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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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2018
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.
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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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