Association analyses of more than 140,000 men identify 63 new prostate cancer susceptibility loci

Research output: Contribution to journalLetterResearchpeer-review

  • Fredrick R Schumacher
  • Ali Amin Al Olama
  • Sonja I Berndt
  • Karina Dalsgaard Sorensen
  • Torben Falck Orntoft
  • Michael Borre
  • Nordestgaard, Børge
  • Røder, Andreas
  • Peter Iversen
  • Australian Prostate Cancer BioResource
  • The IMPACT Study
  • Canary PASS Investigators
  • Breast and Prostate Cancer Cohort Consortium (BPC3)
  • The PRACTICAL (Prostate Cancer Association Group to Investigate Cancer-Associated Alterations in the Genome) Consortium
  • Cancer of the Prostate in Sweden (CAPS)
  • Prostate Cancer Genome-wide Association Study of Uncommon Susceptibility Loci (PEGASUS)
  • The Genetic Associations and Mechanisms in Oncology (GAME-ON)/Elucidating Loci Involved in Prostate Cancer Susceptibility (ELLIPSE) Consortium
  • Zsofia Kote-Jarai
  • Christopher A. Haiman
  • Rosalind A Eeles

Genome-wide association studies (GWAS) and fine-mapping efforts to date have identified more than 100 prostate cancer (PrCa)-susceptibility loci. We meta-analyzed genotype data from a custom high-density array of 46,939 PrCa cases and 27,910 controls of European ancestry with previously genotyped data of 32,255 PrCa cases and 33,202 controls of European ancestry. Our analysis identified 62 novel loci associated (P < 5.0 × 10-8) with PrCa and one locus significantly associated with early-onset PrCa (≤55 years). Our findings include missense variants rs1800057 (odds ratio (OR) = 1.16; P = 8.2 × 10-9; G>C, p.Pro1054Arg) in ATM and rs2066827 (OR = 1.06; P = 2.3 × 10-9; T>G, p.Val109Gly) in CDKN1B. The combination of all loci captured 28.4% of the PrCa familial relative risk, and a polygenic risk score conferred an elevated PrCa risk for men in the ninetieth to ninety-ninth percentiles (relative risk = 2.69; 95% confidence interval (CI): 2.55-2.82) and first percentile (relative risk = 5.71; 95% CI: 5.04-6.48) risk stratum compared with the population average. These findings improve risk prediction, enhance fine-mapping, and provide insight into the underlying biology of PrCa1.

Original languageEnglish
JournalNature Genetics
Volume50
Pages (from-to)928-936
ISSN1061-4036
DOIs
Publication statusPublished - 2018

ID: 212862761