Gene expression profiling in chronic inflammatory demyelinating polyneuropathy

Gene expression profiling in chronic inflammatory demyelinating polyneuropathy

Journal of Neuroimmunology 159 (2005) 203 – 214 www.elsevier.com/locate/jneuroim Gene expression profiling in chronic inflammatory demyelinating poly...

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Journal of Neuroimmunology 159 (2005) 203 – 214 www.elsevier.com/locate/jneuroim

Gene expression profiling in chronic inflammatory demyelinating polyneuropathy Susanne Renauda,*, Arthur P. Haysb, Thomas H. Brannagan IIIa, Howard W. Sandera, Mark Edgarc, Louis H. Weimerd, Marcelo R. Olarted, Marinos C. Dalakase, Zhaoying Xiangf, Moris J. Danong, Norman Latova a

Department of Neurology and Neurosciences, Weill Medical College, Cornell University, New York, NY, USA b Department of Pathology, Columbia University, New York, NY, USA c Department of Pathology, Weill Medical College, Cornell University, New York, USA d Department of Neurology, Columbia University, New York, NY, USA e Neuromuscular Disease Section, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA f Microarray Core Facility, Weill Medical College, Cornell University, New York, NY, USA g Department of Neurology, University of Minnesota, Minneapolis, MN, USA Received 8 October 2004; accepted 11 October 2004

Abstract Gene expression in archived frozen sural nerve biopsies of patients with chronic inflammatory demyelinating polyneuropathy (CIDP) was compared to that in vasculitic nerve biopsies (VAS) and to normal nerve (NN) by DNA microarray technology. Hierarchical clustering analysis demonstrated distinct gene expression patterns distinguishing these disease groups. Of particular interest were: (1) Tachykinin precursor 1, which may be involved in pain mediation; (2) Stearoyl-CoA-desaturase, which may be a marker for remyelination and (3) the Allograft Inflammatory Factor 1 (AIF-1), a modulator of immune response during macrophage activation. Differential gene expression may help distinguish between CIDP, VAS and NN in sural nerve biopsies and identify genes that may be involved in disease pathogenesis. D 2004 Elsevier B.V. All rights reserved. Keywords: CIDP; Vasculitic neuropathy; Nerve biopsy; Microarray; SCD; TAC1; AIF-1

1. Introduction DNA microarray analysis is a powerful tool for simultaneous analysis and comparison of gene products expressed in normal and diseased tissues (Duggan et al., 1999; Lockhart et al., 1996; McGall et al., 1996). Chronic inflammatory demyelinating polyradiculoneuropathy (CIDP) is an immune-mediated disease that targets the peripheral nerves and causes progressive weakness and sensory loss. The diagnosis of CIDP is typically based on * Corresponding author. Current address: Department of Neurology, University Hospital Basel, Petersgraben 4, CH-4031 Basel, Switzerland. Tel.: +41 61 2654151; fax: +41 61 2654100. E-mail address: [email protected] (S. Renaud). 0165-5728/$ - see front matter D 2004 Elsevier B.V. All rights reserved. doi:10.1016/j.jneuroim.2004.10.021

the clinical presentation, absence of other causes of the neuropathic syndrome and results of electrodiagnostic or pathologic studies (Dyck et al., 1975; Latov, 2002; Berger et al., 2003; Ad Hoc Subcommittee of the AAN, 1991). Presence of increased cerebrospinal fluid (CSF) protein and demyelinating changes on nerve biopsy are supportive of the diagnosis, but these are not always present (Barohn et al., 1989; Bouchard et al., 1999). Since there is no marker for this disease, many patients remain undiagnosed. We have undertaken gene expression analysis to identify differentially expressed genes in nerve biopsy samples of CIDP patients, which might serve as markers for the disease or participate in pathogenesis. Results in CIDP nerves were compared to those in normal nerves (NN) or nerves affected by vasculitis, as controls.

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2. Materials and methods 2.1. Patients Nerve biopsies from eight patients with CIDP were included in the study. The diagnosis was based on clinical, pathological and electrophysiological criteria (Berger et al., 2003). The characteristics of the CIDP patients and nerve biopsies are listed in Table 1. In addition, nerve biopsies of three patients with vasculitis representing an inflammatory nondemyelinating pathology were included. As normal controls, biopsy specimens were obtained from three individuals who did not suffer from polyneuropathy but from myopathy, muscular dystrophy and dermatomyositis, respectively. 2.2. RNA sample processing Human sural nerve biopsies were immediately embedded in the embedding medium Tissue-Tek (Sakura Finetek, USA) and stored at 70 8C. The embedded tissue, with each tissue sample weighing ca. 50 mg, was cut with a cryostat (Leitz, Cryostat) in 10-Am sections. Further tissue homogenization was obtained with an electric rotor stator tissue homogenizer (Polytron, Kinematica, Switzerland). For total RNA extraction, we used

TRIzol reagent (Invitrogen, Carlsbad, CA), according to the manufacturers protocol, followed by Rneasy clean-up (Qiagen, Chatsworth, CA), a procedure giving a yield of 1 Ag per 100 mg of biopsy tissue. RNA yields were measured by UV absorbance and RNA quality was assessed by agarose gel electrophoresis with SYBRR Gold nucleic acid stain (Molecular Probes, Eugene, OR), for visualization of ribosomal RNA band integrity. 2.3. cRNA amplification In general, the standard RNA processing and hybridization protocols as recommended by Affymetrix (Santa Clara, CA) were followed in this study; these protocols are available in the GenechipR Expression Analysis Technical Manual. Yields of total RNA for sural nerve biopsy samples were generally low and for the majority of patients it was not possible to use the standard amount of total RNA (N5 Ag) as recommended in the standard protocol. Therefore, a double linear amplification approach (Eberwine et al., 1992) was used in the generation of cRNA for hybridization. In these experiments, equal amounts of starting material were used from each patient. One hundred nanograms of total RNA was converted into biotin-labeled cRNA (complementary RNA) using the Gene Chip Eukaryotic Small Sample Target Labeling Assay Version II (Technical Notes No. 701265

Table 1 CIDP patient data Patient

Age (years)

Sex

Biopsy time after onset

M/S

Course

CSF

EMG

Pathology

1

49

F

72 months

SNM

RR

n.a.

Sensorimotor demyelinating

2

54

M

Several years

SNM

Progressive

n.d.

Absent SNAPs, normal motor nerve conduction and myography

3

20

M

20 months

SNM

Progressive

2 cells, 85%lymphocytes TP 30mg/dl

Absent SNAPs, normal motor nerve conduction

4

47

M

22 months

SNM

RR

TP 52mg/dl

Sensorimotor, mixed axonal and demyelinating neuropathy

5

70

F

48 months

SNM

RR

n.d.

Normal

6

39

F

5 years

S=M

RR

TP elevated

Sensorimotor demyelinating

7 8

45 33

M F

9 months 2 years

S=M S=M

RR RR

TP 50 mg/dl n.a.

Sensorimotor demyelinating Sensorimotor demyelinating with partial conduction block

Segmental demyelination and remyelination no infiltrates Muscle: mild neurogenic abnormalities Severe loss of large-diameter myelinated fibers, segmental remyelination, no infiltrates Muscle: mild neurogenic abnormalities Loss of mainly large myelinated fibers, thinning of myelin lamellae, perinodal demyelination, no infiltrates Muscle: reinnervation Mild loss of myelinated fibers, signs of segmental remyelination no infiltrates Muscle: mild neurogenic abnormalities Segmental Demyelination Muscle: mild neurogenic abnormalities Apparent myelin loss and interstitial fibrosis, mild inflammation No pathology No pathology

S=sensory symptoms, M=motor symptoms, RR=relapsing remitting, n.a.=not available, n.d.=not done, SNAP=sensory nerve action potential, TP=total protein.

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Rev. 2, Affymetrix). Double-stranded cDNA was created by using the Super Script Double-Stranded cDNA Synthesis Kit (Invitrogen) using the T7-(dT) 24-primer [sequence 5VGGCCAGTGAATTGTAATACGACTCACTATAGGGAGGCGG-(dT)24-3V] (Affymetrix). The cDNA was purified by ethanol precipitation and then used for in vitro transcription using the Ambion MEGAscript T7 Kit (Ambion, Houston, TX). The cRNA was then cleaned using the Qiagen Rneasy Mini Kit (Qiagen). In a second cycle, the cRNA obtained in the first cycle was used as a template to create double-stranded cDNA using random primers and the Super Script Double-Stranded cDNA Synthesis Kit (Invitrogen). This second round of cDNA synthesis was similar to the first round except that random hexamers were used in priming of first-strand synthesis, with T7-(dT)24 oligomer priming the second strand. The cDNA was cleaned by ethanol precipitation and then used for in vitro transcription using the ENZO BioArray RNA transcript labeling kit (Affymetrix). Biotin-labeled cRNA was purified by Rneasy Kit (Qiagen) and chemically fragmented randomly to approximately 200 bp (200 mM Tris–acetate, pH 8.2, 500 mM KOAc, 150 mM MgOAc) according to the Affymetrix protocol. 2.4. Expression profiling Each fragmented cRNA sample was hybridized to the Affymetrix Human U133 A microarrays set for 16 h at 60 rpm at 45 8C. The microarray was washed and stained on the Affymetrix Fluidics Station using instructions and reagents provided by Affymetrix. This involved removal of nonhybridized material and then incubation with phycoerythrin–streptavidin to detect bound cRNA. The signal intensity was amplified by second staining with biotinlabeled antistreptavidin antibody followed by phycoerythrin–streptavidin staining. Fluorescent images were read using the Hewlett-Packard G2500A Gene Array Scanner. The microarrays were processed on the fluidics station under the control of the Microarray Suite software and read. 2.5. Data analysis Affymetrix GeneChip 5.0 was used as the image acquisition software for the U133 chips. The signal, which represents the intensity of each gene, was extracted from the image. The target intensity value from each chip was scaled to 250. Data normalization, log transformation, filtering of genes that were not detected in any of the samples, statistical analysis and pattern study were performed by GeneSpringk v 6.1 software (Silicon Genetics, Redwood City, CA). Array data were globally normalized by using GeneSpring software. Firstly, all of the measurements on each chip were divided by the 50th percentile value (per-chip normalization). Secondly, each gene was normalized to the median value of the samples (per-gene normalization). Statistical comparison between the different disease types and normal controls was performed using the Welch

205

t-test with log transformed data. The cutoff for p-value was set at 0.05. A two-way hierarchical clustering by distance measure was used to group genes that were differentially expressed between the different disease groups and normal controls. 2.6. Real time quantitative reverse transcription polymerase chain reaction (RT-PCR) Real Time quantitative RT-PCR was used to verify the microarray results. Since the yield of total RNA was very low, we used the amplified biotinylated cRNA as starting material. cRNA samples (1.0 Ag) were reverse transcribed to yield first-strand cDNA using the Applied Biosystems Reverse Transcription Reagents protocol (Applied Biosystems, Foster City, CA, USA). The reverse transcription reactions were then diluted 1:10 in distilled H2O. Taqman assay PCR reactions (Perkin-Elmer-Applied Biosystems) were performed in 96-well optical plates and run in an ABI PRISMR 7700 Sequence Detection System machine. We used the Assay-on-Demandk Gene Expression Products (Applied Biosystems). For individual reactions, 2.5 Al of each sample was combined with 12.5 Al of 2 Taqman Universal Master Mix, 1.25 Al of Target Assay Mix and 8.75 Al H2O. Data were extracted and amplification plots generated with ABI SDS software. All amplifications were done in triplicate and threshold cycle (C t) scores were averaged for subsequent calculations of relative expression values. The C t scores represent the cycle number at which fluorescence signal crosses an arbitrary (user-defined) threshold. The C t scores for genes of interest for each sample were normalized against C t scores for the corresponding endogenous control gene, which was GAPDH. Relative expression for disease versus normal controls was determinded by the following calculation, as described in the Applied Biosystems users bulletin on relative Quantitation of Gene Expression and as published (Schmittgen et al., 2000): Relative Expression ¼ 2DDCt where DDC t=(C t diseaseC t GAPDH)(C t normalC t GAPDH). For each disease group, the mean of relative expression for each sample was calculated.

3. Results 3.1. Sample and chip quality The yield of RNA varied from 100 ng to 2.9 Ag per sample. The integrity of the RNA as seen by SYBR-GoldR staining after gel electrophoresis was intact and the ratio A260/280 as measure of the RNA purity on UV absorbance ranged for most of the samples from 1.79 to 2.06. Only 2 out of 14 samples had a lower A260/280 ratio which is

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Table 2 CHIP quality Patients

Disease

Present calls (%)

3V/5V ratio GAPDH

1 2 3 4 5 6 7

CIDP CIDP CIDP CIDP CIDP CIDP CIDP

60 56.2 51.3 50 57.3 55.5 51.9

2.19 2.26 2.21 3.95 3.0 1.84 3.27

8

CIDP

52.6

6.8

9 10 11 12 13 14

NN NN NN VAS VAS VAS

55.40 42.3 52.8 55.3 30.5 57.9

2.37 3.28 1.97 1.72 6.58 1.6

3V/5Vratio beta-actin (3V/ M) ratio 7.05 7.43 18.35 19.63 7.91 13.13 29.03 (4.6) 28.02 (6.7) 10.66 3.24 9.52 6.02 17.73 7.47

The Chip Quality was good with present calls between 30.5% and 60%. The 3V/5V ratio of specific maintenance genes (GAPDH/beta-actin) is a measure for RNA degradation and efficiency of transcription reaction. The 3V/M ratio may even be a more realistic representation of the reliability of the data, since most of the probe sets on the Affymetrix Chip are located on the 3V end. Overall, we obtained good sample quality for our amplified cRNA.

probably due to the older age of the biopsy samples. The Chip quality was good with present calls between 30.5% and 60%. We also looked at the probe sets of specific maintenance genes (GAPDH, beta-actin) that are designed to the 3V, middle and 5V regions of the transcript and compared the 3V probe set signal intensity to the 5V probe set signal intensity (3V/5V ratio) as a measure for RNA degradation and efficiency of transcription reaction. The 3V/5V ratio for beta-actin was in most samples below 20 and only in the same 2 out of the 14 samples higher with 29.03 and 28.02, respectively. We also calculated the 3V/Middle probe set ratio (3V/M) of the beta-actin gene because the M probes lie approximately 430–770 bases from the most 3V end and may be a more realistic representation of reliability

Fig. 1. Up-regulation of IL7, TAC, SCD and CD69, and down-regulation of DCXR gene expression genes in CIDP versus normal nerve biopsy samples (NN) were confirmed by RT real-time PCR. A good correlation between fold changes and relative quantities was observed for all genes analyzed.

Fig. 2. Up-regulation of IL7, PTX3, CD69 and HAMP, and downregulation of CRYAB in vasculitic nerve (VAS) compared to NN were confirmed by RT real-time PCR. A good correlation between fold changes and relative quantities was observed for all genes analyzed.

of the array data for those two samples. The resulting 3V/M ratios for the beta-actin gene were with 4.6 and 6.7 acceptable and therefore we decided to use those two samples (Table 2). 3.2. Quantitative RT-PCR validation of differentially expressed genes A subset of 8 transcripts was chosen for validation by quantitative RT-PCR analysis. The genes IL7 (Interleukin 7), TAC1 (Tachykinin 1), Stearoyl CoA Desaturase (SCD), CD69, Dicarbonyl-l-Xylulose Reductase (DCXR) Pentraxin 3 (PTXR), Hepcidine (HAMP) and Crystallin alpha B (CRYAB) were chosen based on potential functions of encoded proteins (i.e., remyelination in the case of Stearoyl CoA Desaturase or early B- and T-cell development in the case of Interleukin 7), or because of the extent of differential regulation between the different nerve biopsy groups. Taqman RT-PCR was used to validate the microarray expression profiling data. The qRT-PCR validation was

Fig. 3. Hierarchical cluster of differentially expressed genes (DEG) in CIDP compared to NN. Red represents up-regulation of gene expression in disease. Blue represents down-regulation of gene expression in disease.

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Table 3 Up-regulated genes in CIDP compared to NN Gene description

Common name

Apoptosis NCK-associated protein 1

NAP1, KIAA0587

Cancer Inducer of promyelocytic leukemia RAB2, member RAS oncogene family Yamaguchi sarcoma viral related oncogene homolog V-yes-1 Yamaguchi sarcoma viral related oncogene homolog Cell communication Placental growth factor, vascular endothelial growth factor-related protein Lectin, galactoside-binding, soluble, 2 (galectin 2) Bone morphogenetic protein Solute carrier family 16 (monocarboxylic acid transporters), member 7 Hepatocyte growth factor (hepapoietin A; scatter factor) Solute carrier family 21 (organic anion transporter), member 9 Integrin, beta 2 (antigen CD18 (p95) Cell cycle regulator HSPC002 protein. S-phase 2 protein Enzyme/metabolism Stearoyl-CoA desaturase (delta-9-desaturase) Stearoyl-CoA desaturase (delta-9-desaturase) NAD(P)H dehydrogenase, quinone 1 TATA box binding protein (TBP)-associated factor, RNA polymerase I, C Tissue factor pathway inhibitor Type 1 tumor necrosis factor receptor shedding aminopeptidase regulator Pro-collagen-lysine, 2-oxoglutarate 5-deoxygenase 2(lysine hydroxylase) N-acylsphingosine amidohydrolase (acid ceramidase)-like Protein tyrosine phosphatase, receptor type, C Prostaglandin D2 synthase, hematopoietic NAD(P)H dehydrogenase, quinone 1 Mannosidase alpha class 1A, member 1 Myosin VA (heavy polypeptide 12, myoxin) Extracellular cell component Macrophage receptor with collagenous structure Asporin (LRR class 1) Pro-collagen-lysine, 2-oxoglutarate 5-deoxygenase 2 (lysine hydroxylase) Collagen, type XI, alpha 1 Spondin 2, extracellular matrix protein Intracellular cell component Nuclear receptor subfamily 1, group D, member 1 NAD(P)H dehydrogenase, quinone 1 Polyadenylate binding protein-interacting protein 1 SAM domain, SH3 domain and nuclear localisation signals, 1 NAD(P)H dehydrogenase, quinone 1 Myosin VA (heavy polypeptide 12, myoxin) Lymphocyte cytosolic protein 2

Fold change

Affymetrix

GenBank

2.566

207738_s_at

NM_013436

MYL, TRIM19 RAB2 LYN JTK8

4.615 2.697 2.463 2.357

211012_s_at 208733_at 202625_at 202626_s_at

BC000080 NM_002865 AI356412 NM_002350

PLGF

3.237

209652_s_at

BC001422

LGALS2 BMP2 MCT2

2.726 2.430 2.416

208450_at 205289_at 207057_at

NM_006498 AA583044 NM_004731

HPTA

2.160

210997_at

M77227

OATPB, OATP-B

2.132

203473_at

NM_007256

LAD, CD18

2.037

202803_s_at

NM_000211

HSPC002

2.130

219260_s_at

NM_015362

SCD SCD NQO1 TAF1C

16.039 4.660 3.417 2.447

211162_x_at 200831_s_at 201468_s_at 203937_s_at

AF116616 AA678241 NM_000903 AW015313

TFPI ARTS-1

2.435 2.428

210665_at 214012_at

AF021834 BE551138

PLOD2

2.327

202619_s_at

AI754404

ASAHL

2.270

214765_s_at

AK024677

PTPRC PGDS DIA4, NMOR1 MAN1A1 MYO5A

2.184 2.150 2.116 2.048 2.040

212588_at 206726_at 210519_s_at 221760_at 204527_at

AI809341 NM_014485 BC000906 BG287153 NM_000259

13.879 2.370 2.327

205819_at 219087_at 202619_s_at

NM_006770 NM_017680 AI754404

STL2, COLL6 DIL1, DIL-1

2.236 2.056

204320_at 218638_s_at

NM_001854 NM_012445

EAR1, hRev NQO1 PAIP1 SAMSN1

5.039 3.417 3.170 2.647

204760_s_at 201468_s_at 209064_x_at 220330_s_at

NM_021724 NM_000903 AL136920 NM_022136

DIA4, NMOR1, NMORI MYO5A LCP2

2.116 2.040 2.003

210519_s_at 204527_at 205269_at

BC000906 NM_000259 AI123251

MARCO PLAP1, FLJ20129 PLOD2

(continued on next page)

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Table 3 (continued) Gene description Immunity Interleukin 1 receptor, type II Allograft inflammatory factor 1 Proteoglycan 2, bone marrow (natural killer cell activator) FYN-binding protein (FYB-120/130) Major histocompatibility complex, class II, DQ beta 1 HLA class II histocompatibility antigen, DQ (W1.1), beta chain (human) Macrophage scavenger receptor 1 Campath-1 antigen Allograft inflammatory factor 1 CD69 antigen (p60, early T-cell activation antigen) Homo sapiens CXCR4 gene encoding receptor CXCR4 T-cell receptor beta locus CD44 antigen FYN-binding protein (FYB-120/130) Interleukin 18 receptor accessory protein Cytokine receptor-like factor 1 Toll-like receptor 7 Coagulation factor III (thromboplastin, tissue factor) Major histocompatibility complex, class II, DR beta 5 Complement component 1, q subcomponent, alpha polypeptide Lymphocyte antigen 75 Leukotriene b4 receptor (chemokine receptor-like 1) Fc fragment of IgG, high affinity Ia, receptor for (CD64) T-cell receptor delta locus Integrin, beta 2 (antigen CD18 (p95)) Toll-like receptor 2 Epstein–Barr virus induced gene 2 Lymphocyte cytosolic protein 2 Membrane Macrophage scavenger receptor 1 Nucleic acid binding Nuclear receptor subfamily 1, group D, member 1 Polyadenylate binding protein-interacting protein 1 RE1-silencing transcription factor CCAAT/enhancer binding protein (C/EBP), alpha Zinc finger protein 80 (pT17) TATA box binding protein (TBP)-associated factor, RNA polymerase I, C RNA-binding protein gene with multiple splicing High-mobility group (nonhistone chromosomal) protein isoforms I and Y MADS box transcription enhancer factor 2, polypeptide A Transcription factor AP-2 gamma Poly(A)-binding protein, cytoplasmic 3 Basic helix–loop–helix domain containing, class B, 3 MADS box transcription enhancer factor 2, polypeptide A Eukaryotic translation initiation factor 1A Signal transduction Tachykinin, precursor 1 LIM protein Placental growth factor, vascular endothelial growth factor-related protein CD69 antigen (p60, early T-cell activation antigen) SAM domain, SH3 domain and nuclear localisation signals, 1

Common name

Fold change

Affymetrix

GenBank

IL1RB IBA1, IRT-1 MBP, BMPG FYB IDDM1, HLA-DQB HLA-DQB1

4.353 4.307 4.263 4.158 4.038 3.955

211372_s_at 209901_x_at 211743_s_at 211794_at 209823_x_at 212998_x_at

U64094 U19713 BC005929 AF198052 M17955 AI583173

MSR1 CDW52 AIF1 CD69 CXCR4 TRB@ CD44 FYB ACPL CLF-1 TLR7 TF, TFA, CD142 HLA-DRB5 C1QA

3.945 3.718 3.147 2.997 2.831 2.765 2.638 2.545 2.489 2.461 2.403 2.317 2.284 2.244

214770_at 34210_at 213095_x_at 209795_at 217028_at 211796_s_at 212063_at 211795_s_at 207072_at 206315_at 220146_at 204363_at 215193_x_at 218232_at

AI299239 N90866 AF299327 L07555 AJ224869 AF043179 BE903880 AF198052 NM_003853 NM_004750 NM_016562 NM_001993 AJ297586 NM_015991

DEC-205, GP200-MR6 BLTR, P2Y FCGR1A

2.241 2.222 2.111

205668_at 210128_s_at 216950_s_at

NM_002349 U41070 X14355

TRD, TCRD LAD, CD18 TLR2 EBI2 LCP2

2.059 2.037 2.033 2.004 2.003

217143_s_at 202803_s_at 204924_at 205419_at 205269_at

X06557 NM_000211 NM_003264 NM_004951 AI123251

MSR1

3.945

214770_at

AI299239

EAR1, hRe PAIP1 REST CEBP ZNF80 TAF1C

5.039 3.170 2.903 2.608 2.543 2.447

204760_s_at 209064_x_at 204535_s_at 204039_at 207272_at 203937_s_at

NM_021724 AL136920 AI978576 NM_004364 NM_007136 AW015313

HERMES HMGIY

2.401 2.365

207836_s_at 206074_s_at

NM_006867 NM_002131

RSRFC4, RSRFC9

2.238

208328_s_at

NM_005587

TFAP2C PABPC3 DEC2, SHARP1 MEF2A

2.233 2.205 2.145 2.043

205286_at 208113_x_at 221530_s_at 214684_at

U85658 NM_030979 AB044088 X63381

EIF1A

2.041

201017_at

BE542684

NK2 LIM PLGF

27.83 3.429 3.237

206552_s_at 216804_s_at 209652_s_at

NM_003182 AK027217 BC001422

2.997 2.647

209795_at 220330_s_at

L07555 NM_022136

CD69 SAMSN1

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Table 3 (continued) Gene description

Common name

G-protein-coupled receptor; Human CB1 cannabinoid receptor (CNR1) gene Yamaguchi sarcoma viral related oncogene homolog MAD (mothers against decapentaplegic, Drosophila) homolog 7 Tissue factor pathway inhibitor Bone morphogenetic protein V-yes-1 Yamaguchi sarcoma viral related oncogene homolog G-protein-coupled receptor 56 Coagulation factor III (thromboplastin, tissue factor) Prostaglandin E receptor 4 (subtype EP4) ADP ribosylation factor 6 Protein tyrosine phosphatase, receptor type, C Hepatocyte growth factor (hepapoietin A; scatter factor) Docking protein 2 CDC42-binding protein kinase beta (DMPK-like) Notch (Drosophila) homolog 3 Taste receptor, type 2, member 10 Integrin, beta 2 (antigen CD18 (p95) Milk fat globule-EGF factor 8 protein Epstein–Barr virus induced gene 2 Lymphocyte cytosolic protein 2

CNR1

Fold change

Affymetrix

GenBank

2.620

213436_at

U73304

LYN MADH8, SMAD7

2.463 2.437

202625_at 204790_at

AI356412 NM_005904

TFPI BMP2 JTK8

2.435 2.430 2.357

210665_at 205289_at 202626_s_at

AF021834 AA583044 NM_002350

GPR56 TF, TFA, CD142 EP4 ARF6 PTPRC HPTA

2.346 2.317 2.291 2.288 2.184 2.160

212070_at 204363_at 204897_at 214182_at 212588_at 210997_at

AL554008 NM_001993 NM_000958 AA243143 AI809341 M77227

DOK2 MRCKB, KIAA1124 NOTCH3 TRB2, T2R10 LAD, CD18 MFGE8 EBI2 LCP2

2.082 2.079 2.039 2.039 2.037 2.016 2.004 2.003

214054_at 217849_s_at 203238_s_at 221397_at 202803_s_at 210605_s_at 205419_at 205269_at

AI828929 NM_006035 NM_000435 NM_023921 NM_000211 BC003610 NM_004951 AI123251

Storage Milk fat globule-EGF factor 8 protein

MFGE8

2.016

210605_s_at

BC003610

Structural protein Macrophage receptor with collagenous structure Asporin (LRR class 1) Neurofilament 3 (150kD medium) Collagen, type XI, alpha 1 Spondin 2, extracellular matrix protein

MARCO PLAP1, FLJ20129 NFM, NEFM, NF-M STL2, COLL6 DIL1, DIL-1

13.874 2.370 2.306 2.236 2.056

205819_at 219087_at 205113_at 204320_at 218638_s_at

NM_006770 NM_017680 NM_005382 NM_001854 NM_012445

Transport Sortilin-related receptor, L(DLR class) A repeats-containing Chloride intracellular channel 2 Solute carrier family 16(monocarboxzlic acid transporters), member 7 Solute carrier family 21 (organic anion transporter), member 9

SORL1

2.810

212560_at

AV728268

CLIC2 MCT2

2.444 2.416

213415_at 207057_at

AI768628 NM_004731

OATPB, OATP-B

2.132

203473_at

NM_007256

Bold = either present in 4 out of 8 CIDP samples for up-regulated genes or in 2 out of 3 NN samples for down-regulated genes.

performed with the amplified biotin-labeled cRNA from 7 CIDP, 3 NN and 3 VAS biopsies. Data for each gene was normalized to expression of a housekeeping gene, GAPDH. Comparison of RT-PCR and microarray data showed an excellent qualitative agreement (i.e., same trend of induction; Figs. 1 and 2). 3.3. Differentially regulated genes 3.3.1. CIDP versus normal appearing nerve Hierarchical clustering analysis demonstrated distinct gene expression patterns distinguishing CIDP from NN, CIDP from VAS and VAS from NN (Fig. 3). In the disease group CIDP versus normal controls, 123 genes were differ-

entially regulated with 101 genes up-regulated and 22 genes down-regulated (greater than twofold change and pb0.05). When we considered only the genes that were present in at least 4 out of 8 CIDP samples for the up-regulated genes and in at least 2 out of 3 control samples for the down-regulated genes, 87 genes were differentially regulated. We have listed in Tables 3 and 4 the differentially regulated genes according to their presumed gene ontology. A majority of the differentially expressed genes were involved in signal transduction, metabolism and immunity or inflammation. 3.3.2. Up-regulated genes in VAS versus NN In VAS versus NN, 244 genes were differentially regulated. One hundred sixty-three genes were up-regulated

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Table 4 Down-regulated genes in CIDP compared to NN Gene description

Common name

Fold change

Affymetrix

GenBank

Cancer Chromogranin A (parathyroid secretory protein 1) Neurofibromin 2 (bilateral acoustic neuroma)

CGA, CgA NF2

0.497 0.211

204697_s_at 211092_s_at

NM_001275 AF122827

Cell communication Autocrine motility factor receptor

GP78

0.477

202203_s_at

NM_001144

Chaperone DnaJ (Hsp40) homolog, subfamily B, member 4

HLJ1, DNAJW

0.387

203811_s_at

NM_007034

Enzyme/metabolism DKFZP586B1621 protein Dicarbonyl/L-xylulose reductase DNA sequence from clone RP11-169017 Beta-1,3-glucuronyltransferase 1 (glucuronosyltransferase P) Calcium/calmodulin-dependent protein kinase (CaM kinase) II beta Cytochrome P450, subfamily IIJ (arachidonic acid epoxygenase) polypeptide 2

DKFZP586B1621 DCXR PH5P, p193 HNK-1, GLCATP, GLCAT-P CAMKB CPJ2

0.483 0.468 0.440 0.370 0.285 0.252

218688_at 217973_at 216822_x_at 219521_at 211483_x_at 205073_at

NM_015533 NM_016286 AL359763 NM_018644 AF081924 NM_000775

Intracellular cell component Cytokine-like nuclear factor n-pac DNA sequence from clone RP11-169017 Cytochrome P450, subfamily IIJ (arachidonic acid epoxygenase) polypeptide 2

N-PAC PH5P, p193 CPJ2

0.496 0.440 0.252

222115_x_at 216822_x_at 205073_at

BC003693 AL359763 NM_000775

Nucleic Acid Binding Sirtuin (silent mating type information regulation 2, S.cerevisiae, homolog) 3 Hypothetical protein FLJ22347

SIR2L3

0.489

221562_s_at

AF083108

FLJ21850, FLJ22267

0.429

218965_s_at

NM_022830

Signal transduction Autocrine motility factor receptor Mitogen activated protein kinase GABA(A) receptors associated protein like 3 Ganglioside-induced differentiation-associated protein 1-like Calcium/calmodulin-dependent protein kinase (CaM kinase) II beta Purinergic receptor P2Y, G-protein coupled, 2

GP78 MAPK4 GABARAPL3 GDAP1LP CAMKB P2U, HP2U, P2Y2

0.477 0.451 0.396 0.389 0.285 0.155

202203_s_at 204707_s_at 211457_at 219668_at 211483_x_at 206277_at

NM_001144 BF115223 AF180519 NM_024034 AF081924 NM_002564

Bold=genes present in at least 2 out of 3 NN samples.

and 81 genes were down-regulated. Again, most genes were involved in signal transduction (26%) in immunity (22.9%) and 20% were enzymes. A list of the genes with putative function in the immune system is given in Table 5.

test with log transformed data; p b 0.05, fold change 2.0, genes present in at least one sample).

4. Discussion 3.3.3. Up-regulated genes in CIDP and VAS Twenty-four genes were overexpressed in both CIDP and VAS compared to NN, most of which are involved in immunity and inflammation. These included the early T-cell activation gene CD69, the allograft inflammatory factor (AIF-1) that is up-regulated in vascular damage and CD44, which has a postulated role in matrix adhesion and lymphocyte activation (Table 5). 3.3.4. Up-regulated genes in CIDP versus VAS and NN Three genes, Stearoyl CoA desaturase (SCD), NADPH dehydrogenase, quinone 1 (NQO1) and eukaryotic translation initiation factor 1A (EIF1A) were significantly upregulated in CIDP in comparison to NN or VAS (Welch t-

Microarray-based analysis of human sural nerve biopsies showed distinct gene expression patterns in CIDP versus NN, CIDP versus VAS and VAS versus NN. The technique is feasible, although small amounts of RNA have to be amplified. The differentially expressed genes are mostly involved in immunity and signal transduction. In the following, we highlight genes that seem to us to be of special interest in CIDP and VAS. 4.1. Stearoyl CoA desaturase Stearoyl CoA desaturae (SCD) is up-regulated in CIDP versus normal nerve and in CIDP versus vasculitis. It is a

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211

Table 5 Differentially regulated genes (DEGs) with putative function in immunity in vasculitc nerve (VAS) compared to normal nerve (NN) Gene description

Common name

Fold change

Affymetrzix

GenBank

Heparanase Allograft inflammatory factor 1 Campath-1 antigen Allograft inflammatory factor 1 Allograft inflammatory factor 1 Major histocompatilbility complex, class II, DR beta 3 Fc fragment of IgG, high affinity Ia, receptor for (CD64) Complement component 3a receptor 1 Lymphocyte antigen 96 Immunoglobulin superfamily, member 6 CD69 antigen (p60, early T-cell activation antigen) CD163 antigen Cytokine-like protein C17 Monokine induced by gamma interferon Fc fragment of IgG, high affinity Ia, receptor for (CD64) Pentaxin-related gene, rapidly induced by IL-1 beta Interleukin 7 B-lymphocyte activator macrophage expressed T-cell receptor gamma locus Ectonucleoside triphosphate diphosphohydrolase 1 Cathepsin S Chemokine (C–C motif) receptor 1 Homo sapiens IgH VH gene for immunoglobulin heavy chain, partial cds. Chemokine (C–C motif) ligand 3, Small inducible cytokine A3 (homologous to mouse Mip-1a) CD53 antigen Ectonucleoside triphosphate diphosphohydrolase 1 Lymphocyte cytosolic protein 2 Cytochrome b-245, beta polypeptide Neutrophil cytosolic factor 2 (65kD, chronic granulomatous disease, autosomal 2) Lymphocyte antigen 86 Fc fragment of IgE, high affinity I, receptor for; gamma polypeptide Arachidonate-5 lipooxygenase Proteoglycan 2, bone marrow (natural killer cell activator, eosinophil granule major basic protein) CD86 antigen (CD28 antigen ligand 2, B7-2 antigen)

HPA, HSE1 IBA1, IRT-1 CDW52 AIF1 AIF1 HLA-DRB3 FCGR1A AZ3B, C3AR, HNFAG09 LY96 DORA CD69 M130, MM130 C17 CMK, SCYB9 FCGR1A PTX3 IL7 SBBI42, BLAME TRG@ CD39, NTPDase-1 CTSS CCR1 IgH VH

11.941 10.862 8.957 8.445 8.219 8.197 8.019 7.815 7.512 7.302 7.029 6.909 6.598 6.528 6.510 5.848 5.613 5.399 5.246 5.023 4.921 4.580 4.536

219403_s_at 209901_x_at 34210_at 215051_x_at 213095_x_at 221491_x_at 214511_x_at 209906_at 206584_at 206420_at 209795_at 215049_x_at 219837_s_at 203915_at 216950_s_at 206157_at 206693_at 219386_s_at 209813_x_at 209474_s_at 202901_x_at 205098_at 216510_x_at

NM_006665 U19713 N90866 BF213829 AF299327 AA807056 L03419 U62027 NM_015364 NM_005849 L07555 Z22969 NM_018659 NM_002416 X14355 NM_002852 NM_000880 NM_020125 M16768 U87967 BC002642 AI421071 AB035175

Hepcidin antimicrobial peptide CD2 antigen (p50), sheep red blood cell receptor CD84 antigen (leukocyte antigen) Sialoadhesin Interleukin 8 CD163 antigen CD86 antigen (CD28 antigen ligand 2, B7-2 antigen) Leukocyte immunoglobulin-like receptor, subfamily A (with TM domain), member 2 Chemokine (C–C motif) receptor-like 2 Chemokine (C–C motif) ligand 4, Small inducible cytokine A4 (homologous to mouse Mip-1b) CD44 antigen Leukocyte immunoglobulin-like receptor, subfamily B (with TM and ITIM domains), member 4 T-cell receptor gamma constant 2 Syndecan 1 Pre-B-cell colony-enhancing factor CD28 antigen (Tp44)

LD78ALPHA, MIP-1-alpha, CCL3 CD53 CD39, NTPDase-1 LCP2 CYBB NCF2

4.099

205114_s_at

NM_002983

3.741 3.706 3.589 3.570 3.555

203416_at 207691_x_at 205269_at 203922_s_at 209949_at

NM_000560 NM_001776 AI123251 AI308863 BC001606

LY86 FCER1G

3.474 3.413

205859_at 204232_at

NM_004271 NM_004106

ALOX5 MBP, BMPG

3.282 3.101

214366_s_at 211743_s_at*

AA995910 BC005929

B70, B7-2, LAB72, CD28LG2 HEPC, LEAP1, LEAP-1 SRBC CD84 SN IL8 M130, MM130 CD86 ILT1, LIR7, LIR-7

3.085

210895_s_at

L25259

3.013 2.978 2.972 2.882 2.812 2.801 2.767 2.724

220491_at 205831_at 205988_at 44673_at 202859_x_at 216233_at 205685_at 211100_x_at

NM_021175 NM_001767 NM_003874 N53555 NM_000584 Z22970 BG236280 U82278

2.652

211434_s_at

AF015524

2.639

204103_at

NM_002984

2.619 2.483

212063_at 210152_at

BE903880 U82979

2.463

215806_x_at

M13231

2.461 2.365 2.268

201287_s_at 217739_s_at 206545_at

NM_002997 NM_005746 NM_006139

HCR, CKRX, CRAM-A, CRAM-B CCL4, ACT2, LAG1, Act-2, AT744.1, MIP-1-BETA CD44 HM18, ILT3, LIR5, LIR-5 TCRGC2, TRGC2(2X), TRGC2(3X) SDC PBEF CD28

(continued on next page)

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Table 5 (continued) Gene description

Common name

Major histocompatibility complex, class I-like sequence IL2-inducible T-cell kinase Lymphocyte antigen 75 Squamous cell carcinoma antigen recognized by T cells 2 Interleukin 8 receptor, beta

MR1 EMT, LYK, PSCTK2 DEC-205, GP200-MR6 SART-2 CXCR2, IL8RA, CMKAR2 CD24A

CD24 antigen (small cell lung carcinoma cluster 4 antigen)

Fold change

Affymetrzix

GenBank

2.150 2.146 2.063 2.031 0.271

207565_s_at 211339_s_at 205668_at 218854_at 207008_at

NM_001531 D13720 NM_002349 NM_013352 NM_001557

0.255

208651_x_at

M58664

Bold = for up-regulated genes present in 2 out of 3 VAS samples, for down-regulated genes present in 2 out of 3 NN samples.

rate-limiting enzyme in the biosynthesis of monunsaturated fatty acids that are present in myelin and a target in leptin signaling (Miyazaki and Ntambi, 2003; Zhang et al., 1999; Cohen et al., 2002). It regulates the synthesis of oleic acid, a major fatty acid in PNS myelin, and in the rat, the SCD mRNA declines during wallerian degeneration and rises again as regenerating axons recontact Schwann cells. This enzyme might have a role in the remyelination process and neonatal myelin development (Garbay et al., 1998). 4.2. NQO1 NAD (P) H: Quinone Oxidoreductase 1 is a ubiquitous cytosolic flavoenzyme that catalyzes the two-electron reduction of various quinones, preventing their participation in redox cycling and subsequent generation of reactive oxygen species. It also has the ability to directly scavenge superoxide (Siegel et al., 2004). It is up-regulated in CIDP versus NN and in CIDP versus VAS, but also in VAS vs NN. This enzyme has been implicated in cancer prevention (Huggins and Fukunishi, 1964). X-radiation and UV radiation, which are known to generate free radicals, are some of the most potent inducers of NQO1 expression in human cells (Boothman et al., 1993; Agrawal et al., 2001). NQO1 physically associates with the tumor suppressor protein p53 in human tumor cells and primary cultures (Anwar et al., 2003). p53 is a powerful transcription factor that up-regulates a number of proteins involved in protection against oxidant stress (Polyak et al., 1997). The role of NQO1 in neuroprotection is seen controversially. It is up-regulated in primary cultures of embryonic cerebellum and cerebral cortex in response to ageing and glutamate treatment (Page and Morton, 1995) and in senile plaques, neurofibirllary tangles and in hippocampal pyramidal neurons of patients with Alzheimer’s disease (Raina et al., 1999; Wang et al., 2000) and in the ischemic penumbra after focal cerebral ischaemia in the rat (Laxton et al., 2001). Therefore, it has been discussed to be neuroprotective. However, in primary cultures of rat cortex, inhibition of NQO1 activity protected neuronal cells from cell death (Kapinya et al., 2003). NQO1 is probably upregulated in our diseased nerve biopsy samples as reaction to some form of oxidative stress, but is probably not specific for CIDP. It remains to be elucidated whether it participates to or whether it protects from tissue damage.

4.3. EIF1A The eukaryotic initiation factor 1 A (EIF1A) is upregulated in CIDP versus NN and in CIDP versus VAS. EIF1A is implicated in the translation initiation pathway, where it enhances ribosome dissociation into subunits and stabilizes the binding of the initiatior Met-tRNA to 40S ribosomal subunits (Marintchev et al., 2003). Increased expression of EIF1A has been shown in doxorubicinresistant K562 human leukemia cells, but whether its upregulation is implicated in drug resistance is unclear (Ichikawa et al., 2004). In yeast and plants, EIF1A is an important determinant in the tolerance to NaCl stress (Rausell et al., 2003). EIF1A has so far not been implicated in neurological diseases. Whether EIF1A is up-regulated in CIDP as answer to a specific stress to the translation initiation pathway is an intriguing question. 4.4. Allograft inflammatory factor The Allograft Inflammatory factor (AIF-1) is both upregulated in CIDP and VAS as compared to NN. This gene was originally cloned from activated macrophages in human and rat atherosclerotic allogenic heart grafts undergoing chronic transplant rejection (Utans et al., 1995). It is a 17kDa IFN-g inducible Ca 2+-binding EF-hand protein encoded within the HLA class III genomic region. It is a modulator of immune response during macrophage activation (Utans et al., 1996). It is constitutively expressed in the brain by a subset of microglial cells and increased there in the context of focal human brain infarctions, human and rat traumatic brain injury, human gliomas, but also in rat autoimmune encephalomyelitis and uveitis (Postler et al., 2000; Beschorner et al., 2000; Deininger et al., 2000; Schluesener et al., 2001). It is therefore an example of a gene that is elevated in inflammatory nerve disease, but is not specific for CIDP. 4.5. CD86 and CD28 In our samples, CD86 and CD28 gene expression were up-regulated in vasculitic nerves, but not in CIDP. CD28 is a costimulatory receptor on T cells, which reacts with the activation antigens CD80 (B7-1) and CD86 (B7-2) on antigen-presenting cells. Antigen presentation in the pres-

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ence of B7 molecules may affect T-cell activation. (Lenschow et al., 1996; Greenfield et al., 1998). In other studies, CD86 expression was shown immunohistochemically in endothelial cells of biopsy specimens from vasculitic neuropathy but not in CIDP or normal nerve, consistent with our observations (Van Rhijn et al., 2000). Of interest, NOD mice deficient in B7-2 develop a CIDP-like illness and are protected from diabetes (Salomon et al., 2001). In other studies, B7-2 was found to be weakly present by immunocytochemistry also in low levels in some CIDP biopsies and weak staining in 2 out of 20 CIDP cases (Kiefer et al., 2000), or on the surface of some T cells but not Schwann cells in CIDP nerves (Murata and Dalakas, 2000). 4.6. Tachykinin Tachykinin, precursor 1 is the most up-regulated gene in CIDP versus normal nerve with a fold change of 27.8. The tachykinins are a family of amidated neuropeptides. The TAC precursor 1 encodes a precursor containing both substance P and neurokinin A. Tachykinins play a role as excitatory neurotransmitters and release of tachykinins from primary afferent pain-sensing receptors is required to produce moderate to intense pain (Cao et al., 1998; Pennefather et al., 2004). Substance P has a well-characterized function as neurotransmitter, but plays also a major role in modulating inflammatory and immune response and is present in sensory nerves, but also in human monocytes, macrophages and lymphocytes as well as in many other tissues (McGillis et al., 1990; Lai et al., 1998; Ho et al., 1997; Pennefather et al., 2004). Substance P stimulates human peripheral blood monocytes to produce cytokines (Ho et al., 1996). In 6 out of 8 of our CIDP patients, pain was present and it might well be that this pain is mediated via tachykinins. In conclusion, up-regulated genes might provide clues to pathogenesis, and identify potential disease markers or targets for therapeutics. Further studies are needed to confirm our findings in other patients with CIDP or vasculitis, determine the mechanism of altered gene expression in these diseases, and elucidate their possible role in pathogenesis.

Acknowledgements We thank Dr. Karsta Lqttich, Dr. Sabine Ehrt and Mallika Mallavarpu for helpful discussions.

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