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Meta-Analysis
. 2014 Oct;46(10):1103-9.
doi: 10.1038/ng.3094. Epub 2014 Sep 14.

A meta-analysis of 87,040 individuals identifies 23 new susceptibility loci for prostate cancer

Ali Amin Al Olama  1 Zsofia Kote-Jarai  2 Sonja I Berndt  3 David V Conti  4 Fredrick Schumacher  4 Ying Han  5 Sara Benlloch  6 Dennis J Hazelett  4 Zhaoming Wang  7 Ed Saunders  8 Daniel Leongamornlert  8 Sara Lindstrom  9 Sara Jugurnauth-Little  8 Tokhir Dadaev  8 Malgorzata Tymrakiewicz  8 Daniel O Stram  4 Kristin Rand  5 Peggy Wan  5 Alex Stram  5 Xin Sheng  5 Loreall C Pooler  5 Karen Park  5 Lucy Xia  5 Jonathan Tyrer  6 Laurence N Kolonel  10 Loic Le Marchand  10 Robert N Hoover  3 Mitchell J Machiela  3 Merideth Yeager  3 Laurie Burdette  3 Charles C Chung  3 Amy Hutchinson  3 Kai Yu  3 Chee Goh  8 Mahbubl Ahmed  8 Koveela Govindasami  8 Michelle Guy  8 Teuvo L J Tammela  11 Anssi Auvinen  12 Tiina Wahlfors  13 Johanna Schleutker  14 Tapio Visakorpi  15 Katri A Leinonen  15 Jianfeng Xu  16 Markus Aly  17 Jenny Donovan  18 Ruth C Travis  19 Tim J Key  19 Afshan Siddiq  20 Federico Canzian  21 Kay-Tee Khaw  22 Atsushi Takahashi  23 Michiaki Kubo  24 Paul Pharoah  25 Nora Pashayan  25 Maren Weischer  26 Borge G Nordestgaard  27 Sune F Nielsen  27 Peter Klarskov  28 Martin Andreas Røder  29 Peter Iversen  29 Stephen N Thibodeau  30 Shannon K McDonnell  30 Daniel J Schaid  30 Janet L Stanford  31 Suzanne Kolb  32 Sarah Holt  33 Beatrice Knudsen  34 Antonio Hurtado Coll  35 Susan M Gapstur  36 W Ryan Diver  36 Victoria L Stevens  36 Christiane Maier  37 Manuel Luedeke  37 Kathleen Herkommer  38 Antje E Rinckleb  37 Sara S Strom  39 Curtis Pettaway  40 Edward D Yeboah  41 Yao Tettey  41 Richard B Biritwum  41 Andrew A Adjei  41 Evelyn Tay  41 Ann Truelove  42 Shelley Niwa  42 Anand P Chokkalingam  43 Lisa Cannon-Albright  44 Cezary Cybulski  45 Dominika Wokołorczyk  45 Wojciech Kluźniak  45 Jong Park  46 Thomas Sellers  46 Hui-Yi Lin  47 William B Isaacs  48 Alan W Partin  48 Hermann Brenner  49 Aida Karina Dieffenbach  49 Christa Stegmaier  50 Constance Chen  9 Edward L Giovannucci  51 Jing Ma  52 Meir Stampfer  53 Kathryn L Penney  54 Lorelei Mucci  54 Esther M John  55 Sue A Ingles  4 Rick A Kittles  56 Adam B Murphy  57 Hardev Pandha  58 Agnieszka Michael  58 Andrzej M Kierzek  58 William Blot  59 Lisa B Signorello  54 Wei Zheng  60 Demetrius Albanes  61 Jarmo Virtamo  62 Stephanie Weinstein  61 Barbara Nemesure  63 John Carpten  64 Cristina Leske  63 Suh-Yuh Wu  63 Anselm Hennis  65 Adam S Kibel  66 Benjamin A Rybicki  67 Christine Neslund-Dudas  67 Ann W Hsing  55 Lisa Chu  55 Phyllis J Goodman  68 Eric A Klein  69 S Lilly Zheng  16 Jyotsna Batra  70 Judith Clements  70 Amanda Spurdle  71 Manuel R Teixeira  72 Paula Paulo  73 Sofia Maia  73 Chavdar Slavov  74 Radka Kaneva  75 Vanio Mitev  75 John S Witte  76 Graham Casey  4 Elizabeth M Gillanders  77 Daniella Seminara  77 Elio Riboli  78 Freddie C Hamdy  79 Gerhard A Coetzee  4 Qiyuan Li  80 Matthew L Freedman  80 David J Hunter  9 Kenneth Muir  81 Henrik Gronberg  82 David E Neal  83 Melissa Southey  84 Graham G Giles  85 Gianluca Severi  86 Breast and Prostate Cancer Cohort Consortium (BPC3)PRACTICAL (Prostate Cancer Association Group to Investigate Cancer-Associated Alterations in the Genome) ConsortiumCOGS (Collaborative Oncological Gene-environment Study) ConsortiumGAME-ON/ELLIPSE ConsortiumMichael B Cook  87 Hidewaki Nakagawa  88 Fredrik Wiklund  89 Peter Kraft  90 Stephen J Chanock  87 Brian E Henderson  91 Douglas F Easton  1 Rosalind A Eeles  92 Christopher A Haiman  91
Affiliations
Meta-Analysis

A meta-analysis of 87,040 individuals identifies 23 new susceptibility loci for prostate cancer

Ali Amin Al Olama et al. Nat Genet. 2014 Oct.

Abstract

Genome-wide association studies (GWAS) have identified 76 variants associated with prostate cancer risk predominantly in populations of European ancestry. To identify additional susceptibility loci for this common cancer, we conducted a meta-analysis of > 10 million SNPs in 43,303 prostate cancer cases and 43,737 controls from studies in populations of European, African, Japanese and Latino ancestry. Twenty-three new susceptibility loci were identified at association P < 5 × 10(-8); 15 variants were identified among men of European ancestry, 7 were identified in multi-ancestry analyses and 1 was associated with early-onset prostate cancer. These 23 variants, in combination with known prostate cancer risk variants, explain 33% of the familial risk for this disease in European-ancestry populations. These findings provide new regions for investigation into the pathogenesis of prostate cancer and demonstrate the usefulness of combining ancestrally diverse populations to discover risk loci for disease.

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Figures

Figure 1
Figure 1
Manhattan Plot of genotyped and imputed results from the European ancestry meta-analysis of overall prostate cancer risk. All SNPs within 500kb of known GWAS SNPs are omitted. The green line represents P=5×10-8. This figure shows all new variants with P<5×10-8, regardless of the confirmation results (one signal on chr1, one on chr4, one on chr17, and 2 on chr X were not confirmed). Many of the new signals are in close proximity to one another on the same chromosome (see Supplementary Table 6).
Figure 2
Figure 2
Manhattan Plot of results from the multiethnic meta-analysis of overall prostate cancer risk. All SNPs within 500kb of known GWAS SNPs are omitted. The green line represents P=5×10-8. This figure shows all new variants with P<5×10-8, regardless of the confirmation results, as well as signals that were reported in the European meta-analysis that also reached 5×10-8 in the multiethnic meta-analysis (see Table 1 and Supplementary Table 6).
Figure 3
Figure 3
Regional plots of two novel genome-wide significant loci associated with prostate cancer risk. rs1041449/21q22 (TMPRSS2 region, left) and rs17694493/9p21 (CDKN2B-AS1region, right). Top: SNPs are plotted by their position 500kb on either side of the index SNP (purple diamond) on the chromosome against their association (-log10 P) with prostate cancer from the multiethnic meta-analysis (rs1041449) and European meta-analysis (rs17694493). SNPs surrounding the index SNP are colored to indicate the local LD structure using pairwise r2 data from the EUR panel of the 1000 Genomes (March 2012). MIDDLE: Significant peaks from TF and histone modification ChIP-seq experiments in the same genomic window (see Online Methods). All ChIP-seq in LNCaP unless otherwise indicated. BOTTOM: Genomic sequence (enclosed in black box) surrounding the SNP (red box) aligned to a LOGO graphic representing the proposed motif disruption.

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References

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