Cancer Causes & Control

, Volume 19, Issue 5, pp 491–503 | Cite as

Vegetables- and antioxidant-related nutrients, genetic susceptibility, and non-Hodgkin lymphoma risk

  • Linda E. Kelemen
  • Sophia S. Wang
  • Unhee Lim
  • Wendy Cozen
  • Maryjean Schenk
  • Patricia Hartge
  • Yan Li
  • Nathaniel Rothman
  • Scott Davis
  • Stephen J. Chanock
  • Mary H. Ward
  • James R. Cerhan
Original Paper


Genetic susceptibility to DNA oxidation, carcinogen metabolism, and altered DNA repair may increase non-Hodgkin lymphoma (NHL) risk, whereas vegetables- and antioxidant-related nutrients may decrease risk. We evaluated the interaction of a priori-defined dietary factors with 28 polymorphisms in these metabolic pathways. Incident cases (n = 1,141) were identified during 1998–2000 from four cancer registries and frequency-matched to population-based controls (n = 949). We estimated diet-gene joint effects using two-phase semi-parametric maximum-likelihood methods, which utilized genotype data from all subjects as well as 371 cases and 311 controls with available diet information. Adjusted odds ratios (95% confidence intervals) were lower among common allele carriers with higher dietary intakes. For the GSTM3 3-base insertion and higher total vegetable intake, the risk was 0.56 (0.35–0.92, p interaction = 0.03); for GSTP1 A114V and higher cruciferous vegetable intake, the risk was 0.52 (0.34–0.81, p interaction = 0.02); for OGG1 S326C and higher daily zinc intake, the risk was 0.71 (0.47–1.08, p interaction = 0.04) and for XRCC3 T241M and higher green leafy vegetable intake, the risk was 0.63 (0.41–0.97, p interaction = 0.03). Calculation of the false positive report probability determined a high likelihood of falsely positive associations. Although most associations have not been examined previously with NHL, our results suggest the examined polymorphisms are not modifiers of the association between vegetable and zinc intakes and NHL risk.


Brassicaceae Zinc GST OGG1 XRCC 



We thank Jane Curtin and Adam Risch of Information Management Services, Inc. for assisting with data analysis and Nilanjan Chatterjee for guidance with the two-phase design, semi-parametric maximum-likelihood method implementation. Financial support: Supported in part by the Intramural Research Program of the National Institutes of Health, National Cancer Institute and contracts with the National Cancer Institute (N01-CP-67010, N01-PC-67008, N01-PC-67009, N01-PC-65064 and N02-PC-71105). LEK was supported by National Institutes of Health Grant R25 CA92049-03.

Supplementary material

10552_2008_9111_MOESM1_ESM.doc (262 kb)
(DOC 261 kb)


  1. 1.
    National Cancer Institute DCCPS, Surveillance Research Program, Cancer Statistics Branch. Surveillance, Epidemiology, and End Results (SEER) Program (Released April 2005 based on the November 2004 submission.) Incidence - SEER 9 Regs Public-Use, Nov 2004 Sub (1973–2002)Google Scholar
  2. 2.
    Hoover RN (1992) Lymphoma risks in populations with altered immunity – a search for mechanism. Cancer Res 52:5477s–5478sPubMedGoogle Scholar
  3. 3.
    Hussain SP, Hofseth LJ, Harris CC (2003) Radical causes of cancer. Nat Rev Cancer 3:276–285PubMedCrossRefGoogle Scholar
  4. 4.
    Li H, Kantoff PW, Giovannucci E et al (2005) Manganese superoxide dismutase polymorphism, prediagnostic antioxidant status, and risk of clinical significant prostate cancer. Cancer Res 65:2498–2504PubMedCrossRefGoogle Scholar
  5. 5.
    Tamimi RM, Hankinson SE, Spiegelman D, Colditz GA, Hunter DJ (2004) Manganese superoxide dismutase polymorphism, plasma antioxidants, cigarette smoking, and risk of breast cancer. Cancer Epidemiol Biomarkers Prev 13:989–996PubMedGoogle Scholar
  6. 6.
    Lampe JW, King IB, Li S et al (2000) Brassica vegetables increase and apiaceous vegetables decrease cytochrome P450 1A2 activity in humans: changes in caffeine metabolite ratios in response to controlled vegetable diets. Carcinogenesis 21:1157–1162PubMedCrossRefGoogle Scholar
  7. 7.
    Le Marchand L, Donlon T, Lum-Jones A, Seifried A, Wilkens LR (2002) Association of the hOGG1 Ser326Cys polymorphism with lung cancer risk. Cancer Epidemiol Biomarkers Prev 11:409–412PubMedGoogle Scholar
  8. 8.
    Tijhuis MJ, Wark PA, Aarts JM et al (2005) GSTP1 and GSTA1 polymorphisms interact with cruciferous vegetable intake in colorectal adenoma risk. Cancer Epidemiol Biomarkers Prev 14:2943–2951PubMedCrossRefGoogle Scholar
  9. 9.
    Kelemen LE, Cerhan JR, Lim U et al (2006) Vegetables, fruit, and antioxidant-related nutrients and risk of non-Hodgkin lymphoma: a National Cancer Institute-Surveillance, epidemiology, and end results population-based case–control study. Am J Clin Nutr 83:1401–1410PubMedGoogle Scholar
  10. 10.
    Wang SS, Davis S, Cerhan JR et al (2006) Polymorphisms in oxidative stress genes and risk for non-Hodgkin lymphoma. Carcinogenesis 9:1828–1834CrossRefGoogle Scholar
  11. 11.
    Morton LM, Schenk M, Hein DW et al (2006) Genetic variation in N-acetyltransferase 1 (NAT1) and 2 (NAT2) and risk of non-Hodgkin lymphoma. Pharmacogenet Genomics 16:537–545PubMedCrossRefGoogle Scholar
  12. 12.
    De Roos AJ, Gold LS, Wang S et al (2006) Metabolic gene variants and risk of non-Hodgkin’s lymphoma. Cancer Epidemiol Biomarkers Prev 15:1647–1653PubMedCrossRefGoogle Scholar
  13. 13.
    Hill DA, Wang SS, Cerhan JR et al (2006) Risk of non-Hodgkin lymphoma (NHL) in relation to germline variation in DNA repair and related genes. Blood 108:3161–3167PubMedCrossRefGoogle Scholar
  14. 14.
    Fowke JH, Chung FL, Jin F et al (2003) Urinary isothiocyanate levels, brassica, and human breast cancer. Cancer Res 63:3980–3986PubMedGoogle Scholar
  15. 15.
    Lin HJ, Probst-Hensch NM, Louie AD et al (1998) Glutathione transferase null genotype, broccoli, and lower prevalence of colorectal adenomas. Cancer Epidemiol Biomarkers Prev 7:647–652PubMedGoogle Scholar
  16. 16.
    Steinkellner H, Rabot S, Freywald C et al (2001) Effects of cruciferous vegetables and their constituents on drug metabolizing enzymes involved in the bioactivation of DNA-reactive dietary carcinogens. Mutat Res 480–481:285–297PubMedGoogle Scholar
  17. 17.
    Tainer JA, Getzoff ED, Richardson JS, Richardson DC (1983) Structure and mechanism of copper, zinc superoxide dismutase. Nature 306:284–287PubMedCrossRefGoogle Scholar
  18. 18.
    Mocchegiani E, Giacconi R, Muzzioli M, Cipriano C (2000) Zinc, infections and immunosenescence. Mech Ageing Dev 121:21–35PubMedCrossRefGoogle Scholar
  19. 19.
    de Haan JB, Cristiano F, Iannello R, Bladier C, Kelner MJ, Kola I (1996) Elevation in the ratio of Cu/Zn-superoxide dismutase to glutathione peroxidase activity induces features of cellular senescence and this effect is mediated by hydrogen peroxide. Hum Mol Genet 5:283–292PubMedCrossRefGoogle Scholar
  20. 20.
    Auchere F, Capeillere-Blandin C (2002) Oxidation of Cu, Zn-superoxide dismutase by the myeloperoxidase/hydrogen peroxide/chloride system: functional and structural effects. Free Radic Res 36:1185–1198PubMedCrossRefGoogle Scholar
  21. 21.
    Johannesen J, Pie A, Pociot F, Kristiansen OP, Karlsen AE, Nerup J (2001) Linkage of the human inducible nitric oxide synthase gene to type 1 diabetes. J Clin Endocrinol Metabol 86:2792–2796CrossRefGoogle Scholar
  22. 22.
    Leeson CP, Hingorani AD, Mullen MJ et al (2002) Glu298Asp endothelial nitric oxide synthase gene polymorphism interacts with environmental and dietary factors to influence endothelial function. Circ Res 90:1153–1158PubMedCrossRefGoogle Scholar
  23. 23.
    Han J, Hankinson SE, Zhang SM, De Vivo I, Hunter DJ (2004) Interaction between genetic variations in DNA repair genes and plasma folate on breast cancer risk. Cancer Epidemiol Biomarkers Prev 13:520–524PubMedCrossRefGoogle Scholar
  24. 24.
    Chatterjee N, Hartge P, Cerhan JR et al (2004) Risk of non-Hodgkin’s lymphoma and family history of lymphatic, hematologic, and other cancers. Cancer Epidemiol Biomarkers Prev 13:1415–1421PubMedGoogle Scholar
  25. 25.
    Bhatti P, Sigurdson AJ, Wang SS et al (2005) Genetic variation and willingness to participate in epidemiologic research: data from three studies. Cancer Epidemiol Biomarkers Prev 14:2449–2453PubMedCrossRefGoogle Scholar
  26. 26.
    Garcia-Closas M, Egan KM, Abruzzo J et al (2001) Collection of genomic DNA from adults in epidemiological studies by buccal cytobrush and mouthwash. Cancer Epidemiol Biomarkers Prev 10:687–696PubMedGoogle Scholar
  27. 27.
    Packer BR, Yeager M, Burdett L et al (2006) SNP500Cancer: a public resource for sequence validation, assay development, and frequency analysis for genetic variation in candidate genes. Nucleic Acids Res 34:D617–D621PubMedCrossRefGoogle Scholar
  28. 28.
    Block G, Hartman AM, Dresser CM, Carroll MD, Gannon J, Gardner L (1986) A data-based approach to diet questionnaire design and testing. Am J Epidemiol 124:453–469PubMedGoogle Scholar
  29. 29.
    Block G, Coyle LM, Hartman AM, Scoppa SM (1994) Revision of dietary analysis software for the health habits and history questionnaire. Am J Epidemiol 139:1190–1196PubMedGoogle Scholar
  30. 30.
    Block G, Woods M, Potosky A, Clifford C (1990) Validation of a self-administered diet history questionnaire using multiple diet records. J Clin Epidemiol 43:1327–1335PubMedCrossRefGoogle Scholar
  31. 31.
    Willett W, Stampfer MJ (1986) Total energy intake: implications for epidemiologic analyses. Am J Epidemiol 124:17–27PubMedGoogle Scholar
  32. 32.
    Breslow NE, Chatterjee N (1999) Design and analysis of two-phase studies with binary outcome applied to Wilms tumour prognosis. Appl Statis 48:457–468Google Scholar
  33. 33.
    Scott AJ, Wild CJ (1997) Fitting regression models to case–control data by maximum likelihood. Biometrika 84:57–71CrossRefGoogle Scholar
  34. 34.
    Rothman K, Greenland S (1998) Modern epidemiology. Lippincott-Reaven Publishers, PhiladelphiaGoogle Scholar
  35. 35.
    Wacholder S, Chanock S, Garcia-Closas M, El Ghormli L, Rothman N (2004) Assessing the probability that a positive report is false: an approach for molecular epidemiology studies. J Natl Cancer Inst 96:434–442PubMedCrossRefGoogle Scholar
  36. 36.
    Pool-Zobel BL, Bub A, Liegibel UM, Treptow-van Lishaut S, Rechkemmer G (1998) Mechanisms by which vegetable consumption reduces genetic damage in humans. Cancer Epidemiol Biomarkers Prev 7:891–899PubMedGoogle Scholar
  37. 37.
    Inskip A, Elexperu-Camiruaga J, Buxton N et al (1995) Identification of polymorphism at the glutathione S-transferase, GSTM3 locus: evidence for linkage with GSTM1*A. Biochem J 312(Pt 3):713–716PubMedGoogle Scholar
  38. 38.
    Ali-Osman F, Akande N, Mao J (1995) Molecular cloning, characterisation and expression of novel functionally different human glutathione S-transferase P1 gene variants Proceedings of the ISSX Workshop on Glutathione S-transferases. Taylor and Francis, LondonGoogle Scholar
  39. 39.
    Turner F, Smith G, Sachse C et al (2004) Vegetable, fruit and meat consumption and potential risk modifying genes in relation to colorectal cancer. Int J Cancer 112:259–264PubMedCrossRefGoogle Scholar
  40. 40.
    Weiss JM, Goode EL, Ladiges WC, Ulrich CM (2005) Polymorphic variation in hOGG1 and risk of cancer: a review of the functional and epidemiologic literature. Mol Carcinog 42:127–141PubMedCrossRefGoogle Scholar
  41. 41.
    Dreosti IE (2001) Zinc and the gene. Mutat Res 475:161–167PubMedGoogle Scholar
  42. 42.
    Smedby KE, Lindgren CM, Hjalgrim H et al (2006) Variation in DNA repair genes ERCC2, XRCC1, and XRCC3 and risk of follicular lymphoma. Cancer Epidemiol Biomarkers Prev 15:258–265PubMedCrossRefGoogle Scholar
  43. 43.
    Huang WY, Chow WH, Rothman N et al (2005) Selected DNA repair polymorphisms and gastric cancer in Poland. Carcinogenesis 26:1354–1359PubMedCrossRefGoogle Scholar
  44. 44.
    Yeh CC, Hsieh LL, Tang R, Chang-Chieh CR, Sung FC (2005) MS-920: DNA repair gene polymorphisms, diet and colorectal cancer risk in Taiwan. Cancer Lett 224:279–288PubMedCrossRefGoogle Scholar
  45. 45.
    Au WW, Salama SA, Sierra-Torres CH (2003) Functional characterization of polymorphisms in DNA repair genes using cytogenetic challenge assays. Environ Health Perspect 111:1843–1850PubMedGoogle Scholar
  46. 46.
    Dorgan JF, Ziegler RG, Schoenberg JB et al (1993) Race and sex differences in associations of vegetables, fruits, and carotenoids with lung cancer risk in New Jersey (United States). Cancer Causes Control 4:273–281PubMedGoogle Scholar
  47. 47.
    Satia-Abouta J, Galanko JA, Martin CF, Ammerman A, Sandler RS (2004) Food groups and colon cancer risk in African-Americans and Caucasians. Int J Cancer 109:728–736PubMedCrossRefGoogle Scholar
  48. 48.
    Popkin BM, Siega-Riz AM, Haines PS (1996) A comparison of dietary trends among racial and socioeconomic groups in the United States. N Engl J Med 335:716–720PubMedCrossRefGoogle Scholar
  49. 49.
    Morton LM, Cahill J, Hartge P (2006) Reporting participation in epidemiologic studies: a survey of practice. Am J Epidemiol 163:197–203PubMedCrossRefGoogle Scholar
  50. 50.
    Lim U, Schenk M, Kelemen LE et al (2005) Dietary determinants of one-carbon metabolism and the risk of non-Hodgkin’s lymphoma: NCI-SEER case–control study, 1998–2000. Am J Epidemiol 162:953–964PubMedCrossRefGoogle Scholar
  51. 51.
    Wang LI, Giovannucci EL, Hunter D, Neuberg D, Su L, Christiani DC (2004) Dietary intake of Cruciferous vegetables, Glutathione S-transferase (GST) polymorphisms and lung cancer risk in a Caucasian population. Cancer Causes Control 15:977–985PubMedCrossRefGoogle Scholar
  52. 52.
    Manuguerra M, Saletta F, Karagas MR et al (2006) XRCC3 and XPD/ERCC2 single nucleotide polymorphisms and the risk of cancer: a HuGE review. Am J Epidemiol 164:297–302PubMedCrossRefGoogle Scholar
  53. 53.
    Rafii S, O’Regan P, Xinarianos G et al (2002) A potential role for the XRCC2 R188H polymorphic site in DNA-damage repair and breast cancer. Hum Mol Genet 11:1433–1438PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2008

Authors and Affiliations

  • Linda E. Kelemen
    • 1
  • Sophia S. Wang
    • 2
  • Unhee Lim
    • 2
  • Wendy Cozen
    • 3
  • Maryjean Schenk
    • 4
  • Patricia Hartge
    • 2
  • Yan Li
    • 2
  • Nathaniel Rothman
    • 2
  • Scott Davis
    • 5
  • Stephen J. Chanock
    • 2
  • Mary H. Ward
    • 2
  • James R. Cerhan
    • 1
  1. 1.Department of Health Sciences ResearchMayo Clinic College of MedicineRochesterUSA
  2. 2.Division of Cancer Epidemiology and GeneticsNational Cancer InstituteBethesdaUSA
  3. 3.Department of Preventive MedicineUniversity of Southern CaliforniaLos AngelesUSA
  4. 4.Karmanos Cancer InstituteEpidemiology SectionDetroitUSA
  5. 5.Fred Hutchinson Cancer Research CenterUniversity of Washington School of Public Health and Community MedicineSeattleUSA

Personalised recommendations