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Complex Segregation Analysis of Pedigrees from the Gilda Radner Familial Ovarian Cancer Registry Reveals Evidence for Mendelian Dominant Inheritance
BACKGROUND: Familial component is estimated to account for about 10% of ovarian cancer. However, the mode of inheritance of ovarian cancer remains poorly understood. The goal of this study was to investigate the inheritance model that best fits the observed transmission pattern of ovarian cancer amo...
Autores principales: | , , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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Public Library of Science
2009
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2694280/ https://www.ncbi.nlm.nih.gov/pubmed/19536330 http://dx.doi.org/10.1371/journal.pone.0005939 |
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author | Tayo, Bamidele O. DiCioccio, Richard A. Liang, Yulan Trevisan, Maurizio Cooper, Richard S. Lele, Shashikant Sucheston, Lara Piver, Steven M. Odunsi, Kunle |
author_facet | Tayo, Bamidele O. DiCioccio, Richard A. Liang, Yulan Trevisan, Maurizio Cooper, Richard S. Lele, Shashikant Sucheston, Lara Piver, Steven M. Odunsi, Kunle |
author_sort | Tayo, Bamidele O. |
collection | PubMed |
description | BACKGROUND: Familial component is estimated to account for about 10% of ovarian cancer. However, the mode of inheritance of ovarian cancer remains poorly understood. The goal of this study was to investigate the inheritance model that best fits the observed transmission pattern of ovarian cancer among 7669 members of 1919 pedigrees ascertained through probands from the Gilda Radner Familial Ovarian Cancer Registry at Roswell Park Cancer Institute, Buffalo, New York. METHODOLOGY/PRINCIPAL FINDINGS: Using the Statistical Analysis for Genetic Epidemiology program, we carried out complex segregation analyses of ovarian cancer affection status by fitting different genetic hypothesis-based regressive multivariate logistic models. We evaluated the likelihood of sporadic, major gene, environmental, general, and six types of Mendelian models. Under each hypothesized model, we also estimated the susceptibility allele frequency, transmission probabilities for the susceptibility allele, baseline susceptibility and estimates of familial association. Comparisons between models were carried out using either maximum likelihood ratio test in the case of hierarchical models, or Akaike information criterion for non-nested models. When assessed against sporadic model without familial association, the model with both parent-offspring and sib-sib residual association could not be rejected. Likewise, the Mendelian dominant model that included familial residual association provided the best-fitting for the inheritance of ovarian cancer. The estimated disease allele frequency in the dominant model was 0.21. CONCLUSIONS/SIGNIFICANCE: This report provides support for a genetic role in susceptibility to ovarian cancer with a major autosomal dominant component. This model does not preclude the possibility of polygenic inheritance of combined effects of multiple low penetrance susceptibility alleles segregating dominantly. |
format | Text |
id | pubmed-2694280 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-26942802009-06-16 Complex Segregation Analysis of Pedigrees from the Gilda Radner Familial Ovarian Cancer Registry Reveals Evidence for Mendelian Dominant Inheritance Tayo, Bamidele O. DiCioccio, Richard A. Liang, Yulan Trevisan, Maurizio Cooper, Richard S. Lele, Shashikant Sucheston, Lara Piver, Steven M. Odunsi, Kunle PLoS One Research Article BACKGROUND: Familial component is estimated to account for about 10% of ovarian cancer. However, the mode of inheritance of ovarian cancer remains poorly understood. The goal of this study was to investigate the inheritance model that best fits the observed transmission pattern of ovarian cancer among 7669 members of 1919 pedigrees ascertained through probands from the Gilda Radner Familial Ovarian Cancer Registry at Roswell Park Cancer Institute, Buffalo, New York. METHODOLOGY/PRINCIPAL FINDINGS: Using the Statistical Analysis for Genetic Epidemiology program, we carried out complex segregation analyses of ovarian cancer affection status by fitting different genetic hypothesis-based regressive multivariate logistic models. We evaluated the likelihood of sporadic, major gene, environmental, general, and six types of Mendelian models. Under each hypothesized model, we also estimated the susceptibility allele frequency, transmission probabilities for the susceptibility allele, baseline susceptibility and estimates of familial association. Comparisons between models were carried out using either maximum likelihood ratio test in the case of hierarchical models, or Akaike information criterion for non-nested models. When assessed against sporadic model without familial association, the model with both parent-offspring and sib-sib residual association could not be rejected. Likewise, the Mendelian dominant model that included familial residual association provided the best-fitting for the inheritance of ovarian cancer. The estimated disease allele frequency in the dominant model was 0.21. CONCLUSIONS/SIGNIFICANCE: This report provides support for a genetic role in susceptibility to ovarian cancer with a major autosomal dominant component. This model does not preclude the possibility of polygenic inheritance of combined effects of multiple low penetrance susceptibility alleles segregating dominantly. Public Library of Science 2009-06-17 /pmc/articles/PMC2694280/ /pubmed/19536330 http://dx.doi.org/10.1371/journal.pone.0005939 Text en Tayo et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Tayo, Bamidele O. DiCioccio, Richard A. Liang, Yulan Trevisan, Maurizio Cooper, Richard S. Lele, Shashikant Sucheston, Lara Piver, Steven M. Odunsi, Kunle Complex Segregation Analysis of Pedigrees from the Gilda Radner Familial Ovarian Cancer Registry Reveals Evidence for Mendelian Dominant Inheritance |
title | Complex Segregation Analysis of Pedigrees from the Gilda Radner Familial Ovarian Cancer Registry Reveals Evidence for Mendelian Dominant Inheritance |
title_full | Complex Segregation Analysis of Pedigrees from the Gilda Radner Familial Ovarian Cancer Registry Reveals Evidence for Mendelian Dominant Inheritance |
title_fullStr | Complex Segregation Analysis of Pedigrees from the Gilda Radner Familial Ovarian Cancer Registry Reveals Evidence for Mendelian Dominant Inheritance |
title_full_unstemmed | Complex Segregation Analysis of Pedigrees from the Gilda Radner Familial Ovarian Cancer Registry Reveals Evidence for Mendelian Dominant Inheritance |
title_short | Complex Segregation Analysis of Pedigrees from the Gilda Radner Familial Ovarian Cancer Registry Reveals Evidence for Mendelian Dominant Inheritance |
title_sort | complex segregation analysis of pedigrees from the gilda radner familial ovarian cancer registry reveals evidence for mendelian dominant inheritance |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2694280/ https://www.ncbi.nlm.nih.gov/pubmed/19536330 http://dx.doi.org/10.1371/journal.pone.0005939 |
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