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J Med Genet. 2018 Nov;55(11):729-734. doi: 10.1136/jmedgenet-2018-105427. Epub 2018 Sep 10.

Bayesian approach to determining penetrance of pathogenic SDH variants.

Author information

1
Hormones and Cancer, Cancer Genetics Laboratory, Kolling Institute, Royal North Shore Hospital, St Leonards, New South Wales, Australia.
2
Department of Medicine, University of Sydney, Sydney, New South Wales, Australia.
3
Department of Cancer Services, Northern Sydney Local Health District Familial Cancer Service, Royal North Shore Hospital, Saint Leonards, New South Wales, Australia.
4
Department of Medical Genetics, University of Cambridge and NIHR Cambridge Biomedical Research Centre and Cancer Research UK Cambridge Centre and Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, UK.
5
School of Biomedical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia.
6
Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia.
7
Department of Endocrinology, Royal Brisbane and Women's Hospital, Brisbane, Queensland, Australia.
8
Department of Oncology, The Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia.
9
Sir Peter MacCallum Department of Oncology, University of Melbourne, Parkville, Victoria, Australia.
10
Faculty of Medicine, University of Tasmania, Hobart, Tasmania, Australia.
11
Cancer Diagnosis and Pathology Group, Kolling Institute of Medical Research, Royal North Shore Hospital, St Leonards, New South Wales, Australia.
12
Genetic Health Queensland, Royal Brisbane and Women's Hospital, Brisbane, Queensland, Australia.
13
Department of Endocrinology, Royal North Shore Hospital, St Leonards, New South Wales, USA.
14
Department of Clinical Genetics, Prince of Wales Hospital, Randwick, New South Wales, Australia.

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.

KEYWORDS:

paraganglioma; pathogenic variant; penetrance; pheochromocytoma; succinate dehydrogenase

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