Estimation of effect size distribution from genome-wide association studies and implications for future discoveries View Full Text


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Article Info

DATE

2010-07

AUTHORS

Ju-Hyun Park, Sholom Wacholder, Mitchell H Gail, Ulrike Peters, Kevin B Jacobs, Stephen J Chanock, Nilanjan Chatterjee

ABSTRACT

We report a set of tools to estimate the number of susceptibility loci and the distribution of their effect sizes for a trait on the basis of discoveries from existing genome-wide association studies (GWASs). We propose statistical power calculations for future GWASs using estimated distributions of effect sizes. Using reported GWAS findings for height, Crohn's disease and breast, prostate and colorectal (BPC) cancers, we determine that each of these traits is likely to harbor additional loci within the spectrum of low-penetrance common variants. These loci, which can be identified from sufficiently powerful GWASs, together could explain at least 15-20% of the known heritability of these traits. However, for BPC cancers, which have modest familial aggregation, our analysis suggests that risk models based on common variants alone will have modest discriminatory power (63.5% area under curve), even with new discoveries. More... »

PAGES

570

References to SciGraph publications

  • 2008-05. Many sequence variants affecting diversity of adult human height in NATURE GENETICS
  • 2008-03. Multiple loci identified in a genome-wide association study of prostate cancer in NATURE GENETICS
  • 2008-03. Multiple newly identified loci associated with prostate cancer susceptibility in NATURE GENETICS
  • 2002-05. Polygenic susceptibility to breast cancer and implications for prevention in NATURE GENETICS
  • 2009-05. A multistage genome-wide association study in breast cancer identifies two new risk alleles at 1p11.2 and 14q24.1 (RAD51L1) in NATURE GENETICS
  • 2008-08. Genome-wide association defines more than 30 distinct susceptibility loci for Crohn's disease in NATURE GENETICS
  • 2008-12. Meta-analysis of genome-wide association data identifies four new susceptibility loci for colorectal cancer in NATURE GENETICS
  • 2009-04. Beyond odds ratios — communicating disease risk based on genetic profiles in NATURE REVIEWS GENETICS
  • 2009-10-08. Finding the missing heritability of complex diseases in NATURE
  • 2008-05. Sizing up human height variation in NATURE GENETICS
  • 2008-05. Genome-wide association analysis identifies 20 loci that influence adult height in NATURE GENETICS
  • 2007-06-28. Genome-wide association study identifies novel breast cancer susceptibility loci in NATURE
  • 2008-05. Identification of ten loci associated with height highlights new biological pathways in human growth in NATURE GENETICS
  • 2009-10. Identification of seven new prostate cancer susceptibility loci through a genome-wide association study in NATURE GENETICS
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/ng.610

    DOI

    http://dx.doi.org/10.1038/ng.610

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1025253932

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/20562874


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    JSON-LD is a popular format for linked data which is fully compatible with JSON.

    curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1038/ng.610'

    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/ng.610'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/ng.610'

    RDF/XML is a standard XML format for linked data.

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