Enabling advances in diagnosis, patient stratification and treatment for dilated cardiomyopathy patients and families.

Projektinformationen

DCM-NEXT

ID Finanzhilfevereinbarung: 101115416

DOI

10.3030/101115416

EK-Unterschriftsdatum 20 Juni 2023

Startdatum 1 Oktober 2023

Enddatum 30 September 2027

Finanziert unter

• The European Innovation Council (EIC)

Gesamtkosten

€ 4 137 718,75

EU-Beitrag

€ 4 137 668,75

Koordiniert durch

STICHTING AMSTERDAM UMC
Netherlands

Periodic Reporting for period 2 - DCM-NEXT (Enabling advances in diagnosis, patient stratification and treatment for dilated cardiomyopathy patients and families.)

Berichtszeitraum: 2024-10-01 bis 2026-03-31

Zusammenfassung vom Kontext und den Gesamtzielen des Projekts

Project Overview: Understanding and Targeting Dilated Cardiomyopathy (DCM).
Dilated Cardiomyopathy (DCM) is a severe heart muscle disease characterized by the thinning and stretching of the heart's chambers, leading to impaired pumping of blood through the body. DCM presents a significant health challenge, affecting a substantial portion of the global population, with prevalence estimates reaching as high as 1 in 250 individuals. This disorder, often striking younger adults, may be associated with significant morbidity and mortality, primarily due to heart failure and sudden cardiac death. Despite its impact, key gaps in scientific knowledge exist, which hamper effective management of affected individuals. Firstly, our knowledge of what causes DCM and how genetics plays a role is incomplete, which limits the usefulness of genetic testing in clinical care. Additionally, treatment options for DCM are limited. Current therapies mainly focus on managing symptoms and are not specific to the disease. The only potential cure is a heart transplant, and there are no approved treatments that address the root causes of the condition.

Project Objectives:
The DCM-NEXT project aims at addressing critical gaps in DCM research and clinical care. The project seeks to achieve two primary objectives:
1)Genetic understanding: Enhance our understanding of the genetic factors underpinning DCM, bridging the gap between genetic causes and the clinical expression of the disease. The goal is to improve genetic testing to allow more accurate prediction of disease onset, progression, and the risk of major adverse cardiac events.
2)Therapeutic advancements: Accelerate the development of novel therapies by identifying and validating targets involved in the pathogenesis of DCM. The project aims to move beyond generic treatments that manage symptoms. By deciphering underlying molecular disease mechanisms, it will inform the development of therapies that target mechanisms of disease.

Arbeit, die ab Beginn des Projekts bis zum Ende des durch den Bericht erfassten Berichtszeitraums geleistet wurde, und die wichtigsten bis dahin erzielten Ergebnisse

Clinical Database: DCM-NEXT leverages clinical data from 5 clinical sites, aggregating the largest collection of comprehensively characterized DCM patients globally. This scale allows for robust analyses, from discovery to validation. As of RP2, a secure database has been established with a standardized data dictionary agreed across the 5 clinical sites. To date, 2,921 patients have been included, and monthly data quality monitoring has been introduced to address missing variables. Database maintenance, governance and integration with multi-modal datasets (imaging, genomics, transcriptomics) are ongoing to support downstream analyses and for long-term sustainability.

Phenomics: The project integrates imaging modalities like echocardiography and magnetic resonance imaging, alongside ECG. Advanced AI-based approaches enhance the utility of these modalities. As of RP2, a multi-site repository of pseudo-anonymised raw CMR, echocardiography, and ECG data has been successfully established. Ongoing work applies advanced AI models to enable automated segmentation and harmonized cardiac geometry modelling for downstream applications.

Genomics: Through different genomic techniques including whole genome sequencing, the project aims to decipher the genetic factors that determine the risk of developing DCM and its severity. Insights gained will improve genetic testing and enable clinicians to better determine the risk in the individual patient, thereby improving patient care. As of RP2, a large NGS gene panel dataset comprising 5,017 DCM probands has been assembled, with ongoing harmonization to enable integrated analyses. Other genomic studies are ongoing.

Data Integration and Patient Stratification Tools: AI-driven models are employed to analyze complex datasets comprehensively. The project aims to create innovative patient stratification tools for optimal, personalized disease management. As of RP2, multi-modal data integration is well underway. Published and in-preparation studies demonstrate the clinical utility of genetic stratification for predicting advanced heart failure, treatment response, and disease progression in DCM cohorts.

Transcriptomics: In-depth analysis of cellular and molecular profiles during DCM progression, aiming to uncover distinct mechanisms based on specific gene variants. As of RP2, the biopsy repository has been expanded to enhance comparative power, and a large-scale snRNA-seq dataset (>200,000 nuclei) has been generated. Ongoing analyses are resolving cell-type–specific and disease-stage–dependent transcriptional changes, with early findings indicating shifts in fibroblast and endothelial populations across disease severity.

Target Identification: Integrated genetic, phenotypic, and transcriptomic data will be used for drug target identification. AS of RP2, gene curation expanded the number of clinically actionable DCM genes from 19 to 34, reflecting significant advances in variant interpretation. GWAS analyses increased the number of identified loci to 100 and further elucidated the inverse genetic correlation between DCM and HCM, while PGS demonstrate robust disease discrimination.

Functional and Mechanistic Studies: We investigate potential therapeutic targets and test interventions for their impact on cardiac structure and function. As of RP2, in vivo validation is advancing, with multiple high-impact publications and patented AAV-based therapeutic strategies demonstrating improved cardiac function and arrhythmia reduction in vivo.

Fortschritte, die über den aktuellen Stand der Technik hinausgehen und voraussichtliche potenzielle Auswirkungen (einschließlich der bis dato erzielten sozioökonomischen Auswirkungen und weiter gefassten gesellschaftlichen Auswirkungen des Projekts)

Societal Impact: The project delivers benefits for patients and healthcare systems by accelerating the transition toward precision medicine in DCM. Integration of genetic information enables more accurate prediction of adverse outcomes, improved timing of interventions, and better selection of patients for therapies. In addition, the identification of early molecular changes opens new opportunities for earlier diagnosis and disease interception. Collectively, these advances have the potential to reduce morbidity and mortality, improve quality of life, and provide patients and families with more care strategies. This work contributes to a shift from reactive to predictive management of cardiomyopathy.

Economic Impact: The project is positioned to help reduce healthcare costs associated with DCM by enabling improved clinical decision-making and the development of disease-modifying therapies. Enhanced risk stratification tools are expected to reduce the burden of advanced heart failure by enabling earlier and more targeted interventions, thereby decreasing hospitalizations, device implantation, and associated healthcare costs. At the same time, the identification and validation of novel therapeutic targets strengthens the cardiovascular innovation pipeline, supporting growth and competitiveness in the biotechnology and pharmaceutical sectors. This translational potential is evidenced by multiple patent applications and engagement with industry partners, creating pathways toward clinical development and commercialization of next-generation therapies.

Scientific Impact: This work provides advances in understanding DCM, driving forward fundamental understanding and translational application. Large-scale genetic studies are defining the genetic architecture of DCM with unprecedented resolution, allowing for interpretation of rare genetic variants in genetic testing approaches, and enabling approaches based on polygenic burden. In parallel, the project has identified novel disease mechanisms and, critically, moved beyond discovery to in vivo validation of targeted therapeutic strategies. The development of gene therapy approaches (including AAV-mediated gene replacement, modulation of key signaling pathways such as p53, and CRISPR-based gene activation), demonstrates the feasibility of molecular interventions for untreatable conditions. Complementing this, the generation of snRNA-seq datasets from cardiac biopsies across genetic backgrounds and disease stages offers an unprecedented resource to study cellular heterogeneity and disease progression. Together, these advances bridge the gap between genomic discovery, mechanistic insight, and therapeutic innovation.