The contribution of coding variants to the heritability of multiple cancer types using UK Biobank whole-exome sequencing data Article Swipe
Naomi Wilcox
,
Jonathan P. Tyrer
,
Joe Dennis
,
Xin Yang
,
John R. B. Perry
,
Eugene J. Gardner
,
Douglas F. Easton
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1016/j.ajhg.2025.02.013
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1016/j.ajhg.2025.02.013
Genome-wide association studies have been highly successful at identifying common variants associated with cancer; however, they do not explain all the inherited risks of cancer. Family-based studies, targeted sequencing, and, more recently, exome-wide association studies have identified rare coding variants in some genes associated with cancer risk, but the overall contribution of these variants to the heritability of cancer is less clear. Here, we describe a method to estimate the genome-wide contribution of rare coding variants to heritability that fits models to the burden effect sizes using an empirical Bayesian approach. We apply this method to the burden of protein-truncating variants in over 15,000 genes for 11 cancers in the UK Biobank using whole-exome sequencing data on over 400,000 individuals. We extend the method to consider the overlap of genes contributing to pairs of cancers. We found ovarian cancer to have the greatest proportion of heritability attributable to protein-truncating variants in genes (46%). The joint cancer models highlight significant clustering of cancer types, including a near-complete overlap in susceptibility genes for breast, ovarian, prostate, and pancreatic cancer. Our results provide insights into the contribution of rare coding variants to the heritability of cancer and identify additional genes with strong evidence of susceptibility to multiple cancer types.
Related Topics
Concepts
Biobank
Exome
Exome sequencing
Heritability
Coding (social sciences)
Computational biology
Biology
Genetics
Statistics
Gene
Mutation
Mathematics
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.ajhg.2025.02.013
- OA Status
- hybrid
- Cited By
- 1
- References
- 38
- Related Works
- 10
- OpenAlex ID
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All OpenAlex metadata
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https://openalex.org/W4408303478Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1016/j.ajhg.2025.02.013Digital Object Identifier
- Title
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The contribution of coding variants to the heritability of multiple cancer types using UK Biobank whole-exome sequencing dataWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-03-11Full publication date if available
- Authors
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Naomi Wilcox, Jonathan P. Tyrer, Joe Dennis, Xin Yang, John R. B. Perry, Eugene J. Gardner, Douglas F. EastonList of authors in order
- Landing page
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https://doi.org/10.1016/j.ajhg.2025.02.013Publisher landing page
- Open access
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://doi.org/10.1016/j.ajhg.2025.02.013Direct OA link when available
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Biobank, Exome, Exome sequencing, Heritability, Coding (social sciences), Computational biology, Biology, Genetics, Statistics, Gene, Mutation, MathematicsTop concepts (fields/topics) attached by OpenAlex
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1Total citation count in OpenAlex
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2025: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.highly | 5 |
| abstract_inverted_index.method | 66, 94, 123 |
| abstract_inverted_index.models | 80, 156 |
| abstract_inverted_index.strong | 198 |
| abstract_inverted_index.types, | 162 |
| abstract_inverted_index.types. | 205 |
| abstract_inverted_index.400,000 | 118 |
| abstract_inverted_index.Biobank | 111 |
| abstract_inverted_index.breast, | 171 |
| abstract_inverted_index.cancer. | 24, 176 |
| abstract_inverted_index.cancer; | 13 |
| abstract_inverted_index.cancers | 107 |
| abstract_inverted_index.explain | 18 |
| abstract_inverted_index.ovarian | 137 |
| abstract_inverted_index.overall | 49 |
| abstract_inverted_index.overlap | 127, 166 |
| abstract_inverted_index.provide | 179 |
| abstract_inverted_index.results | 178 |
| abstract_inverted_index.studies | 2, 34 |
| abstract_inverted_index.Bayesian | 89 |
| abstract_inverted_index.cancers. | 134 |
| abstract_inverted_index.consider | 125 |
| abstract_inverted_index.describe | 64 |
| abstract_inverted_index.estimate | 68 |
| abstract_inverted_index.evidence | 199 |
| abstract_inverted_index.greatest | 142 |
| abstract_inverted_index.however, | 14 |
| abstract_inverted_index.identify | 194 |
| abstract_inverted_index.insights | 180 |
| abstract_inverted_index.multiple | 203 |
| abstract_inverted_index.ovarian, | 172 |
| abstract_inverted_index.studies, | 26 |
| abstract_inverted_index.targeted | 27 |
| abstract_inverted_index.variants | 10, 39, 53, 75, 100, 149, 187 |
| abstract_inverted_index.approach. | 90 |
| abstract_inverted_index.empirical | 88 |
| abstract_inverted_index.highlight | 157 |
| abstract_inverted_index.including | 163 |
| abstract_inverted_index.inherited | 21 |
| abstract_inverted_index.prostate, | 173 |
| abstract_inverted_index.recently, | 31 |
| abstract_inverted_index.additional | 195 |
| abstract_inverted_index.associated | 11, 43 |
| abstract_inverted_index.clustering | 159 |
| abstract_inverted_index.exome-wide | 32 |
| abstract_inverted_index.identified | 36 |
| abstract_inverted_index.pancreatic | 175 |
| abstract_inverted_index.proportion | 143 |
| abstract_inverted_index.sequencing | 114 |
| abstract_inverted_index.successful | 6 |
| abstract_inverted_index.Genome-wide | 0 |
| abstract_inverted_index.association | 1, 33 |
| abstract_inverted_index.genome-wide | 70 |
| abstract_inverted_index.identifying | 8 |
| abstract_inverted_index.sequencing, | 28 |
| abstract_inverted_index.significant | 158 |
| abstract_inverted_index.whole-exome | 113 |
| abstract_inverted_index.Family-based | 25 |
| abstract_inverted_index.attributable | 146 |
| abstract_inverted_index.contributing | 130 |
| abstract_inverted_index.contribution | 50, 71, 183 |
| abstract_inverted_index.heritability | 56, 77, 145, 190 |
| abstract_inverted_index.individuals. | 119 |
| abstract_inverted_index.near-complete | 165 |
| abstract_inverted_index.susceptibility | 168, 201 |
| abstract_inverted_index.protein-truncating | 99, 148 |
| cited_by_percentile_year.max | 95 |
| cited_by_percentile_year.min | 91 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 7 |
| citation_normalized_percentile.value | 0.79375446 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |