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A general framework for estimating the relative pathogenicity of human genetic variants

Abstract

Current methods for annotating and interpreting human genetic variation tend to exploit a single information type (for example, conservation) and/or are restricted in scope (for example, to missense changes). Here we describe Combined Annotation–Dependent Depletion (CADD), a method for objectively integrating many diverse annotations into a single measure (C score) for each variant. We implement CADD as a support vector machine trained to differentiate 14.7 million high-frequency human-derived alleles from 14.7 million simulated variants. We precompute C scores for all 8.6 billion possible human single-nucleotide variants and enable scoring of short insertions-deletions. C scores correlate with allelic diversity, annotations of functionality, pathogenicity, disease severity, experimentally measured regulatory effects and complex trait associations, and they highly rank known pathogenic variants within individual genomes. The ability of CADD to prioritize functional, deleterious and pathogenic variants across many functional categories, effect sizes and genetic architectures is unmatched by any current single-annotation method.

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Figure 1: Relationship of scaled C scores and categorical variant consequences.
Figure 2: Relationship between scaled C scores and genetic variation.
Figure 3: Sensitivity of methods in distinguishing pathogenic and benign variants.
Figure 4: Ranking of pathogenic ClinVar variants among the variants identified by whole-genome sequencing in 11 human individuals from diverse populations.
Figure 5: C scores for GWAS SNPs are higher than for nearby control SNPs and are dependent on study sample size.

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Acknowledgements

We thank P. Green and members of the Shendure laboratory for helpful discussions and suggestions. Our work was supported by US NIH grants U54HG006493 (to J.S. and G.M.C.), DP5OD009145 (to D.M.W.) and DP1HG007811 (to J.S.).

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Contributions

G.M.C. and J.S. designed the study. M.K. processed the annotation data and scores and developed and implemented the simulator and scripts required for scoring. P.J. and B.J.O. prepared and provided data sets and annotations. D.M.W. and M.K. developed the model and performed model training. D.M.W. performed the analysis of individual features and interactions. M.K., D.M.W., G.M.C. and J.S. analyzed the model's performance on different data sets. G.M.C. analyzed the GWAS data. J.S., G.M.C., M.K. and D.M.W. wrote the manuscript with input from all authors.

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Correspondence to Gregory M Cooper or Jay Shendure.

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The authors (M.K., D.M.W., G.M.C. and J.S.) have filed a provisional patent application with the US Patent and Trademark Office on the basis of CADD.

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Kircher, M., Witten, D., Jain, P. et al. A general framework for estimating the relative pathogenicity of human genetic variants. Nat Genet 46, 310–315 (2014). https://doi.org/10.1038/ng.2892

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