Year: 2017
Type: article
Abstract: PurposeWhole-exome and whole-genome sequencing have transformed the discovery of genetic variants that cause human Mendelian disease, but discriminating pathogenic from benign variants remains a daunting challenge. Rarity is recognized as a necessary, although not sufficient, criterion for pathogenicity, but frequency cutoffs used in Mendelian analysis are often arbitrary and overly lenient. Recent very large reference datasets, such as the Exome Aggregation Consortium (ExAC), provide an unprecedented opportunity to obtain robust frequency estimates even for very rare variants.MethodsWe present a statistical framework for the frequency-based filtering of candidate disease-causing variants, accounting for disease prevalence, genetic and allelic heterogeneity, inheritance mode, penetrance, and sampling variance in reference datasets.ResultsUsing the example of cardiomyopathy, we show that our approach reduces by two-thirds the number of candidate variants under consideration in the average exome, without removing true pathogenic variants (false-positive rate<0.001).ConclusionWe outline a statistically robust framework for assessing whether a variant is "too common" to be causative for a Mendelian disorder of interest. We present precomputed allele frequency cutoffs for all variants in the ExAC dataset.
Source: Genetics in Medicine
DOI: 10.1038/gim.2017.26
Institutions: Harefield Hospital, Royal Brompton Hospital, NIHR Royal Brompton Cardiovascular Biomedical Research Unit, Imperial College London, Broad Institute, Massachusetts General Hospital, Harvard University, National University of Singapore, Duke-NUS Medical School, National Heart Centre Singapore, MRC London Institute of Medical Sciences
Language: English
Topic: Genomics and Rare Diseases
Subfield: Genetics
Domain: Life Sciences
Open Access status: hybrid
Estimated APC paid: $4,132
Funders: Wellcome Trust, National Institute for Health and Care Research, British Heart Foundation, Imperial College London, Fondation Leducq, National Institutes of Health, Medical Research Council, National Institute of General Medical Sciences, National Institute of Allergy and Infectious Diseases, National Institute of Diabetes and Digestive and Kidney Diseases
Awards: G1209099612, Genetic determinants of aortic morphology and function, G2058173175, Next generation sequencing of inherited cardiac conditions, G2512866349, G3759812594, Genomic dissection of inherited cardiomyopathies: identifying alleles, genes and mechanisms, for patient stratification., Genomic, epigenomic and systems dissection of mechanisms underlying dilated cardiomyopathy, G6868616705, Comprehensive molecular diagnostics for inherited cardiac disease, G849084591, Genomic dissection of inherited cardiomyopathies: identifying alleles, genes and mechanisms, for patient stratification., G9000096738, G9000172847, G9000254147, Comprehensive molecular diagnostics for inherited cardiac disease, Training Grant in Genetics
OpenAlex ID: W2952445740