Skip to main content
European Commission logo

Pooling resources to make better diagnoses of rare diseases

By pooling patient data and applying state-of-the art genetic methods, EU-funded research is improving the diagnosis of rare diseases that affect the lives of tens of millions of EU citizens.

© s_l #188023440, 2018. Source:

PDF Basket

No article selected

It is estimated that rare diseases affect more than 30 million people in the EU. However, with potentially between 6 000 and 8 000 rare disease entities, patient populations for each individual rare disease are small and dispersed, which makes international collaboration crucial.

The EU-funded project Solve-RD aims to improve the diagnosis of rare diseases and is starting its work with four core networks of care providers, called European Reference Networks. These have been established to share and enhance the knowledge and resources used for treating rare diseases.

The initial four European Reference Networks involved in the project cover rare neurological diseases: neuromuscular diseases, congenital malformations and intellectual disability, and genetic tumour risk syndromes. These will add and share their patient data, taking the lead in improving the diagnosis and treatment of these rare diseases. Other European Reference Networks will be included as the project progresses.

“Patients with a rare disease generally go through a long and arduous process, often described as a ‘rare disease odyssey’, that can last up to 15 years before finding a physician who knows what is actually wrong with them,” explains Holm Graessner, managing director of the coordinating entity for the Solve-RD project at the University of Tübingen in Germany. “Scientific advances can also take a long time as it is difficult to find sufficient numbers of people with the same rare disease to enable successful research.”

Difficult diagnosis

Collectively rare diseases can affect many people, with some perhaps running into hundreds of thousands. However, in recent years, it has become clear that the analysis of a doctor alone does not suffice to diagnose a rare disease. “The key is to develop better genetic tests to effectively diagnose rare disease,” says Graessner.

Applying genomics and other ’omic’ or high-throughput techniques for the molecular characterisation of rare diseases can lead to the development of new types of diagnoses for a large number of undiagnosed rare diseases.

This is where Solve-RD comes in. The academic partners in the project have designed an infrastructure that will enable the coordination and analysis of data generated across Europe on rare diseases.

By combining the existing genetic patient data from all the project collaborators, Solve-RD can greatly increase the chances of finding a second or third patient with the same rare disease. “This commitment to share data on rare diseases on this scale is unique,” Graessner says.

But Solve-RD will also go further by applying the latest available ‘multi-omics’ methods. If the DNA data highlights a particular disease the researchers will turn to other tests to investigate genetic functions.

Again, combining the various ‘omics’ techniques can provide extra information that could ensure the diagnosis of a rare disease. However, the enormous amount of data resulting from this multi-omics approach must be converted into useful, comprehensible information by bioinformatic scientists using smart algorithms. These approaches can include artificial intelligence applications.

Virtual networks

The project will expand its work to the remaining 24 European Reference Networks that were set up to improve and harmonise diagnosis and treatment for people suffering from rare diseases.

“Using shared knowledge and guidelines, a patient in Romania, for example, will receive the same diagnostics and treatment as a patient in Sweden or Spain,” explains Graessner. “Solve-RD will have a significant impact on our knowledge and clinical practice when it comes to diagnosing and treating rare diseases in Europe,” he concludes.

The project aims to increase diagnostic yield by up to 20 % and anticipates diagnosing some 2 000 currently undiagnosed cases.

PDF Basket

No article selected

Project details

Project acronym
Project number
Project coordinator
Project participants:
United Kingdom
United States
Total cost
€ 15 361 621
EU Contribution
€ 15 361 621
Project duration

All success stories

This story in other languages