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Environmental and Occupational Health Sciences Institute, University of Medicine and Dentistry of New Jersey, Piscataway, New Jersey 08854 [S. G.]; Genetics Research Institute, Milan, Italy [S. G., L. G.]; Karolinska Institute, Stockholm, Sweden [A-K. A., A. Ra., M. I-S., I. P.]; National Toxicology Program, Jefferson, Arkansas [C. A.]; University of Aarhus, Aarhus, Denmark [H. A., J. L. A.]; Universitè d’Auvergne, Clermont-Ferrand, France [H. B.]; Odense University Hospital, Odense, Denmark [L. B.]; INSERM, Villejuif, France [S. B., C. B., I. S.]; IARC, Lyon, France [P. B.]; University of Ljubljana, Ljubljana, Slovenia [K. B., V. D.]; Universitatklinikum Charite-Humboldt, Universitat zu Berlin, Berlin, Germany [J. B.]; Ernst Moritz Arndt University, Greifswald, Greifswald, Germany [I. C.]; Fox Chase Cancer Center, Philadelphia, Pennsylvania [M. L. C., C. M. D.]; Universitè de Bordeaux II, Bordeaux, France [C. C.]; University of Newcastle, Newcastle, United Kingdom [A. D.]; Istituto Medicina del Lavoro, Perugia, Italy [M. D.]; Keele University, Staffordshire, United Kingdom [A. F., R. C. S.]; National Institute of Occupational Health, Oslo, Norway [A. Ha., D. R.]; University of Louisville, Louisville, Kentucky [D. W. H.]; National Cancer Institute, Rockville, Maryland [A. Hil.]; Finnish Institute of Occupational Health, Helsinki, Finland [A. Hir.]; Chang Gung University, Tao-yuan, Taiwan [L-L. H.]; P. J. 
afárik University, Ko
ice, Slovakia [I. K., J. Sa.]; Seoul National University College of Medicine, Seoul, Korea [D. K.]; Kyoto University School of Public Health, Kyoto, Japan [M. K., K. N.]; Kyushu University, Fukuoka, Japan [C. K.]; Institut de Pathologie Liége-Belgium, Liege, Belgium [P. K., L. R.]; H. Lee Moffit Cancer Center and Research Institute, Tampa, Florida [P. L.]; University of Hawaii-Honolulu, Honolulu, Hawaii [L. L. M.]; Universidade de Lisboa, Lisboa, Portugal [M. C. L.]; University Hospital, Nijmegen, the Netherlands [E. M. M. v. L., W. H. M. P.]; National Institute for Environmental Health Sciences, Research Triangle Park, North Carolina [S. L.]; University Hospital Maastricht, Maastricht, the Netherlands [J. J. M.]; Centre René Gauducheau Nantes, Nantes-Saint Herblain, France [C. M. M.]; Yao Municipal Hospital, Osaka, Japan [S. M.]; Oregon Health Sciences University, Portland, Oregon [V. N-S.]; Kanazawa University, Kanazawa-Ishikawa, Japan [Y. O.]; Vanderbilt University, Nashville, Tennessee [F. F. P.]; Mario Negri Institute, Milan, Italy [R. P.]; University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania [T. R.]; Deutsches Krebforschungszentrum, Heidelberg, Germany [A. Ri.]; University of Pittsburgh, Pittsburgh, Pennsylvania [M. R.]; National Institute of Environmental Health, Budapest, Hungary [B. S.]; Lund University, Lund, Sweden [J. Se.]; Georgetown University Medical Center, Washington, D.C. [P. G. S.]; University of Oxford, Oxford, United Kingdom [E. S.]; Hôpital Sainte-Justine, Montreal, Quebec, Canada [D. S.]; Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan [H. S.]; Hospital Clinic Provincial, Barcelona, Spain [J. T-F.]; Università degli Studi di Torino, Torino, Italy [P. V.]; University of Southern California/Norris Cancer Center, University of Southern California, Los Angeles, California [M. C. Y.]; and Ospedale Maggiore IRCCS-Direzione Scientifica, Milan, Italy [E. T.]
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Abstract |
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 Top Abstract IntroductionMaterials and MethodsResultsDiscussionReferences |
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Introduction |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
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Over recent years, numerous studies using case-control approaches and generally based on 100–300 cases have examined the association of one or a few polymorphisms with cancer risk (1 , 5, 6, 7, 8) . Although progress has been made, many of these studies have produced conflicting results, in part because of the low penetrance of this category of susceptibility genes, resulting in insufficient power. Whereas the precise penetrance of these genes is not known (see other publications from the GSEC3 ), it is clear that odds ratios of allelic variants rarely exceed 2–3 in the general population, which makes sample size a critical issue in case-control studies assessing the role of these genes in cancer.
To clarify the role of individual and composite genotypes at the most interesting and/or highly studied loci in cancer susceptibility, we began, in 1996, to gather data from investigators around the world on the frequencies of genetic polymorphisms of genes associated with carcinogen metabolism. A more detailed description of this project, the International Project on GSEC, has been recently published (9) . It has been demonstrated in many studies that allele frequencies of the metabolic genes are not randomly distributed throughout the human population but follow diverse ethnic and/or geographic-specific patterns (10, 11, 12, 13) . However, no single published study to date on these gene polymorphisms has been large enough to precisely define the true population-specific frequency of most of these alleles in normal control populations. Furthermore, it has not yet been possible to determine whether other demographic variables are associated with specific allele frequencies. In this work, the contributed data from 52 laboratories representing 73 separate studies (both published and unpublished) have been pooled to characterize allele frequencies in 8 metabolic genes in a very large sample (15,843) of control subjects (defined as those individuals who served as the comparison group for subjects with cancer in case-control studies or groups of healthy individuals studied for other purposes) from different regions of the world.
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Materials and Methods |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
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2 test was used. Multivariate analysis was used to assess the independent contribution of demographic factors such as race, age, sex, and national origin on allele frequency. Frequencies of gene polymorphisms were analyzed only when more than one study and more than 100 subjects were included for that polymorphism or allele. The great majority of the data were generated by PCR analysis, although in a few older studies, some of the genotypes were determined by Southern blot analysis. In all cases, results were confirmed by PCR.
For CYP1A1, CYP2E1 and NAT2, all genotypes were in HWE with P > 0.05 by 2 test. Each individual study or data set was tested for HWE. Only one small data set received by the GSEC study was not included, because data were found not to be in HWE, and allele frequencies were far outside the expected ranges.
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Results |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
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Table 1
shows the number of studies and the number of subjects according to their ethnicity for each gene contained in the database. Table 2
lists all of the data on the frequencies of the common polymorphisms for CYP1A1 and CYP2E1. Some of these data are from studies where only one polymorphism (for example only the Msp1 RFLP in CYP1A1) was examined. Because not all studies included analysis of both polymorphisms for each individual, not all of these data could be used for determining allele frequencies, which depend on information from two major polymorphic sites for each individual for CYP1A1 and CYP2E1. The data shown in the rest of the tables include only those individuals for whom polymorphism analysis was done on both sites. However, even in these cases, a true haplotype is not available because other less common polymorphic sites in these genes were usually not analyzed. For several genes (CYP1A1, CYP2E1, GSTM1, and GSTT1), there were sufficient data from more than one ethnic group to make comparisons between such groups as shown in Table 3
. Frequencies of most of the alleles exhibited large differences between ethnic groups, especially for the CYP genes between Asians and Caucasians. For some of the genes, data was available only for Caucasians. For GSTP, EPHX, and CYP2D6, the database contains relatively sparse information at the present time, and frequencies for these genes are the most likely to be imprecise. This may be particularly true for CYP2D6, which is a complex gene with many alleles, only some of which have been included in the current database. More accurate estimates of CYP2D6 allele frequencies may be found in other publications; therefore, this gene has not been included in Table 3
. The range of values found in individual studies shown in Table 3
gives some idea of the degree of heterogeneity of the contributed data sets. As discussed in "Materials and Methods," the individual data sets were similar to the means presented here, and all were in HWE.
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. For the CYP1A1*2A allele, German and Dutch populations had a significantly lower frequency than the rest of Europe and North America, and for GSTM1, Great Britain had a higher frequency of deletion than the rest of the Caucasian population taken together. Although the frequency of GSTM1 deletion in Portugal was also higher, this was not significant when compared to the rest of Europe and North America by 2 analysis. Three Scandinavian countries (Finland, Denmark, and Sweden) had a significant (2 = 21.2; P < 0.001) and substantially lower (30% less relative to the rest of Europe and North America) frequency of the GSTT1 deletion.
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. However, the numbers of subjects for each of these countries was quite small, making any conclusions regarding heterogeneity within the Asian group premature.
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, no differences in allele frequencies by sex were seen among Caucasians for any gene except for GSTT1. Men appeared to have a lower deletion frequency than women. When the data were adjusted in a multivariate model by country of origin, there was no difference for GSTT1 among Caucasians as a function of sex. Within the three Scandinavian countries, there was no difference in GSTT1 deletion frequency with sex. For Asians, no differences with sex were observed for GSTM1*0, GSTT1*0, and CYP1A1*2A. For GSTT1, the only data including women were from Singapore, therefore the data in Table 6
for GSTT1*0 in Asians by sex refer to Singapore only.
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. To better understand the source of the sex differences observed, multivariate analysis was used, and sex appeared to be the only significant variable for the observed difference in GSTM1 polymorphism frequency.
The age distribution among the controls is exhibited in Fig. 1
. Age data were missing for 1935 individuals. No differences were seen for any polymorphism in any of the genes for which sufficient information was available (GSTM1, GSTT1, and CYP1A1) in any racial group as a function of age. There appeared to be a trend toward higher rates of GSTT1 deletion with increasing age (data not shown), but this was not significant.
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, after adjusting for sex and geographic area in a multivariate analysis, we found that there was no association between control type and genotype in either case.
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. Genotype assignments were made only for those subjects with available data on all the major polymorphisms. For the NAT2 gene, genotypes were computed both using the data from almost 4000 subjects on the major allele groups (*5, 6, and 7) and from subtypes *5A, *5B, *5C, and *6A for a smaller set of subjects.
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. In no case were any significant deviations from expected allele combinations observed, suggesting that for these alleles, there is no linkage between any of the polymorphic alleles at these loci.
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Discussion |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
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Sufficient data for several genes were available to estimate genotype frequencies in Caucasian and, in some cases, Asian populations. As was true for the allele frequencies, the genotype distribution for CYP1A1 differed significantly between these two ethnic groups. In Asians and Africans, the so-called wild-type genotype CYP1A1*1/*1 is in fact present in less than half of the population, which, along with similar situations for other genes such as CYP2D6, calls into question the very concept of the wild-type in human genetics, as has been discussed previously (73) .
The frequency of the various NAT2 genotypes has not been reported previously in any single study using populations of this size, so this represents the first useful analysis of these frequencies. It should be noted that not all alleles were evaluated in this analysis because sufficient data were lacking to make any improvement over existing published values for such alleles.
In addition to providing basic information on allele and genotype frequencies, we were also able to test certain hypotheses concerning genetic heterogeneity among and between populations. Because of previously observed differences in allele frequencies as a function of race, the population was divided into three groups, Caucasians, Asians, and Africans. The latter group included mostly African Americans as well as Africans. The group of Asians included a small number of Asian Americans. It should be stressed here that racial and ethnic identification is a difficult task, especially in situations where considerable admixture has been known to occur, and misclassification of individuals of mixed ancestry is very likely. Furthermore, defining ethnicity or race is probably not a biologically plausible way to divide the human population in terms of genetic differences (74) . However, for the purposes of convenience and for hypothesis testing, we decided to perform the frequency analyses starting with conventional definitions of ethnicity. The often observed differences between population frequencies for the three major racial groupings were confirmed for most of the genes studied.
One of the hypotheses we examined was that the Caucasian population would be heterogeneous with respect to many of these alleles. We were able to test this hypothesis within the limits of the sample size for certain of the more commonly tested alleles. In general, there was very little heterogeneity among Caucasians, although we did find a small degree of heterogeneity between certain ethnic groups, with the largest and most significant example being the frequency of the GSTT1 homozygous deletion in people of Scandinavian origin. It is not yet clear whether the differences in CYP1A1*2A in the German and Dutch populations are due to true population differences or artifacts resulting from differences between laboratories. Furthermore, these differences were comparatively small and possibly not biologically meaningful; the same may be said for the difference in GSTM1 deletion in the British and Portuguese. A more interesting difference, which probably reflects true population heterogeneity, was seen for GSTT1 between Scandinavia and the rest of Europe and North America. This very clear 30% difference between Northern Europeans and Caucasians from the rest of Europe is not easily explained and may be important when comparing allele frequencies in case-control studies when subjects might be from different European origins. However, given the fact that allele frequencies did not vary very much among Caucasians, population stratification in studies of polymorphisms among European Americans is unlikely to be an important confounder (75) .
Although a few differences in polymorphic allele frequencies were seen as a function of sex or source of the population (hospital versus population or other controls), most of these differences proved to be due to confounding factors such as geographic origin. An example was that of GSTT1*0, which appeared to be higher in Caucasian women than men only because of the 10-fold prevalence of men in the Scandinavian studies. Multivariate analysis using the variables of sex, age, and country showed that the differences were only significant with respect to country and confirmed the lack of any effect of sex (as expected because none of these genes is located on the sex chromosomes) or source, with the exception of the difference in Africans for GSTM1 as a function of sex. This difference was statistically significant but difficult to explain biologically. It must be noted that the population used for this analysis was relatively small (479 subjects); therefore, this result must be confirmed with a larger sample size before being accepted as resulting from some factor other than chance. No significant differences were seen with age, despite an intriguing trend for GSTT1*0 to increase from childhood through maturity. We cannot speculate on the implications of a possible increase in GSTT1 deletion with age; however, in a separate study, some of the authors have found a significant increase in GSTT1 deletion among centenarians (76) . The general lack of a significant association between allele frequency and age may allow epidemiologists to rule out the possibility that these polymorphisms are determinants of overall survival. The lack of any effect of choice of controls is important for comparison of different case-control studies that use one or the other source for the control population. These results also suggest that the use of hospital controls in studies of metabolic gene polymorphisms does not introduce bias related to genotype frequencies, although this work does not address other potential problems that may occur with hospital controls.
Because genetic susceptibility to environmental diseases probably must involve more than a single gene, it is useful to know whether any of these gene polymorphisms might be in linkage disequilibrium with each other. For example, if the GSTM1 deletion and the CYP1A1*2B allele were found together in the same subject at a frequency higher than expected from the independent frequencies of each polymorphism alone, it could be indicative of a linkage between these alleles. We observed no such evidence for linkage disequilibrium for any of the possible double combinations of the eight alleles examined in noncancer controls. This is an important finding to serve as a control basis for analysis of such linkages in cancer cases. Of course, this is not a rigorous proof of the absence of linkage disequilibrium, and we have not tested for tri- or tetra-allelic disequilibrium. It should be noted that examples of possible linkage disequilibrium between certain metabolic genes were seen in earlier studies: NAT1*10 was found to be associated with NAT2*4 (77) . There were not sufficient data on NAT1 in the database to confirm this association.
In certain instances, the results presented here should be used with some caution. For example for CYP1A1, allele frequencies of the *2C allele are uncertain because there is still inconsistency in the results between different laboratories. In some laboratories, this allele is rarely or never seen, whereas in others, it is fairly common. This difference is almost definitely due to differences in laboratory methodology and should be resolved by interlaboratory exchanges of samples and methods. Although the population size used to make these estimates is larger than any previously used, for certain of the rarer alleles (such as NAT2*7A), the paucity of the available data makes it difficult to estimate either allele or genotype frequencies.
It should also be emphasized that for most instances, the allele and genotype frequencies presented here do not always consider the complete spectrum of variants at a locus, due to limitations in the available data. Rare or newer alleles that have not yet been extensively analyzed (such as CYP1A1*4, NAT2*14, and so forth) were not considered. For GSTM1*0 and GSTT1*0, currently used methodology is unable to detect heterozygotes reliably, and therefore most studies did not present data on GST heterozygous deletions. This makes calculation of the GST deleted allele difficult. Newer methods (see below) will allow for detection of the heterozygous deletion. Furthermore, there are two GSTM1 alleles, GSTM1A and GSTM1B (78) , which future analyses will have to take into account.
Among other limitations of this study is the fact that information on race and age was collected in different ways by each of the investigators and is therefore not standardized. This is unlikely to have any effect on the results regarding age because very small errors are expected, and no associations were seen with age. As far as race is concerned, it is certainly possible that some misclassification occurred, given the difficulty in making definitive assignments on race as discussed above. However, all cases where race was either unknown or unclear were excluded from the analysis.
Publication bias is always a possible limitation of combining data from various sources as in a typical meta-analysis. This may be less problematic in our work because unpublished data sets were also requested and included in the total data set.
Differences in laboratory techniques for analysis of genotype are probably not a major source of error, because most of the PCR-based techniques currently used for such assignments have become standardized. One exception noted above is the use of allele-specific versus restriction site PCR for detection of the CYP1A1 mutation 2455A>G in exon 7, which is contained in CYP1A1 alleles *2B and *2C. Furthermore, for NAT2, many of the commonly used PCR techniques do not assess all of the identified polymorphisms. Newer high-throughput techniques using fluorescent technologies or microarrays (79) will have the capacity to produce data on genotype much more efficiently than has been done to date, but standardization and common usage of these new methods have yet to be achieved. The analysis of polymorphisms in drug-metabolizing genes will have an important role in establishing a panel of single nucleotide polymorphisms that have known functional significance in post-genome analysis, not only in determining the role of xenobiotics in cancer, but also in other multifactorial disorders where environmental factors may be involved.
Because the information in the GSEC database continues to grow as more investigators become participants in the study, and new genes are added, it should be possible in the near future to update the results presented here and to be more certain of the true population frequencies. It is especially desirable that more data will be forthcoming from Asian and African populations because these have been relatively underrepresented thus far compared with data on Caucasians. With new methods of high-throughput analysis, DNA samples from very large cohorts (>100,000) may be used for detection of multiple allele frequencies in a very efficient manner. It will be interesting to compare frequencies determined by these methods with those reported here, which were generally determined using more standard PCR methods. Until such catalogues of allele frequencies from hundreds of thousands of subjects are available, this report presents the largest and most accurate estimate to date of these frequencies in healthy populations.
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Acknowledgments |
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Footnotes |
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1 Partially supported by European Commission Fund No. 96/CAN/33919. 
2 To whom requests for reprints should be addressed, at EOHSI, 170 Frelinghuysen Road, Piscataway, NJ 08854.
3 The abbreviations used are: GSEC, Genetic Susceptibility to Environmental Carcinogens; HWE, Hardy Weinberg equilibrium.
Received 12/20/00; revised 6/ 8/01; accepted 6/25/01.
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M. J. Gunter, M. A. Watson, A. S. Loktionov, P. Mitrou, T. Cecil, C. Macklin, C. Cardwell, D. T. Bishop, J. Primrose, W. S. Atkin, et al. No Association between Cytochrome P450 and Glutathione S-Transferase Gene Polymorphisms and Risk of Colorectal Adenoma: Results from the UK Flexible Sigmoidoscopy Screening Trial Cancer Epidemiol. Biomarkers Prev., April 1, 2005; 14(4): 1028 - 1030. [Full Text] [PDF]
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P. H. Avogbe, L. Ayi-Fanou, H. Autrup, S. Loft, B. Fayomi, A. Sanni, P. Vinzents, and P. Moller Ultrafine particulate matter and high-level benzene urban air pollution in relation to oxidative DNA damage Carcinogenesis, March 1, 2005; 26(3): 613 - 620. [Abstract] [Full Text] [PDF]
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A.S. Wenzlaff, M.L. Cote, C.H. Bock, S.J. Land, and A.G. Schwartz GSTM1, GSTT1 and GSTP1 polymorphisms, environmental tobacco smoke exposure and risk of lung cancer among never smokers: a population-based study Carcinogenesis, February 1, 2005; 26(2): 395 - 401. [Abstract] [Full Text] [PDF]
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S. E. Hur, J. Y. Lee, H.-S. Moon, and H. W. Chung Polymorphisms of the genes encoding the GSTM1, GSTT1 and GSTP1 in Korean women: no association with endometriosis Mol. Hum. Reprod., January 1, 2005; 11(1): 15 - 19. [Abstract] [Full Text] [PDF]
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S. Pavanello, A. Pulliero, E. Siwinska, D. Mielzynska, and E. Clonfero Reduced nucleotide excision repair and GSTM1-null genotypes influence anti-B[a]PDE-DNA adduct levels in mononuclear white blood cells of highly PAH-exposed coke oven workers Carcinogenesis, January 1, 2005; 26(1): 169 - 175. [Abstract] [Full Text] [PDF]
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M. Peluso, M. Neri, G. Margarino, C. Mereu, A. Munnia, M. Ceppi, M. Buratti, R. Felletti, F. Stea, R. Quaglia, et al. Comparison of DNA adduct levels in nasal mucosa, lymphocytes and bronchial mucosa of cigarette smokers and interaction with metabolic gene polymorphisms Carcinogenesis, December 1, 2004; 25(12): 2459 - 2465. [Abstract] [Full Text] [PDF]
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O. Popanda, T. Schattenberg, C. T. Phong, D. Butkiewicz, A. Risch, L. Edler, K. Kayser, H. Dienemann, V. Schulz, P. Drings, et al. Specific combinations of DNA repair gene variants and increased risk for non-small cell lung cancer Carcinogenesis, December 1, 2004; 25(12): 2433 - 2441. [Abstract] [Full Text] [PDF]
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M. Sorensen, J. Poole, H. Autrup, V. Muzyka, A. Jensen, S. Loft, and L. E. Knudsen Benzene Exposure Assessed by Metabolite Excretion in Estonian Oil Shale Mineworkers: Influence of Glutathione S-Transferase Polymorphisms Cancer Epidemiol. Biomarkers Prev., November 1, 2004; 13(11): 1729 - 1735. [Abstract] [Full Text] [PDF]
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M. Khlat, M.-H. Cazes, E. Genin, and M. Guiguet Robustness of Case-Control Studies of Genetic Factors to Population Stratification: Magnitude of Bias and Type I Error Cancer Epidemiol. Biomarkers Prev., October 1, 2004; 13(10): 1660 - 1664. [Abstract] [Full Text] [PDF]
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F. D. Vogl, E. Taioli, C. Maugard, W. Zheng, L. F. Ribeiro Pinto, C. Ambrosone, F. F. Parl, V. Nedelcheva-Kristensen, T. R. Rebbeck, P. Brennan, et al. Glutathione S-transferases M1, T1, and P1 and Breast Cancer: A Pooled Analysis Cancer Epidemiol. Biomarkers Prev., September 1, 2004; 13(9): 1473 - 1479. [Abstract] [Full Text] [PDF]
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 L.-E Wang, M. L. Bondy, H. Shen, R. El-Zein, K. Aldape, Y. Cao, V. Pudavalli, V. A. Levin, W. K. A. Yung, and Q. Wei Polymorphisms of DNA Repair Genes and Risk of Glioma Cancer Res., August 15, 2004; 64(16): 5560 - 5563. [Abstract] [Full Text] [PDF]
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 S. Ali, B. F. El-Rayes, L. K. Heilbrun, F. H. Sarkar, J. F. Ensley, O. Kucuk, and P. A. Philip Cytochrome P450 and Glutathione Transferase Expression in Squamous Cell Cancer Clin. Cancer Res., July 1, 2004; 10(13): 4412 - 4416. [Abstract] [Full Text] [PDF]
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M. F. Okcu, M. Selvan, L.-E Wang, L. Stout, R. Erana, G. Airewele, P. Adatto, K. Hess, F. Ali-Osman, M. Groves, et al. Glutathione S-Transferase Polymorphisms and Survival in Primary Malignant Glioma Clin. Cancer Res., April 15, 2004; 10(8): 2618 - 2625. [Abstract] [Full Text] [PDF]
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M. Wrensch, K. T. Kelsey, M. Liu, R. Miike, M. Moghadassi, K. Aldape, A. McMillan, and J. K. Wiencke Glutathione-S-Transferase Variants and Adult Glioma Cancer Epidemiol. Biomarkers Prev., March 1, 2004; 13(3): 461 - 467. [Abstract] [Full Text]
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N. Roodi, W. D. Dupont, J. H. Moore, and F. F. Parl Association of Homozygous Wild-Type Glutathione S-Transferase M1 Genotype with Increased Breast Cancer Risk Cancer Res., February 15, 2004; 64(4): 1233 - 1236. [Abstract] [Full Text] [PDF]
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K. M. Egan, Q. Cai, X.-O. Shu, F. Jin, T.-L. Zhu, Q. Dai, Y.-T. Gao, and W. Zheng Genetic Polymorphisms in GSTM1, GSTP1, and GSTT1 and the Risk for Breast Cancer: Results from the Shanghai Breast Cancer Study and Meta-Analysis Cancer Epidemiol. Biomarkers Prev., February 1, 2004; 13(2): 197 - 204. [Abstract] [Full Text] [PDF]
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D. L. Hachey, S. Dawling, N. Roodi, and F. F. Parl Sequential Action of Phase I and II Enzymes Cytochrome P450 1B1 and Glutathione S-Transferase P1 in Mammary Estrogen Metabolism Cancer Res., December 1, 2003; 63(23): 8492 - 8499. [Abstract] [Full Text] [PDF]
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 M Khlat and N Darmon Is there a Mediterranean migrants mortality paradox in Europe? Int. J. Epidemiol., December 1, 2003; 32(6): 1115 - 1118. [Full Text] [PDF]
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 L Buzio, G De Palma, P Mozzoni, M Tondel, C Buzio, I Franchini, O Axelson, and A Mutti Glutathione S-transferases M1-1 and T1-1 as risk modifiers for renal cell cancer associated with occupational exposure to chemicals Occup. Environ. Med., October 1, 2003; 60(10): 789 - 793. [Abstract] [Full Text] [PDF]
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L. E Eberly, J. Ockene, R. Sherwin, L. Yang, and L. Kuller Pulmonary function as a predictor of lung cancer mortality in continuing cigarette smokers and in quitters Int. J. Epidemiol., August 1, 2003; 32(4): 592 - 599. [Abstract] [Full Text] [PDF]
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S. Rollinson, A. P. Levene, F. K. Mensah, P. L. Roddam, J. M. Allan, T. C. Diss, E. Roman, A. Jack, K. MacLennan, M. F. Dixon, et al. Gastric marginal zone lymphoma is associated with polymorphisms in genes involved in inflammatory response and antioxidative capacity Blood, August 1, 2003; 102(3): 1007 - 1011. [Abstract] [Full Text] [PDF]
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S. Landi, V. Moreno, L. Gioia-Patricola, E. Guino, M. Navarro, J. de Oca, G. Capella, and F. Canzian Association of Common Polymorphisms in Inflammatory Genes Interleukin (IL)6, IL8, Tumor Necrosis Factor {alpha}, NFKB1, and Peroxisome Proliferator-activated Receptor {gamma} with Colorectal Cancer , Cancer Res., July 1, 2003; 63(13): 3560 - 3566. [Abstract] [Full Text] [PDF]
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P. Wallstrom, K. Frenkel, E. Wirfalt, B. Gullberg, J. Karkoszka, J. Seidegard, L. Janzon, and G. Berglund Antibodies against 5-Hydroxymethyl-2'-deoxyuridine Are Associated with Lifestyle Factors and GSTM1 Genotype: A Report from the Malmo Diet and Cancer Cohort Cancer Epidemiol. Biomarkers Prev., May 1, 2003; 12(5): 444 - 451. [Abstract] [Full Text] [PDF]
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F. Sata, H. Yamada, T. Kondo, Y. Gong, S. Tozaki, G. Kobashi, E.H. Kato, S. Fujimoto, and R. Kishi Glutathione S-transferase M1 and T1 polymorphisms and the risk of recurrent pregnancy loss Mol. Hum. Reprod., March 1, 2003; 9(3): 165 - 169. [Abstract] [Full Text] [PDF]
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E Taioli, L Gaspari, S Benhamou, P Boffetta, J Brockmoller, D Butkiewicz, I Cascorbi, M. Clapper, V Dolzan, A Haugen, et al. Polymorphisms in CYP1A1, GSTM1, GSTT1 and lung cancer below the age of 45 years Int. J. Epidemiol., February 1, 2003; 32(1): 60 - 63. [Abstract] [Full Text] [PDF]
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 F. D. Gilliland, W. J. Gauderman, H. Vora, E. Rappaport, and L. Dubeau Effects of Glutathione-S-Transferase M1, T1, and P1 on Childhood Lung Function Growth Am. J. Respir. Crit. Care Med., September 1, 2002; 166(5): 710 - 716. [Abstract] [Full Text] [PDF]
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A. Forsti, Q. Jin, E. Grzybowska, M. Soderberg, H. Zientek, M. Sieminska, J. Rogozinska-Szczepka, E. Chmielik, B. Utracka-Hutka, and K. Hemminki Sex hormone-binding globulin polymorphisms in familial and sporadic breast cancer Carcinogenesis, August 1, 2002; 23(8): 1315 - 1320. [Abstract] [Full Text] [PDF]
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K. Hemminki and A. Forsti Proper controls for SNP studies? Carcinogenesis, August 1, 2002; 23(8): 1405 - 1406. [Full Text] [PDF]
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L. S. Engel, E. Taioli, R. Pfeiffer, M. Garcia-Closas, P. M. Marcus, Q. Lan, P. Boffetta, P. Vineis, H. Autrup, D. A. Bell, et al. Pooled Analysis and Meta-analysis of Glutathione S-Transferase M1 and Bladder Cancer: A HuGE Review Am. J. Epidemiol., July 15, 2002; 156(2): 95 - 109. [Abstract] [Full Text] [PDF]
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