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Bayesian approach to determining penetrance of pathogenic SDH variants
by
Zhu, Ying
, Tothill, Richard W
, Field, Michael
, Benn, Diana E
, Dwight, Trisha
, Robinson, Bruce
, Richardson, Anne Louise
, Kim, Edward
, Wilding, Mathilda
, Gill, Anthony J
, Luxford, Catherine
, Andrews, Katrina A
, Tacon, Lyndal
, Tucker, Katherine
, Duncan, Emma L
, Schlosberg, Arran
, Burgess, John
, Crook, Ashley
, Marfan, Helen
, Susman, Rachel
, Hicks, Rodney J
, Trainer, Alison
, Clifton-Bligh, Roderick J
, Maher, Eamonn R
in
Algorithms
/ Alleles
/ Australia
/ Bayes Theorem
/ Bayesian analysis
/ Cancer
/ Cancer Genetics
/ Consortia
/ Dehydrogenases
/ Genes
/ Genetic Association Studies - methods
/ Genetic diversity
/ Genetic Predisposition to Disease
/ Genetic screening
/ Genetic Variation
/ Genetics
/ Genomes
/ Genomics
/ Genotype
/ Humans
/ Isoenzymes
/ Laboratories
/ Models, Genetic
/ Mutation
/ Neuroendocrine tumors
/ Paraganglioma
/ Penetrance
/ Phenotype
/ Pheochromocytoma
/ Population
/ Succinate dehydrogenase
/ Succinate Dehydrogenase - genetics
/ Tumors
/ United Kingdom
2018
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Bayesian approach to determining penetrance of pathogenic SDH variants
by
Zhu, Ying
, Tothill, Richard W
, Field, Michael
, Benn, Diana E
, Dwight, Trisha
, Robinson, Bruce
, Richardson, Anne Louise
, Kim, Edward
, Wilding, Mathilda
, Gill, Anthony J
, Luxford, Catherine
, Andrews, Katrina A
, Tacon, Lyndal
, Tucker, Katherine
, Duncan, Emma L
, Schlosberg, Arran
, Burgess, John
, Crook, Ashley
, Marfan, Helen
, Susman, Rachel
, Hicks, Rodney J
, Trainer, Alison
, Clifton-Bligh, Roderick J
, Maher, Eamonn R
in
Algorithms
/ Alleles
/ Australia
/ Bayes Theorem
/ Bayesian analysis
/ Cancer
/ Cancer Genetics
/ Consortia
/ Dehydrogenases
/ Genes
/ Genetic Association Studies - methods
/ Genetic diversity
/ Genetic Predisposition to Disease
/ Genetic screening
/ Genetic Variation
/ Genetics
/ Genomes
/ Genomics
/ Genotype
/ Humans
/ Isoenzymes
/ Laboratories
/ Models, Genetic
/ Mutation
/ Neuroendocrine tumors
/ Paraganglioma
/ Penetrance
/ Phenotype
/ Pheochromocytoma
/ Population
/ Succinate dehydrogenase
/ Succinate Dehydrogenase - genetics
/ Tumors
/ United Kingdom
2018
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Bayesian approach to determining penetrance of pathogenic SDH variants
by
Zhu, Ying
, Tothill, Richard W
, Field, Michael
, Benn, Diana E
, Dwight, Trisha
, Robinson, Bruce
, Richardson, Anne Louise
, Kim, Edward
, Wilding, Mathilda
, Gill, Anthony J
, Luxford, Catherine
, Andrews, Katrina A
, Tacon, Lyndal
, Tucker, Katherine
, Duncan, Emma L
, Schlosberg, Arran
, Burgess, John
, Crook, Ashley
, Marfan, Helen
, Susman, Rachel
, Hicks, Rodney J
, Trainer, Alison
, Clifton-Bligh, Roderick J
, Maher, Eamonn R
in
Algorithms
/ Alleles
/ Australia
/ Bayes Theorem
/ Bayesian analysis
/ Cancer
/ Cancer Genetics
/ Consortia
/ Dehydrogenases
/ Genes
/ Genetic Association Studies - methods
/ Genetic diversity
/ Genetic Predisposition to Disease
/ Genetic screening
/ Genetic Variation
/ Genetics
/ Genomes
/ Genomics
/ Genotype
/ Humans
/ Isoenzymes
/ Laboratories
/ Models, Genetic
/ Mutation
/ Neuroendocrine tumors
/ Paraganglioma
/ Penetrance
/ Phenotype
/ Pheochromocytoma
/ Population
/ Succinate dehydrogenase
/ Succinate Dehydrogenase - genetics
/ Tumors
/ United Kingdom
2018
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Bayesian approach to determining penetrance of pathogenic SDH variants
Journal Article
Bayesian approach to determining penetrance of pathogenic SDH variants
2018
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Overview
BackgroundUntil 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).MethodsTwo 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).ResultsPathogenic 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.ConclusionPathogenic 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.
Publisher
BMJ Publishing Group LTD,BMJ Publishing Group
Subject
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