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Diagnostic implications of pitfalls in causal variant identification based on 4577 molecularly characterized families.
AlAbdi, Lama; Maddirevula, Sateesh; Shamseldin, Hanan E; Khouj, Ebtissal; Helaby, Rana; Hamid, Halima; Almulhim, Aisha; Hashem, Mais O; Abdulwahab, Firdous; Abouyousef, Omar; Alqahtani, Mashael; Altuwaijri, Norah; Jaafar, Amal; Alshidi, Tarfa; Alzahrani, Fatema; Alkuraya, Fowzan S.
Afiliação
  • AlAbdi L; Department of Zoology, College of Science, King Saud University, Riyadh, Saudi Arabia.
  • Maddirevula S; Department of Translational Genomics, Center for Genomic Medicine, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia.
  • Shamseldin HE; Department of Translational Genomics, Center for Genomic Medicine, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia.
  • Khouj E; Department of Translational Genomics, Center for Genomic Medicine, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia.
  • Helaby R; Department of Translational Genomics, Center for Genomic Medicine, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia.
  • Hamid H; Department of Translational Genomics, Center for Genomic Medicine, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia.
  • Almulhim A; Department of Zoology, College of Science, King Saud University, Riyadh, Saudi Arabia.
  • Hashem MO; Department of Translational Genomics, Center for Genomic Medicine, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia.
  • Abdulwahab F; Department of Zoology, College of Science, King Saud University, Riyadh, Saudi Arabia.
  • Abouyousef O; Department of Translational Genomics, Center for Genomic Medicine, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia.
  • Alqahtani M; Department of Translational Genomics, Center for Genomic Medicine, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia.
  • Altuwaijri N; Department of Translational Genomics, Center for Genomic Medicine, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia.
  • Jaafar A; Department of Translational Genomics, Center for Genomic Medicine, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia.
  • Alshidi T; Department of Translational Genomics, Center for Genomic Medicine, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia.
  • Alzahrani F; Department of Clinical Genomics, Center for Genomic Medicine, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia.
  • Alkuraya FS; Department of Translational Genomics, Center for Genomic Medicine, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia.
Nat Commun ; 14(1): 5269, 2023 08 29.
Article em En | MEDLINE | ID: mdl-37644014
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.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Exoma / Esperança Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Exoma / Esperança Idioma: En Ano de publicação: 2023 Tipo de documento: Article