DNA Methylation and Transcription Patterns in Intestinal Epithelial Cells From Pediatric Patients With Inflammatory Bowel Diseases Differentiate Disease Subtypes and Associate With Outcome

Background & Aims We analyzed DNA methylation patterns and transcriptomes of primary intestinal epithelial cells (IEC) of children newly diagnosed with inflammatory bowel diseases (IBD) to learn more about pathogenesis. Methods We obtained mucosal biopsies (N = 236) collected from terminal ileum and ascending and sigmoid colons of children (median age 13 years) newly diagnosed with IBD (43 with Crohn’s disease [CD], 23 with ulcerative colitis [UC]), and 30 children without IBD (controls). Patients were recruited and managed at a hospital in the United Kingdom from 2013 through 2016. We also obtained biopsies collected at later stages from a subset of patients. IECs were purified and analyzed for genome-wide DNA methylation patterns and gene expression profiles. Adjacent microbiota were isolated from biopsies and analyzed by 16S gene sequencing. We generated intestinal organoid cultures from a subset of samples and genome-wide DNA methylation analysis was performed. Results We found gut segment-specific differences in DNA methylation and transcription profiles of IECs from children with IBD vs controls; some were independent of mucosal inflammation. Changes in gut microbiota between IBD and control groups were not as large and were difficult to assess because of large amounts of intra-individual variation. Only IECs from patients with CD had changes in DNA methylation and transcription patterns in terminal ileum epithelium, compared with controls. Colon epithelium from patients with CD and from patients with ulcerative colitis had distinct changes in DNA methylation and transcription patterns, compared with controls. In IECs from patients with IBD, changes in DNA methylation, compared with controls, were stable over time and were partially retained in ex-vivo organoid cultures. Statistical analyses of epithelial cell profiles allowed us to distinguish children with CD or UC from controls; profiles correlated with disease outcome parameters, such as the requirement for treatment with biologic agents. Conclusions We identified specific changes in DNA methylation and transcriptome patterns in IECs from pediatric patients with IBD compared with controls. These data indicate that IECs undergo changes during IBD development and could be involved in pathogenesis. Further analyses of primary IECs from patients with IBD could improve our understanding of the large variations in disease progression and outcomes.


Genome-wide Multi-Omics
Crohn's Disease [CD] Ulcerative Colitis We also obtained biopsies collected at later stages from a subset of patients. IECs were purified and analyzed for genome-wide DNA methylation patterns and gene expression profiles. Adjacent microbiota were isolated from biopsies and analyzed by 16S gene sequencing. We generated intestinal organoid cultures from a subset of samples and genome-wide DNA methylation analysis was performed. RESULTS: We found gut segment-specific differences in DNA methylation and transcription profiles of IECs from children with IBD vs controls; some were independent of mucosal inflammation. Changes in gut microbiota between IBD and control groups were not as large and were difficult to assess because of large amounts of intra-individual variation. Only IECs from patients with CD had changes in DNA methylation and transcription patterns in terminal ileum epithelium, compared with controls. Colon epithelium from patients with CD and from patients with ulcerative colitis had distinct changes in DNA methylation and transcription patterns, compared with controls. In IECs from patients with IBD, changes in DNA methylation, compared with controls, were stable over time and were partially retained in ex-vivo organoid cultures. Statistical analyses of epithelial cell profiles allowed us to distinguish children with CD or UC from controls; profiles correlated with disease outcome parameters, such as the requirement for treatment with biologic agents. CONCLUSIONS: We identified specific changes in DNA methylation and transcriptome patterns in IECs from pediatric patients with IBD compared with controls. These data I nflammatory bowel diseases (IBD) cause chronic relapsing inflammation that can affect any segments of the digestive tract (ie, Crohn's disease [CD]) or be restricted to the colon (ulcerative colitis [UC]). 1,2 Although these diseases can manifest at any age, approximately one quarter of patients 3 are diagnosed in childhood or early adulthood, when the disease course and subsequent outcomes can be particularly severe. 3 The etiology of IBD is multifactorial, although the interplay of factors is still poorly understood. Large-scale genome-wide association studies have helped to characterize the genetic risk, identifying over 200 diseaseassociated loci. 4,5 The striking overlap of genetic risk loci between CD, UC, and other immune-mediated diseases strongly suggests common immune regulatory pathways are affected in these conditions. 4,5 However, current estimates of the overall genetic contribution to IBD risk are still only 13% for CD and 8% for UC. The rapid increase in the incidence of IBD in recent decades, [6][7][8] the stability of the human genome, the dysbiosis of the gut microbiome, [9][10][11][12] as well as epidemiologic evidence, all suggest an association between the rise in IBD and the recent changes in our environment.
Epigenetic mechanisms operate at the interface between genetic predisposition and our environment, capable of causing stable, potentially heritable changes of cellular function in response to environmental triggers. 13,14 Consequently, epigenetics is being increasingly recognized as a highly plausible mechanism that may both initiate and then maintain intestinal mucosal inflammation in human IBD. A growing number of studies have reported IBD-associated alterations in epigenetic profiles, as well as associated changes in gene expression and/or cellular function. For example, DNA methylation (DNAm) changes in mucosal biopsies and peripheral blood mononuclear cells of both adults and children diagnosed with IBD have been demonstrated. 15,16 However, the vast majority of studies were performed on mixed cell tissue samples (eg, whole blood, peripheral blood mononuclear cells, or mucosal biopsies) and, possibly because of changes in cellular composition, demonstrated a strong effect of inflammation on the observed epigenetic changes. Importantly, advances made by epigenetic consortia such as ROADMAP, 17 BLUE-PRINT, 18 as well as single-cell RNA sequencing, have all demonstrated the importance of studying individual, disease-relevant cell types to best identify molecular alterations involved in pathophysiology.
Genetic and functional studies predominantly using mouse models and cell lines [19][20][21] have provided strong evidence for impaired function of the intestinal epithelium in IBD. Yet, these models have done little to explain how the complex interplay between environmental factors, host genetics, intestinal cell function, and the adjacent microbiome lead to the development of the IBD phenotype and its subsequent evolution. To better elucidate specific alterations in this jigsaw, a genome-wide multi-layered omics approach of carefully selected primary cell samples is required. Importantly, in addition to unravelling novel aspects of disease pathogenesis, this approach in diseaserelevant cell types (ie, the intestinal epithelium) could provide clinically relevant information. For example, in children and adults with IBD, it can be difficult to confidently distinguish CD from UC, with many patients remaining 'unclassified' despite disease progression. Intestinal epithelial cell (IEC)-specific 'omics' signatures have the potential to more rapidly and accurately diagnose the patient and, hence, improve the specificity of treatment management. Furthermore, variations of cell type-specific molecular profiles amongst IBD patients may be indicative of disease sub-phenotype and could therefore help to EDITOR'S NOTES

BACKGROUND AND CONTEXT
The intestinal epithelium is thought to play a critical role in the pathogenesis of inflammatory bowel Diseases (IBD), yet evidence derived from primary human tissue remain scarce.

NEW FINDINGS
Purified intestinal epithelium from children newly diagnosed with IBD display distinct epigenetic and transcriptional alternations, which are partly retained in organoid cultures and correlate with disease outcome.

LIMITATIONS
Relatively small patient numbers require validation in additional cohorts.

IMPACT
Stable epigenetic alterations in the intestinal epithelium of children with IBD may explain variations in disease outcome and have potential to be developed into disease prognostic biomarkers in the future.
understand the large variations in disease behavior and outcome.
Therefore, we simultaneously profiled genotype, epigenotype (ie, DNAm), gene expression, and the adjacent gut microbiota of highly purified IEC, obtained from children newly diagnosed with IBD and a matched cohort of non-IBD controls. We analyzed genome-wide 'omics' layers for potential IBD-specific alterations and functional consequences, as well as cross-talk between layers. Additionally, we generated intestinal epithelial organoids from patient biopsy samples and investigated their epigenetic profiles. Lastly, we applied statistical models to genome-wide datasets to test their ability to distinguish between disease subtypes, as well as potential correlation with disease outcome measures.

Patient Cohort
A cohort of 66 treatment-naïve children at diagnosis of their IBD, along with 30 age-and sex-matched non-inflammatory control children, were recruited by the Paediatric Gastroenterology team at Addenbrooke's Hospital during 2013-2016. This study was conducted with informed patient and/or carer consent as appropriate, and with full ethical approval (REC-12/EE/0482). Sample and patient details are provided in Supplementary Tables 1 and 2. Children with macroscopically and histologically normal mucosa who had a diagnosis of IBD ruled out served as the non-disease control group. Each patient's final clinical diagnosis was based on the revised Porto criteria. 22 At the diagnostic colonoscopy, additional mucosal biopsies were taken from the small bowel (ie, terminal ileum [TI]) and 2 large bowel sections (ie, ascending colon [AC] and sigmoid colon [SC]). A blood sample was taken for patient genotyping. Clinical phenotype and outcome data were prospectively recorded over a minimum of 18 months post-diagnosis (Supplementary Table 1). The inflammation status of a sample (inflamed vs non-inflamed) was based on the histology of a paired sample taken within 2 cm of samples at the time of the initial endoscopy. Longitudinal samples were taken from the TI and SC of a subset of patients that underwent repeat endoscopy (CD: n ¼ 14; UC: n ¼ 9).

Purification of Intestinal Epithelium
Biopsy samples were processed immediately and IECs purified using enzyme digestion and magnetic bead sorting for the epithelial cell adhesion molecule as described previously. 16,23 Mucus for the isolation of adjacent microbiota was collected during tissue processing from sieve and centrifugation supernatant, then pooled, pelleted, and stored at -80 C to extract DNA from the adjacent microbiota. Further information is provided in the Supplementary Methods.

Human Intestinal Epithelial Organoid Culture
Intestinal organoids were generated from mucosal biopsies by isolation of intestinal crypts and culturing as described previously and detailed in the Supplementary Methods section and Supplementary Table 4. 24 DNA and RNA Extraction DNA and RNA were extracted simultaneously from the same sample using the AllPrep DNA/RNA mini kit (Qiagen, Hilden, Germany). DNA from the adjacent microbiota was extracted using QIAamp DNA Stool Mini Kit and from whole blood using the DNeasy Blood and Tissue Kit (both Qiagen). DNA was bisulfite-converted using Zymo DNA methylation Gold kit (Zymo Research, Irvine, CA, USA).

Arrays and Sequencing
Genome-wide DNA methylation was profiled using the Illumina Infinium HumanMethylation450 and EPIC BeadChip platforms (Illumina, Cambridge, UK; Accession Number: E-MTAB-5463). Sample numbers are provided in Supplementary  Table S3. Expression profiling was performed using RNAsequencing (RNA-seq) at the University of Kiel, Germany using an established pipeline as described previously. 10  Locus-specific validation of DNA methylation profiles was performed on bisulfite-converted DNA after polymerase chain reaction amplification using the Pyromark Q24 (Qiagen) pyrosequencing system as described previously. 16

Bioinformatics Analyses
Extensive details of the bioinformatics methods used in this publication are described and referenced in the Supplementary Methods. Briefly, DNAm analyses were performed using minfi, 25 sva, 26 DMRcate, 27 and limma 28 R packages. RNAseq data was processed using established workflows. 10 Microbiota composition analysis was performed using QIIME and phyloseq. 29 Differential analysis was performed using limma 28 for DNAm data (false discovery rate [FDR] <0.01) and DESeq2 30 for gene expression data (FDR <0.01 and log fold change >±0.5). InnateDB 31 and the Reactome pathways were used to perform pathway enrichment analysis for the disease signatures identified from omics data layers. The diagnostic potential of omics data layers was tested using random forest classification models. Diagnostic accuracy was assessed via area under the receiver operator characteristic curve (AUC), precision scores, and receiver operator characteristic (ROC) curves. Weighted Gene Co-expression Network Analysis (WGCNA) 32 was applied to gene expression and DNAm data for each diagnosis (CD and UC) by gut segment to correlate omics datasets with clinical phenotypic variables.

DNA Methylation and Gene Expression Profiling of Purified Intestinal Epithelium Reveals Gut Segment-specific and Disease-associated Alterations
To investigate IEC pathophysiology in pediatric IBD, we first performed unsupervised analysis of genome-wide DNAm, gene expression, and 16S microbial profiles generated from a total of 170 samples ( Figure 1A and Table 1  Taken together, initial unsupervised analysis of genomewide intestinal epithelial profiles reveals highly gut segment-specific signatures and suggests disease-associated alterations of DNAm and gene expression.

Disease-specific Alterations in IEC Epigenetic and Transcriptional Profiles are Partly Independent of Inflammation Status
Given the distinct clustering patterns we observed on a genome-wide scale, we next used a variance component model to assess the relative contribution of diagnosis and inflammation to the observed variance within each data layer, by gut segment. As shown in Figure 2A, the variation explained by disease (ie, diagnosis) exceeds that of inflammation in the majority of datasets. This highlights the presence of disease-specific molecular alterations, which are partly independent of the current inflammatory activity. Full results of the variance decomposition analysis can be found in Supplementary Figure 3. To extend these findings, we performed separate differential analysis (gene expression and DNAm) of inflammation and disease in the colonic epithelium. This allowed us to identify, for each CpG site or gene, the relative significance of inflammation and disease. Results showed that a majority of the differentially methylated positions (DMPs) between CD or UC and controls are primarily driven by diagnostic status and not inflammation (FDR <0.01, Figure 2B and C). Similarly, diagnosis explained 74% and 82% of the differentially expressed genes (DEGs) for CD and UC, respectively ( Figure 2D and E).
Additionally, generating MDS plots by labelling samples according to gut segment, diagnosis, and inflammatory status did not show a clear separation between inflamed and non-inflamed samples (Supplementary Figure S1). Lastly, we also tested for the potential impact of inflammation on cellular composition in our purified samples by generating a gene expression heatmap of common epithelial and immune cell marker genes (Supplementary Figure S4). Although a number of genes were found to be differentially expressed between IBD and control samples (eg, DEFA5, DEFA6, LYZ, PLA2G2A, CD40, CD44), none of the marker genes correlated with inflammatory status, suggesting minimal impact of epithelial cell composition and immune cell contamination on the observed disease-specific molecular changes (Supplementary Figure S4).
In summary, these analyses demonstrate the presence of clear epigenetic, transcriptomic, and adjacent microbial alterations in the intestinal epithelium of children newly diagnosed with IBD, with a proportion being independent of intestinal inflammation.

Differential Methylation Analysis Reveals Disease-specific Signatures That Affect Gene Transcription
Next we performed differential DNAm and gene expression analyses by comparing control, CD-, and UC-derived datasets for each gut segment. When performing these analyses, inflammation was controlled for within the differential analysis thereby allowing us to focus on

February 2018
Intestinal Epithelial Multi-omics in IBD 589 molecular alterations that occur in relative independence of mucosal inflammation. Additionally, in an attempt to connect epigenetic and transcriptomic signatures, we identified differentially methylated regions (DMRs) that were located within 10kb of the transcription start site of a DEG. Such regions were termed regulatory DMRs (rDMRs).
Analysis of ileal IECs revealed CD-specific changes in both DNAm (Figure 3Ai    CpGs and genes with significant P values are plotted in purple for inflammation, in red for diagnosis, and in green if significant for both comparisons.
Adjusted P < .01 was considered as significant.
identified when comparing UC with controls. Importantly, amongst identified rDMRs, several have previously been reported to be associated with IBD (eg, CASP1 33 and APOA1 9 ) ( Figure 3B).
Contrary to the ileum, changes observed in the SC reflected a 'common IBD' signature, with a major overlap between UC and CD signatures and only a single significant DEG (RARRES3 [Retinoic Acid Receptor Responder 3]) identified between the 2 diagnoses ( Figure 3C and Supplementary Tables 9-14). RARRES3 is thought to have growth inhibitory and cell differentiation activities. One example of an rDMR that jointly affects CD and UC in the colon is BACH2 (Figure 3D), a transcription regulator, where a decrease in DNAm matched the increase in gene expression levels in both CD and UC patients. Interestingly, a proportion of the CD-related changes identified in TI samples were also found to be present in SC samples (Supplementary Figure 5).
Overall, these results indicate that CD-specific DNAm and gene-expression changes are present in ileal IECs. In

February 2018
Intestinal Epithelial Multi-omics in IBD 591 contrast, molecular changes observed in the colonic epithelium revealed a major overlap between CD and UC, reflecting a 'common IBD' signature.

Pathway Enrichment Analysis of Identified rDMRs Reveal Both Common IBD and Disease-specific Pathways
The intestinal epithelium serves a wide range of functions as a physical, chemical and immunological barrier and a bridge between the innate and adaptive immune response. 34 We used pathway enrichment analysis to investigate functional pathways (of rDMRs) that may be altered at diagnosis in a child with IBD. A wide variety of immune system-, metabolism-, and signal transduction-related pathways were significantly enriched (Figure 4). Many of the immune system-related pathways (eg, interferon signaling and immuno-regulatory interactions) are shared between the gut segments and diagnoses; suggesting common alterations are present in IBD. Moreover, several of the significantly enriched pathways have previously been implicated in either IBD pathogenesis or IEC function ( Figure 4).

IBD-associated intestinal Epithelial-specific Epigenetic Alterations are Stable Over Time and Partly Retained in Ex-vivo Organoid Culture
Next, we investigated the stability of IEC DNAm profiles in IBD patients over time. We obtained ileal and colonic biopsies (SC) from IBD patients both at diagnosis and at a later stage in their disease (n ¼ 14 CD, n ¼ 9 UC). Strikingly, CD-and UC-associated DMPs showed remarkable stability over time, demonstrated by the strong correlations of the methylation values at diagnosis and repeat endoscopy within each gut segment ( Figure 5A and Supplementary Figure 6). This was in spite of changes to the underlying mucosal inflammatory status (see Supplementary Table 1). To further test the stability and potential inflammation independence of disease-specific epigenetic alterations in IBD-derived IEC, we generated patient-derived intestinal organoids from an additional cohort of children newly diagnosed with CD (n¼5) and matched healthy controls (n¼7). Expansion of mucosal crypts from TI and SC in culture gave rise to 3-dimensional organoids ( Figure 5B). Organoids derived from CD patients did not differ in their microscopic appearance or culturing behavior from those derived from healthy controls ( Figure 5B). However, assessing their genome-wide DNA methylation profiles revealed distinct alterations, suggesting that they retain a proportion of disease-associated epigenetic changes.
Despite the relatively small sample number, CD-associated DMPs (ie, identified in Figure 3) showed a clear trend to be also differentially methylated in CD-derived compared with control organoids. This was indicated by the presence of inflated P values (larger difference between observed vs expected P values) of CD-associated DMPs compared with randomly selected CpGs ( Figure 5C). Using locus-specific pyrosequencing, we were able to validate a subset of CDspecific DMPs that were retained in organoid cultures ( Figure 5D and 5E).
Together, these data demonstrate that diseaseassociated epigenetic alterations in the intestinal epithelium are stable over time and are at least in part retained in ex-vivo organoid cultures.

Intestinal Epithelial DMRs, DEGs, and rDMRs are Enriched Around Genetic IBD Risk Loci
Genome-wide association studies have successfully identified over 200 loci predisposing to IBD. 4,5 However, limited information is currently available on the potential mechanisms involved in mediating genetic risk and/or which cell types are particularly affected. Here we used our epithelial cell-derived molecular signatures to test for an enrichment of disease-specific DMRs, DEGs, and rDMRs within genomic IBD risk loci. We observed highly significant enrichment of DMRs, DEGs, and rDMRs in both colonic and ileal IECs for IBD risk loci, while limited enrichment was found for genetic variants that have been linked to other multifactorial diseases with an immune-mediated pathogenesis, such as Type 1 diabetes and multiple sclerosis (Supplementary Figure 7). Together these results suggest that interactions between the IBD risk loci and DNAm and/or transcription may occur in children carrying disease variants.

IEC DNA Methylation and Gene Expression Signatures Accurately Predict Disease Status and Correlate With Clinical Outcome Measures
Given the striking IBD-associated changes observed in intestinal epithelial DNAm and gene expression, we went on to test the ability of these signatures to predict diagnosis. Additionally, we hypothesized that variation observed within IBD-derived patient samples could be indicative of future disease behavior and outcome. To address these hypotheses, we applied a machine-learning model (random forest) to the individual omics data layers. The model identified those data points (eg, CpGs, genes, operational taxonomic units) that could predict disease status for each patient with high precision and accuracy (see Supplementary Methods section for further details). As demonstrated in Figure 6, DNAm data derived from either gut segment produced a model with a high AUC (>0.8) ( Figure 6A). The best model separating disease from control was based on DNAm data from the SC (AUC¼0.94, cross-validation (CV)¼40) with sensitivity of 75% and specificity of 100% (Figure 6Ai and 6Aii). Importantly, the use of ileal DNAm datasets allowed separation between CD and UC with high precision (77%), sensitivity (57%), and specificity (93%) (AUC¼0.92, CV¼24) ( Figure 6B). The accuracy of the TI DNAm signatures in distinguishing CD and UC was confirmed in a follow-up patient cohort, analyzed using a second DNAm array platform (Illumina EPIC array, see Methods and Supplementary Figure 8). Full details of the models, including AUC, sensitivity, and specificity, can be found in Supplementary Table 15. In contrast, models built using the IBD risk loci from our patient genotyping data yielded the lowest model score (AUC¼0.49) (Figure 6Ai).
To correlate genome-wide IEC profiles with clinical outcome measures (including binary, numerical, and categorical parameters) we used a Weighted Gene Co-expression Network Analysis (WGCNA) approach. WGCNA identifies patterns within a given dataset (ie, RNAseq data) and combines genes or CpGs that vary similarly across samples into modules. Each of these modules was then tested for a significant correlation with clinical outcomes. The application of WGCNA to RNAseq data derived from the TI of CD patients led to the identification of several gene modules (ie, groups of genes) that correlate significantly (correlation >±0.6, P < .05) with a number of disease outcome measures including the requirement for treatment with biologics and number of treatment escalations within the first 18 months following diagnosis ( Figure 6C). Interestingly, modules correlating with disease outcome measures did not show any correlation with gender, age, or disease phenotype at diagnosis (eg, abdominal pain, diarrhea, and Pediatric Crohn's Disease Activity Index). Clustering all samples according to expression levels of genes within the strongest modules separated CD patients in 2 groups (Figure 6Di). Kaplan Meier curves for these groups demonstrated striking differences in both the requirement for biologics and time to third treatment escalation (Figure 6Dii and 6Diii). In addition, we applied WGCNA to the DNAm data. Although the overall correlation of identified modules was less striking, separating samples according to DNAm profiles of the strongest module still demonstrated a significant difference in outcome measures between resulting patient groups (Figure 6Ei-6Eiii). Similar results were obtained from UC patient-derived signatures in SC samples (Supplementary Figure 9). Finally, comparing annotated genes from the top modules identified in RNAseq and DNAm datasets revealed an overlap of 57% and 79%, respectively, suggesting that expression signatures might be in part underpinned by stable epigenetic changes ( Figure 6F). Based on these preliminary results, both DNAm and RNAseq data contain signatures that accurately predict disease status and correlate with selected disease outcome parameters.

Discussion
Substantial evidence suggests that impaired function of the intestinal epithelium plays a major role in IBD pathogenesis. However, our current understanding of the exact mechanisms remains limited. It is also becoming increasingly clear that functional alterations in complex disease are likely to be caused by and/or result in a multifaceted interplay between several layers of cellular regulation. Specific to the GI tract, the intestinal microbiota adds further complexity because it has been shown to influence cellular function of the intestinal epithelium both in health and IBD. 9,10,12 Given the wide range of phenotypes and diverse spectrum of disease behavior within the conditions we currently label as CD and UC, we urgently require novel molecular signatures to allow better classification of clinically relevant disease entities.
Here, we applied a multi-omics profiling approach to a highly purified IEC sample set obtained from a prospectively recruited, treatment-naïve, pediatric patient cohort. Unsupervised analysis revealed fundamental differences in the methylation and gene expression profiles by gut segment. 9,10,16 Moreover, within each gut segment, we observed distinct disease-specific variation in both DNAm and gene expression, which were found to be partly independent of the presence or absence of microscopic mucosal inflammation. Specifically, we found that the majority of DNAm and RNAseq disease signatures from the SC were not primarily explained by inflammation status. This strongly suggests that there are underlying epigenetic and transcriptomic changes within IECs in IBD patients, which are present irrespective of inflammatory activity. Our findings further expand on previous studies using whole gut biopsies, which reported major transcriptional or epigenetic changes that were primarily associated with the presence of mucosal inflammation. 9,10 Although we also observed a strong, inflammation-associated signal, purification of the intestinal epithelium (and thereby removal of infiltrating immune cells) has allowed identification of a cell typespecific signature that does not seem to be exclusively driven by mucosal inflammation.
In contrast to genome-wide DNAm and gene transcription profiles, unsupervised MDS analysis of our 16S data did not show any specific sample clusters and/or clear association with key phenotypes such as gut segment, disease entity or inflammation. This is most likely because of the large interindividual and intra-individual variation; an observation that has been previously reported by others. 9,11,12 However, supervised analyses revealed gut segment as well as diseaseassociated changes in microbial composition. Analysis of the 16S data in combination with the epithelial omics data was unable to identify strong correlations between DEGs and 16S abundances or dose-dependent relationships for subgroups of patients. Nevertheless, we consider the fact that our 16S data was generated from microbes isolated from individual gut segments as novel and therefore potentially highly valuable as reference for future work in this rapidly evolving field.
Further investigating disease-specific DNAm and gene expression changes, we were able to identify a number of significant DEGs and DMRs, a proportion of which overlapped (rDMRs), indicating a functional interconnection between the 2 data layers. Reassuringly, a number of identified genes had previously been reported, including APOA1 12 and CASP1. 9 When comparing identified DMRs, DEGs, and rDMRs, we discovered that significant changes in the TI were only present in CD-derived samples. In contrast, analysis in the colonic epithelium showed both CD-and UC-specific changes, which also displayed a major overlap likely reflecting common phenotypic features shared between the 2 conditions. Together these data suggest the presence of a CD-specific signature in the TI epithelium and a common IBD signature in the SC. The identification of shared, enriched pathways for the 2 diagnoses further supports this hypothesis. Additionally, enrichment for pathways implicated in the cross-talk between cells of the innate and adaptive immune response highlights the important role of the intestinal epithelium in orchestrating intestinal host defense and suggests that alterations in these key processes may lead to the initiation and/or persistence of gut inflammation in IBD.
The impact of the observed IEC-specific epigenetic alterations on IBD pathogenesis will depend at least in part on the stability of such molecular signatures. Investigating IEC DNAm profiles of the same patient at 2 time points (ie, at diagnosis and at later disease stage) allowed us to demonstrate the strikingly high stability of disease-associated methylation signatures in small bowel and colonic IEC. This was despite changes in medication and mucosal inflammation over a period of up to 20 months. These findings suggest that stable epigenetic alterations may contribute to chronic relapsing inflammation by mediating altered IEC function. Interestingly, CD-derived epithelium appeared to retain a degree of disease-specific alterations even when cultured ex-vivo as organoids, further highlighting both their stability and relative independence of mucosal inflammation. Additionally, our findings add further support to recent reports on patient-derived intestinal organoids to be used as novel translational research tools. 35 Despite the major success of genome-wide association studies in identifying disease-predisposing genetic loci, information on the functional consequences and cell specificity remain limited. Expression quantitative trait loci have been identified for a subset of the IBD risk loci from whole biopsies 36 and blood cell subsets. 37 More recently, differences in DNAm and chromatin conformation 38 were also identified for a subset of the IBD risk loci in immune cells. 39 Our study adds further detail and specificity by demonstrating enrichment of disease-specific DMRs, DEGs, and rDMRS within IBD susceptibility loci 4,5 in both gut segments.
An additional major strength of our prospectively recruited pediatric patient cohort was the availability of Validation of genome-wide DNAm data using pyrosequencing. n ¼ 5-7 per group; *P < .05; ***P < .001; unpaired, 2-tailed ttest between Ctrl and CD. detailed phenotype and disease outcome data, allowing us to test for potential correlation between molecular signatures and clinical phenotypes. Despite the relatively small sample numbers included in these analyses, both the potential diagnostic and prognostic value of our IEC signatures is evident. While current diagnostic approaches are sufficient for most patients, a minority of patients requires repeated and prolonged investigations to confirm a diagnosis. Additionally, it is frequently challenging to differentiate UC from CD in children, both at diagnosis and later in the disease course. Therefore, a diagnostic model to reliably differentiate CD from UC, such as the model built using DNAm data from the ileum with high sensitivity and specificity, could be of clinical value. Correlating genome-wide molecular signatures with clinical outcome measures continues to be a major challenge and a wide range of bioinformatics tools have been developed. We decided to utilize WGCNA, which has been successfully applied to both RNA-seq and DNAm datasets, allowing identification and correlation of individual gene modules with clinical parameters. 40 Results are highly encouraging because we discovered a number of gene expression modules that correlated strongly with the number of relapses and the requirement for treatment with biologics. Interestingly, overlapping modules derived from applying WGCNA to RNAseq data with those derived from DNAm data revealed a major overlap, suggesting prognostic expression signatures maybe at least in part underpinned by epigenetic changes.
As a limitation to our study, we acknowledge that the total number of patients included is relatively low and hence some of the analyses performed, particularly those that correlate signatures with clinical outcome, should be considered as preliminary. However, to the best of our knowledge this is the first and largest study applying a multi-omics profiling approach to a unique sample collection of highly purified intestinal epithelium. The fact that all patients were recruited at diagnosis (treatment-naïve) also represents an important strength. Last but not least, although our study was performed on a pediatric patient cohort, we consider our findings to be equally relevant to adult-onset IBD given the similarities in disease phenotype (particularly in teenage onset) and common concepts of disease pathogenesis.
In summary, our study is the first to apply a multi-omics profiling approach to a large collection of purified intestinal epithelial samples. The findings clearly demonstrate disease-specific abnormalities in epithelial cell function in children with IBD. We also highlight how specific data signatures might be indicative of disease status and behavior and therefore have a potential to be of clinical relevance in the future.