iDysChart SIGNED

Project "iDysChart" data sheet

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 Project objective

The central challenge for the immune system is to efficiently recognize and neutralize foreign antigen while protecting self. If the latter fails, autoimmunity and/or autoinflammation may occur, as observed in many human diseases. Though several human genes involved in the process have been identified we still lack: i) a comprehensive appreciation of all contributing molecular pathways, ii) an understanding of the interplay and epistatic relationships among the various elements and iii) a satisfactory strategy to counteract dysregulation based on an understanding of the regulatory logic. I hypothesize that there is only a finite number of pathways involved and that it should be possible to mount a synergistic strategy to create a first chart of the entire “territory”. Key to this endeavor is the identification of sufficient elements by mapping immune dysregulation genes to “anchor” the chart onto signposts of which the human pathophysiological relevance is certain. From these signposts, contextualization and integration is achieved by interaction proteomics and network informatics mining the existing data universe, validated through biochemical and imaging tools to power an established set of immune assays. While it may be preposterous to claim feasibility with one ERC grant, I propose that once such a chart exists, even at initial low resolution, it can help reconcile disconnected observations and coalesce future work while being immensely improved in accuracy and mechanistic understanding by the entire community. iDysChart will work towards these goals by 1) identifying novel monogenic causes of autoimmune/autoinflammatory diseases, enabling elucidation of fundamental mechanisms, 2) creating a network-level understanding of molecular pathways of immune dysregulation and 3) employing chemical and genetic screens to complement human disease gene discovery in predicting the core human immune dysregulome and investigating potential avenues for therapeutic modulation.