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Increased diagnostic yield from negative whole genome-slice panels using automated reanalysis.
Seth I Berger1,2, Georgia Pitsava2, Andrea J Cohen1,2,3
1Children's National Rare Disease Institute, Division of Genetics and Metabolism, Washington, DC, USA.
Clinical Genetics
|May 17, 2023
Summary
Reanalyzing whole genome sequencing (WGS) data with an automated system increased diagnostic yield by 25% in rare pediatric diseases. This approach identified new variants missed by initial targeted gene panels, improving genetic diagnoses.
Area of Science:
- Genomics
- Clinical Diagnostics
- Bioinformatics
Background:
- Undiagnosed rare diseases pose significant challenges in clinical settings.
- Targeted gene panels may miss diagnoses due to incomplete phenotyping or novel gene-disease associations.
- Whole genome sequencing (WGS) offers comprehensive genetic information but requires efficient analysis methods.
Purpose of the Study:
- To evaluate the diagnostic yield of genome-slice panel reanalysis using an automated phenotype/gene ranking system.
- To assess the utility of genome-wide reanalysis of existing WGS data for identifying clinically significant variants.
- To determine the added value of advanced bioinformatic tools in uncovering diagnoses missed by initial clinical testing.
Main Methods:
- Analysis of WGS data from 16 undiagnosed pediatric cases using a machine-learning-based variant prioritization tool (Moon™).
- Reanalysis focused on genome-wide data, not limited by the original targeted gene panel content.
- Comparison of findings from genome-wide reanalysis with initial diagnostic results.
Main Results:
- A 25% increase in diagnostic findings was achieved through automated genome-wide reanalysis.
- Potentially clinically significant variants were identified in 5 out of 16 cases (31.25%).
- Four cases yielded diagnoses in genes not initially included on the targeted panels, and one case identified a complex structural rearrangement missed initially.
Conclusions:
- Automated genome-wide reanalysis of clinical WGS data significantly enhances diagnostic yield for rare pediatric diseases.
- Reanalysis is valuable for uncovering diagnoses missed due to phenotypic expansion, incomplete phenotyping, or complex structural variants.
- This approach demonstrates the added value of comprehensive WGS data reanalysis over routine clinical testing.
