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Atlas of prostate cancer heritability in European and African-American men pinpoints tissue-specific regulation

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  • Alexander Gusev
  • Huwenbo Shi
  • Gleb Kichaev
  • Mark Pomerantz
  • Fugen Li
  • Henry W Long
  • Sue A Ingles
  • Rick A Kittles
  • Sara S Strom
  • Benjamin A Rybicki
  • Barbara Nemesure
  • William B Isaacs
  • Wei Zheng
  • Curtis A Pettaway
  • Edward D Yeboah
  • Yao Tettey
  • Richard B Biritwum
  • Andrew A Adjei
  • Evelyn Tay
  • Ann Truelove
  • Shelley Niwa
  • Anand P Chokkalingam
  • Esther M John
  • Adam B Murphy
  • Lisa B Signorello
  • John Carpten
  • M Cristina Leske
  • Suh-Yuh Wu
  • Anslem J M Hennis
  • Christine Neslund-Dudas
  • Ann W Hsing
  • Lisa Chu
  • Phyllis J Goodman
  • Eric A Klein
  • John S Witte
  • Graham Casey
  • Sam Kaggwa
  • Michael B Cook
  • Daniel O Stram
  • William J Blot
  • Rosalind A Eeles
  • Douglas Easton
  • ZSofia Kote-Jarai
  • Ali Amin Al Olama
  • Børge G Nordestgaard
  • PRACTICAL consortium
  • Maren Weischer
  • Sune Fallgaard Nielsen
  • Martin Andreas Røder
  • Ole Peter Klarskov
  • Peter Iversen
Vis graf over relationer

Although genome-wide association studies have identified over 100 risk loci that explain ∼33% of familial risk for prostate cancer (PrCa), their functional effects on risk remain largely unknown. Here we use genotype data from 59,089 men of European and African American ancestries combined with cell-type-specific epigenetic data to build a genomic atlas of single-nucleotide polymorphism (SNP) heritability in PrCa. We find significant differences in heritability between variants in prostate-relevant epigenetic marks defined in normal versus tumour tissue as well as between tissue and cell lines. The majority of SNP heritability lies in regions marked by H3k27 acetylation in prostate adenoc7arcinoma cell line (LNCaP) or by DNaseI hypersensitive sites in cancer cell lines. We find a high degree of similarity between European and African American ancestries suggesting a similar genetic architecture from common variation underlying PrCa risk. Our findings showcase the power of integrating functional annotation with genetic data to understand the genetic basis of PrCa.

OriginalsprogEngelsk
TidsskriftNature Communications
Vol/bind7
Sider (fra-til)10979
ISSN2041-1723
DOI
StatusUdgivet - 8 apr. 2016

ID: 46502053