Systems medicine has a mechanism-based rather than a symptom- or organ-based approach to disease and identifies therapeutic targets in a nonhypothesis-driven manner. In this work, we apply this to transcription factor nuclear factor (erythroid-derived 2)-like 2 (NRF2) by cross-validating its position in a protein-protein interaction network (the NRF2 interactome) functionally linked to cytoprotection in low-grade stress, chronic inflammation, metabolic alterations, and reactive oxygen species formation. Multiscale network analysis of these molecular profiles suggests alterations of NRF2 expression and activity as a common mechanism in a subnetwork of diseases (the NRF2 diseasome). This network joins apparently heterogeneous phenotypes such as autoimmune, respiratory, digestive, cardiovascular, metabolic, and neurodegenerative diseases, along with cancer. Importantly, this approach matches and confirms in silico several applications for NRF2-modulating drugs validated in vivo at different phases of clinical development. Pharmacologically, their profile is as diverse as electrophilic dimethyl fumarate, synthetic triterpenoids like bardoxolone methyl and sulforaphane, protein-protein or DNA-protein interaction inhibitors, and even registered drugs such as metformin and statins, which activate NRF2 and may be repurposed for indications within the NRF2 cluster of disease phenotypes. Thus, NRF2 represents one of the first targets fully embraced by classic and systems medicine approaches to facilitate both drug development and drug repurposing by focusing on a set of disease phenotypes that appear to be mechanistically linked. The resulting NRF2 drugome may therefore rapidly advance several surprising clinical options for this subset of chronic diseases.

This work was supported by Grants SAF2015-71304-REDT, SAF2016-76520-R, SAF2013-4874R, SAF2015-65267-R, and BIO2014-57518 of the Spanish Ministry of Economy and Competiveness; PII4/00372 from the Health Institute Carlos III; PROMETEOII/2014/071 of Generalitat Valenciana; P_37_732/2016 REDBRAIN of the European Regional Development Fund; Competitiveness Operational Program 2014-2020; and the ERC Advanced Grant RadMed 294683 and COST action 15120 OpenMultiMed (H.H.H.W.S.). M.P. is the recipient of a FPU fellowship of Autonomous University of Madrid. E.G. is supported by a European-cofunded Beatriu de Pinos fellowship. R.L. is supproted by the Miguel Servet II fellow (CPII16/00014).