BACKGROUND: Distinguishing genetic variants that cause disease from variants 
that are rare but benign is one of the principal challenges in contemporary 
clinical genetics, particularly as variants are identified at a pace exceeding 
the capacity of researchers to characterise them functionally.
METHODS: We previously developed a novel method, called paralogue annotation, 
which accurately and specifically identifies disease-causing missense variants 
by transferring disease-causing annotations across families of related proteins. 
Here we refine our approach, and apply it to novel variants found in 2266 
patients across two large cohorts with inherited sudden death syndromes, namely 
catecholaminergic polymorphic ventricular tachycardia (CPVT) or Brugada syndrome 
(BrS).
RESULTS: Over one third of the novel non-synonymous variants found in these 
studies, which would otherwise be reported in a clinical diagnostics setting as 
'variants of unknown significance', are categorised by our method as likely 
disease causing (positive predictive value 98.7%). This identified more than 500 
new disease loci for BrS and CPVT.
CONCLUSIONS: Our methodology is widely transferable across all human disease 
genes, with an estimated 150 000 potentially informative annotations in more 
than 1800 genes. We have developed a web resource that allows researchers and 
clinicians to annotate variants found in individuals with inherited arrhythmias, 
comprising a referenced compendium of known missense variants in these genes 
together with a user-friendly implementation of our approach. This tool will 
facilitate the interpretation of many novel variants that might otherwise remain 
unclassified.