Assessment of polygenic architecture and risk prediction based on common variants across fourteen cancers

  • Yan Dora Zhang
  • Amber N Hurson
  • Haoyu Zhang
  • Parichoy Pal Choudhury
  • Douglas F Easton
  • Roger L Milne
  • Jacques Simard
  • Per Hall
  • Kyriaki Michailidou
  • Joe Dennis
  • Marjanka K Schmidt
  • Jenny Chang-Claude
  • Puya Gharahkhani
  • David Whiteman
  • Peter T Campbell
  • Michael Hoffmeister
  • Mark Jenkins
  • Li Hsu
  • Stephen B Gruber
  • Graham Casey
  • Stephanie L Schmit
  • Tracy A O'Mara
  • Amanda B Spurdle
  • Deborah J Thompson
  • Ian Tomlinson
  • Immaculata De Vivo
  • Maria Teresa Landi
  • Matthew H Law
  • Mark M Iles
  • Florence Demenais
  • Rajiv Kumar
  • Stuart MacGregor
  • D Timothy Bishop
  • Sarah V Ward
  • Melissa L Bondy
  • Richard Houlston
  • John K Wiencke
  • Beatrice Melin
  • Jill Barnholtz-Sloan
  • Ben Kinnersley
  • Margaret R Wrensch
  • Christopher I Amos
  • Rayjean J Hung
  • Paul Brennan
  • James McKay
  • Neil E Caporaso
  • Sonja I Berndt
  • Brenda M Birmann
  • Nicola J Camp
  • Peter Kraft
  • Nathaniel Rothman
  • Susan L Slager
  • Andrew Berchuck
  • Paul D P Pharoah
  • Thomas A Sellers
  • Simon A Gayther
  • Celeste L Pearce
  • Ellen L Goode
  • Joellen M Schildkraut
  • Kirsten B Moysich
  • Laufey T Amundadottir
  • Eric J Jacobs
  • Alison P Klein
  • Gloria M Petersen
  • Harvey A Risch
  • Rachel Z Stolzenberg-Solomon
  • Brian M Wolpin
  • Donghui Li
  • Rosalind A Eeles
  • Christopher A Haiman
  • Zsofia Kote-Jarai
  • Fredrick R Schumacher
  • Ali Amin Al Olama
  • Mark P Purdue
  • Ghislaine Scelo
  • Marlene D Dalgaard
  • Mark H Greene
  • Tom Grotmol
  • Peter A Kanetsky
  • Katherine A McGlynn
  • Katherine L Nathanson
  • Clare Turnbull
  • Fredrik Wiklund
  • Stephen J Chanock
  • Nilanjan Chatterjee
  • Montserrat Garcia-Closas
  • Breast Cancer Association Consortium (BCAC)

Beteiligte Einrichtungen

Abstract

Genome-wide association studies (GWAS) have led to the identification of hundreds of susceptibility loci across cancers, but the impact of further studies remains uncertain. Here we analyse summary-level data from GWAS of European ancestry across fourteen cancer sites to estimate the number of common susceptibility variants (polygenicity) and underlying effect-size distribution. All cancers show a high degree of polygenicity, involving at a minimum of thousands of loci. We project that sample sizes required to explain 80% of GWAS heritability vary from 60,000 cases for testicular to over 1,000,000 cases for lung cancer. The maximum relative risk achievable for subjects at the 99th risk percentile of underlying polygenic risk scores (PRS), compared to average risk, ranges from 12 for testicular to 2.5 for ovarian cancer. We show that PRS have potential for risk stratification for cancers of breast, colon and prostate, but less so for others because of modest heritability and lower incidence.

Bibliografische Daten

OriginalspracheEnglisch
ISSN2041-1723
DOIs
StatusVeröffentlicht - 03.07.2020
PubMed 32620889