Ó 2012 John Wiley & Sons A/S
Acta Neurol Scand 2012: 126 (Suppl. 195): 90–96 DOI: 10.1111/ane.12029
ACTA NEUROLOGICA SCANDINAVICA
Cerebrospinal fluid proteome comparison between multiple sclerosis patients and controls Kroksveen AC, Guldbrandsen A, Vedeler C, Myhr KM, Opsahl JA, Berven FS. Cerebrospinal fluid proteome comparison between multiple sclerosis patients and controls. Acta Neurol Scand: 2012: 126 (Suppl. 195): 90–96. © 2012 John Wiley & Sons A/S.
A. C. Kroksveen1,2, A. Guldbrandsen1,2, C. Vedeler1,3, K. M. Myhr1,3, J. A. Opsahl2, F. S. Berven2,1,3
Objectives – The aim of the present study was to identify proteins in cerebrospinal fluid (CSF) with different abundance between patients with relapsing-remitting multiple sclerosis (RRMS) and controls. Such proteins may be diagnostic biomarkers and contribute with novel information about the disease pathogenesis. Materials and methods – Cerebrospinal fluid from patients with RRMS (n = 17) and controls (n = 17) were trypsin digested and analyzed in a label-free fashion using liquid chromatography mass spectrometry. The resulting data were analyzed using SearchGUI, PeptideShaker, and the Progenesis software. Results – Two hundred and ninety-one proteins were identified, of which 32 were significantly differentially abundant between the patients with RRMS and controls (P-value 0.05, two or more peptides quantified). Among these were proteins which previously have been linked to MS, including immunoglobulin subunits, vitamin D-binding protein, apolipoprotein D, kallikrein-6, neuronal pentraxin receptor, Dickkopf-related protein 3, and contactin-1. Conclusion – The study provides an overview of differentially abundant proteins between RRMS and controls, and a few of these are further discussed. It should be stressed that a larger verification study is needed to reveal the potential value of these proteins as biomarkers for RRMS and their involvement in the disease pathogenesis.
1 The KG Jebsen Centre for MS-research, Department of Clinical Medicine, University of Bergen, Bergen, Norway; 2Proteomics Unit (PROBE), Department of Biomedicine, University of Bergen, Bergen, Norway; 3 Norwegian Multiple Sclerosis Competence Centre, Department of Neurology, Haukeland University Hospital, Bergen, Norway
Introduction
Multiple sclerosis (MS) is a chronic, inflammatory disease of the central nervous system (CNS), characterized by demyelination and axonal loss, and is the leading nontraumatic cause of nervous system disability in young adults (1, 2). The diagnosis is currently based on evaluation of the disease history and neurological examination, supported by magnetic resonance imaging (MRI) and cerebrospinal fluid (CSF) analysis (3). Irreversible axonal damage may occur before the first clinical symptoms (4), but novel biomarkers enabling early diagnosis could allow for earlier treatment, which could slow 90
Key words: multiple sclerosis; cerebrospinal fluid; biomarkers; proteomics; label-free quantitative mass spectrometry; IgG; vitamin D-binding protein A. C. Kroksveen, Proteomics Unit (PROBE), Department of Biomedicine, University of Bergen, Bergen, Norway Tel.: +4755586378 Fax: +4755586360 e-mail:
[email protected] Accepted for publication September 3, 2012
down the disease processes leading to irreversible damage (2, 5, 6). Several proteomic studies have been published presenting biomarker candidates for MS (7–10), where different MS subgroups have been compared with various control categories. These studies have shown a great variety of biomarker candidates, probably due to both the variation in the proteomics approaches and the great diversity of the MS disease. In the current study, we aimed to compare the high- to medium-abundant CSF proteome of patients with MS initially diagnosed with relapsing-remitting multiple sclerosis (RRMS) (n = 17) to controls with other neurological diseases (OND) (n = 17) to discover
CSF proteome comparison between MS and controls differentially abundant proteins using label-free proteomics.
The plate was centrifuged at 200 9 g for 1 min at each step, with 150 9 g for 3 min during the loading step.
Materials and methods LTQ-FT analysis Patient selection
Cerebrospinal fluid was collected from patients undergoing lumbar puncture as part of their diagnostic workup at the Department of Neurology, Haukeland university hospital, Bergen, Norway. The samples comprised CSF from 17 patients initially diagnosed with RRMS and 17 controls with OND. All patients with RRMS were diagnosed according to the revised criteria of McDonald (11). Typical MRI lesions were exclusively found in the patients with MS but not in the controls. The summarized clinical and demographic characteristics of patients and controls are shown in Table 1, and information about the individual patients and controls are in Table S1. The CSF samples were collected and stored according to the guidelines from the BioMSeu consortium (12). The study was approved by The Regional Committee for Medical Research Ethics of Western Norway. Written informed consent was obtained from all patients and controls. Sample preparation
Cerebrospinal fluid (10 lg) was individually digested using trypsin (Promega, Madison, WI, US) as enzyme and desalted using Oasis HLB lElution plates (Waters, Milford, MA, US). The protocol for digestion is described in detail elsewhere (13). For desalting, each well in the plate was conditioned with 80% ACN/0.1% FA, and equilibrated three times with 0.1% FA. The entire volume of sample was loaded, followed by three washes with 0.1% FA. The peptides were eluted in two steps using 80% ACN/0.1% FA. Table 1 Summarized clinical and demographic characteristics for patients with RRMS and OND controls
Number of patients/controls Male/female ratio Age (years) at LP CSF protein concentration (g/L) CSF albumin concentration (g/L) CSF IgG concentration (g/L) % Positive for OCB
RRMS
OND
17 2/15 40.6 (13.2) 0.4878 (0.1125) 0.2235 (0.0959) 0.06 (0.03) 86.7
17 7/10 58.5 (11.1) 0.6074 (0.1596) 0.3224 (0.1261) 0.0329 (0.0092) 5.9
CSF, cerebrospinal fluid; LP, lumbar puncture; OCB, oligoclonal bands; RRMS, relapsing-remitting multiple sclerosis; OND, other neurological diseases. Age, protein concentration, albumin concentration and IgG concentration are given as mean. Standard deviations are in brackets.
LC-MS/MS analyses were carried out as previously described (14) using an Agilent nanoflow HPLC system (Agilent, Palo Alto, CA, USA) directly interfaced to an LTQ-FT mass spectrometer (Thermo Fisher, Waltham, MA, USA) equipped with a custom nano-electrospray ionization source. Analyses were of 90 min total duration. The mass spectrometer was set to do 1 full FTMS scan at 100,000 resolution in profile mode followed by three data-dependent MS/MS scans at low-resolution in centroid mode in the LTQ on the top three most abundant peptide precursor ions. Data and statistical analysis
The data were analyzed with the Progenesis LCMS software (Nonlinear dynamics, UK) for label-free quantification using default settings. The protein intensity (abundance) was calculated based on the sum of the intensities of the peptides uniquely representing the protein. The peptide intensity is the sum of the peak areas within the isotope boundaries found from the mass spectrometry scan. Features with positive charge between 2 and 7 were extracted using 200 ion count and searched (SwissProt human database) and identified using SearchGui (http://www.uib. no/rg/probe/publications/software/searchgui) and PeptideShaker (http://www.uib.no/rg/probe/ publications/software/peptideshaker). Precursor mass tolerance was 10 ppm and product mass tolerance 0.5 Da. Two missed cleavages were allowed. Carbamidometylation was set as fixed modification and oxidation of methionine as variable. For a protein to be considered as significantly differentially abundant it had to be identified and quantified with two or more peptides and with the Student’s t-test P-value 0.05. Results
We identified 291 unique proteins of which 77 proteins were quantified with two or more peptides (Table S2). The data were analyzed as described in the method section, and 32 of the quantified proteins were found with significant abundance difference (P-value 0.05) between patients with RRMS and OND controls. Of the 32 significantly differentially abundant proteins, five immunoglobulin (Ig) variants were 91
Kroksveen et al. found as significantly increased in the patients with RRMS compared with the OND controls, and all Ig variants except Ig kappa chain V-III region VG had a P-value < 0.01 (Table 2). Scatter plots of these Ig variants are shown in Fig. 1. Only Ig gamma-1 chain C region (IgG1) of the Ig variants could be assigned to a specific immunoglobulin class, but the abundance profile of the other variants did correspond well to the pattern of IgG1 for the different patients and controls, as illustrated in Fig. 2 for IgG1 and Ig kappa chain C region (R2 = 0.931). The abundance of the various immunoglobulin variants also correlated to the total CSF IgG measured in routine practice (results not shown). Ig kappa chain C showed the
Table 2 Proteins with significant abundance difference between patients with RRMS (n = 17) and OND controls (n = 17)
Protein name Alpha-1B-glycoprotein Alpha-2-HS-glycoprotein Alpha-2-macroglobulin Amyloid beta A4 protein Antithrombin-III Apolipoprotein D Apolipoprotein A-I Apolipoprotein A-II Apolipoprotein A-IV Beta-2-glycoprotein 1 Beta-Ala-His dipeptidase Ceruloplasmin Clusterin Complement C3 Complement factor B Contactin-1 Cystatin-C Dickkopf-related protein 3 Gelsolin Ig gamma-1 chain C region Ig heavy chain V-III region BRO Ig kappa chain C region Ig kappa chain V-III region VG Ig kappa chain V-IV region Len Kallikrein-6 Major prion protein Monocyte differentiation antigen CD14 Neuronal pentraxin receptor Retinol-binding protein 4 Serotransferrin Serum albumin Vitamin D-binding protein
Fold change RRMSa
t-test P-value
Accession number
Abundance RRMS
P04217 P02765 P01023 P05067 P01008 P05090 P02647 P02652 P06727 P02749 Q96KN2 P00450 P10909 P01024 P00751 Q12860 P01034 Q9UBP4 P06396 P01857 P01766
↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↑ ↑
1.45 1.29 1.41 1.56 1.41 1.44 1.44 1.71 1.89 1.50 1.57 1.29 1.36 1.39 1.60 1.40 1.43 1.50 1.37 2.08 2.06
0.00808 0.02886 0.00763 0.01999 0.00799 0.00159 0.01353 0.02802 0.00053 0.01807 0.01194 0.04578 0.02479 0.02102 0.01374 0.04332 0.02278 0.02247 0.00853 0.00064 0.00501
P01834 P04433
↑ ↑
1.64 2.92
0.00257 0.01507
P01625
↑
1.70
0.00892
Q92876 P04156 P08571
↓ ↓ ↓
1.57 1.64 1.28
0.00206 0.01507 0.02845
O95502
↓
1.46
0.01405
P02753 P02787 P02768 P02774
↓ ↓ ↓ ↓
1.43 1.44 1.39 1.42
0.01979 0.00082 0.00711 0.00256
RRMS, Relapsing-remitting multiple sclerosis; OND, Other neurological diseases. a Negative fold change value indicates reduced abundance in RRMS compared with OND. Positive fold change value indicates increased abundance in RRMS compared with OND.
92
best correlation to total CSF IgG (R2 = 0.976) and the lowest correlation (R2 = 0.726) was found for Ig heavy chain V-III region BRO. Significantly reduced abundance was found for 27 proteins in the patients with RRMS (Table 2). Among these were proteins that could be related to various CNS functions and MS pathology including neuronal pentraxin receptor (NPR), apolipoprotein D (apo D), vitamin D-binding protein (VDB), kallikrein-6, Dickkopf-related protein 3 (Dkk-3), amyloid beta A4 protein (amyloid precursor protein, APP), major prion protein (PrP), and contactin-1. The abundance distributions of these aforementioned proteins are plotted in Fig. 3. Apo D, kallikrein-6, and VDB all had a P-value < 0.01. In addition, several high-abundant plasma proteins (e.g., serum albumin, serotransferrin, and complement C3) were observed with significantly lower abundance in the patients with RRMS compared with OND controls (Table 2). Discussion
We used a label-free semi-quantitative proteomics approach to compare the high- to medium-abundant CSF proteome of patients with RRMS to controls with OND. The majority of proteins were found to be less abundant in the patients with RRMS with the exception of various Ig variants. We found significantly increased abundance of IgG1 in the patients with RRMS compared with the OND controls, which is expected as a consequence of the reported increased intrathecal synthesis of IgG in patients with MS (15). Results from ELISA have shown significantly elevated CSF IgG1 levels in patients with RRMS compared with OND controls, with no significant differences for the other IgG subclasses (IgG2-4) (16), which is in accordance with our results (results not shown). The study from Di Pauli et al. (16) also argued that the elevated levels of IgG1 is a cause of increased intrathecal IgG1 synthesis. For the various Ig variants, there were certain RRMS patients with a distinct higher intensity of the given protein compared with all the controls (Fig. 1). These patients with RRMS did also have the highest total CSF IgG (data not shown). However, there was an overlap between the IgG1 levels for the majority of patients with RRMS and OND controls. This indicates that the effect of the intrathecal synthesis of IgG (oligoclonal bands for 15 of the patients with RRMS and only one OND control) is not always reflected in the CSF levels of IgG1 in such a way that these patients can be distin-
CSF proteome comparison between MS and controls VDB (24). In this study, we found a significant down regulation of VDB in patients with RRMS compared with OND controls, which is in accordance with two other proteomics studies (25, 26). It has been suggested that low levels of VDB causes an up-regulated inflammatory reaction (26). It should be noted, however, that there are contradicting results on the CSF levels of VDB in patients with MS which may be due to various CSF sample collection time, analysis methods, and disease heterogeneity. Despite the lack of consistency, growing evidence indicates that both
Intensity IgG1
x10 7 2.5
x10 7
2.0
2.0
1.5
1.5
1.0
1.0
0.5
0.5
0
RRMS
x10 7
6.0
Ig kappa chain C region
x10 5
2.0
2.0
1.0 0.5
0.5 0
x10 7
1.5
4.0
Intensity
Intensity
Intensity
1.0
0
Figure 2. Correlation between IgG1 and Ig kappa chain C region. Line plot illustrating the correlation between the intensity of IgG1 (Ig gamma-1 chain C region) (black dots) and Ig kappa chain C region (gray squares) for all included relapsing-remitting multiple sclerosis patients and controls.
2.0 1.5
OND
Ig heavy chain V-III region BRO
Ig gamma-1 chain C region 2.5
2.5
Intensity Ig kappa chain C region
guished from those without intrathecal IgG synthesis. Four of the Ig variants found as differentially abundant in our study could not be assigned to a specific Ig class as they were identified as part of the constant kappa chain, the variable kappa chain, and the variable heavy chain. Significantly decreased abundance was found for 27 proteins in the patients with RRMS compared with the OND controls (Table 2), and many of these proteins have previously been reported as biomarker candidates for MS [reviewed in (10)]. Identification of decreased abundance of VDB was particularly interesting as low levels of vitamin D have been associated with increased risk of developing MS (17–19). The majority of vitamin D in the circulation is bound to VDB in its biological inactive but stable form (25-OH-D) (20), where VDB transports vitamin D to target organs. There are four forms of VDB and the genetic variance in the VDB gene is associated with varying vitamin D levels (21). Independently to its carrier function, VDB also has anti-inflammatory and immune-modulatory functions (22), which add a new level to its disease involvement. Structurally, VDB is closely related to albumin (23) and is like albumin predominantly synthesized in the liver. VDB is found in healthy CSF with a limited passage through an intact blood-brain-barrier (BBB), and a restricted passage has been shown for vitamin D bound to
RRMS
OND
0
RRMS
RRMS
OND
Ig kappa chain V-IV region Len
Ig kappa chain V-III region VG 1.5
0
OND
x10 6
5.0
x10 5
Intensity
Intensity
4.0
1.0
0.5
3.0 2.0 1.0
0
RRMS
OND
0
RRMS
OND
Figure 1. Proteins with significantly increased abundance in patients with relapsing-remitting multiple sclerosis (RRMS). Vertical scatter plots showing the intensity (abundance) of the proteins with higher abundance for the patients with RRMS compared with controls with other neurological diseases (OND) (P-value 0.05) as measured by label-free mass spectrometry. The horizontal line represents the median intensity for each group.
93
Kroksveen et al. Amyloid beta A4 protein x10 6
1.0
2.0
0.8
1.5
1.5
0.6
1.0
Intensity
2.0
1.0
RRMS
0
OND
RRMS
Kallikrein-6
RRMS
6
1.0
0.5
0
OND
RRMS
Neuronal pentraxin receptor
Major prion protein 6.0 x10
5
5
1.0 x10
OND
Vitamin D-binding protein 3.0 x10
6
5
0.8
4.0 2.0
4.0
2.0
0.6
Intensity
Intensity
6.0
0
0.4
0
OND
Intensity
8.0 x10
1.5 x10
0.2
0.5
0
Dickkopf-related protein 3
x10 5
Intensity
2.5
0.5
Intensity
Contactin-1
Apolipoprotein D
5
Intensity
Intensity
2.5 x10
0.4
2.0
1.0
0.2
RRMS
OND
0
RRMS
OND
0
RRMS
OND
0
RRMS
OND
Figure 3. Proteins with significantly decreased abundance in patients with relapsing-remitting multiple sclerosis (RRMS). Vertical scatter plots showing the intensity (abundance) of a selection of proteins with lower abundance for the patients with RRMS compared with the controls with other neurological diseases (OND) (P-value 0.05) as measured by label-free mass spectrometry. The horizontal line represents the median intensity for each group is shown.
vitamin D and VDB are involved in the development of MS [reviewed in (27, 28)]. Our study also report decreased abundance of apo D in patients with RRMS compared with OND controls (Table 2). Apo D is widely expressed throughout the body [reviewed in (29)], including the CNS, and is involved in cholesterol transport, neuroprotection, myelination, and synaptogenesis (30–32). In the CNS, it has been suggested that neurons that do not express apo D is more prone for neurodegeneration (33) and absence of apo D in peripheral nerves has been proposed to cause decreased clearance of myelin after nerve injury, resulting in delayed axonal regeneration and remyelination (34). In MS, increased intrathecal synthesis of apo D has been reported (35) and increased levels of apo D have been found in patients with RRMS and primaryprogressive MS (PPMS) compared with healthy controls (7), which is the opposite to the lower abundance of apo D observed in our study when patients with RRMS were compared with OND controls. This dissimilarity could be explained by the two different control groups that are used, or the disease state of the included patients with RRMS. Based on this, the abundance change and role for apo D needs to be further investigated in relation to MS. Neuronal pentraxin receptor and contactin-1 may also have value as biomarker candidates as their abundance is significantly reduced in patients with RRMS compared with OND controls in our study. The scatter plot for NPR in Fig. 3 shows that 11 of 17 patients with RRMS have lower abundance than all but one of the 94
controls, indicating a stable low abundance of NPR in the majority of the patients with RRMS. The NPR is expressed in the CNS, primarily in neurons and glia (36), and associate with the AMPA receptor to enhance the synaptogenesis (37). Our finding of reduced NPR abundance in patients with RRMS could reflect loss of neurons and synaptic contacts. Contactin-1 was significantly reduced in abundance in the patients with RRMS. This neuronal cell adhesion molecule may be important for remyelination through its interaction with the Notch receptor (38, 39). The Notch receptor has been suggested as a potential therapeutic target in MS (40). Typical plasma proteins, for example, serum albumin and serotransferrin, were among the proteins that were significantly less abundant in the patients with RRMS (Table 2). However, these proteins are more likely to appear as differentially abundant due to differences in influx of plasma proteins across the BBB. It has been speculated that the influx of plasma proteins into the CSF is higher in patients with MS due to increased permeability of the BBB in these patients. Our results do, however, show a decrease of plasma proteins in the MS group. None of the proteins with significant abundance difference (Table 2) gave a clear separation between all the patients with RRMS and OND controls (See Figs 1 and 3 for a selection of the proteins). A separation was, however, observed for a subgroup of patients against OND for all of the Ig variants that were more abundant in the patients with RRMS (Fig. 1). Hence, our results point toward the need for the proteins presented
CSF proteome comparison between MS and controls as differently abundant in this study to be part of a panel of several biomarkers to have any potential diagnostic value for the analyzed groups. A larger verification study is needed to evaluate their potential as diagnostic biomarkers.
8.
9.
Acknowledgments The study was supported by the Kristian Gerhard Jebsen Foundation, the National Program for Research in Functional Genomics (FUGE) funded by the Research Council of Norway, Western Norway Regional Healthy Authority, the Leiv Eiriksson Mobility Program, and the Meltzer Foundation.
Conflicts of interest
10.
11.
12.
The authors report no conflicts of interest. 13.
Supporting Information Additional Supporting Information may be found in the online version of this article. Table S1. Contains all data for the patients with relapsing-remitting multiple sclerosis and OND controls. The information include sample identification-number (Sample ID), gender, age at lumbar puncture, diagnosis, CSF albumin concentration, CSF IgG concentration, CSF protein concentration, and information about oligoclonal bands (OCB). Table S2. Contains the Progenesis output for all quantified proteins (quantified by 2 peptides) in sheet 1 and for all the differentially abundant proteins in sheet 2. The differentially abundant proteins had to be identified and quantified by 2 peptides and have a t-test P-value 0.05. Please note: Wiley-Blackwell are not responsible for the content or functionality of any supporting materials supplied by the authors. Any queries (other than missing material) should be directed to the corresponding author for the article.
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