Project title: Linking public and GCA datasets to identify novel pathogenic pathways
Rationale:We hypothesise that major pathogenic pathways can be identified through the analysis of polygenic risk scores derived from relevant immunological or tissue remodelling public datasets and through performing pathway analysis.
Objectives:To explore immunological, vascular and tissue remodelling pathways to develop an evidence base for currently available drugs. Publicly available genetic, proteomic and clinical datasets, and those from existing international collaborations, will be used to (1) derive polygenic risk scores from public datasets and analyse the influence of these biologically-relevant genetic scores on GCA susceptibility and selected GCA phenotypes and (2) conduct pathway analyses of GCA susceptibility using novel approaches based on Bayesian hierarchical models (Objective 6)
Expected Results:Insights into immunological, vascular and tissue remodelling pathogenic GCA pathways associated with discrete phenotypic subgroups.
Planned Secondments:AX: 2 mths (linking genetic analyses to genomic and protein databases), CSIC: 2 mths (to align genetic analyses with ESR7)