European Genomic Reanalysis of Rare Diseases: New Diagnoses and Future Blueprint

Academic Background

Rare diseases are defined as conditions affecting a very small proportion of the population, with the European Union setting the threshold at fewer than 50 individuals per 100,000. Despite the vast diversity of rare diseases (over 6,000 types), more than 70% are linked to genetic factors. These diseases pose significant challenges to individuals and healthcare systems, impacting 3.5%-6.0% of people over their lifetime. Although genomic sequencing has advanced rare disease diagnostics, many patients remain without a definitive molecular diagnosis. Recent studies have shown that reanalyzing existing genomic data can lead to new diagnoses, particularly through the discovery of novel disease genes and improvements in variant annotation. However, due to the time-intensive nature and multidisciplinary expertise required, such reanalyses are not routinely performed.

To address this gap, 37 expert centers across Europe formed the Solve-RD consortium, aiming to enhance diagnostic rates for rare diseases through systematic reanalysis. The project’s goal is to integrate clinical, pedigree, and genomic data, creating a collaborative network to provide new diagnostic opportunities for undiagnosed rare disease patients while offering a scalable blueprint for future international efforts.

Source of the Paper

The study was conducted by over 300 clinicians, geneticists, and translational researchers from multiple renowned institutions, including Radboud University Medical Center, Centro Nacional de Análisis Genómico (CNAG), and the University of Tübingen. Key authors include Steven Laurie, Wouter Steyaert, and Elke de Boer. The paper was published in Nature Medicine in February 2025, titled “Genomic reanalysis of a pan-European rare-disease resource yields new diagnoses.”

Research Workflow

1. Data Collection and Quality Control

The Solve-RD consortium collected genomic data from 6,004 undiagnosed rare disease families across 12 European countries and Canada, involving 6,449 affected individuals and 3,196 unaffected relatives. The dataset included 554 whole genomes and 9,722 exomes, generated using 28 different exome-enrichment kits and various short-read sequencing platforms. After quality control, 9,874 datasets remained (523 whole genomes and 9,351 exomes).

2. Systematic Reanalysis

The study employed a two-level expert review framework, involving both data experts and clinical experts. The reanalysis covered a broad range of genomic variants, including single-nucleotide variants (SNVs), short insertions/deletions (indels), noncanonical splice variants, mitochondrial DNA variants, copy number variants (CNVs), structural variants (SVs), mobile element insertions (MEIs), and short tandem repeat expansions (STRs). Each European Reference Network (ERN) compiled gene lists specific to their disease areas, ranging from 230 genes (Genturis) to 1,820 genes (RND).

3. Diagnostic Outcomes

Through systematic reanalysis, the research team identified new genetic diagnoses in 506 families (8.4%). Among the 552 disease-causing variants identified, 84.1% were SNVs or indels, while the remaining 15.9% were other variant types discovered through bespoke bioinformatics analyses. Additionally, ad hoc expert review diagnosed an additional 249 families (4.1%), bringing the overall diagnostic yield to 12.6%.

4. Variant Type Analysis

In 419 families, SNVs or indels were the primary disease-causing variants (461 variants), including 282 dominant, 85 homozygous recessive, 76 compound heterozygous recessive, and 18 hemizygous variants. Furthermore, the study identified 87 diagnoses caused by other variant types (e.g., CNVs, SVs, MEIs, STRs), with CNVs being the most prevalent type (44 cases).

5. Clinical Actionability

The study further explored the clinical actionability of the diagnostic results, finding that 73 patients (14.4%) harbored variants in potentially actionable genes. These genes were associated with various therapeutic or preventive interventions, and some cases had already received specific treatments based on the findings.

Key Results

1. Discovery of New Diagnoses: Through systematic reanalysis, the research team identified new genetic diagnoses in 506 families, involving 552 disease-causing variants. Of these, 84.1% were SNVs or indels, and the remaining 15.9% were other variant types.

2. Diversity of Variant Types: The study analyzed not only SNVs and indels but also identified rare variant types such as CNVs, SVs, MEIs, and STRs, leading to new diagnoses in 87 families.

3. Clinical Actionability: The study emphasized the clinical utility of the diagnostic results, noting that 14.4% of diagnosed cases had potential treatment or intervention value, with some already receiving specific treatments.

Conclusions and Implications

This study successfully provided new genetic diagnoses for 12.6% of previously undiagnosed rare disease families through systematic genomic reanalysis. It demonstrated the potential of reanalysis to improve diagnostic rates and established a scalable framework for future international collaborations. The infrastructure and collaborative networks developed by the Solve-RD consortium will serve as vital resources for future rare disease research and diagnostics.

Study Highlights

1. Large-Scale Collaboration: The study involved 37 European expert centers, showcasing the importance of large-scale international cooperation in rare disease research.

2. Analysis of Multiple Variant Types: Beyond SNVs and indels, the study utilized bioinformatics tools to identify rare variant types, expanding the scope of rare disease diagnostics.

3. Clinical Actionability: The study highlighted the clinical utility of the diagnostic results, offering new possibilities for the treatment and management of rare disease patients.

Other Valuable Information

The research team proposed practical recommendations, including data standardization, integration of multi-variant calling pipelines, and regular updates to bioinformatics tools. These suggestions provide important guidance for future genomic reanalyses of rare diseases.

Through this study, the Solve-RD consortium has not only brought new hope to rare disease patients but also provided valuable resources and infrastructure for the global rare disease research community.