Single cell heterogeneity and dynamics of immune cell-populations in IBD (Inflammatory Bowel Disease) and PSO (Psoriasis)


Single cell heterogeneity and tissue context of cellular function is an important layer of information which so far has been inaccessible. Single cell genomics (SCG) allows investigation of cellular programs and dynamics of specific cellular subtypes. The subproject will focus on transcriptomic and epigenetic marks of 1) spatial inflammatory differences, 2) therapy response, 3) early prediction to therapy outcome and 4) reprogramming through sequential therapies within single cells. As an integral part of the observational clinical studies to be performed within the consortium, this subproject will assess tissue biopsies(and blood)of a subgroup of patients prior to therapy, at defined time points during therapy and after therapy to determine potential long-term changes in inflammatory cell content. WP1will focus on generating SCG data from biopsy material to be obtained from ongoing trials for IBD (anti-TNF), PSO (anti-IL17), for both (anti-IL12/23) as well as from sequential therapies including two of the above described treatment options in a sequential order. Using SCG technologies established at the PRECISE Platform for Single Cell Genomics and Epigenomics in Bonn sequential samples (up to four) for up to 10 patients within each cohort will be analyzed and compared. Both healthy adjacent as well as diseased tissue will be included. In WP2we will follow very recent computational approaches to model distribution of cells within the tissue. In WP3we will closely collaborate with SP4combining complementary technology to define spatial resolution. The goal will be to further improve spatial predictions of inflammatory mechanisms based on single cell data themselves. In WP4we will assess open chromatin structure on the single cell level by scATAC-seq. All data generated in SP3 will be provided to SP6 for integration into a multi-omics approach to build predictive long-term therapy outcome models.

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