Dataset Information

Identification of 23 new prostate cancer susceptibility loci using the iCOGS custom genotyping array.

ABSTRACT: Prostate cancer is the most frequently diagnosed cancer in males in developed countries. To identify common prostate cancer susceptibility alleles, we genotyped 211,155 SNPs on a custom Illumina array (iCOGS) in blood DNA from 25,074 prostate cancer cases and 24,272 controls from the international PRACTICAL Consortium. Twenty-three new prostate cancer susceptibility loci were identified at genome-wide significance (P < 5 × 10(-8)). More than 70 prostate cancer susceptibility loci, explaining ?30% of the familial risk for this disease, have now been identified. On the basis of combined risks conferred by the new and previously known risk loci, the top 1% of the risk distribution has a 4.7-fold higher risk than the average of the population being profiled. These results will facilitate population risk stratification for clinical studies.

SUBMITTER: Eeles RA

PROVIDER: S-EPMC3832790 | biostudies-literature | 2013 Apr

REPOSITORIES: biostudies-literature

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Identification of 23 new prostate cancer susceptibility loci using the iCOGS custom genotyping array.

Eeles Rosalind A RA Olama Ali Amin Al AA Benlloch Sara S Saunders Edward J EJ Leongamornlert Daniel A DA Tymrakiewicz Malgorzata M Ghoussaini Maya M Luccarini Craig C Dennis Joe J Jugurnauth-Little Sarah S Dadaev Tokhir T Neal David E DE Hamdy Freddie C FC Donovan Jenny L JL Muir Ken K Giles Graham G GG Severi Gianluca G Wiklund Fredrik F Gronberg Henrik H Haiman Christopher A CA Schumacher Fredrick F Henderson Brian E BE Le Marchand Loic L Lindstrom Sara S Kraft Peter P Hunter David J DJ Gapstur Susan S Chanock Stephen J SJ Berndt Sonja I SI Albanes Demetrius D Andriole Gerald G Schleutker Johanna J Weischer Maren M Canzian Federico F Riboli Elio E Key Tim J TJ Travis Ruth C RC Campa Daniele D Ingles Sue A SA John Esther M EM Hayes Richard B RB Pharoah Paul D P PD Pashayan Nora N Khaw Kay-Tee KT Stanford Janet L JL Ostrander Elaine A EA Signorello Lisa B LB Thibodeau Stephen N SN Schaid Dan D Maier Christiane C Vogel Walther W Kibel Adam S AS Cybulski Cezary C Lubinski Jan J Cannon-Albright Lisa L Brenner Hermann H Park Jong Y JY Kaneva Radka R Batra Jyotsna J Spurdle Amanda B AB Clements Judith A JA Teixeira Manuel R MR Dicks Ed E Lee Andrew A Dunning Alison M AM Baynes Caroline C Conroy Don D Maranian Melanie J MJ Ahmed Shahana S Govindasami Koveela K Guy Michelle M Wilkinson Rosemary A RA Sawyer Emma J EJ Morgan Angela A Dearnaley David P DP Horwich Alan A Huddart Robert A RA Khoo Vincent S VS Parker Christopher C CC Van As Nicholas J NJ Woodhouse Christopher J CJ Thompson Alan A Dudderidge Tim T Ogden Chris C Cooper Colin S CS Lophatananon Artitaya A Cox Angela A Southey Melissa C MC Hopper John L JL English Dallas R DR Aly Markus M Adolfsson Jan J Xu Jiangfeng J Zheng Siqun L SL Yeager Meredith M Kaaks Rudolf R Diver W Ryan WR Gaudet Mia M MM Stern Mariana C MC Corral Roman R Joshi Amit D AD Shahabi Ahva A Wahlfors Tiina T Tammela Teuvo L J TL Auvinen Anssi A Virtamo Jarmo J Klarskov Peter P Nordestgaard Børge G BG Røder M Andreas MA Nielsen Sune F SF Bojesen Stig E SE Siddiq Afshan A Fitzgerald Liesel M LM Kolb Suzanne S Kwon Erika M EM Karyadi Danielle M DM Blot William J WJ Zheng Wei W Cai Qiuyin Q McDonnell Shannon K SK Rinckleb Antje E AE Drake Bettina B Colditz Graham G Wokolorczyk Dominika D Stephenson Robert A RA Teerlink Craig C Muller Heiko H Rothenbacher Dietrich D Sellers Thomas A TA Lin Hui-Yi HY Slavov Chavdar C Mitev Vanio V Lose Felicity F Srinivasan Srilakshmi S Maia Sofia S Paulo Paula P Lange Ethan E Cooney Kathleen A KA Antoniou Antonis C AC Vincent Daniel D Bacot François F Tessier Daniel C DC Kote-Jarai Zsofia Z Easton Douglas F DF

Nature genetics 20130401 4

Prostate cancer is the most frequently diagnosed cancer in males in developed countries. To identify common prostate cancer susceptibility alleles, we genotyped 211,155 SNPs on a custom Illumina array (iCOGS) in blood DNA from 25,074 prostate cancer cases and 24,272 controls from the international PRACTICAL Consortium. Twenty-three new prostate cancer susceptibility loci were identified at genome-wide significance (P < 5 × 10(-8)). More than 70 prostate cancer susceptibility loci, explaining ∼30 ...[more]

PMID: 23535732

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Project description:BackgroundPooling genomic DNA samples within clinical classes of disease followed by genotyping on whole-genome SNP microarrays, allows for rapid and inexpensive genome-wide association studies. Key to the success of these studies is the accuracy of the allelic frequency calculations, the ability to identify false-positives arising from assay variability and the ability to better resolve association signals through analysis of neighbouring SNPs.ResultsWe report the accuracy of allelic frequency measurements on pooled genomic DNA samples by comparing these measurements to the known allelic frequencies as determined by individual genotyping. We describe modifications to the calculation of k-correction factors from relative allele signal (RAS) values that remove biases and result in more accurate allelic frequency predictions. Our results show that the least accurate SNPs, those most likely to give false-positives in an association study, are identifiable by comparing their frequencies to both those from a known database of individual genotypes and those of the pooled replicates. In a disease with a previously identified genetic mutation, we demonstrate that one can identify the disease locus through the comparison of the predicted allelic frequencies in case and control pools. Furthermore, we demonstrate improved resolution of association signals using the mean of individual test-statistics for consecutive SNPs windowed across the genome. A database of k-correction factors for predicting allelic frequencies for each SNP, derived from several thousand individually genotyped samples, is provided. Lastly, a Perl script for calculating RAS values for the Affymetrix platform is provided.ConclusionOur results illustrate that pooling of DNA samples is an effective initial strategy to identify a genetic locus. However, it is important to eliminate inaccurate SNPs prior to analysis by comparing them to a database of individually genotyped samples as well as by comparing them to replicates of the pool. Lastly, detection of association signals can be improved by incorporating data from neighbouring SNPs.

Dataset Information

Identification of 23 new prostate cancer susceptibility loci using the iCOGS custom genotyping array.

Publications

Identification of 23 new prostate cancer susceptibility loci using the iCOGS custom genotyping array.

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