Immunome Project Consortium for Autoinflammatory Disorders
ImmunAID is a large, 5-year duration European project aiming to optimize the diagnostic, classification and clinical management of rare systemic autoinflammatory diseases, as well as to deliver a method for rapid and accurate diagnosis across all the spectrum of autoinflammatory disorders. ImmunAID also aims to raise awareness on autoinflammatory diseases at all levels, as well as educate patients.
FMF & AID Global Association is an official ImmunAID partner, and the only patient organization involved.
There are 37 participating hospitals from the following 11 countries: Belgium, France, Germany, Greece, Italy, Netherlands, Slovenia, Spain, Switzerland, Turkey, and the United Kingdom.
Children and adults affected by any of the diseases below are welcome to participate in this clinical study, as well as healthy volunteers. All ImmunAID need is a bit of your time, less than 2 hours (<2h), some blood, urine and fecal samples. Note that all the data we collect and generate will remain anonymous and password protected.
These diseases are included in ImmunAID:
- FMF - Pericarditis
- TRAPS - Still’s disease
- CAPS - Schnitzler
- HIDS - Vasculitis (Kawasaki, Behçet, Takayasu)
- CRMO - Inflammation of unknown origin
Systemic autoinflammatory diseases (SAID) encompass several rare disorders characterised by extensive clinical and biological inflammation. SAID are caused by the dysregulation of the innate immune system. Due to numerous and unspecific symptoms, tentative diagnosis often leads to failure/delay and inadequate treatments. ImmunAID will deliver a method for rapid and accurate diagnosis across all the spectrum of SAID, in order to improve clinical management of SAID patients.
Thanks to parallel analyses run on samples from more than 600 patients with monogenic or undiagnosed SAID collected throughout Europe, ImmunAID will generate a unique and comprehensive set of data, based on unbiased multi-omics approach (gene, transcript, protein, microbiome), and hypothesis-driven assays exploring inflammasome, inflammation resolution and immune networks. A centralised data management strategy will enable to conduct integrated analyses for diagnostic biomarker identification.
In a discovery phase, semi-supervised clustering of omics data will be combined to supervised analysis of pathway-related data to provide robust classification and strong link to clinical features/impact. The related biomarkers will further be validated externally on independent samples and cohorts. Overall, ImmunAID will disentangle the spectrum of SAID, and propose a new omics- and pathogenesis-based SAID classification associated to a clinical decision-making algorithm implementable in daily practice.
An efficient dissemination plan will target e.g. guideline-forming bodies, the medical community and patients with the help of the ERN RITA and with the objective of turning our results into clinical practice. To further support this, proactive innovation management will be implemented. To reach its ambitious goals, ImmunAID interdisciplinary consortium gathers high-level partners, including the founder of SAID concept, experts in omics science, immunology, bioinformatics, and involves clinicians and patient advocacy groups.
These diseases can be divided into two groups:
diseases for which genetic mutations have been identified,
the so-called genetically undetermined diseases for which no genetic mutation has been identified and for which the diagnosis is based on the elimination of other causes of disease.
At present, the causes and mechanisms of these diseases are poorly understood, and their diagnosis is difficult, often leading to misdiagnosis. To date, a patient with one of these diseases can receive up to 5 inappropriate or ineffective treatments before the right diagnosis is made and the right therapy is put in place.
The objective of this study is to develop rapid and effective diagnostic methods for these diseases by the identification of biological markers present in blood, urine or stool of patient in order to develop a rapid and efficient diagnostic method.
Detailed information of this study, can be found on this website.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 779295.