Quantitative approaches to variant classification increase the yield and precision of genetic testing in Mendelian diseases: the case of hypertrophic cardiomyopathy

Abstract

BackgroundInternational 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. Genetic testing is also more likely informative in individuals with well-characterised variants from extensively studied European-ancestry populations. Inherited cardiomyopathies are relatively common Mendelian diseases that allow empirical calibration and assessment of this framework.MethodsWe 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). We analysed the distribution of variants using a bespoke unsupervised clustering algorithm to identify gene regions in which variants are significantly clustered in cases.ResultsAnalysis 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. Non-truncating variant classes with an EF ≥ 0.95 were identified in five established HCM genes. Applying this approach leads to an estimated 14–20% increase in cases with actionable HCM variants, i.e. variants classified as pathogenic/likely pathogenic that might be used for predictive testing in probands’ relatives.ConclusionsWhen 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. This could increase the yield of high confidence actionable variants, consistent with the framework and recommendations of current guidelines. The techniques outlined offer a consistent and unbiased approach to variant interpretation for Mendelian disease genetic testing. We propose adaptations to ACMG/AMP guidelines to incorporate such evidence in a quantitative and transparent manner.Electronic supplementary materialThe online version of this article (10.1186/s13073-019-0616-z) contains supplementary material, which is available to authorized users.

FLNC pathogenic variants in patients with cardiomyopathies: Prevalence and genotype‐phenotype correlations

“…However, the implication of missense variants in HCM is questioned and need to be confirmed. Mainly, two publications did not detect significant excess of rare missense variants between HCM cases and controls . One limitation discussed by Walsh et al is an insufficient size of the cohort .…”

“…20,21 One limitation discussed by Walsh et al is an insufficient size of the cohort. 21 concluded to a haploinsufficiency model. 4 Similarly, in myopathies, the haploinsufficiency mechanism and the mRNA decay activation have been confirmed on fish model.…”

“…Mainly, two publications did not detect significant excess of rare missense variants between HCM cases and controls . One limitation discussed by Walsh et al is an insufficient size of the cohort . Additionally, in the publication of Cui et al, at least three differences could be noticed: (a) the ethnic origin of the cohort, (b) the threshold of variant frequency and (c) the fact that 33% of their patients were carriers of a second mutation in a major gene which could induce a bias in the expression of the disease …”

“…Mainly, two publications did not detect significant excess of rare missense variants between HCM cases and controls. 20,21 One limitation discussed by Walsh et al is an insufficient size of the cohort. 21 concluded to a haploinsufficiency model.…”

Deletions of specific exons of FHOD3 detected by next‐generation sequencing are associated with hypertrophic cardiomyopathy

“…Massive parallel sequencing has contributed to the understanding of the disease, allowing the sequencing of a large number of genes in a short time at a sustainable cost. However, the diagnostic yield of genetic studies in HCM is around 50% 1 . New strategies to increase the yield of genetic testing include the sequencing of deep intronic variants, screening for copy‐number variations (CNVs) in disease‐causing genes, and sequencing of a broader range of candidate genes.…”