Diagnostic implications of pitfalls in causal variant identification based on 4577 molecularly characterized families

Lama AlAbdi, Sateesh Maddirevula, Hanan E. Shamseldin, Ebtissal Khouj, Rana Helaby, Halima Hamid, Aisha Almulhim, Mais O. Hashem, Firdous Abdulwahab, Omar Abouyousef, Mashael Alqahtani, Norah Altuwaijri, Amal Jaafar, Tarfa Alshidi, Fatema Alzahrani and Fowzan S. Alkuraya ()
Additional contact information
Lama AlAbdi: King Saud University
Sateesh Maddirevula: King Faisal Specialist Hospital and Research Center
Hanan E. Shamseldin: King Faisal Specialist Hospital and Research Center
Ebtissal Khouj: King Faisal Specialist Hospital and Research Center
Rana Helaby: King Faisal Specialist Hospital and Research Center
Halima Hamid: King Saud University
Aisha Almulhim: King Saud University
Mais O. Hashem: King Faisal Specialist Hospital and Research Center
Firdous Abdulwahab: King Faisal Specialist Hospital and Research Center
Omar Abouyousef: King Faisal Specialist Hospital and Research Center
Mashael Alqahtani: King Faisal Specialist Hospital and Research Center
Norah Altuwaijri: King Faisal Specialist Hospital and Research Center
Amal Jaafar: King Faisal Specialist Hospital and Research Center
Tarfa Alshidi: King Faisal Specialist Hospital and Research Center
Fatema Alzahrani: King Faisal Specialist Hospital and Research Center
Fowzan S. Alkuraya: King Faisal Specialist Hospital and Research Center

Nature Communications, 2023, vol. 14, issue 1, 1-19

Abstract: Abstract 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.

Date: 2023
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DOI: 10.1038/s41467-023-40909-3

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