Periodic Reporting for period 2 - ImmunAID (Immunome project consortium for AutoInflammatory Disorders)
Reporting period: 2019-11-01 to 2021-04-30
At present, the causes and mechanisms of these diseases are poorly understood and their diagnosis is difficult and time-consuming, often leading to misdiagnosis. On average, up to 5 inadequate or inefficient treatments are prescribed to each patient with SAID-related conditions before a correct diagnosis is made and initiation of adequate immunomodulating drugs. Through parallel analyses of samples from 1616 patients with monogenic or genetically undiagnosed SAID, parents of patients or negative controls, collected from all over Europe, the ImmunAID consortium project will generate a unique and comprehensive set of data based on multi-omic unbiased analysis (genomics, transcriptomics, proteomics, microbiomics), and functional tests of the innate immune system based on hypotheses exploring the inflammasome, the resolution of inflammation and cytokines. Overall, ImmunAID will unravel the spectrum of SAID and propose a new classification based on omics and pathogenesis, combined with a clinical decision algorithm that can be implemented in daily practice
ImmunAID consortium includes a strong clinical network, together with academic research labs and small SME with proven track records in a broad range of analytical techniques and bioinformatic teams expert in artificial intelligence. Professional management is supporting the project implementation.
Preliminary -OMIC analysis (WP2) were run together with further some fine-tuning of the techniques. DNA from 15 samples was analyzed by whole genome sequencing (WGS) and the data complied with the quality control requirements. The RNA isolated from 42 PBMC samples was sequenced by RNA-seq analysis, and the quality of the data obtained was assessed. The transcriptomic data analysis is in progress and already confirmed the quality of reads. The Standard Operating Procedures (SOPs) for miRNAs analysis have been optimized for cell sorting, library preparation and RNA extraction, and are now written and finalized. Similarly, all SOPs for proteomic analysis by mass spectrometry have been written and a validation study running controls determined the variability of protein intensity over time and allowed to assess the normalization procedure. Protein extracted from the first batch of ImmunAID samples have been successfully analyzed by mass spectrometry and data are now submitted to the normalization process. Finally, sampled faecal material was processed and 16S Amplicon Sequencing was carried out for all available samples. Quality of the data passed all criteria.
WP3 is dedicated to studying the inflammasomes in order to identify the dysregulatory mechanisms leading to their abnormally intense and prolonged activation in SAID. The conditions to determine ASC specks by flow cytometry were optimized and anti-IL-1Ra and anti-IL-6 assays were developed for serum samples in parallel with extracellular ASC speck assay. The conditions to study expression and regulation of some of the inflammasome decoy proteins were also developed. Finally, separate assays to diagnose FMF by respectively measuring IL-1β/IL-18 and monitoring pyroptosis kinetics in response to UCN-01 in patients were developed.
WP4 is dedicated to the exploration of the role played by inflammation resolution mediators in the autoflammatory process. The biomarker panel measured in the lipidomic analysis and to be used within the clinical study has been enriched. New controls were validated to strengthen the robustness of lipidomic methodology and avoid inter-assays drifts. Results on plasma and stimulated blood from healthy donors were accumulated to provide a solid basis for comparison with the results that will be obtained from SAID patients’ samples. The lipidomic analysis of the first ImmunAID samples has started. Functional assays have been started as well on patient samples.
WP5 encompasses all the functional analysis of the cytokines and their effectors of patients. Different levels of disease activation in Takayasu patients could be brought to light with a simple set of 4 cytokines. The understanding of the function of S100 proteins and related immune dysregulation in SAID was improved. Methods for the identification of post-translationally cytokines and chemokines were improved. Similarly, an optimal final combination of all antibodies and fluorochromes was chosen for the deep immune-phenotyping of sampled blood cells. Finally, the flow cytometric antibody panels developed to identify alterations in the phenotype and activity of NK-cells was validated.
Data management, analysis and integration are carried out in WP6. The SAID generic molecular map was completed and the FMF and CAPS disease specific maps were updated. The SOPs for quality control to be applied to the OMICS analyses was prepared. In addition, the meta-analysis of identified public data already started, whereas the first version of the pipelines that will be applied to ImmunAID data in order to propose new disease classifications was developed. Using the knowledge maps, two raw boolean models were produced in order to explore in silico the intracellular mechanisms of monocytes from FMF and CAPS patients.
Up to know, ImmunAID has generated 20 peer-reviewed scientific articles, and a communication strategy is being implemented with a current focus on supporting patient recruitment activities.
Thanks to the ImmunAID project results, it will be possible to develop an innovative classification rather pathogenic pathway-based than phenotype-based. In parallel, through ImmunAID’s unbiased omics strategies, we may uncover original signatures spanning biological areas not currently associated to disease physiopathology. The combined application of these two approaches should maximize the efficiency of the discovery process, and provide the most comprehensive set of SAID-associated biomarkers, with strong links to at least one of three disease-associated areas: physiopathology, prognosis/severity, and treatment.