Seven prostate cancer susceptibility loci identified by a multi-stage genome-wide association study
University of Cambridge1, Cancer Council Victoria2, University of Melbourne3, University of Tampere4, University of Copenhagen5, German Cancer Research Center6, Imperial College London7, University of Oxford8, Karolinska Institutet9, Harvard University10, American Cancer Society11, University of Southern California12, Science Applications International Corporation13, National Institutes of Health14, New York University15, Cancer Research UK16, University of Bristol17, Fred Hutchinson Cancer Research Center18, University of Washington19, Aarhus University20, Hannover Medical School21, Washington University in St. Louis22, University of Tasmania23, Pomeranian Medical University24, QIMR Berghofer Medical Research Institute25, Queensland University of Technology26, Griffith University27, University of Queensland28, Mayo Clinic29, Cancer Prevention Institute of California30, Stanford University31, University of Ulm32, University of Michigan33, University of South Florida34, Veterans Health Administration35, University of Utah36, Akita University37, Second Military Medical University38, Queen Mary University of London39, Sofia Medical University40, University of Warwick41, Institute of Cancer Research42, National Health Service43, The Royal Marsden NHS Foundation Trust44, Copenhagen University Hospital45, National Institute for Health and Welfare46, University of Sheffield47, University of Hawaii at Manoa48
TL;DR: The results of stage 3 are reported, in which 1,536 SNPs are evaluated in 4,574 individuals with prostate cancer (cases) and 4,164 controls and a SNP in TERT more strongly associated with PrCa than that previously reported is identified.
Abstract: Prostate cancer (PrCa) is the most frequently diagnosed male cancer in developed countries. We conducted a multi-stage genome-wide association study for PrCa and previously reported the results of the first two stages, which identified 16 PrCa susceptibility loci. We report here the results of stage 3, in which we evaluated 1,536 SNPs in 4,574 individuals with prostate cancer (cases) and 4,164 controls. We followed up ten new association signals through genotyping in 51,311 samples in 30 studies from the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium. In addition to replicating previously reported loci, we identified seven new prostate cancer susceptibility loci on chromosomes 2p11, 3q23, 3q26, 5p12, 6p21, 12q13 and Xq12 (P = 4.0 × 10(-8) to P = 2.7 × 10(-24)). We also identified a SNP in TERT more strongly associated with PrCa than that previously reported. More than 40 PrCa susceptibility loci, explaining ∼25% of the familial risk in this disease, have now been identified.
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University of Iceland1, Harvard University2, Norwegian Institute of Public Health3, Karolinska Institutet4, University of Copenhagen5, University of California6, National University of Health Sciences7, University of Helsinki8, Odense University Hospital9, University of Southern Denmark10, Tampere University of Technology11, National Institute for Health and Welfare12
TL;DR: There was significant excess familial risk for cancer overall and for specific types of cancer, including prostate, melanoma, breast, ovary, and uterus, in this long-term follow-up study among Nordic twins.
Abstract: Importance Estimates of familial cancer risk from population-based studies are essential components of cancer risk prediction. Objective To estimate familial risk and heritability of cancer types in a large twin cohort. Design, Setting, and Participants Prospective study of 80 309 monozygotic and 123 382 same-sex dizygotic twin individuals (N = 203 691) within the population-based registers of Denmark, Finland, Norway, and Sweden. Twins were followed up a median of 32 years between 1943 and 2010. There were 50 990 individuals who died of any cause, and 3804 who emigrated and were lost to follow-up. Exposures Shared environmental and heritable risk factors among pairs of twins. Main Outcomes and Measures The main outcome was incident cancer. Time-to-event analyses were used to estimate familial risk (risk of cancer in an individual given a twin’s development of cancer) and heritability (proportion of variance in cancer risk due to interindividual genetic differences) with follow-up via cancer registries. Statistical models adjusted for age and follow-up time, and accounted for censoring and competing risk of death. Results A total of 27 156 incident cancers were diagnosed in 23 980 individuals, translating to a cumulative incidence of 32%. Cancer was diagnosed in both twins among 1383 monozygotic (2766 individuals) and 1933 dizygotic (2866 individuals) pairs. Of these, 38% of monozygotic and 26% of dizygotic pairs were diagnosed with the same cancer type. There was an excess cancer risk in twins whose co-twin was diagnosed with cancer, with estimated cumulative risks that were an absolute 5% (95% CI, 4%-6%) higher in dizygotic (37%; 95% CI, 36%-38%) and an absolute 14% (95% CI, 12%-16%) higher in monozygotic twins (46%; 95% CI, 44%-48%) whose twin also developed cancer compared with the cumulative risk in the overall cohort (32%). For most cancer types, there were significant familial risks and the cumulative risks were higher in monozygotic than dizygotic twins. Heritability of cancer overall was 33% (95% CI, 30%-37%). Significant heritability was observed for the cancer types of skin melanoma (58%; 95% CI, 43%-73%), prostate (57%; 95% CI, 51%-63%), nonmelanoma skin (43%; 95% CI, 26%-59%), ovary (39%; 95% CI, 23%-55%), kidney (38%; 95% CI, 21%-55%), breast (31%; 95% CI, 11%-51%), and corpus uteri (27%; 95% CI, 11%-43%). Conclusions and Relevance In this long-term follow-up study among Nordic twins, there was significant excess familial risk for cancer overall and for specific types of cancer, including prostate, melanoma, breast, ovary, and uterus. This information about hereditary risks of cancers may be helpful in patient education and cancer risk counseling.
623 citations
Fredrick R. Schumacher1, Ali Amin Al Olama2, Sonja I. Berndt3, Sara Benlloch2 +204 more•Institutions (79)
TL;DR: A large meta-analysis combining genome-wide and custom high-density genotyping array data identifies 63 new susceptibility loci for prostate cancer, enhancing fine-mapping efforts and providing insights into the underlying biology of PrCa1.
Abstract: Genome-wide association studies (GWAS) and fine-mapping efforts to date have identified more than 100 prostate cancer (PrCa)-susceptibility loci. We meta-analyzed genotype data from a custom high-density array of 46,939 PrCa cases and 27,910 controls of European ancestry with previously genotyped data of 32,255 PrCa cases and 33,202 controls of European ancestry. Our analysis identified 62 novel loci associated (P C, p.Pro1054Arg) in ATM and rs2066827 (OR = 1.06; P = 2.3 × 10−9; T>G, p.Val109Gly) in CDKN1B. The combination of all loci captured 28.4% of the PrCa familial relative risk, and a polygenic risk score conferred an elevated PrCa risk for men in the ninetieth to ninety-ninth percentiles (relative risk = 2.69; 95% confidence interval (CI): 2.55–2.82) and first percentile (relative risk = 5.71; 95% CI: 5.04–6.48) risk stratum compared with the population average. These findings improve risk prediction, enhance fine-mapping, and provide insight into the underlying biology of PrCa1. A large meta-analysis combining genome-wide and custom high-density genotyping array data identifies 63 new susceptibility loci for prostate cancer, enhancing fine-mapping efforts and providing insights into the underlying biology.
585 citations
TL;DR: The novel HOXB13 G84E variant is associated with a significantly increased risk of hereditary prostate cancer, and this finding has implications for prostate-cancer risk assessment and may provide new mechanistic insights into this common cancer.
Abstract: Background Family history is a significant risk factor for prostate cancer, although the molecular basis for this association is poorly understood. Linkage studies have implicated chromosome 17q21-22 as a possible location of a prostate-cancer susceptibility gene. Methods We screened more than 200 genes in the 17q21-22 region by sequencing germline DNA from 94 unrelated patients with prostate cancer from families selected for linkage to the candidate region. We tested family members, additional case subjects, and control subjects to characterize the frequency of the identified mutations. Results Probands from four families were discovered to have a rare but recurrent mutation (G84E) in HOXB13 (rs138213197), a homeobox transcription factor gene that is important in prostate development. All 18 men with prostate cancer and available DNA in these four families carried the mutation. The carrier rate of the G84E mutation was increased by a factor of approximately 20 in 5083 unrelated subjects of European desce...
581 citations
Stig E. Bojesen1, Stig E. Bojesen2, Karen A. Pooley3, Sharon E. Johnatty4 +452 more•Institutions (129)
TL;DR: Using the Illumina custom genotyping array iCOGs, SNPs at the TERT locus in breast, ovarian and BRCA1 mutation carrier cancer cases and controls and leukocyte telomere measurements are analyzed to find associations cluster into three independent peaks.
Abstract: TERT-locus SNPs and leukocyte telomere measures are reportedly associated with risks of multiple cancers. Using the Illumina custom genotyping array iCOG, we analyzed similar to 480 SNPs at the TERT locus in breast (n = 103,991), ovarian (n = 39,774) and BRCA1 mutation carrier (n = 11,705) cancer cases and controls. Leukocyte telomere measurements were also available for 53,724 participants. Most associations cluster into three independent peaks. The minor allele at the peak 1 SNP rs2736108 associates with longer telomeres (P = 5.8 x 10(-7)), lower risks for estrogen receptor (ER)-negative (P = 1.0 x 10(-8)) and BRCA1 mutation carrier (P = 1.1 x 10(-5)) breast cancers and altered promoter assay signal. The minor allele at the peak 2 SNP rs7705526 associates with longer telomeres (P = 2.3 x 10(-14)), higher risk of low-malignant-potential ovarian cancer (P = 1.3 x 10(-15)) and greater promoter activity. The minor alleles at the peak 3 SNPs rs10069690 and rs2242652 increase ER-negative (P = 1.2 x 10(-12)) and BRCA1 mutation carrier (P = 1.6 x 10-14) breast and invasive ovarian (P = 1.3 x 10(-11)) cancer risks but not via altered telomere length. The cancer risk alleles of rs2242652 and rs10069690, respectively, increase silencing and generate a truncated TERT splice variant.
522 citations
TL;DR: This study outlines the major sources of genetic and phenotypic variation in iPS cells and establishes their suitability as models of complex human traits and cancer.
Abstract: Technology utilizing human induced pluripotent stem cells (iPS cells) has enormous potential to provide improved cellular models of human disease. However, variable genetic and phenotypic characterization of many existing iPS cell lines limits their potential use for research and therapy. Here we describe the systematic generation, genotyping and phenotyping of 711 iPS cell lines derived from 301 healthy individuals by the Human Induced Pluripotent Stem Cells Initiative. Our study outlines the major sources of genetic and phenotypic variation in iPS cells and establishes their suitability as models of complex human traits and cancer. Through genome-wide profiling we find that 5-46% of the variation in different iPS cell phenotypes, including differentiation capacity and cellular morphology, arises from differences between individuals. Additionally, we assess the phenotypic consequences of genomic copy-number alterations that are repeatedly observed in iPS cells. In addition, we present a comprehensive map of common regulatory variants affecting the transcriptome of human pluripotent cells.
462 citations
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TL;DR: This work proposes a coherent analysis framework that treats the genome-wide association problem as one involving missing or uncertain genotypes, and proposes a model-based imputation method for inferring genotypes at observed or unobserved SNPs, leading to improved power over existing methods for multipoint association mapping.
Abstract: Genome-wide association studies are set to become the method of choice for uncovering the genetic basis of human diseases. A central challenge in this area is the development of powerful multipoint methods that can detect causal variants that have not been directly genotyped. We propose a coherent analysis framework that treats the problem as one involving missing or uncertain genotypes. Central to our approach is a model-based imputation method for inferring genotypes at observed or unobserved SNPs, leading to improved power over existing methods for multipoint association mapping. Using real genome-wide association study data, we show that our approach (i) is accurate and well calibrated, (ii) provides detailed views of associated regions that facilitate follow-up studies and (iii) can be used to validate and correct data at genotyped markers. A notable future use of our method will be to boost power by combining data from genome-wide scans that use different SNP sets.
2,640 citations
TL;DR: An R library for genome-wide association (GWA) analysis that implements effective storage and handling of GWA data, fast procedures for genetic data quality control, testing of association of single nucleotide polymorphisms with binary or quantitative traits, visualization of results and also provides easy interfaces to standard statistical and graphical procedures.
Abstract: Here we describe an R library for genome-wide association (GWA) analysis. It implements effective storage and handling of GWA data, fast procedures for genetic data quality control, testing of association of single nucleotide polymorphisms with binary or quantitative traits, visualization of results and also provides easy interfaces to standard statistical and graphical procedures implemented in base R and special R libraries for genetic analysis. We evaluated GenABEL using one simulated and two real data sets. We conclude that GenABEL enables the analysis of GWA data on desktop computers. Availability: http://cran.r-project.org Contact: i.aoultchenko@erasmusmc.nl
1,794 citations
TL;DR: A genome-wide association study using blood DNA samples from 1,854 individuals with clinically detected prostate cancer diagnosed at ≤60 years or with a family history of disease, and 1,894 population-screened controls with a low prostate-specific antigen (PSA) concentration (<0.5 ng/ml) identified seven loci associated with prostate cancer on chromosomes 3, 6, 7, 10, 11, 19 and X.
Abstract: Prostate cancer is the most common cancer affecting males in developed countries. It shows consistent evidence of familial aggregation, but the causes of this aggregation are mostly unknown. To identify common alleles associated with prostate cancer risk, we conducted a genome-wide association study (GWAS) using blood DNA samples from 1,854 individuals with clinically detected prostate cancer diagnosed at
805 citations
TL;DR: Using reported GWAS findings for height, Crohn's disease and breast, prostate and colorectal cancers, it is determined that each of these traits is likely to harbor additional loci within the spectrum of low-penetrance common variants.
Abstract: We report a set of tools to estimate the number of susceptibility loci and the distribution of their effect sizes for a trait on the basis of discoveries from existing genome-wide association studies (GWASs). We propose statistical power calculations for future GWASs using estimated distributions of effect sizes. Using reported GWAS findings for height, Crohn's disease and breast, prostate and colorectal (BPC) cancers, we determine that each of these traits is likely to harbor additional loci within the spectrum of low-penetrance common variants. These loci, which can be identified from sufficiently powerful GWASs, together could explain at least 15-20% of the known heritability of these traits. However, for BPC cancers, which have modest familial aggregation, our analysis suggests that risk models based on common variants alone will have modest discriminatory power (63.5% area under curve), even with new discoveries.
666 citations
TL;DR: Twenty-seven regions of the genome are identified with one or more sequence variants showing significant association with height and the strongest association was with SNPs in the ZBTB38 gene.
Abstract: Adult human height is one of the classical complex human traits. We searched for sequence variants that affect height by scanning the genomes of 25,174 Icelanders, 2,876 Dutch, 1,770 European Americans and 1,148 African Americans. We then combined these results with previously published results from the Diabetes Genetics Initiative on 3,024 Scandinavians and tested a selected subset of SNPs in 5,517 Danes. We identified 27 regions of the genome with one or more sequence variants showing significant association with height. The estimated effects per allele of these variants ranged between 0.3 and 0.6 cm and, taken together, they explain around 3.7% of the population variation in height. The genes neighboring the identified loci cluster in biological processes related to skeletal development and mitosis. Association to three previously reported loci are replicated in our analyses, and the strongest association was with SNPs in the ZBTB38 gene.
659 citations