Article Impact Level: HIGH Data Quality: STRONG Summary of Nature Medicine, 1–12. https://doi.org/10.1038/s41591-024-03420-w Dr. Steven Laurie et al.
Points
- The Solve-Rare Diseases Consortium (Solve-RD) analyzed genetic data from 6,447 individuals with undiagnosed rare diseases, achieving a diagnostic yield of 12.6% through reanalysis and expert reviews.
- The study identified 552 disease-causing variants in 506 families, with 84.1% being single-nucleotide variants or short insertions/deletions and others identified through advanced bioinformatics and expert consensus.
- Many identified variants were linked to newly published disease genes, including 67 variants in novel genes and numerous reclassifications in ClinVar and expert reviews.
- The study highlights the effectiveness of international collaboration and a two-level expert review framework, providing a scalable model for rare disease diagnosis.
- The Solve-RD initiative has been extended through the European Rare Disease Research Alliance (ERDERA). It aims to analyze over 100,000 datasets, accelerating rare disease diagnosis and potential treatment exploration.
Summary
The Solve-Rare Diseases Consortium (Solve-RD), a collaborative effort of clinical and molecular scientists from 37 European expert centers, studied the genetic diagnosis of rare diseases. The study involved 6,447 individuals with undiagnosed rare diseases and aimed to evaluate the efficacy of reanalyzing genetic data to provide diagnoses. By leveraging exome sequencing data, the research team identified 552 disease-causing variants in 506 families, achieving a diagnostic yield of 8.4%. The identified variants were predominantly single-nucleotide or short insertions/deletions (84.1%), with the remaining causative variants identified through bespoke bioinformatics analyses. An additional 249 families received diagnoses through ad hoc expert reviews, resulting in an % overall diagnostic yield of 12.6%.
The study revealed that many identified variants were linked to recently published novel disease genes, with 67 variants located in newly discovered genes, 187 reclassified in ClinVar, and 210 reclassified based on expert consensus. These findings underscore the potential of international collaboration and the systematic reanalysis of genetic data to provide diagnoses for rare diseases. The research highlights the growing importance of a collaborative, two-level expert review framework, which can be adapted to future international efforts and scaled for broader use in rare disease diagnosis.
The Solve-RD approach provides a model for advancing rare disease diagnosis with significant implications for the broader research community. The consortium’s efforts have been further extended through the European Rare Disease Research Alliance (ERDERA), aiming to analyze over 100,000 rare disease datasets. The expansion of this initiative promises to accelerate the identification of diagnoses for more patients and explore potential treatments for these complex conditions. The success of Solve-RD emphasizes the power of collaboration and offers a promising strategy for future rare disease diagnostics and research.
Link to the article: https://www.nature.com/articles/s41591-024-03420-w
References Laurie, S., Steyaert, W., de Boer, E., Polavarapu, K., Schuermans, N., Sommer, A. K., Demidov, G., Ellwanger, K., Paramonov, I., Thomas, C., Aretz, S., Baets, J., Benetti, E., Bullich, G., Chinnery, P. F., Clayton-Smith, J., Cohen, E., Danis, D., de Sainte Agathe, J.-M., … Hoischen, A. (2025). Genomic reanalysis of a pan-European rare-disease resource yields new diagnoses. Nature Medicine, 1–12. https://doi.org/10.1038/s41591-024-03420-w
