Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : DSBSunrise (Horizon 2020, appel 2019, Advanced grants)
Domaine scientifique : Life Science
Panel : Molecules of Life: Biological Mechanisms, Structures and Functions
Entité participante : Centre national de la recherche scientifique — Pays : France — Rôle : PI
Acronyme de l'entité : CNRS
Type d'entité : Recherche
Financement ERC de l'entité : 2170000.0 €

At the onset of prophase of the first meiotic division, meiotic cells undergo complex molecular events with the induction of several hundred DNA double-strand breaks. These DNA breaks are required because they initiate recombination between homologous chromosomes and to allow chromosome segregation during meiosis. They are essential for fertility. However, they represent a major challenge for genome integrity. It is thought that meiotic DNA break formation is under tight control to ensure that all breaks are properly repaired to maintain genome integrity. But how this control implemented is unknown. We postulate that three critical steps take place to ensure meiotic DNA break formation at the right time, right place, and right frequency. We will test this hypothesis by addressing in mice the three following questions: Q1: We will ask whether a homology-sensing process brings homologous chromosomes in spatial proximity before DNA break formation to improve DSB repair efficiency and avoid topological conflicts. If this is the case, we will determine the molecular mechanism. Q2: We will determine whether the genomic sites undergoing DNA breakage interact with structural components of chromosome axes before break formation, and how. This interaction is predicted to be necessary for proper DSB repair. Q3: We will determine how DNA cleavage is activated. We will do this through in vitro reconstitution of meiotic DSB formation. Answering these key questions will be possible by using in vivo and in vitro approaches. We will pioneer in vitro meiotic differentiation of mouse embryonic stem cells to overcome the current limitations for identifying novel components and interactions. We will thus decipher how a molecular machinery that has evolved from a DNA type II topoisomerase family has been selected and modified to promote a complex reaction initiated by DNA cleavage at multiple sites along chromosomes followed by their repair by homologous recombination.

Mots-clés : meiosis,topoisomerase,genome stability,dna breaks,cohesins
Projet ERC : ATM-GTP (Horizon 2020, appel 2016, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Earth system science
Entité participante : University of Helsinki — Pays : Finlande — Rôle : PI
Acronyme de l'entité : UH
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2500000.0 €

Atmospheric Gas-to-Particle conversion (ATM-GTP) is a 5-year project focusing on one of the most critical atmospheric processes relevant to global climate and air quality: the first steps of atmospheric aerosol particle formation and growth. The project will concentrate on the currently lacking environmentally-specific knowledge about the interacting, non-linear, physical and chemical atmospheric processes associated with nano-scale gas-to-particle conversion (GTP). The main scientific objective of ATM-GTP is to create a deep understanding on atmospheric GTP taking place at the sub-5 nm size range, particularly in heavily-polluted Chinese mega cities like Beijing and in pristine environments like Siberia and Nordic high-latitude regions. We also aim to find out how nano-GTM is associated with air quality-climate interactions and feedbacks. We are interested in quantifying the effect of nano-GTP on the COBACC (Continental Biosphere-Aerosol-Cloud-Climate) feedback loop that is important in Arctic and boreal regions. Our approach enables to point out the effective reduction mechanisms of the secondary air pollution by a factor of 5-10 and to make reliable estimates of the global and regional aerosol loads, including anthropogenic and biogenic contributions to these loads. We can estimate the future role of Northern Hemispheric biosphere in reducing the global radiative forcing via the quantified feedbacks. The project is carried out by the world-leading scientist in atmospheric aerosol science, being also one of the founders of terrestrial ecosystem meteorology, together with his research team. The project uses novel infrastructures including SMEAR (Stations Measuring Ecosystem Atmospheric Relations) stations, related modelling platforms and regional data from Russia and China. The work will be carried out in synergy with several national, Nordic and EU research-innovation projects: Finnish Center of Excellence-ATM, Nordic CoE-CRAICC and EU-FP7-BACCHUS.

Mots-clés : atmospheric aerosols,global challenges,air quality climate interactions and feedbacks,arctic and boreal environments,mega cities,earth surface,atmosphere interactions
Projet ERC : WFNQMC (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and analytical chemical sciences
Entité participante : University of London — Pays : Royaume-Uni — Rôle : PI
Acronyme de l'entité : U. London
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1500000.0 €

Atomistic computational modelling is increasingly an integral component of almost all areas of chemistry, physics and materials science, especially as its predictive ability improves. However, not all systems are equal when it comes to the predictive capabilities of current methods, and many systems are too large or many-body effects too complex to be routinely tractable. The result is that the promise of ‘materials by design’, deduction of reaction pathways or routine simulation on a par with experimental accuracy has not in general come to fruition. This ambitious proposal aims to address this, with development of a suite of novel approaches to stochastically sample the wavefunction. Recent work by the PI has already made huge strides in this direction, with an emerging approach in quantum chemical space having remarkable success for accurate solutions of small problems. Here, we first propose a number of novel developments to order to extend this approach from a tool for small systems to a widespread disruptive technology, with application to a variety of challenging problems. This involves development of the scope, scaling, accuracy and capabilities of this sampling, including admitting time-dependent, spectral and relativistic extensions. Next, we aim to take the successful philosophy of this sampling and exploit its powerful approach in order to reformulate a number of well-established electronic structure tools. Allowing stochasticity has the potential to yield low-scaling formulations of these methods, able to naturally exploit inherent sparsity, and have a revolutionary impact on their use and success. This proposal is highly interdisciplinary, spanning a range of applications and techniques in quantum chemistry, condensed matter and materials science, brought together under the banner of exploiting inherent sparsity by establishing a new paradigm of stochastic tools for correlated electrons, with the opportunity for tremendous impact in a number of fields.

Mots-clés : quantum monte carlo,quantum chemistry,electronic structure methods
Projet ERC : REVERSEAUTISM (Horizon 2020, appel 2016, Starting grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : Institute of Science and Technology Austria — Pays : Autriche — Rôle : PI
Acronyme de l'entité : ISTA
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1498394.0 €

Autism Spectrum Disorders (ASD) are a group of neurological conditions characterized by stereotypical or repetitive behaviours as well as impairments in social interaction and communication skills, often of genetic basis. ASD have been classified as neurodevelopmental disorders, implying irreversible defects in the maturation of neural circuits. We have shown that mutations in the Branched Chain Ketoacid Dehydrogenase Kinase (BCKDK) gene lead to a potentially preventable and reversible form of ASD (Novarino et al. Science 2012). The most direct consequence of BCKDK mutations is a hyper-metabolism of the branched chain amino acids (BCAAs), resulting in atypically low levels of serum and brain BCAAs. Recently, using whole exome sequencing we identified individuals with ASD carrying mutations in the gene SLC7A5, encoding for the transporter mediating BCAA flux across the blood brain barrier. This suggests that the BCAAs are critical for brain development and cognition and reinforces their link with ASD. The simple nature and availability of the BCAAs prompt raising the possibility that this group of amino acids may be employed to treat symptoms of other ASD. We aim at 1) elucidating the link between BCAAs, ASD, brain development and cognition; 2) exploring the possibility of employing the BCAAs to reverse symptoms caused by mutations of ASD-genes. The genetic analysis of ASD is untangling the etiological heterogeneity that may contribute to poor clinical trial outcome. However, recent studies, including our own (Novarino et al. Science 2014), show that genetic causes of neurological disorders converge along specific biological processes. Our third objective is to employ stem cell-derived human cerebral organoids to identify key molecular changes involved in the pathology of genetically distinct but functionally homogenous forms of ASD. These molecules may represent the target for future “broad spectrum” therapeutic strategies as well as potential biomarkers (aim 3).

Mots-clés : autism,neurodevelopmental diseases treatment,human embryonic stem cells
Projet ERC : AUTISMS (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Complexity
Entité participante : Italian Institute of Technology — Pays : Italie — Rôle : PI
Type d'entité : Recherche
Financement ERC de l'entité : 1122969.85 €

Autism spectrum disorders (ASD) affect 1-2% of the population and are a major public health issue. Heterogeneity between affected ASD individuals is substantial both at clinical and etiological levels, thus warranting the idea that we should begin characterizing the ASD population as multiple kinds of ‘autisms’. Without an advanced understanding of how heterogeneity manifests in ASD, it is likely that we will not make pronounced progress towards translational research goals that can have real impact on patient’s lives. This research program is focused on decomposing heterogeneity in ASD at multiple levels of analysis. Using multiple ‘big data’ resources that are both ‘broad’ (large sample size) and ‘deep’ (multiple levels of analysis measured within each individual), I will examine how known variables such as sex, early language development, early social preferences, and early intervention treatment response may be important stratification variables that differentiate ASD subgroups at phenotypic, neural systems/circuits, and genomic levels of analysis. In addition to examining known stratification variables, this research program will engage in data-driven discovery via application of advanced unsupervised computational techniques that can highlight novel multivariate distinctions in the data that signal important ASD subgroups. These data-driven approaches may hold promise for discovering novel ASD subgroups at biological and phenotypic levels of analysis that may be valuable for prioritization in future work developing personalized assessment, monitoring, and treatment strategies for subsets of the ASD population. By enhancing the precision of our understanding about multiple subtypes of ASD this work will help accelerate progress towards the ideals of personalized medicine and help to reduce the burden of ASD on individuals, families, and society.

Mots-clés : autism,precision medicine,heterogeneity,subtypes,stratification,development,toddler,connectome,phenome,big data,brain,gene expression,fmri,clustering,biomarker
Projet ERC : AUTISMS (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Complexity
Entité participante : University of California System — Pays : Etats-Unis — Rôle : Partner
Acronyme de l'entité : UC
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 281250.0 €

Autism spectrum disorders (ASD) affect 1-2% of the population and are a major public health issue. Heterogeneity between affected ASD individuals is substantial both at clinical and etiological levels, thus warranting the idea that we should begin characterizing the ASD population as multiple kinds of ‘autisms’. Without an advanced understanding of how heterogeneity manifests in ASD, it is likely that we will not make pronounced progress towards translational research goals that can have real impact on patient’s lives. This research program is focused on decomposing heterogeneity in ASD at multiple levels of analysis. Using multiple ‘big data’ resources that are both ‘broad’ (large sample size) and ‘deep’ (multiple levels of analysis measured within each individual), I will examine how known variables such as sex, early language development, early social preferences, and early intervention treatment response may be important stratification variables that differentiate ASD subgroups at phenotypic, neural systems/circuits, and genomic levels of analysis. In addition to examining known stratification variables, this research program will engage in data-driven discovery via application of advanced unsupervised computational techniques that can highlight novel multivariate distinctions in the data that signal important ASD subgroups. These data-driven approaches may hold promise for discovering novel ASD subgroups at biological and phenotypic levels of analysis that may be valuable for prioritization in future work developing personalized assessment, monitoring, and treatment strategies for subsets of the ASD population. By enhancing the precision of our understanding about multiple subtypes of ASD this work will help accelerate progress towards the ideals of personalized medicine and help to reduce the burden of ASD on individuals, families, and society.

Mots-clés : autism,precision medicine,heterogeneity,subtypes,stratification,development,toddler,connectome,phenome,big data,brain,gene expression,fmri,clustering,biomarker
Projet ERC : NeurAntigen (Horizon 2020, appel 2020, Proof of concept grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : Institut d'Investigació Biomédica de Bellvitge — Pays : Espagne — Rôle : PI
Acronyme de l'entité : IDIBELL;IDIBELL-CERCA
Type d'entité : Recherche
Financement ERC de l'entité : 150000.0 €

Autoimmune encephalitides (AE) are a category of diseases that result from an immune attack against proteins present in patient’s own brain cells (antigens). Clinical symptoms include both neurological and psychiatric manifestations, that differ greatly between patients and during disease progression. Upon prompt diagnosis and immunotherapy symptoms gradually resolve. Current epidemiological studies estimate an annual incidence of encephalitis of any aetiology is 2-3 patients per 100.000 per year. However, given that new autoantibodies are being discovered on a half-yearly basis, the incidence of AE is increasing over time and is nowadays comparable to infectious encephalitis. Methods to diagnose AE rely on immunodetection of autoantigens, using rat brain tissue or transfected cells as a source of neural cell surface proteins. Despite being successful in identifying known autoantibodies, in 50% of all AE cases the affected antigen is unknown and cannot be detected using current technologies. Therefore, there is an urgent clinical need for a diagnostic kit that is able to detect all cell surface neuronal antigens. Thanks to the skills acquired during the ERC-StG, we have developed a platform to identify the presence of autoantibodies against neuronal surface antigens in patient serum or CSF using human induced pluripotent stem cell (hiPSC) derived neural cells. Moreover, first experiments validate that our technology can detect an autoantigen in seronegative samples. In the context of this project, we aim to conduct the necessary steps to bring a successful diagnostic approach developed in the bench towards its application as a diagnostic device at the bedside. To this end, we will develop a minimum viable product (MVP), to assess its capability to detect new AE-associated antigens, to distribute it to reference diagnostic laboratories for benchmarking and to explore the possibility of licensing the invention to a third-party company.

Mots-clés : autoimmune encephalitis  ae,ipsc technology,in vitro diagnosis,human ipsc derived neuronal,cultures
Projet ERC : LightAtLHC (Horizon 2020, appel 2019, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Fundamental constituents of matter
Entité participante : Johannes Gutenberg University Mainz — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1572500.0 €

Axions and other very light axion-like particles (ALPs) appear in many extensions of the Standard Model and are well motivated theoretically: ALPs can solve the well-known strong CP problem, act as a dark matter candidate and could also explain the famous muon (g-2) discrepancy. The experimental effort to search for ALPs as dark matter candidates is ongoing and has been considerably intensified in recent years, leading to the proposal and construction of a wide range of dedicated experiments. However, none of these dedicated experiments is sensitive to those ALPs that can explain low-energy anomalies such as (g-2). I propose therefore to pioneer an alternative search strategy for axion-like particles via their decay into two photons, using data collected at the Large Hadron Collider. This approach requires fundamental innovations on the photon identification capabilities of the current detectors as well as radically new analysis strategies. Within the LightAtLHC project, I will study proton-proton and lead-lead collisions, collected during LHC Run-3, and search for Higgs Boson decays in two ALPs as well as the direct production of ALPs via photon fusion and their subsequent decay into two low-energy photons. To achieve the required sensitivity, I will develop highly specialized photon reconstruction algorithms for the ATLAS detector. These efforts will largely cover the relevant parameter space, leaving out only a small region. To also close this gap, I will extend the upcoming FASER experiment at the LHC by an innovative presampler detector, which allows for an unambiguous ALPs detection. By the end of the LightAtLHC project, I can either rule out the most promising ALP models in a mass range from 10 MeV to 1 TeV, or discover a new elementary particle.

Mots-clés : axion like particle,atlas
Projet ERC : PREG-LAB (Horizon 2020, appel 2014, Consolidator grants)
Domaine scientifique : Life Science
Panel : Immunity, Infection and Immunotherapy
Entité participante : Leibniz Association — Pays : Allemagne — Rôle : Partner
Acronyme de l'entité : LG
Type d'entité : Recherche
Financement ERC de l'entité : 79563.94 €

B cells can act both as negative regulators and as drivers of immunity through the production of cytokines. Through secretion of interleukin (IL)-10 B cells inhibited immunity in autoimmune and infectious diseases. For instance, IL-10 from B cells drove complete recovery from disease in experimental autoimmune encephalomyelitis (EAE), the primary animal model for multiple sclerosis (MS), while a lack of IL-10 production by B cells resulted in a severe chronic EAE. B cells can also suppress immunity via IL-35. Human B cells might similarly play inhibitory roles. In few patients with immune-mediated diseases B cell depletion therapy with Rituximab was associated with exacerbation of symptoms, or onset of new pathologies. Conversely, an opposite role of B cells as drivers of immunity was highlighted by the beneficial effect of Rituximab in some patients with rheumatoid arthritis or MS. Clinical improvement often precedes reduction in autoantibody levels in Rituximab treated patients, indicating that B cell-mediated pathogenesis is largely antibody-independent. A candidate factor for the deleterious effects of B cells in MS is IL-6. IL-6 secretion is a major mechanism of B cell-mediated pathogenesis in EAE, and B cells from MS patients produced more IL-6 than cells from healthy individuals. There is now an urgent need for the characterization of the phenotypes of the B cells producing IL-6, IL-10, and IL-35 in vivo at single cell and molecular levels. Markers for these cells might allow understanding the paradoxical effects of B cell-depletion therapy, and guide the development of novel agents depleting distinctively pro-inflammatory B cells, while sparing the remaining of the B cell compartment. Using advanced genetic models to identify and track cytokine-expressing cells, our project aims at characterizing B cells with pro- and anti-inflammatory functions in mice in vivo, to subsequently guide the identification of comparable markers in human.

Mots-clés : b cell,il 10,il 35,plasma cell,autoimmunity
Projet ERC : IT4B-ALL (Horizon 2020, appel 2018, Proof of concept grants)
Domaine scientifique : Life Science
Panel : Physiology in Health, Disease and Ageing
Entité participante : Fundación Josep Carreras Contra la Leucemia — Pays : Espagne — Rôle : PI
Type d'entité : Recherche
Financement ERC de l'entité : 150000.0 €

B-ALL is the commonest cancer of childhood. There remain childhood B-ALL subgroups with dismal prognosis such as infant B-ALL and B-ALL carrying MLL rearrangements (MLLr). In addition, the prognosis of adult B-ALL is worse, and refractory/relapse (R/R) B-ALL remains dismal. CD19-targeted immunotherapies have emerged as promising therapeutic approaches for R/R B-ALL. CD19 CAR T-cells have shown impressive efficacy in R/R B-ALL. However, relatively rapid relapses are frequently observed, a proportion of them losing CD19 expression upon CAR19 T-cell therapy due to massive antigen pressure over CD19, resulting in a myeloid lineage switch in MLLr B-ALL, or the selection of CD19-/CD34+ preleukemic progenitors. Further CD19-targeted therapy is thus ineffectual for CD19neg R/R B-ALL. Our overarching goal is to provide novel therapeutic options for (R/R) B-ALL.Targeting surface antigens whose expression, opposite to CD19, are commonly retained at relapse is a valid strategy to circumvent the loss of CD19 found in (R/R) B-ALL after CD19-targeted therapies. Recent work funded by my ERC-2014-CoG has identified NG2 and CD22 as key antigens to be targeted in (R/R) B-ALL. First, both antigens are retained in CD19neg R/R B-ALL. Second, NG2 is solely expressed in MLLr B-ALL, and is associated with CNS infiltration, aggressiveness and glucocorticoid resistance. Third, CD22 is a pan-B marker expressed developmentally earlier than CD19, and CD34+CD22+CD19- cells may represent pre-malignant progenitors escaping the CD19-targeted pressure. These results have just been protected by a European Patent (EPI173825514), and are the proof-of-principle demonstration of NG2 & CD22 representing promising immunotherapeutic targets, when combined with CD19 for both MLLr & MLL-germline B-ALL, respectively. Here we propose to consolidate preclinical work and GMP production of anti-NG2 monoclonal antibody and NG2/CD19 and CD22/CD19 CAR T-cells to launch a PhaseI academic clinical trial for R/R B-ALL

Mots-clés : b cell acute lymphoblastic leukemia,relapse b all,car t cells,ng2 antigen,cd22,tandem cars,mll rearrangement,clinical development,phase i clinical trial