Coordinator: Head of Node: Reinhard Schneider, Luxembourg Centre for Systems Biomedicine, University of Luxembourg

ELIXIR, the European infrastructure for life science information, aims to provide long-term access to bioinformatics tools and biological data. ELIXIR-LU, the national ELIXIR node, focuses on long-term sustainability of tools and data for translational medicine, the combination between the clinical and experimental environment. On the national level, support in standardising and electronic capture of clinical data is provided together with hosting and analysis pipelines. Internationally, translational medicine data is hosted by the Bioinformatics Core and support is given in the curation and standardisation of data sets to improve the reusability and value of the data for the research community.

Official website: https://elixir-luxembourg.org

Innovative Medicines Initiative (IMI-JU)

Coordinator: Pieter Jelle Visser, Maastricht University, Netherlands

Alzheimer’s disease (AD) and Parkinson’s disease (PD) are among the most common neurodegenerative conditions. They pose a major societal burden, because treatments that slow down these diseases are lacking. Treatment development is impeded by lack of biomarkers that can detect individuals early in the disease, measure treatment effects, and stratify patients.
European cohorts on aging and neurodegeneration provide a huge potential for biomarker discovery and validation since they collect bio-samples together with deep clinical and imaging phenotyping. However, the cohorts are difficult to access, because an overview of the availability of data and samples is lacking and protocols and regulations for data and sample collection, storage and sharing vary. The objective of EPND is to develop a self-sustainable European platform to facilitate access to bio-samples and related data. We will build EPND using infrastructures that have shown proven value in public-private multi-stakeholder settings. In connection with the AD Workbench, EPND will support resource and participant level discovery, data harmonisation, central and federated data and sample storage and data analysis. The design of EPND is guided by ethical, legal and regulatory experts, patients and other stakeholders. EPND will also provide protocols for data and sample collection.
The sample and data discovery tools will be connected to a network of >60 supporting cohort studies on AD, PD, and related disorders. They give access to data from over 120.000 research participants including CSF samples (n=25.000), plasma samples (n=120.000), stools (n=6000), urine (n=27.000), saliva (n=17.000) and digital biomarkers (n=2000).
EPND will provide the community with a new and powerful environment to discover and validate biomarkers for neurodegenerative disorders. This will be critical for advancing the development of treatments for AD and PD.

Michael J Fox Foundation (MJFF)

Since neurodegenerative disorders are generally diagnosed late in the already advanced stage of the disease, possible neuroprotective interventions may be applied too late. The prodromal conditions of the most common neurodegenerative disorders (Parkinson’s disease and dementia disorders) are relatively well defined by non-motor symptoms and mild cognitive decline. The prodromal conditions have already been studied in mostly at-risk cohorts, but comprehensive population-based studies and information on the presence of risk factors are mostly lacking to date. The HeBA project anticipates to identify prodromal conditions and risk factors for PD and/or dementia early in a population based cohort and conduct in-person visits with biofluid collection, examinations and other structured assessments in subjects with high and low risk defined by an online questionnaire. The in-person visits will be repeated annually for up to 5 years, or longer, and the resulting cohort of subjects at risk to develop Parkinson’s disease and/or dementia in the general population. It is anticipated to enroll some of the probands in the Parkinson progression Marker Initiative of the Michael J. Fox Foundation.

Official website: heba.lu

Horizon 2020

Official website: https://by-covid.org

Horizon 2020

HealthyCloud’s strategic agenda will lay the foundations for the establishment of a trusted and decentralised European computational system for the use and better exploitation of health data by humans and machines. This project will be built upon 4 strategic objectives

Objective #1 – Impulse a dialogue with a broad range of stakeholders for identifying needs, challenges and opportunities so they can be modelled and prioritized in the HealthyCloud’s strategic agenda.
Objective #2 – Overcoming legal and administrative barriers of a borderless sharing of human data in Europe and establishing a robust and trustable governance that combines efficient support for research with full endorsement of citizens’ rights and interests.
Objective #3 – Provide recommendations, guidelines and best practices to enable accessing, using and reusing health data for better research outcomes across Europe within an ethically sound and legally compliant framework.
Objective #4 – Drive the adoption of mechanisms for the sustainable use of European capabilities on computational systems including both Cloud and High Performance Computing.

Coordinator: Juan Gonzalez, Instituto Aragones de Ciencias Salud, Spain

Official website: https://healthycloud.eu

Horizon
2020

Horizon 2020

It can take less than one day to sequence a whole human genome. This technical prowess, unthinkable just a few decades ago, has opened up new possibilities for improving human health, from preventative medicine (based on genetic predisposition) and faster and more accurate diagnosis, to the development of pharmacogenomics (more efficient treatments with reduced harmful side effects). Unleashing the potential of personalised medicine, a healthcare approach that takes into account a person’s genetic make-up, is expected to bring significant socio-economic benefits, including more efficient national health systems, leading to better health and quality of life of patients, and increased life expectancy. This is, however, uncharted territory where common mechanisms to securely share the required information have yet to be designed, agreed and implemented, at national, European and international levels, so that genomic and phenotypic (clinical, lifestyle) data can be searched and accessed, within and across national jurisdictions. Europe is uniquely placed to take on this challenge and position itself as a global leader in this field.
Until recently, genomic data have predominantly been generated, curated and used in research settings, with health care systems lacking the necessary processes to bring in this genomic knowledge into their daily practice. Notably, it is the lack of integration of genomic and clinical data that represents a major bottleneck, both in research and health settings. Furthermore, it is generally complex to share genomic data within and across national jurisdictions – this reduces sample sizes and hence the statistical power required for adequate research and clinical decisions to happen, of particular relevance to rare diseases, the understanding of polygenic diseases, and minority ethnic groups. Working in partnership with European countries that have signed, or not, the ‘Towards access to at least 1 million sequenced genomes in the EU by 2022’ Declaration, as well as national health care providers, patient organisations, research infrastructures and the industry, the B1MG (Beyond 1 Million Genome) project aims to bridge the gap between research and practice, to accelerate translation into improved healthcare. This will be achieved by collaboratively developing a roadmap for the integration of genomic data with phenotypic data across borders using demonstrators from different medical areas.

Coordinator: Serena Scollen, ELIXIR-Europe, United Kingdom

Official website: https://b1mg-project.eu

Horizon 2020

Long-term sustainability of a distributed research infrastructure rests on a foundation of stable national Nodes. ELIXIR’s long-term sustainability plan sets out a range of actions to secure operations and provide the scientific capabilities needed to support cutting-edge research. Several components of our long-term sustainability plan are already on-going and *this project* is designed to drive significant progress against the major, complex and outstanding issue of aligning national data management practice, impact assessments and national roadmap positioning. Thus, the focus of *This project* is on strengthening the national ELIXIR Nodes. *this project* will harmonise toolkits, operations and monitoring indicators. The long-term operation of a pan-European network that delivers national and transnational data management requires the development of business models, funding strategies and service agreements that ensure long-term operations of national Nodes. Specifically, we aim to achieve this transformation by delivering results against four project objectives:

Objective 1: Develop a sustainable and scalable operating model for transnational life-science data management support by leveraging national capabilities in ELIXIR Nodes
Objective 2: Strengthen Europe’s data management capacity through a comprehensive training programme delivered throughout the European Research Area
Objective 3: Align national data management standards, tools and services into a long-term sustainable, scalable and cost-effective toolkit
Objective 4: Building on national investments in both Nodes and the joint ELIXIR Programme to drive harmonised monitoring and impact assessments, increasing the global influence of ELIXIR.

Coordinator: Niklas Blomberg, ELIXIR-Europe, United Kingdom

Official website: https://elixir-europe.org/about-us/how-funded/eu-projects/converge

Horizon 2020

Smart4Health will enable the citizen-centred EU EHR exchange for personalised health. This will pave the way for the full deployment of citizen-centred solutions and services in a digital single market for wellbeing and healthcare. It will provide for interoperability, complementarity and cooperativity with profiles that are currently used e.g. by Member States and regions. Smart4Health will enable the bridging between the diverse EU EHR data and citizen-generated health data. It will connect citizens to science and personalised health services.

The European Commission 2017 review of the Digital Single Market lists three priorities:

• Citizens´ secure access to electronic health records and the possibility to share it across borders
• Supporting data infrastructure, to advance research, disease prevention and personalised health and care
• Facilitating feedback and interaction between patients and healthcare providers, to support prevention and citizen empowerment as well as quality and patient-centred care.

Smart4Health addresses these priorities with an outstanding consortium that develops, tests and validates a platform prototype for the Smart4Health citizen-centred health record EU-EHR exchange. Smart4Health provides an easy-to-use, secure, constantly accessible and portable health data and services prototype, thus advancing citizen health and wellbeing, and digital health innovation. Smart4Health builds on the strength of the European infrastructures CEF, ELIXIR, the EIT Health, BBMRI-ERIC, the European Virtual Laboratory for Enterprise Interoperability (I-VLab), the experience and knowledge gained and generated, the EU/US collaboration in eHealth, e.g. the Icahn School of Medicine at Mount Sinai, the momentum of initiatives in the Member States, e.g. ‘Medizininformatik Initiative’ of the BMBF in Germany. Smart4Health enables citizens to manage and bridge their own health data throughout the EU and beyond, advancing own and societal health and wellbeing.

Coordinator: Ricardo Goncalves, UNINOVA, Portugal

Official website: https://www.smart4health.eu

Innovative Medicines Initiative (IMI-JU)

Wide sharing of knowledge and data drives the progression of science. Shared data allows other researchers to reproduce findings and benchmark quality of experiments. Sharing data so that other researchers can Find, Access and Interoperate – i.e. integrate the data with the outcomes of their own experiments – allows Reuse and an opportunity to build the large aggregated cohorts we need to detect rare signals and manage the many confounding factors in translational research. This project will develop the guidelines and tools needed to make data FAIR. Through worked examples using IMI and EFPIA data and application and extension of existing methods we will improve the level of discovery, accessibility, interoperability and reusability of selected IMI and EFPIA data. In addition, through disseminated guidelines and tailored training for data handlers in academia, SMEs and pharmaceuticals, data management culture will change and be sustained and datasets will be reused by pharmaceutical companies, academia and SMEs. Our FAIR SME & Innovation programme will enable wide data reuse and foster an innovation ecosystem around these data that power future re-use, knowledge generation, and societal benefit. We call this approach ‘FAIRplus’.

Coordinator: Serena Scollen, ELIXIR-Europe, United Kingdom

Official website: https://fairplus-project.eu

Horizon 2020

Coronavirus disease 2019 (COVID-19) caused by infection with SARS coronavirus 2 (SARS-CoV-2) has reached pandemic proportions with more than 7 million people infected and 0.4 million people killed worldwide. Death rates are accentuated by cardiovascular comorbidities and arrhythmias leading to unexpected major cardiovascular events. Being able to identify COVID-19 patients at risk of developing cardiovascular events leading to death would allow improving surveillance and care. Currently, there is no accurate method to predict outcome of COVID-19 patients. COVIRNA is a patient-centered Innovation Action aiming to satisfy this urgent and unmet need. COVIRNA will complete and deploy a prognostic system based on cardiovascular biomarkers of COVID-19 clinical outcomes combined with digital tools and artificial intelligence analytics (i.e. prediction model). Complementary expertise of 15 EU partners from the healthcare sector, academia, association and industry will allow conducting a large retrospective study on existing cohorts of COVID-19 patients. By upscaling the already validated and patented research use only FIMICS panel of cardiac-enriched long noncoding RNA biomarkers into an in-vitro diagnostic test (COVIRNA) adapted to COVID-19 patients, the project will quickly deliver a minimally-invasive, simple yet robust and affordable prognosis tool that can be used in the context of the current COVID-19 crisis as well as in further major health issues. By tackling the cardiovascular complications in COVID-19, known to contribute significantly to mortality, the project outputs are expected to have a major impact on the pandemic outcomes. The COVIRNA test will be CE-marked and prepared for commercialisation, allowing to risk stratify patients, adapt therapies and to inform drug design.

Coordinator: Yvan Devaux (LIH), Luxembourg

Official website: https://covirna.eu

Horizon 2020

This HPC centre of excellence optimises codes for cell-level simulations in HPC/Exascale and bridges the gap between organ and molecular simulations, thus contributing to the European Personalised Medicine Roadmap.

The centre will become the entry point to Exascale-ready cell-level simulation software, able to transform personal omics data into actionable mechanistic models of medical relevance, supporting developers and end-users with know-how and best practices. It will connect simulation software developers with HPC, HTC and HPDA experts at centres of excellence such as POP and HiDALGO. PerMedCoE will also work with other biomedical consortia such as ELIXIR and LifeTime, connecting pre-exascale infrastructures hosted by supercomputing centres such as the Barcelona Supercomputing Center and CSC–IT Center for Science.

The LCSB is one of the 12 partners from across Europe participating in this project. The Bioinformatics Core is in charge of developing and optimising a pre exascale cell level simulation software and leads the development of guidelines for data protection and privacy preservation in an exascale HPC environment.

Coordinator: Alfonso Valencia, Barcelona Supercomputing Center (BSC), Spain

Official website: www.permedcoe.eu

JPND (FNR INTER)

Age represents by far the highest risk factor for dementia, including Alzheimer’s disease (AD). However, not every person will develop dementia during aging, indicating that age-related processes may not inescapably lead to dementia. The elucidation of the fundamental processes occurring in aging is likely to prevent or postpone the development of dementia. One such key mechanism is cellular senescence, which causes chronic inflammation through the release senescence-associated secretory phenotype (SASP) profile of mediators. PREADAPT will build on the hypothesis that chronic systemic- and neuroinflammation, quantified through a set of SASP mediators, affects the basal trajectory of the senescence occurring in the aging brain, thus allowing to predict future cognitive decline and dementia. The levels and changes of SASP mediators during aging are modulated by different genetic and environmental factors defining thereby a personalised risk for progressing to dementia. Importantly, research has identified that SASP mediators are also altered in cerebrospinal fluid of AD patients. Moreover, SASP together with genetics, known AD biomarkers, and other comorbidities define a combined Risk Profile which provides personalised information on the risk of progressing to dementia. To achieve these goals, PREADAPT has gathered a team of leading experts in the field of neuroinflammation, epidemiology, genetics, epigenetics, neuropsychology, and clinical research. PREADAPT has access to state-of-the-art methodology and knowhow on inflammatory markers to define a set of SASP mediators which derived from PREADAPT own preliminary research. PREADAPT has also access to large epidemiological and clinical follow-up studies that are characterised in-depth using neuroimaging, genomics, and proteomics. This unique configuration will enable PREADAPT to identify, already at pre-dementia stages, age-related profiles informing on the personalised future risk to decline cognitively and to progress to dementia. From a translational perspective, PREADAPT will provide first evidence showing that a SASP personalised risk profile responds to specific intervention depending on the profile of an individuum.

Coordinator: Alfredo Ramirez, University of Cologne, Germany

EUROSTARS (FNR INTER)

ReDiRECt targets to introduce in the pharmaceutical company sector (the market) candidates for drug repurposing in bladder cancer (BC) (the products). An in silico drug repurposing based on the comparison of the molecular signature of BC against the molecular signature of drugs will be applied. The BC signature will be derived from integration of proteomics data with publicly available transcriptomics and literature- mined data. The most promising findings will be tested in model systems.

Coordinator: Harald Mischak, Mosaiques Diagnostics, Germany

ERA PerMed (FNR INTER)

Heart failure, the number 1 reason for death in the EU, is a disease with complex aetiology (e.g. volume dependent heart failure, ischemic heart disease, hypertension, etc.) and varying severity (HFpEF, HFrEF). As these influencing factors vary between patients, individual treatment options are urgently needed. This heterogeneity also often prevents the transfer of mono-causal animal models to humans as the shared and disliked features are unknown.

The availability of bio-medical data on individual patients (imaging, sensors, omics) has increased dramatically in recent years and deep-phenomapping has the potential to better classify patients based on heterogeneous data sets. Furthermore, mechanistic models have matured to clinical application enabling molecular understanding of complex pathophysiological processes if data quality is sufficient.

Here we propose a novel concept (the HeartMed platform) to enhance translational medicine and support personalised medical decision making.

HeartMed will compile heterogeneous data of animal models and human patients and perform deep-phenomapping to identify heart failure subclasses and assess conformities and differences between pre- and clinical phenotypes. For patient specific modelling models have to be parameterised with data of sufficient high quality, that are difficult and expensive to obtain from patients (e.g. omics from myocardial tissue). This results in so called “missing data”. Based on the phenomapping classification, HeartMed will combine pre-/clinical information for complementing missing data to enable patient specific mechanistic modelling for a broader class of patients.

In a Clinical proof-of-concept study of patients with heart failure (retrospective data), we will use the HeartMed platform to improve patient classification, determine transferability of animal models and use animal data to improve patient specific modelling with metabolic and hemodynamic models.

Coordinator: Titus Kühne, Charité, Germany

Innovative Medicines Initiative (IMI-JU)

Immune-mediated diseases (IMIDs) are an increasing medical burden in industrialised countries worldwide. IMIDs are characterised by an enormous heterogeneity with regard to disease outcome and response to targeted therapies, which currently cannot be adequately anticipated to tailor individual patient management. Hence, mechanistic understanding of this heterogeneity and biomarkers predictive for disease control and therapy response over time are important prerequisites of a future precision medicine in IMIDs. ImmUniverse has been formed as a European transdisciplinary consortium to tackle these unmet needs and to understand the role of the crosstalk between tissue microenvironment and immune cells in disease progression and response to therapy of four different IMIDs: ulcerative colitis, Crohn’s disease, Psoriasis and atopic dermatitis. Following this unique cross-disease approach ImmUniverse will fill the gap and the limitations of current studies, which do not systematically compare the complex interactions between recirculating immune cells and the respective tissue microenvironment. The consortium will combine analysis of tissue-derived signatures with “circulating signatures” detectable in liquid biopsies, employing state-of-the-art profiling technologies corresponding to multi-Omics datasets. The project will also bring diagnostics in IMID to a new level by implementing disruptive non-invasive liquid-biopsy methodology in combination with novel, validated circulating biomarker assays which are expected to improve diagnosis, inform early in the clinical course on disease severity and progression and enable treatment response monitoring. The identified signature will be validated to monitor state/progression and response to therapy in prospective observational cohorts. Realisation of these objectives will result in improvement of patient management, lead to increased patient well-being and will significantly reduce the socioeconomic burden of these diseases.

Coordinator: Silvio Danese, HUMANITAS MIRASOLE SPA, Italy

Official website: https://www.immuniverse.eu

Innovative Medicines Initiative (IMI-JU)

The vision of Immune Safety Avatar (imSAVAR) is to develop a platform for integrated nonclinical assessments of immunomodulatory therapy safety and efficacy. Existing nonclinical models do not adequately represent the complexity of the immune system and its interactions in both immunoncology and immunmediated diseases. They also do not accurately reflect the diversity of response to new therapies that is seen in clinical medicine. We will, thus, constantly refine existing and develop new nonclinical models with the final goal of validation aiming at:

• understanding the value of nonclinical models for predicting efficacy and safety of immunomodulators incorporating cellular high throughput assays, complex organisms models and micro physiological systems
• developing new endpoints and better monitoring approaches for immune function tests
• designing cellular and molecular biomarkers for early detection of adverse effects.

The platform imSAVAR will be based upon case studies for prioritised therapeutic modalities and has been built around institutes of the Fraunhofer-Gesellschaft which has strong track records in applied science and in particular toxicology. The consortium will improve the prediction of the transferability of safety and efficacy of immunomodulators from pre-clinical models to first-in-human studies in collaboration with the private sector, pharma, regulators and technology providers. We will share experience on customised models that can be deployed (w.r.t. the 3Rs principles), establish the necessary infrastructure, conduct the analyses and provide wider disease domain expertise. This conjoint effort assures that the platform imSAVAR constantly benefits the field of immune safety evaluation, and will generate opportunities for European businesses. A guiding principle of this consortium is the meaningful engagement of multiple stakeholders including patients and regulators.

Coordinator: Peter Loskill, Fraunhofer, Germany

Official website: https://imsavar.eu

Marie Sklodowska Curie Actions Innovative Training Networks

Dementia is currently diagnosed largely based on cognitive decline, while pathology starts years before symptom onset. To make progress in the development of effective drugs for dementia, there is an urgent need for biomarkers to enable precision health: for early and specific diagnosis and objective monitoring of disease progression.
With its multidisciplinary team of scientists from academia, industry, and patient organisations, MIRIADE aims to train a new generation of scientists able to optimise and accelerate development of novel biomarkers for dementia.
MIRIADE will integrate biomarker discovery data from multiple platforms and develop a Dementia Disease Map to enhance biomarker identification (WP1). We will develop assays for prioritised biomarkers (WP2), and selected markers will be clinically validated (WP3). We will study pre-analytical stability and validate against regulatory requirements (WP4) and develop a roadmap for optimal biomarker development (WP5). MIRIADE will thus establish an innovative biomarker-focussed cross-sectoral research and training programme that will equip ESRs with a unique combination of skills in big data analysis, biomarker assay development, innovation management, and a thorough understanding of medical needs. This programme will provide a new task force of scientists that are optimally trained to the accelerate the biomarker development for dementias and able to progress effective biomarker tools to the clinic.

Coordinator: Charlotte Teunissen, VUMC (NL)

Official website: https://miriade.eu

Innovative Medicines Initiative (IMI-JU)

Our objective is to provide a taxonomic and predictive systems medicine model of Atopic Dermatitis and Psoriasis based on clinical and molecular profiling to (i) identify determinants of clinically relevant outcomes (disease manifestation, progression, comorbidity development and treatment response) (ii) improve understanding on shared and distinct disease mechanism(s) and associated signatures, and their relative importance in patient subpopulations and (iii) deliver biomarkers that identify disease trajectories and treatment response for use in drug development and clinical practice. BIOMAP will create a biospecimen and data resource of unprecedented scale and depth accessible via a central, open-source data and analysis portal, harmonising diverse, high quality, multi-dimensional datasets on skin and blood (whole and single cell), large scale population-based and trial data alongside clinical research infrastructure delivering supplementary material flexible to the needs of the consortium. This resource will be systematically analysed using state-of-the-art methodologies in epidemiology, molecular profiling, skin biology and mathematical modelling to define disease and drug endotypes and how these interact with lifestyle and environmental factors. Selected, highly discriminatory, associated biomarkers will pass through a diagnostics pipeline (novel in-silico trial methods and assay development), ready for immediate translation. BIOMAP is expected to drive drug discovery to target causal mechanisms, shorten drug development pathways, and fundamentally change the diagnosis and management paradigm, from re-active to pro-active strategies that encompass disease biology and life-time trajectory, matching the intervention (prevention, modification of risk factors, therapeutics) with endotypes. Clinically annotated endotypes and associated biomarkers will identify when, in whom and how to intervene to minimise disease impact and improve outcomes.

Coordinator: Stephan Weidinger, University Kiel, Germany

Official website: https://www.biomap-imi.eu

Marie Sklodowska Curie Actions Innovative Training Networks

Glioblastoma (GBM) is the most frequent, aggressive and lethal of all brain tumours. It has a universally fatal prognosis with 85% of patients dying within two years. New treatment options and effective precision medicine therapies are urgently required. This can only be achieved by focused multi-sectoral industry-academia collaborations in newly emerging, innovative research disciplines. GLIOTRAIN will exploit the intractability of GBM to address European applied biomedical research training needs. The ETN, which comprises 9 beneficiaries and 14 partner organisations from 8 countries, will train 15 innovative, creative and entrepreneurial ESRs. The research objective of GLIOTRAIN is to identify novel therapeutic strategies for application in GBM, while implementing state of the art next generation sequencing, systems medicine and integrative multi-omics to unravel disease resistance mechanisms. Research activities incorporate applied systems medicine, integrative multi-omics leveraging state of the art platform technologies, and translational cancer biology implementing the latest clinically relevant models. The consortium brings together leading European and international academics, clinicians, private sector and not-for-profit partners across GBM fields of tumour biology, multi-omics, drug development, clinical research, bioinformatics, computational modelling and systems biology. Thus, GLIOTRAIN will address currently unmet translational research and clinical needs in the GBM field by interrogating innovative therapeutic strategies and improving the mechanistic understanding of disease resistance. The GLIOTRAIN ETN addresses current needs in academia and the private sector for researchers that have been trained in an environment that spans translational research, medicine and computational biology, and that can navigate confidently between clinical, academic and private sector environments to progress applied research findings towards improved patient outcomes.

Coordinator: Annette Byrne, Royal College of Surgeons in Ireland, Ireland

Website: https://www.gliotrain.eu

Horizon 2020

The SYSCID consortium aims to develop a systems medicine approach for disease prediction in CID. We will focus on three major CID indications with distinct characteristics, yet a large overlap of their molecular risk map: inflammatory bowel disease, systemic lupus erythematodes and rheumatoid arthritis. We have joined 15 partners from major cohorts and initiatives in Europe (e.g.IHEC, ICGC, TwinsUK and Meta-HIT) to investigate human data sets on three major levels of resolution: whole blood signatures, signatures from purified immune cell types (with a focus on CD14 and CD4/CD8) and selected single cell level analyses. Principle data layers will comprise SNP variome, methylome, transcriptome and gut microbiome. SYSCID employs a dedicated data management infrastructure, strong algorithmic development groups (including an SME for exploitation of innovative software tools for data deconvolution) and will validate results in independent retrospective and prospective clinical cohorts. Using this setup we will focus on three fundamental aims : (i) the identification of shared and unique “core disease signatures” which are associated with the disease state and independent of temporal variation, (ii) the generation of “predictive models of disease outcome”- builds on previous work that pathways/biomarkers for disease outcome are distinct from initial disease risk and may be shared across diseases to guide therapy decisions on an individual patient basis, (iii) “reprogramming disease”- will identify and target temporally stable epigenetic alterations in macrophages and lymphocytes in epigenome editing approaches as biological validation and potential novel therapeutic tool. Thus, SYSCID will foster the development of solid biomarkers and models as stratification in future long-term systems medicine clinical trials but also investigate new causative therapies by editing the epigenome code in specific immune cells, e.g. to alleviate macrophage polarisation defects.

Coordinator: Philip Rosenstiel, Christian-Albrechts-Universität zu Kiel, Germany

Official website: https://syscid.eu

Parkinson’s disease (PD) is the second most prevalent neurodegenerative disease in the world. Although many genetic and environmental factors contributing to the risk of PD have been identified, no unique causal mechanism is defined.
Information on various aspects of PD pathogenesis is rapidly increasing and needs to be efficiently organized, so that the resulting data is available for exploration and analysis. To that end, LCSB, in the collaboration with the Systems Biology Institute, Tokyo (SBI), has developed the Parkinson’s disease (PD) map (Fujita et al.).
The PD map is a manually curated knowledge repository established to describe molecular mechanisms of PD. It compiles literature-based information on PD into an easy to explore and freely accessible molecular interaction map and offers research-facilitating functionalities such as the overlay of experimental data and the identification of drug targets on the map (see user guide).
We envision the PD map as a hub for the PD community to deal with the exponentially increasing information on PD and we encourage the PD community to join forces and support this project by integrating their expertise to continuously refine and expand the knowledge within the PD map (see community).
With our continuous efforts in developing the computational tools and the joint curation of content with the PD community, we hope that thefreely accessible PD map opens new avenues in PD research.
To get newest information on PD map, please subscribe for the PD map newsletter.

BioKB platform, a pipeline which, by exploiting text mining and semantic technologies, helps researchers easily access semantic content of thousands of abstracts and full text articles. The text mining component analyses the articles content and extracts relations between a wide variety of concepts, extending the scope from proteins, chemicals and pathologies to biological processes and molecular functions. Extracted knowledge is stored in a knowledge base publicly available for both, human and machine access, via this web application and SPARQL endpoint.

Website: http://biokb.lcsb.uni.lu

Fonds National de la Recherche

NCER-PD represents a joint effort between 4 partners in Luxembourg that unite their expertise in Parkinson’s disease. In order to answer the urgent questions surrounding the occurance of Parkinson’s disease, researchers need to analyse clinical data and samples from hundreds of patients and healthy control persons. Our group provides NCER-PD with our competences and technology for the integration, curation and analysis of multidimensional data. To this end, the Data and Computation platform will establish secure and anonymised data ows among other NCER-PD platforms. Well-grounded machine learning and computational modeling approaches will enable data analysis and interpretation.

Coordinator: Rejko Krüger, University of Luxembourg

Official website: https://www.parkinson.lu

Michael J Fox Foundation (MJFF)

The age of onset and penetrance (likelihood of disease) of individuals with the LRRK2 G2019S mutation varies considerably, the latter ranging in some families from as high as 100 percent to as low as 22 percent. This variation suggests that genetic modifiers contribute to LRRK2 pathogenesis in Parkinson’s disease (PD). The objective of this project is to collect and sequence the genomes of multiple LRRK2 families and use innovative technology and computational approaches to identify and validate novel genetic modifiers of LRRK2-mediated neurodegeneration. The overarching goal is to identify genetic modifiers of LRRK2 G2019S–induced neurodegeneration in PD. To do this, researchers propose a four-phase plan:

• identification and collection of samples from LRRK2 families
• integrating analysis of existing genetic data on PD patients with LRRK2 G2019S mutations to confirm the identity of candidate genetic modifiers
• whole genome sequencing data on LRRK2 G2019S families to identify novel genetic modifiers
• funneled into a validation scheme to directly test potential genetic modifiers for modifying LRRK2 G2019S-induced neurodegeneration in induced pluripotent stem cell (iPSC)-derived neurons from patients with the LRRK2 G2019S mutation.

This project hopes to identify genes that are important for the progression of LRRK2 associated PD. By sequencing the genomes of individuals from many families harboring LRRK2 mutations, investigators will use computational approaches to pinpoint specific genetic mutations that either enhance or lessen the onset and/or progression of LRRK2-associated PD. They will then use neurons, derived from patients with LRRK2 mutations, to validate and understand the role of these genetic mutations within cells. This work would not only increase understanding of what goes wrong in the cells of LRRK2 patients, but also help with genetic testing and in identifying potential therapeutic targets.

NHGRI

Epi25 is a collaborative of more than 200 partners from 40 research cohorts from around the world. More than 14,000 exomes have been sequenced as part of this collaborative effort. We expect to find evidence that accurate and detailed phenotypic data reduces genetic heterogeneity, allows for identification of a well-matched replication cohort, and clarifies the phenotypic spectrum associated with a gene. This approach will help us address fundamental questions about the importance of rare variants, common variants, or de novo changes as the basis for specific forms of epilepsy.

Website: http://epi-25.org

DFG Research Unit (FNR co-funded)

Epilepsy is a common, severe, and disabling condition with a significant disease burden worldwide. Despite many available treatment options, the seizures are not well controlled in one third of all patients with epilepsy. Gene discovery and first functional analyses of genetic defects have been major drivers to unravel disease mechanisms in the last 20 years and have brought about the first personalised treatment options. However, most of the genetic alterations underlying epilepsy remain to be elucidated and the mechanisms driving a healthy into an epileptic brain are not well understood. A common feature of genetic epilepsies is the typical age dependency the origin of which is largely unknown and which differs between syndromes. Therefore, developmental factors are likely to play a pivotal role for epileptogenesis of genetic epilepsies. In this Research Unit (RU), we aim to investigate if and how genetic mutations induce a cascade of multidimensional epileptogenic processes, such as transcriptional, cellular (morphological, neurophysiological), and network changes, and how these interact with developmental processes which likely contribute to the age‐dependent manifestation of seizure and behavioral phenotypes in genetic epilepsies.

Coordinator: Holger Lerche, University of Tübingen, Germany

Fonds National de la Recherche

Mitochondria play an essential role in neuronal function and survival. Maintaining the functional integrity of mitochondria is important for cell survival. Extensive prior data generated by use of genotyping arrays and/or exome sequencing approaches in monogenetic and sporadic forms of PD has unequivocally implicated mitochondrial dysfunction as one of the central pathophysiological pathways in PD. Nevertheless, there remains an appreciable gap in deciphering the missing heritability in PD. Primarily, this may result from a dominating focus on understanding the impact of common and rare variants encoded by nuclear genes in PD. By contrast, emerging evidence suggests that genetic variability within mitochondrial DNA may explain missing heritability which, hitherto, cannot be deciphered by nuclear encoded genes alone. This hypothesis is supported by various genetic studies which have shown the involvement of mitochondrial “haplogroups” in causing disease susceptibility for PD. However, results have remained inconclusive so far due to inadequate sample sizes.

In the proposed project, MiRisk-PD, we will implement an integrative approach to understand the role and impact of both nuclear encoded mitochondrial genes and the mitochondrial genome in explaining the missing heritability in PD. This new integrative strategy will be based on (i) a large exome repository of clinically well-defined PD cohort (4500 cases and 5500 controls) within Parkinson disease Genomics Sequencing Consortium (PDGSC) to define nuclear encoded “mitochondrial-network map”; (ii) a unique collection of families with autosomal dominant and autosomal recessive PD (for mitochondrial genome sequencing) and (iii) a large cohort of clinically well-defined sporadic PD patients (45,000 cases and 40,000 controls) from the Genetic Epidemiology of Parkinson disease (GEoPD) consortium, covering different populations worldwide for genetic studies that will translate into (iv) functional validation studies in patient-derived cellular models.

The multisystem approach, as outlined in our MiRisk-PD proposal, will identify stratified cohorts based on the genomic profile to identify and explore novel therapeutic targets, paving the way for a personalised medicine program for PD.

Coordinator: Rejko Krüger, University of Luxembourg

BMBF Individualisierte Medizin

Treat-ION represents a network of clinicians and scientists across Germany to advance the knowledge about recognising and treating rare neurological ion channel and transporter disorders. Those comprise a variety of neuropsychiatric diseases and symptoms including developmental delay, epilepsy, episodic and chronic ataxia, migraine and others, which often occur in combination or are caused by mutations in the same channels. Due to the common fundamental function of channels and transporters to regulate neuronal excitability and ionic homeostasis, pathophysiological and therapeutic principles are shared across diseases. The main goal of this grant application is to translate findings from genetic and pathophysio- logical studies into rational, individualised therapies. We will therefore focus on therapeutic studies in cellular, animal and human models, which will be complemented by in silico searches for new treatments, better predictions for the functional consequences of mutations for therapeutic purposes and cellular drug screens. We will focus our efforts on approved and available ‘repurposed’ drugs. As a proof-of-principle, we successfully have been per- forming n-of-1 trials and established three investigator-initiated trials in specific rare channel disorders with other funding, which will be of great value for the network. The results of our research and the knowledge of experts will be systematically and directly delivered to patients through a structured molecular therapeutic board attached to the German academy of rare neurological diseases (DASNE).

Coordinator: Holger Lerche, University of Tübingen, Germany

Laurent Heirendt, Vilem Ded, Marina Popleteeva, Miroslav Kratochvil, Jenny Tran, Kaan Çimir 

The aim of the Responsible and Reproducible Research (R3) initiative at the LCSB is to raise research quality and increase the overall reproducibility of scientific results. This ambitious goal is achieved through state-of-the-art infrastructure and software, GDPR compliant data processes, and data handling methods, as well as platforms and tools for high-quality scientific computing code. The classical research publication workflow is standardized by structuring data, capturing lab protocols, and experimental methods in electronic lab notebooks, source code versioning, workflow management, and freezing of project states via virtualization technologies.  

The R3 program is built on five pillars: the R3 pathfinder, the R3 school, the R3 accelerator, R3 pre-publication check (PPC), and R3 data.  

• Based on individual consultations, the R3 pathfinder program helps the individual groups of LCSB to follow best practices.  
• The R3 school includes courses and learning materials on data protection, version control, and scientific computing. 
• The R3 accelerator aims at more mature projects with strong R3 components that can be further boosted in their level of quality and reproducibility.  
• The R3 pre-publication check (PPC) provides state-of-art pre-review, support and feedback for the publication efforts at LCSB.  
• R3 data further supports data stewardship and data management activities at LCSB.  

Additionally, in the R3 clinic, scientists and researchers receive hands-on support to push the boundaries with their individual projects. 

Email: lcsb-r3@uni.lu 

Visiting address: 

Campus Belval | Rouden Eck | 4^th floor
1, Boulevard du Jazz 
L- 4370 Belvaux