Extending the Coding-variant Allelic Series Test to Summary Statistics

The coding-variant allelic series test (COAST) was introduced to identify genes harboring rare variant allelic series. Specifically, COAST targets genes where a dose-response relationship exists between mutational severity and phenotypic impact. Such genes are of therapeutic interest because the effect of pharmacological modulation can be predicted from the natural variation present in a population. The original COAST required access to individual-level data. However, such data are often unavailable due to privacy concerns or logistical challenges. Meanwhile, single-variant summary statistics of the type produced by genome-wide association studies are plentiful. Here we introduce COAST-SS, an extension of COAST that accepts summary statistics as input, namely the per-variant effect sizes and standard errors, along with estimates of the minor allele frequency and local linkage disequilibrium (LD). As a running example, we consider identifying allelic series for circulating lipid traits in the UK Biobank. Through extensive analyses of real and simulated data, we demonstrate that COAST-SS provides p-values effectively equivalent to those from the original COAST. Interestingly, we find that when LD is low, as is expected among rare variants, COAST-SS is robust to misspecification of the LD matrix, providing valid inference even when the LD matrix is set to the identity. We explore several strategies for annotating the pathogenicity of variants supplied to COAST-SS, finding that they often yield similar power for detecting associations. Lastly, we employ COAST-SS to screen for lipid trait allelic series in an expanded cohort of 350K subjects. COAST-SS has been incorporated into the publicly available AllelicSeries R package.