Aberrant Mucin Expression Profiles Associate With Pediatric Inflammatory Bowel Disease Presentation and Activity

Abstract

Background

Intestinal mucosal healing is nowadays preferred as the therapeutic endpoint in inflammatory bowel disease (IBD), but objective measurements at the molecular level are lacking. Because dysregulated mucin expression is suggested to be involved in mucosal barrier dysfunction in IBD, we investigated mucin expression in association with barrier mediators and clinical characteristics in colonic tissue of a pediatric IBD population.

Methods

In this cross-sectional monocentric study, we quantified messenger RNA (mRNA) expression of mucins, intercellular junctions, and cell polarity complexes in inflamed and noninflamed colonic biopsies from pediatric IBD (n = 29) and non-IBD (n = 15) patients. We then validated mucin expression at protein level and correlated mucin mRNA expression with expression of barrier mediators and clinical data.

Results

The expression of MUC1, MUC3A, MUC4, and MUC13 was increased in the inflamed colon of pediatric IBD patients compared with the noninflamed colon of non-IBD control subjects. Especially MUC13 mRNA expression associated with the expression of barrier mediators, including CDH1, OCLN, and TJP2. MUC1 and MUC3B mRNA expression in combination with calprotectin levels most accurately discriminated IBD patients from non-IBD control subjects (90.6% area under the receiver-operating characteristic curve [AUC_ROC], 92.0% sensitivity, 73.7% specificity), whereas aberrant mRNA expression of MUC1, MUC3A, MUC4, and MUC13 was distinctive for ulcerative colitis and of MUC3B for Crohn’s disease. Furthermore, expression of MUC3A, MUC3B, and MUC4 correlated with clinical disease activity (ie, Pediatric Ulcerative Colitis Activity Index and Pediatric Crohn’s Disease Activity Index), and of MUC1, MUC2, MUC4, and MUC13 with endoscopic colitis severity in ulcerative colitis patients.

Conclusions

Colonic mucin expression is disturbed in pediatric IBD patients and associates with disease activity and presentation, suggesting its use as molecular marker to aid in disease diagnosis and management.

pediatric IBD, intestinal mucosal barrier, biomarkers

Key Messages

What is already known?

Intestinal mucosal barrier dysfunction is a hallmark of the inflammatory bowel disease (IBD) pathophysiology and involves impaired expression of mucin glycoproteins.

What is new here?

We identified colonic mucin messenger RNA signatures as having great potential to discriminate pediatric-onset IBD patients from non-IBD control subjects and to monitor mucosal healing in children diagnosed with UC.

How can this study help patient care?

Molecular characterization of the intestinal mucosal barrier, through the assessment of mucin messenger RNA expression, provides novel biomarkers useful for the diagnosis and management of IBD patients.

Introduction

Inflammatory bowel diseases (IBDs), including Crohn’s disease (CD) and ulcerative colitis (UC), are disease entities characterized by chronic relapsing inflammation of the intestines.¹ Although most IBD patients are diagnosed in adolescence or young adulthood, the incidence in pediatric populations is rising.² Pediatric-onset IBD patients require increased attention, as they can present with a more extensive and complicated disease course, having a serious impact on the child’s development.³ Following diagnosis, the main treatment goal is to induce and maintain disease remission and involves nutritional support in combination with therapeutic intervention. It is thus of utmost importance to diagnose disease and optimize treatment at an early stage to improve the clinical outcome and reduce healthcare costs.³ Nowadays, clinicians prefer mucosal healing as a therapeutic endpoint and because of the changing concept of a treat-to-target strategy, objective measurements at the molecular level are lacking.⁴ The use of biomarkers, such as fecal calprotectin (FCP) and C-reactive protein, has proven their worth in the follow-up of gastrointestinal inflammatory diseases, but their predictive value for endoscopic remission and treatment response remains rather disappointing.⁵ Hence, molecular characterization of the intestinal mucosal barrier in the presence or absence of inflammation could provide novel biomarkers that permit an accurate and robust assessment of treatment response.

The intestinal mucosal barrier consists of a thick layer of mucus, comprising secreted (ie, MUC2) and transmembrane mucins (ie, MUC1, MUC3A/B, MUC4, MUC13), covering the epithelium underneath, as described in detail in The Lancet.^6,7 Intestinal epithelial cells are mechanically tied to one another by intercellular junctions allowing cell–cell adherence and sealing the paracellular spaces. A polarized and tightly linked monolayer of intestinal epithelial cells is thus essential to the proper regulation of intestinal permeability and the prevention of microbial penetration into the underlying tissues.⁸ Impairment of mucin expression, as characterized by excessive degradation of secreted mucins and overexpression of transmembrane mucins, has been described in IBD.⁶ Furthermore, there is compelling evidence that inappropriate overexpression of transmembrane mucins can affect barrier integrity by modulating junctional protein function upon inflammation.^9,10 Given that mucins are active mediators of the mucosal barrier, interacting with the microbiome as well,⁷ associating a specific mucin signature with disease activity could greatly enhance our understanding and management of IBD.

In this cross-sectional monocentric study, we first assessed the expression of mucins, intercellular junctions, and cell polarity proteins in colonic mucosal biopsies of pediatric IBD and non-IBD patients. Subsequently, we correlated the mucin expression patterns with the expression of the other barrier mediators on the one hand and clinical data on the other hand to identify mucins as potential novel biomarkers to evaluate disease activity and presentation in children.

Methods

Study Design and Population

For this monocentric cross-sectional, descriptive study, 44 pediatric patients 6 to 18 years of age who needed to undergo an endoscopy due to gastrointestinal complaints and with a diagnosis or a suspicion of IBD were recruited via the department of pediatric gastroenterology from the Antwerp University Hospital between November 2019 and July 2022. Prior to endoscopy, FCP levels were determined. Based on the results of the endoscopy and histology, the diagnosis of IBD as well as the specific IBD subtype (CD or UC) were either established or ruled out; in case of a rule out of IBD, patients were classified as non-IBD. When no clear discrimination between CD and UC was possible based on the inflammatory lesions assessed by endoscopy and histology, the diagnosis of IBD unclassified (IBDU) was used. Upon IBD diagnosis, clinical disease activity was further established based on the Pediatric Ulcerative Colitis Activity Index (PUCAI) and Pediatric Crohn’s Disease Activity Index (PCDAI) scores.^11–13 The recorded data for the pediatric patients included demographic and baseline clinical characteristics and are summarized in Table 1. Intergroup differences in age and sex were investigated as potential confounders. Colonic biopsies from macroscopically inflamed (if present) and noninflamed tissue were collected and stored in RNAlater (Sigma-Aldrich) at -80°C or embedded in paraffin until gene and protein expression analyses, respectively. This study was approved by the Ethical Committee of the Antwerp University Hospital (Belgian Registration Number B300201940503), and written informed consent of both the children and their representatives was obtained.

Table 1.

Baseline clinical characteristics at the time of endoscopy

	Control (n = 15)	IBD				P Value
		All (n = 29)	CD (n = 15)	UC (n = 11)	IBDU (n = 3)	IBD vs Control	IBD
General
Sex
Male	9 (60.00)	15 (51.72)	9 (60.00)	4 (36.36)	2 (66.67)	.75	.48
Female	6 (40.00)	14 (48.28)	6 (40.00)	7 (63.64)	1 (33.33)
Age
All patients, y	13 (6-17)	13 (9-17)	11 (9-17)	13 (9-16)	14 (10-16)	.49	.30
Male patients, y	13 (6-17)	11 (9-17)	11 (9-17)	13 (9-16)	15 (14-16)	.65	.37
Female patients, y	13 (7-17)	13 (9-16)	11.5 (9-15)	13 (10-16)	10 (-)	.61	.20
Clinical characteristics
Disease score (UC: PUCAI, CD: PCDAI
Remission (PUCAI/PCDAI <10)	–	–	5 (38.46)	0 (0.00)	–	–	–
Mild (PUCAI 10-34; PCDAI 10-30)	–	–	4 (30.77)	3 (30.00)	–
Moderate (PUCAI 35-64)	–	–	–	4 (40.00)	–
Severe (PUCAI >65; PCDAI >30)	–	–	4 (30.77)	3 (30.00)	–
Abdominal pain
Absent	1 (6.67)	9 (31.03)	6 (40.00)	2 (18.18)	1 (33.33)	.20	.24
Mild	5 (33.33)	8 (27.59)	2 (13.33)	4 (36.36)	2 (66.67)
Severe	9 (60.00)	12 (41.38)	7 (46.67)	5 (45.45)	0 (0.00)
Rectal bleeding
Absent	9 (60.00)	10 (34.48)	9 (60.00)	0 (0.00)	1 (33.33)	.30	.003a
Volume <50%, frequency <50%	2 (13.33)	7 (24.14)	3 (20.00)	2 (18.18)	2 (66.67)
Volume <50%, frequency >50%	3 (20.00)	5 (17.24)	1 (6.67)	4 (36.36)	0 (0.00)
Volume >50%	1 (6.67)	7 (24.14)	2 (13.33)	5 (45.45)	0 (0.00)
Stool consistency
Normal	5 (33.33)	10 (34.48)	8 (53.33)	1 (9.09)	1 (33.33)	.32	.12
Partially formed	9 (60.00)	12 (41.38)	4 (26.67)	6 (54.54)	2 (66.67)
Not formed at all	1 (6.67)	7 (24.14)	3 (20.00)	4 (36.36)	0 (0.00)
Stool frequency
0-2/24 h	6 (40.00)	12 (44.44)	8 (53.33)	3 (27.27)	1 (33.33)	.52	.39
3-5/24 h	6 (40.00)	9 (33.33)	4 (26.67)	4 (36.36)	1 (33.33)
6-8/24 h	0 (0.00)	3 (11.11)	0 (0.00)	2 (18.18)	1 (33.33)
> 8/24 h	0 (0.00)	3 (11.11)	1 (6.67)	2 (18.18)	0 (0.00)
Obstipation	5 (33.33)	2 (6.90)	2 (13.33)	0 (0.00)	0 (0.00)	.04a	.59
Nocturnal stool	2 (13.33)	8 (27.59)	3 (20.00)	5 (45.45)	0 (0.00)	.45	.23
Vomiting	4 (26.67)	3 (10.34)	1 (6.67)	2 (18.18)	0 (0.00)	.21	.68
Nausea/decreased appetite	5 (33.33)	8 (27.59)	3 (20.00)	4 (36.36)	1 (33.33)	.74	.61
Perianal fistula/abscess	0 (0.00)	2 (6.90)	2 (13.33)	0 (0.00)	0 (0.00)	.54	.59
Weight loss
No weight loss	9 (60.00)	16 (57.14)	9 (64.29)	5 (45.45)	2 (66.67)	.24	.82
1%-9%	2 (13.33)	9 (32.14)	3 (21.43)	5 (45.45)	1 (33.33)
>10%	4 (26.67)	3 (10.71)	2 (14.29)	1 (9.09)	0 (0.00)
Limitation in daily activity
Absent	9 (60.00)	18 (62.07)	10 (66.67)	6 (54.54)	2 (66.67)	1.00	.95
Moderate	4 (26.67)	8 (27.59)	3 (20.00)	4 (36.36)	1 (33.33)
Severe	2 (13.33)	3 (10.34)	2 (13.33)	1 (9.09)	0 (0.00)
Tiredness	3 (20.00)	7 (24.14)	2 (13.33)	5 (45.45)	0 (0.00)	1.00	.12
Fecal calprotectin
0-50 µg/g	4 (28.57)	1 (3.70)	1 (7.14)	0 (0.00)	0 (0.00)	.01a	.65
50-200 µg/g	3 (21.43)	2 (7.41)	2 (14.28)	0 (0.00)	0 (0.00)
>200 µg/g	7 (50.00)	24 (88.89)	11 (78.57)	10 (100.00)	3 (100.00)
Treatment at time of endoscopy
Treatment (yes/no)	2 (13.33)	11 (37.90)	7 (46.67)	4 (36.36)	0 (0.00)	.16	.42
Nutritional therapy	0 (0.00)	1 (3.45)	1 (6.67)	0 (0.00)	0 (0.00)	1.00	1.00
Antibiotics	0 (0.00)	2 (6.90)	0 (0.00)	2 (18.18)	0 (0.00)	.54	.34
Probiotics	1 (6.67)	1 (3.45)	0 (0.00)	1 (9.09)	0 (0.00)	1.00	.48
Aminosalicylates (5-ASA [eg, mesalazine, sulfasalazine])	1 (6.67)	2 (6.90)	0 (0.00)	2 (18.18)	0 (0.00)	1.00	.34
Corticosteroids (eg, prednisone, budesonide)	1 (6.67)	2 (6.90)	0 (0.00)	2 (18.18)	0 (0.00)	1.00	.34
Immunomodulators (eg, azathioprine, 6-mercaptopurine, methotrexate)	1 (6.67)	7 (24.14)	6 (40.00)	1 (14.29)	0 (0.00)	.23	.19
Biological therapy (eg, infliximab, adalimumab)	0 (0.00)	3 (10.34)	2 (13.33)	1 (14.29)	0 (0.00)	.54	1.00
Extraintestinal manifestations
Growth/development restriction	1 (6.67)	5 (17.24)	3 (20.00)	1 (9.09)	1 (33.33)	.65	.50
Fever	1 (6.67)	0 (0.00)	0 (0.00)	0 (0.00)	0 (0.00)	.34	1.00
Uveitis	1 (6.67)	0 (0.00)	0 (0.00)	0 (0.00)	0 (0.00)	.34	1.00
Arthritis/arthralgia	3 (20.00)	3 (10.34)	2 (13.33)	1 (9.09)	0 (0.00)	.39	1.00
Anemia	2 (13.33)	6 (20.69)	5 (33.33)	1 (9.09)	0 (0.00)	.70	0.25

Values are n (%) or median (range).

Abbreviations: 5-ASA, 5-aminosalicylic acid; CD, Crohn’s disease; IBD, inflammatory bowel disease; IBDU, inflammatory bowel disease unclassified; PCDAI, Pediatric Crohn’s Disease Activity Index; PUCAI, Pediatric Ulcerative Colitis Activity Index; UC, ulcerative colitis.

^aP < 0.05.

Messenger RNA Expression of Mucins and Junctional and Polarity Proteins by Real-Time Quantitative Polymerase Chain Reaction

Total RNA was extracted using the NucleoSpin RNA plus kit (Macherey-Nagel) following the manufacturer’s instructions. The concentration and purity of the RNA were evaluated using the NanoDrop ND-1000 UV-Vis Spectrophotometer (Thermo Fisher Scientific). Subsequently, 1 μg RNA was converted to complementary DNA by reverse transcription using the SensiFast cDNA synthesis kit (Bioline). Relative gene expression was then determined by SYBR Green real-time quantitative polymerase chain reaction (RT-qPCR) using the GoTaq qPCR master mix (Promega) on a QuantStudio 3 Real-Time PCR instrument (Thermo Fisher Scientific). Primer sequences are shown in Supplementary Table 1. All RT-qPCRs were performed in duplicate and involved an initial DNA polymerase activation step for 2 minutes at 95°C, followed by 40 cycles of denaturation at 95°C for 15 seconds and annealing/extension for 1 minute at 60°C. Analysis and quality control were performed using the qbase + software (Biogazelle). Relative expression of the target genes was normalized to the expression of the housekeeping genes ACTB and GAPDH. The log2 fold change expression (relative expression inflamed/relative expression noninflamed) was also calculated to investigate the associations of differential mucin expression of inflamed vs noninflamed colonic tissue in the same patient with clinical parameters.

Immunohistochemistry

Five-micrometer cross-sections were deparaffinized, rehydrated, and used for immunohistochemical stainings using target specific primary antibodies and visualization with a secondary streptavidin–horseradish peroxidase-conjugated antibody and AEC (3-amino-9-ethylcarbazole) substrate to detect the expression and localization of MUC1 (AF6298; R&D systems; 1:500), MUC2 (NBP1-31,231; Novus Biologicals; 1:2000), MUC3 (NBP2-44,434; Novus Biologicals; 1:100), MUC4 (NBP1-52193; Novus Biologicals; 1:3000), and MUC13 (MABC209; Merck Millipore; 1:1000). The stained sections were analyzed by light microscopy (Olympus BX43).

Statistical Analysis

Statistical analysis was performed using GraphPad Prism 9, IBM SPSS Statistics version 27, and RStudio version 1.4.1106 (R version 4.0.5). Patient characteristics are expressed as median (range) for continuous variables and analyzed by independent Student’s t test or 1-way analysis of variance. Differences between proportions are indicated as number and percentage were analyzed by Fisher exact tests. Analysis of variance (repeated measures) and Kruskal-Wallis tests were used to evaluate differences in relative messenger RNA (mRNA) expression of mucins, junctional proteins, and polarity proteins in inflamed and noninflamed biopsies from IBD patients and non-IBD control subjects when appropriate. Spearman correlations were performed to identify relationships between mucin expression, junctional protein expression, and clinical parameters. Correlograms plotting the Spearman’s rank correlation coefficient (r) between all parameter pairs were created as well as correlation plots displaying specific correlations of mucin mRNA expression, junctional proteins, and clinical parameters.¹⁴ Furthermore, a principal component analysis (PCA) (unsupervised method) and sparse partial least-squares discriminant analysis (sPLS-DA) (supervised method) were carried out to evaluate the potential of mucin expression patterns as predictor variables for IBD diagnosis.¹⁴ Subsequently, a least absolute shrinkage and selection operator (LASSO) regression with leave-one-out cross-validation and receiver-operating characteristic (ROC) analysis was also done to investigate which mucin expression levels are the most accurate predictors for IBD presentation and subtype.¹⁴ Patients with missing values for a certain variable were not included in that analysis. Outliers were substituted with group means. P values below .05 were considered statistically significant after correction for multiple testing.

Results

Patient Clinical Characteristics

A total of 44 patients were included in this study, 29 of whom were diagnosed with IBD (CD: 15 [34.1%]; UC: 11 [25.0%]; IBDU: 3 [6.8%]). Although 5 CD patients were in clinical remission (ie, PCDAI <10), endoscopy revealed the presence of inflammatory lesions in the colon of 2 of them. Fifteen patients were not diagnosed with IBD, of whom 6 showed discrete macroscopic inflammation in their colon, most probably resulting from a previous infection. The baseline clinical characteristics are shown in Table 1. Of the 44 patients, 24 (54.5%) were male and 20 (45.5%) were female, and the median age was 13 (male age range: 6-17; female age range: 7-17) years, with an equal distribution among all patients (sex: P = .75; age: P = .49) (Table 1) and between IBD subgroups (sex: P = .48; age: P = .30) (Table 1). Among the UC patients, 30.0% showed a mild, 40.0% a moderate, and 30.0% a severe course of the disease based on the PUCAI score (Table 1). Regarding the CD patients, 30.8% presented mild disease, 30.8% presented severe disease, and 38.5% were in remission based on the PCDAI score (Table 1). High FCP levels (>200 µg/g) were found in most IBD patients without intergroup differences (78.6% CD, 100.0% UC, 100.0% IBDU; P = .65) (Table 1) but with a higher frequency compared with the non-IBD control subjects (88.9% vs 50%; P = .01) (Table 1). Furthermore, the presence of rectal bleeding was significantly different among IBD subtypes with the highest prevalence in UC patients (100% vs 40% [CD] and 66.7% [IBDU] patients; P = .003) (Table 1).

Overall, symptoms described in the IBD and non-IBD groups were similar. More specifically, 69.0% of IBD patients experienced abdominal pain (vs 93.3% in control subjects; P = .20), 65.5% loose stools (vs 66.7% in control subjects; P = .32), 65.5% blood in stool (vs 40% in control subjects; P = .30), and 27.6% nocturnal stools (vs 15% in control subjects; P = .45) (Table 1). On the contrary, obstipation seemed to be more frequently reported in non-IBD control subjects (33.3% vs 6.9%; P = .04) (Table 1). Finally, although a higher number of IBD patients received treatment compared with non-IBD control subjects at the time of endoscopy, it was not statistically different (P = .16) (Table 1).

These results indicate that the discrimination of IBD subtypes and of IBD patients and non-IBD control subjects in general cannot be unambiguously performed based on gastrointestinal symptoms. In addition, high FCP levels (>200 µg/g) are found in both IBD patients and non-IBD control subjects, although with a higher frequency in IBD patients, endorsing the importance of additional analyses to correctly diagnose these patients.

Mucin Expression Profiles in IBD Patients and Non-IBD Control Subjects

First, we analyzed mucin mRNA expression in the inflamed and noninflamed mucosal samples from both the pediatric IBD patients and non-IBD control subjects. Elevated mRNA levels of MUC1and MUC3A were found in both the inflamed and noninflamed colon of IBD patients as compared with the noninflamed colon of non-IBD control subjects (Figure 1A). In addition, expression of MUC4 and MUC13 mRNA was increased in the inflamed colon of IBD patients as compared with the noninflamed colon of non-IBD control subjects (Figure 1A). Next, we analyzed mucin expression in paired inflamed/noninflamed colonic samples from IBD patients and non-IBD control subjects to assess the interaction of intestinal inflammation and IBD subtype on mucin expression in the same patient (Supplementary Figure S1). Here, an upregulated expression of MUC1, MUC4, and MUC13 mRNA was noted in the inflamed colon compared with the noninflamed colon within UC patients (Supplementary Figure S1A, S1E, S1F).

Figure 1.

Expression of mucins in the colon of pediatric inflammatory bowel disease (IBD) patients and non-IBD control subjects. A, Relative messenger RNA (mRNA) expression of MUC1, MUC2, MUC3A, MUC3B, MUC4, and MUC13 in inflamed and noninflamed colonic tissue of IBD patients and non-IBD control subjects. Significant differences are indicated by *P < .05; **P < .01; ***P < .001 (1-way analysis of variance or Kruskal-Wallis, Tukey ,and Dunn multiple comparison post hoc test). B, Immunohistochemical analysis of MUC1, MUC2, MUC3, MUC4, and MUC13 expression in colonic biopsies from non-IBD control subjects and IBD patients. Representative images were selected. Scale bars = 20 μm.

Finally, mucin expression was also evaluated using immunohistochemistry to evaluate if observations at protein level were similar to our findings at mRNA level (Figure 1B). Compared with the healthy tissue from non-IBD control subjects, an increased expression of MUC1 was noted among the IBD group with the highest staining intensity seen in inflamed tissue of especially UC patients, whereas no clear differences in protein expression were observed for MUC2 (Figure 1B). MUC3 showed a moderate increase in colonic tissue from IBD patients and from inflamed regions of non-IBD control patients (Figure 1B). Concerning MUC4 and MUC13, the highest staining intensity was observed in inflamed colonic tissue from IBD patients (Figure 1B). However, MUC13 was also slightly elevated in inflamed colonic tissue from non-IBD control subjects and noninflamed colonic tissue from IBD patients (Figure 1B). Under healthy conditions, transmembrane mucins are present at the apical side of epithelial cells. Upon inflammation, overexpression of transmembrane mucins can result in a repositioning over the whole cell membrane, causing physical hindrance of neighboring cells to make cell contact. In addition, the transmembrane mucins can also translocate to the cytoplasm to modulate intracellular signaling pathways, which is often observed in inflammatory conditions and cancer.^7,8 In our study, MUC4 and MUC13 were mainly expressed on the apical side of epithelial cells in noninflamed colonic tissue, whereas an increased expression of both mucins was also observed in the cytoplasm of the inflamed tissue (Figure 1B). On the contrary, MUC1, which is expressed at low levels in the cytoplasm of healthy colonic epithelial cells, extended apically upon inflammation (Figure 1B).

The alterations in mucin expression seen in the colonic mucosa of our pediatric IBD cohort further support a key role of mucin signaling in the IBD pathophysiology.

Aberrant Mucin Expression Associated With Markers of Altered Mucosal Barrier Function

Subsequently, mRNA expression of several tight junctions (CLDN1, CLDN2, CLDN3, CLDN4, CLDN7, OCLN, TJP1, and TJP2), adherens junctions (CDH1), and major cell polarity (PAR3, CRB3, and SCRIB) proteins was investigated in the mucosal samples. CLDN1 and CLDN2 mRNA expression showed a significant increase and OCLN mRNA expression a significant decrease in the inflamed colon of IBD patients compared with both the healthy and inflamed tissue of non-IBD control subjects (Figure 2A). In addition, the mRNA expression levels of CLDN3, CLDN7, and CDH1 were only significantly reduced in the inflamed colon of IBD patients compared with the healthy colon of non-IBD control subjects (Figure 2A). When comparing inflamed and noninflamed tissue of IBD patients, the mRNA expression levels of CLDN1 and CLDN2 were increased while the mRNA expression levels of OCLN, TJP1, and CDH1 were decreased in the inflamed compared with its noninflamed counterpart from IBD patients (Figure 2A). No differences regarding the mRNA expression levels of cell polarity complexes were noticed in the colon of IBD patients and non-IBD control subjects (Figure 2B). In addition, we investigated the expression patterns of these barrier mediators in paired colonic samples from IBD patients (Supplementary Figure S2). In CD patients, mRNA expression of CLDN1 (P = .06) and CLDN2 increased and mRNA expression of OCLN and CDH1 (P = .06) decreased in the inflamed colon. In UC patients, an elevated mRNA expression of CLDN2, and in IBDU patients, a decreased expression of CLDN3 was noticed in the inflamed compared with noninflamed tissue (Supplementary Figure S2).

Figure 2.

Messenger RNA (mRNA) expression of intercellular junctions and cell polarity complexes and their association with mucin expression in the colon of pediatric inflammatory bowel disease (IBD) patients. Relative mRNA expression of (A) CLDN1, CLDN2, CLDN3, CLDN4, CLDN7, OCLN, TJP1, TJP2, and CDH1; (B) PAR3, CRB3, and SCRIB in inflamed and noninflamed colonic tissue of IBD patients and non-IBD control subjects. Significant differences are indicated by *P < .05; **P < .01; ***P < .001 (1-way analysis of variance or Kruskal-Wallis, Tukey, and Dunn multiple comparison post hoc test). C and D, Correlogram of relative mRNA expression levels of mucins, intercellular junctions, and polarity complexes in the (C) noninflamed (n = 25) and (D) inflamed (n = 26) colon of IBD patients. Spearman rank order correlation values (r) are shown from red (–1.0) to blue (1.0); r values are indicated by color and square size. P values are indicated by black asterisks (*P < .05; **P < .01; ***P < .001) (See online version for color figure).

Furthermore, we also verified collinearity between the mRNA expression data of mucins, tight junctions, adherens junctions, and major polarity complex proteins among the IBD patient cohort (Figure 2C, 2D). In both inflamed and noninflamed tissue from IBD patients, MUC1 mRNA expression positively correlated with CLDN3 and CRB3 mRNA expression, MUC3B mRNA expression positively correlated with CDH1 and CLDN7 mRNA expression, MUC4 mRNA expression positively correlated with CRB3 mRNA expression, and MUC13 mRNA expression strongly associated with the mRNA expression levels of OCLN, TJP2, and CDH1 (Figure 2C, 2D; Supplementary Figure S3). Furthermore, positive correlations were identified for MUC1 with OCLN mRNA expression; MUC2 with CLDN3, CLDN7, and PAR3 mRNA expression; MUC4 with CLDN3 mRNA expression; MUC13 with CLDN4, and CLDN7 mRNA expression in noninflamed tissue (Figure 2C; Supplementary Figure S3). Several positive associations also emerged in the inflamed tissue. These include mRNA expression of MUC3A with TJP2, CDH1, PAR3, and CRB3; MUC4 and TJP2; and MUC13 with CRB3 and SCRIB (Figure 2D; Supplementary Figure S3).

The observed changes in the expression patterns of several tight junction and adherens junction proteins and their association with aberrant mucin expression further underline the presence of intestinal barrier dysfunction in the inflamed colonic mucosae of pediatric IBD patients. Interestingly, these alterations were not observed in inflamed intestinal regions of non-IBD control subjects, which further endorses the key role of intestinal barrier dysfunction in IBD.

Mucin mRNA Signatures Associated With IBD Diagnosis and Subtypes

To test the hypothesis that IBD patients display an aberrant mucin mRNA expression profile in their colonic mucosa, a PCA based on the relative mucin mRNA expression data from both inflamed an noninflamed tissue was first undertaken. Therefore, the presence of (macroscopic and microscopic) inflammation was included as an additional parameter in the analysis. Strikingly, mucin mRNA expression levels distinguished the IBD subgroups (ie, CD, UC, and IBDU) from the non-IBD control subjects (Figure 3A), making them appropriate for further testing. To identify which of these mucin variables were the major discriminators for IBD (CD and UC) or non-IBD control subjects, an sPLS-DA was carried out. The sPLS-DA plot showed a clear discrimination among the groups (Figure 3B), with the mRNA expression of MUC3B as the major determinant for CD patients and of MUC1, MUC4, MUC3A, and MUC13 as major determinants for UC patients (Figure 3C, 3D). Thereafter, LASSO regression with internal leave-one-out cross-validation and ROC analysis was used to compare the separate and combined performance of mucin mRNA and calprotectin levels to distinguish IBD patients from non-IBD control subjects (Figure 4). The simultaneous use of both mucin mRNA (MUC1 and MUC3B as withhold predictors) and calprotectin levels was superior to distinguish IBD patients from non-IBD patients in general, with an area under the ROC curve (AUC_ROC) of 90.6%, a sensitivity of 92.0%, and a specificity of 73.7%) (Figure 4A). The separate use of calprotectin levels outperformed mucin mRNA levels (MUC1, MUC2, MUC3A, MU3B, and MUC4 as withhold predictors) in overall performance (AUC_ROC, 85.1% vs 79.7%), with a similar sensitivity (80.0% vs 82.0%) but increased specificity (89.5% vs 52.6%) (Figure 4E). Similarly, the combinatory use of calprotectin and mucin mRNA levels outperformed their separate use to distinguish CD from UC patients (AUC_ROC of 72.5%, sensitivity of 69.2%, and specificity of 73.7%) (Figure 4B) and CD from non-IBD control patients (AUC_ROC of 83.0%, sensitivity of 73.1%, and specificity of 84.2%) (Figure 4C). When considering UC patients and control subjects, the best performance was observed when analyzing calprotectin levels separately (AUC_ROC of 93.1%, sensitivity of 84.2%, and specificity of 89.5%) (Figure 4D). These findings clearly indicate that IBD patients can be discriminated from non-IBD control subjects based on mucin mRNA expression patterns. Furthermore, the association of individual mucins to the IBD subtypes was different, suggesting that different molecular mechanisms are present with regard to mucin signaling in the intestinal mucosal barrier. Because mucins can modulate various signaling pathways in intestinal epithelial cells, it can be assumed that the overall changes in expression will determine the eventual cellular effect on intestinal barrier homeostasis, eventually resulting in a clinical manifestation.

Figure 3.

Colonic mucin messenger RNA (mRNA) expression levels as variables associated with inflammatory bowel disease (IBD) presentation and subtypes. A, Three-dimensional principal component (PC) analysis plot based on mucin mRNA expression values from noninflamed and inflamed colonic tissue from IBD patients (Crohn’s disease [CD]: n = 25; ulcerative colitis [UC]: n = 19; IBD unclassified [IBDU]: n = 5) and non-IBD control subjects (n = 19). PC1 and PC2 explain 48.8% and 18.4% of the variation, respectively. B, Sparse partial least-squares discriminant analysis (sPLS-DA) plot based on mucin mRNA expression values from the noninflamed and inflamed colon as major predictors for the presence of IBD (CD: n = 25; UC: n = 19; non-IBD control subjects: n = 19). C and D, The major determinants of (C) component 1 (PLS-DA1) and (D) component 2 (PLS-DA2) of the sPLS-DA analysis.

Figure 4.

Receiver-operating characteristic (ROC) curves for the prediction model of inflammatory bowel disease (IBD) subtypes and non-IBD control subjects obtained by LASSO (least absolute shrinkage and selection operator) logistic regression based on mucin messenger RNA (mRNA) expression values from noninflamed and inflamed colonic tissue and fecal calprotectin (FCP) levels. A, ROC curves for IBD patients (n = 50) vs non-IBD control subjects (n = 19). ROC_mucins (green): area under the curve (AUC) of 79.7% (95% confidence interval [CI], 68.2%-89.7%), sensitivity of 82.0% (95% CI, 69.6%-90.8%), specificity of 63.2% (95% CI, 40.4%-82.2%); ROC_FCP (orange): AUC of 85.1% (95% CI, 73.8%-94.0%), sensitivity of 80.0% (95% CI, 67.3%-89.4%), specificity of 89.5% (95% CI, 69.4%-98.2%); ROC_{FCP & mucins} (blue): AUC of 90.6% (95% CI, 82.5%-96.9%), sensitivity of 92.0% (95% CI, 81.9%-97.4%), specificity of 73.7% (95% CI, 51.0%-89.6%). B, ROC curves for CD patients (n = 25) vs UC patients (n = 19). ROC_mucins (green): AUC of 53.6% (95% CI, 28.7%-64.4%), sensitivity of 88.5% (95% CI, 71.8%-97.0%), specificity of 31.6% (95% CI, 14.0%-54.5%); ROC_FCP (orange): 63.8% (95% CI, 46.6%-79.6%), sensitivity of 76.9% (95% CI, 58.1%-90.1%), specificity of 52.6% (95% CI, 30.7%-73.9%); ROC_{FCP & mucins} (blue): AUC of 72.5% (95% CI, 56.5%-86.4%), sensitivity of 69.2% (95% CI, 49.9%-84.6%), specificity of 73.7% (95% CI, 51.0%-89.6%). C, ROC curves for CD patients (n = 25) vs non-IBD control subjects (n = 19). ROC_mucins (green): AUC of 77.1% (95% CI, 62.1%-90.3%), sensitivity of 84.6% (95% CI, 67.0%-94.9%), specificity of 57.9% (95% CI, 35.4%-78.2%); ROC_FCP (orange): AUC of 70.2% (95% CI, 53.6%-84.8%), sensitivity of 84.6% (95% CI, 67.0-94.9%), specificity of 42.1% (95% CI, 21.9%-64.6%); ROC_{FCP & mucins} (blue): AUC of 83.0% (95% CI, 69.8%-93.9%), sensitivity of 73.1% (95% CI, 53.9%-87.4%), specificity of 84.2% (95% CI, 62.8%-95.8%). D, ROC curves for UC patients (n = 19) vs non-IBD control subjects (n = 19). ROC_mucins (green): AUC of 73.4% (95% CI, 55.1%-89.5%), sensitivity of 68.4% (95% CI, 45.5%-86.1%), specificity of 84.2% (95% CI, 62.8%-95.8%); ROC_FCP (orange): AUC of 93.1% (95% CI, 83.7%-98.9%), sensitivity of 84.2% (95% CI, 62.8%-95.8%), specificity of 89.5% (95% CI, 69.4%-98.2%); ROC_{FCP & mucins} (blue): AUC of 87.0% (95% CI, 72.3-99.4%), sensitivity of 94.7% (95% CI, 76.7%-99.7%), specificity of 84.2% (95% CI, 62.8%-95.8%). AUC_ROC, area under the receiver-operating characteristic curve (See online version for color figure).

Finally, associations between the mucin mRNA expression data and clinical parameters of IBD patients were investigated as well (Figure 5; Supplementary Figure S4 and S5). Within the IBD cohort, we identified a positive correlation of MUC3B mRNA expression in the inflamed colon and a negative correlation of MUC4 mRNA expression in the noninflamed colon with the PUCAI score (Figure 5B; Supplementary Figure S4A). MUC3A mRNA expression in noninflamed tissue was strongly associated with the PCDAI score in CD patients (Figure 5C). Regarding the macroscopic assessment of inflammation during endoscopy, MUC1, MUC2, MUC4, and MUC13 mRNA levels in the noninflamed colon of UC patients negatively correlated with the Mayo score (Figure 5D, 5E; Supplementary Figure S4B, S4C). In addition, significant associations were also identified for MUC3A/MUC3B mRNA expression and weight loss (Figure 5F; Supplementary Figure S4D); MUC1, MUC4, and MUC13 mRNA expression and age (Supplementary Figure S4E-S4G); MUC1, MUC3A, MUC3B, MUC4, and MUC13 mRNA expression and anemia (Supplementary Figure S4H-S4L); MUC3B mRNA expression and ulcer size (Supplementary Figure S4M); and MUC13 mRNA expression and nocturnal stool (Supplementary Figure S4N). Finally, we also evaluated the correlation of differential expression of mucins and clinical parameters, by determining the log2 fold change of mucin expression in inflamed vs noninflamed colonic tissue from paired samples (Supplementary Figure S5). Strong positive correlations were identified for the differential expression of MUC1, MUC2, MUC4, and MUC13 with the Mayo score (Supplementary Figure S5A-S5D); MUC2 and MUC13 with stool frequency (Supplementary Figure S5E, S5F); MUC2 with stool consistency (Supplementary Figure S5G); MUC3B with ulcer size (Supplementary Figure S5H), and MUC13 with rectal bleeding (Supplementary Figure S5I). These correlations underline a link between changes in mucin expression and the presentation of specific clinical features in pediatric IBD.

Figure 5.

Associations of colonic mucin messenger RNA (mRNA) expression with clinical disease parameters in pediatric inflammatory bowel disease (IBD) patients. A, Correlogram of relative mucin mRNA expression and clinical data in pediatric-onset IBD. Spearman rank order correlation values (r) are shown from red (-1.0) to blue (1.0); r values are indicated by color and square size. P values are indicated by black asterisks (*P < .05; **P < .01; ***P < .001). NI indicates mucin mRNA expression in the noninflamed colon; I indicates mucin mRNA expression in the inflamed colon; I_vs_NI indicates log2 fold change of mucin mRNA expression in inflamed colon relative to the noninflamed colon in the same patient. B-F, Correlation of (B) MUC3B mRNA expression with the Pediatric Ulcerative Colitis Activity Index score (NI: n = 7; I: n = 10), (C) MUC3A mRNA expression with the Pediatric Crohn’s Disease Activity Index score (NI: n = 13; I: n = 8), (D) MUC1 mRNA expression with the Mayo score (NI: n = 8; I: n = 12), (E) MUC4 mRNA expression with the Mayo score (NI: n = 8; I: n = 12), and (F) MUC3A mRNA expression with weight loss (NI: n = 24; I: n = 24). r Values are shown and significance is indicated by asterisks (*P < .05; **P < .01) (See online version for color figure).

Discussion

This is the first study specifically looking at the transcriptional landscape of mucins in the colonic mucosa of pediatric IBD and non-IBD patients with gastrointestinal complaints as potential biomarkers associated with IBD presentation/activity and subtypes.

When first comparing the mucin gene expression levels between IBD and non-IBD patients, we found an overall increase of MUC1 and MUC3A expression in the colonic mucosa of IBD patients, whereas the mRNA levels of MUC4 and MUC13 were elevated in the inflamed colon of IBD patients. Our findings of aberrant transmembrane mucin expression in pediatric-onset IBD were also confirmed at protein level and are consistent with previously published mucin data in adult-onset IBD patients.^8,15–18 Interestingly, when distinguishing among the different IBD subtypes, significant higher expression levels of MUC1, MUC4, and MUC13 mRNA were measured in the inflamed colon vs noninflamed colon of especially UC patients. In CD and IBDU patients, no clear difference in mucin expression was found between the inflamed and noninflamed tissue specimens. These results highlight key alterations in mucin expression patterns during inflammation in each IBD subtype, which could be related to underlying differences in the inflammatory phenotype seen in IBD patients. Whereas the intestinal inflammation is continuous and limited to the superficial mucosa in the colon of UC patients, it has a patchy, transmural appearance affecting the whole gastrointestinal tract in CD patients.¹ In this way, adjacent noninflamed regions in UC patients may be more comparable to healthy colonic tissue in control subjects, whereas in CD patients general defects may be present. Accordingly, mucin expression in noninflamed tissue of UC patients was comparable to that of non-IBD control subjects. Furthermore, because several studies have also reported that multiple inflammatory cytokines can affect intestinal mucin expression and that different immune signaling networks are present in UC and CD patients, it is possible that the immune microenvironment modulates mucin expression in different ways.^8,17,19 Of note, MUC2 is the main component of the secreted mucus layer and provides the first line of defense against invading pathogens and toxins in the intestines.⁸ Although aberrant MUC2 expression has been described in the colon and ileum of adult IBD patients,^16,20,21 we did not identify any significant differences in both noninflamed and inflamed colonic tissue of our pediatric IBD patients, which is similar to the findings of Hensel et al.²² However, large variations of MUC2 mRNA expression in the colon of pediatric IBD patients were noted.

Furthermore, we also observed strong associations between mRNA expression of transmembrane mucins, junctional proteins, and major components of cell polarity complexes in mucosal samples from IBD patients in both the presence and absence of inflammation. Interestingly, increased mRNA expression of MUC13 mRNA associated with the mRNA expression levels of CDH1, OCLN, and TJP2 in both inflamed and noninflamed tissue, of CLDN4 and CLDN7 in noninflamed tissue, and of CRB3 and SCRIB in inflamed tissue only. Similar associations of mRNA expression levels between MUC13 and junctional and polarity proteins have also been reported during the course of murine colitis.⁸ Loss of the crumbs complex, as characterized by a decrease in CRB3, results in a dissociation of tight junctions and adherens junctions, such as CDH1 and OCLN.²³ As mucins have been shown to interact with major regulators of epithelial differentiation and intercellular junctions assembly, including ZEB1, β-catenin and CRB3,²⁴ it remains to be further elucidated how aberrant mucin expression, and specifically MUC13, affects intestinal barrier integrity in IBD. Nevertheless, the above findings further underscore (1) the importance of transmembrane mucins affecting mucosal barrier function upon disease by modulating intracellular signaling pathways and subsequent junctional protein function and (2) that the loss of barrier integrity, which is generally accepted as a major hallmark of the IBD pathophysiology,⁸ is present in the colonic mucosa of IBD patients irrespective of the presence of inflammation.

Due to the large heterogeneity described in IBD, it is difficult to find the right therapy for the right patient. Currently, clinicians prefer mucosal healing as a therapeutic endpoint, and thus the restoration of mucosal barrier integrity, but molecular markers to monitor mucosal barrier function in IBD patients are currently lacking. In our study, PCA and sPLS-DA identified key mucins that clearly distinguished patients with an IBD subtype (CD: MUC3B; UC: MUC1, MUC3A, MUC4, MUC13) from non-IBD cases with gastrointestinal complaints. Previous reports also reported a dysregulation of MUC1, MUC4, and MUC13 expression in the colon of adult IBD patients, highlighting them as interesting biomarkers to aid in IBD diagnosis.^8,15,17 Subsequently, we also compared the performance of calprotectin and mucin mRNA expression levels to distinguish IBD patients and non-IBD control subjects using LASSO regression models and ROC analyses. Whereas calprotectin levels overall showed a better performance compared with mucin mRNA levels (except for CD patients vs non-IBD control subjects), the inclusion of both calprotectin and mucin mRNA levels showed the highest discriminative performance in most models (except for UC patients vs non-IBD control subjects). These findings clearly highlight the added value of measuring mucin expression levels in the intestinal mucosa to define IBD presentation and subtypes. Furthermore, as we also observed differences in the mRNA expression of MUC1, MUC4, and MUC13 between inflamed and noninflamed colonic tissue of UC patients, the evaluation of mucin expression might be a valuable tool to assess mucosal healing in these patients.

Finally, striking correlations also existed between the key mucins for IBD diagnosis and subtypes and certain clinical parameters. A strong association between MUC3A, MUC3B, and MUC4 mRNA expression and clinical disease activity, as reflected by the PUCAI for UC and the PCDAI for CD patients, was identified, whereas MUC1, MUC2, MUC4, and MU13 mRNA expression correlated with the Mayo score, reflecting colitis severity as observed during endoscopy. Similarly, a positive correlation between MUC1 and disease activity^25,26 as well as an association between altered MUC2 glycosylation and disease severity have also been reported in adult-onset IBD.²⁷ We additionally also observed associations between MUC2 mRNA expression and stool frequency and consistency, and between MUC13 mRNA expression and rectal bleeding and stool frequency, which might be the result of reciprocal effects from changes in intestinal barrier integrity and inflammation as well as changes in the intestinal microbiome.^8,28 All these correlations further emphasize the potential role of mucosal mucin mRNA expression profiles in shaping the IBD phenotype.

Nevertheless, this study has several limitations. During endoscopy, sample collection of inflamed and noninflamed tissue was performed based on macroscopic characteristics (Simple Endoscopic Score and Mayo score). Although colonic biopsies were also examined by microscopy, we cannot rule out that mild inflammatory lesions were present in adjacent biopsies of macroscopically noninflamed regions that were used for mRNA expression analyses, which could potentially affect the expression of mucins or barrier mediators. Second, our control group comprised children that presented with gastrointestinal complaints at the time of endoscopy but were not diagnosed with IBD. Although the presence of intestinal mucosal inflammation was negligible, they could possess certain intestinal mucosal barrier defects, which may bias our results. Finally, although the overall effect of IBD treatment on individual mucin expression was minor, MUC13 mRNA expression in the noninflamed colon of IBD patients showed a trend toward statistical significance (P = .054) when comparing patients under treatment with treatment-naïve patients. Of note, we did not make a distinction between the different treatment categories, and future studies are recommended to further investigate this aspect.

Conclusions

In summary, we identified mucin mRNA signatures as having great potential to discriminate pediatric-onset IBD patients from non-IBD control subjects and to monitor mucosal healing in children diagnosed with UC. However, an adequate independent external validation (ie, mucin expression measurements at baseline and during treatment follow-up) in other large sets of IBD patients (both pediatric and adult cohorts) is recommended to further evaluate the potential of these mucin mRNA signatures as novel molecular biomarker for the diagnosis and follow-up of IBD patients.

Supplementary Data

Supplementary data is available at Inflammatory Bowel Diseases online.

Acknowledgments

We thank Lieve Vits, Mandy Vermont, Liesbet Goossens, Petra Aerts, and Marleen Vinckx for their skilled technical assistance.

Author Contribution

T.B., B.Y.D.W., N.M., and A.S. contributed to the concept and design of the study. T.B., W.A., E.B., L.-E.B., L.K., E.V.d.V., A.V.G., and N.M. were responsible for patient inclusion and collection of colonic tissue samples from inflammatory bowel diseasepatients and non–inflammatory bowel disease control subjects. Data curation was performed by T.B., W.A., E.B., L.-E.B., and L.K. T.B. and A.S. wrote the first version of the manuscript. The tables and figures were created by T.B., E.B., L.-E.B., L.K., and A.S. Review and editing of the manuscript were performed by T.B., WA, J.D.M., B.Y.D.W., N.M., and A.S. All the authors contributed to the analysis and interpretation of the data and approved the final draft.

Funding

This work was supported by the University of Antwerp (DOCPRO4 34782, IOF-SBO 42601).

Conflicts of Interest

T.B., B.Y.D.W. and A.S. are inventors on a patent related to mucin isoforms in diseases characterized by barrier dysfunction, including inflammatory bowel disease, irritable bowel syndrome, gastrointestinal infections and cancer (WO/2021/013479). The other authors declared no conflicting interests.

Data Availability

The data underlying this article will be shared on reasonable request to the corresponding author.

Author notes

Shared senior authorship.