article · Nature Communications
In a cohort of 4577 molecularly characterised families with Mendelian disease, significant analytical difficulties in identifying and interpreting causal genetic variants were examined. These diagnostic challenges span multiple distinct categories, including clinical phenotype, pedigree structure, positional mapping, novel gene-disease assertions, and complex variant inheritance. The findings indicate a 34.3 percent probability of encountering at least one of these interpretive obstacles during evaluation. Crucially, addressing challenges that do not stem from sequencing technology alone is estimated to increase diagnostic yield by around 71 percent. When applied to 314 patient cases with previously negative clinical exome or genome results, this comprehensive interpretive strategy resolved 54.5 percent of cases by pinpointing likely causal variants. This demonstrates that improving outcomes for rare genetic conditions requires addressing broad clinical and analytical pitfalls rather than relying strictly on sequencing hardware.
Many patients with rare inherited conditions remain undiagnosed even after standard genomic sequencing. By classifying the non-sequencing pitfalls that obscure causal mutations, this work provides clear guidance on resolving inconclusive tests. Adopting these broader analytical practices can help clinical teams solve difficult cases, shorten diagnostic delays for families, and maximise the utility of existing genomic data.
This work directly benefits clinical diagnostic laboratories, genetic testing providers, and developers of genomic interpretation software. Incorporating these identified categories of interpretive pitfalls into diagnostic workflows and variant-filtering algorithms could substantially enhance diagnostic hit rates. Having been applied and tested on a cohort of 314 unsolved cases, the approach is mature and ready for implementation within clinical diagnostic services and undiagnosed disease programmes.
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Despite large sequencing and data sharing efforts, previously characterized pathogenic variants only account for a fraction of Mendelian disease patients, which highlights the need for accurate identification and interpretation of novel variants. In a large Mendelian cohort of 4577 molecularly characterized families, numerous scenarios in which variant identification and interpretation can be challenging are encountered. We describe categories of challenges that cover the phenotype (e.g. novel allelic disorders), pedigree structure (e.g. imprinting disorders masquerading as autosomal recessive phenotypes), positional mapping (e.g. double recombination events abrogating candidate autozygous intervals), gene (e.g. novel gene-disease assertion) and variant (e.g. complex compound inheritance). Overall, we estimate a probability of 34.3% for encountering at least one of these challenges. Importantly, our data show that by only addressing non-sequencing-based challenges, around 71% increase in the diagnostic yield can be expected. Indeed, by applying these lessons to a cohort of 314 cases with negative clinical exome or genome reports, we could identify the likely causal variant in 54.5%. Our work highlights the need to have a thorough approach to undiagnosed diseases by considering a wide range of challenges rather than a narrow focus on sequencing technologies. It is hoped that by sharing this experience, the yield of undiagnosed disease programs globally can be improved.
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DOI: 10.1038/s41467-023-40909-3
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