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Molecular Psychiatry (2010) 15, 1088–1100 & 2010 Macmillan Publishers Limited All rights reserved 1359-4184/10 www.nature.com/mp

ORIGINAL ARTICLE

Global proteomic profiling reveals altered proteomic signature in schizophrenia serum Y Levin1,3, L Wang1,3, E Schwarz1, D Koethe2, FM Leweke2 and S Bahn1 1 Institute of Biotechnology, University of Cambridge, Cambridge, UK and 2Department of Psychiatry and Psychotherapy, University of Cologne, Cologne, Germany

Schizophrenia is one of the most severe psychiatric disorders affecting 1% of the world population. There is yet no empirical method to validate the diagnosis of the disease. The identification of an underlying molecular alteration could lead to an improved disease understanding and may yield an objective panel of biomarkers to aid in the diagnosis of this devastating disease. Presented is the largest reported liquid chromatography-mass spectrometry-based proteomic profiling study investigating serum samples taken from first-onset drug-naive patients compared with samples collected from healthy volunteers. The results of this large-scale study are presented along with enzyme-linked immunosorbent assay-based validation data. Molecular Psychiatry (2010) 15, 1088–1100; doi:10.1038/mp.2009.54; published online 23 June 2009 Keywords: schizophrenia; biomarkers; label free; nanoLC-MS/MS; LC-MSE; serum

Introduction Schizophrenia is a severe, complex neuropsychiatric disorder. Despite substantial variation, especially with regard to gender, urbanicity and migrant status, schizophrenia affects approximately 1% of the population, on a global scale.1,2 Currently, there is no empirical test aiding the accurate diagnosis of people suffering from schizophrenia. Although some insights into the aetiology of schizophrenia have been gained using the current interview-based methodology, the molecular basis of the disease is still unknown. A more biomedical approach to understanding the aetiology of the disease would improve management and treatment of schizophrenia. Several studies have been conducted in search for genetic mutations linked to the disorder. However, no genetic polymorphism is consistent across the different studies.3 Genetic factors alone do not account for illness onset,4 which is heavily influenced by environmental factors. The proteome holds the key to unravelling disease mechanisms enabling the development of improved diagnostics, the assessment of drug response, drug efficacy and drug toxicity.5 The latest proteomic Correspondence: Dr S Bahn, Institute of Biotechnology, University of Cambridge, Tennis Court Road, Cambridge, Cambridgeshire CB 2 1QT, UK. E-mail: [email protected] 3 These authors contributed equally to this work. Received 27 January 2009; revised 7 April 2009; accepted 4 May 2009; published online 23 June 2009

techniques enable the measurement of diseaseassociated changes in a large number of proteins simultaneously. Proteomic studies have many advantages over mRNA gene expression analyses as they focus on the protein as the ‘biological effector molecule’.6 Most proteomics platforms are centred around the implementation of mass spectrometry techniques in conjunction with separation technologies.5 Over the past decade, these technologies have matured and now enable the relative abundance of measurements of hundreds or even thousands of proteins in one experiment.5 Thus, researchers can monitor the global expression of proteins and protein groups in search for disease-related differences, which can provide an insight into the aetiology of diseases and the ability to find disease-specific markers. One of the major requirements of an objective biomedical diagnostic test is that the biological sample must be accessible. However, this is not the case for every body fluid or tissue. Central nervous system tissue, for example, is clinically not readily accessible for analysis. In the case of neuropsychiatric disorders, this is a critical issue, as these disorders manifest themselves with brain dysfunctions. Serum, on the other hand, is a highly accessible bodily fluid, which can be sampled with minimal discomfort to the patient. Moreover, it has been shown that for many diseases, the serum proteome holds the greatest promise for the discovery of disease biomarkers.7 One of the main reasons for this is that it circulates and is in molecular exchange with every tissue and every organ in the body. It therefore reflects both

Altered proteomic signature in schizophrenia serum Y Levin et al

physiological and pathological processes in the body and is most suited for disease diagnosis and monitoring. Analysis of the serum proteome, however, holds several challenges for quantitative proteomics. The first and the foremost is the overwhelming dynamic range of abundance of the proteins. It is estimated that it spans across 10–12 orders of magnitude.8 This is an enormous challenge as most high-throughput quantitative platforms only have a dynamic range of up to 3 orders of magnitude.9 Another challenge of the analysis of the serum is the diverse range of analytes present. These include very large molecules such as proteins, and smaller molecules such as lipids and other metabolites as well as electrolytes.7 Finally, it is estimated that serum includes around 10 000 individual proteins.7,8 These challenges must be dealt with during sample preparation to extract maximum information from the precious clinical samples. To overcome the aforementioned challenges, we used a non-hypothesis-based label-free proteomic approach that is sensitive, reproducible and accurate as described previously in Levin and Schwarz.10 The presented study is the largest liquid chromatographymass spectrometry (LC-MS)-based proteomic profiling study conducted to date for the purpose of investigating sera taken from first-onset drug-naive schizophrenia patients.

Materials and methods The Ethical Committee of the Medical Faculty of the University of Cologne reviewed and approved the protocol of this study and the procedures for sample collection and analysis. All study participants gave their written informed consent. All clinical investigations were conducted according to the principles expressed in the Declaration of Helsinki. Clinical serum samples A set of 55 clinical samples were prepared. The samples have been stored at 80 1C in identical conditions following collection and have undergone two freeze–thaw cycles. The samples included 22 serum samples from patients diagnosed with firstonset paranoid schizophrenia (DSM-IV 295.30) and 33 serum samples taken from demographically matched controls. The healthy volunteers were chosen carefully to make sure that there was no family history of Schizophrenia or other detectable psychiatric, neurological or medical history. Lastly, the healthy volunteers were demographically matched to the diseased patients (see Table 1). Quality control samples Along with the 55 clinical samples were 12 quality controls (QCs) that were aliquoted from one serum sample before any preparation. The QCs were incorporated among the real samples to monitor the preparation and nanoUPLC-MSE performance.

Table 1 Demographic information for the clinical serum samples used in the profiling study (values are mean±s.d.)

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Schizophrenia Control Significance Serum sample size Age Gender (male/female)

n = 22 29.0±11 15/7

n = 33 28±7 18/15

P = 0.71 P = 0.31

Sample preparation All samples were prepared and analysed blindly and randomly. The total protein concentration of each serum sample was measured using a protein assay (Bio-Rad, Hercules, CA, USA) before preparation. Each sample was depleted of the 20 most abundant proteins: albumin, immunoglobulin (Ig)G, IgA, IgM, IgD, transferrin, fibrinogen, a2-macroglobulin, a1antitrypsin, haptoglobulin, a1-acid glycoprotein, ceruloplasmin, apolipoprotein A1, apolipoprotein A2, apolipoprotein B, complement C1q, complement C3, complement C4, plasminogen and transthyretin. This was performed using an immunoaffinity kit (Sigma, St Louis, MO, USA), loading a total of 560 mg of protein (average of 5 ml) of each sample onto the depletion column. Buffer exchange was performed with 50 mM ammonium bicarbonate using spin columns (Millipore, Bedford, MA, USA) with a 5kDa-molecular weight cutoff to separate proteins from small molecules in the serum. The proteins were reduced using 5 mM dithriotheitol (Sigma, USA) at 60 1C for 30 min and alkylated with 10 mM iodoacetemide (Sigma, USA) in the dark at room temperature for 30 min. The proteins were digested using trypsin (Promega, Madison, WI, USA), at a ratio of 1:50 (w/w trypsin/protein) for 16 h at 37 1C. The digestion was stopped by adding 2.3 ml of 8.8 M HCl to each sample. The samples were stored at 80 1C until analysis. Before nanoUPLC-MSE analysis, each sample was spiked with 25 fmol ml1 tryptically digested Enolase from Yeast (Waters, Milford, MA, USA), which was used for normalization. Pure Saccharomyces cerevisiae Enolase digest was injected with identical LC and MS methods to assure correct peptides were selected for normalization (data not shown). Liquid chromatography For all chromatographic steps, LC-MS grade solvents were used (Fisher Scientific, Loughborough, UK). Each sample was injected and analysed three times followed by a blank injection (to ensure there is no carry-over of peptides from one sample to the other in this sequential process), except for the QC samples that were injected once. For each sample, approximately 0.5 mg of total protein digest was loaded using split-less nano-Ultra Performance Liquid Chromatography (10kpsi nanoAcquity; Waters). Buffers used were A: H2O þ 0.1% formic acid; B: acetonitrile þ 0.1% formic acid. Desalting of the samples was performed online with 100% buffer A for 3 min, Molecular Psychiatry


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using an online Reverse-Phase C18 trapping column (180 mm i.d., 20 mm length and 5 mm particle size) (Waters). The samples were separated using a C18 nanoColumn (75 mm i.d., 200 mm length and 1.7 mm particle size) (Waters), at 300 nl min1. Mass spectrometry The nanoLC was coupled online through a nanoESI emitter of 7 cm length and 10 mm tip (New Objective, Woburn, MA, USA) to a Quadrupole Time-of-Flight Mass Spectrometer (Qtof Premier; Waters). Data were acquired in MSE (Expression) mode. In this mode, the quadrupole is set to transfer all ions while the collision cell switches from low to high collision energy intermittently throughout the acquisition time. In the low-energy scans, collision energy was set to 4 eV, whereas in the high-energy scans, it was ramped from 20 to 43 eV. This mode enables accurate mass measurement of both intact peptides and fragments, and the conservation of the true chromatographic profile for both intact peptides and fragments. Mass accuracy was maintained throughout the analysis by the use of a LockSpray apparatus. A reference compound (Glu-Fibrinopeptide B; Sigma, USA) was continuously infused using the LockSpray and scanned intermittently every 30 s. During data processing, the analyte spectra were corrected based on the difference between the detected m/z peak and the theoretical m/z peak (785.8426 [m þ 2H] þ ) of Glu-Fibrinopeptide B. Data processing and time alignment Raw data, acquired in continuum format, were processed using the ProteinLynx Global Server software version 2.3 (also known as IdentityE) (Waters). Both quantitative and qualitative information were produced automatically by the software, using default parameters. Chromatograms were aligned in time and annotated using identified peptides and proteins from all injections. Protein identification Proteinlynx Global Server version 2.3 (IdentityE) was also used for database searches. The data were searched against the Human IPI version 3.34 (October 2007), appended with the sequence of Saccharomyces cerevisiae Enolase. The database search algorithm of the software was described by Li et al.11 and Vissers et al.12 Briefly, the software matches fragment ions with their corresponding precursor peptides based on (1) accurate mass measurement of both intact peptides (lowenergy channel) and fragmented peptides (highenergy channel) and (2) the retention time profile of both intact peptides and fragments. This enables high sampling of eluting peptides as well as a high rate of fragmentation, as there is no need for isolation of peptides using the quadrupole as is performed in traditional data-dependant analysis. All protein identifications were based on at least two peptides.

Molecular Psychiatry

Quantitative information Intensity measurements were obtained by integration of the total ion volume of each extracted, charge-statereduced, deisotoped and mass-corrected ion across the mass spectrometric and chromatographic volume (a three-dimensional version of extracted ion chromatogram method). In this type of acquisition, chromatographic profile is maintained reproducibly throughout the sample set; thus, it is possible to directly compare the intensities of precursor ions across all injections of all samples, following normalization based on the internal standard—digested Saccharomyces cerevisiae Enolase—that was added to each sample. The data set was then filtered using the free software package R (www.r-project.org) and only peptides that were detected in at least two out of three injections of each sample and at least 70% of the samples were included in the analysis. Those peptides that did not pass these filtering criteria were excluded from the analysis as the quantitative information they generate is of low confidence due to poor replication. The intensities of the correlating peptides of each identified protein were averaged to produce total protein intensity across all samples in which they were detected, as described by Schwarz et al.13 A two-tailed Student’s t-test was performed based on log-transformed protein intensities with a significance cutoff of P < 0.05. ELISA validation analysis Serum samples were randomized and the identity of all subjects was blinded by a code number until all biochemical analyses were completed. The samples used for enzyme-linked immunosorbent assay (ELISA) were selected to demographically match with the controls. They were partially independent, with an overlap of 25 samples between LC-MS/MS analysis and ELISA validation (Table 2). ApoA1, -A2, -A4 and a-2-HS glycoprotein (a-2HSG) standard (ApoA1: Sigma, St Louis, MO, USA; ApoA4: American Research Products Inc., Belmont, MA, USA; ApoA2 and a-2HSG: BIODESIGN, Kennebunk, ME, USA) alongside human serum samples from patients and control subjects were diluted 1:1000, 1:3000, 1:300 and 1:3000, respectively, with phosphate-buffered saline (Sigma). ApoA1, -A2, -A4, a-2HSG standard and samples were then loaded onto ELISA Maxisorb plates (Nunc, Roskilde, Denmark) and incubated for 60 min. After washing with washing buffer (0.03% Tween 20 in phosphate-buffered saline), the plates were blocked with 5% dried skimmed milk powder in phosphatebuffered saline for 60 min. A total of 100 ml primary antibody (apoA1: Calbiochem, San Diego, CA, USA; apoA2: Calbiochem; apoA4 and a-2HSG: Atlas Antibodies, Stockholm, Sweden) was incubated in 96well plates for 60 min. The plates were washed four times with wash buffer followed by the addition of 100 ml secondary antibody (apoA1, apoA2, apoA4 and


a-2HSG: Cell Signalling, Danvers, MA, USA; 1:1000) to each well and incubated for 60 min. Finally, after washing four times with wash buffer, 100 ml substrate (TMB One solution; Promega) was added to each well and incubated at room temperature for 10 min. The plates were read with a plate reader (Bio-Rad, Model 680) at 450 nm.

Results A total of 55 individual (non-pooled) clinical serum samples and 12 QC serum samples were compared in this study. These comprised 22 samples taken from first-onset drug-naive patients and 33 samples from demographically matched healthy volunteers. The samples were analysed using a label-free nanoLCMSE-based global proteomic profiling approach. In this study, 1411 proteins were identified according to the criteria outlined in Materials and methods section. These proteins were identified based on 3619 peptides. Among these, 217 proteins were identified Table 2 (a) Demographic detail of schizophrenia and control subjects for ELISA ApoA2, -A4 and a-2HSG; (b) demographic detail of schizophrenia and control subjects for ELISA ApoA1 Schizophrenia

Control

(a) Serum sample size Age (years) Gender (male/female)

n = 17 29.0±11.4 11/6

n = 20 17.10±5.1 13/7

(b) Serum sample size Age (years) Gender (male/female)

n = 35 28.0±8.8 21/14

n = 63 27.6±5.0 33/30

Abbreviations: a-2HSG, a-2-HS glycoprotein; enzyme-linked immunosorbent assay. Data are shown as average±s.d.

ELISA,

based on peptides detected in at least two out of three replicate injections and at least 70% of the samples in any one group. A detailed table showing the total number of detected proteins and peptides in each filtering stage is provided as Supplementary Information. To verify that none of the demographics altered the proteomic signature so as to bias the analysis, principal component analysis was performed based on all proteins detected based on peptides that passed the filtering criteria. The principal component analysis plots are provided as Supplementary Information. It can be seen that there is no clustering of samples based on any of the parameters listed above. This shows that the highest variation in the data was not due to any of the demographic parameters. Ten proteins showed a statistically significant reduction in expression in schizophrenia subjects compared with that in controls (P < 0.05) (see Table 3). It is worth noting that all significantly changed proteins were downregulated. To visualize the statistical significance of these proteins, the intensity distributions are displayed in Figure 1 as box plots. These were obtained by summing the measured intensity of the correlating peptides that passed the filtering criteria for each protein. The detected intensity is related to the abundance of the proteins in the samples, that is the more abundant the protein the higher its intensity. Owing to the similar P-values for changes in CD5L and Igm, we calculated the correlation between the two proteins and found a Pearson correlation coefficient of 0.97. This reflects the known biological interaction between the two proteins14 (Figure 2).

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Validation with ELISA To validate the findings from the proteomic profiling study, ELISAs were performed to quantitatively measure apolipoprotein A1, apolipoprotein A2, apolipoprotein A4 and a-2HSG. These assays were performed using crude serum without any preparation before measurement. The assays showed significantly

Table 3 A list of the most significant (P-value < 0.05) proteins found to be differentially expressed when comparing the control with the schizophrenia group Protein accession number

Name

O43866 P01871 P05160 P02787 P05090 P02647 P02765 P06727 P02652 P02654

CD5L Igm Coagulation factor XIII B Transferrin Apolipoprotein D Apolipoprotein A1 a-2-HS glycoprotein Apolipoprotein A4 Apolipoprotein A2 Apolipoprotein C1

Total number of peptides detected

T-test (P-value)

3 5 4 31 6 29 21 29 9 2

0.0014 0.0016 0.014 0.0199 0.0241 0.0302 0.0366 0.0412 0.0422 0.0444

Ratio disease/control 0.44 0.48 0.82 0.73 0.83 0.79 0.86 0.82 0.81 0.81

(2.28 down) (2.08 down) (1.22 down) (1.37 down) (1.2 down) (1.27 down) (1.16 down) (1.22 down) (1.23 down) (1.23 down)

Ratio of disease/control was determined based on the average of the correlating peptides of each protein, which also passed the filtering criteria listed in Materials and methods section. Molecular Psychiatry


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Alpha-2-HS-Glycoprotein p=0.0366

Box plots of the normalized intensity distributions for all 10 significantly changing proteins.

that it was possible to validate the results for apolipoproteins A1 and A2, which are depleted in the sample preparation for LC-MS/MS, shows the quantitative accuracy of the platform. An attempt was also made to develop an ELISA assay for apoD and CD5L; however, this was not successful due to the poor performance of antibodies for this protein.

5.5 5.0

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se D

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Igµ vs CD5L Pearson correlation = 0.97

4.5 4.0 3.5 3.0 2.0

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Figure 2 Correlation in measured abundance between CD5L and Igm, with a Pearson correlation of 0.97.

lower levels in sera of first-onset schizophrenia patients compared with those in controls (Figure 3) for the measured proteins. This result validates the findings of the discovery study. Furthermore, the fact Molecular Psychiatry

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Factor XIIIB p=0.014

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ApoA1 p=0.0302

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IgMu p=0.0016

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Molecular networks To explore the biological function of the significantly changing proteins, we applied Ingenuity Pathway Analysis (IPA) knowledge base (Ingenuity Systems, Redwood City, CA, USA, www.ingenuity.com). A data set containing the protein accession numbers and corresponding expression values was uploaded into the application. Each protein identifier was converted to its gene identification and mapped to its corresponding gene object in the IPA knowledge base. These genes, called focus genes, were overlaid onto a global molecular network developed from information contained in the IPA knowledge base, which is based entirely on findings reported in the literature. Networks of these focus genes were then algorithmically generated based on their connectivity.


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and the total number of molecules in IPA knowledge base that could potentially be included in networks. The network score is based on the hypergeometric distribution and is calculated with the right-tailed Fisher’s exact test. The score is the negative log of this P-value. The significantly changing proteins and other proteins linked to them are not part of one biological pathway, which can be expected as they are secreted proteins. However, they take part in several biological functions such as lipid metabolism, small-molecule biochemistry, molecular transport, cardiovascular disease, metabolic disease and nutritional disease. It can be seen that apolipoproteins A1, A2, C1 and A4 are key nodes in the network. Apart from CD5L and IgM, there is a direct link between each of the molecules, which may indicate an interaction between them.

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Figure 3 Downregulation of the levels of serum apolipoproteins A1, A2, A4 and a-2-HS glycoprotein (a-2HSG) in first-onset drug-naive schizophrenia patients. (a) Enzymelinked immunosorbent assay (ELISA) analysis of apoA1 levels in sera of first-onset drug-naive schizophrenia patients (n = 35) and healthy controls (n = 63). The mean value±s.d. of apoA1 concentrations in schizophrenia patients and controls is shown. P = 0.0039 (two-tailed t-test). (b–d) ELISA analysis of apoA4, -A2 and a-2HSG levels in sera of first-onset drug-naive schizophrenia patients, respectively, (n = 17) and healthy controls (n = 20). The mean value±s.d. of apoA2 and -A4 concentrations in schizophrenia patients and controls is shown. P = 0.05 (apoA2) (two-tailed t-test), P = 0.016 (apoA4) (twotailed t-test) and P = 0.004 (a-2HSG).

This platform enables researchers to visualize the potential interactions between the molecules of interest and others, which may not have been detected in a particular study. Using the IPA, we were able to determine that 9 of the 10 proteins identified in the schizophrenia cohort can be mapped onto a specific molecular network15–143 (see Figure 4), with a score of 25. Genes or gene products are represented as nodes, and the biological relationship between two nodes is represented as an edge (line). All edges are supported by at least one reference from the literature, from a textbook or from canonical information stored in the IPA knowledge base. Human, mouse and rat orthologues of a gene are stored as separate objects in the IPA knowledge base, but are represented as a single node in the network. The network score is a numerical value used to rank networks according to their degree of relevance to the Network Eligible molecules in the data set. The score takes into account the number of Network Eligible molecules in the network and its size, as well as the total number of Network Eligible molecules analysed

Discussion A global proteomic profiling study was performed in search for novel protein disease biomarkers for schizophrenia. A total of 55 clinical serum samples along with 12 QC samples were analysed. The importance of using samples from drug-naive patients cannot be overestimated. One of the most challenging issues in biomarker discovery is the ability to find markers that represent the disease state. Much of the published results regarding molecular alterations in schizophrenia patients have been obtained using samples taken from patients who have undergone treatment at some stage of their lives. As the mechanisms of action of antipsychotic medication are not fully understood, one cannot be sure that the changes found are disease related and not drug related or a consequence of chronic impairment. Among the proteins detected, 10 were found to be statistically significant. Validation assays were performed for four of these proteins and all were found to be significant, with abundance ratios (so called fold changes) similar to the LC-MS/MS data. Interestingly, all proteins were found to be downregulated in the schizophrenia population. This could have been due to an experimental artefact; however, the findings are supported by the ELISA validation in crude serum and by previously reported findings. Furthermore, we have previously shown data collected from the QC and clinical samples analysed in this study (reported in Levin et al.10), which show the integrity of the method in general and this study specifically. Apolipoproteins Five of the most significantly changed proteins (apoA1, apoA2, apoA4, apoC1 and apoD) belong to the apolipoprotein superfamily. All apolipoproteins were significantly decreased in the serum of schizophrenia patients. ApoA1, ApoA2, ApoA4 and ApoD are constituents of the high-density lipoprotein fraction, which regulate plasma levels of free fatty acids, and are known to have an important role in the Molecular Psychiatry


1094 APOF

Tcf 1/3/4

HDL-cholestrol

Apoa 1/2

APOD

GPLD 1 LCAT

CETP APOA2

CRB1

ABCA7

AHSG

24(S),25-epoxycholesterol

APOA4 PLTP

cholesterol

APOA 1 EXOC6 C20ORF121

LIPC KIAA1409 APOC 1

ABCA6

CD5L

1,2-dipalmitoylphosphatidylcholine

IGKC TF C1QC

TBC1D19

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IGL@

Relationships

Chemical or Drug

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Transcription Regulator Translation Regulator

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acts on

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Growth Factor

IGHM

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B

Transmembrane Receptor Transporter Other

direct interaction indirect interaction Notes: “Acts on” and “inhibits” edges may also include a binding event.

Figure 4 Molecular network showing possible connections and interactions between molecules, based on IPA knowledge base. The proteins filled in grey colour are the ones detected in this study.

metabolism of high-density lipoprotein and triglyceride-rich lipoproteins and in the reverse cholesterol transport pathway.144 Apolipoproteins have previously been found altered in schizophrenia and other brain disorders. Recently, we reported decreased ApoA1 in both brain and peripheral tissue in schizophrenia patients;144 this implies that some schizophrenia-associated changes detected in the central nervous system are reflected in peripheral tissues. Previously, we also reported upregulation of apoL mRNA levels in schizophrenia145 and others have identified changes in apoD and apoE levels in schizophrenia post-mortem brain.146 Interestingly, Molecular Psychiatry

Thomas et al.147 also reported increased levels of apolipoprotein D in the central nervous system and a decrease in serum of schizophrenia patients, which could imply a compensatory role of apoD for a neuropathological process that is initiated by systemic lipid metabolism insufficiencies. Jiang et al.148 found apolipoprotein A-IV to be downregulated in cerebrospinal fluid of schizophrenia patients. Furthermore, clozapine treatment of rats has been found to alter apoD gene expression. In addition, changes in apoA1, apoE and other apolipoproteins have been found in various types of dementia.149 Evidence of mitochondrial dysfunction


and increased oxidative stress has also been noted in both schizophrenia and Alzheimer’s disease.150,151 Although the function of apolipoproteins in the central nervous system is less clear, they are likely to have an important role in neuronal and glial metabolism and may be involved in the predisposition and pathophysiology of Alzheimer’s disease and other dementias.152 The finding that apolipoprotein levels are altered in the schizophrenia population may reflect their pathophysiological role in schizophrenia. However, further investigations are required. Immune response The most significantly changed proteins were Igm and CD5L, which are both part of the immune system. Igm is the heavy chain of IgM, which is the major component of the natural antibodies. During an immune response, it is the first class of antibody produced, primarily by B1 cells.153 IgM molecules can bind to antigens or pathogens even in the case where the host has never been exposed to it153 and are part of the ‘innate’ immune system.154 Several studies have been conducted in the past, searching for a link between schizophrenia and serum immunoglobulins. The reported results of these studies draw an inconclusive picture with regard to the link between the two,as some studies found an increase in IgM and other immunoglobulins and others report a decrease in IgM levels. Legros et al.155 found elevated levels of IgM in the serum taken from 95 schizophrenia patients who were drug free for 8 weeks, compared with those in the 150 controls. It can be hypothesized that the effect of antipsychotics on the immune system is longer lasting than 8 weeks, which would explain the high level of IgM even after 8 weeks without treatment. Sane et al.156 also report significantly higher levels of IgM in patients suffering from psychiatric disorders; however, those levels were similar to that in other patients hospitalized in the same hospital preoperatively. Chong-Thim et al.157 also report elevated levels of IgM in schizophrenia serum, without mentioning whether the patients were drug treated or not. DeLisi158 found no reduction of IgM levels in chronic schizophrenia patients who were drug free for only 3 weeks. IgM is a nonspecific marker of change in the immune system as its levels can change under many different circumstances.154 This can explain inconsistent reports of IgM levels in the serum of schizophrenia patients. Nevertheless, as part of a panel of biomarkers for schizophrenia, it may have an important role in distinguishing diseased from healthy people. The other significantly changing protein that is part of the immune system is CD5L (also known as SP-a). There is little functional information available for CD5L;159 however, it has been suggested that it may have a major role in regulation of the innate and adaptive immune systems.159 Gebe et al.160 found RNA transcripts encoding CD5L in human bone

marrow, spleen, lymph node, thymus and foetal liver but not in non-lymphoid tissues. This evidence supports the hypothesis that CD5L has a role in the immune system as well as in the interaction with IgM.14 Tissot et al.14 also report that CD5L is associated with IgM; however, the interaction between the two proteins is not clear. This report is supported by our finding of high correlation between the two proteins. Two of the significant proteins identified were transferrin and a-2HSG. Stefan et al.161 reported that a-2HSG is associated with insulin resistance and fat accumulation in the liver in humans, which may link it with the alteration in apolipoproteins found in this study. Until now, however, there has been no published data correlating schizophrenia and a2HSG. Transferrin is an 80-kDa protein that binds Fe(III) very tightly, but reversibly. Hakak et al.162 report a decrease in mRNA levels for transferrin in the post-mortem prefrontal cortex of schizophrenia patients. This is in agreement with our finding of lower transferrin levels in serum compared with that in controls. It has been suggested that transferrin levels in plasma are decreased during inflammation and it is hence deemed one of the ‘negative acute-phase’ proteins.163 As transferrin was found to be downregulated in this study, it may strengthen the link between inflammation and schizophrenia. In conclusion, we found that the schizophreniaassociated disease process leaves a distinct molecular signature in peripheral tissues that can be measured using standard biochemical methods. However, to develop an accurate diagnostic test more research needs to be carried out on the lower abundance fractions of the serum proteome.

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Conflict of interest The authors declare no conflict of interest.

Acknowledgments The research was kindly funded by the Stanley Medical Research Institute and by Psynova Neurotech Ltd. We would like to express our appreciation to Paul Guest and Hassan Rahmoune for their input and assistance.

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Supplementary Information accompanies the paper on the Molecular Psychiatry website (http://www.nature.com/mp)
