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Bayesian approach to determining penetrance of pathogenic SDH variants.

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.

SUBMITTER: Benn DE

PROVIDER: S-EPMC6252366 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

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Bayesian approach to determining penetrance of pathogenic SDH variants.

Benn Diana E DE Zhu Ying Y Andrews Katrina A KA Wilding Mathilda M Duncan Emma L EL Dwight Trisha T Tothill Richard W RW Burgess John J Crook Ashley A Gill Anthony J AJ Hicks Rodney J RJ Kim Edward E Luxford Catherine C Marfan Helen H Richardson Anne Louise AL Robinson Bruce B Schlosberg Arran A Susman Rachel R Tacon Lyndal L Trainer Alison A Tucker Katherine K Maher Eamonn R ER Field Michael M Clifton-Bligh Roderick J RJ

Journal of medical genetics 20180910 11

<h4>Background</h4>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 (<i>SDHA-C</i>) genetic variants associated with hereditary pheoch ...[more]

PMID: 30201732

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Project description:ObjectiveAutism, schizophrenia, and other clinically distinct neurodevelopmental psychiatric disorders (NPDs) have shared genetic etiologies, including single-gene and multigenic copy number variants (CNVs). Because rare variants are primarily investigated in clinical cohorts, population-based estimates of their prevalence and penetrance are lacking. The authors determined the prevalence, penetrance, and NPD risk of pathogenic single-gene variants in a large health care system population.MethodsThe authors analyzed linked genomic and electronic health record (EHR) data in a subset of 90,595 participants from Geisinger's MyCode Community Health Initiative, known as the DiscovEHR cohort. Loss-of-function pathogenic variants in 94 high-confidence NPD genes were identified through exome sequencing, and NPD penetrance was calculated using preselected EHR diagnosis codes. NPD risk was estimated using a case-control comparison of DiscovEHR participants with and without NPD diagnoses. Results from single-gene variant analyses were also compared with those from 31 previously reported pathogenic NPD CNVs.ResultsPathogenic variants were identified in 0.34% of the DiscovEHR cohort and demonstrated a 34.3% penetrance for NPDs. Similar to CNVs, sequence variants collectively conferred a substantial risk for several NPD diagnoses, including autism, schizophrenia, and bipolar disorder. Significant NPD risk remained after participants with intellectual disability were excluded from the analysis, confirming the association with major psychiatric disorders in individuals without severe cognitive deficits.ConclusionsCollectively, rare single-gene variants and CNVs were found in >1% of individuals in a large health care system population and play an important contributory role in mental health disorders. Diagnostic genetic testing for pathogenic variants among symptomatic individuals with NPDs could improve clinical outcomes through early intervention and anticipatory therapeutic support.

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Bayesian approach to determining penetrance of pathogenic SDH variants.

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Bayesian approach to determining penetrance of pathogenic SDH variants.

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