Literature DB >> 20972438

A multi-stage genome-wide association study of bladder cancer identifies multiple susceptibility loci.

Nathaniel Rothman1, Montserrat Garcia-Closas, Nilanjan Chatterjee, Nuria Malats, Xifeng Wu, Jonine D Figueroa, Francisco X Real, David Van Den Berg, Giuseppe Matullo, Dalsu Baris, Michael Thun, Lambertus A Kiemeney, Paolo Vineis, Immaculata De Vivo, Demetrius Albanes, Mark P Purdue, Thorunn Rafnar, Michelle A T Hildebrandt, Anne E Kiltie, Olivier Cussenot, Klaus Golka, Rajiv Kumar, Jack A Taylor, Jose I Mayordomo, Kevin B Jacobs, Manolis Kogevinas, Amy Hutchinson, Zhaoming Wang, Yi-Ping Fu, Ludmila Prokunina-Olsson, Laurie Burdett, Meredith Yeager, William Wheeler, Adonina Tardón, Consol Serra, Alfredo Carrato, Reina García-Closas, Josep Lloreta, Alison Johnson, Molly Schwenn, Margaret R Karagas, Alan Schned, Gerald Andriole, Robert Grubb, Amanda Black, Eric J Jacobs, W Ryan Diver, Susan M Gapstur, Stephanie J Weinstein, Jarmo Virtamo, Victoria K Cortessis, Manuela Gago-Dominguez, Malcolm C Pike, Mariana C Stern, Jian-Min Yuan, David J Hunter, Monica McGrath, Colin P Dinney, Bogdan Czerniak, Meng Chen, Hushan Yang, Sita H Vermeulen, Katja K Aben, J Alfred Witjes, Remco R Makkinje, Patrick Sulem, Soren Besenbacher, Kari Stefansson, Elio Riboli, Paul Brennan, Salvatore Panico, Carmen Navarro, Naomi E Allen, H Bas Bueno-de-Mesquita, Dimitrios Trichopoulos, Neil Caporaso, Maria Teresa Landi, Federico Canzian, Borje Ljungberg, Anne Tjonneland, Francoise Clavel-Chapelon, David T Bishop, Mark T W Teo, Margaret A Knowles, Simonetta Guarrera, Silvia Polidoro, Fulvio Ricceri, Carlotta Sacerdote, Alessandra Allione, Geraldine Cancel-Tassin, Silvia Selinski, Jan G Hengstler, Holger Dietrich, Tony Fletcher, Peter Rudnai, Eugen Gurzau, Kvetoslava Koppova, Sophia C E Bolick, Ashley Godfrey, Zongli Xu, José I Sanz-Velez, María D García-Prats, Manuel Sanchez, Gabriel Valdivia, Stefano Porru, Simone Benhamou, Robert N Hoover, Joseph F Fraumeni, Debra T Silverman, Stephen J Chanock.   

Abstract

We conducted a multi-stage, genome-wide association study of bladder cancer with a primary scan of 591,637 SNPs in 3,532 affected individuals (cases) and 5,120 controls of European descent from five studies followed by a replication strategy, which included 8,382 cases and 48,275 controls from 16 studies. In a combined analysis, we identified three new regions associated with bladder cancer on chromosomes 22q13.1, 19q12 and 2q37.1: rs1014971, (P = 8 × 10⁻¹²) maps to a non-genic region of chromosome 22q13.1, rs8102137 (P = 2 × 10⁻¹¹) on 19q12 maps to CCNE1 and rs11892031 (P = 1 × 10⁻⁷) maps to the UGT1A cluster on 2q37.1. We confirmed four previously identified genome-wide associations on chromosomes 3q28, 4p16.3, 8q24.21 and 8q24.3, validated previous candidate associations for the GSTM1 deletion (P = 4 × 10⁻¹¹) and a tag SNP for NAT2 acetylation status (P = 4 × 10⁻¹¹), and found interactions with smoking in both regions. Our findings on common variants associated with bladder cancer risk should provide new insights into the mechanisms of carcinogenesis.

Entities:  

Mesh:

Substances:

Year:  2010        PMID: 20972438      PMCID: PMC3049891          DOI: 10.1038/ng.687

Source DB:  PubMed          Journal:  Nat Genet        ISSN: 1061-4036            Impact factor:   38.330


Bladder cancer is the fourth most common incident cancer in men1 and its frequent recurrence requires regular screening and interventions. Cigarette smoking and occupational exposure to aromatic amines have been strongly linked to bladder cancer risk.1 A family history of bladder cancer is associated with an approximately two-fold increase in risk; however, multiple-cancer families are rare and no high-penetrance genes have been identified to date2-4. Large meta-analyses of candidate gene studies have provided support for associations between NAT2 slow acetylation phenotype5 (defined by NAT2 haplotypes) and a common gene deletion of GSTM16 with bladder cancer risk7,8. Further, gene-environment interactions have been shown for smoking and NAT2 acetylation, with an increased risk in slow acetylators, apparent only among cigarette smokers7,8. Previous genome-wide association studies (GWAS) in bladder cancer have identified common variants in four genomic regions on chromosomes 3q289 (TP63), 4p16.3 (TMEM129, TACC3-FGFR3)10, 8q24.219, and 8q24.311 (PSCA) that are associated with risk. Interestingly, the variants on 8q24.21 map to a region centromeric to MYC that has been identified in GWAS of breast, colorectal and prostate cancers, as well as chronic lymphocytic leukemia12-18. Also, in follow-up analyses, an association with bladder cancer risk has been suggested for variants near the TERT-CLPTM1L locus on chromosome 5p15.33, which has also been associated by GWAS with risk for basal cell carcinoma, cutaneous melanoma, lung, brain and pancreatic cancers19-23. However, the previously reported association with bladder cancer did not achieve genome-wide significance. We conducted a multi-stage GWAS involving 3,532 cases and 5,120 controls of self-described European descent in stage I, and followed up the most notable signals in two stages of replication (stages IIa/b and III) totaling 8,381 cases and 48,275 controls (Figure 1 and Online Methods). Individuals with scan data in stage I were participants in two case-control studies carried out in Spain and the USA (Maine and Vermont component of the New England Bladder Cancer Study) and three prospective cohort studies in the USA and Finland (see Supplementary Table 1 online for details). Replication analyses in stage II were carried out using existing scan data from two earlier studies. First, we evaluated the 100 most significant SNPs (excluding previously reported loci and SNPs with pairwise r2>0.8) in 969 cases and 957 controls from the Texas Bladder Cancer study in the USA (stage IIa)11. Five of these SNPs were further evaluated in a second scan of 1,274 cases and 1,832 controls in The Netherlands (stage IIb)9. Three of the five SNPs were included or tagged at a pair-wise r2>0.8 in the Dutch scan, and risk associations were confirmed for all three. In stage III, the three SNPs plus a tagging SNP for the NAT2 acetylation status were evaluated in 6,141 cases and 45,486 controls from 11 case-control and 3 prospective cohort studies in the USA and Europe (see Figure 1 and Supplementary Table 1).
Figure 1

Study design of multi-stage GWAS of bladder cancer

See Online Methods and Supplementary Table 1 for details of study designs and sample sizes. *The tag SNP, rs1495741 located 3′ of NAT241 was genotyped in subjects in stage II and III studies as well as on the Illumina bead chips used in stage I. **Includes 338 additional cases from NBCS that were added to the final combined analyses.

After quality control analysis of genotypes, we combined the data sets in stage I resulting in 589,299 SNPs available for analysis (based on the common SNPs called from both the Illumina Human1M and Human 610-Quad) in 3,532 cases and 5,120 controls (Online Methods). A logistic regression model was fit for genotype trend effects (1 d.f.) adjusted for study center, age, sex, smoking status (current, former or never) and DNA source (blood/buccal). The quantile-quantile (Q-Q) plot showed little evidence for inflation of the test statistics as compared to the expected distribution (corrected λ1000 subjects=1.021), which minimizes the likelihood of substantial hidden population substructure or differential genotype calling between cases and controls24 (Online Methods and Supplementary Figure 1). A Manhattan plot displays the results of the combined GWAS in stage I (Supplementary Figure 2). Data from the first stage confirm the associations reported with tag SNPs in the four previously identified genomic regions on chromosomes 3q28 (rs710521)9, 8q24.21 (rs9642880)9, 8q24.3 (rs2294008)11 and 4p16.3 (rs798766)10 as well as a suggested region in 5p15.33 (rs401681; a neighboring SNP, rs2736098, was also reported but data were not available in our study)19 (Table 1 and Supplementary Figure 3). Consistent with prior reports9,10, rs9642880 on 8q24.21 and rs798766 on 4p16.3 were most strongly associated with tumors of low grade/low risk of progression (Supplementary Table 2). A stronger association with low grade/low risk disease was also suggested for rs401681 on 5p15.33 (Supplementary Table 2). In addition, we used a copy number variation TaqMan assay7 to assess the presence of GSTM1 on 1p13.3 to genotype stage I samples, and confirmed an association with increased bladder cancer risk (Table 1).
Table 1

Previously reported genetic variants associated with bladder cancer risk

Results of meta-analyses of allelic OR estimates for the markers reported to achieve genome-wide significance25. Studies in Kiemeney et al. 20089 include: NBCS, LBCS, IBCS, TBCS, Sweden, Belgium, EEBCS, BBCS, ZBCS. Studies in Wu et al. 200911 include: NBCS, TXBCS1/2, New Hampshire, LBCS, IBCS, TBCS, Sweden, EEBCS, Belgium, BBCS, ZBCS, MSKCC. Studies in Rafnar et al 200919 include NBCS, IBCS, LBCS, Sweden, TBCS, EEBCS, Belgium, ZBCS, BBCS.

Markera, riskalleleb, chrc,locationc andgenedGroups of studiesNeCasesControlsFreq.fAllelic OR(95%CI)gP valueh
rs9642880 [T]Previously reported i 993,85537,9850.451.221.151.297.8E-12
Chr 8q24.21:Stage I53,5255,1080.451.211.131.294.6E-08
128787250Combined147,38043,0931.211.161.272.0E-18
MYC
rs710521 [A]Previously reported i 993,85537,9850.731.191.121.271.1E-07
Chr 3q28:Stage I53,5195,1100.721.151.071.253.3E-04
191128627Combined147,37443,0951.181.121.241.8E-10
TP63
rs2294008 [T]Previously reported i 11136,66739,5900.461.151.101.202.0E-10
Chr 8q24.3:Stage I53,5295,1150.451.081.011.162.2E-02
143758933Combined1810,19644,7051.131.091.174.4E-11
PSCA
rs401681 [C]Previously reported i 1994,14734,9880.541.121.061.185.1E-05
Chr 5p15.33:Stage I53,5265,1170.551.111.041.192.9E-03
1375087Combined147,67340,1051.111.071.165.0E-07
TERT-CLPTM1L
rs798766 [T]Previously reported i 10114,58045,2690.191.241.171.329.5E-12
Chr 4p16.3:Stage I53,5315,1180.191.141.051.232.6E-03
1704037Combined168,11150,3871.201.141.263.9E-13
TMEM129 TACC3-FGFR3
Deletion AssayPreviously reported i 7,9285,0726,4660.511.461.351.581.9E-21
Chr 1p13.3Stage Ij42,4803,2220.491.491.331.683.7E-11
GSTM1 Combined327,5529,6880.531.471.381.575.0E-31

NCBI dbSNP identifier.

Risk allele shown in [].

Chromosome and NCBI Human Genome Build 36.3 location.

Gene neighborhood closest to the most notable SNP.

N: number of studies

Risk allele frequency in control populations.

Estimate assuming multiplicative odds model, OR, odds ratio; CI, 95% confidence interval.

1 d.f. trend test.

Summary estimates differ slightly from previously published because we used a fixed effects meta-analysis.

Data from SBCS was excluded from stage I because it had been included in the previous meta-analyses published in Garcia-Closas et al. 20057.. Data from NEBCS are reported separately (Unpublished data to appear in “GSTM1 null and NAT2 Slow Acetylation Genotypes, Smoking Intensity, and Bladder Cancer Risk: Results from the New England Bladder Cancer Case-Control Study and Meta-Analyses” by Moore LE, Baris D, Figueroa J, Garcia-Closas M, Karagas M, Schwenn M, Johnson A, Lubin J, Hein DW, Dagnall C, Colt J, Kida M, Jones M, Schned A, Cherela S, Chanock S, Cantor K, Silverman D, Rothman N)

In a combined analysis based on case/control counts by genotype and study, we estimated odds ratios (ORs) using logistic regression analyses adjusted for study center. Meta-analyses of estimated ORs adjusted for age, sex, smoking status and DNA source produced comparable point estimates (Supplementary Table 3). Our combined analysis of stages I, II and III identified three novel genomic regions on chromosomes 22q13.1, 19q12 and 2q37.1 that were associated with bladder cancer risk below the threshold for genome-wide significance (P<5 × 10−7)25 (Table 2 and Supplementary Figure 4 for study and stage specific estimates, Figure 2). We also confirmed a signal below genome-wide significance for rs1495741, which tags the NAT2 acetylator status26 previously reported as a bladder cancer susceptibility locus on 8p227,8. The new SNP is located approximately 10kb of the 3′ end of the gene.
Table 2

Novel SNPs identified in a multi-stage GWAS of bladder cancer

Results of the meta-analysis of genotype counts included in combined stages I, II and III. The initial scan results were adjusted by age, gender, smoking status, study site and DNA source.

Markera, minoralleleb, chrc,locationc and genedStudiesincludedNeCasesControlsFreq.fAllelic OR(95%CI)gP valueh
rs1014971 [C ]Stage I53,5295,0920.380.870.820.936.1E-05
Chr 22q13.1:Stage II and III158,27747,5170.370.890.850.933.0E-08
37662569Combined2011,80652,6090.380.880.850.918.4E-12
CBX6, APOBEC3A
rs8102137 [C]Stage I53,5305,1140.331.131.061.211.6E-04
Chr 19q12:Stage II and III158,26147,7080.321.131.081.182.6E-08
34988693Combined2011,79152,8220.331.131.091.171.7E-11
CCNE1
rs11892031 [C]Stage I53,5245,1080.080.790.700.896.9E-05
Chr 2q37.1:Stage II and III158,28447,7270.080.860.800.931.8E-04
234230022Combined2011,80852,8350.080.840.790.891.0E-07
UGT1A cluster j
rs1495741 [G]Stage I5352551160.240.860.800.931.5E-04
Chr 8p22:Stage II and III158,27947,7440.220.870.830.926.8E-08
18317161Combined2011,80452,8600.240.870.830.914.2E-11
NAT2

NCBI dbSNP identifier.

Minor allele shown in [].

Chromosome and NCBI Human Genome Build 36.3 location.

Gene neighborhood closest to the most notable SNP.

N: number of studies

Minor allele frequency in control populations.

Estimate assuming multiplicative odds model, OR, odds ratio; CI, 95% confidence interval.

1 d.f. trend test.

Figure 2

Association results, recombination and linkage disequilibrium plots for four regions on chromosomes 22q13.1, 19q12, 2q37.1 and 8p22

Results of stage I (green circles), combined stages II and III (blue diamonds) and combined data from the three stages (red diamonds) with P-values for log-additive association results with recombination rates (cm/Mb) based on HapMap phase II data. Pairwise r2 values based on control populations are displayed at the bottom for all SNPs included in the GWAS analysis. Panel A depicts chromosome 22q13.1 region (37,617,065 to 37,743,614). Panel B depicts the region of chromosome 19q12 (34,922,089 to 35,080,325). Panel C depicts the region of 2q37.1 (234,131,582 to 234,286,564). Panel D depicts the region of 8p22 (18,216,291 to 18,406,519). Genomic coordinates are based on NCBI Human Genome Build 36.3.

The locus on chromosome 22q13.1, rs1014971 (P=8.4×10−12; OR per C allele =0.88, 95%CI 0.85-0.91)), was primarily associated with high-risk tumors (Supplementary Table 2). The locus is located in a non-genic region, approximately 25 kb centromeric of the catalytic polypeptide-like 3A (APOBEC3A) and 64 kb telomeric of the chromobox homolog 6 (CBX6). APOBEC3A is an apolipoprotein B mRNA editing enzyme that belongs to the cytidine deaminase gene family, which can play a role in the initiation of tumorigenesis by deamination of cytosine (C) to uracil (U)27. CBX6 is a component of the chromatin –associated polycomb complex involved in transcriptional repression. In the combined analysis, we observed an association with rs8102137 on chromosome 19q12 (P=1.7×10−11; OR per C allele =1.13, 95%CI 1.09-1.17), which maps to the cyclin E1 gene (CCNE1). CCNE1 is a key member of the cyclin/cyclin-dependent kinase (Cdk)/retinoblastoma protein (pRB) pathway which determines the rates of cell cycle transition from G1 to S phase, and is commonly altered in bladder cancer and other tumors28. Cyclin E1 expression in bladder cancer has been associated with high grade or muscle invasive tumors and poor clinical outcome29. Consistently, rs8102137 was most strongly associated with risk of high grade/high risk tumors (Supplementary Table 2). A third locus is marked by rs11892031 (P=1.0×10−7; OR per C allele =0.84, 95%CI 0.79-0.89) on chromosome 2q37.1 and resides in an intronic region of the UDP-glucuronosyltransferase (UGT) 1A gene locus, which encodes the UGT1A family of proteins. Glucuronidation by UGTs facilitates solubility and removal of substrates such as endo- and xenobiotics (including carcinogens in tobacco smoke) via bile or urine30. Genetic variation in UGT1A has been associated with predisposition to severe gastrointestinal toxicity of the anticancer drug irinotecan31. The UGT1A locus is represented by at least nine highly homologous transcripts, collectively known as UGTs, generated by alternative splicing. Tissue-specific loss or decreased expression of UGTs has been associated with several gastrointestinal cancers and bladder cancer32-34, as well as experimentally induced bladder cancer in animal models35. Previously, a promising signal in the CLPTM1L-TERT locus on chromosome 5p15.33 was reported in a region in which common variants have been associated with multiple cancers in recent GWAS19-23. In addition, rare mutations in TERT have been linked to dyskeratosis congenita (a bone marrow failure syndrome), idiopathic pulmonary fibrosis, acute myelogenous leukemia and chronic lymphocytic leukemia36-39. In the first stage of this GWAS, we observed a moderately significant effect for rs401681 (P= 2.9 × 10−3), which was at genome-wide significance when combined with the Rafnar et al. data (P = 5.0 × 10−7; OR per C allele 1.11, 95% CI 1.07-1.16) (Table 1, Supplementary Figure 3). The risk associated with GSTM1 and NAT2 varied in strength across categories of cigarette smoking, whereas genotype risk associations by smoking categories were of similar magnitude for the eight susceptibility loci identified by GWAS (Supplementary Table 4). In a combined analysis, the risk association with GSTM1 deletion was strongest in never smokers (OR=1.75, 95%CI=1.44-2.13), and progressively weaker in former (OR=1.55, 95%CI=1.35-1.78) and current smokers (OR=1.25, 95%CI =1.07-1.46; Pinteraction = 0.008 for current vs. never smokers; Table 3). The stronger association of the GSTM1 deletion among non-smokers is a novel observation that was not evident in previous case-only meta-analyses7. rs1495741 located on the 3′ end of NAT2 is a marker of the NAT2 phenotype associated with bladder cancer risk26. The rs1495741 GG genotype marking the slow acetylation phenotype, compared to the combined AG/AA genotypes corresponding to the intermediate/rapid acetylation phenotypes, showed a highly significant (P=5.5×10−7) association with increased bladder cancer risk that was limited to cigarette smokers (OR=1.24, 95% CI=1.16-1.32 P=4.3×10−11; Pinteraction=6.3×10−5) (Supplementary Figure 5 and Supplementary Table 3). This interaction is consistent with the role of NAT2 in the detoxification of bladder carcinogens such as aromatic amines from tobacco smoke.
Table 3

Interaction of NAT2 tagSNP (rs1495741) and GSTM1 deletion with cigarette smoking in bladder cancer risk

Results from logistic regression analyses of aggregated data adjusted by study. rs1495741 genotypes were classified according to an established approach based on the phenotype of NAT2 acetylators; AA/AG were collapsed to tag rapid/intermediate acetylation, and GG tags slow acetylation.26

Cases
Controls
P
NAT2(rs1495741)AA/AGGGAA/AGGGOR95% CIPInteraction
All subjects 3,7846,9155,2338,1821.151.091.222.9E-07
By smoking status
Never smoker7601,2021,6792,7580.950.851.063.3E-01Ref.
Ever smoker3,0245,7133,5545,4241.241.161.324.3E-116.3E-05
 Former smoker1,8593,4552,3003,5591.201.111.296.8E-066.7E-04
 Current smoker1,1652,2581,2541,8651.271.141.407.2E-061.6E-04
GSTM1 Del PresentNullPresentNull

All subjects 1,3191,9951,7171,7261.471.331.624.4E-14
By smoking status
Never smoker2103465195101.711.382.126.9E-07Ref.
Ever smoker1,1091,6491,1981,2161.471.301.672.1E-091.1E-01
 Former smoker5649616226531.621.391.894.7E-106.9E-01
 Current smoker5456885765631.191.001.404.5E-028.1E-03
Our three-stage study had adequate power to detect variants of moderate effect sizes over a range of common allele frequencies. For the newly discovered SNP markers, the power to detect the observed associations at a level of genome-wide significance was at 54%, 30%, 30% and 6% for rs104971, rs1495741, rs8102137 and rs11892031, respectively. In light of the limited power to discover SNPs with modest effect sizes, additional loci with similar effect sizes will likely be identified with larger scale GWAS. Based on a recent estimator40 that incorporates novel and previously reported loci together, we estimate that approximately two dozen additional bladder cancer susceptibility SNP markers of similar magnitude and frequencies might be discovered. Future studies should be powered with adequate sample size to detect additional variants. With the exception of the GSTM1 deletion, relative risk estimates for novel loci are based on associations using tag SNPs, which most likely underestimate the association with biologically important alleles. Accordingly, further studies are needed to define the functional variants and the clinical utility of risk models that combine genetic markers with epidemiologic risk factors for bladder cancer (i.e. smoking, occupational and environmental exposures, family history). Our combined analysis of 12,254 individuals with bladder cancer and 53,395 controls has uncovered three new genomic regions associated with bladder cancer risk. Fine-mapping studies of these three regions are needed to identify candidate variants for functional studies that should shed light into biological mechanisms for the associations reported through GWAS. This knowledge could establish the foundation for developing improved preventive, diagnostic and/or therapeutic approaches.
  51 in total

1.  Segregation analysis of urothelial cell carcinoma.

Authors:  Katja K H Aben; Laura Baglietto; Agnes Baffoe-Bonnie; Jan-Willem W Coebergh; Joan E Bailey-Wilson; Barry Trink; André L M Verbeek; Mark P Schoenberg; J Alfred Witjes; Lambertus A Kiemeney
Journal:  Eur J Cancer       Date:  2006-06-05       Impact factor: 9.162

2.  SequenceLDhot: detecting recombination hotspots.

Authors:  Paul Fearnhead
Journal:  Bioinformatics       Date:  2006-10-23       Impact factor: 6.937

Review 3.  Family 1 uridine-5'-diphosphate glucuronosyltransferases (UGT1A): from Gilbert's syndrome to genetic organization and variability.

Authors:  Christian P Strassburg; Tim O Lankisch; Michael P Manns; Ursula Ehmer
Journal:  Arch Toxicol       Date:  2008-05-20       Impact factor: 5.153

4.  Estimation of effect size distribution from genome-wide association studies and implications for future discoveries.

Authors:  Ju-Hyun Park; Sholom Wacholder; Mitchell H Gail; Ulrike Peters; Kevin B Jacobs; Stephen J Chanock; Nilanjan Chatterjee
Journal:  Nat Genet       Date:  2010-06-20       Impact factor: 38.330

5.  A genome-wide association study of lung cancer identifies a region of chromosome 5p15 associated with risk for adenocarcinoma.

Authors:  Maria Teresa Landi; Nilanjan Chatterjee; Kai Yu; Lynn R Goldin; Alisa M Goldstein; Melissa Rotunno; Lisa Mirabello; Kevin Jacobs; William Wheeler; Meredith Yeager; Andrew W Bergen; Qizhai Li; Dario Consonni; Angela C Pesatori; Sholom Wacholder; Michael Thun; Ryan Diver; Martin Oken; Jarmo Virtamo; Demetrius Albanes; Zhaoming Wang; Laurie Burdette; Kimberly F Doheny; Elizabeth W Pugh; Cathy Laurie; Paul Brennan; Rayjean Hung; Valerie Gaborieau; James D McKay; Mark Lathrop; John McLaughlin; Ying Wang; Ming-Sound Tsao; Margaret R Spitz; Yufei Wang; Hans Krokan; Lars Vatten; Frank Skorpen; Egil Arnesen; Simone Benhamou; Christine Bouchard; Andres Metspalu; Andres Metsapalu; Tonu Vooder; Mari Nelis; Kristian Välk; John K Field; Chu Chen; Gary Goodman; Patrick Sulem; Gudmar Thorleifsson; Thorunn Rafnar; Timothy Eisen; Wiebke Sauter; Albert Rosenberger; Heike Bickeböller; Angela Risch; Jenny Chang-Claude; H Erich Wichmann; Kari Stefansson; Richard Houlston; Christopher I Amos; Joseph F Fraumeni; Sharon A Savage; Pier Alberto Bertazzi; Margaret A Tucker; Stephen Chanock; Neil E Caporaso
Journal:  Am J Hum Genet       Date:  2009-10-15       Impact factor: 11.025

6.  Genome-wide association study identifies five susceptibility loci for glioma.

Authors:  Sanjay Shete; Fay J Hosking; Lindsay B Robertson; Sara E Dobbins; Marc Sanson; Beatrice Malmer; Matthias Simon; Yannick Marie; Blandine Boisselier; Jean-Yves Delattre; Khe Hoang-Xuan; Soufiane El Hallani; Ahmed Idbaih; Diana Zelenika; Ulrika Andersson; Roger Henriksson; A Tommy Bergenheim; Maria Feychting; Stefan Lönn; Anders Ahlbom; Johannes Schramm; Michael Linnebank; Kari Hemminki; Rajiv Kumar; Sarah J Hepworth; Amy Price; Georgina Armstrong; Yanhong Liu; Xiangjun Gu; Robert Yu; Ching Lau; Minouk Schoemaker; Kenneth Muir; Anthony Swerdlow; Mark Lathrop; Melissa Bondy; Richard S Houlston
Journal:  Nat Genet       Date:  2009-07-05       Impact factor: 38.330

7.  Adult-onset pulmonary fibrosis caused by mutations in telomerase.

Authors:  Kalliopi D Tsakiri; Jennifer T Cronkhite; Phillip J Kuan; Chao Xing; Ganesh Raghu; Jonathan C Weissler; Randall L Rosenblatt; Jerry W Shay; Christine Kim Garcia
Journal:  Proc Natl Acad Sci U S A       Date:  2007-04-25       Impact factor: 11.205

8.  Population structure and eigenanalysis.

Authors:  Nick Patterson; Alkes L Price; David Reich
Journal:  PLoS Genet       Date:  2006-12       Impact factor: 5.917

Review 9.  The AID/APOBEC family of nucleic acid mutators.

Authors:  Silvestro G Conticello
Journal:  Genome Biol       Date:  2008-06-17       Impact factor: 13.583

10.  Population substructure and control selection in genome-wide association studies.

Authors:  Kai Yu; Zhaoming Wang; Qizhai Li; Sholom Wacholder; David J Hunter; Robert N Hoover; Stephen Chanock; Gilles Thomas
Journal:  PLoS One       Date:  2008-07-02       Impact factor: 3.240

View more
  219 in total

1.  Mapping of the UGT1A locus identifies an uncommon coding variant that affects mRNA expression and protects from bladder cancer.

Authors:  Wei Tang; Yi-Ping Fu; Jonine D Figueroa; Núria Malats; Montserrat Garcia-Closas; Nilanjan Chatterjee; Manolis Kogevinas; Dalsu Baris; Michael Thun; Jennifer L Hall; Immaculata De Vivo; Demetrius Albanes; Patricia Porter-Gill; Mark P Purdue; Laurie Burdett; Luyang Liu; Amy Hutchinson; Timothy Myers; Adonina Tardón; Consol Serra; Alfredo Carrato; Reina Garcia-Closas; Josep Lloreta; Alison Johnson; Molly Schwenn; Margaret R Karagas; Alan Schned; Amanda Black; Eric J Jacobs; W Ryan Diver; Susan M Gapstur; Jarmo Virtamo; David J Hunter; Joseph F Fraumeni; Stephen J Chanock; Debra T Silverman; Nathaniel Rothman; Ludmila Prokunina-Olsson
Journal:  Hum Mol Genet       Date:  2012-01-06       Impact factor: 6.150

2.  Unraveling genes, hormones, and breast cancer.

Authors:  Jonine D Figueroa; Louise A Brinton
Journal:  J Natl Cancer Inst       Date:  2012-04-03       Impact factor: 13.506

3.  Distribution of allele frequencies and effect sizes and their interrelationships for common genetic susceptibility variants.

Authors:  Ju-Hyun Park; Mitchell H Gail; Clarice R Weinberg; Raymond J Carroll; Charles C Chung; Zhaoming Wang; Stephen J Chanock; Joseph F Fraumeni; Nilanjan Chatterjee
Journal:  Proc Natl Acad Sci U S A       Date:  2011-10-14       Impact factor: 11.205

4.  Simultaneously testing for marginal genetic association and gene-environment interaction.

Authors:  James Y Dai; Benjamin A Logsdon; Ying Huang; Li Hsu; Alexander P Reiner; Ross L Prentice; Charles Kooperberg
Journal:  Am J Epidemiol       Date:  2012-07-06       Impact factor: 4.897

5.  Inference from a multiplicative model of joint genetic effects for [corrected] ovarian cancer risk.

Authors:  Sholom Wacholder; Summer S Han; Clarice R Weinberg
Journal:  J Natl Cancer Inst       Date:  2010-12-17       Impact factor: 13.506

6.  Impact of smoking status at diagnosis on disease recurrence and death in upper tract urothelial carcinoma.

Authors:  Behfar Ehdaie; Helena Furberg; Emily Craig Zabor; Jamie S Ostroff; Shahrokh F Shariat; Bernard H Bochner; Jonathan A Coleman; Guido Dalbagni
Journal:  BJU Int       Date:  2012-05-29       Impact factor: 5.588

7.  Evaluation of a two-step iterative resampling procedure for internal validation of genome-wide association studies.

Authors:  Guolian Kang; Wei Liu; Cheng Cheng; Carmen L Wilson; Geoffrey Neale; Jun J Yang; Kirsten K Ness; Leslie L Robison; Melissa M Hudson; Deo Kumar Srivastava
Journal:  J Hum Genet       Date:  2015-09-17       Impact factor: 3.172

8.  Response.

Authors:  Jonine D Figueroa; Ludmila Prokunina-Olsson; Stella Koutros; Montserrat Garcia-Closas; Stephen Chanock; Debra T Silverman; Nathaniel Rothman
Journal:  J Natl Cancer Inst       Date:  2016-02-07       Impact factor: 13.506

9.  The association between rs9642880 gene polymorphism and bladder cancer risk: a meta-analysis.

Authors:  Jingyuan Tang; Xiao Li; Xuping Jiang; Weizhang Xu; Zhen Xu; Wei Wang; Bianjiang Liu; Qiang Lv; Wei Zhang
Journal:  Int J Clin Exp Med       Date:  2015-11-15

10.  Association between CCNE1 polymorphisms and the risk of breast cancer in a sample of southeast Iranian population.

Authors:  Shadi Amininia; Mohammad Hashemi; Mahboubeh Ebrahimi; Mohammad Ali Mashhadi; Seyed Mehdi Hashemi; Mohsen Taheri; Saeid Ghavami
Journal:  Med Oncol       Date:  2014-08-27       Impact factor: 3.064

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.