Person:

Funke, Birgit

Purpose: The accurate interpretation of variation in Mendelian disease genes has lagged behind data generation as sequencing has become increasingly accessible. Ongoing large sequencing efforts present huge interpretive challenges, but they also provide an invaluable opportunity to characterize the spectrum and importance of rare variation. Methods: We analyzed sequence data from 7,855 clinical cardiomyopathy cases and 60,706 Exome Aggregation Consortium (ExAC) reference samples to obtain a better understanding of genetic variation in a representative autosomal dominant disorder. Results: We found that in some genes previously reported as important causes of a given cardiomyopathy, rare variation is not clinically informative because there is an unacceptably high likelihood of false-positive interpretation. By contrast, in other genes, we find that diagnostic laboratories may be overly conservative when assessing variant pathogenicity. Conclusions: We outline improved analytical approaches that evaluate which genes and variant classes are interpretable and propose that these will increase the clinical utility of testing across a range of Mendelian diseases. Genet Med 19 2, 192–203.

Purpose Integrating genomic sequencing in clinical care requires standardization of variant interpretation practices. The Clinical Genome Resource has established expert panels to adapt the American College of Medical Genetics and Genomics/Association for Molecular Pathology classification framework for specific genes and diseases. The Cardiomyopathy Expert Panel selected MYH7, a key contributor to inherited cardiomyopathies, as a pilot gene to develop a broadly applicable approach. Methods: Expert revisions were tested with 60 variants using a structured double review by pairs of clinical and diagnostic laboratory experts. Final consensus rules were established via iterative discussions. Results: Adjustments represented disease-/gene-informed specifications (12) or strength adjustments of existing rules (5). Nine rules were deemed not applicable. Key specifications included quantitative frameworks for minor allele frequency thresholds, the use of segregation data, and a semiquantitative approach to counting multiple independent variant occurrences where fully controlled case-control studies are lacking. Initial inter-expert classification concordance was 93%. Internal data from participating diagnostic laboratories changed the classification of 20% of the variants (n = 12), highlighting the critical importance of data sharing. Conclusion: These adapted rules provide increased specificity for use in MYH7-associated disorders in combination with expert review and clinical judgment and serve as a stepping stone for genes and disorders with similar genetic and clinical characteristics.

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.

Abstract Aim Hypertrophic cardiomyopathy (HCM) exhibits genetic heterogeneity that is dominated by variation in eight sarcomeric genes. Genetic variation in a large number of non-sarcomeric genes has also been implicated in HCM but not formally assessed. Here we used very large case and control cohorts to determine the extent to which variation in non-sarcomeric genes contributes to HCM. Methods and results We sequenced known and putative HCM genes in a new large prospective HCM cohort (n = 804) and analysed data alongside the largest published series of clinically genotyped HCM patients (n = 6179), previously published HCM cohorts and reference population samples from the exome aggregation consortium (ExAC, n = 60 706) to assess variation in 31 genes implicated in HCM. We found no significant excess of rare (minor allele frequency < 1:10 000 in ExAC) protein-altering variants over controls for most genes tested and conclude that novel variants in these genes are rarely interpretable, even for genes with previous evidence of co-segregation (e.g. ACTN2). To provide an aid for variant interpretation, we integrated HCM gene sequence data with aggregated pedigree and functional data and suggest a means of assessing gene pathogenicity in HCM using this evidence. Conclusion: We show that genetic variation in the majority of non-sarcomeric genes implicated in HCM is not associated with the condition, reinforce the fact that the sarcomeric gene variation is the primary cause of HCM known to date and underscore that the aetiology of HCM is unknown in the majority of patients.