Strategy

The overall aim of WP7 is to ensure that the project’s objectives are realised and that the project is implemented in compliance with the EC Grant Agreement and CA.

Output

1. Provide scientific coordination and management of the project to ensure efficient and within budget successful achievement of objectives, completion of deliverables and milestones
2. Ensure that METHYLOMIC is carried out under EU regulations, according to the contractual legal requirements and financial guidelines and facilitate swift decision-making
3. Foster collaboration within METHYLOMIC and actively trail research feeding into the project
4. Establish measures for adequate data management
5. Implement an online tool to facilitate data sharing and internal communication.

Partners

A management structure has been designed to create optimal conditions to conduct this project. Due to the scale of the project, a Project Support Team composed of the Project Coordinator (Prof. Geert D’Haens, AMC), Deputy Coordinator (Prof. Wouter de Jonge), one senior EU project manager (Drs Paul Bessems, DESCIN) and one senior EU project controller (Drs Ralf Zaal, DESCIN) will be installed. The General Assembly, chaired by the Project Coordinator, is the highest decision-making body in METHYLOMIC and consists of 1 representative per beneficiary. To keep the management structure straightforward the Project Coordinator, Deputy Coordinator and Work Package leaders will be clustered in the Executive Committee, chaired by the Project Coordinator, representing each Work Package and is the core group for implementing decisions made in the General Assembly into the Work Packages. An External Advisory Board will officially be installed. The Project Coordinator and WP6 leader will ensure close involvement and collaboration with the External Advisory Board, Dissemination, Exploitation, and Intellectual Property committee and Patient Advisory Council (established in WP6) and actively involve them in the project meetings and stakeholder workshops.

Strategy

The overall aim of WP6 is to maximise the scientific, economic, and societal impacts of METHYLOMIC by implementing appropriate strategies for dissemination, exploitation and communication, and setting-up stakeholder workshops and cutting-edge trainings.

Output

The activities of this WP are governed by a shared consortium level plan for the dissemination and exploitation of the results. The project and its results will be promoted via a series of communication activities specifically aimed at relevant target groups. Stakeholder engagement, training and sustainability activities complement the dissemination and exploitation plan and further enhance the expected impacts of METHYLOMIC.

Partners

Dr Gionata Fiorino (Vita-Salute San Raffaele University) will coordinate all measures to maximise impact and lead WP6. With his track-record, Dr Fiorino is well equipped to roll-out the dissemination, exploitation and communication strategies and chair the Dissemination, Exploitation, and Intellectual Property Committee (DEIPC). This committee has a key role in the management of innovations and will advise on the management of knowledge, intellectual property and on other innovation-related activities in the project. The DEIPC will consist of representatives of the partners’ technological transfer departments and all Work Package leaders. The WP6 team will be assisted by communication experts from the participating universities, ECCO and EFCCA to complement activities with narratives and visualisations as much as possible. In addition, a Patient Advisory Council will be established.

Strategy

The overall aim of this work is to discover how DNA methylome-based biomarkers predict therapy response. What cell in blood is responsible, and what genes determine response in each individual patient? While DNA methylation measured on bulk material is useful for biomarker discovery, it is unclear what the biological relevance is epigenetic markers to the disease process. Such mechanistic insight helps acceptance of our therapy guidance platform. To disentangle cell-specific differences in DNA methylation, we will study the DNA methylome of individual cells. However, since no single-cell DNA methylation reference of peripheral blood currently exists, measuring DNA methylation in single cells remains challenging as we would have no way of annotating the individual cells. However, many datasets are accessible to date of annotated single-cell transcriptomic profiles in similar blood cells, which we will use for this purpose. Accordingly, our setup delivers a single-cell multi-omic map where both the DNA methylome and the transcriptome of the same cell is assayed. This approach provides unique insight into how cellular differences in DNA methylation are associated with transcriptional differences; what cell contributes what to the disease process. We seek to understand whether the previously identified response-associated DNA methylation biomarkers relevant for gene transcription differences-to make our prediction even more specific and effective.

Output

Single cell methylome and transcriptomes related to the predictor CpGs (methylation of the cytosine base at a CG dinucleotide position) for each of the three studied biologicals in CD.

Innovative elements

•  Use of ground-breaking methods combining DNA methylation and RNA-sequencing of individual cells.
• Identification of novel cellular modules, which would potentially provide targets of interest that could ameliorate non-response.
• Creation of a reference for future bulk DNA methylation studies in blood cells.

Partners

Amsterdam University Medical Centres – location AMC, University of Oxford – Nuffield Department of Experimental Medicine Division, and Diagenode hold ample experience with single-cell transcriptomics as well as epigenomic analyses separately, and together with Horaizon, we are well able to interpret multiomic analyses.

Strategy

The overall aim of this WP is to confirm the potential of DNA methylation markers for the prediction of biological therapy success in RA and PsO. Similar to CD, biological therapies are also partly effective for RA. However, remission upon biological therapy is achieved in less than 50% of RA cases. For PsO, biological therapy success is better, but a stratification is certainly needed as well. There are limited tools to help clinicians select the most appropriate biological for these patients. A pilot study conducted at AMC and Reade Amsterdam, identified epigenetic marks in RA patients (50 responders vs. 43 non-responders) that predict biological therapy response in patients treated with anti-TNF. Our prior work on CD patients make it logical to establish discovery and validation cohorts to identify patterns of epigenetic biomarkers in the blood of patients with RA, similar as to CD. Three centres of expertise in RA and renowned clinical trial units are committed to collaborate in this work.

Output

Sampling (n=400) from discovery and validation RA and PsO cohorts completed, predictive algorithms validated, and methylation assays designed.

Innovative elements

•  Pivotal collaboration among gastroenterologists, dermatologists, and rheumatologists on diseases with common underlying mechanisms
• Use of stringent and validated endpoints in an observational trial
• Remote and cross-site monitoring and data management.

Partners

Three clinical RA and PsO centers of expertise (Instituto de Medicina Molecular João Lobo Antunes, Ghent University, and Amsterdam University Medical Centres – location AMC) with ongoing cohort studies of patients on 3 commonly prescribed biologicals.

Strategy

The overall aim of WP3 is to ensure the successful implementation and completion of the prospective randomised clinical trial for individualised therapy in CD patients. This can be split into the following objectives:

1. Design and coordination of the clinical trial
2. Register and report on the trial in public trial registries
3. Build and maintain a web-based randomisation platform, clinical database and electronic case report forms
4. Obtain regulatory approval of the trial at 54 sites in 6 countries (NL, BE, UK, IT, SL, HU)
5. Include, stratify, treat, follow, and assess 378 patients with CD for 6 months
6. Trial monitoring
7. Manage all data, and perform the statistical analyses
8. Write interim and full study reports
9. Perform an economic evaluation of the predictive algorithm supported by the newly developed targeted methylation assay for the participating countries at a European level.

Output

378 patients with CD have been enrolled in the trial by 54 sites across 6 countries.

Innovative elements

• Web-based eCRF with direct patient input on outcomes and health economically relevant data
• Patient input on secondary endpoints / PROs (patient reported outcomes)
• Remote monitoring and data management
• Approximately 1/3 of patients will be assessed by ultrasound in addition to endoscopy, using a central independent platform comparable to that established for endoscopy
• Last but not least, a prospective clinical trial dedicated to therapy guidance based on epigenetic biomarkers is completely novel.

Partners

Experienced clinical sites, a clinical research organization and patients will team-up with proven successes in CD trials (Amsterdam University Medical Centres – location AMC, Alimentiv, BIRD Group, King’s College London, Vita-Salute San Raffaele University, University of Szeged, University Medical Centre Ljubljana, and European Federation of Crohn’s & Ulcerative Colitis Associations).

Strategy

The overall aim of this WP is to develop a targeted methylation assay that will be useful in clinical use, that could work as a Companion Diagnostic. Such an assay will be used in a clinical trial in CD patients in WP3 that will put our idea to the test in clinical practice by the treating physicians by using an app device.

Output

Validated predictive biomarker assay, aligned with regulatory requirements and ready for use in the clinical trial.

Innovative elements

• The assay is new in its ability to capture DNA methylation markers fast; within 2 weeks. The assay is a capture-based sequencing kit predicting best response to therapy- this is novel in its potential especially outside of the field of oncology.
• The predictor markers might also yield insights into the biological pathways underlying therapy resistance and the pathophysiology of CD, which could in turn provide new targetable pathways.

Partners

Five dedicated Small and medium-sized enterprises with complementary know-how in diagnostic assay development (Genome Diagnostics [GenDx]), epigenetics (Diagenode), DNA target enrichment (Twist Bioscience), machine learning (Horaizon), and IVD regulation (Asphalion).

Strategy

The main aim of this WP is to generate, improve and refine the algorithms capable of predicting response to biological treatment based on epigenetic DNA methylation markers that we found to discriminate responders from non-responders to treatment with 3 different mainstream biologicals in CD. Further, we also test the validity of this approach in Rheumatoid Arthritis (RA) and Psoriasis (PsO). This work is built on an earlier study in 240 patients (performed together with researchers from Radcliff Hospital at Oxford University) in it was found that epigenetic biomarkers can indeed be used to guide personalized medication in these chronic immune diseases.

Output

Calibrated and validated models for each biological used for CD, RA and PsO.

Innovative elements

• An algorithm based on Machine Learning is created by our small and medium enterprises partner Horaizon and is unique and state-of-the-art in its kind, reflected by multiple high impact publications in the field
• Algorithms not only predict CD therapy success (to be validated in WP3) but will also be developed for RA/PsO -in WP4- as auto-immune diseases with a similar unpredictable biological treatment efficacy.

Partners

A sound combination of geneticists, bioinformaticians (Amsterdam University Medical Centres – location AMC and University of Oxford – Nuffield Department of Experimental Medicine Division) and a deep-tech company (Horaizon) with a solid track record in machine learning methods applied in previous CD and RA cohorts.