A general framework for estimating the relative pathogenicity of human genetic variants
Open accessAbstract
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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A CADD score above 12.37 is the threshold for a variant to be potentially pathogenic.
“A CADD score above 12.37 is the threshold to be potentially pathogenic 23 .”
From Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence (2018) · cites this paper as [23]
The Technical Report says CADD scores rank known pathogenic variants highly, but it does not establish 12.37 as a pathogenicity threshold. It also says C-scores cannot be precisely calibrated to the likelihood that a variant is pathogenic and are best interpreted as indicating likelihood of deleteriousness. (LLM, conf=0.87)
Experimental — accuracy not yet measuredNewer in-silico tools are beginning to address additional noncoding sequences.
“Newer tools are beginning to address additional noncoding sequences. 13”
Convergent evidence of strong association (z = 9.49) and the highest observed probability of a deleterious protein effect (CADD score = 34) were found for rs13107325.
“Convergent evidence of strong association (z = 9.49) and the highest observed probability of a deleterious protein effect (CADD 23 score = 34) were found for rs13107325.”
From Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence (2018) · cites this paper as [23]
Among 390 de novo missense variants in affected offspring, 43.6% are predicted deleterious using CADD score ≥25 and show 1.28-fold enrichment compared with baseline expectation (p-value = 6.6 × 10−4).
“Among the 390 de novo missense variants in affected offspring, 43.6% are predicted to be deleterious using CADD score ≥2510 and show 1.28-fold enrichment compared with baseline expectation in the general population (p-value = 6.6 × 10−4 by one-sided exact Poisson test).”
From Exome sequencing of 457 autism families recruited online provides evidence for autism risk genes (2019) · cites this paper as [10]
Existing methods for detecting gene-specific enrichment of damaging de novo mutations ignore much prior information about which variants are more likely disease-associated.
“Existing methods to detect gene-specific enrichments of damaging DNMs ignore much prior information about which variants are more likely to be disease-associated; missense variants and protein-truncating variants (PTVs) vary in their impact on protein function3–6.”
From Evidence for 28 genetic disorders discovered by combining healthcare and research data (2020) · cites this paper as [3]
Missense variants and protein-truncating variants differ in their impact on protein function.
“missense variants and protein-truncating variants (PTVs) vary in their impact on protein function3–6.”
From Evidence for 28 genetic disorders discovered by combining healthcare and research data (2020) · cites this paper as [3]
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REVEL and BayesDel outperform other in silico meta-predictors for clinical variant classification
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KAT6A Syndrome: genotype–phenotype correlation in 76 patients with pathogenic KAT6A variants
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Predicting functional effect of missense variants using graph attention neural networks
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- Authors
- Kircher, M., Witten, D. M., Jain, P., O'Roak, B. J., Cooper, G. M., & Shendure, J.
- Affiliations
- University of Washington (US)
- HudsonAlpha Institute for Biotechnology (US)
- Corresponding author
- Cooper, Gregory M
- Shendure, Jay
- Venue
- Nature Genetics
- Published
- 2014-02-02
- Volume
- 46
- Issue
- 3
- Pages
- 310-315
- ISSN
- 1061-4036 (ISSN-L)
- 1546-1718
- PMC
- PMC3992975
- OpenAlex
- W2160995259
- Cited by
- 6,183
- References
- 65
- Citations by year
- 2026: 306 · 2025: 433 · 2024: 521 · 2023: 480 · 2022: 583 · 2021: 600 · 2020: 580 · 2019: 704 · 2018: 667 · 2017: 542 · 2016: 396 · 2015: 275 · 2014: 88 · 2013: 1 · 2012: 1
- FWCI
- 281.40
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Genetics (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (DP5OD009145)
- National Human Genome Research Institute (DP1HG007811, U54HG006493, UM1HG006493)
- National Center for Chronic Disease Prevention and Health Promotion (DP1 HG007811)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- CADD, genetic variant annotation, deleterious mutations, single nucleotide variants, indels, support vector machine, regulatory effects, disease severity, allelic diversity, variant prioritization
- MeSH terms
- Humans, Models, Genetic, Selection, Genetic, Genetic Variation, Genome, Human, Polymorphism, Single Nucleotide, INDEL Mutation, Genome-Wide Association Study, Molecular Sequence Annotation, Support Vector Machine
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