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

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 molecula...

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Published inNature communications Vol. 14; no. 1; p. 5269
Main Authors 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, Al-Sagheir, Afaf I., Mansour, Ahmad M., Alawaji, Ali, Aldhilan, Amal, Alhashem, Amal, Alhemidan, Amal, Nabil, Amira, Khan, Arif O., Aljohar, Aziza, Alsaleem, Badr, Tabarki, Brahim, Lourenco, Charles Marques, Faqeih, Eissa, AlShail, Essam, Almesaifri, Fatima, Mutairi, Fuad Al, Alzaidan, Hamad, Morsy, Heba, Alshihry, Hind, Alkuraya, Hisham, Girisha, Katta Mohan, Al-Fayez, Khawla, Al-Rubeaan, Khalid, kraoua, Lilia, Alnemer, Maha, Tulbah, Maha, Zaki, Maha S., Alfadhel, Majid, Abouelhoda, Mohammed, Nezarati, Marjan M., Al-Qattan, Mohammad, Shboul, Mohammad, Abanemai, Mohammed, Al-Muhaizea, Mohammad A., Al-owain, Mohammed, Bafaqeeh, Mohammed Sameer, Alshammari, Muneera, Abukhalid, Musaad, Alsahan, Nada, Derar, Nada, Meriki, Neama, Bohlega, Saeed A., Tala, Saeed Al, Alhassan, Saad, Wali, Sami, Mohamed, Sarar, Coskun, Serdar, Saadeh, Sermin, Tkemaladze, Tinatin, Kurdi, Wesam, Alhumaidi, Zainab Ahmed, Rahbeeni, Zuhair, Alkuraya, Fowzan S.
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group 29.08.2023
Nature Publishing Group UK
Nature Portfolio
Subjects
Complex compounds
Diagnostic systems
Disease
Disorders
Gene mapping
Genetic diversity
Genetic screening
Genetic variance
Genomes
Genomic imprinting
Information sharing
Phenotypes
Recombination
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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.
AbstractList 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.
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. Despite large sequencing and data sharing efforts it often remains challenging to provide a genetic diagnosis for individuals with suspected Mendelian (single-gene) disorders. Here, the authors describe their experiences in identifying likely causal genetic variants in thousands of families and highlight the need to consider a wide range of challenges rather than a narrow focus on sequencing technologies.
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.Despite large sequencing and data sharing efforts it often remains challenging to provide a genetic diagnosis for individuals with suspected Mendelian (single-gene) disorders. Here, the authors describe their experiences in identifying likely causal genetic variants in thousands of families and highlight the need to consider a wide range of challenges rather than a narrow focus on sequencing technologies.
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.
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.
ArticleNumber 5269
Author Abdulwahab, Firdous
Helaby, Rana
Maddirevula, Sateesh
Alshidi, Tarfa
Alshammari, Muneera
Alhumaidi, Zainab Ahmed
Abouelhoda, Mohammed
Alsaleem, Badr
Alnemer, Maha
Al-Fayez, Khawla
Tulbah, Maha
Abouyousef, Omar
Girisha, Katta Mohan
Alhemidan, Amal
Mutairi, Fuad Al
Nezarati, Marjan M.
Altuwaijri, Norah
kraoua, Lilia
Tabarki, Brahim
AlAbdi, Lama
Saadeh, Sermin
Hamid, Halima
Aljohar, Aziza
Alkuraya, Fowzan S.
Alqahtani, Mashael
Alkuraya, Hisham
Alzaidan, Hamad
Abanemai, Mohammed
Alhassan, Saad
AlShail, Essam
Tkemaladze, Tinatin
Bafaqeeh, Mohammed Sameer
Lourenco, Charles Marques
Almesaifri, Fatima
Mansour, Ahmad M.
Faqeih, Eissa
Abukhalid, Musaad
Alfadhel, Majid
Shboul, Mohammad
Hashem, Mais O.
Almulhim, Aisha
Shamseldin, Hanan E.
Tala, Saeed Al
Meriki, Neama
Mohamed, Sarar
Al-Sagheir, Afaf I.
Al-owain, Mohammed
Aldhilan, Amal
Rahbeeni, Zuhair
Alshihry, Hind
Khouj, Ebtissal
Coskun, Serdar
Al-Rubeaan, Khalid
Alawaji, Ali
Alhashem, Amal
Morsy, Heba
Alzahrani, Fatema
Bohlega, Saeed A.
Nabil, Amira
Derar, Nada
Alsahan, Nada
Jaafar, Amal
Khan, Arif O.
Kurd
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Springer Nature Limited 2023
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Snippet Abstract Despite large sequencing and data sharing efforts, previously characterized pathogenic variants only account for a fraction of Mendelian disease...
Despite large sequencing and data sharing efforts, previously characterized pathogenic variants only account for a fraction of Mendelian disease patients,...
Abstract Despite large sequencing and data sharing efforts, previously characterized pathogenic variants only account for a fraction of Mendelian disease...
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StartPage 5269
SubjectTerms Complex compounds
Diagnostic systems
Disease
Disorders
Gene mapping
Genetic diversity
Genetic screening
Genetic variance
Genomes
Genomic imprinting
Information sharing
Phenotypes
Recombination
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Title Diagnostic implications of pitfalls in causal variant identification based on 4577 molecularly characterized families
URI https://www.proquest.com/docview/2858510158/abstract/
https://search.proquest.com/docview/2858986705
https://pubmed.ncbi.nlm.nih.gov/PMC10465531
https://doaj.org/article/d4f8244eab354a59b6af99779f7a3556
Volume 14
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