Identifying cross-disease components of genetic risk across hospital data in the UK Biobank.
Genetic risk factors frequently affect multiple common human diseases, providing insight into shared pathophysiological pathways and opportunities for therapeutic development. However, systematic identification of genetic profiles of disease risk is limited by the availability of both comprehensive...
| Hauptverfasser: | , , , , |
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| Format: | Journal article |
| Sprache: | English |
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Nature Research
2019
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| _version_ | 1826256464805625856 |
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| author | Cortes, A Albers, PK Dendrou, CA Fugger, L McVean, G |
| author_facet | Cortes, A Albers, PK Dendrou, CA Fugger, L McVean, G |
| author_sort | Cortes, A |
| collection | OXFORD |
| description | Genetic risk factors frequently affect multiple common human diseases, providing insight into shared pathophysiological pathways and opportunities for therapeutic development. However, systematic identification of genetic profiles of disease risk is limited by the availability of both comprehensive clinical data on population-scale cohorts and the lack of suitable statistical methodology that can handle the scale of and differential power inherent in multi-phenotype data. Here, we develop a disease-agnostic approach to cluster the genetic risk profiles for 3,025 genome-wide independent loci across 19,155 disease classification codes from 320,644 participants in the UK Biobank, representing a large and heterogeneous population. We identify 339 distinct disease association profiles and use multiple approaches to link clusters to the underlying biological pathways. We show how clusters can decompose the variance and covariance in risk for disease, thereby identifying underlying biological processes and their impact. We demonstrate the use of clusters in defining disease relationships and their potential in informing therapeutic strategies. |
| first_indexed | 2024-03-06T18:02:40Z |
| format | Journal article |
| id | oxford-uuid:00596587-c3b7-43b5-acfe-1c1232df1e20 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T18:02:40Z |
| publishDate | 2019 |
| publisher | Nature Research |
| record_format | dspace |
| spelling | oxford-uuid:00596587-c3b7-43b5-acfe-1c1232df1e202022-03-26T08:29:05ZIdentifying cross-disease components of genetic risk across hospital data in the UK Biobank.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:00596587-c3b7-43b5-acfe-1c1232df1e20EnglishSymplectic ElementsNature Research2019Cortes, AAlbers, PKDendrou, CAFugger, LMcVean, GGenetic risk factors frequently affect multiple common human diseases, providing insight into shared pathophysiological pathways and opportunities for therapeutic development. However, systematic identification of genetic profiles of disease risk is limited by the availability of both comprehensive clinical data on population-scale cohorts and the lack of suitable statistical methodology that can handle the scale of and differential power inherent in multi-phenotype data. Here, we develop a disease-agnostic approach to cluster the genetic risk profiles for 3,025 genome-wide independent loci across 19,155 disease classification codes from 320,644 participants in the UK Biobank, representing a large and heterogeneous population. We identify 339 distinct disease association profiles and use multiple approaches to link clusters to the underlying biological pathways. We show how clusters can decompose the variance and covariance in risk for disease, thereby identifying underlying biological processes and their impact. We demonstrate the use of clusters in defining disease relationships and their potential in informing therapeutic strategies. |
| spellingShingle | Cortes, A Albers, PK Dendrou, CA Fugger, L McVean, G Identifying cross-disease components of genetic risk across hospital data in the UK Biobank. |
| title | Identifying cross-disease components of genetic risk across hospital data in the UK Biobank. |
| title_full | Identifying cross-disease components of genetic risk across hospital data in the UK Biobank. |
| title_fullStr | Identifying cross-disease components of genetic risk across hospital data in the UK Biobank. |
| title_full_unstemmed | Identifying cross-disease components of genetic risk across hospital data in the UK Biobank. |
| title_short | Identifying cross-disease components of genetic risk across hospital data in the UK Biobank. |
| title_sort | identifying cross disease components of genetic risk across hospital data in the uk biobank |
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