期刊
GENETICS IN MEDICINE
卷 19, 期 10, 页码 1151-1158出版社
NATURE PUBLISHING GROUP
DOI: 10.1038/gim.2017.26
关键词
allele frequency; clinical genomics; ExAC; inherited cardiovascular conditions; variant interpretation
资金
- Wellcome Trust [107469/Z/15/Z]
- Medical Research Council (UK)
- NIHR Biomedical Research Unit in Cardiovascular Disease at Royal Brompton & Harefield NHS Foundation Trust
- Imperial College London
- Fondation Leducq [11 CVD-01]
- Department of Health, UK [HICF-R6-373]
- National Institute of Diabetes and Digestive and Kidney Diseases
- National Institute of General Medical Sciences of the NIH [U54DK105566, R01GM104371]
- National Institutes of Health under Ruth L. Kirschstein National Research Service Award (NRSA) NIH Individual Predoctoral Fellowship [AI122592-01A1]
- National Institutes of Health under Ruth L. Kirschstein National Research Service Award [4T32GM007748]
- Department of Health
- Wellcome Trust
- Health Innovation Challenge Fund award from Wellcome Trust
- British Heart Foundation [FS/15/81/31817, SP/10/10/28431] Funding Source: researchfish
- Medical Research Council [MC_UP_1102/20, MC_U120085815] Funding Source: researchfish
- Wellcome Trust [107469/Z/15/Z] Funding Source: researchfish
- MRC [MC_UP_1102/20, MC_U120085815] Funding Source: UKRI
Purpose: Whole-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. Methods: We 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. Results: Using 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). Conclusion: We 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.
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