4.5 Article

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Journal

HUMAN MOLECULAR GENETICS
Volume 24, Issue 19, Pages 5589-5602

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/hmg/ddv203

Keywords

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Funding

  1. European Commission [223175 (HEALTH-F2-2009-223175)]
  2. Cancer Research UK [C5047/A7357, C1287/A10118, C5047/A3354, C5047/A10692, C16913/A6135]
  3. National Institute of Health (NIH) Cancer Post-Cancer GWAS initiative [1 U19 CA 148537-01]
  4. Institute of Cancer Research
  5. Cancer Research UK [17528, 19727, 16563, 10588, 13065, 16491, 19170, 14136, 16561, 15007] Funding Source: researchfish
  6. Medical Research Council [G1000143, G0401527] Funding Source: researchfish
  7. National Institute for Health Research [NF-SI-0509-10242, NF-SI-0611-10106, NF-SI-0512-10114] Funding Source: researchfish
  8. The Francis Crick Institute
  9. Cancer Research UK [10124] Funding Source: researchfish

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Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain similar to 38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same region.

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