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Bayesian approach to determining penetrance of pathogenic SDH variants
BACKGROUND: Until recently, determining penetrance required large observational cohort studies. Data from the Exome Aggregate Consortium (ExAC) allows a Bayesian approach to calculate penetrance, in that population frequencies of pathogenic germline variants should be inversely proportional to their...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6252366/ https://www.ncbi.nlm.nih.gov/pubmed/30201732 http://dx.doi.org/10.1136/jmedgenet-2018-105427 |
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author | Benn, Diana E Zhu, Ying Andrews, Katrina A Wilding, Mathilda Duncan, Emma L Dwight, Trisha Tothill, Richard W Burgess, John Crook, Ashley Gill, Anthony J Hicks, Rodney J Kim, Edward Luxford, Catherine Marfan, Helen Richardson, Anne Louise Robinson, Bruce Schlosberg, Arran Susman, Rachel Tacon, Lyndal Trainer, Alison Tucker, Katherine Maher, Eamonn R Field, Michael Clifton-Bligh, Roderick J |
author_facet | Benn, Diana E Zhu, Ying Andrews, Katrina A Wilding, Mathilda Duncan, Emma L Dwight, Trisha Tothill, Richard W Burgess, John Crook, Ashley Gill, Anthony J Hicks, Rodney J Kim, Edward Luxford, Catherine Marfan, Helen Richardson, Anne Louise Robinson, Bruce Schlosberg, Arran Susman, Rachel Tacon, Lyndal Trainer, Alison Tucker, Katherine Maher, Eamonn R Field, Michael Clifton-Bligh, Roderick J |
author_sort | Benn, Diana E |
collection | PubMed |
description | BACKGROUND: Until recently, determining penetrance required large observational cohort studies. Data from the Exome Aggregate Consortium (ExAC) allows a Bayesian approach to calculate penetrance, in that population frequencies of pathogenic germline variants should be inversely proportional to their penetrance for disease. We tested this hypothesis using data from two cohorts for succinate dehydrogenase subunits A, B and C (SDHA–C) genetic variants associated with hereditary pheochromocytoma/paraganglioma (PC/PGL). METHODS: Two cohorts were 575 unrelated Australian subjects and 1240 unrelated UK subjects, respectively, with PC/PGL in whom genetic testing had been performed. Penetrance of pathogenic SDHA–C variants was calculated by comparing allelic frequencies in cases versus controls from ExAC (removing those variants contributed by The Cancer Genome Atlas). RESULTS: Pathogenic SDHA–C variants were identified in 106 subjects (18.4%) in cohort 1 and 317 subjects (25.6%) in cohort 2. Of 94 different pathogenic variants from both cohorts (seven in SDHA, 75 in SDHB and 12 in SDHC), 13 are reported in ExAC (two in SDHA, nine in SDHB and two in SDHC) accounting for 21% of subjects with SDHA–C variants. Combining data from both cohorts, estimated lifetime disease penetrance was 22.0% (95% CI 15.2% to 30.9%) for SDHB variants, 8.3% (95% CI 3.5% to 18.5%) for SDHC variants and 1.7% (95% CI 0.8% to 3.8%) for SDHA variants. CONCLUSION: Pathogenic variants in SDHB are more penetrant than those in SDHC and SDHA. Our findings have important implications for counselling and surveillance of subjects carrying these pathogenic variants. |
format | Online Article Text |
id | pubmed-6252366 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-62523662018-12-10 Bayesian approach to determining penetrance of pathogenic SDH variants Benn, Diana E Zhu, Ying Andrews, Katrina A Wilding, Mathilda Duncan, Emma L Dwight, Trisha Tothill, Richard W Burgess, John Crook, Ashley Gill, Anthony J Hicks, Rodney J Kim, Edward Luxford, Catherine Marfan, Helen Richardson, Anne Louise Robinson, Bruce Schlosberg, Arran Susman, Rachel Tacon, Lyndal Trainer, Alison Tucker, Katherine Maher, Eamonn R Field, Michael Clifton-Bligh, Roderick J J Med Genet Cancer Genetics BACKGROUND: Until recently, determining penetrance required large observational cohort studies. Data from the Exome Aggregate Consortium (ExAC) allows a Bayesian approach to calculate penetrance, in that population frequencies of pathogenic germline variants should be inversely proportional to their penetrance for disease. We tested this hypothesis using data from two cohorts for succinate dehydrogenase subunits A, B and C (SDHA–C) genetic variants associated with hereditary pheochromocytoma/paraganglioma (PC/PGL). METHODS: Two cohorts were 575 unrelated Australian subjects and 1240 unrelated UK subjects, respectively, with PC/PGL in whom genetic testing had been performed. Penetrance of pathogenic SDHA–C variants was calculated by comparing allelic frequencies in cases versus controls from ExAC (removing those variants contributed by The Cancer Genome Atlas). RESULTS: Pathogenic SDHA–C variants were identified in 106 subjects (18.4%) in cohort 1 and 317 subjects (25.6%) in cohort 2. Of 94 different pathogenic variants from both cohorts (seven in SDHA, 75 in SDHB and 12 in SDHC), 13 are reported in ExAC (two in SDHA, nine in SDHB and two in SDHC) accounting for 21% of subjects with SDHA–C variants. Combining data from both cohorts, estimated lifetime disease penetrance was 22.0% (95% CI 15.2% to 30.9%) for SDHB variants, 8.3% (95% CI 3.5% to 18.5%) for SDHC variants and 1.7% (95% CI 0.8% to 3.8%) for SDHA variants. CONCLUSION: Pathogenic variants in SDHB are more penetrant than those in SDHC and SDHA. Our findings have important implications for counselling and surveillance of subjects carrying these pathogenic variants. BMJ Publishing Group 2018-11 2018-09-10 /pmc/articles/PMC6252366/ /pubmed/30201732 http://dx.doi.org/10.1136/jmedgenet-2018-105427 Text en © Author(s) (or their employer(s)) 2018. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/. |
spellingShingle | Cancer Genetics Benn, Diana E Zhu, Ying Andrews, Katrina A Wilding, Mathilda Duncan, Emma L Dwight, Trisha Tothill, Richard W Burgess, John Crook, Ashley Gill, Anthony J Hicks, Rodney J Kim, Edward Luxford, Catherine Marfan, Helen Richardson, Anne Louise Robinson, Bruce Schlosberg, Arran Susman, Rachel Tacon, Lyndal Trainer, Alison Tucker, Katherine Maher, Eamonn R Field, Michael Clifton-Bligh, Roderick J Bayesian approach to determining penetrance of pathogenic SDH variants |
title | Bayesian approach to determining penetrance of pathogenic SDH variants |
title_full | Bayesian approach to determining penetrance of pathogenic SDH variants |
title_fullStr | Bayesian approach to determining penetrance of pathogenic SDH variants |
title_full_unstemmed | Bayesian approach to determining penetrance of pathogenic SDH variants |
title_short | Bayesian approach to determining penetrance of pathogenic SDH variants |
title_sort | bayesian approach to determining penetrance of pathogenic sdh variants |
topic | Cancer Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6252366/ https://www.ncbi.nlm.nih.gov/pubmed/30201732 http://dx.doi.org/10.1136/jmedgenet-2018-105427 |
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