IBD risk loci are enriched in multigenic regulatory modules encompassing putative causative genes.

GWAS have identified >200 risk loci for Inflammatory Bowel Disease (IBD). The majority of disease associations are known to be driven by regulatory variants. To identify the putative causative genes that are perturbed by these variants, we generate a large transcriptome data set (nine disease-relevant cell types) and identify 23,650 cis-eQTL. We show that these are determined by ∼9720 regulatory modules, of which ∼3000 operate in multiple tissues and ∼970 on multiple genes. We identify regulatory modules that drive the disease association for 63 of the 200 risk loci, and show that these are enriched in multigenic modules. Based on these analyses, we resequence 45 of the corresponding 100 candidate genes in 6600 Crohn disease (CD) cases and 5500 controls, and show with burden tests that they include likely causative genes. Our analyses indicate that ≥10-fold larger sample sizes will be required to demonstrate the causality of individual genes using this approach

Flooding of tunnels: quantifying climate change effects on infrastructure

To develop climate proof road infrastructure it is of importance to understand the quantitative effects of expected climate change on the performance of individual components, such as tunnels and road sections, and their contributions to the performance of the overall road network.A full understanding of quantitative effects on infrastructure and the effect of measures is currently lacking. In this study, a method is developed to quantify the effects of climate change on infrastructure by performing a resilience analysis of individual objects. To illustrate this method the frequency of flooding due to (extreme) rainfall induced by climate change of a fictitious tunnel in The Netherlands, is studied as a test case. This structured method is a promising technique that might be a good basis for decision making processes. The analysis shows that several data is missing, both climatological data as well as quantified requirements on the performance of infrastructural components