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A pedigree-based prediction model identifies carriers of deleterious de novo mutations in families with Li-Fraumeni syndrome

De novo mutations (DNMs) are increasingly recognized as rare disease causal factors. Identifying DNM carriers will allow researchers to study the likely distinct molecular mechanisms of DNMs. We developed Famdenovo to predict DNM status (DNM or familial mutation [FM]) of deleterious autosomal domina...

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Autores principales: Gao, Fan, Pan, Xuedong, Dodd-Eaton, Elissa B., Recio, Carlos Vera, Montierth, Matthew D., Bojadzieva, Jasmina, Mai, Phuong L., Zelley, Kristin, Johnson, Valen E., Braun, Danielle, Nichols, Kim E., Garber, Judy E., Savage, Sharon A., Strong, Louise C., Wang, Wenyi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7462073/
https://www.ncbi.nlm.nih.gov/pubmed/32817165
http://dx.doi.org/10.1101/gr.249599.119
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author Gao, Fan
Pan, Xuedong
Dodd-Eaton, Elissa B.
Recio, Carlos Vera
Montierth, Matthew D.
Bojadzieva, Jasmina
Mai, Phuong L.
Zelley, Kristin
Johnson, Valen E.
Braun, Danielle
Nichols, Kim E.
Garber, Judy E.
Savage, Sharon A.
Strong, Louise C.
Wang, Wenyi
author_facet Gao, Fan
Pan, Xuedong
Dodd-Eaton, Elissa B.
Recio, Carlos Vera
Montierth, Matthew D.
Bojadzieva, Jasmina
Mai, Phuong L.
Zelley, Kristin
Johnson, Valen E.
Braun, Danielle
Nichols, Kim E.
Garber, Judy E.
Savage, Sharon A.
Strong, Louise C.
Wang, Wenyi
author_sort Gao, Fan
collection PubMed
description De novo mutations (DNMs) are increasingly recognized as rare disease causal factors. Identifying DNM carriers will allow researchers to study the likely distinct molecular mechanisms of DNMs. We developed Famdenovo to predict DNM status (DNM or familial mutation [FM]) of deleterious autosomal dominant germline mutations for any syndrome. We introduce Famdenovo.TP53 for Li-Fraumeni syndrome (LFS) and analyze 324 LFS family pedigrees from four US cohorts: a validation set of 186 pedigrees and a discovery set of 138 pedigrees. The concordance index for Famdenovo.TP53 prediction was 0.95 (95% CI: [0.92, 0.98]). Forty individuals (95% CI: [30, 50]) were predicted as DNM carriers, increasing the total number from 42 to 82. We compared clinical and biological features of FM versus DNM carriers: (1) cancer and mutation spectra along with parental ages were similarly distributed; (2) ascertainment criteria like early-onset breast cancer (age 20–35 yr) provides a condition for an unbiased estimate of the DNM rate: 48% (23 DNMs vs. 25 FMs); and (3) hotspot mutation R248W was not observed in DNMs, although it was as prevalent as hotspot mutation R248Q in FMs. Furthermore, we introduce Famdenovo.BRCA for hereditary breast and ovarian cancer syndrome and apply it to a small set of family data from the Cancer Genetics Network. In summary, we introduce a novel statistical approach to systematically evaluate deleterious DNMs in inherited cancer syndromes. Our approach may serve as a foundation for future studies evaluating how new deleterious mutations can be established in the germline, such as those in TP53.
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spelling pubmed-74620732020-09-11 A pedigree-based prediction model identifies carriers of deleterious de novo mutations in families with Li-Fraumeni syndrome Gao, Fan Pan, Xuedong Dodd-Eaton, Elissa B. Recio, Carlos Vera Montierth, Matthew D. Bojadzieva, Jasmina Mai, Phuong L. Zelley, Kristin Johnson, Valen E. Braun, Danielle Nichols, Kim E. Garber, Judy E. Savage, Sharon A. Strong, Louise C. Wang, Wenyi Genome Res Method De novo mutations (DNMs) are increasingly recognized as rare disease causal factors. Identifying DNM carriers will allow researchers to study the likely distinct molecular mechanisms of DNMs. We developed Famdenovo to predict DNM status (DNM or familial mutation [FM]) of deleterious autosomal dominant germline mutations for any syndrome. We introduce Famdenovo.TP53 for Li-Fraumeni syndrome (LFS) and analyze 324 LFS family pedigrees from four US cohorts: a validation set of 186 pedigrees and a discovery set of 138 pedigrees. The concordance index for Famdenovo.TP53 prediction was 0.95 (95% CI: [0.92, 0.98]). Forty individuals (95% CI: [30, 50]) were predicted as DNM carriers, increasing the total number from 42 to 82. We compared clinical and biological features of FM versus DNM carriers: (1) cancer and mutation spectra along with parental ages were similarly distributed; (2) ascertainment criteria like early-onset breast cancer (age 20–35 yr) provides a condition for an unbiased estimate of the DNM rate: 48% (23 DNMs vs. 25 FMs); and (3) hotspot mutation R248W was not observed in DNMs, although it was as prevalent as hotspot mutation R248Q in FMs. Furthermore, we introduce Famdenovo.BRCA for hereditary breast and ovarian cancer syndrome and apply it to a small set of family data from the Cancer Genetics Network. In summary, we introduce a novel statistical approach to systematically evaluate deleterious DNMs in inherited cancer syndromes. Our approach may serve as a foundation for future studies evaluating how new deleterious mutations can be established in the germline, such as those in TP53. Cold Spring Harbor Laboratory Press 2020-08 /pmc/articles/PMC7462073/ /pubmed/32817165 http://dx.doi.org/10.1101/gr.249599.119 Text en © 2020 Gao et al.; Published by Cold Spring Harbor Laboratory Press http://creativecommons.org/licenses/by-nc/4.0/ This article, published in Genome Research, is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/.
spellingShingle Method
Gao, Fan
Pan, Xuedong
Dodd-Eaton, Elissa B.
Recio, Carlos Vera
Montierth, Matthew D.
Bojadzieva, Jasmina
Mai, Phuong L.
Zelley, Kristin
Johnson, Valen E.
Braun, Danielle
Nichols, Kim E.
Garber, Judy E.
Savage, Sharon A.
Strong, Louise C.
Wang, Wenyi
A pedigree-based prediction model identifies carriers of deleterious de novo mutations in families with Li-Fraumeni syndrome
title A pedigree-based prediction model identifies carriers of deleterious de novo mutations in families with Li-Fraumeni syndrome
title_full A pedigree-based prediction model identifies carriers of deleterious de novo mutations in families with Li-Fraumeni syndrome
title_fullStr A pedigree-based prediction model identifies carriers of deleterious de novo mutations in families with Li-Fraumeni syndrome
title_full_unstemmed A pedigree-based prediction model identifies carriers of deleterious de novo mutations in families with Li-Fraumeni syndrome
title_short A pedigree-based prediction model identifies carriers of deleterious de novo mutations in families with Li-Fraumeni syndrome
title_sort pedigree-based prediction model identifies carriers of deleterious de novo mutations in families with li-fraumeni syndrome
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7462073/
https://www.ncbi.nlm.nih.gov/pubmed/32817165
http://dx.doi.org/10.1101/gr.249599.119
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