Differential Intestinal Mucosa Transcriptomic Biomarkers for Crohn's Disease and Ulcerative Colitis.
Inflammatory bowel diseases (IBD) are a distinct class of gastrointestinal diseases mainly represented by Crohn's disease (CD) and ulcerative colitis (UC). These are chronic diseases characterized by a relapsing remitting course with an increasingly high incidence and prevalence worldwide . The current accepted model for IBD etiology implies the existence of a genetic predisposition, perturbations in the intestinal barrier components, and altered microbiota, which combined will lead to an aberrant immune response . Distinguishing between the two diseases represents a problem in clinical practice due to some similarities in endoscopic and morphological aspects which in turn will lead to a change in diagnosis throughout the course of disease . However, some fundamental differences between CD and UC have been reported: UC is characterized by diffuse inflammation confined to the colorectal mucosa, whereas in CD, the inflammation is discontinuous, transmural, and can affect the entire gastrointestinal tract. Moreover, CD patients often present complications like intestinal strictures, fistulas, and abscesses . Despite these differences, physiopathological mechanisms, clinical criteria, and therapeutical strategies considerably overlap, but CD and UC seem to be triggered and maintained by differential molecular mechanisms, which are not completely known.
Genetic studies in IBD have gained importance during the past decade since endoscopic assessment and biopsies provide limited data regarding early disease activity and factors for relapse. The candidate gene approach, genome wide association studies, and meta-analyses have contoured the genetic background of these disorders, revealing more than 200 risk loci in both European and non-European individuals . However, previous studies showed that many of these loci are shared between CD and UC , and no specific genetic markers entered clinical practice yet.
A number of candidate gene expression studies, RNA sequencing, and microarray studies on mucosa from IBD patients have been published in the last years with the attempt to find a specific profile able to discriminate UC and CD. Gene expression analysis of tissue samples from affected and nonaffected individuals can help in discovering important events involved in disease pathogenesis. For example, individual mRNA levels can be sensitive markers for improving classification and diagnosis, identifying new therapeutic targets, and providing prognostic information .
Studies conducted so far analyzing the expression levels of cytokines and transcription factors in mucosa revealed that CD has been associated with an impairment of Th1/ Th17 response , whereas UC has been associated with a Th2/NKT cell response . Other genes have been indicated as putative differential biomarkers, including [alpha]-defensin-5 , circadian genes , TNFAIP3, PIGR, TNF, and PIGR . Other studies based on RNA-seq approaches revealed important transcriptomic differences between normal mucosa, noninflamed CD mucosa, and inflamed CD mucosa  as well as differences among colon biopsies from CD patients, UC patients, and non-IBD controls .
In this study, we aimed to identify the inflammatory signature specific for UC and CD both in endoscopically inflamed and not inflamed mucosa and how the type of therapy can influence the gene expression profile in Romanian patients. To address these questions, we evaluated the gene expression profile of a panel of 84 selected genes (previously associated to IBD) in paired mucosa samples of 21 UC and 22 CD patients, and we compared them with the profiles obtained in a group of 21 non-IBD healthy controls.
2. Materials and Methods
2.1. Patients. Forty-three IBD patients (21 UC and 22 CD) and 21 non-IBD controls have been enrolled in the study at the Department of Gastroenterology and Hepatology, "Elias" Emergency University Hospital and at the "Fundeni" Clinical Institute of Bucharest, Romania. In terms of disease location, patients with CD had colonic and ileocolic forms of the disease. All the patients and controls were of Romanian origin. Written informed consent was obtained from all participants prior to biopsy collection, and the study was approved by the local ethics committees. The diagnosis had been made based on clinical, endoscopic, and histological criteria according to European Crohn's and Colitis Organization Guidelines . From each UC and CD patients, paired colonic inflamed mucosa (IM) and macroscopically colonic noninflamed mucosa (NM) were obtained during a colonoscopy. We defined the inflammation status based on the presence of erythema, ulcerations, and bleeding of the mucosa. A biopsy of a normal-looking colonic mucosa was obtained also from a group of non-IBD controls during a colonoscopy screening. Exclusion criteria for non-IBD controls were as follow: (1) presence of digestive symptoms, (2) current or previous nonsteroidal anti-inflammatory treatments (within the past 3 months), and (3) current or previous anticoagulant/antiplatelet treatments (within the past 3 months). The characteristics of the three groups are reported in Table 1.
2.2. Total RNA Isolation and qPCR. Total RNA isolation from fresh-frozen tissues preserved in RNA later was performed using RNeasy mini Kit (Qiagen), according to the manufacturer's protocols. The quantity and quality of RNA were determined using the NanoDrop 2000 (Thermo Scientific). An amount of 600 ng of RNA was reverse transcribed to cDNA using the RT2 First Strand Kit (Qiagen). The Human Crohn's Disease RT2 Profiler PCR Array (PAHS169Z, Qiagen), using SYBR Green chemistry, evaluated the expression of 84 key genes, according to the manufacturer's protocol, on the ABI-7500 fast instrument (Applied Biosystems). The expression levels of each gene were normalized on the geometric mean values of two housekeeping genes (GAPDH and HPRT1) based on RefFinder algorithm (http://leonxie.esy.es/RefFinder/)  analysis of five candidate reference genes (ACTB, B2M, GAPDH, HPRT1, and RPLP0).
2.3. Statistical Analysis. qRT-PCR data analysis was conducted using the Statistical Package for Social Science (SPSS version 17.0). Categorical variables were tested by means of the chi-square test, and continuous variables with the t-test. Paired t-test was used to assess difference in gene expression levels of IM and NM.
The group of patients and controls was homogeneous for age (p > 0.05) and sex ([chi square] = 4.880, p = 0.087) distribution, and the UC and CD groups did not statistically differ for the class of treatment ([chi square] = 6.409, p = 0.171).
3.1. Gene Expression Alterations in Paired Inflamed and Noninflamed Mucosa of UC and CD Patients. Gene expression analysis was performed on 21 pairs of tissues representing IMUC and NMUC and 22 pairs of tissues representing IMCD and NMCD. In IM, 11 genes out of 84 were found differentially overexpressed both in UC and CD compared with the paired NM. Thirty-three transcripts were found specifically altered only in UC patients (two downregulated and 31 upregulated). Results are shown in Table 2.
3.2. Gene Expression Alterations in CD and UC Patients Compared with Non-IBD Controls. Gene expression analysis was performed on 21 noninflamed and inflamed mucosa from UC patients, 22 from CD, and 21 from healthy controls. Considering a fold change (FC) > [absolute value of 2.0] and a p value below 0.05, 32 genes out of 84 were found differentially expressed both in UC and CD compared with C (two downregulated and 30 upregulated), and 17 were specifically altered only in UC patients (four downregulated and 13 upregulated). No gene was found modified only in CD. When comparing the NM tissues vs. C, we found two transcripts upregulated in UC and five upregulated in CD (Table 3). A graphic representation of the results is shown in Figure 1. Genes whose expression differed between NM and controls and are also different comparing paired IM-NM are shown in Figures 2(a) and 2(b).
3.3. Differences in Gene Expression in IBD Patients on Different Treatments. Due to the limited sample size of the UC and CD groups, we analyzed the treatment effect on gene expression levels considering the entire IBD cohort. Comparing the patients treated with 5-ASA (n = 21) vs. drug-free patients (n = 7), we found that ISG15 ubiquitin-like modifier (ISG15) was downregulated both in inflamed and not inflamed tissues with FC and p value of -2.04, p = 0.003 in IM and -1.84, p = 0.033 in NM. Moreover, we found that the six patients with biologic treatment showed lower levels of serum amyloid A1 (SAA1) with FC of -6.66 and p = 0.025 in IM.
Comparing patients with biological treatment vs. 5-ASA, we found that CCR1 was upregulated in IM with FC = 2.1 and p = 0.005 and TFF1 was downregulated both in IM and NM with FC = -2.5, p = 0.001 and FC = -2.4, p = 0.004, respectively.
Despite the limited size of the two groups, an additional analysis to find a putative effect of the treatment on the candidate genes (IL1RN and C4BP4 for UC and CCL11 and MMP10 for CD) has been performed separately both on UC and CD groups. No changes in IL1RN and C4BP4 levels were found between the three UC patients without treatment and the UC patients in treatment with 5-ASA (p = 0.704, p = 0.718), biological treatment (p = 0.384, p = 0.567), or polytherapy (p = 0.891, p = 0.680). In the CD group, no difference in CCL11 and MMP10 was found comparing the four patients without treatment and the other groups (p > 0.05 in all the comparisons). However, a trend toward significance was observed in MMP10 levels comparing the 4 CD patients without treatment and the group of the seven patients using 5-ASA (p = 0.056).
Overlapping features have been reported in up to 30% of IBD  leading to a not accurate diagnosis and increasing the risk of inappropriate treatment. In this study, we sought to determine whether mucosal gene profile could be used to develop diagnostic biomarker(s) to discriminate between the two main inflammatory bowel diseases (UC and CD) more accurately.
To the best of our knowledge, this is the first study that evaluated 84 transcripts by qRT-PCR considering a larger cohort of participants than previous studies, including paired inflamed and not inflamed tissues from CD and UC as well as a cohort of non-IBD controls.
Using this approach, we identified 17 genes differentially expressed only in the inflamed mucosa from UC that did not differ for the CD patients. A common signature of 32 genes was identified, and no gene specific for CD inflamed mucosa was found.
Among the genes belonging to the common signature, five and two were found differentially expressed comparing the not inflamed mucosa with mucosa from non-IBD controls of CD and UC, respectively.
Interestingly, in UC, CCL11 and MMP10 were increased substantially in non-IBD controls, NM and IM, whereas in CD, this increase was observed for C4BPB and IL1RN. Hence, these four genes seem to be specific markers of UC and CD inflammation levels.
Eotaxin-1 (CCL11), a potent eosinophil chemoattractant that is considered a major contributor to tissue eosinophilia, is a key regulator of intestinal inflammation  and seems to be involved both in UC and CD. Indeed, unlike other chemokines, the human mRNA for eotaxin-1 is constitutively expressed in the small intestine and colon  where the intestinal myeloid cells seem to be a source .
Levels of eotaxin-1 have been found increased in sera from UC patients [19-21] as well as in colon biopsies . In line with our findings that suggested an increase according to the inflammation status, a significant increase of its levels was found in patients with active UC but not in the quiescent state . These data suggest that also the peripheral levels may increase accordingly to the inflammation grade as we observed in mucosa.
Increased levels of eotaxin-1 have been found also in the sera from CD patients [19, 20], and our group found that its mucosal mRNA levels were higher in active CD than in controls. However, no changes were observed in the remission state  or in UC .
Another transcript having a similar trend like CCL11 in UC was MMP10. MMP10 belongs to the human matrix metalloproteinases family consisting of 24 zinc-dependent endopeptidases and is produced by infiltrating myeloid cells. Their levels are transcriptionally upregulated in response to proinflammatory cytokines, and both transcripts and protein levels of some MMPs are demonstrated to be upregulated in inflamed mucosa or serum of IBD patients [26, 27] even in the naive to treatment subgroup . In addition, increased expression of epithelial MMP10 has been found in colonic mucosa of both UC and CD pediatric patients compared to non-IBD patients . MMP10 was seen as a possible therapeutic target in IBD because its expression had been observed close to the edges of healing ulcers in human specimens of UC . Its influence, however, can be debated since it could have a role in disease resolution but also in the proinflammatory process. In animal models of experimental colitis, MMP10 seems to promote mucosal healing, and in its absence due to persistent colonic inflammation, dysplastic lesions could be promoted . Human genetic studies identified six SNPs across the MMP10 gene associated with UC, suggesting that these genetic variants may play a role in UC susceptibility and clinical outcome .
Moving forward to the specific genes associated to CD in our cohort, C4BPB and IL1RN, they will be discussed below.
The C4BPB gene encodes for C4b-binding protein, a multimeric protein that controls the complement cascade. There is one single study for this gene in CD which evaluated the serum level of C4BPB in patients treated with infliximab, revealing that upregulation of this protein is associated with primary nonresponse to this treatment . Our investigation took into account current biologic treatment, but none of the patients included had had a nonresponse status declared. Thus, we can only suggest that increased expression can only be attributed to the inflammatory process.
Finally, our analysis associated the IL1RN (interleukin 1 receptor antagonist) gene with inflammation in CD. The IL1RN gene encodes for a protein member of the interleukin 1 cytokine family. This protein inhibits the interleukin 1 alpha and beta activities and modulates a variety of related immunoinflammatory responses.
Discordant results regarding the associations between IL1RN genetic variants and IBD have been published. Some studies reported significant associations with CD [34, 35] and UC predispositions [36, 37], treatment outcome , and age at the onset ; on the contrary, other studies did not find any associations [40-42]. Interestingly, IL-1RN*2 variant has been associated with reduced levels of IL-1ra protein and IL-1RN mRNA in the colonic mucosa from UC patients .
Summarizing, against our expectations, only four putative candidate biomarkers able to discriminate UC and CD were found. This can be due to the large gene expression intravariability observed both in the colonic mucosa from non-IBD and IBD groups. Indeed, due to a number of parameters not yet included (histologically active/in remission, duration, and response to treatment), this group intravariability might have increased. Furthermore, the raw data reported that a larger number of genes seemed to be differentially expressed (with high fold difference) without reaching statistical significance due to the high standard deviation. Accordingly, in order to find a more specific signature, the study should be validated in a larger, more homogenous cohort.
Another aim of this study was to evaluate the influence of treatment on the entire IBD cohort. Our results showed a downregulation of ISG15 in patients treated with 5-ASA and a downregulation of SAA 1 in patients with biologic treatment compared to patients without IBD treatment. The effect of different therapeutic agents on IBD gene expression should be assessed in a longitudinal cohort.
The main limitation of this study was the absence of data regarding the clinical scores (MAYO and CDAI) measuring the activity and severity of IBD.
In conclusion, we obtained differential intestinal mucosa expression signatures of 17 genes that could specifically characterize the UC inflamed mucosa. Of note, two genes in UC (CCL11 and MMP10) and two in CD (C4BPB and IL1RN) had significantly upregulated expression in the noninflamed and inflamed mucosa compared to controls. Our putative biomarkers, once validated in a larger cohort, could help in clinical practice for the differential diagnosis between UC and CD and could guide new researches on future therapeutic targets.
The data used to support the findings of this study are included within the article.
Conflicts of Interest
The authors declare that they have no conflict of interests.
Maria Dobre and Elena Milanesi contributed equally to this work.
The authors thank the patients involved in the study and the endoscopy department team of the hospitals involved for the generous collaboration. This research was supported by projects PN 16.22.03.01/2016 and PN 18.21.01.05/2018 with the support of the Romanian Autoritatea Nationala pentru Cercetare Stiintifica (ANCSI through the "Nucleu" Program).
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Maria Dobre, (1) Elena Milanesi (ID), (1) Teodora Ecaterina Manuc (ID), (2) Dorel Eugen Arsene, (1,3) Cristian George Jieranu, (4,5) Carlo Maj (ID), (6) Gabriel Becheanu, (2,4) and Mircea Manuc (2,4)
(1) Victor Babes National Institute of Pathology, 050096 Bucharest, Romania
(2) Fundeni Clinical Institute, 022328 Bucharest, Romania
(3) National Institute of Neurology and Neurovascular Diseases, 041914 Bucharest, Romania
(4) Carol Davila University of Medicine and Pharmacy, 050474 Bucharest, Romania
(5) Elias Emergency University Hospital, 011461 Bucharest, Romania
(6) Institute for Genomic Statistics and Bioinformatics, University Hospital Bonn, Germany
Correspondence should be addressed to Teodora Ecaterina Manuc; firstname.lastname@example.org
Received 9 July 2018; Accepted 4 September 2018; Published 17 October 2018
Guest Editor: Donato Zipeto
Caption: Figure 1: Venn diagram showing the genes differentially expressed across the performed different comparisons with controls. Genes marked with asterisk (*) are differentially expressed in the paired IM-NM analysis. IM = inflamed mucosa; NM = noninflamed mucosa.
Caption: Figure 2: Bar graphs represent the mean of the 2A-ACT values, and error bars represent the standard error. The graphs show the genes differentially expressed comparing inflamed mucosa (IM) vs. noninflamed mucosa (NM) IM vs. NM (paired), IM vs. C, and NM vs. C in UC (a) and in CD (b). C = non-IBD controls; IM = inflamed mucosa; NM = noninflamed mucosa.
Table 1: Clinical and demographical parameters of individuals involved in the study. CTRL (n = 21) UC (n = 21) Sex, n (%) Male 9 (42.9) 16 (76.2) Female 12 (57.1) 5 (23.8) Age, yrs, mean [+ or -] SD 46.5 [+ or -] 16.7 44.4 [+ or -] 12.8 Medications at tissue acquisition n (%) None 21 (100) 3 (14.3) Biological -- 2 (9.5) 5-ASA -- 14 (66.7) Cortisone -- -- Polytherapy -- 2 (9.5) CD (n = 22) Sex, n (%) Male 13 (59.1) Female 9 (40.9) Age, yrs, mean [+ or -] SD 45.1 [+ or -] 15.1 Medications at tissue acquisition n (%) None 4 (18.2) Biological 4 (18.2) 5-ASA 7 (31.8) Cortisone 2 (9.1) Polytherapy 5 (22.7) Table 2: The table shows the transcripts that differed by >2.0 fold with p < 0.05 in inflamed mucosa (IM) vs. noninflamed mucosa (NM) in UC and CD patients. Genes are arranged by alphabetic order. Italic fonts indicate genes differentially expressed only in IM from UC. Gene Description C3 Complement C3 C4BPB Complement component 4 binding protein beta CCL11 C-C motif chemokine ligand 11 CCL20 C-C motif chemokine ligand 20 CD55 CD55 molecule (Cromer blood group) CHI3L1 Chitinase 3 like 1 CR2 Complement C3d receptor 2 CXCL1 C-X-C motif chemokine ligand 1 CXCL10 C-X-C motif chemokine ligand 10 CXCL11 C-X-C motif chemokine ligand 11 CXCL2 C-X-C motif chemokine ligand 2 CXCL3 C-X-C motif chemokine ligand 3 CXCL9 C-X-C motif chemokine ligand 9 CXCR1 C-X-C motif chemokine receptor 1 EDN3 Endothelin 3 FPR1 Formyl peptide receptor 1 IFNG Interferon gamma IL1RN Interleukin 1 receptor antagonist IL23A Interleukin 23 subunit alpha IL2RA Interleukin 2 receptor subunit alpha CXCL8 C-X-C motif chemokine ligand 8 ITGB2 Integrin subunit beta 2 LCN2 Lipocalin 2 LTB Lymphotoxin beta LYZ Lysozyme MMP1 Matrix metallopeptidase 1 MMP10 Matrix metallopeptidase 10 MMP3 Matrix metallopeptidase 3 MMP7 Matrix metallopeptidase 7 NOS2 Nitric oxide synthase 2 PCK1 Phosphoenolpyruvate carboxykinase 1 PECAM1 Platelet endothelial cell adhesion molecule 1 REG1A Regenerating family member 1 alpha S100A8 S100 calcium binding protein A8 S100A9 S100 calcium binding protein A9 SAA1 Serum amyloid A1 SELL Selectin L SOD2 Superoxide dismutase 2 STAT1 Signal transducer and activator of transcription 1 TDO2 Tryptophan 2,3-dioxygenase TFF1 Trefoil factor 1 TIMP1 TIMP metallopeptidase inhibitor 1 TNF Tumor necrosis factor UBD Ubiquitin D UC CD Gene Paired IM vs. NM Paired IM vs. NM FC p value FC p value C3 5.48 0.0106 C4BPB 5.86 <0.0001 2.98 0.0090 CCL11 2.01 0.0121 2.27 0.0045 CCL20 4.05 0.0003 CD55 3.63 <0.0001 CHI3L1 16.96 0.0045 4.19 0.0328 CR2 7.00 0.0150 CXCL1 17.99 <0.0001 6.82 0.0413 CXCL10 3.23 0.0008 CXCL11 8.93 0.0001 4.32 0.0380 CXCL2 14.98 <0.0001 CXCL3 9.79 <0.0001 CXCL9 5.16 0.0002 5.22 0.0059 CXCR1 19.22 0.0131 EDN3 -2.92 0.0048 FPR1 10.57 0.0035 IFNG 2.82 <0.0001 IL1RN 8.15 0.0018 5.68 0.0498 IL23A 3.11 <0.0001 IL2RA 3.45 0.0006 CXCL8 19.40 0.0185 ITGB2 2.31 0.0003 LCN2 13.05 0.0003 LTB 4.01 0.0007 LYZ 2.06 0.0009 2.16 0.0344 MMP1 9.98 0.0108 MMP10 14.92 0.0004 MMP3 30.01 0.0016 MMP7 37.37 0.0036 6.00 0.0098 NOS2 10.99 0.0005 PCK1 -6.29 0.0002 PECAM1 2.42 0.0046 REG1A 10.11 0.0123 S100A8 17.91 0.0018 S100A9 9.31 0.0005 SAA1 62.83 0.0016 SELL 5.31 <0.0001 SOD2 2.14 0.0003 2.03 0.0429 STAT1 2.26 <0.0001 TDO2 4.00 <0.0001 TFF1 2.74 0.0001 TIMP1 4.48 <0.0001 TNF 2.58 0.0022 UBD 7.95 0.0002 2.92 0.0116 Table 3: The table shows the transcripts that differed by >2.0 fold with p < 0.05 in inflamed mucosa (IM) and noninflamed mucosa (NM) of UC and CD patients compared with healthy controls. Genes are arranged by alphabetic order. Italic fonts indicate genes differentially expressed both in NM and IM compared to controls. Gene Description ABCB1 ATP binding cassette subfamily B member 1 ALDOB Aldolase, fructose-bisphosphate B C3 Complement C3 C4BPB Complement component 4 binding protein beta CCL11 C-C motif chemokine ligand 11 CCL2 C-C motif chemokine ligand 2 CCL20 C-C motif chemokine ligand 20 CCL25 C-C motif chemokine ligand 25 CCR9 C-C motif chemokine receptor 9 CD55 CD55 molecule (Cromer blood group) CHI3L1 Chitinase 3 like 1 CSTA Cystatin A CXCL1 C-X-C motif chemokine ligand 1 CXCL10 C-X-C motif chemokine ligand 10 CXCL11 C-X-C motif chemokine ligand 11 CXCL2 C-X-C motif chemokine ligand 2 CXCL3 C-X-C motif chemokine ligand 3 CXCL9 C-X-C motif chemokine ligand 9 CXCR1 C-X-C motif chemokine receptor 1 DEFA5 Defensin alpha 5 DEFA6 Defensin alpha 6 FPR1 Formyl peptide receptor 1 IFNG Interferon gamma IL13 Interleukin 13 IL17A Interleukin 17A IL1RN Interleukin 1 receptor antagonist IL23A Interleukin 23 subunit alpha IL2RA Interleukin 2 receptor subunit alpha CXCL8 C-X-C motif chemokine ligand 8 ITGB2 Integrin subunit beta 2 LCN2 Lipocalin 2 LTB Lymphotoxin beta MMP1 Matrix metallopeptidase 1 MMP10 Matrix metallopeptidase 10 MMP3 Matrix metallopeptidase 3 MMP7 Matrix metallopeptidase 7 MUC1 Mucin 1, cell surface associated N0S2 Nitric oxide synthase 2 PCK1 Phosphoenolpyruvate carboxykinase 1 PECAM1 Platelet and endothelial cell adhesion molecule 1 S100A8 SI00 calcium binding protein A8 S100A9 SI00 calcium binding protein A9 SELL Selectin L S0D2 Superoxide dismutase 2 TD02 Tryptophan 2,3-dioxygenase TFF1 Trefoil factor 1 TIMP1 TIMP metallopeptidase inhibitor 1 UBD Ubiquitin D VWF Von Willebrand factor UC Gene IM (n = 21) vs. NM (n = 21) vs. C(n = 21) C (n = 21) FC p value FC p value ABCB1 -7.04 0.0158 ALDOB -18.72 0.0269 C3 3.77 0.0264 C4BPB 10.05 <0.0001 CCL11 3.99 0.0003 2.056 0.003 CCL2 2.58 0.0413 CCL20 3.36 0.0009 CCL25 -13.47 0.0403 CCR9 -2.89 0.0179 CD55 4.63 <0.0001 CHI3L1 42.55 0.0016 CSTA 2.64 0.0045 CXCL1 12.34 <0.0001 CXCL10 2.85 0.0013 CXCL11 7.28 0.0003 CXCL2 9.16 <0.0001 CXCL3 7.17 <0.0001 CXCL9 5.36 <0.0001 CXCR1 50.54 0.0103 DEFA5 -11.68 0.0422 DEFA6 -12.36 0.0368 FPR1 11.09 0.0031 IFNG 2.89 0.0001 IL13 4.08 0.0046 IL17A 4.31 0.0032 IL1RN 12.45 0.0011 IL23A 3.26 0.0013 IL2RA 2.61 0.0026 CXCL8 24.75 0.0169 ITGB2 2.32 0.0005 LCN2 19.25 0.0002 LTB 2.91 0.0061 MMP1 16.79 0.0074 MMP10 53.71 0.0002 3.6 0.0085 MMP3 52.13 0.0013 MMP7 286.33 0.0027 MUC1 2.65 <0.0001 N0S2 11.93 0.0006 PCK1 -6.49 <0.0001 PECAM1 3.09 0.0021 S100A8 28.57 0.0014 S100A9 16.56 0.0002 SELL 3.87 0.0003 S0D2 2.17 0.0005 TD02 3.88 <0.0001 TFF1 3.06 0.0001 TIMP1 6.12 <0.0001 UBD 5.19 0.0006 VWF 3.17 <0.0001 CD Gene IM (n = 22) vs. NM (n = 22) vs. C (n = 21) C (n = 21) FC p value FC p value ABCB1 -3.76 0.0417 ALDOB C3 C4BPB 8.21 <0.0001 2.76 0.0310 CCL11 3.90 <0.0001 CCL2 CCL20 CCL25 CCR9 CD55 2.80 0.0006 CHI3L1 39.26 0.0049 CSTA CXCL1 12.60 0.0240 CXCL10 9.36 0.0416 CXCL11 12.59 0.0077 CXCL2 10.09 0.0368 CXCL3 5.74 0.0123 CXCL9 11.04 0.0016 CXCR1 53.31 0.0152 DEFA5 DEFA6 FPR1 IFNG 3.11 0.0287 IL13 2.82 0.0083 IL17A 2.39 0.0048 IL1RN 14.78 0.0233 2.6 0.0233 IL23A IL2RA 2.44 0.0073 CXCL8 ITGB2 1.75 0.0126 LCN2 13.56 0.0006 5.957 0.0074 LTB MMP1 MMP10 22.84 <0.0001 MMP3 MMP7 87.38 0.0030 MUC1 2.79 0.0017 2.14 0.0024 N0S2 7.09 <0.0001 PCK1 -2.36 0.0077 PECAM1 2.57 0.0060 S100A8 S100A9 33.97 0.0364 3.61 0.0257 SELL 3.97 0.0418 S0D2 2.33 0.0166 TD02 TFF1 2.91 0.0440 TIMP1 4.21 0.0011 UBD 4.99 0.0007 VWF 2.84 0.0022
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|Title Annotation:||Research Article|
|Author:||Dobre, Maria; Milanesi, Elena; Manuc, Teodora Ecaterina; Arsene, Dorel Eugen; Jieranu, Cristian Geor|
|Publication:||Journal of Immunology Research|
|Date:||Jan 1, 2018|
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