrenia Æproteomics Æshot-
gun Æprefrontal cortex Æbiomarkers
Introduction
Previous studies of global gene expression in different
brain regions of schizophrenia (SCZ) patients re-
vealed dysfunctions in synaptogenesis and neural
plasticity, energy metabolism, cytoskeleton assembly
and oligodendrocyte metabolism [8,10,41,50,67,69,
92,93]. Since gene fluctuations are not always directly
correlated with a differential protein expression, gene
expression studies are nicely complemented by pro-
teomics. A few proteome studies were performed in
distinct brain regions such as anterior cingulate cor-
tex and the corpus callosum [13,30,73,75,78,86].
The prefrontal cortex (PFC) is the anterior region
of frontal lobes located above the motor and premotor
areas, and it is the neocortical region that is most
elaborated in primates in order to provide a diverse
and flexible repertoire of behaviors. Divided into
dorsolateral, orbitofrontal, and medial areas, PFC
functions are neurologically denoted as ‘‘Executive
Functions’’. These functions include differentiation of
conflicting thoughts, determination of good and bad
perspectives in accordance with determined actions,
D. Martins-de-Souza ÆW.F. Gattaz ÆE. Dias-Neto (&)
Laborato
´rio de Neurocie
ˆncias
Instituto de Psiquiatria-Faculdade de Medicina-Universidade de
Sa
˜o Paulo
Rua. Dr. Ovidio Pires de Campos, no 785, Consolac¸a
˜o
Sa
˜o Paulo (SP) 05403-010, Brazil
Tel.: +55-11/3069-7267
Fax: +55-11/3069-7283
E-Mail: emmanuel@usp.br
D. Martins-de-Souza ÆC. Rewerts ÆG. Maccarrone
C.W. Turck (&)
Max Planck Institute of Psychiatry
Kraepelinstrasse 2
80804 Munich, Germany
Tel.: +49-89/30622-317
Fax: +49-89/30622-610
E-Mail: turck@mpipsykl.mpg.de
A. Schmitt
Department of Psychiatry
University of Goettingen
Von Siebold Str. 5
37075 Goettingen, Germany
A. Schmitt
Central Institute of Mental Health, J5
68159 Mannheim, Germany
Present Address
E. Dias-Neto
University of Texas, MD Anderson Cancer Center
1515 Holcombe Blvd
Houston (TX) 77030, USA
Eur Arch Psychiatry Clin Neurosci (2009) 259:151–163 DOI 10.1007/s00406-008-0847-2
EAPCN 847
moderating correct social behavior, future conse-
quences of current activities, as well as working
memory. An important function influenced by PFC is
personality expression. Basically, the activities of this
region are the organization of thoughts and actions
according to internal aims (cognitive control) [61,
68]. Dysfunction of the dorsolateral prefrontal cortex
(DLPFC) has been implicated in the pathophysiology
of SCZ [12,98]. SCZ hallmarks such as differential eye
and hand movements probably are dysfunctions in
frontal cortical circuits [80].
In the current work, a shotgun proteomic analysis
of the DLPFC of SCZ and control samples was per-
formed and a quantitative analysis was done using
Isotope-Coded Protein Label (ICPL), a method for the
accurate quantitative comparative analysis of protein
regulation [82], aiming the identification of proteins
differentially expressed.
Defining a set of proteins that are consistently
altered in this disease and define specific pathways
altered in SCZ will be valuable not only for a better
understanding of the biological basis of the disease, but
also for drug development efforts as well as the deter-
mination of potential protein markers to the diagnosis.
Materials and methods
jMaterials
All chemicals and solvents were from Bio-Rad (Hercules, CA, USA)
and of the highest purity available. The ICPL kit was from Serva
Electrophoresis (Heidelberg, Germany) and Prespotted Anchor-
Chips were obtained from Bruker Daltonics (Bremen, Germany).
jHuman dorsolateral prefrontal cortex samples
Post-mortem brain samples from the DLPFC tissue (BA46) were
collected from 9 schizophrenia patients and 7 controls, who were
free from psychiatry disorders, somatic diseases or brain tumors
and were never treated with antidepressant or antipsychotic
medications. Brain samples were dissected by an experienced
neuropathologist (on average 24.3 h after death) and deep-frozen
immediately after collection.
All samples were obtained from the brain bank of the Central
Institute of Mental Health (Mannheim, Germany). Controls were
collected at the Institute of Neuropathology, Heidelberg University,
and their clinical records were collected from their relatives and
general practitioners. Patient samples derived from in-patients of
the Mental State Hospital Wiesloch, Germany. All cases and con-
trols were German whites. All SCZ patients have been long-term
inpatients at the Mental State Hospital Wiesloch, Germany, and the
diagnosis of schizophrenia was made ante mortem by an experi-
enced psychiatrist according to the DSM IV criteria [7]. For each
patient the antipsychotic treatment history was assessed by exam-
ining the medical charts and calculated in chlorpromazine equiv-
alents (CPE), through the algorithm developed by Jahn and
Mussgay [45]. All patients and controls underwent neuropathologic
characterization to rule out associated neurovascular or neurode-
generative disorders. The classification according to Braak was
stage II or less for all subjects [19,20]. Patients and controls had no
history of alcohol, drug abuse, or severe physical illness. All
assessment and post mortem evaluations and procedures were
previously approved by the ethics committee of the Faculty of
Medicine of Heidelberg University, Germany. Detailed patient
information are given in Table 1.
jSample preparation
Fifty milligrams of human DLPFC (gray matter) were individually
homogenized in 1.5 ml tubes with glass spheres in 200 llof6M
GuanidineÆHCl and 0.1 M HEPES buffer. Samples were centrifuged
for 10 min at 14,000 rpm and quantified [22] to prepare equimolar
pools. To achieve a similar final quantity of protein (100 lg),
control pools were made with 14.3 lg of protein from each of the
seven samples, whereas SCZ pools were made with 11.1 lgof
protein from each of the nine samples.
jICPL labeling
One hundred micrograms of total protein from SCZ or controls
(5 mg/ml) were reduced for 30 min at 60C, as specified by the
ICPL kit protocol. After cooling to room temperature (RT), free
thiol groups were alkylated in the dark with 1 ml of 0.4 M iodoa-
cetamide for 30 min at RT. Excess iodoacetamide was quenched by
adding 1 ml of 0.5 M N-acetylcysteine. For protein labeling, a
10-fold molar excess (based on free amino groups) of light tag for
the control sample and heavy tag for the SCZ samples were added
to the proteins and the reactions were allowed to proceed for 2 h at
RT. Four mililiter of 1.5 M hydroxylamine were added to each
sample to inactivate the remaining Nic-NHS reagents, and equal
aliquots of both samples were combined. Esters, which are also
formed during the labeling procedure, were hydrolyzed by raising
the pH to 11–12 for 20 min.
jDigestion of labeled proteins and fractionation
of peptides by isoelectric focusing
Protein samples were digested in 200 mM NH
4
HCO
3
, pH 8.3, with
1 mg/ml trypsin at a ratio 1:50 (P:E) at 37C for 4 h. Resulting
peptides were fractionated on Immobilized pH gradient strips (IPG
17 cm), pH 3.5–4.5. The strips were rehydratated for 12 h and run
for 8 h with a constant voltage of 10,000 V. The strip was manually
cut in 47 pieces and the peptides were extracted with 1% formic
acid.
jFractionation of peptides by nano high
performance liquid chromatography
Each of the 47 peptide samples from isoelectric focusing was fur-
ther fractionated on a micro-LC-System (HP1100 Agilent Tech-
nologies, Waldbronn, Germany) using an RP-C-18 monolithic
column (200 lm id. ·5 cm, Dionex, Sunnyvale, CA) with a flow
rate of 4 ll/min and a 40 min gradient from 10 to 100% of solvent B
(ACN; 0.1% TFA). Each isoelectric focusing eluate was chromato-
graphed and fractions were collected onto Prespotted AnchorChip
targets (Bruker Daltonics) using a PROTEINEER-FC robot (Bruker
Daltonics).
jMass spectrometry
Mass spectra from each target spot were acquired using an Ultraflex
MALDI-TOF/TOF mass spectrometer (Bruker Daltonics) in fully
automatic mode. Measurements were performed with a nitrogen
laser in positive reflector mode and a 20,000 V acceleration voltage.
Hundred shots and 1,000 shots were accumulated, respectively, for
MS spectra and for MS/MS spectra. WARP-LC 1.0 software was
used for spectra acquisition and to control the automatic selection
of peptides for further MS/MS analysis. The ICPL–labeled peptides
were selected for MS/MS analysis based on their H/L ratio.
152
Table 1 Patient and control clinical data
Sample
ID
Case Age
(years)
Gender PMI
(hours)
Type of SCZ Duration
of disease
(years)
Duration of
medication
(years)
atyptyp CPE
last
dosis
CPElifetime Cause of death DSM IV Age at
onset
Last medication Cigarettes Alcohol Hosp ECT
13/00 SCZ 64 F 11 Residual, Chronic
Paranoid episodes
48 45 3 1,536 7.7 Pulmonary insufficiency 295.6 16 Clozapine 500 mg,
haloperidol 40 mg,
ciatyl 40 mg
0 No 21 Yes
36/02 SCZ 73 M 20 Residual, chronic
Paranoid episodes
43 40 1 507.4 1.7 Heart infarction 295.6 30 Perphenazine 32 mg,
promethazine 150 mg
30/day No 33 No
39/02 SCZ 43 M 18 Residual, chronic
paranoid episodes
22 20 2 464 2.6 Heart infarction 295.6 20 Zuclopethixol 40 mg,
valproate 1,200 mg,
tiapride 300 mg
0No13No
39/03 SCZ 77 F 32 Residual, chronic
Paranoid episodes
49 48 2 2,555 8.3 Lung emboly 295.6 28 Clozapine 400 mg,
benperidol 25 mg,
chlorprothixen 150 mg
0 No 48 Yes
43/03 SCZ 76 F 17 Residual, chronic
Paranoid episodes
49 47 1 300 4.9 Cardio-pulmonary
insufficiency
295.6 27 Perazine 300 mg 0 No 30 Yes
46/00 SCZ 63 F 31 Residual, chronic
paranoid episodes
40 30 3 75 1.8 Heart infarction 295.6 24 Olanzapine 15 mg 30/day No 30 Yes
50/01 SCZ 81 M 4 Residual, chronic
paranoid episodes
62 50 1 92.8 1.4 Cor pulmonale, heart
insufficiency
295.6 19 Haloperidol 4 mg,
prothypendyl 80 mg
20/day No 48 No
75/02 SCZ 92 F 37 Residual, chronic
paranoid episodes
51 48 1 100 3.4 Pancreas-carcinoma 295.6 41 Prothipendyl 160 mg,
perazine 100 mg
0No51No
83/01 SCZ 71 M 28 Residual, chronic
paranoid episodes
40 35 1 782.4 10 Heart infarction 295.6 30 Haloperidol 32 mg,
pipamperone 40 mg
40/day No 12 No
02/02 Control 41 M 7 Heart infarction 0 No
43/01 Control 91 F 16 Cardio-pulmonary
insuffiency
0No
50/02 Control 69 F 96 Lung emboly 0 No
51/02 Control 57 M 24 Heart infarction 0 No
57/02 Control 53 M 18 Heart infarction 0 No
59/02 Control 63 M 13 Heart infarction 0 No
61/01 Control 66 M 16 Heart infarction 0 No
atyptyp duration of atypical treatment/duration of treatment with typical neuroleptis during lifetime, CPE medication calculated in chlorpromazine equivalents (mg), CPE last 10 years the sum of medications during the last
10 years in kg, Hosp hospitalization time in years, ECT electroconvulsive therapy
153
jProtein identification
Acquired MS and MS/MS spectra were automatically sent as
combined peak lists by the WARP-LC 1.0 to Biotools software 3.0
(Bruker Daltonics) and searched against the NCBI database
(Dec.16th, 2006) using an in-house version of MASCOT 2.1
(Matrix Science, London, UK). The parameter settings were as
follows: Homo sapiens for organism, trypsin and Lys-C for
enzymes (considering 1 missed cleavage), carbamidomethylation
as fixed modification and oxidized methionine and heavy and
light ICPL labels of lysines and N-terminal protein as variable
modifications.
jICPL quantitative analysis
The determination of the ratios of isotope-labeled peptide pairs
(heavy and light) was performed by the WARP-LC 1.0 Protein
Browser (Bruker Daltonics), comparing the relative heavy and light
cluster signal intensities. The identified heavy and light peptide-
pair sequences containing up to four labeled lysines with a mass
difference of 6.0204 Da per labeled amino group were obtained by
BioTools 3.0. The workflow of protein shotgun mass spectrometry
and ICPL-quantitation of differentially expressed proteins is shown
in Fig. 1.
jDetermination of regulated proteins in SCZ
samples
Three parameters were applied to determine the putative regulated
proteins:
1) BioTools software provides for each identified protein a MAS-
COT score value that is derived from the peptide hit scores.
Significant identifications were considered only for peptide
scores greater than 38.
2) We only considered proteins identified with two or more pep-
tides. Proteins identified by a single peptide were considered
provisional.
3) The regulation status of a protein was defined by the ratio of the
relative peptide signal intensities. SCZ proteins were labeled with
heavy tags and control proteins with light tags. The proteins in
both samples generated the same peptides after digestion, but
peptides from SCZ samples had an approximately 6 Da greater
mass per labeled amino group than peptides labeled with light
tags. In the analysis, a minimum of 40% variation was considered
as significant regulation. Thus, proteins considered upregulated
in SCZ had ratios ‡1.4, whereas downregulated proteins had
ratios £0.6. Ratio values between 0.6–0.8 and 1.2–1.4 were con-
sidered borderline.
Results
jProtein regulation in schizophrenia dorsolateral
prefrontal cortex
Shotgun mass spectrometry allowed the analysis of
2,541 peptide sequences (Fig. 2a), leading to the
identification of 1,261 proteins in DLPFC (Fig. 2b);
634 proteins (50.28%) were identified by unlabeled
peptides and 627 (49.72%) by labeled peptides.
For relative quantitation, peptide data for 627
proteins were evaluated. No significant variations
between SCZ and control samples were observed for
433 proteins (69.1%). Of the remaining 194 proteins,
110 (56.7%) were discarded due to low identification
scores or because it were identified by only one
peptide (‘‘one hit wonders’’), whereas 77 (39.7%)
appeared to be upregulated and 7 (3.6%) downregu-
lated, yielding a total of 84 confirmed regulated pro-
teins. All proteins that showed regulated expression in
the DLPFC of SCZ patients could be unambiguously
identified and are listed in Table 2.
SCZ Proteins
CTRL Proteins
Identification Quantitation
Cell Lysis
Reduction
Alkylation
ICPL
Labeling
ICPL
Light Tag
ICPL
Heavy Tag
Light Tag Light Tag
Light Tag
Heavy Tag
Heavy Tag Heavy Tag
Heavy Tag
Light Tag
Mix
Trypitic
Digestion IEF of Peptides
(Fractionation 1)
3,5 4,5
1,7
1
+–
HPLC of Peptides
(Fractionation 2)
Mass Spectrometry
0
0.833
1.011
1.533
2.067
3.033
3.417
3.833
5.067
8.660
264
Time (m/n)
810
H3N+
H3N+
Cly LYS
LYS IIo Yal Cy8 GIu GIn LYS IIo Yal Cy8 LYS GIn Asn COO –
LYS LYS GIn AsnCO O–
IIo Yal Cy8
Yal Cy8 GIu GIn
Arg
Arg
Arg
Arg
Arg Arg
Arg
Arg
LYS
LYS
LYS
LYS
IIo
IIo
YaI
YaI
YaI
YaI
Cy8
Cy8
CIn
CIn
Fig. 1 Shotgun sequencing workflow: Cells were disrupted and proteins are labeled with light or heavy ICPL reagents, combined and digested with trypsin. Tryptic
peptides were fractionated by isoelectric focusing (IEF) on an IPG strip and then subjected to LC-MALDI mass spectrometry for identification and ICPL quantitation
Peptides Per Protein
More than 4
11%
160
140
120
80
100
Number of peptides
60
40
20
01 2 4 5 6 7 8 9 10 11 12 12 13 14 15 16 17 18 19 20 21 22 23 24
IPG No.
26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47
3 peptides
5%
2 peptides
23% 1 peptide
61%
Fig. 2 Shotgun mass spectrometry results. aNumber of peptides identified from each IPG fraction; bNumber of peptides that identified a protein
154
Table 2 Proteins regulated in schizophrenia brains, classified according to their biological function
Biological process Reg. in
SCZ
H/L
ratio
Gene
name
Protein name (HPRD) MW
(th)
Chr loci Id.
pept
MASCOT
score
Previously described in
SCZ (*= proteome and # = gene expression)
Signal transduction/Cell
communication,
**protein modification
fl0.39 SIRPA SIRP alpha 1 54,967 20p13 2 125.11
›1.42 PEBP1 Phosphatidylethanolamine binding protein
(Raf kinase inhibitor protein)
21,057 12q24.23 19 51.19 Clark et al. [30]*
›1.43 SORBS1 Sorbin and SH3 domain containing 1 142,496 10q23.3-q24.1 2 42.14
›1.46 PPP1R9B Protein phosphatase 1, regulatory subunit 9B 89,451 17q21.33 2 56.27
›1.49 GSPT1 G1 to S phase transition 1 55,756 16p13.1 2 65.64
›1.52 CTNND2 Delta catenin 132,656 5p15.2 2 58.55
›1.52 OPA1 Dynamin like 120 kDa protein, mitochondrial 117,770 3q28-q29 4 73.1 Clark et al. [30]*; Pennington et al. [75]*
›1.53 SH3GL2 SH3 containing GRB2 like protein 2 39,962 9p22 5 65.91 Prabakaran et al. [78]*
›1.55 SLC9A3R1 Solute carrier family 9, isoform A3, regulatory factor 1 38,868 17q25.1 3 38.88
›1.60 HOMER1 Homer neuronal immediate early gene 40,277 5q14.2 2 73.93
›1.61 SIRPB1 Signal regulatory protein beta 1 43,254 20p13 3 106.8
›1.65 PRKCG Protein kinase C, gamma 78,448 19q13.4 3 61.91 Vawter et al. [93] (Lymp) #;
›1.98 CSNK2A1 **Casein kinase II, alpha 1 45,143 20p13 2 43.43
›2.00 CHP Calcium binding protein P22 22,456 15q13.3 2 51.92
›2.20 STRN Striatin calmodulin binding protein 86,132 2p22-p21 2 44.18
Cell growth/maintenance fl0.53 MYO1D Myosin ID 116,202 17q11-q12 2 76.37
›1.40 PKP4 Plakophilin 4 131,868 2q23-q31 2 39.5
›1.41 EPB41L3 Band 4.1 like protein 3 120,677 18p11.32 7 84.97
›1.42 DES Desmin 53,536 2q35 2 75.79
›1.46 EPB41L1 Neuron type nonerythroid protein 4.1 98,503 20q11.2-q12 2 59.57
›1.52 TRIM3 Brain expressed RING finger 80,829 11p15.5 2 78.65
›1.52 MAP6 Microtubule associated protein 6 86,505 11q13.3 3 41.03
›1.52 MRLC2 Myosin regulatory light chain MRLC2 19,779 18p11.31 2 65.91
›1.53 MAP2 Microtubule associated protein 2 202,758 2q34-q35 7 94.94
›1.58 MAP1A Microtubule associated protein 1A 291,964 15q13-qter 5 50.55
›1.58 TUBB2B Tubulin beta polypeptide paralog 49,953 6p25 7 98.31 Virgo et al. [95]
#
; Beasley et al., [13]*;
Sivagnanasundaram et al. [86]*
›1.62 LMNB2 Lamin B2 67,689 19p13.3 4 47.66
›1.64 KIF21A Kinesin family member 21A 185,510 12q12 2 47.63 Hakak et al.[41]
#
›1.67 VIM Vimentin 53,652 10p13 2 74.17
›1.70 NSFL1C NSFL1 (p97) cofactor (p47) 40,573 20p13 2 44.69 Prabakaran et al. [78]*
Metabolism/energy
pathways
fl0.50 CNP 2¢,3¢cyclic nucleotide,3¢-phosphodiesterase 45,099 17q21 18 93.81 Hakak et al. [41]
#
; Tkachev et al. [92]
#
;
Aston et al. [10]
#
; Prabakaran et al. [78]*;
Katsel et al. [50]
#
; Dracheva et al. [33]
#
;
McCullumsmith et al. [65]
›1.40 ADH5 Alcohol dehydrogenase 5, chi polypeptide 39,724 4q21-q25 2 57.78
›1.41 GAPDH Glyceraldehyde 3 phosphate dehydrogenase 36,054 12p13 25 87.78 Prabakaran et al. [78]*
›1.42 STUB1 STIP1 homologous and U box containing protein 1 34,856 16p13.3 2 86.17
›1.44 PRDX2 Peroxiredoxin 2 21,892 19p13.2 2 90.83
›1.53 HK1 Hexokinase 1 102,738 10q22 2 62.27 Prabakaran et al. [78]*
›1.55 UQCRC1 Cytochrome bc1 52,646 3p21.3 1 94.36 Prabakaran et al. [78]*
›1.56 NDUFV2 NADH ubiquinone oxidoreductase flavoprotein 2 27,363 18p11.31-p11.2 2 76.63
›1.68 PFKM Phosphofructokinase 85,182 12q13.3 2 52.28
155
Table 2 continued
Biological process Reg. in
SCZ
H/L
ratio
Gene
name
Protein name (HPRD) MW
(th)
Chr loci Id.
pept
MASCOT
score
Previously described in
SCZ (*= proteome and # = gene expression)
›1.71 CKB Creatine kinase brain type 42,644 14q32 5 86.64 Prabakaran et al. [78]*; Clark et al. [30]*;
Beasley et al. [13]*; Sivagnanasundaram et al. [86]*
›1.78 PPT1 Palmitoyl protein thioesterase 1 34,193 1p32 2 41.11
›2.47 AK1 Adenylate kinase 1 21,635 9q34.1 3 50.9
›3.69 PRDX6 Peroxiredoxin 6 25,035 1q25.1 4 55.98
Regulation of nucleobase,
nucleoside, nucleotide
and nucleic acid
metabolism
*also belongs to
this class
›1.42 HNRPU Heterogeneous nuclear ribonucleoprotein U 90,584 1q44 5 45.76
›1.44 SFRS7 Splicing factor, arginine/serine-rich 7,35 kDa 27,366 2p22.1 2 94.2
›1.45 NONO Non pou domain containing octamer binding protein 54,231 Xq13.1 2 71.75
›1.49 FUBP1 Far upstream element binding protein 68,604 1p31.1 2 47.36
›1.53 SFRS6 Splicing factor, arginine/serine-rich 6 39,587 20q12-q13.1 3 43.85
›1.56 HNRPK Heterogeneous nuclear ribonucleoprotein K 51,028 9q21.32-q21.33 3 83.54
›1.69 PurA Purine rich element binding protein A 34,911 5q31 2 54.29
›1.83 NUCKS1 Nuclear ubiquitous casein kinase and cyclin
dependent kinase substrate
27,296 1q32.1 2 14,4.54
›1.90 HP1BP3 HP1-BP74 61,207 1p36.12 2 51.2
›1.92 BSN Zinc finger protein 231 416,464 3p21.31 2 59.78
›1.96 HNRPA0 Heterogeneous nuclear ribonucleoprotein A0 30,841 5q31 2 62.9
Protein metabolism fl0.54 HSPA5 BIP 72,333 9q33-q34.1 2 81.99 Prabakaran et al. [78]*; Clark et al. [30]*;
Sivagnanasundaram et al. [86]*
›1.41 CKAP1 Cytoskeleton associated protein 1 27,325 19q13.11-q13.12 4 66.94
›1.46 SERPINA3 Alpha 1 antichymotrypsin 47,651 14q32.1 2 41.1 Arion et al. [8]
#
›1.46 HSPA1A Heat shock 70 KD protein 1A 70,038 6p21.3 10 94.04 Prabakaran et al. [78]*; Clark et al. [30]*; Arion et al. [8]
#
›1.49 FARSLA Phenylalanyl-tRNA synthetase alpha chain 57,563 19p13.2 2 44.11
›1.50 DNAJC6 DnaJ (Hsp40) homolog subfamily C member 6 99,996 1pter-q31.3 2 76.4 Arion et al. [8]
#
›1.53 CCT3 Chaperonin containing T complex polypeptide 1,
subunit 1
60,534 1q23 2 93.78
›1.61 UBE2 N Ubiquitin conjugating enzyme E2N 17,138 12q22 3 97.82
Transport fl0.54 HBB Hemoglobin beta chain 15,998 11p15.5 7 56.38
›1.47 ATCAY Caytaxin 42,120 19p13.3 2 53.87
›1.50 VAPB VAMP associated protein B 27,228 20q13.33 5 59.09
›1.51 APOE Apolipoprotein E 36,154 19q13.2 2 43.33
›1.66 ATP6V0D1 ATPase H+ transporting lysosomal 38 KD V0
subunit D, isoform 1
40,329 16q22 2 89.36
›1.72 RLBP1 Retinaldehyde binding protein 1 36,474 15q26 2 51
Immune response fl0.31 MOG Myelin oligodendrocyte glycoprotein 28,647 6p22.1 1 97.74 Tkachev et al. [92]
#
; Katsel et al. [50]
#
; Arion et al. [8]
#
fl0.57 IGSF4B Immunoglobulin superfamily member 4B 47,021 1q21.2-q22 2 66.04
›1.69 KIR3DL2 NK associated transcript 4 50,216 19q13.4 2 109.11
Cytoskeletal anchoring ›1.68 PLEC1 Plectin 1 531,789 8q24 2 46.48
Osmoregulation/hormone
metabolism
›1.56 CRYM Crystallin mu 33,775 16p13.11-p12.3 2 106.46 Hakak et al. [41]
#
; Middleton et al. [67]
#
;
Vawter et al. [93] (Lymp)
#
; Sivagnanasundaram
et al. [86]*, Arion et al. [8]
#
156
jFunctional classification of regulated proteins
The regulated proteins were divided in functional
classes according to the human protein reference
database (HPRD—http://www.hprd.org) and are
shown in Table 2. Most of them belong to cell com-
munication and signal transduction (15/84), cell
growth maintenance (15/84) and energy metabolism
(13/84) pathways.
Discussion
jShotgun and ICPL methodologies for proteomic
analysis
We employed in our analysis a shotgun methodology
consisted in two methods of peptide fractionation,
aiming to reveal the differential expression of the
widest proteome possible, including mainly the low-
expressed proteins, which are normally not detected
in conventional proteome analysis.
The quantification of shotgun-generated data was
improved using ICPL, a stable isotope labeling which
allows a more precise proteome comparison and
quantification [82]. This kind of analysis is quite
superior in sensibility and accuracy if compared with
the known post-eletrophoretic staining methodologies.
jThe differentially expressed proteins
in schizophrenia
Our findings support previous reports on altered pro-
tein expression in SCZ, and suggest new targets which
may be relevant for the pathobiology of the disease.
Schizophrenia as an immune system disease
The first time immunological effects were implicated
in SCZ was in 1845 by Esquirol, who described SCZ
as an epidemic outbreak of psychotic disorders.
Many years later a new concept emerged, now known
as ‘psychoneuroimmunology’, which is defined as
the investigation of influences of the immune sys-
tem on the central nervous system (CNS) and its
consequences on behavior and mental illness. Previ-
ously-observed alterations in the concentrations of
immunotransmitters, cytokines such as interleukin-2,
-4, -6 and -10, interferon-gamma and tumor necrosis
factor-alpha strongly suggested that the immune
system plays a role in disease pathology reviewed in
[70,88]. The differential regulation of immune system
related-proteins presented in this study reinforces this
concept.
Signal-regulatory protein alpha (SIRPA—down-
regulated: 2.56x) and Signal regulatory protein beta 1
(SIRPB1—upregulated: 1.61x) are transmembrane
Table 2 continued
Biological process Reg. in
SCZ
H/L
ratio
Gene
name
Protein name (HPRD) MW
(th)
Chr loci Id.
pept
MASCOT
score
Previously described in
SCZ (*= proteome and # = gene expression)
DNA repair ›1.89 APEX2 DNA-(apurinic or apyrimidinic site) lyase 2 57,400 Xp11.22 2 56.43
Biological_process unknown ›2.92 CGI–38 CGI-38 brain specific protein 18,985 16q22.1 2 94.3
›1.41 SEPT4 Septin 4 55,098 17q22-q23 2 53.71
›1.42 TTC9C Hypothetical protein MGC29649 20,013 11q12.3 2 41.67
›1.43 RTN4 Reticulon 4 12,031 2p16.3 5 40.83
›1.45 L1CAM L1 cell adhesion molecule 140,002 Xq28 2 71.6
›1.49 LANCL2 LanC lantibiotic synthetase component C like 2 50,854 7q31.1-q31.33 2 48.03
›1.51 KIAA1189 (Ermin (myelinating oligodendrocyte-specific protein)) 34,301 2q24.1 2 78.22
›1.54 RBMXL1 Similar to RNA binding motif protein X linked 42,141 1p22.2 2 74.47
›1.59 EFHD2 EF hand domain family member D2 26,697 1p36.21 5 53.89
›1.88 WDR1 WD repeat protein 1 66,193 4p16.1 2 55.84
MW (th) predicted protein molecular weight, Chr Loci gene locus, Id. Pept number of peptides that identified the protein, MASCOT score identified peptide database search score; other researches which found the differential
regulation of the same gene or protein)
*Previously described in reports of SCZ proteome;
#
Previously described in reports of SCZ gene expression; **CSNK2A1 belongs to Protein Modification Biological Process
157
glycoprotein receptors, involved in the negative reg-
ulation of receptor tyrosine kinase-coupled signaling
processes and belong to the immunoglobulin super-
family. SIRPA interacts with Janus kinase 2 (JAK2)
and Olanzapine treatment (used by 1 of 9 patient-
s—Table 1) demonstrates activation of the JAK-STAT
signaling cascade, increasing the phosphorylation
of both proteins [85]. SIRPA regulates neutrophil
transmigration [62], B lymphocyte recruitment
[102] and destruction of host cells in autoimmune
diseases [74] through CD47 binding. SIRPB1 regulates
neutrophil transepithelial migration and plays an
important role in the response to inflammatory
stimuli [63]. Peroxiredoxin 2 (PRDX2—upregulated:
1.44x), which contributes to CD8(+) T-cell activity
[66], due to its antioxidant role [81], may represent a
link with oxidative stress previously described in SCZ
[79]. Plectin 1 (PLEC1—upregulated: 1.68x) is a reg-
ulator of T lymphocyte cytoarchitecture [24].
Cytoskeleton assembly
Cytoskeleton proteins display a tissue-specific pattern
of expression and their altered expression can directly
influence key cellular processes, including symmetri-
cal shape, structural polarity, neuritogenesis, and
neurotransmission, that are essential for the physiol-
ogy of the neuron reviewed in [15].
Abnormalities in cytoarchitectural pattern were
previously described in brain tissues of SCZ patients
[9]. The differential regulation of proteins such as
Vimentin (VIM—upregulated: 1.67x), Lamin B2
(LMNB2—upregulated: 1.62x), Desmin (DES—upreg-
ulated: 1.42x), Plectin 1 (PLEC1—upregulated: 1.68x),
Tubulin beta polypeptide (TUBB2B—upregulated:
1.58x), reinforces these observed abnormalities. In
addition, Cytoskeleton associated protein 1 (CKAP1—
upregulated: 1.41x), that facilitates the dimerization of
alpha- and beta-tubulin through nitric oxide signaling,
and Kinesin family member 21A (KIF21A—upregu-
lated: 1.64x),) which interacts with disrupted-in-
schizophrenia 1 (DISC1), are also likely causal factors of
SCZ. Moreover, we found the upregulation of 3 MAP
(Microtubule-associated protein) proteins (MAP1A,
MAP2 and MAP6—upregulated: 1.58x, 1.53 and 1.53)
that are involved in microtubule assembly, an essential
step in neurogenesis. Proteins of the MAP family were
previously described to be involved in SCZ and have
been suggested as potential therapeutic targets [15].
TAU, APOE, Alzheimer’s disease and SCZ-altered
proteins
TAU is a neuronal microtubule-binding protein and
its inclusions are the main feature of several neuro-
degenerative diseases, including Alzheimer’s disease
(AD). TAU ubiquitination and hyperphosphorylation
[48] generate filamentous polymers that lead to neu-
ronal apoptosis [46]. STIP1 homologous (STUB1—
upregulated: 1.42x) and Ubiquitin conjugating
enzyme E2N (UBE2N—upregulated: 1.61x—gene was
found downregulated in SCZ DLPFC [94]) participate
in the ubiquitination of hyperphosphorylated TAU
leading to filamentous polymers [84]. Moreover, STIP1
interacts with the chaperone heat shock 70 KDa protein
1A (HSPA1A—upregulated: 1.46x), whose gene was re-
cently described to be upregulated in SCZ DLPFC [8].
Apolipoprotein E (APOE—upregulated: 1.51x) and
Serpin peptidase inhibitor (SERPINA3—upregulated:
1.46x) are proteins involved in lipid metabolism and
are present in AD amyloid deposits [29,90]. The
interaction of APOE with TAU has been reported
numerous times [14]. Moreover, Peroxiredoxin 2
(PRDX2—upregulated: 1.44x) have previously been
described to be involved in AD and to be differentially
regulated in SCZ DLPFC.
Crystallin (CRYM—downregulated 1.56x) that
modulates cytoskeleton assembly, was found regu-
lated in astrocytes associated with senile plaques and
cerebral amyloid angiopathy in AD patients [99] and
in gene expression and proteome analysis [8,41,86].
Ca
2+
homeostasis
jCa
2+
and neurotransmission Ca
2+
is considered to
be a pivotal metabolite for the dopamine hypothesis in
SCZ [17]. In addition, the identification of the altered
expression of many Ca
2+
-related proteins corroborates
the concept of Ca
2+
altered homeostasis in SCZ.
Intracellular calcium levels control the dopamine
receptor function [17] and the maintenance of neuro-
transmitter exocytosis during stimulation [23,28].
These processes are controlled by Neuronal protein 4.1
(EPB41L1—upregulated: 1.46x), which stabilizes dopa-
mine receptors at the neuronal plasma membrane [18]
and also by Endophilin A1 (SH3GL2—upregulated:
1.53x), which is essential for the formation of synaptic
vesicles from the plasma membrane. Phosphatidyleth-
anolamine-binding protein 1 (PEBP1—upregulated:
1.42x), is a substrate of calpain [27], a Ca
2+
-dependent
protease that has been implicated in processes that
produce persistent changes in synaptic chemistry and
structure [36].
Calcium plays a critical role in signaling glutama-
tergic synapses. The regulation of Presynaptic cyto-
matrix protein (BSN—upregulated: 1.92x) suggests a
glutamatergic dysfunction. In BSN-null mice an
inactivation of a significant fraction of glutamatergic
synapses [6] occurs. Moreover, Homer homolog 1
(HOMER1—upregulated: 1.6x), a protein previously
associated with SCZ [72], regulates the metabotropic
glutamate receptor function [91]. In addition, Halo-
peridol treatment induced the increased expression of
158
HOMER1 in different brain region in rats [76]. This is
important in light of the fact that 3 out of 9 patients in
the present study had been treated with Haloperidol.
Finally, Myosin regulatory light chain (MRLC2—
upregulated: 1.52x) is an enzyme activated by calcium.
jCalmodulin and calcineurin related proteins Cal-
modulin, the most prominent calcium-modulated
protein, is involved in the control of many biochem-
ical processes and binds several proteins such as
Striatin (STRN—upregulated: 2.2x), Casein kinase II,
alpha 1 (CSNK2A1—upregulated: 1.98x), Myosin ID
(MYO1D—downregulated: 1.88x), and Casein kinase
II, alpha 1 (CSNK2A1—upregulated: 1.98x—found
downregulated in frontal cortex of SCZ [4]. This
protein has been implicated in several cellular func-
tions including cellular growth control, proliferation
and apoptosis [1].
Calcineurin is a regulator of dopaminergic [38] and
glutamatergic [103] neurotransmission, which is vital
for normal cognitive and behavioral functioning
and is frequently compromised in SCZ [25,57,83].
Calcineurin homologous protein (CHP—upregulated:
2x), which interacts with Solute carrier family 9,
isoform A3 (SLC9A3—upregulated: 1.55x), inhibits
calcineurin activity, most likely compromising regu-
lation of neurotransmission.
jCa
2+
and actin-related proteins Cell adhesion is
mediated by Cadherins, which are Ca
2+
dependent, and
Catenins, which bind actin [51,64]. We found in SCZ
DLPFC the regulation of Catenin 4 (PKP4—upregulated:
1.4x) and Delta catenin (CTNND2—upregulated: 1.52x)
proteins, which regulate cadherin function and inter-
action with actin [43], and Band 4.1 like protein 3
(EPB41L3—upregulated: 1,41x), a protein that acts in
intercellular junctions by binding actin [101].
Spinophilin (PPP1R9B—upregulated: 1.46x), a
dendritic protein that regulates glutamate receptor
activity, has an actin-binding domain, necessary for
targeting spinophilin to dendrites [39] and interacts
with D1 and D2 dopamine receptors [87] which are
directly controlled by Ca
2+
. Despite a study impli-
cating PPP1R9B in SCZ hippocampal dendritic
pathology [56], the administration of clozapine and
haloperidol (antipsychotics used by our patients)
could regulate the PPP1R9B concentrations [31].
Moreover, PPP1R9B may contribute to the dysfunc-
tion of the dopamine system in DLPFC SCZ, since
altered levels of dopamine receptor-binding proteins
may lead to a dopamine imbalance [11,52].
Mitochondrial metabolism
Mitochondrial hypoplasia, imbalance of the oxidative
phosphorylation system, and differentially expressed
genes and proteins related to mitochondria are be-
lieved to be involved in SCZ mitochondrial dysfunc-
tion [16,30,78]. This leads to alterations in ATP
production, generation of reactive oxygen species and
alterations in intracellular calcium concentrations.
These processes combined result in an altered syn-
aptic state, compromising the plasticity, neuronal
polarity and synaptogenesis reviewed in [16].
Our data show the differential regulation of mito-
chondrial proteins such as Dynamin-like 120 kDa
protein (OPA1—upregulated: 1.52x), that participate
in mitochondrial biogenesis and stabilization of
mitochondrial membrane integrity [5]; Cytochrome
bc1 (UQCRC1—upregulated: 1.55x), that was previ-
ously implicated in SCZ [49]; and NADH ubiquinone
oxidoreductase flavoprotein 2 (NDUFV2—upregu-
lated: 1.56x) that participates in nervous system
development [42].
Energy metabolism
Glucose metabolism involves different interconnected
pathways that have been identified as involved in the
pathogenesis of SCZ [21,53]. The relationship be-
tween glucose regulation and SCZ is significant since
glucose administration decreases deficits in verbal
declarative memory [37] and atypical antipsychotic
medications generate hyperglycemia [40,77]. In
addition, alterations in basal glucose metabolism in
DLPFC could generate SCZ hypofrontality [100].
We found several regulated enzymes involved in
glucose metabolism. These include Glycolysis en-
zymes such as Hexokinase 1 (HK1—upregulated:
1.53x), Phosphofructokinase (PFKM—upregulated:
1.68x), and Glyceraldehyde 3 phosphate dehydroge-
nase (GAPDH—upregulated: 1.41x). We also found
regulated proteins involved in lipid metabolism.
Peroxiredoxin (PRDX6—upregulated: 3.69x) is a
bifunctional enzyme that, despite its redox regulation
role in the cell, acts as a Ca
2+
-independent phospho-
lipase A2 for cellular phospholipid turnover [26]. Rats
treated with chlorpromazine and clozapine showed
altered PRDX levels in the hippocampus [54]. The
upregulation of a redox regulation enzyme could be a
hallmark of cellular oxidative stress previously de-
scribed in SCZ [78]. Palmitoyl protein thioesterase 1
(PPT1—upregulated: 1.78x) is a key enzyme for fatty
acid synthesis that participates in many biochemical
pathways, including brain and neuronal development
[44,60] and sphingolipid catabolic processes [3].
PPT1 is present in axons and metabolizes synaptic
vesicles [2]. Alcohol dehydrogenase 5, chi polypeptide
(ADH5—upregulated: 1.40x) metabolizes, among
many other substrates, lipid peroxidation products
[35]. Apolipoprotein E (APOE—upregulated: 1.51x)
and Alpha 1 antichymotrypsin (SERPINA3—upregu-
lated: 1.46x) are essential for lipid metabolism.
159
Oligodendrocyte-related proteins
Our study revealed differential regulation of myelin
oligodendrocyte glycoprotein (MOG—downregulated:
3.23x), 2¢,3¢cyclic nucleotide, 3¢-phosphodiesterase
(CNP—downregulated: 2.00x) and ermin—
ERM-like protein (ERMN—upregulated: 1.51x), cor-
roborating several cDNA microarray study data [10,
41,50,92] and other gene expression analyses [33,65,
97]. All these studies revealed an alteration of a series
of myelin-related genes in SCZ. The myelination and
maintenance of myelin sheets in axons of the CNS is
the most important function of the oligodendroglia,
and the diminution or malformation of the myelin
sheath results in an increased ion leakage and a re-
duced propagation of nerve impulses. Moreover, other
functions such as trophic signaling to nearby neurons,
synthesis of growth factors, neuronal survival and
development, neurotransmission and synaptic func-
tion are executed by oligodendrocytes [32,34].
jOne hit wonders
We discard from our list of differentially expressed
proteins the ones that were identified by only one
peptide. However, we sustained in Table 2the pro-
teins UQCRC1 and MOG, even identified by one
peptide, since there were proteins previously identi-
fied by our group and other groups as differentially
expressed besides the potential their role previously
described in SCZ.
jAnalysis of protein pools
For a number of reasons we compared protein pools
instead of individual protein extracts in the present
study. While we are aware that more dramatic alter-
ations in certain proteins of a single individual might
‘contaminate’ the pool, suggesting unreal alterations,
we believe that the advantages of sample pooling may
overcome its disadvantages. Foremost, sample-pool-
ing reduces the influence of individual proteome
variations (not related to the disease) while high-
lighting the most consistent (disease-related) altera-
tions. An additional advantage is the reduction of the
amount of protein required from each sample,
allowing experimental replicates and subsequent
studies. This approach has been successfully used by
several groups not only for proteomics [47,58,59],
but also for gene expression analysis [50,93] and
genotyping [96]. By using comparative genome
hybridization for the analysis of copy number varia-
tions, the authors showed that neither specific DNA
variations nor specific genes were consistently asso-
ciated with SCZ. Rather, their results showed that the
disease is likely to be caused by rare alterations which
disrupt pathways related to neural regulation and
development. As shown in the present report, the
analysis of sample pools is capable of implicating
recurring pathway alterations in a consistent manner.
jConfounding factors
We cannot confirm that all protein alterations de-
tected in our analyses are directly associated with
SCZ. If associated with SCZ, we also cannot confirm
that their regulation is causative for the disease pro-
cess, or rather a consequence of age, gender, diet and/
or medications taken by the patients. All these vari-
ables can directly influence the proteome. Thus, va-
lidation experiments have to be done.
As is evident from Table 1, all SCZ samples used in
this study came from patients that have taken dif-
ferent antipsychotic drugs. This is a limitation of the
current and many additional studies. Three out of
nine patients from our study were taking haloperidol
at death. Sugai et al. [89], using cDNA arrays from
cynomolgus monkeys and Narayan et al. [71], using
in situ hybridization analysis of mice, showed that
myelin basic protein (MBP) is modulated as a result
of haloperidol treatment. An altered expression of
Apolipoprotein A-I in plasma of SCZ medicated pa-
tients was also found [55], whereas Malate dehydro-
genase, Peroxiredoxin 3, Vacuolar ATP synthase
subunit beta and Mitogen-activated protein kinase
kinase 1 were found to be regulated in the hippo-
campus of chlorpromazine/clozapine treated rats
[54]. However, a considerable number of proteins
identified here have not been reported to be associ-
ated with any of the drugs used by the patients and
many have been associated with SCZ processes largely
independent of an exogenous drug effect, such as
genetic linkage studies. We expected that the pooling
strategy adopted here would contribute to dilute
protein alterations driven by haloperidol in 1/3 of our
patients, but we cannot exclude that some of the
alterations seen here could be drug-related, rather
that SCZ-related.
Whereas the study of brain samples derived from
psychotropic drug-naı
¨ve patients [79] and animal
models are of utmost importance, the vast majority of
samples available worldwide are derived from treated
patients. As the samples used in the studies were
derived from patients under distinct therapeutic reg-
imens, the recurrent identification of the same targets
might implicate certain genes and proteins in the
pathobiology of the disease. Thus, we believe that the
findings described here will reinforce the interest in
certain pathways, and moreover suggest new protein
candidates, which can be further investigated in fu-
ture studies.
jAcknowledgments The authors would like to thank ABADHS
(Associac¸a
˜o Beneficente Alzira Denise Hertzog da Silva), FAPESP
(Fundac¸a
˜o de Amparo a Pesquisa do Estado de Sa
˜o Paulo), and
160
CNPq (Conselho Nacional de Desenvolvimento Cientı
´fico e Tec-
nolo
´gico) for the financial support of this project in Brazil. We also
would like to acknowledge the DAAD (Deutscher Akademischer
Austauschdienst) and the Max Planck Society for their financial
support of this work in Germany. We thank Ms. Molly McEwen for
editorial help.
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