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Segregation analysis of 17,425 population-based breast cancer families: Evidence for genetic susceptibility and risk prediction

Rare pathogenic variants in known breast cancer-susceptibility genes and known common susceptibility variants do not fully explain the familial aggregation of breast cancer. To investigate plausible genetic models for the residual familial aggregation, we studied 17,425 families ascertained through...

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Autores principales: Li, Shuai, MacInnis, Robert J., Lee, Andrew, Nguyen-Dumont, Tu, Dorling, Leila, Carvalho, Sara, Dite, Gillian S., Shah, Mitul, Luccarini, Craig, Wang, Qin, Milne, Roger L., Jenkins, Mark A., Giles, Graham G., Dunning, Alison M., Pharoah, Paul D.P., Southey, Melissa C., Easton, Douglas F., Hopper, John L., Antoniou, Antonis C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9606477/
https://www.ncbi.nlm.nih.gov/pubmed/36206742
http://dx.doi.org/10.1016/j.ajhg.2022.09.006
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author Li, Shuai
MacInnis, Robert J.
Lee, Andrew
Nguyen-Dumont, Tu
Dorling, Leila
Carvalho, Sara
Dite, Gillian S.
Shah, Mitul
Luccarini, Craig
Wang, Qin
Milne, Roger L.
Jenkins, Mark A.
Giles, Graham G.
Dunning, Alison M.
Pharoah, Paul D.P.
Southey, Melissa C.
Easton, Douglas F.
Hopper, John L.
Antoniou, Antonis C.
author_facet Li, Shuai
MacInnis, Robert J.
Lee, Andrew
Nguyen-Dumont, Tu
Dorling, Leila
Carvalho, Sara
Dite, Gillian S.
Shah, Mitul
Luccarini, Craig
Wang, Qin
Milne, Roger L.
Jenkins, Mark A.
Giles, Graham G.
Dunning, Alison M.
Pharoah, Paul D.P.
Southey, Melissa C.
Easton, Douglas F.
Hopper, John L.
Antoniou, Antonis C.
author_sort Li, Shuai
collection PubMed
description Rare pathogenic variants in known breast cancer-susceptibility genes and known common susceptibility variants do not fully explain the familial aggregation of breast cancer. To investigate plausible genetic models for the residual familial aggregation, we studied 17,425 families ascertained through population-based probands, 86% of whom were screened for pathogenic variants in BRCA1, BRCA2, PALB2, CHEK2, ATM, and TP53 via gene-panel sequencing. We conducted complex segregation analyses and fitted genetic models in which breast cancer incidence depended on the effects of known susceptibility genes and other unidentified major genes and a normally distributed polygenic component. The proportion of familial variance explained by the six genes was 46% at age 20–29 years and decreased steadily with age thereafter. After allowing for these genes, the best fitting model for the residual familial variance included a recessive risk component with a combined genotype frequency of 1.7% (95% CI: 0.3%–5.4%) and a penetrance to age 80 years of 69% (95% CI: 38%–95%) for homozygotes, which may reflect the combined effects of multiple variants acting in a recessive manner, and a polygenic variance of 1.27 (95% CI: 0.94%–1.65), which did not vary with age. The proportion of the residual familial variance explained by the recessive risk component was 40% at age 20–29 years and decreased with age thereafter. The model predicted age-specific familial relative risks consistent with those observed by large epidemiological studies. The findings have implications for strategies to identify new breast cancer-susceptibility genes and improve disease-risk prediction, especially at a young age.
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spelling pubmed-96064772022-10-28 Segregation analysis of 17,425 population-based breast cancer families: Evidence for genetic susceptibility and risk prediction Li, Shuai MacInnis, Robert J. Lee, Andrew Nguyen-Dumont, Tu Dorling, Leila Carvalho, Sara Dite, Gillian S. Shah, Mitul Luccarini, Craig Wang, Qin Milne, Roger L. Jenkins, Mark A. Giles, Graham G. Dunning, Alison M. Pharoah, Paul D.P. Southey, Melissa C. Easton, Douglas F. Hopper, John L. Antoniou, Antonis C. Am J Hum Genet Article Rare pathogenic variants in known breast cancer-susceptibility genes and known common susceptibility variants do not fully explain the familial aggregation of breast cancer. To investigate plausible genetic models for the residual familial aggregation, we studied 17,425 families ascertained through population-based probands, 86% of whom were screened for pathogenic variants in BRCA1, BRCA2, PALB2, CHEK2, ATM, and TP53 via gene-panel sequencing. We conducted complex segregation analyses and fitted genetic models in which breast cancer incidence depended on the effects of known susceptibility genes and other unidentified major genes and a normally distributed polygenic component. The proportion of familial variance explained by the six genes was 46% at age 20–29 years and decreased steadily with age thereafter. After allowing for these genes, the best fitting model for the residual familial variance included a recessive risk component with a combined genotype frequency of 1.7% (95% CI: 0.3%–5.4%) and a penetrance to age 80 years of 69% (95% CI: 38%–95%) for homozygotes, which may reflect the combined effects of multiple variants acting in a recessive manner, and a polygenic variance of 1.27 (95% CI: 0.94%–1.65), which did not vary with age. The proportion of the residual familial variance explained by the recessive risk component was 40% at age 20–29 years and decreased with age thereafter. The model predicted age-specific familial relative risks consistent with those observed by large epidemiological studies. The findings have implications for strategies to identify new breast cancer-susceptibility genes and improve disease-risk prediction, especially at a young age. Elsevier 2022-10-06 2022-10-06 /pmc/articles/PMC9606477/ /pubmed/36206742 http://dx.doi.org/10.1016/j.ajhg.2022.09.006 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Li, Shuai
MacInnis, Robert J.
Lee, Andrew
Nguyen-Dumont, Tu
Dorling, Leila
Carvalho, Sara
Dite, Gillian S.
Shah, Mitul
Luccarini, Craig
Wang, Qin
Milne, Roger L.
Jenkins, Mark A.
Giles, Graham G.
Dunning, Alison M.
Pharoah, Paul D.P.
Southey, Melissa C.
Easton, Douglas F.
Hopper, John L.
Antoniou, Antonis C.
Segregation analysis of 17,425 population-based breast cancer families: Evidence for genetic susceptibility and risk prediction
title Segregation analysis of 17,425 population-based breast cancer families: Evidence for genetic susceptibility and risk prediction
title_full Segregation analysis of 17,425 population-based breast cancer families: Evidence for genetic susceptibility and risk prediction
title_fullStr Segregation analysis of 17,425 population-based breast cancer families: Evidence for genetic susceptibility and risk prediction
title_full_unstemmed Segregation analysis of 17,425 population-based breast cancer families: Evidence for genetic susceptibility and risk prediction
title_short Segregation analysis of 17,425 population-based breast cancer families: Evidence for genetic susceptibility and risk prediction
title_sort segregation analysis of 17,425 population-based breast cancer families: evidence for genetic susceptibility and risk prediction
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9606477/
https://www.ncbi.nlm.nih.gov/pubmed/36206742
http://dx.doi.org/10.1016/j.ajhg.2022.09.006
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