Arrhythmogenic cardiomyopathy (ACM) is an inherited cardiac disease characterized by myocardial atrophy, fibro-fatty replacement, and a high risk of ventricular arrhythmias that lead to sudden death. In 2009, genetic data from 57 publications were collected in the arrhythmogenic right ventricular dysplasia/cardiomyopathy (ARVD/C) Genetic Variants Database (freeware available at http://www.arvcdatabase.info), which comprised 481 variants in eight ACM-associated genes. In recent years, deep genetic sequencing has increased our knowledge of the genetics of ACM, revealing a large spectrum of nucleotide variations for which pathogenicity needs to be assessed. As of April 20, 2014, we have updated the ARVD/C database into the ARVD/C database to contain more than 1,400 variants in 12 ACM-related genes (PKP2, DSP, DSC2, DSG2, JUP, TGFB3, TMEM43, LMNA, DES, TTN, PLN, CTNNA3) as reported in more than 160 references. Of these, only 411 nucleotide variants have been reported as pathogenic, whereas the significance of the other approximately 1,000 variants is still unknown. This comprehensive collection of ACM genetic data represents a valuable source of information on the spectrum of ACM-associated genes and aims to facilitate the interpretation of genetic data and genetic counseling.

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Exome sequencing is now mainstream in clinical practice. However, identification of pathogenic Mendelian variants remains time-consuming, in part, because the limited accuracy of current computational prediction methods requires manual classification by experts. Here we introduce CAPICE, a new machine-learning-based method for prioritizing pathogenic variants, including SNVs and short InDels. CAPICE outperforms the best general (CADD, GAVIN) and consequence-type-specific (REVEL, ClinPred) computational prediction methods, for both rare and ultra-rare variants. CAPICE is easily added to diagnostic pipelines as pre-computed score file or command-line software, or using online MOLGENIS web service with API. Download CAPICE for free and open-source (LGPLv3) at https://github.com/molgenis/ capice.