Variants classified as disease-causing are associated with both disease status and clinical severity, including a 21% increased risk (95% confidence interval 11-29%) of severe adverse outcomes by age 60 in patients with hypertrophic cardiomyopathy. Prasad, Sanjay K., Cook, Stuart A., Ware, James S., Walsh, Roddy.
CardioBoost obtains excellent accuracy (cardiomyopathies 90.2% arrhythmias 91.9%) for variants classified with >90% confidence, and increases the proportion of variants classified with high confidence more than twofold compared with existing tools. William, Wilk, Alicja, Whiffin, Nicola, Govind, Risha, Mazaika, Erica, de Marvao. RESULTS: CardioBoost has high global discrimination accuracy (precision recall area under the curve 0.91 for cardiomyopathies 0.96 for arrhythmias), outperforming existing tools (4-24% improvement). Roddy Walsh, Francesco Mazzarotto, Erica Mazaika, Euan Ashley, Michelle Michels. We assessed CardioBoost's ability to discriminate known pathogenic from benign variants, prioritize disease-associated variants, and stratify patient outcomes. Quantitative approaches to variant classification increase the yield and precision of genetic testing in Mendelian. METHODS: We developed a disease-specific variant classifier, CardioBoost, that estimates the probability of pathogenicity for rare missense variants in inherited cardiomyopathies and arrhythmias. We hypothesized that incorporating disease-specific information would improve tool performance. State-of-the-art machine learning variant prioritization tools are imprecise and ignore important parameters defining gene-disease relationships, e.g., distinct consequences of gain-of-function versus loss-of-function variants. PURPOSE: Accurate discrimination of benign and pathogenic rare variation remains a priority for clinical genome interpretation. Log in or sign up for Facebook to connect with friends, family and people you know. Join Facebook to connect with Erica Mazreka and others you may know. Disease-specific variant pathogenicity prediction significantly improves variant interpretation in inherited cardiac conditions. View the profiles of people named Erica Mazreka.
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