Bayesian approach to determining penetrance of pathogenic SDH variants.

Benn, DE; Zhu, Y; Andrews, KA; Wilding, M; Duncan, EL; Dwight, T; Tothill, RW; Burgess, J; Crook, A; Gill, AJ; Hicks, RJ; Kim, E; Luxford, C; Marfan, H; Richardson, AL; Robinson, B; Schlosberg, A; Susman, R; Tacon, L; Trainer, A; Tucker, K; Maher, ER; Field, M; Clifton-Bligh, RJ

Bayesian approach to determining penetrance of pathogenic SDH variants.

Benn, DE Zhu, Y Andrews, KA Wilding, M Duncan, EL Dwight, T Tothill, RW Burgess, J Crook, A

Gill, AJ Hicks, RJ Kim, E Luxford, C Marfan, H Richardson, AL Robinson, B Schlosberg, A Susman, R Tacon, L Trainer, A Tucker, K Maher, ER Field, M Clifton-Bligh, RJ

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Publisher:: BMJ PUBLISHING GROUP
Publication Type:: Journal Article
Citation:: J Med Genet, 2018, 55, (11), pp. 729-734
Issue Date:: 2018-11

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Field	Value	Language
dc.contributor.author	Benn, DE
dc.contributor.author	Zhu, Y
dc.contributor.author	Andrews, KA
dc.contributor.author	Wilding, M
dc.contributor.author	Duncan, EL
dc.contributor.author	Dwight, T
dc.contributor.author	Tothill, RW
dc.contributor.author	Burgess, J
dc.contributor.author	Crook, A https://orcid.org/0000-0001-5578-0460
dc.contributor.author	Gill, AJ
dc.contributor.author	Hicks, RJ
dc.contributor.author	Kim, E
dc.contributor.author	Luxford, C
dc.contributor.author	Marfan, H
dc.contributor.author	Richardson, AL
dc.contributor.author	Robinson, B
dc.contributor.author	Schlosberg, A
dc.contributor.author	Susman, R
dc.contributor.author	Tacon, L
dc.contributor.author	Trainer, A
dc.contributor.author	Tucker, K
dc.contributor.author	Maher, ER
dc.contributor.author	Field, M
dc.contributor.author	Clifton-Bligh, RJ
dc.date.accessioned	2022-10-29T00:55:42Z
dc.date.available	2018-08-20
dc.date.available	2022-10-29T00:55:42Z
dc.date.issued	2018-11
dc.identifier.citation	J Med Genet, 2018, 55, (11), pp. 729-734
dc.identifier.issn	0022-2593
dc.identifier.issn	1468-6244
dc.identifier.uri	http://hdl.handle.net/10453/162850
dc.description.abstract	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.
dc.format	Print-Electronic
dc.language	eng
dc.publisher	BMJ PUBLISHING GROUP
dc.relation.ispartof	J Med Genet
dc.relation.isbasedon	10.1136/jmedgenet-2018-105427
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	06 Biological Sciences, 11 Medical and Health Sciences
dc.subject.classification	Genetics & Heredity
dc.subject.mesh	Algorithms
dc.subject.mesh	Alleles
dc.subject.mesh	Australia
dc.subject.mesh	Bayes Theorem
dc.subject.mesh	Genetic Association Studies
dc.subject.mesh	Genetic Predisposition to Disease
dc.subject.mesh	Genetic Variation
dc.subject.mesh	Genotype
dc.subject.mesh	Humans
dc.subject.mesh	Isoenzymes
dc.subject.mesh	Models, Genetic
dc.subject.mesh	Penetrance
dc.subject.mesh	Phenotype
dc.subject.mesh	Succinate Dehydrogenase
dc.subject.mesh	United Kingdom
dc.subject.mesh	Humans
dc.subject.mesh	Genetic Predisposition to Disease
dc.subject.mesh	Succinate Dehydrogenase
dc.subject.mesh	Isoenzymes
dc.subject.mesh	Bayes Theorem
dc.subject.mesh	Genotype
dc.subject.mesh	Phenotype
dc.subject.mesh	Penetrance
dc.subject.mesh	Alleles
dc.subject.mesh	Algorithms
dc.subject.mesh	Models, Genetic
dc.subject.mesh	Australia
dc.subject.mesh	Genetic Variation
dc.subject.mesh	Genetic Association Studies
dc.subject.mesh	United Kingdom
dc.title	Bayesian approach to determining penetrance of pathogenic SDH variants.
dc.type	Journal Article
utslib.citation.volume	55
utslib.location.activity	England
utslib.for	06 Biological Sciences
utslib.for	11 Medical and Health Sciences
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Health
utslib.copyright.status	open_access	*
dc.date.updated	2022-10-29T00:55:39Z
pubs.issue	11
pubs.publication-status	Published
pubs.volume	55
utslib.citation.issue	11

Abstract:

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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http://hdl.handle.net/10453/162850