Dig Dis Sci DOI 10.1007/s10620-015-3700-2

ORIGINAL ARTICLE

Correlation of Biomarker Expression in Colonic Mucosa with Disease Phenotype in Crohn’s Disease and Ulcerative Colitis Maria E. C. Bruno1,2 • Eric W. Rogier1,3 • Razvan I. Arsenescu4,5 • Deborah R. Flomenhoft4 • Cathryn J. Kurkjian1,6 • Gavin I. Ellis1,7 Charlotte S. Kaetzel1



Received: 27 February 2015 / Accepted: 2 May 2015 Ó Springer Science+Business Media New York 2015

Abstract Background Inflammatory bowel diseases (IBD), including Crohn’s disease (CD) and ulcerative colitis (UC), are characterized by chronic intestinal inflammation due to immunological, microbial, and environmental factors in genetically predisposed individuals. Advances in the diagnosis, prognosis, and treatment of IBD require the identification of robust biomarkers that can be used for molecular classification of diverse disease presentations. We previously identified five genes, RELA, TNFAIP3 (A20), PIGR, TNF, and IL8, whose mRNA levels in colonic mucosal biopsies could be used in a multivariate analysis to classify patients with CD based on disease behavior and responses to therapy.

Aim We compared expression of these five biomarkers in IBD patients classified as having CD or UC, and in healthy controls. Results Patients with CD were characterized as having decreased median expression of TNFAIP3, PIGR, and TNF in non-inflamed colonic mucosa as compared to healthy controls. By contrast, UC patients exhibited decreased expression of PIGR and elevated expression of IL8 in colonic mucosa compared to healthy controls. A multivariate analysis combining mRNA levels for all five genes resulted in segregation of individuals based on disease presentation (CD vs. UC) as well as severity, i.e., patients in remission versus those with acute colitis at the time of biopsy. Conclusion We propose that this approach could be used as a model for molecular classification of IBD patients, which could further be enhanced by the inclusion of

& Charlotte S. Kaetzel [email protected]

2

Present Address: Markey Cancer Center, University of Kentucky, Lexington, KY 40536, USA

3

Eric W. Rogier [email protected]

Present Address: Division of Parasitic Diseases and Malaria, Centers for Disease Control and Prevention, Atlanta, GA 30333, USA

4

Razvan I. Arsenescu [email protected]

Department of Internal Medicine, University of Kentucky, Lexington, KY 40536, USA

5

Deborah R. Flomenhoft [email protected]

Present Address: Department of Internal Medicine, The Ohio State University, Columbus, OH, USA

6

Present Address: Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, 450 West Drive, Chapel Hill, NC 27599, USA

7

Present Address: Department of Microbiology, Perelman School of Medicine, Abramson Family Cancer Research Institute, University of Pennsylvania, 3400 Civic Center Blvd, Philadelphia, PA 19104, USA

Maria E. C. Bruno [email protected]

Cathryn J. Kurkjian [email protected] Gavin I. Ellis [email protected] 1

Department of Microbiology, Immunology and Molecular Genetics, University of Kentucky, Lexington, KY 40536, USA

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additional genes that are identified by functional studies, global gene expression analyses, and genome-wide association studies. Keywords Crohn’s disease  Ulcerative colitis  Colonic mucosa  mRNA biomarkers  Multivariate analysis

Introduction Inflammatory bowel diseases (IBD) represent a spectrum of disorders characterized by chronic gut inflammation in individuals with genetic and/or environmental risk factors [1, 2]. At one end of the clinical spectrum in IBD is Crohn’s disease (CD), defined by discontinuous, transmural, frequently granulomatous intestinal inflammation, which can involve the small and/or large bowel [3, 4]. At the other end of the spectrum is ulcerative colitis (UC), defined by continuous mucosal inflammation without granulomas, extending from the rectum to varying lengths into the colon [5, 6]. Individual presentations of IBD can vary along this spectrum and can range in severity from mild to life-threatening. While differential diagnosis of CD, UC, or IBD type unclassified is critical for clinical management of patients [7, 8], it has been estimated that up to 10 % of patients presenting with IBD-associated colitis cannot be classified differentially using current diagnostic paradigms based on clinical, endoscopic, and radiological criteria [9]. It has been proposed that assessment of molecular markers in the evaluation of IBD patients may be a valuable complement to clinical criteria and may better explain changes in disease behavior, particularly when several markers are combined [10, 11]. We previously reported that a multivariate analysis of mRNA levels in colonic mucosa for five ‘‘signature’’ genes, comprising RELA, TNFAIP3 (also known as A20), PIGR, TNF, and IL8, was predictive of disease behavior and responses to therapy in CD patients [12]. These candidate genes were chosen based on their functional relevance to intestinal homeostasis and IBD. The RELA gene encodes the p65/RelA subunit of the nuclear factor (NF)jB signaling complex that regulates epithelial barrier function but can also be associated with pathological inflammation in the intestine [13, 14]. NF-jB signaling induces transcription of the TNFAIP3 gene, encoding a ubiquitin-modifying enzyme A20 that negatively regulates the NF-jB signaling pathway [15–20]. The PIGR gene encodes the polymeric immunoglobulin receptor, which promotes mucosal homeostasis by transporting protective secretory (S)IgA antibodies across intestinal epithelial cells into the gut lumen [21–25]. The TNF gene encodes the proinflammatory cytokine tumor necrosis factor, which has been associated with mucosal inflammation and is the

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target of therapeutic antibodies for treatment of IBD [26– 28]. However, TNF also has protective roles in innate immunity, including epithelial restitution, control of potentially pathogenic luminal bacteria, and induction of pIgR expression [29–31]. The IL8 gene encodes interleukin (IL)-8 (also known as CXCL8), which is a potent chemoattractant for neutrophils, a major component of the cellular infiltrate in acute intestinal inflammation [32]. Polymorphisms in the RELA, TNFAIP3, PIGR, TNF, and IL8 genes have been identified within genetic loci associated with increased risk of IBD [33, 34]. We hypothesize that genetic and/or environmental factors may influence expression of these genes in the colonic mucosa of IBD patients and that altered levels of gene expression may influence the clinical course of IBD and responses to therapy. In the current study, we expanded our study population to include individuals with UC as well as CD. The purpose of the present study was threefold: first, to evaluate the utility of these five mRNA biomarkers in colonic mucosa for predicting clinical outcome in IBD patients; second, to examine potential differences in biomarker expression between CD and UC patients; and third, to validate the predictive value of a multivariate approach with combined biomarkers as opposed to single biomarkers.

Materials and Methods Study Individuals Colonic mucosal biopsies were obtained from subjects undergoing colonoscopy at the University of Kentucky Medical Center, following written informed consent approved by the Institutional Review Board. The diagnosis of UC was based on clinical, endoscopic, radiological, and histopathological criteria. The presence of active disease was based on endoscopic evidence of inflammation. Biopsies were collected from regions of the colon that were visibly inflamed and non-inflamed, as subsequently confirmed by histological examination. Control subjects underwent colonoscopies for evaluation of constipation or chronic abdominal pain or for routine screening for colon cancer. Patients were classified as normal when endoscopic, radiological, and/or histological evaluation detected no colonic disease. Analysis of mRNA Levels in Colonic Mucosal Biopsies Biopsied tissue samples were collected into an RNA-stabilizing solution (RNAlater, Qiagen, Germantown, MD, USA) and stored at -80 °C until analyzed. Total RNA was

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necessarily be a consequence of localized inflammation. Accordingly, comparisons in gene expression between IBD patients and healthy controls were restricted to those regions of the colon that were macroscopically and microscopically non-inflamed. Although the median age of the cohort of healthy controls was higher than that of IBD patients (Table 1), there was no significant correlation between age at the time of biopsy and expression of RELA, TNFAIP3, PIGR, or TNF (Table 2). However, younger subjects in general had significantly higher levels of IL8 expression in non-inflamed colonic mucosa, as evidenced by the negative correlation with age. Within individuals, levels of RELA, TNFAIP3, and PIGR mRNA were highly correlated, whereas expression of these genes was not correlated with IL8 (Table 2). Interestingly, expression of TNF was correlated with expression of all the other biomarkers within individuals. This finding is consistent with the hypothesis that elevated expression of RelA enhances transcription of the TNFAIP3, PIGR, and TNF genes through the classical NF-jB signaling pathway. Other signaling pathways may also enhance transcription of the TNF and IL8 genes. While expression levels of individual biomarkers varied considerably among individuals, some differences were noted between clinical groups (Fig. 1). Median levels of TNFAIP3 and TNF mRNA were significantly lower in CD patients but not UC patients, compared to healthy controls. Interestingly, median levels of PIGR mRNA were reduced in both CD and UC patients compared to healthy controls. Although levels of RELA mRNA were correlated with levels of TNFAIP3, PIGR, and TNF mRNA within all individuals (Table 2), the wide variation in RELA expression among individuals precluded the finding of significant differences among clinical groups. Although some individual CD and UC patients had elevated expression of IL8 mRNA, median levels for each category did not differ significantly from that of healthy controls. The finding that median IL8 mRNA levels were significantly elevated in UC patients with acute inflammation compared to UC patients in remission suggests that increased expression of IL8 may be associated with the inflammatory process in UC. This concept was supported by the finding that IL8 levels in UC patients, but not CD patients, were significantly elevated in

purified using the RNeasy Protect mini kit (Qiagen) and reverse-transcribed to generate cDNA templates using the TaqMan Gold RT-PCR kit (Applied Biosystems, Foster City, CA, USA). Levels of individual mRNA transcripts were analyzed by quantitative real-time polymerase chain reaction (qRT-PCR), using the ABI Prism 7700 Sequence Detection System (Applied Biosystems) as previously described [12]. The threshold cycles (CT) for test mRNAs were normalized to the CT for b2-microglobulin according to the formula: 2ðCT testCT b2 microglobulinÞ  100 %: Statistical Analyses Human gene expression data were analyzed by nonparametric Mann–Whitney and Spearman correlation tests (http://www.winstat.com). Comparisons between gene expression in paired biopsies from non-inflamed and inflamed colonic mucosa were made using the Wilcoxon signedrank test (http://vassarstats.net/wilcoxon.html). Multifactorial principal component analyses (PCA) of gene expression data were conducted using multibase statistical analysis software (http://www.numericaldynamics.com).

Results Biomarker Expression in Colonic Mucosa of IBD Patients and Healthy Controls To determine whether mRNA levels for five candidate genes could be used to classify IBD patients into clinically relevant subsets, biopsies of colonic mucosa were collected during colonoscopy from 113 IBD patients (60 CD, 53 UC) and 44 healthy controls (Table 1). Diagnosis of CD or UC was based on clinical, radiological, and endoscopic criteria according to the Montreal classification [35], supported by histopathological findings. IBD patients were subclassified into those with or without acute inflammation, as evidenced by areas of macroscopically visible tissue inflammation on colonoscopy. We hypothesized that changes in gene expression throughout the colonic epithelium of IBD patients could promote development of an inflammatory response and would not Table 1 Patient characteristics

Diagnosis

Number of subjects

Age

Gender

Median

Range

Male (%)

Female (%)

Control

44

54

17–78

34.1

65.9

CD in remission

42

40

20–64

36.4

63.6

CD with acute inflammation

18

31

19–72

50.0

50.0

UC in remission

34

39

24–65

45.5

54.5

UC with acute inflammation

19

38

26–61

71.4

28.6

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Dig Dis Sci Table 2 Correlation analysis of biomarker expression and age at biopsy Variables

Age at biopsy RELA TNFAIP3

RELA

TNFAIP3 (A20)

PIGR

TNF

IL8

r

P

r

P

r

P

r

-0.009

0.468

0.091

0.206

0.153

0.082

-0.021

0.618

7.80E-17

0.479

6.14E-10

0.392

6.05E-07

0.594

2.20E-15

0.351 0.246

PIGR TNF

P

r

P

0.424

-0.274

0.006

0.044

0.300

8.09E-06

0.119

0.079

0.001

0.036

0.336

0.362

4.12E-06

Data for gene expression (Fig. 1) and age at biopsy (Table 1) were pooled for all subjects and analyzed by nonparametric Spearman correlation analysis. Correlation coefficients (r) and p values (P) are listed for each comparison. Values shown in bold are statistically significant (P \ 0.05)

Fig. 1 Expression of five biomarkers in colonic mucosa of UC patients and healthy controls. CD and UC patients were subclassified as being in remission or with acute inflammation, based on macroscopic evidence of localized tissue inflammation during colonoscopy. For the purpose of this analysis, biopsies were obtained from regions of the colon of CD and UC patients that were not visibly

inflamed, and absence of inflammation in these biopsies was confirmed microscopically. Levels of mRNA were measured by qRT-PCR and normalized to b2-microglobulin. Horizontal lines indicate the median level of mRNA for each group. Significant differences among groups were determined by the Mann–Whitney nonparametric test

biopsies from visibly inflamed colonic mucosa compared to paired samples from non-inflamed colonic mucosa from the same individuals (Table 3). By contrast, no significant differences were observed in the levels of RELA, TNFAIP3, PIGR, or TNF between inflamed and noninflamed colonic mucosa in either CD or UC patients.

Multivariate Analysis of Biomarker Expression in Colonic Mucosa

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Given the wide variability in expression of individual biomarkers within groups in our cohort, we hypothesized that a multivariate approach would be more useful for

Dig Dis Sci Table 3 Comparison of biomarker expression in paired biopsies of non-inflamed and inflamed colonic mucosa from CD and UC patients

Table 4 Principal component analysis of biomarker expression in non-inflamed colonic mucosa of IBD patients and healthy controls

Genes

Principal component analysis

PC1

PC2

P value

Contribution to overall variance (%)

40.7

27.8

0.215

Eigenvalue

Samples

CD Median

RELA

Non-inflamed

1.714

Inflamed

1.905

TNFAIP3

Non-inflamed Inflamed

0.441 0.382

PIGR

Non-inflamed Inflamed

TNF

Non-inflamed Inflamed

IL8

96.4

UC P value 0.629

0.332

0.038

Inflamed

0.045

0.643 0.450

Genes

127.5

0.889 0.522

104.2 0.332

0.059

Non-inflamed

3.443 2.105

0.119

75.0 0.047

Median

0.791

1.64

1.12

Weighting coefficients PC1

PC2

RELA

-0.544

-0.050

TNFAIP3

-0.588

-0.197

PIGR

-0.563

-0.089

0.119

TNF

-0.166

0.682

0.025

IL8

-0.115

0.697

0.081

0.072 0.049

0.757

Expression levels for biomarkers were analyzed as described in Fig. 1 in paired biopsies from regions of non-inflamed and inflamed colon from 17 CD and 15 UC patients. Statistical differences were determined by nonparametric Wilcoxon signed-rank test; p values \0.05 were considered statistically significant and are noted in bold

predicting clinical outcome in IBD patients. Accordingly, the composite data for expression of the five biomarkers were reduced to two ‘‘supervariables,’’ or principal components (PCs) for each individual (Table 4). The results of the PCA indicated that PC1 accounted for 40.7 % of the overall variance in expression of the five biomarkers in this population of individuals, while PC2 accounted for 27.8 %. For each individual, the value of PC1 and PC2 is calculated as the sum of normalized mRNA level for each gene, multiplied by the weighting coefficient (on a scale of -1 to ?1) for that gene. As noted in Table 4, PC1 had strongly negative coefficients for RELA, TNFAIP3, and PIGR, and moderately negative coefficients for TNF and IL8. In other words, high expression levels for RELA, TNFAIP3, and/or PIGR (and to a lesser extent TNF and IL8) in an individual subject would result in a low score for PC1. By contrast, PC2 had strongly positive coefficients for TNF and IL8, a moderately negative coefficient for TNFAIP3, and weakly negative coefficients for RELA and PIGR. Therefore, high expression of TNF and/or IL8 in any individual subject would result in a high score for PC2, which could be lowered somewhat by high expression of TNFAIP3 and to a lesser extent RELA or PIGR. To examine the distribution of PC scores among clinical groups, a two-dimensional scatter plot was constructed showing PC1 and PC2 scores for each individual (Fig. 2). This plot was divided into four quadrants based on positive or negative values for PC1 and PC2. By examining the distribution of individuals within each clinical group among the four quadrants, it can be determined whether

Expression levels for biomarkers were analyzed in biopsies from regions of non-inflamed colon as described in Fig. 1. Data for individual genes were combined for all study subjects and reduced to two principal components (PCs) as described in ‘‘Materials and Methods’’ section. Weighting coefficients for each gene are listed for PC1 and PC2

Fig. 2 Principal component analysis of gene expression in colonic mucosa. Levels of mRNA for five biomarkers were analyzed as described for Fig. 1, combined for all subjects, and then reduced to two principal components (PCs) for each individual based on the sum of the normalized expression level multiplied by the weighting coefficient for each gene (Table 4). Symbols denote individual subjects, including healthy controls (green), CD patients (red), and UC patients (yellow). CD or UC patients in remission are denoted by squares, and patients with acute inflammation are denoted by triangles. Individuals were distributed into four quadrants based on their scores for PC1 and PC2. a PC1\0, PC2\0. b PC1[0, PC2\0. c PC1 [0, PC2 [0. d PC1 \0, PC2 [0

levels of the composite variables PC1 and PC2 are useful for predicting clinical outcome. Chi-square analysis was used to determine whether individuals in different clinical groups were evenly distributed among the four quadrants,

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or whether there was a bias toward one or more quadrants (Table 5A). Healthy control subjects were distributed roughly equally between quadrant A (41 %) and quadrant B (48 %) and only minimally represented in quadrant C (7 %) and quadrant D (5 %). This pattern indicates that the majority of healthy controls had low values for PC2, but evenly distributed values for PC1. By contrast, CD patients were more heavily distributed in quadrant B (52 %), followed by quadrant A (24 %), quadrant C (18 %), and quadrant D (8 %). However, the subgroup of CD patients with clinical evidence of acute inflammation was more evenly distributed among the four quadrants (as noted by the nonsignificant Chi-square value), with the greatest numbers found in quadrant B (44 %) and quadrant C (33 %). The distribution of all UC patients was similar to that of all CD patients in that there was a bias toward quadrant B (45 %) followed by quadrant A (28 %), but UC patients had a more even distribution between quadrants C Table 5 Chi-square analysis of distribution of study subjects based on principal component analysis of biomarker expression in non-inflamed colonic mucosa

Clinical group

(13 %) and D (15 %). As was the case with CD, UC patients with clinical evidence of acute inflammation were more evenly distributed among the four quadrants, as noted by the nonsignificant Chi-square value. Another approach for evaluation of the two-dimensional PCA data was to compare the distribution of individuals in different clinical groups within each quadrant (Table 5B). Within quadrant A (PC1 \0, PC2 \0), there was a significantly higher proportion of healthy controls compared to CD patients (P = 0.017). However, this did not hold true for UC patients compared to healthy controls, nor were there significant differences within quadrant A between CD or UC patients with or without acute inflammation. Within quadrant B (PC1 [0, PC2 \0), there were no significant differences among any of the groups. Interestingly, a bias toward active CD was seen in quadrant C (PC1 [0, PC2 [0), as demonstrated by a significantly higher proportion of CD patients compared to healthy controls (P = 0.028), and

Fraction within each quadrant A

B

C

(A) Distribution of clinical groups into PCA quadrants

Chi square

P value

D a,b

Control subjects

0.41

0.48

0.07

0.04

26.73

6.72E-06

All CD patients

0.22

0.52

0.18

0.08

25.07

1.50E-05

CD remission

0.24

0.55

0.12

0.09

21.81

7.15E-05

CD acute

0.17

0.44

0.33

0.06

6.44

0.092

All UC patients

0.28

0.45

0.12

0.15

10.60

0.014

UC remission

0.30

0.48

0.11

0.11

10.19

0.017

UC acute

0.23

0.39

0.15

0.23

1.46

0.691

Comparison

Quadrant A

B

(B) Comparison of clinical groups within each PCA quadrant Control versus CD CD in remission versus CD acute Control versus UC UC in remission versus UC acute

C

D

4.84

0.69

c

5.73

0.16

Chi square

0.017

0.689

0.028

0.405

P value

1.20

1.22

9.80

1.00

Chi square

0.274

0.269

0.002

0.317

P value

2.45

0.10

1.80

5.00

Chi square

0.118

0.756

0.180

0.025

P value

0.92

1.16

0.62

4.24

Chi square

0.336

0.281

0.433

0.040

P value

Levels of mRNA for RELA, TNFAIP3, PIGR, TNF, and IL8 were analyzed as described in Fig. 1 and reduced to two principal components (PCs) as described in Table 4 a A two-dimensional ordination plot was used to categorize study subjects into four quadrants based on individual scores for PC1 and PC2, as described in Fig. 2: A PC1 \0, PC2 \0; B PC1 [0, PC2 \0; C PC1 [0, PC2 [0; D PC1 \0, PC2 [0 b

This Chi-square analysis tests the null hypothesis that subjects within each clinical group are evenly distributed among the four quadrants. Values shown in bold are statistically significant (P \ 0.05)

c

This Chi-square analysis tests the null hypothesis that subjects within each quadrant are evenly distributed between the indicated clinical groups. Values shown in bold are statistically significant (P \ 0.05)

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an even greater proportion of CD patients with acute inflammation compared to CD patients in remission (P = 0.002). By contrast, a bias toward UC was seen in quadrant D (PC1 \0, PC2 [0), as demonstrated by a significantly higher proportion of UC patients compared to healthy controls (P = 0.025), as well as a significantly higher proportion of UC patients with acute inflammation compared to UC patients in remission (P = 0.04). In summary, a multivariate approach combining five biomarkers was more predictive of clinical outcome than was any single biomarker. A characteristic of both CD and UC was a shift toward elevated levels of PC2 (quadrants C and D), which could result from elevated expression of TNF and/or IL8 and could be mitigated somewhat by increased expression of TNFAIP3. The finding that healthy controls were more highly represented than were CD patients in quadrant A (PC1\0, PC2\0) suggested that lower levels of PC1, resulting from elevated expression of RELA, TNFAIP3, and/or PIGR, could be protective against inflammation in this disease. This conclusion is consistent with the greater representation of CD patients with acute inflammation than those in remission in quadrant C (PC1 [0, PC2 [0). However, low PC1 values were not associated with improved outcome in UC patients, as evidenced by no significant difference from healthy controls in quadrant A (PC1 \0, PC2 \0), and the greater representation of UC patients with acute inflammation compared to those in remission in quadrant D (PC1 \0, PC2 [0). These differences between CD and UC patients in overall patterns of biomarker expression, which were not revealed by analysis of single biomarkers, may represent inherent differences in the underlying pathology of the two forms of IBD.

Discussion The findings from the present study extend our earlier findings on gene expression in CD patients [12] and reveal interesting differences in gene expression between patients with CD and UC (Fig. 1). In contrast to our previous finding with a smaller study population, we did not find a significant reduction in RELA mRNA in CD patients compared to healthy controls. However, consistent with our earlier study, we found that median levels of TNFAIP3, PIGR, and TNF mRNA in non-inflamed colonic mucosa were significantly lower in CD patients compared to healthy controls. In this context, it is important to note that TNFAIP3, PIGR, and TNF are target genes of the RelA-dependent NF-jB signaling pathway in intestinal epithelial cells [36]. Therefore, decreased transcription of the TNFAIP3, PIGR, and TNF genes could result either from decreased levels of RelA protein or from suppression of the RelA signaling pathway, and these regulatory events

could differ from patient to patient. Interestingly, median levels of PIGR mRNA were decreased in UC patients, but levels of RELA, TNFAIP3, and TNF mRNA were not significantly different between UC patients and healthy controls. The finding of decreased PIGR mRNA in the colonic mucosa of both CD and UC patients is consistent with important role of protective SIgA antibodies in protection against intestinal inflammation [24]. We and others have reported that targeted deletion of the Pigr gene in mice is associated with alterations in the gut microbiota and increased susceptibility to chemically induced colitis [25, 37, 38]. Surprisingly, median levels of TNFAIP3 were not reduced in the colonic mucosa of UC patients. Furthermore, median levels of mRNA encoding IL8, a proinflammatory factor that we observed not to be correlated with RELA, were elevated in colonic mucosa of UC patients but not CD patients. Taken together, these findings suggest that some signaling pathways controlling target gene expression may be differentially regulated in CD versus UC, whereas other pathways, including some that regulate PIGR gene transcription, could be dysregulated in both CD and UC. Further studies of these signaling pathways in IBD patients could reveal unique features of CD and UC that could have important implications for targeted molecular therapies. Consistent with our earlier study with CD patients [12], findings from the present study highlight the benefits of a multivariate approach in analyzing patterns of mucosal gene expression in both CD and UC patients (Table 5). When all five biomarkers were considered together, unique distributions were observed for patients with CD, UC, and healthy controls. In contrast to the analysis with individual biomarkers, the multivariate approach distinguished patients in remission from those with acute colonic inflammation. Another useful outcome of a multivariate biomarker analysis could be the identification of specific individuals who segregate outside the range of the majority of patients within each category. Recognition of differences in patterns of gene expression among individual IBD patients could be important for development of personalized treatment strategies and potentially for monitoring the efficacy of medical interventions. We did not observe a significant effect of medications on expression of these five biomarkers in our previous study of CD patients, but this could have been due to variable drug combinations and duration of treatments in our cohort [12]. In the present study, we did not observe significant effects of medications on biomarker expression in those individuals for whom medical histories were available (data not shown). However, it could prove valuable to monitor changes in biomarker expression in a prospective study under conditions where combinations, doses, and duration of medications could be controlled.

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Maximizing the benefit of multivariate gene expression analysis as a diagnostic, prognostic, and therapeutic tool for the management of IBD patients will require the identification of sensitive and specific biomarkers. Our candidate gene approach, based on functional relevance to intestinal inflammation, has identified five potential biomarkers. This approach could be extended by including additional genes that are identified by functional studies, global gene expression analyses, and genome-wide association studies. Technological advances in multiplex analysis of mRNA levels in small tissue samples, accompanied by robust statistical analysis, should allow multivariate analysis of mucosal gene expression to become an important component of personalized medicine for IBD patients. Acknowledgments This work was supported by NIH/NIDCR Grant 5P20RR020145 to M.E.C.B. and R.I.A.; NIH Grant AI069027 (and an associated American Recovery and Reinvestment Act supplement) and a Senior Research Award from the Crohn’s and Colitis Foundation of America (CCFA) to C.S.K. Conflict of interest

None.

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Correlation of Biomarker Expression in Colonic Mucosa with Disease Phenotype in Crohn's Disease and Ulcerative Colitis.

Inflammatory bowel diseases (IBD), including Crohn's disease (CD) and ulcerative colitis (UC), are characterized by chronic intestinal inflammation du...
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