Polygenic risk modeling with latent trait-related genetic components Article Swipe
Matthew Aguirre
,
Yosuke Tanigawa
,
Guhan Venkataraman
,
Rob Tibshirani
,
Trevor Hastie
,
Manuel A. Rivas
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1101/808675
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1101/808675
Polygenic risk models have led to significant advances in understanding complex diseases and their clinical presentation. While models like polygenic risk scores (PRS) can effectively predict outcomes, they do not generally account for disease subtypes or pathways which underlie within-trait diversity. Here, we introduce a latent factor model of genetic risk based on components from Decomposition of Genetic Associations (DeGAs), which we call the DeGAs polygenic risk score (dPRS). We compute DeGAs using genetic associations for 977 traits in the UK Biobank and find that dPRS performs comparably to standard PRS while offering greater interpretability. We show how to decompose an individual’s genetic risk for a trait across DeGAs components, highlighting specific results for body mass index (BMI), myocardial infarction (heart attack), and gout in 337,151 white British individuals, with replication in a further set of 25,486 non-British white individuals from the Biobank. We find that BMI polygenic risk factorizes into components relating to fat-free mass, fat mass, and overall health indicators like physical activity measures. Most individuals with high dPRS for BMI have strong contributions from both a fat mass component and a fat-free mass component, whereas a few ‘outlier’ individuals have strong contributions from only one of the two components. Overall, our method enables fine-scale interpretation of the drivers of genetic risk for complex traits.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/808675
- https://www.biorxiv.org/content/biorxiv/early/2020/08/30/808675.full.pdf
- OA Status
- green
- Cited By
- 1
- References
- 62
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2980376231
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2980376231Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1101/808675Digital Object Identifier
- Title
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Polygenic risk modeling with latent trait-related genetic componentsWork title
- Type
-
preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2019Year of publication
- Publication date
-
2019-10-17Full publication date if available
- Authors
-
Matthew Aguirre, Yosuke Tanigawa, Guhan Venkataraman, Rob Tibshirani, Trevor Hastie, Manuel A. RivasList of authors in order
- Landing page
-
https://doi.org/10.1101/808675Publisher landing page
- PDF URL
-
https://www.biorxiv.org/content/biorxiv/early/2020/08/30/808675.full.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://www.biorxiv.org/content/biorxiv/early/2020/08/30/808675.full.pdfDirect OA link when available
- Concepts
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Biobank, Trait, Interpretability, Genetic architecture, Body mass index, Quantitative trait locus, Biology, Medicine, Genetics, Computer science, Artificial intelligence, Internal medicine, Gene, Programming languageTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
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2020: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| primary_location.landing_page_url | https://doi.org/10.1101/808675 |
| publication_date | 2019-10-17 |
| publication_year | 2019 |
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