Medico - Scientific Background
The concept of autoinflammatory/autoimmune disease continuum (AADC)
Chronic inflammation, a condition present in various diseases including those with an immune component, is an important cause of morbidity/mortality in the developed world. Recent advances in the pathophysiology of autoinflammatory/autoimmune diseases have led to a re-examination of their nosology. It now appears that autoinflammatory and autoimmune diseases do not represent two distinct categories of disorders. Rather, they form a disease continuum ranging from pure autoinflammatory disorders to pure autoimmune diseases, encompassing a large panel of inflammatory diseases with some autoimmune component, and vice versa. A wide range of disorders fall into this disease category. These are rare or common disorders, whose management requires an integrated approach in which clinicians from internal medicine or medical specialties and research teams collaborate closely in translational research programs.
WP1: Implementing deep-phenotyping and immunomics
WP leaders: A. Six, P. Benech, M. Rosenzwajg
Aim 1: Designing a standardized database for integration of clinical and biological data
We are developing a database following international standards. A dedicated coordination Cohort management team (CMT) will perform on site cohort monitoring for compliance and clinical research file and queries collection. CMT will liaise with clinicians, database managers, and scientists.
Aim 2: Deep PhenOmics
To reach a comprehensive understanding of the immune system, a complete representation of the diversity and complexity of the immune system in disease involves several overlapping levels and requires the integration of this information. For this goal, we will acquire clinical as well as flow cytometry, genomic, transcriptomic, proteomic, and deep sequencing TCR repertoire data. Standards procedures for Tregs/ Teffs sorting and deep immunophenotyping by flow cytometry have already been set up.
Aim 3: Literature mining to qualify and quantify the domain model
The aim is to apply text mining technologies to take advantage of literature of the domain to improve our comprehension of inflammatory and autoimmune diseases. This domain knowledge base will allow a more efficient analysis of genomic/proteomic data and study their relation to drugs and treatments.
WP2: Cross-phenotyping in the inflammatory/autoimmune diseases continuum
WP leaders: S. Amselem, P. Cacoub, A. Six
Aim 1: Establishment of disease & healthy donor cohorts
Thirteen caracteristic inflammatory and autoimmune diseases (i.e. type 1 diabetes, systemic lupus erythematosus/antiphospholipid syndrome, myositis, vasculitis, rheumatoid arthritis, ankylosing spondylitis, uveitis, FMF/TRAPS/CAPS, Crohn's Disease, ulcerative rectocolitis, arthritis, muscular dystrophy) have been selected for cross-phenotyping modelling. Hundred patients per disease will be recruited together with a group of 100 healthy controls. Based on clinical & biological data collected, we will implement modelling schemes in order to identify pathophysiological signatures and biomarkers.
Aim 2: Defining the normal Immunome
The aim is to initiate an “Immuno-physiome” model of the immune system and define the ranges of normality and variability that exist between individuals through genetics, from young adult to elderly people. The challenge is to qualify and quantify perturbations occurring at the molecular and cell level through age. This task will be important to guide the interpretation of signatures & biomarkers obtained in the studied disease states.
Aim 3: Defining the immunome of the different diseases studied
The chosen autoimmune/inflammatory pathologies will be analyzed based on samples and clinical/biological data produced by WP1. For example, this comparative analysis across diseases will characterize the immunome:
- between auto-Ab related diseases and their negative counterpart,
- between organ specific and non organ specific autoimmune diseases,
- of kidney involvement in different autoimmune diseases,
- of each IAD before and after treatment (i.e. active versus non active disease)
Aim 4: Identification of novel genes involved in AISs
This aim will allow to decipher the molecular basis of familial forms and syndromic cases of inflammatory/autoimmune diseases. The search for new genes involved in AISs will be conducted following complementary state-of-the-art approaches (SNPs and exome sequencing). These studies should contribute to the identification of molecular markers of diagnostic value.
Aim 5: T repertoire analyses by deep sequencing
Deep sequencing analysis will be carried out in order to characterize the extent of repertoire diversity perturbation associated with inflammatory or autoimmune disease processes. These analyses will provide new hypotheses on the type of immune responses involved, and will help to identify candidate antigens which will be targeted by ad hoc biotherapies.
Aim 6: Data modelling & Biomarker discovery
This aim will elaborate and validate data modelling schemes needed to serve aims of WP2. This includes:
- Elaboration of a static structural model presenting components involved in disease,
- Extraction of molecular and cellular parameters being specific for sub-groups of the studied population,
- Identification of disease- or pathological process-specific characteristic signatures & biomarkers,
- Construction of dynamical models providing mechanistic descriptions of the disease process.
WP3: Biomarkers and biotherapies evaluation
WP leaders: D. klatzmann, F. Berenbaum, V. Doppler
Aim 1: Clinical investigation of Biotherapies
In T1D, we have an ongoing series of trials that are planned, which will give us important information relative to dose and scheme of administration, aspects that are important and not yet fully investigated. Based on this knowledge, we will design the trials to be performed in our diseases of interest for this program. In uveitis, for which we have a planed clinical trial investigating the intra-occular injection of ex vivo activated Treg, we will test the adjunction of IL-2 in situ or parenterally, with the aim to improve the efficacy of the injected cells. This will be compared to injection of IL-2 alone. Similarly, in IBM for which we have a planed clinical trial investigating the injection of ex vivo expanded Treg injected parenterally, we will test the adjunction of IL-2. This will be compared to injection of IL-2 alone. Finally, RA is our next target for testing IL-2 in a highly inflammatory disease.
Aim 2: Development of new biotherapies
The aim is to validate the identified potential bio-therapeutic tools or targets delivered by WP1, WP2 and to develop new human biotherapies. This includes:
- Development of drug or biological based therapies
- Development of antigen-based therapies
- Optimization of Treg-cell based therapies
WP1: Implementing deep-phenotyping and immunomicsWP Leaders: A. Six, P. Benech, M. Rosenzwajg
Our innovative aim is to develop and integrate an immunological database in compliance with standards, and semantic interoperable computational approach to better understand the complexity of the immuno-physiome and immunopathologies. We are implementing the tools and procedures for patients’ deep phenotyping.
- the implementation of routine procedures to acquire formatted information
- and the establishment of a database based on standards from systems biology for data storage and cross analyses.
WP2: Cross-phenotyping in the inflammatory/autoimmune diseases continuum.WP Leaders: S. Amselem, P. Cacoub, A. Six
Thirteen diseases that cover relevant aspects of the inflammatory autoimmune disease continuum (IADC) have been selected for study. Data from normal individual across age and gender will be acquired to define a “normal immunome”. These data will be stored in the database developed in WP1 and will be analyzed for biomarker and target discovery, across diseases.
WP3: Biomarkers and biotherapies evaluation.WP Leaders: D. klatzmann, F. Berenbaum, V. Doppler
Our efforts will focus on two strategies aimed at modulating Treg. We aim to develop and evaluate Treg-targeted biotherapies in the IACD. This will comprise primarily the investigation of IL-2 and engineered Tregs, and molecules identified in WP2. We will also whenever appropriate perform clinical validation of biomarkers in prospective trials. We will use phenomics for monitoring.
- Barennes P, Quiniou V, Shugay M, Egorov ES, Davydov AN, Chudakov DM, Uddin I, Ismail M, Oakes T, Chain B, Eugster A, Kashofer K, Rainer PP, Darko S, Ransier A, Douek DC, Klatzmann D, Mariotti-Ferrandiz E
Benchmarking of T cell receptor repertoire profiling methods reveals large systematic biases
Nature Biotechnology, 2020
- Hulot JS, Salem JE, Redheuil A, Collet JP, Varnous S, Jourdain P, Logeart D, Gandjbakhch E, Bernard C, Hatem SN, Isnard R, Cluzel P, Le Feuvre C, Leprince P, Hammoudi N, Lemoine FM, Klatzmann D, Vicaut E, Komajda M, Montalescot G, Lompré AM, Hajjar RJ; AG
Effect of intracoronary administration of AAV1/SERCA2a on ventricular remodelling in patients with advanced systolic heart failure: results from the AGENT-HF randomized phase 2 trial
Eur J Heart Fail 2017, 19(11):1534-1541
- Dérian D, Bellier B, Pham HP, Tsitoura E, Kazazi D, Huret C, Mavromara P, Klatzmann D, Six A
Early transcriptome signatures from immunized mouse dendritic cells predict late vaccine-induced T-cell responses
PLOS Computational Biology 2016, 12(3):e1004801
- Zeidan MJ, Saadoun D, Garrido M, Klatzmann D, Six A, Cacoub P
Behçet's disease physiopathology: a contemporary review
Auto Immun Highlights 2016, 7(1):4
- Mariotti-Ferrandiz E, Pham HP, Dulauroy S, Gorgette O, Klatzmann D, Cazenave PA, Pied S, Six A
A TCRβ repertoire signature can predict experimental cerebral malaria
PLoS One 2016, 11(2):e0147871
- Nehar-Belaid D, Courau T, Dérian N, Florez L, Ruocco MG, Klatzmann D
Regulatory T Cells Orchestrate Similar Immune Evasion of Fetuses and Tumors in Mice
J Immunol 2015, pii:1501834
- Hoffmann TW, Pham HP, Bridonneau C, Aubry C, Lamas B, Martin-Gallausiaux C, Moroldo M, Rainteau D, Lapaque N, Six A, Richard ML, Fargier E, Le Guern ME, Langella P, Sokol H
Microorganisms linked to inflammatory bowel disease-associated dysbiosis differentially impact host physiology in gnotobiotic mice
ISME J 2016, 10(2):460-77
- Rosenzwajg M, Churlaud G, Mallone R, Six A, Dérian N, Chaara W, Lorenzon R, Long SA, Buckner J, Afonso G, Pham HP, Hartemann A, Yu A, Pugliese A, Malek TR, Klatzmann D
Low-dose interleukin-2 fosters a dose-dependent regulatory T cell tuned milieu in T1D patients
J. Autoimmun. 58, 48–58 (2015)
- Bergot AS*, Chaara W*, Ruggiero E, Mariotti-Ferrandiz, E, Dulauroy S, Schmidt M, von Kalle C, Six A**, Klatzmann D** (*/** equal contributions)
TCR sequences and tissue distribution discriminate the subsets of naïve and activated/memory Tregs in mice
Eur. J. Immunol. 45(5), 1524-1534 (2015)
- Rosenzwajg M, Churlaud G, Hartemann A, Klatzmann D
Interleukin 2 in the pathogenesis and therapy of type 1 diabetes
Curr. Diab. Rep. 14, 553 (2014)
- Vlková V, Štěpánek I, Hrušková V, Šenigl F, Mayerová V, Šrámek M, Šímová J, Bieblová J, Indrová M, Hejhal T, Dérian N, Klatzmann D, Six A, Reiniš M
Epigenetic regulations in the IFNγ signalling pathway: IFNγ-mediated MHC class I upregulation on tumour cells is associated with DNA demethylation of antigen-presenting machinery genes
Oncotarget 5, 6923–6935 (2014)
- Eymard F, Pigenet A, Citadelle D, Flouzat-Lachaniette CH, Poignard A, Benelli C, Berenbaum F, Chevalier X, Houard X
Induction of an Inflammatory and Prodegradative Phenotype in Autologous Fibroblast-like Synoviocytes by the Infrapatellar Fat Pad From Patients With Knee Osteoarthritis
Arthritis Rheumatol. 66, 2165–2174 (2014)
- Bougault C, Priam S, Houard X, Pigenet A, Sudre L, Lories RJ, Jacques C, Berenbaum F
Protective role of frizzled-related protein B on matrix metalloproteinase induction in mouse chondrocytes
Arthritis Res. Ther. 16, R137 (2014)
- Thomas-Vaslin V
A complex immunological idiotypic network for maintenance of tolerance
Front. Immunol. 5, 369 (2014)
- Allenbach Y, Chaara W, Rosenzwajg M, Six A, Prevel N, Mingozzi F, Wanschitz J, Musset L, Charuel JL, Eymard B, Salomon B, Duyckaerts C, Maisonobe T, Dubourg O, Herson S, Klatzmann D, Benveniste O
Th1 response and systemic treg deficiency in inclusion body myositis
PLoS ONE 9(3), e88788 (2014)
- Laiguillon MC, Houard X, Bougault C, Gosset M, Nourissat G,Sautet A, Jacques C, Berenbaum F, Sellam J
Expression and function of visfatin (Nampt), an adipokine-enzyme involved in inflammatory pathways of osteoarthritis
Arthritis Res. Ther. 16, R38 (2014)
- Pecchi E, Priam S, Gosset M, Pigenet A, Sudre L, Laiguillon MC, Berenbaum F, Houard X
Induction of nerve growth factor expression and release by mechanical and inflammatory stimuli in chondrocytes: possible involvement in osteoarthritis pain
Arthritis Res. Ther. 16, R16 (2014)
- Meyer M, Sellam J, Fellahi S, Kotti S, Bastard JP, Meyer O, Lioté F, Simon T, Capeau J, Berenbaum F
Serum level of adiponectin is a surrogate independent biomarker of radiographic disease progression in early rheumatoid arthritis: results from the ESPOIR cohort
Arthritis Res. Ther. 15, R210 (2013)
- Six A, Mariotti-Ferrandiz E, Chaara W, Magadan S, Pham HP, Lefranc MP, Mora T, Thomas-Vaslin V, Walczak AM, Boudinot P
The past, present and future of immune repertoire biology - the rise of next-generation repertoire analysis
Frontiers in Immunology 4, 413 (2013).
- Houard X, Goldring MB, Berenbaum F
Homeostatic mechanisms in articular cartilage and role of inflammation in osteoarthritis
Curr. Rheumatol. Rep. 15, 375 (2013)
- Hartemann A, Bensimon G, Payan C, Jacqueminet S, Bourron O, Nicolas N, Fonfrede M, Rosenzwajg M, Bernard C, Klatzmann D
Low-dose interleukin 2 in patients with type 1 diabetes: a phase 1/2 randomised, double-blind, placebo-controlled trial
Lancet Diabetes Endocrinol. 1(4), 295-305 (2013)
- Thomas-Vaslin V, Six A, Ganascia JG, Bersini H
Dynamical and mechanistic reconstructive approaches of T lymphocyte dynamics: Using visual modeling languages to bridge the gap between immunologists, theoreticians, and programmers
Front. Immunol. 4, 300 (2013)
- Thomas-Vaslin V, Six A, Bellier B, Klatzmann D
Lymphocytes dynamics repertoires, modeling
Dubitzky W., Wolkenhauer O., Kwang-Hyun C., Hiroki Y.(eds). Encyclopedia of Systems Biology. Springer,Heidelberg New York (2013) DOI 10.1007/978-1-4419-9
- Sheridan C.
Recasting natural product research.
Nat Biotechnol. 2012 May 7;30(5):385-7.
- Ainsworth C.
Networking for new drugs.
Nat Med. 2011 Oct 11;17(10):1166-8.
- Gosset M, Berenbaum F, Thirion S, Jacques C
Primary culture and phenotyping of murine chondrocytes
Nature Protoc. 2008;3(8):1253-60.