Identifying cross-disease components of genetic risk across hospital data in the UK Biobank

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  • Adrian Cortes, University of Oxford, Oxford
  • ,
  • Patrick K Albers, University of Oxford, Oxford
  • ,
  • Calliope A Dendrou, University of Oxford, Oxford
  • ,
  • Lars Fugger
  • Gil McVean, University of Oxford, Oxford

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.

A method to cluster genetic risk profiles applied to 3,025 loci across 19,155 disease codes from over 300,000 individuals in the UK Biobank identifies 339 distinct disease association profiles and links clusters to biological pathways.

Original languageEnglish
JournalNature Genetics
Volume52
Issue1
Pages (from-to)126-134
Number of pages9
ISSN1061-4036
DOIs
Publication statusPublished - Jan 2020
Externally publishedYes

    Research areas

  • Adult, Aged, Biological Specimen Banks, Female, Gene-Environment Interaction, Genetic Diseases, Inborn/genetics, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male, Middle Aged, Phenotype, Polymorphism, Single Nucleotide, Prospective Studies, Quantitative Trait, Heritable, Risk Factors, United Kingdom, PATHWAYS, SUSCEPTIBILITY LOCI, MUTATIONS, TRAITS, GENOME-WIDE ASSOCIATION, VARIANTS, THROMBOSIS, IDENTIFICATION, SELECTION, INSIGHTS

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