Cutting Edge: Hypoxia Sensing by the Histone Demethylase UTX (KDM6A) Limits Colitogenic CD4+ T Cells in Mucosal Inflammation.

Hypoxia is a hallmark of inflammatory conditions (e.g., inflammatory bowel disease [IBD]), and adaptive responses have consequently evolved to protect against hypoxia-associated tissue injury. Because augmenting hypoxia-induced protective responses is a promising therapeutic approach for IBD, a more complete understanding of these pathways is needed. Recent work has demonstrated that the histone demethylase UTX is oxygen-sensitive, but its role in IBD is unclear. In this study, we show that hypoxia-induced deactivation of UTX downregulates T cell responses in mucosal inflammation. Hypoxia results in decreased T cell proinflammatory cytokine production and increased immunosuppressive regulatory T cells, and these findings are recapitulated by UTX deficiency. Hypoxia leads to T cell accumulation of H3K27me3 histone modifications, suggesting that hypoxia impairs UTX's histone demethylase activity to dampen T cell colitogenic activity. Finally, T cell-specific UTX deletion ameliorates colonic inflammation in an IBD mouse model, implicating UTX's oxygen-sensitive demethylase activity in counteracting hypoxic inflammation.

CoVar: A generalizable machine learning approach to identify the coordinated regulators driving variational gene expression.

Network inference is used to model transcriptional, signaling, and metabolic interactions among genes, proteins, and metabolites that identify biological pathways influencing disease pathogenesis. Advances in machine learning (ML)-based inference models exhibit the predictive capabilities of capturing latent patterns in genomic data. Such models are emerging as an alternative to the statistical models identifying causative factors driving complex diseases. We present CoVar, an ML-based framework that builds upon the properties of existing inference models, to find the central genes driving perturbed gene expression across biological states. Unlike differentially expressed genes (DEGs) that capture changes in individual gene expression across conditions, CoVar focuses on identifying variational genes that undergo changes in their expression network interaction profiles, providing insights into changes in the regulatory dynamics, such as in disease pathogenesis. Subsequently, it finds core genes from among the nearest neighbors of these variational genes, which are central to the variational activity and influence the coordinated regulatory processes underlying the observed changes in gene expression. Through the analysis of simulated as well as yeast expression data perturbed by the deletion of the mitochondrial genome, we show that CoVar captures the intrinsic variationality and modularity in the expression data, identifying key driver genes not found through existing differential analysis methodologies.

Aberrant miR-29 is a predictive feature of severe phenotypes in pediatric Crohn's disease.

Crohn's disease (CD) is a chronic inflammatory gut disorder. Molecular mechanisms underlying the clinical heterogeneity of CD remain poorly understood. MicroRNAs (miRNAs) are important regulators of gut physiology, and several have been implicated in the pathogenesis of adult CD. However, there is a dearth of large-scale miRNA studies for pediatric CD. We hypothesized that specific miRNAs uniquely mark pediatric CD. We performed small RNA-Seq of patient-matched colon and ileum biopsies from treatment-naive pediatric patients with CD (n = 169) and a control cohort (n = 108). Comprehensive miRNA analysis revealed 58 miRNAs altered in pediatric CD. Notably, multinomial logistic regression analysis revealed that index levels of ileal miR-29 are strongly predictive of severe inflammation and stricturing. Transcriptomic analyses of transgenic mice overexpressing miR-29 show a significant reduction of the tight junction protein gene Pmp22 and classic Paneth cell markers. The dramatic loss of Paneth cells was confirmed by histologic assays. Moreover, we found that pediatric patients with CD with elevated miR-29 exhibit significantly lower Paneth cell counts, increased inflammation scores, and reduced levels of PMP22. These findings strongly indicate that miR-29 upregulation is a distinguishing feature of pediatric CD, highly predictive of severe phenotypes, and associated with inflammation and Paneth cell loss.

Linking gene expression to clinical outcomes in pediatric Crohn's disease using machine learning.

Pediatric Crohn's disease (CD) is characterized by a severe disease course with frequent complications. We sought to apply machine learning-based models to predict risk of developing future complications in pediatric CD using ileal and colonic gene expression. Gene expression data was generated from 101 formalin-fixed, paraffin-embedded (FFPE) ileal and colonic biopsies obtained from treatment-naïve CD patients and controls. Clinical outcomes including development of strictures or fistulas and progression to surgery were analyzed using differential expression and modeled using machine learning. Differential expression analysis revealed downregulation of pathways related to inflammation and extra-cellular matrix production in patients with strictures. Machine learning-based models were able to incorporate colonic gene expression and clinical characteristics to predict outcomes with high accuracy. Models showed an area under the receiver operating characteristic curve (AUROC) of 0.84 for strictures, 0.83 for remission, and 0.75 for surgery. Genes with potential prognostic importance for strictures (REG1A, MMP3, and DUOX2) were not identified in single gene differential analysis but were found to have strong contributions to predictive models. Our findings in FFPE tissue support the importance of colonic gene expression and the potential for machine learning-based models in predicting outcomes for pediatric CD.

TNF promoter hypomethylation is associated with mucosal inflammation in IBD and anti-TNF response.

Background and aims: Inflammatory Bowel Diseases (IBD) are chronic inflammatory conditions influenced heavily by environmental factors. DNA methylation is a form of epigenetic regulation linking environmental stimuli to gene expression changes and inflammation. Here, we investigated how DNA methylation of the TNF promoter differs between inflamed and uninflamed mucosa of IBD patients, including anti-TNF responders and non-responders. Methods: We obtained mucosal biopsies from 200 participants (133 IBD and 67 controls) and analyzed TNF promoter methylation using bisulfite sequencing, comparing inflamed with uninflamed segments, in addition to paired inflamed/uninflamed samples from individual patients. We conducted similar analyses on purified intestinal epithelial cells from bowel resections. We also compared TNF methylation levels of inflamed and uninflamed mucosa from a separate cohort of 15 anti-TNF responders and 17 non-responders. Finally, we sequenced DNA methyltransferase genes to identify rare variants in IBD patients and functionally tested them using rescue experiments in a zebrafish genetic model of DNA methylation deficiency. Results: TNF promoter methylation levels were decreased in inflamed mucosa of IBD patients and correlated with disease severity. Isolated IECs from inflamed tissue showed proportional decreases in TNF methylation. Anti-TNF non-responders showed lower levels of TNF methylation than responders in uninflamed mucosa. Our sequencing analysis revealed two missense variants in DNMT1, one of which had reduced function in vivo. Conclusions: Our study reveals an association of TNF promoter hypomethylation with mucosal inflammation, suggesting that IBD patients may be particularly sensitive to inflammatory environmental insults affecting DNA methylation. Together, our analyses indicate that TNF promoter methylation analysis may aid in the characterization of IBD status and evaluation of anti-TNF therapy response.