Abstract

Irritable bowel syndrome (IBS), inflammatory bowel disease (IBD), and celiac disease (CeD) present with similar gastrointestinal (GI) symptoms. DNA methylation-based biomarkers have not been investigated as diagnostic biomarkers to classify these disorders. We aimed to study DNA methylation profiles of IBS, IBD, CeD, and healthy controls (HC), develop machine learning-based classifiers, and identify associated gene ontology (GO) terms. Genome-wide DNA methylation of peripheral blood mononuclear cells from 315 patients with IBS, IBD, CeD, and HC was measured using Illumina's 450K or EPIC arrays. A methylation dataset on 304 IBD and HC samples was used for external validation. Differential methylation was measured using general linear models. Classifiers were developed using penalized generalized linear models using double cross-validation controlling for confounders. Functional enrichment was assessed using GO. Three hundred and fifteen participants (148 IBS, 47 IBD, 34 CeD, and 86 HC) had DNA methylation data. IBS-IBD and IBD-CeD showed the highest number of differentially methylated CpG sites followed by IBD-HC, CeD-HC, and IBS-HC. IBS-associated genes were enriched in cell adhesion and neuronal pathways, while IBD- and CeD-associated markers were enriched in inflammation and MHC class II pathways, respectively (p < 0.05). Classification performances assessed using area under the receiver operating characteristic curves (AUC) for IBS-IBD, IBS-CeD, and IBD-CeD were 0.80 (95% CI = 0.7-0.87, p = 6.75E-10), 0.78 (95% CI = 0.68-0.86, p = 4.57E-10), and 0.73 (95% CI = 0.62-0.83, p = 0.03), respectively. The performance of IBD-HC was successfully validated using external data (AUC = 0.74 [95% CI = 68-0.80, p < 0.001]). Blood-based DNA methylation biomarkers can potentially distinguish chronic GI disorders that present with similar symptoms. GO suggested functional significance of the classifiers in disease-specific pathology.

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