![]() ![]() These were in part prompted by the plethora of erroneous variant-disease associations in the research literature and the increasing realisation that individually rare variants are collectively common for many genes, as highlighted by population datasets such as the Exome Aggregation Consortium (ExAC). In an effort to standardise variant assessment in clinical settings, guidelines from the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) were produced in 2015 and have now been widely adopted. ![]() We propose adaptations to ACMG/AMP guidelines to incorporate such evidence in a quantitative and transparent manner.Īdvances in sequencing technology have dramatically expanded the scope for genetic testing in rare Mendelian diseases, but have exposed variant interpretation as a key limiting factor for clinical application. The techniques outlined offer a consistent and unbiased approach to variant interpretation for Mendelian disease genetic testing. This could increase the yield of high confidence actionable variants, consistent with the framework and recommendations of current guidelines. When found in a patient confirmed to have disease, novel variants in some genes and regions are empirically shown to have a sufficiently high probability of pathogenicity to support a “likely pathogenic” classification, even without additional segregation or functional data. variants classified as pathogenic/likely pathogenic that might be used for predictive testing in probands’ relatives. Applying this approach leads to an estimated 14–20% increase in cases with actionable HCM variants, i.e. Non-truncating variant classes with an EF ≥ 0.95 were identified in five established HCM genes. ResultsĪnalysis of variant distribution identified regions in which variants are significantly enriched in cases and variant location was a better discriminator of pathogenicity than generic computational functional prediction algorithms. ![]() We analysed the distribution of variants using a bespoke unsupervised clustering algorithm to identify gene regions in which variants are significantly clustered in cases. We compared rare variants in large hypertrophic cardiomyopathy (HCM) cohorts (up to 6179 cases) to reference populations to identify variant classes with high prior likelihoods of pathogenicity, as defined by etiological fraction (EF). Inherited cardiomyopathies are relatively common Mendelian diseases that allow empirical calibration and assessment of this framework. Genetic testing is also more likely informative in individuals with well-characterised variants from extensively studied European-ancestry populations. International guidelines for variant interpretation in Mendelian disease set stringent criteria to report a variant as (likely) pathogenic, prioritising control of false-positive rate over test sensitivity and diagnostic yield. ![]()
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