Iris H. Jonkers

This paper develops an autologous co-culture system to study human intestinal IEL-epithelial interactions, showing both non-destructive and cytotoxic responses under different conditions.

This study compares hiPSC-derived intestinal epithelial cells cultured in organoids, Transwells, and intestine-on-chip systems, showing that the latter promotes stronger gene expression related to nutrient and drug metabolism and a more mature state.

This study shows that repeated cytokine exposure in endothelial cells induces memory-like responses, linking chronic inflammation to vascular disease risk through persistent transcriptional and epigenetic changes.

This study shows that butyrate increases global histone acetylation by preventing p300 recruitment to acetylated histones, rather than targeting specific genomic regions.

This study identifies gene expression patterns and eQTLs in duodenal epithelial lining of coeliac disease patients that reflect inflammation status and disease condition.

This study analyzes the gut microbiome of treated coeliac disease patients at strain level, revealing increased interindividual variation and specific microbial associations.

This study identifies 13 novel genetic associations for celiac disease, with the 5p15.33 locus showing strong potential, and links IRX1 to rheumatoid arthritis.

This paper links common and rare disease genetics by identifying key genes affected by common variants through gene regulatory networks, finding many key genes are outside GWAS loci.

The paper improves genetic mapping resolution in autoimmune diseases by identifying shared alleles across multiple conditions and reveals widespread shared mechanisms.

The paper identifies TRAFD1 as a master regulator of IFNγ signalling in celiac disease by systematically prioritizing candidate genes in disease loci using multiple computational methods.

The paper introduces Decon2, a method to deconvolute bulk blood eQTL effects into immune cell subpopulations, showing high concordance with experimental and single-cell studies.

The paper predicts Xist-induced gene silencing kinetics using a Random Forest model based on epigenetic and genomic features, identifying key factors like distance to Xist and promoter pre-marking.