Description of Work Packages

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Multi-omics analyses are non-targeted approaches that can be used to unravel new biomarkers in the genome, transcriptome, proteome and microbiome of patients with SAID. In WP2, we will perform state-of-the–art omics analyses using genome-wide approach based on next generation sequencing analysis, miRNA analysis, mass spectrometry and multiplexed proteomic analyses, and investigate microbiome changes of patients with SAID. The objectives of WP2 are the discovery of novel genetic variants, unique miRNA profiles in immune cells, disease-specific new protein biomarkers in plasma, and new microbiome changes that diagnose disease or predict treatment outcomes, stratify patients and instruct therapy in SAID. It will also serve as a discovery strategy to identify mechanisms of pathogenesis and targets of intervention. All omics data will be primarily stored and pre-processed locally by the generating centers, then uploaded on the centralized data management environment for integration within WP6.


Inflammasome-associated pathways in sporadic and undiagnosed systemic autoinflammatory disorders

The overall goal of the tasks in this WP3 is to assess the range of functions, dysfunction and biomarker potential of the inflammasome complexes in SAID. Furthermore, these tasks will assess whether the genes identified by the Omics approaches (some of which might be of unknown functions) affect the inflammasome pathways.


Inflammation resolution

The WP4 has 4 objectives:

  • To characterize specialized pro-resolving lipid mediator networks in SAID patients and determine their diagnostic and prognostic potential
  • To profile the SPM biosynthetic pathway in whole blood cells and identify potential abnormalities in their generation in SAID patients
  • To determine the functional effects of SPMs of immune cells and identify potential abnormalities in their response in SAID patients
  • To develop/identify agonists that induce SPM production and drive resolution of inflammation


Immune networks (cytokine and cellular networks)

This WP will encompass three major themes, i.e.

  • soluble factor profiling (cytokine, chemokine, adipokine dosages, tryptophan metabolism, signatures of S100-alarmins and pro-/anti-inflammatory mediators)
  • deep-phenotyping of protein structures and modifications (structural and/or post-translational modifications, modifying enzymes) and
  • specific immune cell profiling (NK cells, deep-profiling of PBMC subpopulations) in SAIDs. We will focus on specific cells such as PMNs, mast cells, Tregs and NK cells. There will be an integration and network analyses of mechanisms involved in inflammation generation and resolution (including modifying enzymes, structural data on key components such as IL18/IL18BP and S100-proteins).


Data analysis and integration

This WP will centrally manage, analyze, and integrate the most important datasets and biological knowledge generated by other WPs. The objectives will be to use complex multi-omics datasets in order to identify clinically meaningful classes of SAID patients. Diagnostic classifications will be selected for their potential prognostic and therapeutic impact. In order to achieve that, we will exploit the latest methodologies in bioinformatics, statistical modeling, machine learning and deep learning. We will combine supervised and unsupervised approaches, as well as knowledge-driven approaches in order to optimize the classification process while keeping a strong link to biological mechanisms and clinical impact.