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A catalogue of new incidence estimates of monogenic neurodevelopmental disorders caused by de novo variants

A large fraction of rare and severe neurodevelopmental disorders are caused by sporadic de novo variants. Epidemiological disease estimates are not available for the vast majority of these de novo monogenic neurodevelopmental disorders because of phenotypic heterogeneity and the absence of large-sca...

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Autores principales: López-Rivera, Javier A, Pérez-Palma, Eduardo, Symonds, Joseph, Lindy, Amanda S, McKnight, Dianalee A, Leu, Costin, Zuberi, Sameer, Brunklaus, Andreas, Møller, Rikke S, Lal, Dennis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7174049/
https://www.ncbi.nlm.nih.gov/pubmed/32168371
http://dx.doi.org/10.1093/brain/awaa051
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author López-Rivera, Javier A
Pérez-Palma, Eduardo
Symonds, Joseph
Lindy, Amanda S
McKnight, Dianalee A
Leu, Costin
Zuberi, Sameer
Brunklaus, Andreas
Møller, Rikke S
Lal, Dennis
author_facet López-Rivera, Javier A
Pérez-Palma, Eduardo
Symonds, Joseph
Lindy, Amanda S
McKnight, Dianalee A
Leu, Costin
Zuberi, Sameer
Brunklaus, Andreas
Møller, Rikke S
Lal, Dennis
author_sort López-Rivera, Javier A
collection PubMed
description A large fraction of rare and severe neurodevelopmental disorders are caused by sporadic de novo variants. Epidemiological disease estimates are not available for the vast majority of these de novo monogenic neurodevelopmental disorders because of phenotypic heterogeneity and the absence of large-scale genomic screens. Yet, knowledge of disease incidence is important for clinicians and researchers to guide health policy planning. Here, we adjusted a statistical method based on genetic data to predict, for the first time, the incidences of 101 known de novo variant-associated neurodevelopmental disorders as well as 3106 putative monogenic disorders. Two corroboration analyses supported the validity of the calculated estimates. First, greater predicted gene-disorder incidences positively correlated with larger numbers of pathogenic variants collected from patient variant databases (Kendall’s τ = 0.093, P-value = 6.9 × 10(−6)). Second, for six of seven (86%) de novo variant associated monogenic disorders for which epidemiological estimates were available (SCN1A, SLC2A1, SALL1, TBX5, KCNQ2, and CDKL5), the predicted incidence estimates matched the reported estimates. We conclude that in the absence of epidemiological data, our catalogue of 3207 incidence estimates for disorders caused by de novo variants can guide patient advocacy groups, clinicians, researchers, and policymakers in strategic decision-making.
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spelling pubmed-71740492020-04-27 A catalogue of new incidence estimates of monogenic neurodevelopmental disorders caused by de novo variants López-Rivera, Javier A Pérez-Palma, Eduardo Symonds, Joseph Lindy, Amanda S McKnight, Dianalee A Leu, Costin Zuberi, Sameer Brunklaus, Andreas Møller, Rikke S Lal, Dennis Brain Reports A large fraction of rare and severe neurodevelopmental disorders are caused by sporadic de novo variants. Epidemiological disease estimates are not available for the vast majority of these de novo monogenic neurodevelopmental disorders because of phenotypic heterogeneity and the absence of large-scale genomic screens. Yet, knowledge of disease incidence is important for clinicians and researchers to guide health policy planning. Here, we adjusted a statistical method based on genetic data to predict, for the first time, the incidences of 101 known de novo variant-associated neurodevelopmental disorders as well as 3106 putative monogenic disorders. Two corroboration analyses supported the validity of the calculated estimates. First, greater predicted gene-disorder incidences positively correlated with larger numbers of pathogenic variants collected from patient variant databases (Kendall’s τ = 0.093, P-value = 6.9 × 10(−6)). Second, for six of seven (86%) de novo variant associated monogenic disorders for which epidemiological estimates were available (SCN1A, SLC2A1, SALL1, TBX5, KCNQ2, and CDKL5), the predicted incidence estimates matched the reported estimates. We conclude that in the absence of epidemiological data, our catalogue of 3207 incidence estimates for disorders caused by de novo variants can guide patient advocacy groups, clinicians, researchers, and policymakers in strategic decision-making. Oxford University Press 2020-04 2020-03-13 /pmc/articles/PMC7174049/ /pubmed/32168371 http://dx.doi.org/10.1093/brain/awaa051 Text en © The Author(s) (2020). Published by Oxford University Press on behalf of the Guarantors of Brain. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Reports
López-Rivera, Javier A
Pérez-Palma, Eduardo
Symonds, Joseph
Lindy, Amanda S
McKnight, Dianalee A
Leu, Costin
Zuberi, Sameer
Brunklaus, Andreas
Møller, Rikke S
Lal, Dennis
A catalogue of new incidence estimates of monogenic neurodevelopmental disorders caused by de novo variants
title A catalogue of new incidence estimates of monogenic neurodevelopmental disorders caused by de novo variants
title_full A catalogue of new incidence estimates of monogenic neurodevelopmental disorders caused by de novo variants
title_fullStr A catalogue of new incidence estimates of monogenic neurodevelopmental disorders caused by de novo variants
title_full_unstemmed A catalogue of new incidence estimates of monogenic neurodevelopmental disorders caused by de novo variants
title_short A catalogue of new incidence estimates of monogenic neurodevelopmental disorders caused by de novo variants
title_sort catalogue of new incidence estimates of monogenic neurodevelopmental disorders caused by de novo variants
topic Reports
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7174049/
https://www.ncbi.nlm.nih.gov/pubmed/32168371
http://dx.doi.org/10.1093/brain/awaa051
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