PlumX Metrics
Embed PlumX Metrics

Rare variant contribution to human disease in 281,104 UK Biobank exomes

Nature, ISSN: 1476-4687, Vol: 597, Issue: 7877, Page: 527-532
2021
  • 238
    Citations
  • 0
    Usage
  • 400
    Captures
  • 3
    Mentions
  • 431
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    238
  • Captures
    400
  • Mentions
    3
    • References
      2
      • Wikipedia
        2
    • News Mentions
      1
      • News
        1
  • Social Media
    431
    • Shares, Likes & Comments
      431
      • Facebook
        431

Most Recent News

Deciphering Immunometabolic Landscape in Rheumatoid Arthritis: Integrative Multiomics, Explainable Machine Learning and Experimental Validation

Introduction Rheumatoid arthritis (RA) is a chronic, systemic autoimmune disease characterized by persistent polyarticular inflammation, synovial hyperplasia, pain, joint swelling and stiffness.1 The global prevalence

Article Description

Genome-wide association studies have uncovered thousands of common variants associated with human disease, but the contribution of rare variants to common disease remains relatively unexplored. The UK Biobank contains detailed phenotypic data linked to medical records for approximately 500,000 participants, offering an unprecedented opportunity to evaluate the effect of rare variation on a broad collection of traits. Here we study the relationships between rare protein-coding variants and 17,361 binary and 1,419 quantitative phenotypes using exome sequencing data from 269,171 UK Biobank participants of European ancestry. Gene-based collapsing analyses revealed 1,703 statistically significant gene–phenotype associations for binary traits, with a median odds ratio of 12.4. Furthermore, 83% of these associations were undetectable via single-variant association tests, emphasizing the power of gene-based collapsing analysis in the setting of high allelic heterogeneity. Gene–phenotype associations were also significantly enriched for loss-of-function-mediated traits and approved drug targets. Finally, we performed ancestry-specific and pan-ancestry collapsing analyses using exome sequencing data from 11,933 UK Biobank participants of African, East Asian or South Asian ancestry. Our results highlight a significant contribution of rare variants to common disease. Summary statistics are publicly available through an interactive portal (http://azphewas.com/).

Bibliographic Details

Quanli Wang; Ryan S. Dhindsa; Keren Carss; Andrew R. Harper; Abhishek Nag; Ioanna Tachmazidou; Dimitrios Vitsios; Sri V. V. Deevi; Alex Mackay; Daniel Muthas; Michael Hühn; Susan Monkley; Henric Olsson; Bastian R. Angermann; Ronen Artzi; Carl Barrett; Maria Belvisi; Mohammad Bohlooly-Y; Oliver Burren; Lisa Buvall; Benjamin Challis; Sophia Cameron-Christie; Suzanne Cohen; Andrew Davis; Regina F. Danielson; Brian Dougherty; Benjamin Georgi; Zara Ghazoui; Pernille B. L. Hansen; Fengyuan Hu; Magda Jeznach; Xiao Jiang; Chanchal Kumar; Zhongwu Lai; Glenda Lassi; Samuel H. Lewis; Bolan Linghu; Kieren Lythgow; Peter Maccallum; Carla Martins; Athena Matakidou; Erik Michaëlsson; Sven Moosmang; Sean O’Dell; Yoichiro Ohne; Joel Okae; Amanda O’Neill; Dirk S. Paul; Anna Reznichenko; Michael A Snowden; Anna Walentinsson; Jorge Zeron; Menelas N. Pangalos; Sebastian Wasilewski; Katherine R. Smith; Ruth March; Adam Platt; Carolina Haefliger; Slavé Petrovski

Springer Science and Business Media LLC

Multidisciplinary

Provide Feedback

Have ideas for a new metric? Would you like to see something else here?Let us know