The genetic risk map of chronic inflammatory diseases (CID) points to a large number of involved loci and associated biological processes. Although different cellular pathways can be affected by genetic variants in individual patients ( e.g. classical cytokines of the adaptive immune system like IL17/23 vs. autophagic processes (ATG16/ATG5/LRRK2)) the overt symptoms and pathologic appearance is highly similar and cannot guide individualized therapy decisions. Importantly, a detailed and dynamic picture of therapeutic response and non-response in relation to genetic and epigenetic determinants is still missing.
Aim of the project is to annotate dynamic processes of approved targeted therapies acting against specific pathways ( e.g. TNF/IL6) and to improve our understanding of disease pathophysiology and drug response mechanisms. The specific systems biology set up is fostered by the interruption of the steady state of disease pathophysiology at very specific points in a dense longitudinal pattern.
We are investigating the mucosal/stool microbiome repertoire (16SrDNA seq, methylation-pattern differences and transcriptome profiles of mucosal biopsies and peripheral blood monocytes. Targeted metabolomic (adiponectine, insuline, Lp(a), HbA1c, lipid electrophoresis, insuline sensitivity and targeted proteome (i.e. cytokine profile using available antibody array) analyses are carried out.
The data will be subjected to systems biological modelling and hypotheses will be validated in available larger cohorts.
Keywords: individual disease course, epigenome, transcriptome, microbiome