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. 2016 Apr 7:7:10979.
doi: 10.1038/ncomms10979.

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

Alexander Gusev  1   2 Huwenbo Shi  3 Gleb Kichaev  3 Mark Pomerantz  4 Fugen Li  5   6 Henry W Long  4   5 Sue A Ingles  7 Rick A Kittles  8 Sara S Strom  9 Benjamin A Rybicki  10 Barbara Nemesure  11 William B Isaacs  12 Wei Zheng  13 Curtis A Pettaway  14 Edward D Yeboah  15   16 Yao Tettey  15   16 Richard B Biritwum  15   16 Andrew A Adjei  15   16 Evelyn Tay  15   16 Ann Truelove  17 Shelley Niwa  17 Anand P Chokkalingam  18 Esther M John  19   20 Adam B Murphy  21 Lisa B Signorello  1   22 John Carpten  23 M Cristina Leske  11 Suh-Yuh Wu  11 Anslem J M Hennis  11   24 Christine Neslund-Dudas  10 Ann W Hsing  19   20 Lisa Chu  19   20 Phyllis J Goodman  25 Eric A Klein  26 John S Witte  27   28 Graham Casey  7 Sam Kaggwa  29 Michael B Cook  30 Daniel O Stram  7 William J Blot  13   22 Rosalind A Eeles  31   32 Douglas Easton  33 Zsofia Kote-Jarai  31 Ali Amin Al Olama  33 Sara Benlloch  33 Kenneth Muir  34   35 Graham G Giles  36   37 Melissa C Southey  38 Liesel M Fitzgerald  36 Henrik Gronberg  39 Fredrik Wiklund  39 Markus Aly  39   40 Brian E Henderson  41 Johanna Schleutker  42   43 Tiina Wahlfors  43 Teuvo L J Tammela  44 Børge G Nordestgaard  45   46 Tim J Key  47 Ruth C Travis  47 David E Neal  48   49 Jenny L Donovan  50 Freddie C Hamdy  51   52 Paul Pharoah  53 Nora Pashayan  53   54 Kay-Tee Khaw  55 Janet L Stanford  56   57 Stephen N Thibodeau  58 Shannon K McDonnell  58 Daniel J Schaid  58 Christiane Maier  59 Walther Vogel  59 Manuel Luedeke  60 Kathleen Herkommer  61 Adam S Kibel  62 Cezary Cybulski  63 Dominika Wokolorczyk  63 Wojciech Kluzniak  63 Lisa Cannon-Albright  64   65 Craig Teerlink  64   65 Hermann Brenner  66   67 Aida K Dieffenbach  66   67 Volker Arndt  66 Jong Y Park  68 Thomas A Sellers  68 Hui-Yi Lin  69 Chavdar Slavov  70 Radka Kaneva  71 Vanio Mitev  71 Jyotsna Batra  72 Amanda Spurdle  73 Judith A Clements  72 Manuel R Teixeira  74   75 Hardev Pandha  76 Agnieszka Michael  76 Paula Paulo  74 Sofia Maia  74 Andrzej Kierzek  76 PRACTICAL consortiumDavid V Conti  77 Demetrius Albanes  78 Christine Berg  79 Sonja I Berndt  30 Daniele Campa  80 E David Crawford  81 W Ryan Diver  82 Susan M Gapstur  82 J Michael Gaziano  1   83   84 Edward Giovannucci  1   85 Robert Hoover  30 David J Hunter  1 Mattias Johansson  86   87 Peter Kraft  1   88 Loic Le Marchand  89 Sara Lindström  1   88 Carmen Navarro  90   91 Kim Overvad  79 Elio Riboli  92 Afshan Siddiq  93 Victoria L Stevens  82 Dimitrios Trichopoulos  1   94   95 Paolo Vineis  96   97 Meredith Yeager  30 Gosia Trynka  98   99 Soumya Raychaudhuri  2   98   100 Frederick R Schumacher  77 Alkes L Price  1   2 Matthew L Freedman  2   4   5 Christopher A Haiman  77 Bogdan Pasaniuc  3   101   102
Collaborators, Affiliations

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

Alexander Gusev et al. Nat Commun. .

Abstract

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.

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Figures

Figure 1
Figure 1. Functional partitioning for variants within ARBS for PrCa.
Bars graphs detailing %SNP heritability estimates from two models of PrCa relevant functional annotations. (a) Joint comparison of variants within 5 kb of tumour-only and normal-only regions in the ARBS in prostate tissue (P=2.1 × 10−19 for difference by Z-test). (b) Estimates from ARBS in prostate tissue (no longer using a 5 kb flank) and ARBS in LNCaP cell lines (P=4.4 × 10−7 for difference). The null formula image is labelled by the dashed lines. Error bars show analytical standard error of estimate.
Figure 2
Figure 2. Functional partitioning of heritability across six main epigenetic classes.
Each point corresponds to an estimate of % SNP heritability (y axis) from SNPs within a cell-type-specific functional annotation versus annotation size (%SNPs, x axis). Overall, 544 annotations were tested, and red points indicate significant deviations from the null of formula image equal to %SNPs after accounting for all tests. The two most significant annotations in each class are shown with triangle/cross, respectively, and labelled in bottom right (see Supplementary Data for all annotations).
Figure 3
Figure 3. Pairwise analysis of DHS marks in three prostate cell types.
Joint model from all pairs of DHS marks shown for: cancer cell line (LNCAP); normal prostate epithelial (PREC); and immortalized prostate epithelial (RWPE1). Circle size corresponds to % SNPs, with % SNP heritability and significance labelled. P value was computed for difference between formula image and %SNP, with bold representing significance after correcting for nine tests. The observed trend is LNCAP>PREC>RWPE1: (a)formula image in LNCaP DHS was nominally significantly higher than PrEC (P=0.01); and formula image in LNCaP and PrEC was significantly higher than RWPE1 (b,c; P=1.5 × 10−9, P=1.2 × 10−5, respectively). All P values computed by Z-test using formula image estimate and analytical standard error.
Figure 4
Figure 4. Comparison of enhancers and super enhancers across 49 cell types.
Each bar represents the %SNP heritability formula image/ %SNP for enhancers (left) and super enhancers (right) from a given cell type tested marginally. Red indicates significant difference from 1.0 (no enrichment) after accounting for 49 tests. Enhancer LNCAP is most significant, with other cancers also appearing significant and non-cancer tissues least significant. Error bars show analytical s.e. of estimate.
Figure 5
Figure 5. Partitioning of heritability across functional classes in prostate cancer.
Visual representation of heritability enrichment in three studies a,b: iCOGS; c: AAPC; d: BPC3 (shown numerically in Table 1). Each subplot corresponds to an analysis of the listed joint model, with coloured slices representing the functional annotations evaluated. Volume of each interior (light coloured) pie-chart slice represents the %SNP for the functional annotation, which is equal to the expected formula image under the null of no enrichment. Volume of each shaded pie-chart slice represents the actual formula image inferred by the model. Slices extending outside/inside the middle pie correspond to enrichment/depletion in SNP heritability, as indicated by the dotted lines. Colour coding is consistent across all subpanels. * (**) denotes significant deviation at P<0.05 (P<0.05/15) of fraction of SNP heritability (formula image from null model of formula image by Z-test; see Supplementary Table 6 for P values).

References

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