Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Supplemental Materials and Methods Patients We used nine case-control series, in total 1419 bladder cancer cases and 1758 controls that have been collected by the IfADo and its cooperation partners from 1995 to 2010. The sample collection was approved by the local Ethics Committee and by the IRB (institutional review board). Cases and controls that were younger than 20 years of age were excluded from the study groups. Hungary The Hungary case-control series contains 263 bladder cancer cases and 66 controls from the Department of Urology, Semmelweis University, Budapest. All cases and controls are Caucasians, which were confirmed by questionnaire-based documentation of nationality. The median age at diagnosis was 70 (range 27-95) years. 60% of the participants were males. The controls (80% males) were cancer free. Data were collected from 2004 to 2006. Data on tumour stage and grade were obtained through the cancer registry. Controls without malignant disease were frequency-matched for age (time of examination) with the cases. Data collected in cases and controls include age, gender, a documentation of occupational activities and exposures to known or suspected occupational bladder carcinogens and lifetime smoking habits. East Germany The Wittenberg case-control series (Lutherstadt Wittenberg bladder cancer study) as described [S1] was used. In brief, 217 patients with a confirmed bladder cancer from the Department of Urology, Paul Gerhardt Foundation, Lutherstadt Wittenberg, 1 Germany, were included. Patients were enrolled from December 1995 to January 1999. The median age at diagnosis was 66 (range 20-91) years. 86% of the participants were males. Controls (N=200, 86% males) were from the same department of urology, but were admitted for treatment of benign urological diseases. Exclusion criteria were a malignant disease in the medical history or a missing written informed consent. All cases and controls were Caucasians, which were confirmed by questionnaire-based documentation of nationality. Data were collected from July 2000 to May 2005. Cases and controls were matched for age. Data collected for cases and controls include age, gender, a complete documentation of occupational activities performed at least for six months, documentation of work places with known bladder cancer risk over the entire working life, exposures to known or suspected occupational bladder carcinogens, lifetime smoking habits, family history of bladder cancer, numbers of urinary infections treated by drugs during the previous 10 years, place of birth and places of residency for more than 10 years. In the case of bladder cancer cases, data on tumour staging, grading and treatment were taken from the records. Bladder cancer was diagnosed from July 1979 to January 1999. West Germany West Germany-ongoing case-control series (W. Germany-ongoing) The West Germany ongoing case-control series contains bladder cancer cases and controls from the Department of Urology, St.-Josefs-Hospital Dortmund-Hörde, the Department of Urology, Klinikum Dortmund, the Department of Urology, Lukasklinik Neuss, the Department of Urology at the Heinrich-Heine University of Düsseldorf and from the department of Urology at the Johannes Gutenberg University of Mainz, Germany. All cases and controls are Caucasians, which was confirmed by 2 questionnaire-based documentation of nationality. Data on tumour stage and grade were obtained through the cancer registry. All study groups are still ongoing. Exclusion criterion was a missing written informed consent. Controls were frequencymatched for age (time of examination) with the cases. Data collected for cases and controls include age, gender, a complete documentation of occupational activities performed at least for six months, documentation of work places with known bladder cancer risk over the entire working life, exposures to known or suspected occupational bladder carcinogens, lifetime smoking habits, family history of bladder cancer, numbers of urinary infections treated by drugs during the previous 10 years, place of birth and places of residency for more than 10 years. Dortmund bladder cancer study, St.-Josefs-Hospital Dortmund-Hörde, Germany The case-control series consists of 133 patients with a confirmed bladder cancer from the Department of Urology, St.-Josefs-Hospital Dortmund-Hörde, located in an area of former coal, iron and steel industries and 142 controls from the same Department of Urology, admitted for treatment of benign urological diseases, enrolled from July 2009 to July 2010. The median age at diagnosis was 71 (range 35-89) years. 77% of the participants were males. The 142 control individuals (70% males) were cancer free and frequency-matched for age with the cases (median age 67, range 22-99). Dortmund bladder cancer study, Klinikum Dortmund, Germany Thirty-two bladder cancer cases and five controls from the Department of Urology, Klinikum Dortmund, Germany, located in an area of former coal, iron and steel industries, enrolled from July 2007 to July 2010 were included. The median age at diagnosis was 67 (range 40-84) years. 71% of the participants were males. Data 3 were collected from July 2007 to April 2010. The five controls (three males) were cancer free (median age 70, range 65-83). Neuss bladder cancer study, Lukasklinik Neuss, Germany The ongoing case-control series consists of 96 bladder cancer cases and two controls from the Department of Urology, Lukasklinik Neuss, Germany. The median age at diagnosis was 74 (range 26-93) years. 77% of the participants were males. Data on tumour stage and grade were obtained through the cancer registry. The two male control individuals (age 64 and 73) were cancer free. Data was collected from June 2009 to July 2010. Düsseldorf bladder cancer study, Heinrich-Heine University, Germany The ongoing case-control series consists of 39 bladder cancer cases and 15 controls from the department of Urology at the Heinrich-Heine University of Düsseldorf, Germany. The median age at diagnosis was 70 (range 27-95) years. 82% of the participants were males. The controls (93% males) were cancer free (median age 68, rage 27-85). Data was collected from November 2009 to July 2010. Mainz bladder cancer study, Johannes Gutenberg University, Germany Eighteen bladder cancer cases and nine controls from the department of Urology at the Johannes Gutenberg University of Mainz, Germany, were included. The median age at diagnosis was 63 (range 37-81) years. 72% of the participants were males. Data on tumour stage and grade were obtained through the cancer registry. The nine control individuals (78% male) were cancer free (median age 68, range 49-71). Data was collected from January 2010 to July 2010. 4 West Germany–industrial burdened case-control series (W. Germany-industrial) The West Germany – industrial burdened case-control series (W. Germany industrial) consists of two independent case groups and one control cohort. Dortmund hospital based case-series (DO-hospital) Eighty-five patients with confirmed bladder cancer from the Department of Urology, Klinikum Dortmund, Germany, located in an area of former coal, iron, and steel industries, were included. Exclusion criterion was a missing written informed consent. Data were collected from November 1993 to June 1995. All items of the questionnaire applied in Dortmund were also included in the extended version of the questionnaire presented to the cases and controls in the Lutherstadt Wittenberg group. Bladder cancer was diagnosed from July 1981 to June 1995. The median age at diagnosis was 67 (range 45-84) years. 85% of the participants were males. Dortmund occupational case-control series (DO-occupational) The Occupational case-series (study on patients with suspected occupational bladder cancer) as described [S1] was used. Details of the ongoing study on 331 suspected cases of occupational bladder cancer from Germany, mainly from the Federal State of North Rhine-Westphalia, reported to the authorities and surveyed for recognition of an occupational disease (in Germany named “Berufskrankheit BK 1301”) from February 1996 to July 2010 were reported recently. The individuals were suspected to be exposed to occupational bladder carcinogens, mostly carcinogenic aromatic amines, azo dyes based on carcinogenic aromatic amines or polycyclic aromatic hydrocarbons. According to the situation at work places in former decades, 93% of the patients were males. All patients were Caucasians. The median age at diagnosis was 61 (range 32-84) years. All surveyed bladder cancer patients gave 5 informed consent for genotyping of enzymes relevant for bladder cancer and Nacetyltransferase 2 phenotyping by caffeine metabolites. Therefore, blood and urine samples were also obtained. Occupational and concurrent non-occupational risk factors for bladder cancer were explored by three medical specialists in a personal interview. Dortmund controls (DO-controls) The control group consists of persons from the greater Dortmund area, Germany, who did not present a malignancy in the medical history. Dortmund is a city with approximately 600,000 inhabitants located in North Rhine-Westphalia, which is the westernmost and - in terms of population and economic output - the largest Federal State of Germany. Briefly, 181 patients of the Department of Surgery of the Klinikum Dortmund without any malignancy in the medical history, 228 patients without malignancies from the St. Elisabeth Hospital in Iserlohn, Germany, 21 persons with suspected occupational diseases other than bladder cancer, 95 former hard coal miners with pneumoconiosis recognized for an occupational disease surveyed for the course of their disease, 323 persons participating in an ongoing study on the impact of enzyme polymorphisms on selected brain functions as well as 56 staff of the Dortmund institute serving as controls in different studies were included. In total, 904 individuals were combined to a control group representing inhabitants of the greater Dortmund area. The median age at examination was 68 (range 20-91 years) and 51 % of the controls were males. Pakistan The Pakistan case-control series contains 103 bladder cancer cases, 100 controls from the Sindh Institute of Urology and Transplantation, Civil Hospital, Karachi and 6 125 population based controls. All cases and controls are Pakistani, which was confirmed by questionnaire-based documentation of nationality. The median age at diagnosis was 61 (range 24-82) years. 87% of the participants were males. The controls (80% males) were cancer free. Data were collected from April 2003 to January 2004. Data on tumour stage and grade were obtained through the cancer registry. Controls without malignant disease were frequency-matched for age (time of examination) with the cases. Data collected in cases and controls include age, gender, a documentation of occupational activities and exposures to known or suspected occupational bladder carcinogens and lifetime smoking habits. Venezuela The Venezuelan case-control series contain 102 bladder cancer cases from Departments of Urology, University Hospital at Central University, Caracas; Domingo Luciani Hospital from the Venezuelan Institute of Social Security, Caracas; Oncologic Hospital “Padre Machado”, Caracas, and Policlínica Metropolitana, Caracas. A total of 190 controls were from the same departments of urology, as well as from the Medical Faculty at Central University, Caracas, and all were free of any type of cancer. All cases and controls are Venezuelan; though some of the patients were residents in Venezuela but were of different origin, mainly Colombian, Ecuadorian, Peruvian, Italian and Portuguese which was confirmed by questionnaire-based documentation of nationality. The median age at diagnosis was 60 (range 39-87) years. 68% of the participants were males. The controls (41% males) were cancer free. Data were collected from December 2006 to November 2009, the study is still ongoing. Data on tumour stage and grade were obtained by the cancer registry. Controls without malignant disease were frequency-matched for age (time of examination) with the cases. Data collected in cases and controls include age, 7 gender, a complete documentation of occupational activities performed at least for six months, documentation of work places with known bladder cancer risk over the entire working life, exposures to known or suspected occupational bladder carcinogens, lifetime smoking habits, family history of bladder cancer, numbers of urinary infections treated by drugs during the previous 10 years, place of birth and places of residency for more than 10 years. In the case of bladder cancer cases, data on tumour staging, grading and treatment were taken from the records. The local ethics committees approved the study plan and design. Subgroups phenotyped for NAT2 or genotyped on SNP chip A subgroup of 344 Caucasians was phenotyped for NAT2 using the caffeine test consisting of 267 cases from the Dortmund occupational case-control series, 38 cases from the Dortmund hospital based case-control series and 39 healthy controls from the Dortmund control group (IfADo staff). A further subgroup of 308 German cases (211 East Germany cases and 96 Dortmund occupational cases) was genotyped on the Affymetrix 5.0 SNP chip. Analysis of polymorphisms For differentiating between the homozygous frequent (A/A), homozygous variant (G/G) and heterozygous (A/G) form of the sequence of interest venous blood was taken and frozen at -20°C [S2]. DNA was isolated out of leucocytes using a QIAamp DNA blood maxi kit (Qiagen, Hilden, Germany) according to the manufacturer’s protocol [S3]. DNA concentrations were determined using a NanoDrop ND-1000 UV/Vis-spectrophotometer (PEQLAB Biotechnologie GMBH, Erlangen, Germany). Analysis of G/A substitution (rs1495741) on chromosome 8p23, position 18272881, 8 and differentiating between the homozygous [A/A], homozygous [G/G] and heterozygous [A/G] form of the sequence: GCTGAAGGATGATTTTCATAATAAT[A/G]TGGGCATTCACAGTAGCTTCAGGGC was performed on an ABI7500 Sequence Detection System with the use of TaqMan ® assays (Applied Biosystems, Darmstadt, Germany). Analysis of data was performed according to the manufacturer’s instructions (Applied Biosystems 7300/7500/7500, fast Real-Time PCR System Allelic Discrimination Getting Started Guide). NAT2 genotyping NAT2 genotyping was performed using PCR- and RFLPbased standardized methods [S4-S6]. A total of seven SNPs, which are adequate to genotype Caucasians for NAT2 [S4], were investigated, namely rs1801279 (G191A), rs1041983 (C282T), rs1801280 (T341C), rs1799929 (C481T), rs1799930 (G590A), rs1208 (A803G) and rs1799931 (G857A). Lymphocyte DNA is isolated from a sample of human blood. Amplification of two fragments of DNA with 442 and 559 bp (base pairs) is achieved by means of PCR (polymerase chain reaction). The amplificate from the first PCR is cleaved using three different restriction enzymes, and that of the second PCR with four different restriction enzymes. After subsequent gel electrophoresis with the addition of ethidium bromide, the various DNA fragments are detected in UV light. The results are documented by photography, and the alleles are assigned according to an evaluation scheme. NAT2 phenotyping (caffeine test) For phenotyping NAT2 the caffeine test is applied [S7-S15]. The ratio of the caffeine metabolites 9 1-methylxanthine (1-MX) and 5-acetylamino-6-formylamino-3- methyluracil (AFMU) to each other is determined in urine samples voided two and four hours after the administration of caffeine in form of two cups of coffee. For this purpose the analytes were separated from the urine sample by liquid-liquid extraction. The quantitative determination of both caffeine metabolites is carried out by means of high performance liquid chromatographic separation with UV detection. The standard addition procedure is used in this case. The ratios enable differentiation at a cut-off of 0.85 between so-called slow (<0.85) and rapid acetylators (0.85). SNP chip analysis All 308 samples were genotyped on the Affymetrix Genome-Wide Human SNP Array 5.0 according to the manufacturer's protocols. Genotype calling was performed using the CRLMM-v2 algorithm (Corrected Robust Linear Model with Maximum-likelihood based distances, [S16]). A call was not produced when the posterior probability of a correct call was less than 0.95 for all three genotypes. Samples with a signal-to-noise ratio computed by CRLMM smaller than five were excluded from the further analysis. We also removed all SNPs with a call rate of less than 95% or a CRLMM quality score of less than 0.7 as well as all monomorphic SNPs, leading to 294 samples and 392,582 SNPs. The control cohort consisting of 936 controls from the KORA-gen [S17] and the PopGen [S18] studies were measured with the Affymetrix Genome-Wide Human SNP Array 6.0. All SNPs having a call rate larger than 95%, showing a minor allele frequency larger than 1%, being in Hardy-Weinberg Equilibrium (HWE) (p > 0.01), and showing no significant differences in the allele frequencies between the control populations (p < 0.001) were selected as described in Steffens et al. [S19]. The remaining 620,711 SNPs were matched against the 394,860 SNPs from the case 10 cohort to identify the SNPs available for both cases and controls. Thus 312,694 SNPs were available for the linkage disequilibrium (LD) analysis. Statistical analysis Cigarette smoking was defined as non-smokers, former smokers, i.e. smokers that quit smoking at least one year before diagnosis (cases) or examination (controls), and current smokers. Age was defined as “age at diagnosis” for the cases and “age at examination” for the control persons. Deviations from HWE were checked for each of the eight SNPs in each study group and separately for cases and controls using exact chi-square tests. The NAT2 haplotype pairs were determined from the seven NAT2 SNPs using PHASE, v2.1.1 [S20-S22] as described earlier [S23]. The results of the best reconstruction were used in accordance with the nomenclature of the Nacetyltransferases [S24] to derive the acetylation status. This genotype derived acetylation status was denoted as 7-SNP genotype. The sensitivity, specificity and false discovery rate were determined with respect to the 7-SNP genotype and with respect to the phenotype for all single, nonmonomorphic SNPs and for all their combinations. The arithmetic mean of the sensitivity and specificity was used to discover optimal combinations of SNPs. The sum of slow alleles over all combined SNPs was considered to discriminate between slow and rapid acetylators using the mean of sensitivity and specificity to determine the cut-off point. The ROC curve was plotted using the SPSS Statistics software, version 18.0 (SPSS Inc., Chicago, Illinios, USA). Exact Wald tests for the equality of proportions were carried out comparing the sensitivity, specificity and false discovery rate (FDR) of the tagging SNP, the 7-SNP and the 2-SNP genotype with respect to the phenotype. Spearman's correlation coefficients (R) were calculated comparing 11 the genotypes. All tests, calculations and plots were performed using the software package SAS/STAT®, version 9.2 [S25], if not indicated otherwise. The level of significance was = 0.05 for all tests and confidence intervals. The linkage disequilibrium (LD) plot of r² based on HapMap CEU data version 3, release 2, for a region covering the NAT2 haploblock (chromosome 8, 18.290.000 18.329.000) was obtained using the Haploview V4.2 program [S26]. The LD plot of the present data was based on 308 German cases analysed by the AffymetrixGenome-Wide Human SNP Array 5.0 and supplemented by the missing data of five NAT2 SNPs rs1801279 (G191A), rs1041983 (C282T), rs1801280 (T341C), rs121208 (A803G), rs1700031 (G857A) and the tagSNP rs1495741. Furthermore, the genotypes of NAT2 SNPs rs1799929 (C481T) and rs1799930 (G590A) determined by the SNP chip are substituted by the RT-PCR derived genotypes. Pairwise r² values were plotted for a region covering the NAT2 haploblock (chromosome 8, 18.186.200 - 18.433.000). The software R, version 2.10.1 [S27] and the software package trio, version 1.1.12 [S28] were used to determine the LD measures r² and D' among the eight investigated SNPs and for the LD plot of the present data. 12 References [S1] Golka K, Hermes M, Selinski S, Blaszkewicz M, Bolt HM, Roth G et al. Susceptibility to urinary bladder cancer: relevance of rs9642880[T], GSTM1 0/0 and occupational exposure. Pharmacogenet Genomics 2009;19:903-6. [S2] Saravana Devi S, Vinayagamoorthy N, Agrawal M, Biswas A, Biswas R, Naoghare P et al. Distribution of detoxifying genes polymorphism in Maharastrian population of central India. Chemosphere 2008;700:1835-9. [S3] Arand M, Mühlbauer R, Hengstler J, et al. A multiplex polymerase chain reaction protocol for the simultaneous analysis of the glutathione S-transferase GSTM1 and GSTT1 polymorphisms. Anal Biochem 1996;236:184-6. [S4] Blaszkewicz M, Dannappel D, Thier R, Lewalter J. N-acetyltransferase 2 (genotyping). In: Angerer J, Müller M, Weiss T et al., eds. Analyses of hazardous substances in biological materials, vol 9. Special issue: Markers of susceptibility. Weinheim: Wiley-VCH; 2004. pp. 135-163. [S5] Cascorbi I, Brockmöller J, Mrozikiewicz PM, Bauer S, Loddenkemper R, Roots I. Homozygous rapid arylamine N-acetyltransferase NAT2 genotype as susceptibility factor for lung cancer. Cancer Res 1996;56:3961-6. [S6] Cascorbi I, Drakoulis N, Brockmöller J, Maurer A, Sperling K, Roots I. Arylamine Nacetyltransferase (NAT2) mutations and their allelic linkage in unrelated Caucasian individuals: correlation with phenotypic activity. Am J Hum Genet 1995;57:581-92. [S7] Rihs HP, John A, Scherenberg M, Seidel A, Brüning T. Concordance between the deduced acetylation status generated by high-speed: real-time PCR based NAT2 genotyping of seven single nucleotide polymorphisms and human NAT2 phenotypes determined by a caffeine assay. Clin Chim Acta 2007;376:240-3. [S8] Bolt HM, Selinski S, Dannappel D, Blaszkewicz M, Golka K. Re-investigation of the concordance of human NAT2 phenotypes and genotypes. Arch Toxicol 2005;79:196-200. 13 [S9] Blaszkewicz M. N-Acetyltransferase 2 (phenotyping: caffeine test) In: Angerer J, Müller M, Weiss T et al., eds. Analyses of hazardous substances in biological materials, vol 9. Special issue: Markers of susceptibility. Weinheim: Wiley-VCH; 2004. pp. 165-182. [S10] Röhrkasten R, Raatz P, Kreher RP, Blaszkewicz M. Synthesis of the caffeine metabolites 5-acetylamino-6-formylamino-3-methyluracil (AFMU) and 5-acetylamino-6- amino-3-methyluracil (AAMU) on a preparative scale. Z Naturforsch 1997;52b:1526-32. [S11] Golka K, Prior V, Blaszkewicz M, Cascorbi I, Schöps W, Kierfeld G et al. Occupational history and genetic N-acetyltransferase polymorphism in urothelial cancer patients of Leverkusen, Germany. Scand J Work Environ Health 1996;22:332-8. [S12] Tang BK, Kadar D, Kalow W. An alternative test for acetylator phenotyping with caffeine. Clin Pharmacol Ther 1987;42:509-13. [S13] Rankin RB, Hudson SA, Fell AF. Caffeine as a potential indicator for acetylator status. J Clin Pharm Ther 1987;12:47-51. [S14] Grant DM, Tang BK, Kalow W. A simple test for acetylator phenotype using caffeine. Br J Clin Pharmacol 1984;17:459-64. [S15] Grant DM, Tang BK, Kalow W. Polymorphic N-acetylation of a caffeine metabolite. Clin Pharmacol Ther 1983;33:355-9. [S16] Carvalho BS, Louis TA, Irizarry, RA. Quantifying Uncertainty in Genotype Calls. Bioinformatics 2010;26:242-8. [S17] Wichmann HE, Gieger C, Illig T. KORA-gen - Resource for population genetics, controls and a broad spectrum of disease phenotypes. Gesundheitswesen 2005;67(Suppl.1):155-66. [S18] Krawczak M, Nikolaus S, von Eberstein H, Croucher PJ, El Mokhtari NE, Schreiber S. PopGen: Population-based recruitment of patients and controls for the analysis of complex genotype-phenotype relationships. Community Genetics 2006;9:55-61. [S19] Steffens M, Becker T, Sander T, Fimmers R, Herold C, Holler DA et al. Feasible and successful: genome-wide interaction analysis involving 1.9 x 1011 pair-wise interaction tests. Human Heridity 2010;69:268-284. 14 [S20] Stephens M, Scheet P. Accounting for decay of linkage disequilibrium in haplotype inference and missing-data imputation. Am J Hum Genet 2005;76:449-62. [S21] Stephens M, Donnelly P. A comparison of Bayesian methods for haplotype reconstruction. Am J Hum Genet 2003;73:1162-9. [S22] Stephens M, Smith NJ, Donnelly P. A new statistical method for haplotype reconstruction from population data. Am J Hum Genet 2001;68:978-89. [S23] Golka K, Blaszkewicz M, Samimi M, Bolt HM, Selinski S. Reconstruction of Nacetyltransferase 2 haplotypes using PHASE. Arch Toxicol 2008;82:265-70. [S24] Arylamine N-acetyltransferase Nomenclature Committee. Latest update November 1, 2010. http://www.louisville.edu/medschool/pharmacology/NAT.html [S25] SAS/STAT® software, version 9.2. Copyright © 2002-2008, SAS Institute Inc. Cary, NC, USA. [S26] Barrett JC, Fry B, Maller J, Daly MJ. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 2005;21:263-5. [S27] R Development Core Team. R: A language and environment for statistical computing, R Foundation for Statistical Computing, Vienna, Austria, 2008. [S28] Schwender H, Li Q. trio: Detection of disease-associated SNP interactions in caseparent trio data. R package version 1.1.12, 2010. http://CRAN.R-project.org/package=trio. 15