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.