Standardized transcriptome analysis improves rare disease diagnosis in the pan-European Solve-RD consortium

Abstract

RNA sequencing (RNA-seq) provides a powerful complement to DNA sequencing for uncovering pathogenic defects affecting gene expression and splicing in individuals with genetically undiagnosed rare disorders. However, as large rare disease consortia adopt RNA-seq, challenges arise due to cohort heterogeneity, variability in tissues and sample sizes, and differences in interpretation practices. Here, we present a harmonized analytical and interpretation framework developed by the pan-European Solve-RD consortium to address these challenges. We analyzed 521 RNA-seq samples from whole blood, fibroblasts, muscle and peripheral blood mononuclear cells collected across more than 30 clinics and five European Reference Networks. Aberrant expression and splicing events were identified using OUTRIDER and FRASER 2.0 and analysed through a standardized four-level scoring framework that encompassed RNA-seq outlier reliability, phenotype relevance, variant mechanism, and segregation evidence, captured in structured reports for interpretation. Regular meetings, and collaborative "Solvathon" workshops were used to evaluate variant pathogenicity. This effort resulted in molecular diagnoses for 19 families out of 248 (7.7%) for whom DNA analyses had been inconclusive. Furthermore, three cases diagnosed using DNA analyses were confirmed, and 49 candidate events and five novel candidate disease genes were identified in the remaining families. Our results demonstrate the feasibility and impact of large-scale, standardized RNA-seq analysis in a transnational research setting. This framework provides a model for other international initiatives such as the Undiagnosed Diseases Network and ERDERA, paving the way for broader clinical implementation of transcriptome-based rare disease diagnostics.