Next-generation sequencing (NGS) has vastly improved the diagnostic capabilities in the field of rare and undiagnosed diseases. However, there are still a number of limitations, such as difficulty in detecting and interpreting complex variants and addressing nebulous gene-disease associations. This blog highlights how Golden Helix’s VarSeq software provides a number of powerful solutions to address some of the challenges that remain for using NGS in rare and undiagnosed disease analysis.  

Successes and Challenges of NGS for Undiagnosed Diseases

A recent study published in the Orphanet Journal of Rare Diseases and another study published in the Journal of Clinical Investigation highlight the notable impact that NGS has had on the field of rare and undiagnosed disease diagnostics. This includes increasing diagnostic rates, facilitating the identification of novel disease-causing events, such as small deletions and duplications and non-coding variants that would not have otherwise been found using traditional methods. NGS also has the capacity to reduce the diagnostic odyssey for patients with rare and undiagnosed diseases, potentially decreasing overall healthcare costs by eliminating unnecessary tests and procedures.

While these improvements are invaluable, several challenges remain, such as:

• Difficulties distinguishing pathogenic from benign or uncertain variants, particularly for novel or rare variants that are not reported in databases such as ClinVar.
• Undiagnosed diseases with complex genetic roots, including structural variations and non-coding variants that are challenging to detect and interpret, or may even be related to epigenetic states such as methylation status.
• Diverse clinical presentations of the same genetic disorder complicate diagnosis, requiring sophisticated gene-disease association analysis.

Leveraging VarSeq to Addresses These Challenges

VarSeq offers powerful solutions that directly address several of the challenges mentioned above:

• Complex Genomic Analyses – VarSeq handles both long and short read data, enabling better capture of non-coding variants and complex genomic elements that might be missed by traditional approaches. This capability opens the gateway for analysis of structural variants such as complex rearrangements and translocations, as well as methylation status identified from long read data (see recent webcast on this topic).
• Copy Number Variant Detection – The VarSeq platform can detect copy number variation directly from BAM/CRAM files of short read sequencing from targeted panels, exomes, or whole genomes, reducing the need for additional assays to identify deletions and duplications.
• Family and Cohort Analyses – VarSeq’s sophisticated algorithms for family analysis (duo, trio, quad and extended families) and case control cohort studies excel at identifying potentially pathogenic variants shared across individuals. This is critical for rare disease research where cohort or family studies can provide useful diagnostic evidence.
• Variant Warehousing – The assessment cataloging and VarSeq Warehouse variant repository and querying features streamline the organization and retrieval of variant information, facilitating collaborative research and longitudinal studies essential for undiagnosed disease programs.
• Phenotypic Matching – The platform’s phenotype ranking and virtual panel algorithms connect genotypic data with potential or indicated clinical presentations, helping to address the challenge of phenotypic heterogeneity.
• Gene Disease Association – Integrated gene-disease association databases enable the establishment of connections between novel variants and known diseases and disorders, helping researchers and clinicians identify potential diagnoses that might otherwise be overlooked.
• Streamlined Identification of Pathogenic Variants– The VarSeq platform also affords direct annotation access to databases such as ClinVar, ClinGen, GnomAD, and functional impact prediction databases such as CADD, REVEL, and Alpha Missense. Combined with our ACMG guideline based variant classification algorithms VarSeq facilitates identification of both well-known and rare or novel pathogenic variants.

Conclusion

While the diagnostic battle for patients with undiagnosed diseases remains challenging, the combination of advanced NGS technologies and sophisticated variant analysis tools like VarSeq represents a powerful approach for providing answers. If you have questions or comments about the content of this article or would like to learn more about the utility of VarSeq for rare and undiagnosed disease analysis, please reach out to [email protected].