Quantitative approaches to variant classification increase the yield and precision of genetic testing in Mendelian diseases: The case of hypertrophic cardiomyopathy
Walsh R., Mazzarotto F., Whiffin N., Buchan R., Midwinter W., Wilk A., Li N., Felkin L., Ingold N., Govind R., Ahmad M., Mazaika E., Allouba M., Zhang X., Marvao AD., Day SM., Ashley E., Colan SD., Michels M., Pereira AC., Jacoby D., Ho CY., Thomson KL., Watkins H., Barton PJR., Olivotto I., Cook SA., Ware JS.
<jats:title>ABSTRACT</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>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. 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.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>We compared rare variants in large hypertrophic cardiomyopathy (HCM) cohorts to reference populations to identify variant classes with high prior likelihoods of pathogenicity, as defined by etiological fraction (EF). Analysis 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, and therefore clinically actionable, were identified in 5 established HCM genes. Applying this approach leads to an estimated 14-20% increase in cases with actionable HCM variants.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>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. 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, unbiased and equitable 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.</jats:p></jats:sec>