Garrote et al.indd Drug Target Insights 2008:3 1–11 1 ORIGINAL RESEARCH Correspondence: Dr. J.A. Garrote. Research Unit. Hospital Clinico Universitario. C/ Ramon y Cajal 3. 47011 Valladolid. (Spain). Tel: +34983420000 (ext. 20422); Email: jgarrote@hcuv.sacyl.es Copyright in this article, its metadata, and any supplementary data is held by its author or authors. It is published under the Creative Commons Attribution By licence. For further information go to: http://creativecommons.org/licenses/by/3.0/. Cytokine, Chemokine and Immune Activation Pathway Profi les in Celiac Disease: An Immune System Activity Screening by Expression Macroarrays José A. Garrote1,2, Emma Gómez1, Alberto J. León1, David Bernardo1, Carmen Calvo3, Luis Fernández-Salazar4, Alfredo Blanco-Quirós1 and Eduardo Arranz1 1Group of Mucosal Immunology. Pediatrics and Immunology Areas- Instituto de Biologia y Genética Molecular (IBGM). University of Valladolid. (Spain); and 2Research Unit, 3Pediatrics Gastroenterol- ogy and 4Adults Digestive Diseases Services. Hospital Clinico Universitario of Valladolid. (Spain). Abstract: The aims of the study were to assess the usefulness of expression macroarrays to determine the pattern of expression of cytokines, chemokines and molecules related to immune system activation pathways, in non-stimulated intact intestinal tissue specimens from patients with active CD (aCD) and on a gluten-free diet (GFD), to compare it with two groups of controls with either normal or altered mucosal architecture, and to establish putative targets for diagnostic markers or therapeutic intervention. We have experienced the lack of sensitivity to detect signal of genes with low level of expression. In spite of that, active CD seems to show a Th1 cytokine pattern, but with signs of Th2 activity. Cytokines such as IL-9, IL-11, IL-21 or MIF might be involved in mucosal infl ammation in CD. In GFD, some memory cells and DC’s activity remains, and factors that maintain this remnant activation might be responsible of the fast mucosal response on gluten chal- lenge. STAT3 and STAT5 pathways, and their regulatory molecules SOCS’s may result keys for understanding mucosal infl ammation in gut and putative targets for further research. Keywords: Th2, IL-21, MIF, CX3CR1, STAT3, STAT5, Celiac Disease Introduction Celiac Disease (CD) is an immune-mediated enteropathy caused by the ingestion of gluten, a group of store proteins of certain cereals (wheat, rye, barley and probably oats) in genetically predisposed indi- viduals (Maki and Collin, 1997). The typical celiac intestinal mucosa shows fl attened villi, crypt hyper- plasia, and intraepithelial infi ltration of lymphocytes (IEL). The current treatment is a life-long strict gluten-free diet (GFD), after which a complete remission of the symptoms and mucosal recovery are found. T cells have a central role in the immunopathogenesis of CD, and cytokines released during a T cell- mediated hypersensitivity may trigger the development of the enteropathy (MacDonald and Spencer, 1988; Sollid, 2000). Specifi c lamina propria T helper cells recognize gluten peptides modifi ed by the enzyme tissue transglutaminase in the context of HLA-DQ2 or DQ8 molecules (Godkin and Jewell, 1998; Schuppan, 2000; Sollid, 2002). It has been reported that the immune response to gluten may fol- low two complementary (and sometimes parallel) pathways, mediated by the adaptive and innate immunity (Maiuri, Ciacci et al. 2003). Previous reports on cytokine expression in CD have studied biopsies from untreated patients (Nilsen, Jahnsen et al. 1998; Monteleone, Pender et al. 2001; Forsberg, Hernell et al. 2002), after ex vivo stim- ulation with gluten. Gluten-specifi c T helper cell clones, HLA-DQ restricted, isolated from the intestine of CD patients show a TH1 cytokine pattern following gluten challenge (Lundin, Scott et al. 1993; Nilsen, Lundin et al. 1995), and a similar profi le, characterized by high expression of IFNγ, but no IL12, has been found by mRNA expression in biopsy homogenates (Nilsen, Jahnsen et al. 1998; Troncone, Gianfrani et al. 1998; Monteleone, Pender et al. 2001), or isolated T cell populations (Forsberg, Hernell et al. 2002), from patients with active CD. Gluten challenge has been reported to induce also the expres- sion of IL-2, IL4, IL5, IL6, and TNFα (Nilsen, Jahnsen et al. 1998), as well as IL-18, IL-15 (Maiuri, Ciacci et al. 2000; Monteleone, Pender et al. 2001; Salvati, MacDonald et al. 2002), and TGFβ, but not http://creativecommons.org/licenses/by/3.0/ http://creativecommons.org/licenses/by/3.0/ 2 Garrote et al Drug Target Insights 2008:3 of IL10 (Nilsen, Jahnsen et al. 1998; Lionetti, Pazzaglia et al. 1999; Forsberg, Hernell et al. 2002; Hansson, Ulfgren et al. 2002). These fi ndings may be secondary to the acute response triggered by gluten on tissue specimens or isolated T cell populations, but not refl ect the situation in vivo of a long-standing infl ammatory reaction occurring in CD patients at diagnosis. The use of intact non-stimulated intestinal tissue specimens may help to identify the cytokine profi le in the intestine with a well-established on-going chronic infl ammation. The aims of the study were to assess the useful- ness of low density expression arrays (or macroar- rays) to determine the pattern of expression of cytokines, chemokines and molecules and tran- scription factors related to immune system activity pathways, in non-stimulated intact intestinal tissue specimens from adults and children with active CD (aCD) and on a gluten-free diet (GFD), and to compare it with two groups of controls with either normal or altered mucosal architecture, and to establish putative targets for diagnostic markers or therapeutic intervention. Patients and Methods Patients Intestinal biopsy specimens where collected from 8 CD patients, (mean age 20 years, range 3–52 years). From these, 4 cases were untreated (active Celiac Disease group aCD) and 4 cases were on a gluten-free diet for at least 3 months (GFD group). All patients attended the Adult and Pediatric Gas- troenterology Clinics, Hospital Clínico Universi- tario of Valladolid, as part of the routine diagnostic procedures for suspicion or follow up of CD. Adult intestinal small bowel biopsies were obtained during upper gastrointestinal endoscopy using a fybergastroscope with forceps (Olympus, Tokyo, Japan), and jejunal biopsies from children were obtained using a pediatric Crosby capsule. Patients with active CD showed altered biopsy histology, positive anti-transglutaminase antibod- ies and the HLA-DQ2 genotype, and the diagnosis was later confi rmed by the remission of symptoms and recovery of the histological and serological markers after treatment. Mucosal abnormalities in biopsies were described following the modifi ed Marsh classification (Marsh, 1992; United European Gastroenterology, 2001). CD patients on GFD presented normal mucosal histology and negative anti-transglutaminase antibodies. Two other groups of patients were studied: A) a group of controls with normal biopsy histology, which includes 4 patients, (mean age 27.7 years, range 8–53), who underwent diagnostic investiga- tions due to clinical suspicion of a gastrointestinal disorder which was later ruled out due to the fi nding of a normal biopsy histology, and no signs of intes- tinal infection, infl ammation or allergy (Healthy Control group, HC). B) 2 adult patients (mean age 35 years, range 14–56) with signs of non-specifi c intestinal infl ammation, altered intestinal biopsy histology, and negative both serological markers of CD and the HLA-DQ2 genotype, but presenting small bowel symptoms (Diseased or Pathologic Control group, PC). Informed consent was obtained from patients and/or their parents following the institutional protocols and recommendations, and the study protocol was approved by the ethics com- mittee of the University Hospital. Sample preparation (RNA extraction and cDNA preparation) After collection, samples were immediately sub- merged in 1mL of RNA-Later® solution (Ambion Inc, TX, USA) and stored at −20 °C to preserve RNA integrity until processing. Total RNA was purifi ed from intact biopsy specimens using the TRIZOL® reagent (Invitrogen, Life Technologies, USA). Samples were placed in sterile tubes, sub- merged in 1mL of TRIZOL, and homogenised using a DIAX 900 tissue homogeniser (Heidolph, Germany), followed by the steps detailed in the protocol provided by the manufacturer. Following steps, transcription with annealing by random primers, linear polymerase reaction (LPR) and labelling by means of biotin-16-dUDP, were car- ried out using the SuperScript® First-Stand Syn- thesis System for RT-PCR Kit (Invitrogen, Life Technologies, USA) and SuperArray Ampolabel- ling (LPR) kit, according to the instructions of the manufacturers to produce biotin-labeled probes. Gene expression testing GEArray TM Q Series (SuperArray Bioscence Cop. USA) membranes were used to test human infl am- matory cytokines/chemokines and receptors (HS- 015.2, GEArray® Q Series Human Infl ammatory Cytokines and Receptors Gene Array), and JAK/ STAT pathways and transcription factor molecules 3 Macroarray immune screening of Celiac Disease Drug Target Insights 2008:3 (HS-039, GEArray® Q Series Human JAK/STAT Signaling Pathway Gene Array). The membranes were hybridated with the biotin-labeled probes fol- lowing the manufacturer’s protocol. Previously, a label test was performed by successive dilution of the probes to assess the suitable working dilution. After hybridation step, the membranes were revealed with SuperArray GEArray TM chemilu- miniscent detection kit and autoradiographied. Each kind of Q Series presented 114 clover- shaped dots formed by 4 spots of 60 mer oligonu- cleotids corresponding to 96 specifi c genes, 5 housekeeping genes and blank dots. Infl ammatory cytokines/chemokines and recep- tors membranes allow testing the following specifi c genes expression: BLR1, CCR1, CCR2, CCR3, CCR4, CCR5, CCR6, CCR7, CCR8, CCR9, XCR1, CX3CR1, Chemiokine (CXC) motif Receptor (CXCR) 4, IFNγ, IL-10, IL-10Rα, IL-10Rβ, IL-11, IL-11Rα, IL-12p35, IL-12p40, IL-12Rβ1, IL-12Rβ2, IL-13, IL-13Rα1, IL-13Rα2, IL-15, IL-15Rα, IL-16, IL-17, IL-17R, IL-18, IL-18R1, IL-1α, IL1β, IL- 1R1, IL-1R2, IL-2, IL-20, IL-21, C19orf10, IL- 2Rα, IL-2Rβ, IL-2Rγ, IL-4, IL-5, IL-5Rα, IL-6, IL-6R, IL-6ST, IL-9, IL-9R, Leptin (LEP), Linfo- toxin (LT)α, LTβ, LTβR, MIF, CCL1, CCL11, CCL13, IL-3, CCL15, CCL16, CCL17, CCL18, CCL19, CCL2, CCL20, CCL21, CCL22, CCL23, CCL24, CCL25, CCL3, CCL4, CCL5, CCL7, CCL8, CXCL10, CXCL11, CXCL13, CXCL5, CXCL6, XCL1, XCL2, CX3CL1, Small inducible cytokine subfamily E (SCYE) 1, CXCL12, Stromal cell-derived factor (SDF2), TGFα, TGFβ1, TGFβ2, TGFβ3, TNF, TNFRSF1α y TNFRSF1β. And JAK/STAT pathways and transcription factors membranes, the following: Alpha 2 Macroglobulin (A2M), BCL2-Related Gene (BCL-X), Cyclin D1, Cyclin-dependent kinase inhibitor 1 a (CIP1 o CDKN1A) 1a, CCAAT/Enhacer binding protein beta (CEBPβ), Creb Binding Protein (CREBBP), V-crk sarcoma virus CT10 oncogene holomolog (avian)-like (CRKL), C-reactive protein pentraxin-related (CRP), CSF1R, CSF2RB, Casein beta (CSN2), CXCL9, EGFR, EPOR, Fc Fragment Of IgE High Affi nity I Receptor For alpha subunit (FCER1α), Fc Fragment Of IgE Low Affi nity II Receptor (FCER2), Fc Fragment Of IgG High Affi nity I Receptor For alpha subunit (FCGR1α), Interferon alpha inducible protein clone IFI-6-16 (G1P3), GATA3, Guanylate Binding Protein 1 (GBP1), Interferon Induced Protein IFI-15K (G1P2), High Mobility Group At-Hook 1 (HMGa1), IFNαR1, IFNαR2, IFNγ, IFNγR1, IFNγR2, Immunoglobulin heavy constant delta (IGHD), IL-10Rα, IL-10Rβ, IL-10Rα, IL-22Rα1, IL-2Rα, IL-2Rγ, IL-4, IL-4R, GP130 o IL-6ST, Indoleamine-pyrrole 2,3 dioxy- genase (INDO), IRF1, p48/IRF9, JAK1, JAK2, JAK3, O V-Jun Avian Sarcoma Virus 17 Oncogene Homolog (JUN), JUNB, SMAD1, SMAD2, SMAD3, SMAD4, SMAD5, SMAD6, SMAD7, SMAD9, V-Maf Avian Musculoaponeurotic Fib- rosarcoma Oncogene Homolog (MAF), Cell Divi- sion Cycle 46 (CDC46 o MCM5), MHC Class II Transactivator (MHCIITA), PIAS2, MMP3, Myeloproliferative Leucemia Virus Oncogene (MPL), V-Myc Avian Myelocytomatosis Viral Oncogene Homolog (MYC), Nuclear Receptor Coactivator 1 (NCOA1), NF-κB1, NMYC Interac- tor (NMI), Nitric Oxide Synthase 2A (NOS2A), Oligoadenylate Synthetase 1 (OAS1), OSM, PIAS1, PIAS3, PIAS4, Oncogen PIM1, Protein Tyrosin Phosphatase non receptor type 1 (PTPTN1), PTPNS1, CD45 o PTPRC, Adaptor Protein (SH2B), SOCS1, SOCS2, SOCS3, SOCS4, SOCS5, SOCS6, Specificity Protein 1 (SP1), Hematopoietic transcription factor PU-1, Onco- gene C-Src, Signal Transducing Adaptor Molecule (STAM), STAT1, STAT2, STAT3, STAT4, STAT5A, STAT5B, STAT6, STIP1 Homologous U box containing protein 1 (STUB1), FAS Antigen (FAS), TYK2, Upstream Transcription factor 1 (USF1) and transcription factor YY1. As housekeeping genes: pUC18 (3 dots), Glyc- eraldehyde 3 Phosphate Dehydrogenase (GAPDH, 2 dots), Cyclophilin A (PPIA, 4 dots), Ribosomal Protein L 13a (RPL13A, 2 dots) and β-Actin (2 dots). Densitometric measurements and statistic analysis Films were scanned and processed with GEArray Expression Analysis Suite version 1.0 of Superar- ray Bioscience Corporation, USA (http://geasuite. superarray.com/) for densitometric analysis. The average density of each spot was measured with “clover” mode on. Background was corrected with the “local background” mode. The results were normalized with the housekeeping genes expres- sion. The application considers “absent” gene (non-expressed) when the spot density is lower than the 75 percentile of the average local 4 Garrote et al Drug Target Insights 2008:3 background of the spots non-classified as “bleeding”. The remainders are considered “present” (expressed). Bleeding spots are those ones with an average density higher than the aver- age value of all the spots and that it differs from its local background less than 30%. All genes clas- sifi ed as “absent” or “bleeding” were visually assessed and 0 values was assigned to “absent” ones and the value of the normalized measure of density with the general background correction to “bleeding” ones. Differential gene expression between two groups was carried out by calculating the ratio of the median values of expression for each gene. Genes with a ratio equal or higher than 2 were considered over-expressed, and equal or lower than 0.5 sub-expressed. The statistical signifi cance of these differences was checked by non-parametric tests: Krustall-Wallis and Mann-Whitney U tests. This simple statistical treatment was previously use for a similar approach with microarrays in IBD (Costello, Mah et al. 2005). Results Infl ammatory cytokines and chemok- ines. (Tables 1 and 2) IL-11Rα (r:E/p = 0.005), IL-1R2 (r:12.026/ p = 0.019) and IL-2Rβ (r:E/p = 0.025) genes r e s u l t e d o v e r- e x p r e s s e d a n d n o n e u n d e r- expressed in active Celiac Disease (aCD) as compared with Healthy Controls (HC). However, XCR1, CX3CR1, IL-11, IL-11Rα and MIF are over-expressed in GFD CD small intestine vs HC (r:3.278/p = 0.026, r:E/p = 0.01, r:2.474/p = 0.007, r:E/p = 0.001 and r:2.402/p = 0.01 respectively) and the gene of the chemokine CXCL11 under- expressed (r:0/p = 0.01). IL-1R2 and IL9R resulted over-expressed in aCD when compared with GFD (r:4.974/p = 0.029 and r:E/p = 0.048). When compared with Diseased (pathologic) Controls (PC), CCR9 (r:E/p = 0.027), IFNγ (r:E/p = 0.034), IL-21 (r:13,31/p = 0.005) and IL-5 (r:21,319/p = 0.005) were over-expressed in aCD group. However, only CXCL5 (r:E/p = 0.037) resulted over-expressed in PC as compared with HC, and IFNγ (r:0/p = 0.006), IL-21 (r:0.107/ p = 0.006), IL-5 (r:0.077/p = 0.006) and chemokine CCL17 (r:0/p = 0.017) were under-expressed. JAK/STAT pathway. (Tables 3 and 4) EGFR (r:E, p = 0.045), GATA3(r:E/p = 0.028), HMGA (r:E/p = 0.045), JAK3 (r:E/p = 0.045), JUNB (r:E/p = 0.014), SMAD3 (r:E/p = 0.045), SMAD5 (r:E/p = 0.045), MAF (r:411.205/ p = 0.049), PIM1 (r:17.769/p = 0.014), PTPRC (r:E, p = 0.014), SOCS1 (r:2.642/p = 0.025), SRC (r:E/p = 0.05), STAM (r:E/p = 0.045), TYK2 (r:E/p = 0.045) and YYF (r:E/p = 0.045) were over-expressed in aCD intestinal mucosa as com- pared with HC group, while CCND1 (r:0.174/ p = 0.045) y STAT3 (r:0/p = 0.014) resulted under- expressed. In GFD group, CSF2RB (r:4.154/p = 0.01),CSN2 (r:E/p = 0.008), FCRE2 (r:23.827/p = 0.01), G1P3 (r:29.956/p = 0.01), SMAD2 (r:3.834/p = 0.01), PIAS2 (r:51.937/p = 0.032) and SOCS2 (r:5.405/ p = 0.01) were over-expressed and PTPNS1 (r:0/ p = 0.008), STAT3 (r:0/p = 0.023) and STAT5A (r:0/p = 0.023) under-expressed when compared with HC group. When compared aCD and DSG groups, we found GATA3 (r:E/p = 0.038), IL6ST (r:E/ p = 0.038), JUNB (r:E/p = 0.038), MCM5 (r:E/ p = 0.038), NF-κB1 (r:E/p = 0.013), PIAS4 (r:E/ p = 0.038), PIM1 (r:E/p = 0.013), PTPNS1 (r:E/ p = 0.023), PTPRC (r:E/p = 0.038), SRC (r:E/ p = 0.038) and FAS (r:E/p = 0.038) over-expressed in aCD group and CCND1 (r:0.185/p = 0.046), EPOR (r:0.355/p = 0.046), FCER2 (r:0.044 p = 0.003) and IL-10Rα (r:0/p = 0.038) under- expressed. SMAD2, MAF and PTPRC are also over- expressed in aCD group vs PC group (r:E/ p = 0.038, r:E/p = 0.003 y r:E/p = 0.038) respec- tively, and CCND1 (r:0.156/p = 0.013), STAT2 (r:0.346/p = 0.052) under-expressed. And PC group had GATA3 (r:0/p = 0.006) and OSM (r:2.162/p = 0.011) over-expressed, and STAT3 and STAT5A (r:0/p = 0.023 and r:0/p = 0.023, respectively) under-expressed when compared with HC group. Discussion Expression arrays techniques have resulted important tools in genomic studies, such as in positional genetics as in the study of tissues physiology and in the changes induced by disease in them. However, these techniques are susceptible of methodologic and interpretative variability, resulting in an obstacle for fi ndings reproducibility 5 Macroarray immune screening of Celiac Disease Drug Target Insights 2008:3 Table 1. Medians fold ratios (mARN) and p values of comparations amongst groups of expression of Cytokines and Chemokines genes. Gen p(total)*= aCD/HC p*= GFD/ HC p*= PC/HC p*= aCD/ GFD p*= aCD/PC p*= CCR9 0.069 4.660 0.109 3.369 0.192 0 0.113 1.382 E 0.027 XCR1 0.106 0.297 0.569 3.278 0.026 0.729 0.090 0.271 0.408 CX3CR1 0.039 NE E 0.01 NE 0 0.339 NE CXCR4 0.194 NE E 0.153 NE 0 0.213 NE IFNG 0.086 0.898 1.405 0 0.006 0.639 E 0.034 IL10RA 0.382 0.705 1.611 0 0.256 0.437 0.373 E 0.174 IL11 0.252 1.697 2.474 0.007 2.136 0.865 0.685 0.794 IL11RA 0.02 E 0.005 E 0.01 NE 4.191 0.322 E 0.162 IL12B 0.133 NE E 0.071 NE 0 0.908 NE IL16 0.231 NE E 0.198 NE 0 0.817 NE IL17R 0.121 1.021 1.413 0.406 0.174 0.722 2.509 0.103 IL1R1 0.34 0 0.403 1.033 0 0.053 0 0.087 NE IL1R2 0.101 12.026 0.019 2.417 1 10.193 0.468 4.974 0.029 1.179 IL21 0.016 1.424 1.403 0.107 0.006 1.015 13.310 0.005 IL2RB 0.079 E 0.025 NE NE E 0.811 E 0.099 IL4 0.2 E 0.097 E 0.198 NE 10.576 0.436 E 0.131 IL5 0.041 1.659 1.293 0.077 0.006 1.283 21.319 0.005 IL5RA 0.22 1.973 1.389 0 0.124 1.420 E 0.083 IL9R 0.163 E 0.153 NE NE E 0.048 E 0.481 LEP 0.384 NE E 0.391 NE 0 1 NE LTA 0.836 0.897 2.347 3.425 0.61 0.382 0.514 0.262 1 LTB 0.457 1.415 1.021 0.315 0.126 1.385 4.486 0.247 LTBR 0.269 NE E 0.153 NE 0 0.081 NE MIF 0.178 0.714 2.402 0.01 1.653 0.297 0.126 0.432 1 CCL1 0.2 2.376 0.091 1.558 0.914 1.524 2.598 0.12 CCL15 0.242 1.132 1.144 0.152 0.126 0.989 7.418 0.065 CCL16 0.665 NE E 0.382 E 0.449 0 0.271 0 0.51 CCL17 0.123 0.629 0.571 0 0.017 1.101 E 0.24 CCL18 0.698 0 0.922 0.366 0.893 0 0.256 0 0.728 NE CCL21 1.247 1.301 1.639 0.958 0.760 CCL22 0.486 0.357 0.619 1.521 0.541 0.234 0.322 0.660 CCL23 1.142 1.129 1.059 1.011 1.078 CCL24 0.736 0.273 0.39 1.419 2.400 0.864 0.192 0.271 0.114 0.651 CCL25 0.275 NE E 0.215 NE 0 0.643 NE CCL4 0.088 1.388 0.566 1.332 2.450 0.051 1.041 CXCL11 0.071 0 0.306 0 0.01 0.792 NE 0 0.546 CXCL13 0.271 1.873 2.476 0.396 2.301 0.396 0.756 0.814 CXCL5 0.174 NE NE E 0.037 NE 0 0.168 CXCL6 0.545 3.345 0.18 0.315 0.231 6.646 0.231 10.589 0.444 0.503 XCL1 0.82 E 0.363 NE NE E 0.633 E 0.695 SCYE1 0.258 0 0.063 0.218 0.235 0.343 0.3 0 0.473 0 0.539 CXCL12 0.544 0 0.204 6.617 0.687 2.597 0.856 0 0.213 0 0.479 SDF2 0.325 0.413 1 1.449 0 570 0.285 0.155 E 0.365 TGFA NE NE E 0.686 NE 0 0.288 TNF 0.228 0 0.41 0.777 2.873 0.73 0 0.356 0 0.156 TNFRSF1B 0.549 NE NE E 0.705 NE 0 0.156 p*(total): Krustal-Wallis test (p � 0.05); p: Mann-Whitney non parametric test (p � 0.05); E: Overexpression with divisor = 0; NE: Non expressed. Red case, over-expression. White case, 2�Ratio�0.5. Green case: under-expression. aCD: Active Celiac Disease; GFD: Celiac patients on Gluten Free Diet; PC: Pathological Contols; HC: Healthy Contols. 6 Garrote et al Drug Target Insights 2008:3 and comparison amongst different laboratories (Li, Gu et al. 2002). Low density arrays or macroarrays are more user-friendly variants than microarrays, designed specifi cally for one system or pathway, to explore some tens or a few hundreds of genes. However we have not to forget that both versions are screening tools, and that the fi ndings should be considered as a fi rst approach, and susceptible of been validated by other techniques. This technique has been used by numerous research groups and its limitations are well known. We have experienced the lack of sensitivity to detect signal of genes with low level of expression. Perhaps, increasing the number of cycles of the sample ampli- fi cation, it would be possible to achieve the number of copies and to enhance the performance of the hybridation. Another pitfall for sensitivity is the use of intact whole tissue (intestinal mucosa in our case). In this case the coexistence of multiple cell lineages would tend to mask some changes of expression in one of the lineages. This technique shows better performances with homogeneous samples (of one cell lineage)(Torres-Munoz, Stockton et al. 2001). We found an inter-assay variability for the same sample similar to the intra-assay one (determined for housekeeping genes -Data not shown-) in an accept- able range. However, we found a wide biological variability for each one of the analytes amongst the several samples of the same group, what claims for a higher casuistic for more robust results. We should not forget that arrays techniques were designed with the aim of detect wide variations in the expression of multiple genes, to determine pathways or patterns of gene activation/repression with gross differences (being used inicially in oncology). This means, wide changes in multiple related genes behaviour, in a parallel manner, and not to observe individual differences in one gene separately. We have tried to extrapolate from this use to a group of diseases with subtler changes, and we have found that the sensitivity of the technique result a limiting factor. Complex tissues tend to buffer the changes in one of its several components versus to very homogeneous tissues, as tumors are. On the other hand, the quantity of the difference of gene expression used to be lower in diseases non so extrem as neoplastic tissues. As a consequence of all the previously exposed, we have not pretended to draw any conclusion about isolated molecules, but to get an overall view of the immunologic activity in each group of patients, regarding to the cytokine/chemokine pat- tern and the activation pathways activated. The quantitative expression analysis of cytokine and chemokines in intestinal mucosa mucosa shows that, although Th1 pattern factors are expressed, Th2 pattern related molecules have also a role in active CD intestinal mucosa. Cytokine receptor IL-11Rα, IL-1R2 and IL-2R gene expres- sion is increased in active EC as compared with healthy controls and IL9R as compared with CD Table 2. Resume of molecules with differential expression between groups, by functional families in cytokines/ chemokines array. r: fold ratio. p: statistical signifi cance by Mann-Whitney test. Gene aCD vs HC GFD vs HC aCD vs GFD PC vs HC aCD vs PC IFNγ r:0/p = 0.006 r:E/p=0.034 IL-5 r:0.077/p = 0.006 r:21.319/p = 0.005 IL-11 r:2.474/p = 0.007 IL-21 r:0.107/p = 0.006 r:13.31/p = 0.005 MIF r:2.402/p = 0.01 IL-1R2 r:12.026/p = 0.019 r:4.974/p = 0.029 IL-2Rβ r:E/p = 0.025 IL-9R r:E/p = 0.048 IL-11Rα r:E/p = 0.005 r:E/p = 0.001 CCL17 r:0/p = 0.017 CXCL11 r:0/p = 0.01 CXCL5 r:E/p = 0.037 CCR9 r:E/p = 0.027 XCR1 r:3.278/p = 0.026 CX3CR1 r:E/p = 0.01 7 Macroarray immune screening of Celiac Disease Drug Target Insights 2008:3 Table 3. Medians fold ratios (mARN) and p values of comparations amongst groups of expression of JAK/STAT pathway genes. Gen p(total)*= aCD/HC p*= GFD/HC p*= PC/HC p*= aCD/GFD p*= aCD/PC p*= CCND1 0.028 0.174 0.045 0.938z 1.114 0.185 0.046 0.156 0.013 CEBPB 0.332 0 0.286 0 0.116 3427.909 0.82 NE 0 0.339 CREBBP 0.17 NE NE E 0.068 NE 0 0.577 CSF2RB 1.922 4.154 0.01 2.533 0.392 0.462 0.051 0.758 CSN2 0.145 E 0.217 E 0.008 E 337 0.256 0.135 0.323 0.796 CXCL9 0.161 E 0.11 NE E 0.19 E 0.094 0.656 EGFR E 0.045 NE E 0.068 E 0.094 0.222 0.796 EPOR 0.546 1.537 0.998 0.355 0.046 0.547 FCER2 0.004 1.071 23.827 0.01 0 0.055 0.044 0.003 E 0.094 G1P3 0.219 22.143 0.252 29.956 0.01 24.927 0.087 0.739 0.888 GATA3 0.005 E 0.028 NE E 0.006 E 0.038 0.291 0.143 GBP1 0.161 E 0.11 NE E 0.19 E 0.094 0.667 G1P2 0.239 E 0.217 NE E 0.337 E 0.094 0.412 0.796 HMGA1 0.079 E 0.045 NE E 0.068 E 0.094 0.048 IFNGR2 0.489 E 0.303 NE E 0.19 E 0.094 0.169 0.796 IGHD 0.326 NE NE E 0.19 NE 0 0.577 IL10RA 0.189 NE E 0.078 E 1 0 0.038 0 1 IL4R 0.369 169.793 1 271.786 0.392 162.841 0.66 0.624 0.051 1.042 IL6ST 0.219 E 0.433 NE E 0.337 E 0.038 0.775 JAK3 0.083 E 0.045 NE E 0.063 E 0.094 0.080 0.796 JUNB 0.014 E 0.014 NE E 0.068 E 0.038 3.027 0.135 SMAD2 0.032 1.918 3.864 0.01 0 0.055 0.496 0.392 E 0.038 SMAD3 0.036 E 0.045 NE NE E 0.094 E 0.094 SMAD5 0.036 E 0.045 NE NE E 0.094 E 0.094 SMAD9 0.234 E 0.695 NE E 1 E 0.038 0.793 MAF 0.008 411.205 0.049 221.186 0.392 0 0.055 1.859 E 0.003 MCM5 0.164 27.868 1 0 0.055 14.565 0.66 E 0.038 1.913 MHC2TA 0.12 0 0.764 0 0.055 0 0.055 NE NE PIAS2 0.21 12.883 0.845 51.937 0.032 11.865 0.66 0.248 0.319 1.085 NFKB1 0.118 21.944 0.572 0 0.055 19.626 0.66 E 0.013 1.118 NMI 0.445 E 1 NE E 1 E 0.094 0.258 0.796 NOS2A 0.084 0 0.217 0 0.055 0 0.055 NE NE OAS1 0.171 E 0.681 NE NE E 0.094 E 0.094 OSM 0.071 1.037 1.587 2.162 0.011 0.653 0.479 0.052 PIAS4 0.041 4.337 1 0 0.055 7.143 0.392 E 0.038 0.607 0.051 PIM1 0.014 17.769 0.014 0 0.055 6.144 0.66 E 0.013 2.891 0.222 PTPNS1 0.044 3.327 1 0 0.008 0.681 E 0.023 4.882 0.11 PTPRC 0.006 E 0.014 NE NE E 0.038 E 0.038 SOCS1 0.121 2.642 0.025 1.701 2.514 0.087 1.552 1.050 SOCS2 0.041 3.996 0.09 5.405 0.01 2.824 0.087 0.739 1.414 SOCS4 0.114 E 0.537 E 0.187 NE 0.269 0.262 E 0.094 SP1 0.709 2.669 0.349 2.100 0.394 2.115 0.394 1.271 1.262 SRC 0.07 E 0.05 NE E 0.337 E 0.038 0.338 0.618 STAM 0.036 E 0.045 NE NE E 0.094 E 0.094 STAT2 0.790 1.228 2.279 0.088 0.643 0.346 0.052 STAT3 0.008 0 0.014 0 0.023 0 0.023 NE NE STAT4 0.077 1.176 0 0.055 0 0.055 E 0.094 E 0.094 STAT5A 0.018 0.171 0.101 0 0.023 0 0.023 E 0.094 E 0.094 STAT5B 0.228 0 0.123 0 0.116 3.612 0.82 NE 0 0.339 STUB1 NE NE E 0.068 NE 0 0.658 FAS 0.166 E 0.695 NE E 0.379 E 0.038 1.399 TYK2 0.036 E 0.045 NE NE E 0.094 E 0.094 YY1 0.036 E 0.045 NE NE E 0.094 E 0.094 p*(total): Krustal-Wallis test (p � 0.05); p: Mann-Whitney non parametric test (p � 0.05); E: Overexpression with divisor = 0; NE: Non expressed. Red case, over-expression. White case, 2�Ratio�0.5. Green case, under-expression. aCD: Active Celiac Disease; GFD: Celiac patients on Gluten Free Diet; PC: Pathological Contols; HC: Healthy Contols. 8 Garrote et al Drug Target Insights 2008:3 Table 4. Resume of molecules with differential expression between groups, by functional families of JAK/STAT pathway array. r: fold ratio. p: statistical signifi cance by Mann-Whitney test. Gene aCD vs HC GFD vs HC aCD vs GFD PC vs HC aCD vs PC STAT2 r:0.346/p = 0.052 STAT3 r:0/p = 0.014 r:0/p = 0.023 r:0/p = 0.023 STAT5A r:0/p = 0.023 r:0/p = 0.023 GATA3 r:E/p = 0.028 r:E/p = 0.038 r:0/p = 0.006 JUNB r:E/p = 0.014 r:E/p = 0.038 MAF r:411.205/p = 0.049 r:E/p = 0.003 NFkB1 r:E/p = 0.013 SMAD2 r:3.834/p = 0.01 r:E/p = 0.038 SMAD3 r:E/p = 0.045 SMAD5 r:E/p = 0.045 PIAS2 r:51.937/p = 0.032 PIAS4 r:E/p=0.038 SOCS1 r:2.642/p = 0.025 SOCS2 r:5.405/p = 0.01 JAK3 r:E/p = 0.045 TYK2 r:E/p = 0.045 PIM1 r:17.769/p = 0.014 r:E/p = 0.013 SRC r:E/p = 0.05 r:E/p = 0.038 FAS r:E/p = 0.038 EGFR r:E. p = 0.045 CSF2Rb r:4.154/p = 0.01 FCRE2 r:23.827/p = 0.01 r:0.044/p = 0.003 EPOR r:0.355/p = 0.046 IL-10Ra r:0/p = 0.038 IL-6ST r:E/p = 0.038 CD45/PTPRC r:E. p = 0.014 r:E/p = 0.038 r:E/p = 0.038 PTPNS1 r:0/p = 0.008 r:E/p = 0.023 G1P3 r:29.956/p = 0.01 OSM r:2.162/p = 0.011 STAM r:E/p = 0.045 YYF r:E/p = 0.045 HMGA r:E/p = 0.045 CCDN1 r:0.174/p = 0.045 r:0.185/p = 0.046 r:0.156/p = 0.013 CSN2 r:E/p = 0.008 MCM5 r:E/p = 0.038 9 Macroarray immune screening of Celiac Disease Drug Target Insights 2008:3 patients in remission. Both IL-11Rα and IL-9R are receptors related to Th2 response regulation. IL-11 is regulated by the antiinfl ammatory cytokine IL10. IL-9 is growth factor whose receptor is expressed in eosinophils, very abundant in CD intestinal mucosa, and it may contribute synergically with IL-13 to mucosal infl ammation. This double faced immune pattern may be also found in ulcerative colitis, whose immune pattern is simplistically described as Th2, but it shows increased presence of typically Th1 cytokines in injured colonic mucosa (Gordon, Di Sabatino et al. 2005). Cytokines IFNγ, IL-21 and IL-5 genes seem specifi cally expressed in active CD mucosa, but not in diseased controls. IL-5 also is a cytokine related to the regulation of eosinophil activation, as IL-9, and it is a paradigmatic component of Th2 pattern (Broide, Hoffman et al. 1999). The presence of IL-5 in CD is controversial. It has not been found in CD intestinal mucosa by some authors (Nilsen, Johansen et al. 1998), but described by others (Desreumaux, Delaporte et al. 1998). IL-21 is a cytokine that modules as Th1 immune response as Th2 type, and it has been related to innate immune response and NK cells activity (Mehta, Wurster et al. 2005). IL-21 gene maps in a genome region that recently has been described as linked to CD susceptibility (van Heel, Franke et al. 2007), and its expression has been found increased in CD. IFNγ has been yet previous described as the main cytokine responsible of mucosal damage in CD (Wapenaar, van Belzen et al. 2004; Leon, Sanchez et al. 2005; Leon, Garrote et al. 2006), but not specifi c of this disease. There are also other target genes involved in the in active phase of this enteropathy, as IL-1R2 or IL-2Rβ. IL-1R2 is a receptor induced by IL-4, and it might have a role in negative regulation of IL-1 expression (Colotta, Re et al. 1993). IL-2Rβ is the signal transducer of IL-2 and IL-15, and it is an important receptor as in innate as in adaptive response, controlling T lymphs expansion and autoimmunity (Suzuki, Kundig et al. 1995). Surprisingly, in the group of CD patients in GFD, we found overexpression in a group of chemokine receptor genes related to dendritic cell (DC) functionality: CX3CR1 y XCR1. The fi rst one is expressed in monocytes, NK and memory cells (Sozzani, Allavena et al. 1999) and it is involved in the emission of transepithelial den- drites by CDs, with the possible function of sam- pling antigens in gut lumen, with the consequent impact in infl ammation or tolerance triggering (Niess, Brand et al. 2005; Rescigno and Chieppa, 2007). XCR1 is the receptor for lymphotactin, highly expressed by myeloid cells and chemoat- tractant of NK cells and T lymphocytes, amongst other non well known actions (Luttichau, Johnsen et al. 2007). These expressions might indicate an increased basal activity of DC’s in CD, even in remission. There are other proinfl ammatory factors over- expressed in GFD CD patients as the macrophage migration inhibitory factor (MIF). This molecule is involved in infl ammatory and autoimmune proc- esses. A polymorphism in the gene promoter of MIF has been related to CD genetic susceptibility (Nunez, Rueda et al. 2007). In contrast with our results, O’Keeffe et al. found overexpression of MIF in intestinal epithelial cells of active CD patients (O’Keeffe, Lynch et al. 2001). Cytokines, chemokines and growing factors regulate large aspects of hematopoiesis and immune response through interaction with their specific receptors. These ones trigger their responses through signalling pathways activity. In our results, we fi nd overexpressed molecules of pathways related to Th2 pattern in active CD intestinal mucosa. There is an increase in the expression of GATA3 and JUNB genes in the group of active CD patients as compared with healthy control group or GFD group. GATA3 mediate in the Th1 pattern inhibition and Th2 induction. JUNB and MAF (also overexpressed in aCD group) are also related with NF-kB activity. MAF seems spe- cifi c of CD in activity, with and increased expres- sion above healthy or diseased controls. It is an activating factor of cell differentiation (Blank and Andrews, 1997), and also promoter of Th2 immune response, through IL4 gene upregulation (Valan- ciute, le Gouvello et al. 2004). MAF expression is controlled by NF-kB (Nenci, Becker et al. 2007). JUNB is an oncogene, member of AP-1 family of transcription factors. When T lymphs are stimulated the degradation process of JUNB is increased, controlling the cytokine production of effector T cells (Gao, Labuda et al. 2004). JUNB is also capa- ble of inducing proinfl ammatoy response through NF-kB activation (Mathas, Hinz et al. 2002). GATA3 and STAT6 compose a tandem that induces the polarization of Th0 lymphocytes towards Th2. In previous studies no differences have been found between CD patients and controls in GATA3 expression (Monteleone, Monteleone et al. 2004). 10 Garrote et al Drug Target Insights 2008:3 The oncogene SCR codifi es for a kinase that has been related with several signalling pathways of some importance in cell growth, migration or cell survival. It is activated by several kinds of receptors: integrins, cytokines or growing factors and it is a factor in charge of regulating the cell communication for cell growth (Azarnia, Reddy et al. 1988), in relation with TRANCE, a family member of TNF (Wong, Besser et al. 1999). Experiments of in vitro inhibition of scr in intes- tinal epithelial cell lines have resulted in a paral- lel decrease of stat3, an important mediator of the antiapoptotic response. So, SCR expression prevents cell apoptosis, increasing the mucosal infl ammation (Bhattacharya, Ray et al. 2006). We fi nd increased expression of SCR gene in the group of active CD compared with diseased controls. In CD patients in remission (GFD), we fi nd a decrease in STAT3 and STAT5 expression, with an increase in SOCS2, SMAD2 and PIAS2 as com- pared to healthy controls. STAT3 is related to signal transmission of cytokine receptors sharing gp130 (IL-6, IL-11, IL-12 or IL-23 receptors), while STAT5 is related to some members of γC receptor family (IL-2, IL-9 or IL-21 receptors) or to the single chain receptor family (EPO, GH or prolactine receptors). STAT3 pathway activity and its fi nal actions on gene expression is modulated by SOCS3 and IL-10 (Kinjyo, Inoue et al. 2006; Qasimi, Ming-Lum et al. 2006). STAT3 pathway activation had been previously described in Infl am- matory Bowel Disease and in EC (Mazzarella, MacDonald et al. 2003; Musso, Dentelli et al. 2005) and it may mediate in IL-17 production. SOCS2 increased expression might explain the decrease of STAT5 expression, as SOCS2 down- regulates gene products that activate STAT5 (IL-6, IL-9, EPO or GH), and it may result the key for intestinal inflammation controlling in these patients. PIAS2 product is a nuclear level inhibitor of STAT4 (Chen, Daines et al. 2004), and down- regulator of proinfl ammatory genes expression. SMAD2 is a positive transcription factor in TGFβ signalling pathway (Becker, Fantini et al. 2006), the main regulatory cytokine in intestinal mucosa. Diseased controls present an expression pattern of the molecules of the activation pathways between the patients with active CD and patients in GFD, with an increase of GATA3 expression, but a low expression of STAT3 or STAT5. In conclusion, active CD seems to show a Th1 cytokine pattern, but with signs of Th2 activity. Cytokines such as IL-9, IL-11, IL-21 or MIF might be involved in mucosal infl ammation in CD. In spite of the mucosal recovery following GFD, some memory cells and DC’s activity remains, and factors that maintain this remnant activation might be responsible of the fast mucosal response on gluten challenge, and they should be inquired. STAT3 and STAT5 pathways, and their regulatory molecules SOCS's may result keys for understand- ing mucosal infl ammation in gut and putative targets for research. 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