Plasticity of gene expression in injured human dorsal root ganglia revealed by GeneChip oligonucleotide microarrays

Journal of Clinical Neuroscience (2004) 11(3), 289–299 0967-5868/$ - see front matter ª 2003 Elsevier Ltd. All rights reserved. doi:10.1016/j.jocn.2003.05.008

Laboratory study

Plasticity of gene expression in injured human dorsal root ganglia revealed by GeneChip oligonucleotide microarrays Douglas Rabert1,* PHD, Yuanyuan Xiao2,* PHD, Yiangos Yiangou3 PHD, Dirk Kreder1,y Lakshmi Sangameswaran1,z PHD, Mark R. Segal4 PHD, C. Anthony Hunt2 PHD, Rolfe Birch5

FRCS,

Praveen Anand3 FRCP

1

Neurobiology Unit, Roche Bioscience, Palo Alto, CA, USA, 2Department of Biopharmaceutical Sciences, University of California, San Francisco, CA, USA, Peripheral Neuropathy Unit, Imperial College London, Hammersmith Hospital, London, UK, 4Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA, 5Peripheral Nerve Injury Unit, Royal National Orthopaedic Hospital, Stanmore, Middlesex, UK 3

Summary Root avulsion from the spinal cord occurs in brachial plexus lesions. It is the practice to repair such injuries by transferring an intact neighbouring nerve to the distal stump of the damaged nerve; avulsed dorsal root ganglia (DRG) are removed to enable nerve transfer. Such avulsed adult human cervical DRG (n ¼ 10) obtained at surgery were compared to controls, for the first time, using GeneChip oligonucleotide arrays. We report 91 genes whose expression levels are clearly altered by the injury. This first study provides a global assessment of the molecular events or “gene switches” as a consequence of DRG injuries, as the tissues represent a wide range of surgical delay, from 1 to 100 days. A number of these genes are novel with respect to sensory ganglia, while others are known to be involved in neurotransmission, trophism, cytokine functions, signal transduction, myelination, transcription regulation, and apoptosis. Cluster analysis showed that genes involved in the same functional groups are largely positioned close to each other. This study represents an important step in identifying new genes and molecular mechanisms in human DRG, with potential therapeutic relevance for nerve repair and relief of chronic neuropathic pain. ª 2003 Elsevier Ltd. All rights reserved. Keywords: human, DRG, microarrays, nerve injury, pain

INTRODUCTION Road traffic accidents or incidents occurring during complicated births are the most common causes of brachial plexus spinal root avulsion injuries. Usually both ventral and dorsal roots are involved, and the patient is subjected to paralysis and sensory dysfunction, with numbness in the limb in conjunction with intractable pain in adults. It is now the practice to repair spinal cord root avulsion injuries by transferring an intact neighbouring nerve to the distal stump of the damaged nerve, to restore some motor and sensory function.1 The intercostal and accessory nerves are commonly used for this purpose. The avulsed DRG has to be removed to enable nerve transfer to the distal stump – such avulsed DRGs have been collected for our studies. There is currently only limited information on the molecular level of changes that occur within the human dorsal root ganglion (DRG) following such an avulsion injury. Use of new technologies for large-scale measurements of gene expression in diseased or damaged human tissues that are available in limited quantities may yield new insights and treatment strategies. With the emergence of high-density DNA array technology, it has become possible to investigate the range of mRNA changes that are a consequence of such injuries. We have therefore employed GeneChip oligonucleotide

Received 7 March 2003 Accepted 9 May 2003 Correspondence to: P. Anand MA MD FRCP, Peripheral Neuropathy Unit, Imperial College London, Area A, Ground Floor, Hammersmith Hospital, DuCane Road, London W12 ONN, UK. Tel.: (+44)-020-8383-3309/3319; Fax: (+44)-020-8383-3363/3364; E-mail: [email protected] * D. Rabert and Y. Xiao contributed equally to this research. y Present address: Abgenix, Inc., 6701 Kaiser Dr, Fremont, CA 94555, USA. z Present address: Pherin Pharmaceuticals, Inc., 350 N. Bernardo Ave., Mountain View, CA 94043, USA.

arrays to study gene expression changes in avulsed human DRG from adult patients with closed brachial plexus traction injuries. While there are a number of categories of genes that may be differentially expressed in injured DRG, novel targets for chronic neuropathic pain are of particular interest. It is not possible to directly relate the changes in avulsed dorsal root ganglia to pain mechanisms in patients with spinal cord root avulsion injury, as the pain in such patients is related to de-afferentation, and the generation of abnormal impulses and other mechanisms within dorsal spinal cord.2 A number of these patients will also have had injuries distal to the dorsal root ganglion at other spinal levels, which may contribute to their pain. However, spinal nerve root injuries occur commonly in patients with prolapsed intervertebral discs, with consequent radiating pain, which may be intractable even after surgery; our findings may be relevant to mechanisms of pain in such cases. Further, the nature of the DRG avulsion injury is different in some respects from a surgical rhizotomy, and the changes observed may share features with DRG following peripheral axotomy: there is marked displacement of the DRG, associated vascular disturbance, and an acute inflammatory response. It is known that axotomy of the central process of sensory ganglia leads to different changes within dorsal root ganglion cells, in comparison with injuries distal to the dorsal root ganglion. For example, the expression of GAP-43 and of c-Jun in dorsal root ganglions may not be up-regulated following central axotomy, but is up-regulated following peripheral axotomy.3;4 However, where dorsal root section was adjacent to the dorsal root ganglia, there was a small and transient increase of GAP-43 mRNA levels.4 Classical anatomical and physiological factors provide the setting for considering the relationship of any changed genes to pathology. Three types of nerve injury have been distinguished:5 neurapraxia – with myelin damage, with conduction block; axonotmesis – a degenerative lesion of the axon with basal lamina of Schwann cell intact, with no conduction; and neurotmesis – a degenerative lesion in which all elements of the nerve are 289

290 Rabert et al.

sion by visual inspection and evidence of conduction from exposed nerves to the cortex or spinal cord (SSEP) and across lesions exposed at operation. All patients reported pain. The most common descriptive words used by patients were shooting, burning, aching, and crushing.

interrupted, with no conduction. None of these classifications fully describe lesions of the brachial plexus or lumbosacral plexus, in which there may be intradural rupture of the spinal nerve roots. With neurapraxia and axonotmesis, the prognosis is favourable if the cause is removed. Neurapraxic lesions usually improve within days or weeks, rarely as late as 6 months. Both axonotmesis and neurotmesis are degenerative lesions. If the lesion leaves the Schwann cell basal lamina intact, axonotmesis, the pathways for axonal regeneration remain.6;7 With neurotmesis, recovery can occur only after nerve repair, and will usually be imperfect. The structure of peripheral nervous tissue is one of nerve fibres (axons-Schwann cell units) suspended in collagen rich extracellular space.8 The spinal nerve roots and rootlets within the spinal canal are fragile and easily damaged; they have lost the supporting envelope of the epineurium, nerve fibres are more densely packed, and extrinsic blood vessels are scanty. Supporting structures outside the foramina make the nerves here more robust; the epineurium, a prolongation of the dural sleeve, is composed of longitudinally directed collagen fibres and fibroblasts,9 while the perineurium, which ensheaths the nerve fascicles, is composed of flattened cell processes alternating with layers of collagen. Within days of axonotomy there is reduction in the calibre of the proximal axon, which may progress to atrophy.10 The velocity of conduction in the proximal segment drops,11 and there are changes in the cell body. In brachial plexus injury, there is degeneration of somatic efferent and pre-ganglionic autonomic efferent fibres, and central processes of sensory fibres; the distal axons of somatic afferents remain intact. The latter are electrophysiologically “functional”, and continue to mediate cutaneous axon-reflex vasodilatation.12 However, cutaneous axon-reflex vasodilatation is reduced,2 and may be related to changes in the DRG tissue we have studied. Review of series from both civil and military practice13–15 shows that age, level of injury, type of nerve, violence of injury and delay from injury to repair are all significant. Of these factors violence of injury and delay to repair are particularly important. Studies of avulsed human DRGs may also provide strategies for successful re-implantation of avulsed sensory roots in patients. Spinal nerve root repair and re-implantation of avulsed ventral roots into spinal cord after brachial plexus injury16 provides evidence about the harmfulness of delay in reconnection. This first study provides a global assessment of the molecular events as a consequence of DRG injuries, as there was a wide range of surgical delay, from 1 to 100 days.

Human tissues and RNA Avulsion injury tissues obtained fresh at surgery were snap-frozen in liquid nitrogen. All tissues were removed as a necessary part of the surgical repair procedure, and not for research studies; informed consent was obtained from patients and approval from the local Ethics Committee for these studies. Total RNA was extracted from the processed tissue samples using the Trizol protocol (LifeTechnologies). PolyAþ RNA was recovered using Oligotex mRNA Spin Columns (Qiagen). A control sample of human DRG total RNA containing pooled extracts from n ¼ 8 post-mortem DRG tissues was obtained from a commercial source (Clontech). Preparation of biotinylated target cRNA Biotinylated cRNA targets were prepared from either 20 lg total RNA or 1 lg polyAþ RNA using a modified version of the protocol from the chip manufacturer. RNA samples were mixed with 200 pmol priming oligonucleotide (50 GGCCAGTGAATTGT AATACG ACTCACTATAGGGAG GCGG-(dT)24 ) in a total volume of 22 ll, and heated at 70
C for 10 min. First and second strand cDNA synthesis reactions were performed with the SuperScript Choice system (LifeTechnologies); all reaction components and the total volume were increased 2-fold. The first strand reaction was incubated at 37
C for 1 h and the second strand cDNA reaction was incubated at 16
C for 2 h followed by a 5 min 16
C incubation with T4 DNA polymerase (20 units). Doublestrand cDNA was treated with 5 lg RNase A at 37 C for 30 min followed by the addition of 75 lg proteinase K and 15 ll of 10% SDS, and the reaction was incubated at 37
C for 30 min. The cDNA products were de-proteinized by performing three phenol:chloroform:isoamyl alcohol (24:1:1) extraction steps with phase separation accomplished using Phase Lock Gel I, light (Eppendorf-5 Prime, Inc.). The reaction product was recovered from the final aqueous phase by ethanol precipitation. The resulting cDNA preparation was used in the in vitro transcription reaction to generate biotinylated cRNA target using the MEGAscript T7 kit (Ambion). The T7 in vitro transcription reaction was performed in a final volume of 40 ll at 37
C for 6 h (ribonucleotide concentrations: 7.5 mM ATP, 7.5 mM GTP, 5.6 mM CTP, 5.6 mM UTP, 1.9 mM Biotin-11-CTP, and 1.9 mM Biotin16-UTP). Biotinylated cRNAs were purified using the RNeasy Mini kit (Qiagen). Recovery of the biotinylated cRNAs was determined by spectrophotometric measurements. The pooled con-

MATERIALS AND METHODS Patients Cervical avulsed human DRG tissues (n ¼ 10) were obtained from adult male patients (n ¼ 10), all with traumatic injuries to the brachial plexus (see Table 1). The surgeon confirmed the leTable 1

Patient Information

Patient ID Number

Days from Injury

Displacement (cm)

rtery (y/n)

Local Fracture (y/n)

Tinel (y/n)

Recovery (y/n)

02 07 18

7 7 5

2 7 2

n n n

y n y

n y y

y y y

04 06 10

1 3 4

2 8 5

y y n

y y y

n y y

y y y

11 12 15 17

1 100 56 21

2 1 3 8

y n n n

y n y y

n y n y

y n n y

Journal of Clinical Neuroscience (2004) 11(3), 289–299

ª 2003 Elsevier Ltd. All rights reserved.

Gene expression microarrays of injured human DRG 291

trol sample was processed in triplicate and each biotinylated cRNA target was hybridized to a separate array. Preparation of GeneChip arrays Biotinylated cRNA target (20 lg) was fragmented at 94
C for 35 min in 40 mM Tris–acetate, pH 8.1, 100 mM potassium acetate, 30 mM magnesium acetate buffer. 15 lg of the fragmented biotinylated cRNA was combined with hybridization solution (1
MES (100 mM MES, 1 M [Naþ ], 20 mM EDTA, 0.01% Tween 20), 50 pM B2 control oligonucleotide, control cRNAs (1.5 pM BioB, 5 pM BioC, 25 pM BioD and 100 pM cre), 0.1 mg/ ml herring sperm DNA (Promega), and 0.5 mg/ml acetylated BSA) to yield a final volume of 300 ll. The hybridization solution was then incubated at 99
C for 5 min and at 45
C for 5 min. Supernatant was recovered after a 10 min centrifugation. Affymetrix GeneChip HuGeneFL arrays (Hu6800) were prehybridized for 15 min using 200 ll of 1
MES buffer at 45
C. Subsequently, the arrays were incubated at 45
C for 16 h using a volume of 200 ll hybridization solution. After the hybridization the arrays were washed with 250 ll of non-stringent buffer (6
SSPE, 0.01% Tween 20, 0.005% antifoam) and then stained according to the EukGE_WS2 protocol for the Affymetrix GeneChip Fluidics Station 400. The stained arrays were washed in two steps using stringent (100 mM MES, 0.1 M [Naþ ], 0.01% Tween 20) and non-stringent wash buffer. Finally, signal was amplified using SAPE stain solution (1
stain buffer (100 mM MES, 1 M [Naþ ], 0.05% Tween 20, 0.005% antifoam O30 (Sigma)); acetylated BSA, 2 g/l; streptavidin R-phycoerythrin (Molecular Probes), 10 lg/ml) and antibody solution (1
stain buffer; acetylated BSA, 2 mg/ml; normal goat IgG, 0.1 mg/ml (Sigma); biotinylated anti-streptavidin, 3 lg/ml (Vector Laboratories)) and each array was scanned twice with a Hewlett–Packard GeneArray Scanner. Data analysis All data for patient and control samples was preprocessed (background subtraction, calculation of differential intensities) using Affymetrix GeneChip software. Average differential intensity (ADI) values were then normalized across all experiments and filtered based on standard deviation and log (base 2) transformed change factors. Expression values that passed the filters applied were then subjected to hierarchical clustering using the program Cluster.17 Clustering was applied to both axes using the weighted pair-group method with centroid average as implemented by the authors. The distance matrixes applied here were Pearson correlation for clustering of samples and the inner product of vectors normalized to magnitude 1 for clustering of genes (see Cluster manual available at http://www.microarrays.org/software/ for details). The results were then visualized with the program Tree View written by the same authors.1 Normalization All data collected in each hybridization experiment was processed using the GeneChip software supplied with the Affymetrix instrumentation system. To determine the quantitative amounts of RNA associated with each gene probe set, the average of the differences (perfect match minus mismatch) of the fluorescence intensity for each oligonucleotide probe pair (at least 20) in a

1

Column E: method of selection of genes: 1, genes that have p values of t statistics ¼ 0.01; 2, genes that fold changes P 5 or 6 -4; 3, genes that are implicated in literature to be involved in pain sensational pathways. Column F: *genes discussed in the paper.

ª 2003 Elsevier Ltd. All rights reserved.

probe set was calculated as previously described. The resulting difference intensity values were then re-scaled to equalize the overall intensity for all 13 (patients + controls) arrays by calculating the average intensity within and across arrays. The ratio of these two numbers became the rescaling factor for each array. The original intensity multiplied by the rescaling factor yielded the rescaled fluorescence intensity difference. This rescaled fluorescence intensity value was taken as an objective measure of the level of expression of mRNA corresponding to the gene-specific probe set, and is hereafter referred to as expression level (or level of expression). A threshold value of 20 fluorescence units was assigned to any gene with a calculated, rescaled expression level below 20. The expression data were then displayed in a 7129
13 matrix with rows corresponding to gene-specific probe sets and columns corresponding to the array used to analyze a given DRG tissue extract. Two sample t tests A two-group t statistic (using the pooled-variance estimate) was used to test the null hypothesis that gene probe set i in the patient and control groups have equal expression
1i  X
2i Þ ðX ti ¼ pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ; 2 ðsi =n1 Þ þ ðs2i =n2 Þ

where s2i ¼

ðn1  1Þs21i þ ðn2  1Þs22i n1 þ n2  2

X
1i and X
2i denote the mean expression levels for gene probe set i in the patient and control groups; s2i is the pooled-variance estimate; s21i and s22i denote the variances of the expression levels for gene probe set i in the patient ðn1 ¼ 10Þ and control ðn2 ¼ 3Þ groups. Because the minimum intensity value was set at 20 units, t statistics could only be calculated for 5638 probe sets. Fold changes The mean expression level values for each gene in the patient and control groups were calculated. The fold change for an individual gene was determined as the ratio of these two values. To facilitate comparisons, when the patient: control ratio is <1, the reciprocal ratio was calculated and given a negative value; i.e., a patient: control ratio of 3.0 was used without modification and referred to as 3-fold increase in gene expression level, whereas a value of 0.333 was transformed to )3.0 and referred to as 3-fold decrease in gene expression level. Selection of genes Genes were determined to have differential expression levels in the patient group compared to the control group if one of the two criteria is satisfied: (1) p values of t tests 6 0.01; (2) 5-fold or 4fold change or greater (because of the unsymmetrical distribution of fold changes the cut-offs for up regulated genes and down regulated genes were different). Genes that have been previously reported as being involved in pain signalling pathways were also discussed. Hierarchical clustering After filtering and categorization, genes in Table 2 were standardized to have mean 0 and standard deviation 1. They were then clustered by a hierarchical clustering algorithm (available at http:// rana.lbl.gov/EisenSoftware.htm). Average linkage method is employed. RESULTS The transcription profile for each DRG sample was analyzed using the HuGeneFL array that contains probe sets for 7129 human genes. Comparison of the expression profiles from the patient and Journal of Clinical Neuroscience (2004) 11(3), 289–299

292 Rabert et al.

Table 2

A partiala list of genes that are differentially expressed in the patient group

Gene description

Probe Set

NGFB, nerve growth factor, b polypeptide TrkA receptors Proto-Oncogene Trk p75 GFRA2, Glial cell line derived neurotrophic factor receptor

X52599 M14764 HG1437-HT1437 U94319 AF002700

Neurotrophins/receptors 0.031 )1.84 0.040 )2.39 0.002 )3.91 0.055 3.75 0.046 )2.09

GLRA2, Glycine receptor, a2 u-Opioid receptor Glutmate receptor,ionotropic,kainate 3 NMDA receptor, glutamate gated TTX resistant Na channel, type V High conductance potassium inward rectifying channel Cholinergic receptor, nicotinic, a polypeptide 3

X52008 L25119 U16127 L13266 M77235 L36069 M86383

Neurotransmitter receptors 0.171 11.45 0.090 )1.95 0.022 )2.29 0.024 )2.97 0.018 )2.78 0.004 )2.72 0.008 )3.19

2 3 3 3 3 1 1

IGFBP6 Insulin-like growth factor Cysteine-rich fibroblast growth factor receptor MDK, Midkine (neurite growth-promoting factor 2) Nuclear phosphoprotein mRNA Fmlp-related receptor I IGF2, Insulin-like growth factor CSF2RB, Colony stimulating factor TGFBR3, Transforming growth factor, b receptor III GRO2 oncogene 6-16 gene (interferon-inducible protein) Monocyte chemotactic protein 1 Glia maturation factor b Interferon r receptor 2 Iterferon r receptor induced protein 16 Interferon r receptor induced protein 30 Iterleukine 13 Tachykinin Tachykinin-A (PPT-A)

M62402 U28811 M94250 L22343 HG2480-HT2576 J03242 M59941 L07594 M57731 U22970 HG4069-HT4339 AB001106 U05875 M63838 J03909 U31120 U37529 M68907

Cytokine/receptor related 0.000 )4.23 0.000 )4.04 0.001 )4.34 0.005 )2.42 0.006 )2.85 0.007 )3.90 0.008 )1.81 0.008 )2.70 0.288 10.31 0.070 7.11 0.199 5.84 0.086 5.17 0.050 2.57 0.018 3.51 0.176 12.39 0.000 )2.88 0.095 1.91 0.133 5.08

1,2 1,2 1,2 1 1 1 1 1 2 2 2 2 3 3 2,3 1,3 3 2,3

Protein kinase A, cAMP dependent, catalytic, b WD repeat protein HAN11 mRNA Calcium, calmodulin-dependent protein kinase PRKCD, Protein kinase C, delta Frizzled gene product mRNA ARH6, Aplysia ras-related homolog RGP4 mRNA GSK-3, Glycogen syntase kinase Ras-related C3 botulinum toxin Protein-tyrosine phosphatase ERBB3 V-erb-b2 avian erythroblastic leukemia viral oncogene homolog 3 65 KD yes-associated protein G protein c-10 subunit mRNA Protein kinase (Gb:M59287) M1S1 gene extracted from human SH3 domain-containing protein 1B Caspase 2, apoptosis – related cysteine protease Prostaglandin I2 synthase Phospholipid scramblase mRNA

M34181 U94747 U50360 D10495 L37882 M12174 U27768 L33801 HG1102-HT1102 M68941 M34309 X80507 U31383 HG3484-HT3678 J04152 U61167 U13022 D38145 AF008445_at

0.060 0.000 0.000 0.000 0.001 0.001 0.002 0.005 0.005 0.006 0.006 0.009 0.126 0.016 0.063 0.406 0.002 0.077 0.299

MBP, Myelin basic protein Myelin proteolipid protein MPZ, Myelin protein zero (Charcot–Marie–Tooth neuropathy 1B) Myelin basic protein Peripheral myelin protein CNP, 20 ,30 -cyclic nucleotide 30 -phosphohydrolase MPZ, Myelin protein zero (Charcot–Marie–Tooth neuropathy 1B) ARSA, Arylsulfatase A

M13577 HG3437-HT3628 D10537 HG1877-HT1917 U08096 M19650 L24893 X52151

0.000 0.001 0.001 0.002 0.004 0.005 0.006 0.003

Homeo box c8 protein, mRNA GC-Box binding protein BTEB2 Clones 23667 and 23775 zinc finger protein Homolog of Drosophila enhancer TTF-I interacting peptide 20 mR Transducin-like enhancer protein Glucocorticoid receptor repressor SNF2L1 SNF2 (sucrose nonfermenting, yeast, homolog) like 1

M16938 D14520 U90919 U04241 AF000560 M99435 M73077 M88163

0.000 0.000 0.001 0.001 0.003 0.003 0.004 0.005

Journal of Clinical Neuroscience (2004) 11(3), 289–299

p Value

Fold change

Signal transduction )1.72 )8.58 )3.59 )3.69 )3.35 )3.56 )3.48 )2.94 )2.48 )2.15 )2.30 )2.12 9.14 7.54 7.41 6.65 )2.14 )1.69 7.96 Myelination )3.72 )4.40 )2.91 )6.11 )2.79 )3.76 )4.08 )3.01 Transcription factors )2.89 )4.38 )2.26 )4.11 )3.91 )2.60 )3.11 2.99

Inclusion criterion

3 3 1,3 3 3

3 1,2 1 1 1 1 1 1 1 1,3 1 1 2 2 2 2 1 3 2

1 1,2 1 1,2 1 1 1,2 1

1 1,2 1 1,2 1 1 1 1

ª 2003 Elsevier Ltd. All rights reserved.

Gene expression microarrays of injured human DRG 293

Table 2

(continued )

Gene description

Probe Set

p Value

Fold change

Inclusion criterion

HMGI-C chimeric transcription factor IKBL mRNA CAMP-response element binding protein DNA-binding protein mel-18 Id1 DNA, binding protein from Human ICSBP1, Interferon consensus sequence binding protein 1 Zinc finger protein, clone RES4 Transcriptional coactivator Pc4 EGR2, Early growth response 2 (Krox-20 (Drosophila) homolog) STAT3, signal transducer and activator of transcription 3 Stat-like protein (Fe65) mRNA TFAP4, Transcription factor AP-4 Phosphoprotein Tal2

U28131 X77909 X60003 D13969 HG3342-HT3519 Z97054 M91196 AB000468 HG4297-HT4567 J04076 L29277 L77864 S73885 HG4068-HT4338

0.005 0.006 0.006 0.007 0.008 0.009 0.009 0.085 0.056 0.165 0.023 0.348 0.030 0.280

)2.28 )3.19 )1.80 )1.31 )1.70 )2.35 )4.05 7.13 9.23 9.01 )2.39 5.48 5.38 5.04

1 1 1 1 1 1 1,2 2 2 2 3 2,3 2 2

GIF, metallothionein, growth inhibitory factor Fatty acid amide hydrolase mRNA Lysophosphatidic acid acyltransferase PCM-1, Autoantigen pericentriol material AHNAK nucleoprotein (desmoyokin) DPP6, Dipeptidylpeptidase VI GMAT, Guanidinoacetate N-methyltransferase Protein tyrosine phosphatase, receptor type TNA, Tetranectin (plasminogen-binding protein) PRELP, Proline arginine-rich end leucine-rich repeat protein RYR1, gene extracted from human Somatostatin

S72043 U82535 U56417 L27841 M80899 M96859 Z49878 U35234 X64559 U41344 J05200 J00306

0.001 0.001 0.006 <0.001 <0.001 <0.001 0.003 0.005 <0.001 0.005 <0.001 0.007

Miscellaneous )2.80 )3.08 )2.56 7.34 )3.25 )2.16 )3.44 )2.16 )6.61 )4.06 )4.75 )2.02

1 1 1 1,2 1 1 1 1 1,2 1,2 1,2 1,3

Genes are subdivided into different functional groups. The last column indicates the inclusion criteria applied for a specific gene: (1) t test p value; (2) fold change; (3) reported in literature. a An additional 154 significantly changed genes are listed in the Appendix.

control DRG tissues allowed for the identification of differentially regulated genes associated with the tissue injury. Fig. 1(A) and (B) show the similarity in gene expression levels within the patient and control groups, respectively. As expected, the majority of the points follows the identity line and shows acceptable within-group intersubject variability. On the contrary, scatter plot for a patient and a control (Fig. 1(C)) indicates a considerable deviation from the identity line, which is suggestive of discordance in the patterns of gene expression between the patient and control groups. Our goal is to identify the subset of genes that are primarily responsible for such discordance. Given that this is the first study of global gene expression profile changes in damaged human DRG, it is important to have a global and comprehensive assessment of differential gene expression in the damaged human DRG tissue. We therefore opted to use both t test and fold change to identify specific genes having altered expressions in the patients, so that valuable gene targets that would have been missed if only one of the criteria was applied will be recovered. We are highly aware of the multiple testing problems inherent in univariate microarray data analysis methods applied here,18–20 however our goal here is to provide interested biologists with a working list of the majority of genes that could be valuable for further exploration. Readers who are interested in the multiple testing problems applied on this dataset are referred to the statistical discussion of these issues.21 The avulsion injuries in all patients are followed by intractable pain. It is therefore logical that we also consider the expression values for a set of 14 genes that have been previously reported as being involved in pain signalling pathways, even though some of which do not satisfy the above criteria. The final result is a set of 244 genes. The combined set of 244 genes may represent one or more networks (or portions thereof) of interacting gene products that ª 2003 Elsevier Ltd. All rights reserved.

substantially account for the chronic pain. The 91 genes listed in Table 2 that are found to have differential expression in the avulsion patients compared to controls are involved in either neurotransmission, neurotrophins/receptors, cytokine functions, signal transduction, myelination, or transcription regulation. The expression patterns of these 91 genes are displayed and clustered in Fig. 2 using a hierarchical clustering algorithm. Genes that are down regulated in the patient group and those that are up regulated in the patient group fall into two different clusters. Genes that are involved in the same functional groups are largely positioned close to each other. For example, genes that play key roles in myelination are clustered very closely; interferon related genes are also next to each other in the bottom of the figure.

DISCUSSION Changes in the gene expression profile of the avulsed DRG may not only reflect the degeneration of central axons of sensory neurons, but they may also involve other complex processes. Some of these changes are similar to those seen after peripheral axotomy, and others to inflammatory processes. For example, both spinal cord root avulsion and distal injuries produced a highly significant reduction in skin flares,2 and alternative mechanisms can be considered in the light of our results. A likely explanation for the decreased flares in avulsion injury is vascular damage to the dorsal root ganglion, with consequent small cell loss or dysfunction. Alternatively, there may be a failure of trophic mechanisms necessary for phenotypic properties or survival of these cells. Another possibility is that there is normally a significant contribution to the flare response from overlapping dermatomes, which is reduced in cases with a lesion distal to the dorsal root ganglion neighbouring an avulsion. Journal of Clinical Neuroscience (2004) 11(3), 289–299

294 Rabert et al.

Fig. 1 Global comparison of the differences in gene expression levels (calculated as described in the text) within and between the patient and control groups. (A) Scatter plot of expression levels for patients 15 and 12. (B) Scatter plot of expression levels for controls C1 and C2. (C) Scatter plot of expression levels of a patient 12 and a control C1.

As it is not possible to obtain human DRG at operation with peripheral nerve injuries, we are limited to future post-mortem studies to clarify the relationship of central versus peripheral axotomy in human sensory neurons. Data analysis DNA arrays of different types are being extensively used to study gene expression levels on a large scale. When analyzing the thousands of genes at the same time in a single experiment, one must be concerned with multiple testing errors. Exploring methodologies for tackling the problem of family-wise errors, and thereby minimizing the impact of false positives, is a component of our ongoing research. We are also evaluating the appropriateJournal of Clinical Neuroscience (2004) 11(3), 289–299

ness of some multivariate statistical methodologies that may allow us to dissect out important nerve injury gene expression networks. There are several commonly used multivariate statistical methodologies to analyze array data. Clustering methods that are based on unsupervised learning techniques are widely used to identify sets of genes with similar expression patterns.17;22 Classification methods that are based on supervised learning techniques provide a powerful means for exploiting prior knowledge, including knowledge of gene function, to assign genes into different functional categories.23;24 The goal of this study is to identify sets of potentially informative genes in DRG tissues that exhibit different expression profiles as a consequence of the avulsion injury. Accordingly, we face a relatively simple univariate testing problem for each gene. We appropriately apply the t tests and fold change calculations to analyze the data for each gene. Even though we are not yet testing hypotheses, each approach is useful at identifying subgroups of differentially expressed genes. Genes that have only two modes in their expression profiles, “on” and “off”, are the ideal candidates for the t tests as long as the assumptions underlying the tests are reasonably valid. The use of the t statistic presupposes that the variances of the two groups are similar. Furthermore, for a specified difference in mean expression levels, a significant t statistic requires the variances of the two groups to be small. Some of the many genes that do not meet our t statistic criterion may, nevertheless, have phenotype-specific, interesting and informative patterns of expression, where the expression regulation mechanisms are more complicated than simply being either on or off, high or low. It follows that the large variances in the expression levels of some genes within the patient samples may mask biologically significant changes, especially those changes that are related to different patient classifiers or phenotypes, such as severity of injury. It is not surprising that we find that most of the up regulated genes in Table 2 that fail to meet our t test criterion, are nevertheless identified as being significantly altered based on fold change. This analysis provides a global assessment of the molecular events as a consequence of DRG injuries. However, the functional networks that relate the various proteins known to be associated with pain and neuronal disorder have yet to be elucidated (see Table 3). Consequently, it is too early to know, or even to speculate, how some genes in Table 2 might be functionally related in the damaged DRG tissue. Detailed study of the results of this and future studies, including stratification of tissues (e.g., severity and time course) will eventually lead to understanding. Until then it seems appropriate to draw attention to sets of genes that appear to be significantly up or down regulated in the patient group, along with several of the genes known to be associated with important or well-studied disorders. Here, we limit this discussion to a selection of genes in six functional categories along with a set of several genes known to be important in pain sensation pathways. Given the wide range of durations between injury and collection of DRG at surgery, it is not surprising that some transiently regulated genes do not appear in the changed list. To illustrate, the formation of a neuroma may lead to positive sensory symptoms, following accumulation of sodium channels that generate spontaneous and evoked discharges. Recently, the distribution of two TTX-resistant “sensory neurone specific” sodium channels – SNS/PN3 and NaN/SNS2, which are preferentially expressed in nociceptors, were identified in injured human neurones; SNS/PN3 was shown to be acutely decreased in avulsed DRG sensory neurones but not nerve fibres, and to accumulate at the site of nerve injury.25 Specific potassium channels were also found to show differential and transient changes in neurons of different diameters in avulsed human DRG.26 There was a dramatic (several hundred fold) increase of IL-6 within 3 days, but only up to 2 ª 2003 Elsevier Ltd. All rights reserved.

Gene expression microarrays of injured human DRG 295

Fig. 2 Genes that are differentially expressed in avulsion patients. The 91 genes that categorized in Table 2 are shown in the clustering tree produced by CLUSTER. Each column corresponds to expression levels in individual samples and each row corresponds to individual genes. Expression levels for each gene are normalized across the samples to have mean 0 and standard deviation 1. Expression levels greater than the mean are colour coded in red, those less than the mean are coded in blue.

weeks, in human dorsal root ganglia following root avulsion injury.27 Other important peripheral pain mechanisms such as ephaptic transmission and nociceptor sensitization may not be addressed in our tissues.28–31

ª 2003 Elsevier Ltd. All rights reserved.

Neurotrophic factors/receptors While peripheral sources of NGF are predominant and NGF protein is decreased in avulsed human DRG, possibly secondary to defective retrograde transport,32 local synthesis of NGF in DRG Journal of Clinical Neuroscience (2004) 11(3), 289–299

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Table 3

What genes are expressed in human DRG ?

Categories Cell type Sensory neurones Schwann cells Satellite cells Fibroblasts Inflammatory cells Vascular endothelium/smooth muscle Function Structural proteins, ion channels, receptors, growth factors, transcription factors peptides, enzymes, mitochondrial, nuclear Pathways Signalling pathways Axonal elongation Myelination Membrane excitability Chronic inflammation Targets Pain Nerve regeneration/maturation Collateral sprouting Neuropathy mechanisms

tissues has been reported previously.33 NGF may be expressed in DRG by different cell types including smooth muscle of blood vessels, fibroblasts and satellite or inflammatory cells. In this study, the local expression of nerve growth factor (NGF) in the avulsed DRG was decreased, the significance of which is uncertain; while NGF excess may lead to hypersensitivity, a paracrine role in DRG has not been demonstrated. The NGF high-affinity trk A was also decreased in the avulsed, in accord with known effect of reduced NGF uptake and retrograde transport in animal models.34 Another neurotrophin receptor, p75, is up regulated in the patient group, possibly related to expression by Schwann cells that have lost axonal contact, as these express p75 but not trk A.35 Neurotransmitter receptors Expression of the NMDA receptor subtype of glutamate-gated ion channels, is decreased in patients. There is also a decrease in NMDA receptor expression in rat DRG following complete Freund’s adjuvant-induced inflammation.36 It possesses high Ca permeability and voltage-dependent sensitivity to Mg. Much evidence points to the involvement of N-methyl-D -aspartate (NMDA) receptors in the development and maintenance of neuropathic pain in the spinal cord; electrophysiological and behavioural data both indicate a significant role of NMDA receptor mechanisms underlying wind-up and central sensitization.37 However, its role in DRG is as yet unknown. Expression of another neurotransmitter receptor, neuronal acetylcholine receptor, nAChR,38 is also decreased in patients. A recent study by Bernardini et al.39 confirms the presence of nAChRs in sensory neurons and, in contrast to activation of CNS nicotinic receptors, demonstrates their roles in C-fibre excitation and physiological pain mechanisms. Intradermal injections of nicotine are used to induce axon reflex sweating, but at higher concentrations induce pain and axon reflex vasodilatation,40 the latter mediated by unmyelinated afferents (our unpublished observations). Cytokines Several of the important cytokines that are involved in neuronal functions exhibit different expression profiles in patients. MidJournal of Clinical Neuroscience (2004) 11(3), 289–299

kine41 is a retinoic acid-responsive gene that is associated with neurite growth and was recently discovered to have potent neuroprotective activity in vivo, which was taken to suggest that midkine might be useful as a therapeutic agent for prevention of neuronal death in neurodegenerative diseases.42 Midkine is dramatically down regulated as a consequence of the avulsion injuries suffered by patients. Another noteworthy cytokine is glial maturation factor b.43 It is responsible for differentiation of brain cells, stimulation of neural regeneration, and inhibition of proliferation of tumour cells. Its expression level in the avulsion group, compared to the control group, is increased 5.2-fold. Tissue damage, infection and inflammation produce pain, which may be mediated by cytokines. Local pH, vascular flow and permeability changes are accompanied by immune cell migration to the site of injury, which is followed by release of cytokines (interleukins, tumour necrosis factor, interferons). The cytokine interferon-c (IFN-c) activates macrophages to produce nitric oxide and TNF-a. Knock out mice lacking receptors for IFN-c exhibited reduced autotomy behaviour, suggesting a possible role for IFN-c in neuropathic pain.44 In avulsion patients, interferon-c receptor 2,45 interferon c-induced protein 16 ðp ¼ 0:018Þ, and interferon-c induced protein 30 are all up-regulated, whereas interleukine 13, a cytokine which inhibits inflammatory cytokine production, is down regulated. These alterations correlate well in patient’s tissues, implicating the role of IFN-c as a peripheral mediator. In addition, the expression level of tachykinin, a peptide that has long been thought to be involved in nociceptive processing, is also changed in the avulsion patients. Two different probes (U37529 and M68907) on the arrays, coding for b and c tachykinin, respectively, are both up regulated in the patient group. Tachykinins are found to be up regulated by inflammation in an NGF-dependent fashion,46 but decreased after peripheral axotomy; however, there are differential changes in sensory neurons of small and large diameter after peripheral nerve injury in the rat, which deserve further study in injured human DRG. Myelin function PMP22 (peripheral myelin protein), MPZ (myelin protein zero) and EGR2 (early growth response gene 2)47 are all thought to play a role in Charcot–Marie–Tooth (CMT) disease, also known as hereditary motor and sensory neuropathy (HMSN). Both PMP22 and MPZ were significantly down-regulated in avulsed DRG, whereas EGR2 expression is increased. PMP22 is involved in growth regulation, and in myelination in the peripheral nervous system (GeneCards http://nciarray.nci.nih.gov/cards/).48 Abnormal PMP22 cause CMT1A, which is characterized by early onset of severe motor and sensory neuropathy and slow nerve conduction velocities (GeneCards http://nciarray.nci.nih.gov/cards/).48 Defects in PMP22 are also associated with hereditary neuropathy with liability to pressure palsies, an autosomal dominant disorder causing transient episodes of peripheral nerve palsy. Mutations of the second protein, MPZ, have been associated with CMT1B, Dejerine-Sottas disease, and with congenital hypomyelination, all of which are inherited demyelinating neuropathies.49 In support of the reproducibility of oligoarray analysis, the two different oligo probes (D10537, L24893) coding for MPZ showed the same trend, substantially decreased expression in the patient group. The third protein, EGR2, belongs to a family of zinc finger transcription factors that have been implicated in the control of cell growth, differentiation, and apoptosis within the nervous system, the immune system, and elsewhere.50 EGR2 is involved in early myelination within the peripheral nervous system. It links initial cytoplasmic events to long-term alterations of cellular gene expression and is induced by various stimuli. In the patient group, ª 2003 Elsevier Ltd. All rights reserved.

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EGR2 expression is increased 9-fold in the patient group relative to control values. Defective EGR2 are implicated in congenital hypomyelination, CMT, as well as in Dejerine-Sottas disease. Congenital hypomyelination is characterized, clinically, by early onset of hypotonia, areflexia, distal muscle weakness, and very slow nerve conduction velocities. Expression of myelin proteolipid protein (PLP1), which plays an important role in the formation or maintenance of the multilamellar structure of myelin, is also altered in the patient group. In mice and rats, defects in PLP1 are the cause of the dysmyelinating diseases jimpy and rumpshaker (mouse) and md (rat). In addition, expression of myelin basic protein (MBP), a component of myelin whose function is to maintain proper structure of myelin, is substantially suppressed in the avulsion DRGs. Similarly, the expression level of 20 ,30 -cyclic nucleotide 30 -phosphohydrolase (CNP), which is associated exclusively with glial cells and plays a significant role in the process of myelin formation, is significantly suppressed. Interestingly, in the taiep rat, a myelin mutant in which initial hypomyelination is followed by progressive demyelination of the CNS, the expression of PLP1, MBP, and CNP are also diminished.51 Arylsulfatase A expression is also down regulated in the patient group and functions to hydrolyse cerebroside sulfate. Defects in arylsulfatase-A are a cause of metachromatic leucodystrophy, a disease characterized by the storage of cerebroside-3-sulfate in the myelin membranes and primarily affects oligodendrocytes,52 and is associated with peripheral neuropathy. HER3 (erbB3, epidermal growth factor receptor), a signal transducing transmembrane receptor for neuregulins, is down regulated in the patient group. It is expressed in Schwann cells and involved in Schwann cell development and myelination.53;54 Signal transduction Caspase 2 is an apoptosis-related cysteine protease that is expressed specifically in neural precursor cells and is developmentally down regulated. It is, presumably, involved in apoptosis execution by either activating several proteins required for cell death or inactivating proteins necessary for cell survival.55 It is considered as an apoptosis initiator. Its expression is substantially down regulated in avulsion patients. Protein kinase C (PKC) delta type is inhibited by oxidative stress as well as being involved in the induction of apoptosis.56 All avulsion injury patients in this study show a dramatic reduction in the expression of PKC delta. Cleavage of PKC and activation of the PKC signal transduction pathway is associated with the activation of caspases. On the other hand, reduction of PKC expression blocks the caspases-dependent apoptosis pathway. Both PKC delta and caspase 2 are upstream of apoptosis activation and their down regulation following the avulsion injury may protect cells from entering apoptosis. Another gene, glycogen synthase kinase 3b (GSK-3), is a key downstream target of the PI3-kinase/AKT survival signalling pathway. It is also involved in the regulation of apoptosis, and is down regulated in avulsion patients. This down-regulation accords with the down regulation of PKC and caspase 2, since it was shown that selective inhibition of the endogenous pool of GSK-3 activity in primary neurons is sufficient to protect neurons from death.57 The altered expression of another protein was also implicated in prevention of apoptosis: Frizzled (fz), a developmentally regulated protein, functions as a receptor in the Frizzled-Dishevelled signal transduction cascade. It has been shown that over expression of fz induces apoptosis.58 This gene was also down-regulated in avulsed DRG. On the other hand, the endogenous removal of injured tissues is a normal part of the recovery process. We find that phospholipid scramblase, a protein whose function is closely linked to this purpose, is substantially up-regulated (a 7.96-fold ª 2003 Elsevier Ltd. All rights reserved.

increase). Phospholipid scramblase activity has been observed in many cells, and is thought to be central to the rapid movement of phospholipids from inner plasma to the outer membrane leaflet in injured and apoptotic cells. Transcription factors Within the patient group, the expression of two transcription factors is increased significantly whereas one is decreased. SNF2 is a general transcriptional activator, S. cerevisiae SWI/SNF related protein. It is involved in remodelling of chromatin structure during transcriptional modulation,59 as well as being implicated in neural differentiation.59 Its expression is increased in the patient group. Tal2, a helix–loop–helix transcription factor, is mainly involved in T cell leukemogenesis. A recent report shows that it plays a pivotal role in brain development.60 Its expression undergoes a 5.0-fold increase in avulsion patients. Inhibitor of DNA binding 1 (Id1) is a transcription regulator potentially required for neurogenesis and angiogenesis. It is postulated to be induced during nerve injury and to deactivate myelin genes, especially MPZ.61 However, within the avulsion injury group, expression of both Id1 and MPZ are depressed significantly. This paradoxical result might indicate a secondary or pathological response. STAT3, signal transducer and activator of transcription 3, is involved in the transcriptional attenuation of many cytokine- and growth factor-inducible genes,62 and its expression level is down regulated in the patient group. Miscellaneous The differential expression of some other genes are also intriguing. Metallothionein (MT)-III is a brain specific isomer of MTs, a zinc- and copper-binding metallothionein family. The distribution of zinc selenite and expression of metallothionein-III mRNA in the spinal cord and dorsal root ganglia of the rat suggests a role for zinc in sensory transmission.63 In the study of the effect of zinc on pain induced by peripheral inflammation,64 found that the administration of zinc produced hyperalgesia and an elevation in the levels of interleukin-1b (IL-1b) and nerve growth factor (NGF).64 The expression of NGF was also changed in the samples in this study. However, it is too early to speculate whether MT-III and NGF are part of a common network. Furthermore, zinc is known to interact with NMDA and non-NMDA receptors, which are thought to play an important role in nociceptive transmission.65 Another function of MT-III, its neuroinhibitory activity, is also noteworthy. The significant decrease of MT-III in the patient samples might lead to promotion of neurite extension.66 Fatty acid amide hydrolase (FAAH) is a membrane protein that degrades neuromodulating fatty acid amides at their sites of action and is involved in their regulation. Its effective substrates include anandamide. Anandamide is an endogenous fatty acid that binds to the central CB1 and peripheral CB2 cannabinoid receptors through which it is thought to exhibit its analgesic and cannabinoid effects. Endogenous anandamide levels increase on painful stimulation, implicating its role in suppressing pain neurotransmission and in behavioural analgesia.67 The inhibition of the expression of FAAH in the patient group reinforces the possible roles of FAAH and anandamide as therapeutic treatments of pain. Somatostatin, a major factor in the control of metabolism, also functions in the central nervous system as a neurotransmitter and neuromodulator. Somatostatin is expressed by dorsal root ganglion neurons and may be involved in nociception.68 In addition, somatostatin is also found to have an effect on the phosphorylation of STAT3,62 and both the expression levels of somatostatin and STAT3 are decreased in the patients. Journal of Clinical Neuroscience (2004) 11(3), 289–299

298 Rabert et al.

CONCLUSION This first human DRG microarray study represents an important step in identifying new genes and molecular mechanisms, with potential therapeutic relevance for nerve repair and relief of chronic neuropathic pain. The data presented greatly increases the vista for further functional studies, which are necessary to realize its value. ACKNOWLEDGEMENTS This work was funded by Roche Bioscience. REFERENCES 1. Birch R, Bonney G, Wynn Parry CB (eds) Surgical Disorders of the Peripheral Nerves. Churchill Livingstone, London 1998; 467–490. 2. Berman J, Birch R, Anand P. Pain following avulsion injuries of the human brachial plexus and the effect of surgery. Pain 1998; 75: 199–207. 3. Broude E, McAtee M, Kelley MS, Bregman BS. C-Jun expression in rat dorsal root ganglion neurons: differential response after central or peripheral axotomy. Exp Neurol 1997; 148: 367–377. 4. Chong MS, Reynolds ML, Irwin N et al. GAP-43 expression in primary sensory neurons following central axotomy. J Neurosci 1994; 14: 4375–4384. 5. Seddon HJ. Three types of nerve injury. Brain 1943; 66: 237–288. 6. Young JZ. Factors influencing the regeneration of nerves. Adv Surg 1949; 1: 165–220. 7. Thomas PK. Changes in the endoneurial sheaths of peripheral myelinated nerve fibres during Wallerian degeneration. J Anat 1964; 98: 175–182. 8. Berthold CH, Carlstedt T, Corneliuson O. Anatomy of the mature transitional zone. In: Dyck PJ, Thomas PK, Griffin JW, Low PA, Poduslo JF (eds) Peripheral Neuropathy. third edn. WB Saunders, Philadelphia 1993; 75–80. 9. Gamble HJ, Eames RA. An electron microscope study of the connective tissues of human peripheral nerve. J Anat 1964; 98: 655–662. 10. Guttman E, Sanders FK. Recovery of fibre numbers and diameters in the regeneration of peripheral nerves. J Physiol 1943; 101: 489–518. 11. Cragg B, Thomas PK. Changes in conduction velocity and fibre size proximal to peroneal nerve lesions. J Physiol 1961; 157: 315–327. 12. Bonney G, Gillliatt RW. Sensory nerve conduction after traction lesion of the brachial plexus. Proc R Soc Med 1958; 51: 365–367. 13. Zachary RB. Results of nerve suture. In: Seddon HJ (eds). Peripheral Nerve Injuries. By the Nerve Injury Committee of the Medical Research Council, HMSO, London;1954:354–386. 14. Kline DG, Hudson AR (eds) Nerve Injuries. first edn. WB Saunders, Philadelphia 1995. 15. Birch R, Raji ARM. Repair of median and ulnar nerves. JB & JS 1991; 73B: 154–157. 16. Carlstedt T, Anand P, Hallin R, Misra PV, Noren G, Seferlis T. Spinal nerve root repair and re-implantation of avulsed ventral roots into spinal cord after brachial plexus injury. J Neurosurg (Spine) 2000; 93: 237–247. 17. Eisen MB, Spellman PT, Brown PO, Botstein D. Cluster analysis and display of genome-wide expression patterns. Proc Natl Acad Sci USA 1998; 95: 14863–14868. 18. Dudoit S, Yang SY, Callow M, Speed TP. Statistical methods for identifying differentially expressed genes in replicated cDNA microarray experiments. Technical Report;2000:578. 19. Callow MJ, Dudoit S, Gong EL, Speed TP, Rubin EM. Microarray expression profiling identifies genes with altered expression in HDL-deficient mice. Genome Res 2000; 10: 2022–2029. 20. Storey JD. A direct approach to false discovery rates. J R Stat Soc B 2002; 64: 479–498. 21. Xiao Y, Segal MR, Rabert D et al. Assessment of differential gene expression in human peripheral nerve injury. BMC Genom 2002; 3. 22. Tamayo P, Slonim D, Mesirov J et al. Interpreting patterns of gene expression with self-organizing maps: methods and application to hematopoietic differentiation. Proc Natl Acad Sci USA 1999; 96: 2907–2912. 23. Brown MP, Grundy WN, Lin D et al. Knowledge-based analysis of microarray gene expression data by using support vector machines. Proc Natl Acad Sci USA 2000; 97: 262–267. 24. Golub TR, Slonim DK, Tamayo P et al. Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science 1999; 286: 531–537. 25. Coward K, Plumpton C, Facer P et al. Immunolocalization of SNS/PN3 and NaN/SNS2 sodium channels in human pain states. Pain 2000; 85: 41–50. 26. Boettger MK, Till S, Chen MX et al. Calcium-activated potassium channel SK1- and IK1-like immunoreactivity in injured human sensory neurones and its regulation by neurotrophic factors. Brain 2002; 125: 252–263.

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