This project is divided into 9 work packages (WP):

  • WP1 Coordination (Project Management and Governance)
  • WP2 Sample collection and Biobanking
  • WP3 Clinical Data Management
  • WP4 Genomics, transcriptomics, epigenomics
  • WP5 Flow Citometry and Cellular Separations from blood of patients with SADS and pre-clinical models
  • WP6 Proteomics, Metabolomics and Serology of SADS
  • WP7 Tissue Taxonomy and Imaging Analysis
  • WP8 Data Analysis, Bioinformatics and biostatistics

Work on pre-clinical models done in parallel, runs through WPs 4-8 transversally.
With the aim of molecularly reclassify Systematic Autoimmune Diseases, we have designed a structure that has at its base, two patient cohorts, one for discovery (cross-sectional) and one for validation (Inception), and a pre-clinical set. To do this, the overall project follows a logical structure with WPs 2-7 representing activity cores that are fed by the cohorts and converge onto the WP8 on bioinformatics and biostatistics. WP8 integrates the data from the cores and end up in the validated systemic and tissue-based taxonomies, and therefore constitutes the central axis of the project. WP1 and WP9 are transversal throughout the whole project and oversee through management structures the correct function of the parts, including monitoring of ethical and regulatory approvals. WP9 is the output WP with dissemination of results and evaluation/incidence reports to the advisory boards, scientific community and stakeholders with adequate training on all aspects.

PRECISESADS gathers a well-balanced partnership and focuses on diseases that have been little studied but that share pathogenic mechanisms. While SLE is a prototype systemic autoimmune disease, its clinical relationship with Scleroderma, Sjögren’s syndrome, rheumatoid arthritis, primary antiphospholipid syndrome and mixed connective tissue disease is well documented. The pharmaceutical members are completely integrated in the activities, and 2 SMEs take care of important aspects of the project. The research complementarities are ensured with “omics” cores, clinical teams and a biostatistics team:

  • Sample collection and biobanking: FPS (Andalusian Biobank), IRCCS, CHP, SCS, IDIBAPS, UKK, MHH, MUW, UNIGE, DRFZ, UBO, SAS, ELI-LILLY, USZ, UNIMI

  • Clinical data management and recruitment: 18 clinical centres involved with EFPIA members.

  • Cellular analyses: UBO, FPS (GENYO), DFRZ, SAS, CHP, IDIBELL, MHH, UNIGE
  • Proteomics/metabolomics:  KI, UGR, UNIMI, FPS (BIONAND), ELI-LILLY
  • Tissue taxonomy and imaging: UCL, Althia, K.U.LEUVEN, CING, BAYER
  • Bioinformatics/biostatistics: QBIO, FPS (GENYO), CSIC, UBO, IDIBELL, BAYER, ELI-LILLY, I.R.I.S.