Oxidative damage caused by reactive oxygen species and other free radicals is involved in carcinogenesis. It has been suggested that high vegetable and fruit intake may reduce the risk of non-Hodgkin lymphoma (NHL) as vegetables and fruit are rich in antioxidants. The aim of this study is to evaluate the interaction of vegetable and fruit intake with genetic polymorphisms in oxidative stress pathway genes and NHL risk. This hypothesis was investigated in a population-based case-control study of NHL and NHL histologic subtypes in women from Connecticut, including 513 histologically confirmed incident cases and 591 randomly selected controls. Gene-vegetable/fruit joint effects were estimated using unconditional logistic regression model. The false discovery rate method was applied to adjust for multiple comparisons. Significant interactions with vegetable and fruit intake were mainly found for genetic polymorphisms on nitric oxide synthase (NOS) genes among those with diffuse large B-cell lymphoma and follicular lymphoma. Two single nucleotide polymorphisms in the NOS1 gene were found to significantly modify the association between total vegetable and fruit intake and risk of NHL overall, as well as the risk of follicular lymphoma. When vegetables, bean vegetables, cruciferous vegetables, green leafy vegetables, red vegetables, yellow/orange vegetables, fruit, and citrus fruits were examined separately, strong interaction effects were narrowed to vegetable intake among patients with diffuse large B-cell lymphoma. Our results suggest that genetic polymorphisms in oxidative stress pathway genes, especially in the NOS genes, modify the association between vegetable and fruit intake and risk of NHL. (Cancer Epidemiol Biomarkers Prev 2009;18(5):1429–38)

Non-Hodgkin lymphoma (NHL) presents a heterogeneous group of malignancies arising from lymphocytes throughout the body. It has been estimated that 66,120 individuals will be diagnosed with NHL, and that 19,160 will die from NHL in the United States in 2008. Although established risk factors such as immunodeficiency and viral infection may be responsible for a portion of the cases, the vast majority of the NHL cases remain unexplained.

Reactive oxygen species and other free radicals can cause oxidative damage to all components of the cell (i.e., proteins, lipids, and DNA) and have been shown to be involved in a number of pathologic conditions including cancer (1-7). Vegetables and fruit are rich in antioxidants that protect cells from such damage. As such, high vegetable and fruit intake has been hypothesized to reduce the risk of NHL. However, results from epidemiologic studies have been inconsistent (8-22). Variation in genetic susceptibility within these populations under study could, in part, account for some of the conflicting findings in previous investigations into the role of fruit and vegetable intake.

It is biologically plausible that the role of antioxidant-rich vegetable and fruit intake in lymphomagenesis is modified by common genetic variation in oxidative stress pathway genes. Oxidative stress pathway genes can modify the effect of oxidative damage at many stages of carcinogenesis (4), including tumor initiation due to the genotoxicity of reactive oxygen species, tumor promotion by oxidants and free radicals, inflammatory responses mediated by oxide synthase and oxygenase, inhibition of intercellular communication regulating cellular proliferation and differentiation, and alteration of the extracellular matrix involved in tumor invasion and metastasis. We therefore investigated NHL risk in general and by subtype in relation to common genetic variation in the oxidative stress pathway in conjunction with vegetable and fruit intake in a population-based case-control study of females in Connecticut.

Study Population

The study population has been described in detail elsewhere (8, 23). Briefly, cases were histologically confirmed, incident NHL patients diagnosed in Connecticut between 1996 and 2000, restricted to women ages 21 to 84 at diagnosis, without previous diagnosis of cancer except nonmelanoma skin cancer, and alive at the time of interview. Out of 832 eligible NHL cases, 601 (72%) cases completed in-person interviews. Participants were slightly older than nonparticipants, with mean ages of 67 and 62, respectively. The race distribution was similar between participants and nonparticipants. Out of 601 cases, 518 provided a biosample (461 provided a blood sample and 57 provided a buccal cell sample), excluding 5 cases with dietary information missing, yielding 513 cases for final analysis.

Pathology slides or tissue blocks were obtained from the hospitals where the cases were diagnosed. The specimens were reviewed by two independent study pathologists. All NHL cases were classified according to the WHO classification system (24, 25), including 160 cases of diffuse large B-cell lymphoma (DLBCL), 117 cases of follicular lymphoma (FL), 59 cases of chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL), 35 cases of marginal zone B-cell lymphoma, 39 cases of T/natural killer-cell lymphoma (T cell), and 103 cases of other rare and unspecified subtypes.

Population-based controls with Connecticut addresses were recruited using random digit-dialing methods for those below age 65 y, and files provided by the Centers for Medicare and Medicaid Services were used to recruit those ages 65 y or older, and were frequency-matched to cases by age (±5 y). The participation rates were 69% for controls from random digit-dialing and 47% for controls from the Centers for Medicare and Medicaid Services. The distribution of age and race between participants and nonparticipants was similar. Out of 717 controls, 597 provided a biosample (535 provided a blood sample and 62 provided a buccal cell sample), excluding 6 controls with dietary information missing, yielding 591 controls for final analysis.

The study was approved by the Human Subjects Research Review Committee at Yale University, the Connecticut Department of Public Health, and the National Cancer Institute. Written and informed consent was obtained from all subjects.

Exposure Assessment

In-person interviews were conducted by trained personnel using a standardized questionnaire to collect demographic information and other major known or suspected NHL risk factors, such as family history of cancer, pesticide exposure, medical history, smoking, alcohol consumption, UV radiation, and hair-coloring products use. Diet was assessed using a mailed self-administered semiquantitative food frequency questionnaire developed by the Fred Hutchinson Cancer Research Center (Seattle, WA), in which subjects were asked to characterize their usual diet in the year prior to being interviewed. Reproducibility and validity studies indicated that fruits and vegetables on the food frequency questionnaire reasonably reflect long-term dietary intake (26). Following completion, the food frequency questionnaire was sent to the Fred Hutchinson Cancer Research Center for analysis. Average daily nutrient intakes were calculated using the University of Minnesota Nutrition Coding Center Nutrient Data System database.

The food frequency questionnaire collects data on consumption frequency and portion size for approximately 120 foods, including 19 vegetables and 11 fruits (Table 1). Besides overall vegetable intake, we individually analyzed bean vegetables, cruciferous vegetables, green leafy vegetables, red vegetables, and yellow/orange vegetables. In addition to total fruit intake, we individually analyzed citrus fruits.

Table 1.

Vegetables and fruit in the food frequency questionnaire

Category of foodComposition of food categories
Vegetable Bean vegetables; cruciferous vegetables; green leafy vegetables; red vegetables; yellow/orange vegetables; avocado or guacamole; corn; summer squash such as zucchini; onions, leeks, including in cooking; mixed lettuce salad with vegetables, such as carrots, tomatoes, etc. 
Fruit Apples, pears; bananas; peaches, nectarines or plums; cantaloupes; other melon, watermelon, honeydew, etc.; apricots; other dried fruit, raisins, prunes, etc.; strawberries; any other fruit (fruit cocktail, berries, applesauce, grapes, pineapple, etc.); citrus fruits 
Bean vegetables String beans, green beans; peas; beans, such as baked beans, pinto, kidney, lima beans, lentils 
Cruciferous vegetables Broccoli; coleslaw; cabbage, sauerkraut, Brussels sprouts; cauliflower 
Green leafy vegetables Cooked greens (spinach, mustard greens, turnip greens, collards, etc.); lettuce, plain lettuce salad 
Red vegetables Tomatoes, fresh or juice; tomatoes cooked, tomato sauce, salsa 
Yellow/orange vegetables Carrots, including in mixed dishes; winter squash, such as acorn, butternut; sweet potatoes, yams 
Citrus fruits Oranges, grapefruit or tangerines; orange juice, grapefruit juice, or vitamin C–enriched fruit drinks 
Category of foodComposition of food categories
Vegetable Bean vegetables; cruciferous vegetables; green leafy vegetables; red vegetables; yellow/orange vegetables; avocado or guacamole; corn; summer squash such as zucchini; onions, leeks, including in cooking; mixed lettuce salad with vegetables, such as carrots, tomatoes, etc. 
Fruit Apples, pears; bananas; peaches, nectarines or plums; cantaloupes; other melon, watermelon, honeydew, etc.; apricots; other dried fruit, raisins, prunes, etc.; strawberries; any other fruit (fruit cocktail, berries, applesauce, grapes, pineapple, etc.); citrus fruits 
Bean vegetables String beans, green beans; peas; beans, such as baked beans, pinto, kidney, lima beans, lentils 
Cruciferous vegetables Broccoli; coleslaw; cabbage, sauerkraut, Brussels sprouts; cauliflower 
Green leafy vegetables Cooked greens (spinach, mustard greens, turnip greens, collards, etc.); lettuce, plain lettuce salad 
Red vegetables Tomatoes, fresh or juice; tomatoes cooked, tomato sauce, salsa 
Yellow/orange vegetables Carrots, including in mixed dishes; winter squash, such as acorn, butternut; sweet potatoes, yams 
Citrus fruits Oranges, grapefruit or tangerines; orange juice, grapefruit juice, or vitamin C–enriched fruit drinks 

The methods for evaluating genotypes in our study population have been described previously by Lan et al. (27). Briefly, DNA was extracted from blood or buccal cell samples using phenol-chloroform extraction. One hundred and thirty-seven Tag single nucleotide polymorphisms (SNP) from 18 candidate genes (Table 2) involved in the oxidative stress pathway were chosen from the designable set of common SNPs (minor allele frequency >5%) genotyped in the Caucasian population sample of the HapMap Project (data release 20/Phase II, NCBI Build 35 assembly, dpSNPb125) using the software Tagzilla5

, which implements a tagging algorithmFN2 based on the pairwise binning method of Carlson et al. (28). For each gene, SNPs within the region 20 kb 5′ of the ATG-translation initiation codon and 10 kb 3′ of the end of the last exon were binned using a binning threshold of r2 > 0.80. When there were multiple transcripts available for genes, the primary transcript was assessed. Genotyping was conducted at the National Cancer Institute Core Genotyping Facility6 (Advanced Technology Center, Gaithersburg, MD; ref. 29) using a real-time PCR assay (18 SNPs) and a custom-designed GoldenGate assay7 (129 SNPs; Illumina). Duplicate samples and replicate samples were genotyped for quality control, and blinded to laboratory personnel. The concordance rates were 99% to 100% for all assays.

Table 2.

Candidate genes in the oxidative stress pathway

Candidate gene* (N = 18)Chromosomal location*Gene name (aliases)*Total SNPs (N = 137)SNP500 alias (dbSNP ID)
AKR1A1 1p33-p32 Aldo-keto reductase family 1, member A1 (aldehyde reductase) AKR1A1_02 (rs2088102) 
AKR1C1 10p15-p14 Aldo-keto reductase family 1, member C1 (dihydrodiol dehydrogenase 1; 20-α (3-α)-hydroxysteroid dehydrogenase) AKR1C1_02 (rs8483) 
AKR1C3 10p15-p14 Aldo-keto reductase family 1, member C3 (3-α hydroxysteroid dehydrogenase, type II) AKR1C3_01 (rs12529), AKR1C3_08 (rs2245191) 
ATG9B 7q36.1 ATG9 autophagy-related 9 homologue B (S. cerevisiaeATG9B_01 (rs2373929) 
CYBA 16q24 Cytochrome b-245, α polypeptide CYBA_01 (rs4673), CYBA_02 (rs1049255), CYBA_07 (rs7195830), CYBA_08 (rs12709102), CYBA_14 (rs3794624) 
GPX1 3p21.3 Glutathione peroxidase 1 GPX1_01 (rs1050450) 
MPO 17q23.1 Myeloperoxidase MPO_02 (rs2333227), MPO_03 (rs2243828), MPO_04 (rs2071409), MPO_17 (rs12452417), MPO_18 (rs4401102) 
NCF2 1q25 Neutrophil cytosolic factor 2 (65 kDa, chronic granulomatous disease, autosomal 2) NCF2_27 (rs10797888), NCF2_28 (rs11588654), NCF2_29 (rs12753665), NCF2_30 (rs3843293), NCF2_31 (rs3845466), NCF2_34 (rs11579965), NCF2_35 (rs2333686) 
NCF4 22q13.1 Neutrophil cytosolic factor 4, 40 kDa 18 NCF4_12 (rs3788523), NCF4_18 (rs729749), NCF4_33 (rs2072711), NCF4_34 (rs2075938), NCF4_35 (rs4821544), NCF4_36 (rs741998), NCF4_37 (rs746713), NCF4_38 (rs760519), NCF4_39 (rs10854693), NCF4_41 (rs1883113), NCF4_42 (rs4821542), NCF4_43 (rs5750326), NCF4_44 (rs5756372), NCF4_45 (rs5756381), NCF4_46 (rs5995355), NCF4_47 (rs6000462), NCF4_48 (rs8137602), NCF4_49 (rs9680849) 
NOS1 12q24.2-q24.31 Nitric oxide synthase 1 (neuronal) 31 NOS1_01 (rs10850803), NOS1_02 (rs11068446), NOS1_03 (rs1123425), NOS1_04 (rs11611788), NOS1_05 (rs12578547), NOS1_06 (rs1353939), NOS1_07 (rs1552227), NOS1_08 (rs2291908), NOS1_09 (rs2293054), NOS1_10 (rs2293055), NOS1_12 (rs3782218), NOS1_13 (rs3782221), NOS1_14 (rs483589), NOS1_15 (rs532967), NOS1_16 (rs545654), NOS1_17 (rs6490121), NOS1_18 (rs7295972), NOS1_19 (rs7298903), NOS1_20 (rs816293), NOS1_21 (rs816351), NOS1_22 (rs816353), NOS1_23 (rs816361), NOS1_24 (rs884847), NOS1_25 (rs9658354), NOS1_26 (rs9658490), NOS1_27 (rs11068458), NOS1_28 (rs12424669), NOS1_29 (rs1879417), NOS1_30 (rs4767535), NOS1_31 (rs816347), NOS1_32 (rs9658282) 
NOS2A 17q11.2-q12 Nitric oxide synthase 2A (inducible, hepatocytes) 22 NOS2A_01 (rs944722), NOS2A_02 (rs2297518), NOS2A_03 (rs9282799), NOS2A_07 (rs9282801), NOS2A_09 (rs12944039), NOS2A_11 (rs2255929), NOS2A_12 (rs2297516), NOS2A_13 (rs3729508), NOS2A_14 (rs3794763), NOS2A_15 (rs3794766), NOS2A_16 (rs4795067), NOS2A_17 (rs8072199), NOS2A_18 (rs944725), NOS2A_19 (rs9797244), NOS2A_20 (rs11080358), NOS2A_21 (rs12150211), NOS2A_22 (rs2248814), NOS2A_23 (rs2531863), NOS2A_25 (rs2779248), NOS2A_26 (rs2779252), NOS2A_28 (rs8081248), NOS2A_29 (rs9901734) 
NOS3 7q36 Nitric oxide synthase 3 (endothelial cell) NOS3_01 (rs1799983), NOS3_07 (rs1007311), NOS3_11 (rs2070744), NOS3_23 (rs743507), NOS3_38 (rs3918227), NOS3_39 (rs12703107), NOS3_40 (rs2373961), NOS3_41 (rs4496877) 
OGG1 3p26.2 8-Oxoguanine DNA glycosylase OGG1_04 (rs1052133) 
RAC1 7p22 Ras-related C3 botulinum toxin substrate 1 (rho family, small GTP binding protein Rac1) RAC1_05 (rs3729790), RAC1_06 (rs6463554), RAC1_07 (rs6967221), RAC1_08 (rs702484), RAC1_09 (rs4720672), RAC1_10 (rs836551), RAC1_11 (rs836554) 
RAC2 22q13.1 Ras-related C3 botulinum toxin substrate 2 (rho family, small GTP binding protein Rac2) 15 RAC2_01 (rs1476002), RAC2_05 (rs6572), RAC2_06 (rs7390410, RAC2_09, RAC2_14 (rs2213430), RAC2_15 (rs2239773), RAC2_16 (rs2239774), RAC2_17 (rs2239775), RAC2_18 (rs5756573), RAC2_19 (rs8135343), RAC2_20 (rs9607432), RAC2_21 (rs12484031), RAC2_22 (rs4820274), RAC2_23 (rs7288979), RAC2_24 (rs739043) 
SOD1 21q22.11 Superoxide dismutase 1, soluble [amyotrophic lateral sclerosis 1 (adult)] SOD1_03 (rs10432782), SOD1_08 (rs202445), SOD1_16 (rs1041740) 
SOD2 6q25.3 Superoxide dismutase 2, mitochondrial SOD2_01 (rs4880), SOD2_16 (rs2758352), SOD2_20 (rs5746136), SOD2_29 (rs2758331), SOD2_30 (rs5746151) 
SOD3 4p16.3-q21 Superoxide dismutase 3, extracellular SOD3_16 (rs2695234), SOD3_26 (rs13434451), SOD3_27 (rs2284659), SOD3_28 (rs758946) 
Candidate gene* (N = 18)Chromosomal location*Gene name (aliases)*Total SNPs (N = 137)SNP500 alias (dbSNP ID)
AKR1A1 1p33-p32 Aldo-keto reductase family 1, member A1 (aldehyde reductase) AKR1A1_02 (rs2088102) 
AKR1C1 10p15-p14 Aldo-keto reductase family 1, member C1 (dihydrodiol dehydrogenase 1; 20-α (3-α)-hydroxysteroid dehydrogenase) AKR1C1_02 (rs8483) 
AKR1C3 10p15-p14 Aldo-keto reductase family 1, member C3 (3-α hydroxysteroid dehydrogenase, type II) AKR1C3_01 (rs12529), AKR1C3_08 (rs2245191) 
ATG9B 7q36.1 ATG9 autophagy-related 9 homologue B (S. cerevisiaeATG9B_01 (rs2373929) 
CYBA 16q24 Cytochrome b-245, α polypeptide CYBA_01 (rs4673), CYBA_02 (rs1049255), CYBA_07 (rs7195830), CYBA_08 (rs12709102), CYBA_14 (rs3794624) 
GPX1 3p21.3 Glutathione peroxidase 1 GPX1_01 (rs1050450) 
MPO 17q23.1 Myeloperoxidase MPO_02 (rs2333227), MPO_03 (rs2243828), MPO_04 (rs2071409), MPO_17 (rs12452417), MPO_18 (rs4401102) 
NCF2 1q25 Neutrophil cytosolic factor 2 (65 kDa, chronic granulomatous disease, autosomal 2) NCF2_27 (rs10797888), NCF2_28 (rs11588654), NCF2_29 (rs12753665), NCF2_30 (rs3843293), NCF2_31 (rs3845466), NCF2_34 (rs11579965), NCF2_35 (rs2333686) 
NCF4 22q13.1 Neutrophil cytosolic factor 4, 40 kDa 18 NCF4_12 (rs3788523), NCF4_18 (rs729749), NCF4_33 (rs2072711), NCF4_34 (rs2075938), NCF4_35 (rs4821544), NCF4_36 (rs741998), NCF4_37 (rs746713), NCF4_38 (rs760519), NCF4_39 (rs10854693), NCF4_41 (rs1883113), NCF4_42 (rs4821542), NCF4_43 (rs5750326), NCF4_44 (rs5756372), NCF4_45 (rs5756381), NCF4_46 (rs5995355), NCF4_47 (rs6000462), NCF4_48 (rs8137602), NCF4_49 (rs9680849) 
NOS1 12q24.2-q24.31 Nitric oxide synthase 1 (neuronal) 31 NOS1_01 (rs10850803), NOS1_02 (rs11068446), NOS1_03 (rs1123425), NOS1_04 (rs11611788), NOS1_05 (rs12578547), NOS1_06 (rs1353939), NOS1_07 (rs1552227), NOS1_08 (rs2291908), NOS1_09 (rs2293054), NOS1_10 (rs2293055), NOS1_12 (rs3782218), NOS1_13 (rs3782221), NOS1_14 (rs483589), NOS1_15 (rs532967), NOS1_16 (rs545654), NOS1_17 (rs6490121), NOS1_18 (rs7295972), NOS1_19 (rs7298903), NOS1_20 (rs816293), NOS1_21 (rs816351), NOS1_22 (rs816353), NOS1_23 (rs816361), NOS1_24 (rs884847), NOS1_25 (rs9658354), NOS1_26 (rs9658490), NOS1_27 (rs11068458), NOS1_28 (rs12424669), NOS1_29 (rs1879417), NOS1_30 (rs4767535), NOS1_31 (rs816347), NOS1_32 (rs9658282) 
NOS2A 17q11.2-q12 Nitric oxide synthase 2A (inducible, hepatocytes) 22 NOS2A_01 (rs944722), NOS2A_02 (rs2297518), NOS2A_03 (rs9282799), NOS2A_07 (rs9282801), NOS2A_09 (rs12944039), NOS2A_11 (rs2255929), NOS2A_12 (rs2297516), NOS2A_13 (rs3729508), NOS2A_14 (rs3794763), NOS2A_15 (rs3794766), NOS2A_16 (rs4795067), NOS2A_17 (rs8072199), NOS2A_18 (rs944725), NOS2A_19 (rs9797244), NOS2A_20 (rs11080358), NOS2A_21 (rs12150211), NOS2A_22 (rs2248814), NOS2A_23 (rs2531863), NOS2A_25 (rs2779248), NOS2A_26 (rs2779252), NOS2A_28 (rs8081248), NOS2A_29 (rs9901734) 
NOS3 7q36 Nitric oxide synthase 3 (endothelial cell) NOS3_01 (rs1799983), NOS3_07 (rs1007311), NOS3_11 (rs2070744), NOS3_23 (rs743507), NOS3_38 (rs3918227), NOS3_39 (rs12703107), NOS3_40 (rs2373961), NOS3_41 (rs4496877) 
OGG1 3p26.2 8-Oxoguanine DNA glycosylase OGG1_04 (rs1052133) 
RAC1 7p22 Ras-related C3 botulinum toxin substrate 1 (rho family, small GTP binding protein Rac1) RAC1_05 (rs3729790), RAC1_06 (rs6463554), RAC1_07 (rs6967221), RAC1_08 (rs702484), RAC1_09 (rs4720672), RAC1_10 (rs836551), RAC1_11 (rs836554) 
RAC2 22q13.1 Ras-related C3 botulinum toxin substrate 2 (rho family, small GTP binding protein Rac2) 15 RAC2_01 (rs1476002), RAC2_05 (rs6572), RAC2_06 (rs7390410, RAC2_09, RAC2_14 (rs2213430), RAC2_15 (rs2239773), RAC2_16 (rs2239774), RAC2_17 (rs2239775), RAC2_18 (rs5756573), RAC2_19 (rs8135343), RAC2_20 (rs9607432), RAC2_21 (rs12484031), RAC2_22 (rs4820274), RAC2_23 (rs7288979), RAC2_24 (rs739043) 
SOD1 21q22.11 Superoxide dismutase 1, soluble [amyotrophic lateral sclerosis 1 (adult)] SOD1_03 (rs10432782), SOD1_08 (rs202445), SOD1_16 (rs1041740) 
SOD2 6q25.3 Superoxide dismutase 2, mitochondrial SOD2_01 (rs4880), SOD2_16 (rs2758352), SOD2_20 (rs5746136), SOD2_29 (rs2758331), SOD2_30 (rs5746151) 
SOD3 4p16.3-q21 Superoxide dismutase 3, extracellular SOD3_16 (rs2695234), SOD3_26 (rs13434451), SOD3_27 (rs2284659), SOD3_28 (rs758946) 

Statistical Analysis

Intake of vegetables and fruit, all vegetables, bean vegetables, cruciferous vegetables, green leafy vegetables, red vegetables, yellow/orange vegetables, fruit, and citrus fruits was dichotomized into high and low levels according to the median daily consumption (servings of medium portions per day) in controls. Odds ratios and 95% confidence intervals were calculated to estimate the relative risk of NHL and NHL subtypes in relation to the SNP genotype using unconditional logistic regression models in different vegetable and/or fruit strata (high and low). The homozygote of the most common allele was used as the referent group. The significance of gene-vegetable and/or fruit intake interaction was assessed by adding an interaction term in the logistic models. The reference groups with a homozygote wild-type genotype were coded as 0, and the heterozygote and homozygote variant genotypes were grouped together to increase power and coded as 1. Statistical analyses were done using the SAS system, version 9.1 (SAS Institute, Cary, NC).

Haplotype analyses were conducted for all genes in which more than one SNP was genotyped. Haplotype block structure was evaluated with the program HaploView (Whitehead Institute, Cambridge, MA) in controls using the four-gamete rule with a minimum frequency of 0.005 for the fourth gamete. Haplotypes were estimated using the estimation-maximization algorithm (30) in SAS Genetics (SAS Institute). An unconditional logistic regression model was used to estimate the effect of individual haplotypes in different vegetable and/or fruit intake level strata.

All models were adjusted for age, race (white and other), family history of NHL, total energy intake (kcal), smoking (never/ever), alcohol consumption (g/d), and body mass index (kg/m2). Total energy intake was examined for extreme values and exclusion of these subjects did not result in material changes for the observed associations.

The false discovery rate method (31) was applied to adjust for multiple comparisons. The false discovery rate provides the expected ratio of erroneous rejections of the null hypothesis compared with the total number of rejected hypotheses. False discovery rate values were calculated separately for each vegetable and/or fruit category from the results of the 137 tests (i.e., total number of SNPs studied) evaluating the association between each SNP-vegetable and/or fruit interaction and the risk of NHL. Interactions were deemed significant at a false discovery rate level of 0.20.

Selected demographic characteristics of cases and controls were compared (Table 3). Cases and controls were similar with respect to age, race, reported family history of NHL, smoking status, and total energy intake. However, cases tended to consume less alcohol and have a higher body mass index.

Table 3.

Selected characteristics of NHL cases and controls among women from Connecticut

CharacteristicCase (N = 513)Control (N = 591)P
Age (y) 61.8 (±13.6) 62.1 (±14.2) 0.71* 
Race   0.11 
    White 492 (95.9) 554 (93.7)  
    Other 21 (4.1) 37 (6.3)  
Family history of NHL   0.08 
    Yes 9 (1.8) 3 (0.5)  
    No 504 (98.2) 588 (99.5)  
Smoking   0.33 
    Never 227 (44.2) 279 (47.2)  
    Ever 286 (55.8) 312 (52.8)  
Alcohol consumption (g/d) 3.4 (±9.6) 4.7 (±8.5) 0.05* 
Total energy intake (kcal) 1708.3 (±592.3) 1642.3 (±596.4) 0.07* 
Body mass index (kg/m226.1 (±5.7) 25.4 (±5.0) 0.03* 
CharacteristicCase (N = 513)Control (N = 591)P
Age (y) 61.8 (±13.6) 62.1 (±14.2) 0.71* 
Race   0.11 
    White 492 (95.9) 554 (93.7)  
    Other 21 (4.1) 37 (6.3)  
Family history of NHL   0.08 
    Yes 9 (1.8) 3 (0.5)  
    No 504 (98.2) 588 (99.5)  
Smoking   0.33 
    Never 227 (44.2) 279 (47.2)  
    Ever 286 (55.8) 312 (52.8)  
Alcohol consumption (g/d) 3.4 (±9.6) 4.7 (±8.5) 0.05* 
Total energy intake (kcal) 1708.3 (±592.3) 1642.3 (±596.4) 0.07* 
Body mass index (kg/m226.1 (±5.7) 25.4 (±5.0) 0.03* 

NOTE: Table values are mean ± SD for continuous variables and n (%) for categorical variables.

*

P value is for t test.

P value is for χ2 test.

P value is for Fisher's exact test.

Significant effect modification was identified for eight SNPs in nitric oxide synthase (NOS) genes, one SNP in myeloperoxidase (MPO) genes, and one SNP in superoxide dismutase 3 (SOD3) genes, with total vegetable and fruit intake, vegetable intake, red vegetable intake, or yellow/orange vegetable intake among either NHL overall or the three most common subtypes DLBCL, FL, and CLL/SLL (Table 4). No significant result was found for marginal zone B-cell lymphoma or T-cell lymphoma (data not shown).

Table 4.

Associations between genetic polymorphisms and NHL overall and histologic subtype risks by vegetable and fruit intake (servings per day)

NHL overall
DLBCL
FL
CLL/SLL
Low
High
Low
High
Low
High
Low
High
Ca/CoOR (95% CI)Ca/CoOR (95% CI)CaOR (95% CI)CaOR (95% CI)CaOR (95% CI)CaOR (95% CI)CaOR (95% CI)CaOR (95% CI)
Vegetables and fruits                 
MPO (rs4401102)                 
    CC 126/141 108/165 43 37 23 29 20 12 
    CT + TT 86/115 0.9 (0.6-1.3) 121/95 1.9 (1.3-2.8) 22 0.7 (0.4-1.3) 41 2.0 (1.2-3.4) 17 0.9 (0.5-1.8) 33 1.9 (1.1-3.5) 10 0.6 (0.3-1.3) 10 1.5 (0.6-3.7) 
P-interaction    0.0026    0.0052    0.1173    0.1243 
NOS1 (rs2293054)                 
    GG 108/144 130/108 35 42 13 39 17 10 
    AG + AA 103/112 1.2 (0.8-1.7) 98/152 0.5 (0.4-0.8) 30 1.1 (0.6-1.9) 36 0.6 (0.4-1.0) 26 2.7 (1.3-5.6) 23 0.4 (0.2-0.7) 13 1.0 (0.5-2.1) 11 0.7 (0.3-1.9) 
P-interaction    0.0024    0.1467    0.0001    0.6042 
NOS1 (rs7298903)                 
    TT 161/215 187/200 50 65 26 55 24 13 
    CT + CC 51/41 1.7 (1.1-2.8) 42/60 0.8 (0.5-1.2) 15 1.7 (0.8-3.4) 13 0.7 (0.3-1.3) 14 3.0 (1.4-6.3) 0.4 (0.2-1.0) 1.3 (0.5-3.5) 2.6 (1.0-6.7) 
P-interaction    0.0121    0.0459    0.0003    0.3442 
                 
Vegetables                 
NOS1 (rs545654)                 
    CC 68/68 63/66 30 12 11 22 10 
    CT + TT 153/183 0.8 (0.5-1.2) 151/192 0.8 (0.6-1.3) 42 0.4 (0.2-0.8) 57 1.9 (0.9-3.8) 31 1.0 (0.4-2.1) 37 0.6 (0.3-1.1) 19 0.8 (0.3-1.8) 16 0.8 (0.3-2.0) 
P-interaction    0.8548    0.0028    0.3679    0.9955 
SOD3 (rs2284659)                 
    GG 75/103 87/95 22 21 19 25 14 
    GT + TT 147/148 1.5 (1.0-2.2) 126/164 0.8 (0.6-1.2) 50 1.6 (0.9-2.9) 48 1.4 (0.8-2.4) 24 1.0 (0.5-2.0) 34 0.8 (0.5-1.5) 25 4.6 (1.5-13.7) 0.4 (0.2-0.9) 
P-interaction    0.0463    0.578    0.7281    0.0007 
                 
Red vegetables                 
NOS1 (rs11068446)                 
    CC 174/196 149/185 51 57 38 37 23  
    CT + TT 66/53 1.5 (1.0-2.3) 44/73 0.8 (0.5-1.2) 22 1.7 (0.9-3.1) 10 0.4 (0.2-0.9) 17 1.9 (1.0-3.8) 0.6 (0.3-1.4) 10 1.7 (0.7-3.8)  1.2 (0.4-3.5) 
P-interaction    0.0353    0.0057    0.0377    0.7181 
NOS1 (rs3782221)                 
    GG 126/154 113/134 31 43 29 28 18 
    AG + AA 112/96 1.4 (1.0-2.1) 80/121 0.8 (0.5-1.2) 42 2.2 (1.3-3.9) 24 0.6 (0.3-1.1) 24 1.5 (0.8-2.8) 18 0.7 (0.4-1.3) 14 1.3 (0.6-2.8) 15 6.3 (1.7-22.7) 
P-interaction    0.0243    0.0011    0.1128    0.0448 
NOS1 (rs545654)                 
    CC 80/63 50/70 31 10 17 16 10 
    CT + TT 158/183 0.6 (0.4-0.9) 140/185 1.1 (0.7-1.7) 41 0.4 (0.2-0.7) 56 2.4 (1.1-5.0) 37 0.6 (0.3-1.2) 30 0.8 (0.4-1.5) 23 0.8 (0.4-1.8) 11 0.7 (0.2-1.8) 
P-interaction    0.0593    0.0002    0.718    0.6200 
NOS1 (rs7298903)                 
    TT 186/210 158/197 53 60 40 40 25 12 
    CT + CC 55/40 1.6 (1.0-2.6) 35/61 0.7 (0.5-1.2) 20 2.1 (1.1-3.9) 0.4 (0.2-0.9) 15 2.3 (1.1-4.7) 0.5 (0.2-1.2) 1.9 (0.8-4.5) 1.7 (0.6-4.7) 
P-interaction    0.0172    0.0015    0.0101    0.9399 
NOS1 (rs12424669)                 
    CC 201/194 149/202 64 47 40 35 29 16 
    CT + TT 39/55 0.6 (0.4-1.0) 44/55 1.1 (0.7-1.7) 0.4 (0.2-0.9) 20 1.7 (0.9-3.2) 15 1.2 (0.6-2.3) 11 1.2 (0.5-2.5) 0.4 (0.1-1.2) 0.5 (0.1-2.3) 
P-interaction    0.0961    0.0073    0.9057    0.7909 
NOS2A (rs3729508)                 
    CC 76/103 82/94 20 30 13 19 14 
    CT + TT 161/145 1.5 (1.0-2.2) 111/161 0.8 (0.5-1.2) 53 2.0 (1.1-3.7) 37 0.7 (0.4-1.2) 40 2.2 (1.1-4.4) 27 0.8 (0.4-1.6) 18 0.9 (0.4-1.9) 11 0.9 (0.3-2.5) 
P-interaction    0.021    0.0086    0.0445    0.9647 
                 
Yellow/orange vegetables                 
NOS1 (rs11068446)                 
    CC 155/205 166/183 49 59 34 40 22 12 
    CT + TT 60/50 1.7 (1.1-2.7) 49/75 0.7 (0.5-1.1) 23 2.1 (1.1-3.8) 10 0.4 (0.2-0.9) 12 1.6 (0.8-3.4) 13 0.9 (0.4-1.7) 1.9 (0.8-4.5) 1.5 (0.5-4.0) 
P-interaction    0.0068    0.001    0.2339    0.709 
NOS1 (rs1552227)                 
    CC 93/128 113/117 25 40 20 25 12 12 
    CT + TT 122/128 1.3 (0.9-2.0) 103/141 0.8 (0.5-1.1) 47 2.1 (1.2-3.7) 29 0.6 (0.3-1.0) 26 1.4 (0.7-2.6) 28 1.0 (0.5-1.8) 19 1.4 (0.6-3.1) 0.5 (0.2-1.3) 
P-interaction    0.0195    0.0014    0.3022     
NOS1 (rs7298903)                 
    TT 163/213 179/200 50 63 36 43 23  13  
    CT + CC 52/43 1.7 (1.1-2.8) 37/58 0.7 (0.5-1.2) 22 2.3 (1.2-4.3) 0.3 (0.1-0.8) 10 1.5 (0.7-3.3) 10 0.8 (0.4-1.8) 2.1 (0.8-5.2) 1.8 (0.6-4.9) 
P-interaction    0.0104    0.0005    0.3115    0.8504 
NHL overall
DLBCL
FL
CLL/SLL
Low
High
Low
High
Low
High
Low
High
Ca/CoOR (95% CI)Ca/CoOR (95% CI)CaOR (95% CI)CaOR (95% CI)CaOR (95% CI)CaOR (95% CI)CaOR (95% CI)CaOR (95% CI)
Vegetables and fruits                 
MPO (rs4401102)                 
    CC 126/141 108/165 43 37 23 29 20 12 
    CT + TT 86/115 0.9 (0.6-1.3) 121/95 1.9 (1.3-2.8) 22 0.7 (0.4-1.3) 41 2.0 (1.2-3.4) 17 0.9 (0.5-1.8) 33 1.9 (1.1-3.5) 10 0.6 (0.3-1.3) 10 1.5 (0.6-3.7) 
P-interaction    0.0026    0.0052    0.1173    0.1243 
NOS1 (rs2293054)                 
    GG 108/144 130/108 35 42 13 39 17 10 
    AG + AA 103/112 1.2 (0.8-1.7) 98/152 0.5 (0.4-0.8) 30 1.1 (0.6-1.9) 36 0.6 (0.4-1.0) 26 2.7 (1.3-5.6) 23 0.4 (0.2-0.7) 13 1.0 (0.5-2.1) 11 0.7 (0.3-1.9) 
P-interaction    0.0024    0.1467    0.0001    0.6042 
NOS1 (rs7298903)                 
    TT 161/215 187/200 50 65 26 55 24 13 
    CT + CC 51/41 1.7 (1.1-2.8) 42/60 0.8 (0.5-1.2) 15 1.7 (0.8-3.4) 13 0.7 (0.3-1.3) 14 3.0 (1.4-6.3) 0.4 (0.2-1.0) 1.3 (0.5-3.5) 2.6 (1.0-6.7) 
P-interaction    0.0121    0.0459    0.0003    0.3442 
                 
Vegetables                 
NOS1 (rs545654)                 
    CC 68/68 63/66 30 12 11 22 10 
    CT + TT 153/183 0.8 (0.5-1.2) 151/192 0.8 (0.6-1.3) 42 0.4 (0.2-0.8) 57 1.9 (0.9-3.8) 31 1.0 (0.4-2.1) 37 0.6 (0.3-1.1) 19 0.8 (0.3-1.8) 16 0.8 (0.3-2.0) 
P-interaction    0.8548    0.0028    0.3679    0.9955 
SOD3 (rs2284659)                 
    GG 75/103 87/95 22 21 19 25 14 
    GT + TT 147/148 1.5 (1.0-2.2) 126/164 0.8 (0.6-1.2) 50 1.6 (0.9-2.9) 48 1.4 (0.8-2.4) 24 1.0 (0.5-2.0) 34 0.8 (0.5-1.5) 25 4.6 (1.5-13.7) 0.4 (0.2-0.9) 
P-interaction    0.0463    0.578    0.7281    0.0007 
                 
Red vegetables                 
NOS1 (rs11068446)                 
    CC 174/196 149/185 51 57 38 37 23  
    CT + TT 66/53 1.5 (1.0-2.3) 44/73 0.8 (0.5-1.2) 22 1.7 (0.9-3.1) 10 0.4 (0.2-0.9) 17 1.9 (1.0-3.8) 0.6 (0.3-1.4) 10 1.7 (0.7-3.8)  1.2 (0.4-3.5) 
P-interaction    0.0353    0.0057    0.0377    0.7181 
NOS1 (rs3782221)                 
    GG 126/154 113/134 31 43 29 28 18 
    AG + AA 112/96 1.4 (1.0-2.1) 80/121 0.8 (0.5-1.2) 42 2.2 (1.3-3.9) 24 0.6 (0.3-1.1) 24 1.5 (0.8-2.8) 18 0.7 (0.4-1.3) 14 1.3 (0.6-2.8) 15 6.3 (1.7-22.7) 
P-interaction    0.0243    0.0011    0.1128    0.0448 
NOS1 (rs545654)                 
    CC 80/63 50/70 31 10 17 16 10 
    CT + TT 158/183 0.6 (0.4-0.9) 140/185 1.1 (0.7-1.7) 41 0.4 (0.2-0.7) 56 2.4 (1.1-5.0) 37 0.6 (0.3-1.2) 30 0.8 (0.4-1.5) 23 0.8 (0.4-1.8) 11 0.7 (0.2-1.8) 
P-interaction    0.0593    0.0002    0.718    0.6200 
NOS1 (rs7298903)                 
    TT 186/210 158/197 53 60 40 40 25 12 
    CT + CC 55/40 1.6 (1.0-2.6) 35/61 0.7 (0.5-1.2) 20 2.1 (1.1-3.9) 0.4 (0.2-0.9) 15 2.3 (1.1-4.7) 0.5 (0.2-1.2) 1.9 (0.8-4.5) 1.7 (0.6-4.7) 
P-interaction    0.0172    0.0015    0.0101    0.9399 
NOS1 (rs12424669)                 
    CC 201/194 149/202 64 47 40 35 29 16 
    CT + TT 39/55 0.6 (0.4-1.0) 44/55 1.1 (0.7-1.7) 0.4 (0.2-0.9) 20 1.7 (0.9-3.2) 15 1.2 (0.6-2.3) 11 1.2 (0.5-2.5) 0.4 (0.1-1.2) 0.5 (0.1-2.3) 
P-interaction    0.0961    0.0073    0.9057    0.7909 
NOS2A (rs3729508)                 
    CC 76/103 82/94 20 30 13 19 14 
    CT + TT 161/145 1.5 (1.0-2.2) 111/161 0.8 (0.5-1.2) 53 2.0 (1.1-3.7) 37 0.7 (0.4-1.2) 40 2.2 (1.1-4.4) 27 0.8 (0.4-1.6) 18 0.9 (0.4-1.9) 11 0.9 (0.3-2.5) 
P-interaction    0.021    0.0086    0.0445    0.9647 
                 
Yellow/orange vegetables                 
NOS1 (rs11068446)                 
    CC 155/205 166/183 49 59 34 40 22 12 
    CT + TT 60/50 1.7 (1.1-2.7) 49/75 0.7 (0.5-1.1) 23 2.1 (1.1-3.8) 10 0.4 (0.2-0.9) 12 1.6 (0.8-3.4) 13 0.9 (0.4-1.7) 1.9 (0.8-4.5) 1.5 (0.5-4.0) 
P-interaction    0.0068    0.001    0.2339    0.709 
NOS1 (rs1552227)                 
    CC 93/128 113/117 25 40 20 25 12 12 
    CT + TT 122/128 1.3 (0.9-2.0) 103/141 0.8 (0.5-1.1) 47 2.1 (1.2-3.7) 29 0.6 (0.3-1.0) 26 1.4 (0.7-2.6) 28 1.0 (0.5-1.8) 19 1.4 (0.6-3.1) 0.5 (0.2-1.3) 
P-interaction    0.0195    0.0014    0.3022     
NOS1 (rs7298903)                 
    TT 163/213 179/200 50 63 36 43 23  13  
    CT + CC 52/43 1.7 (1.1-2.8) 37/58 0.7 (0.5-1.2) 22 2.3 (1.2-4.3) 0.3 (0.1-0.8) 10 1.5 (0.7-3.3) 10 0.8 (0.4-1.8) 2.1 (0.8-5.2) 1.8 (0.6-4.9) 
P-interaction    0.0104    0.0005    0.3115    0.8504 

NOTE: ORs (95% CI) were adjusted for age, race (white, other), family history of NHL, total energy intake (kcal), smoking (ever/never), alcohol consumption (g/d), and body mass index.

Italics, P < 0.05 values and ORs (95% CI) which do not include 1. Boldface, P values that were significant after false discovery rate adjustment for multiple comparisons.

Abbreviations: MZBL, marginal zone B-cell lymphoma; T cell, T/natural killer-cell lymphoma; OR, odds ratio; CI, confidence interval; Ca, cases; Co, controls.

Significant effect modification was identified for SNPs in MPO and NOS1 genes, with total vegetable and fruit intake, were found for NHL overall and FL. Carriers of the variant allele for MPO (rs4401102; CT or TT) had a 1.9-fold increased risk of NHL overall and FL in the high vegetable and fruit intake group, but not in the low intake group. Carriers of the variant allele for NOS1 (rs2293054; AG or AA) had a 50% reduced risk of NHL and a 60% reduced risk of FL in the high vegetable and fruit intake group, and a 2.7-fold increased risk of FL in the low intake group. Carriers of the variant allele for another NOS1 (rs7298903; CT or CC) had a 1.7-fold increased risk of NHL and a 3.0-fold increased risk of FL in the low vegetable and fruit intake group but a 60% reduced risk of FL in the high intake group.

When vegetable intake was investigated alone, significant interactions with SNPs in NOS1 and SOD3 genes were found for DLBCL and CLL/SLL. Carriers of the variant allele for NOS1 (rs545654; CT or TT) had a 60% reduced risk of DLBCL in the low vegetable intake groups but not in the high intake group. Carriers of the variant allele for SOD3 (rs2284659; GT or TT) had a 4.6-fold increased risk of CLL/SLL in the low intake group, whereas a 60% reduced risk of CLL/SLL was observed in the high intake group.

When different types of vegetables were investigated separately, no significant interaction was found for bean vegetables, cruciferous vegetables, or green leafy vegetables after adjusting for multiple comparisons. For red vegetable intake, significant interactions with five SNPs in the NOS1 gene and one SNP in the NOS2A gene were found for DLBCL. Those with variant alleles for NOS1 (rs11068446; CT or TT), NOS1 (rs3782221; AG or AA), NOS1 (rs7298903; CT or CC), and NOS2A (rs3729508; CT or TT) had a 1.7-fold to 2.2-fold increased risk of DLBCL in the low red vegetable intake group, whereas those in the high intake group had a 30% to 60% reduced risk of DLBCL. Those with variant alleles for NOS1 (rs545654; CT or TT) and NOS1 (rs12424669; CT or TT) had a 60% reduced risk of DLBCL in the low red vegetable intake group and a 1.7-fold to 2.4-fold increased risk of DLBCL in the high intake group.

For yellow/orange vegetable intake, significant interactions with three SNPs in the NOS1 gene were found for DLBCL. Those with variant alleles for NOS1 (rs11068446; CT or TT), NOS1 (rs1552227; CT or TT), and NOS1 (rs7298903; CT or CC) had a 2.1-fold to 2.3-fold increased risk of DLBCL in the low yellow/orange vegetable intake group, although it reduces the risk by 40% to 70% in the high intake group. No significant interaction was found when fruit intake overall, or citrus fruit was investigated.

There were a total of 26 haplotype structures identified in the investigated genes (16 two-SNP haplotypes, 7 three-SNP haplotypes, 1 four-SNP haplotype, and 2 five-SNP haplotypes). No significant interaction with haplotype was found for NHL overall or for any histologic subtype. The results were similar when the analyses were limited to Caucasian subjects.

Our study offers the first comprehensive analysis of the interaction between vegetable and fruit intake, genetic polymorphisms in oxidative stress pathway genes, and NHL risk overall and by histologic subtype. We observed that the risk of NHL differs by vegetable and fruit intake when considered in conjunction with genetic variation in NOS1, NOS2A, MPO, and SOD3, with a majority findings of in NOS1, especially for the most prevalent histologic subtypes, DLBCL and FL.

The interaction between vegetable intake and polymorphisms in 28 genes and the risk of NHL overall was recently studied (32). We shared six common SNPs (GPX P200L rs1050450, NOS2A S608L rs2297518, NOS3 D298E rs1799983, NOS3 -762C>T rs2070744, OGG S326C rs1052133, and SOD2 V16A rs4880). Our results are consistent with the previous findings as no interaction was observed for any of overlapping SNPs and vegetable intake.

High vegetable and fruit intake is believed to be protective for many types of cancers as vegetables and fruit are good sources of vitamins and minerals, carotenoids and other antioxidants, and various phytochemicals, each of which may play a role in reducing cancer risk. It is likely a combination of these factors, and other factors not yet explored, that confers protection (33). Vegetable and fruit intake has been previously examined as protective factors for NHL (8-22). Although the majority of studies indicate that a protective effect is found when vegetables and fruit are combined, or for specific types of vegetables and fruits, the evidence from prospective data has been weak (10, 19, 22), and inconsistencies have been observed. Potential explanations for the inconsistency in findings may be due to gender differences (34), lack of examination by NHL histologic subtypes, and the issue of multiple comparisons. However, the gene-diet interactions identified in our multiple comparison–adjusted analyses by NHL subtype could address the inconsistencies observed in previous epidemiologic studies.

The gene-diet interactions identified in our study confer support for prior findings that oxidative stress pathway genes alter NHL risk (27, 35, 36). The genes with polymorphisms shown to affect risk include AKR1A1 and CYBA (27), CPX1 (35), NOS2A, and SOD2 (35, 36). However, in an investigation of the same study population, Lan et al. (27) did not find an association between genetic polymorphisms in MPO or NOS2A and susceptibility to NHL and its major subtypes. Our results suggest that the dietary differences in vegetables and fruit might have masked the role of these genes in the susceptibility of NHL in the previous analyses.

We observed vegetable and/or fruit intake interactions with eight SNPs in NOS genes (seven in NOS1 and one in NOS2A). NOS are isoenzymes that catalyze the synthesis of nitric oxide (NO), a free radical whose role in tumor biology is still controversial (37). On the one hand, NO can favor tumor growth and development by stimulating angiogenesis (38) and causing immunosuppression (39, 40); on the other hand, NO could play a role in tumor regression through its ability to induce apoptosis (41) and facilitate an immune response/rejection of the tumor (42). Studies have shown that certain antioxidants in vegetables and fruit regulate NOS expression and NO production. For example, polyphenols (43-46), which are widely distributed in fruit and vegetables, lutein (47), primarily found in dark-green leafy vegetables and fruit, and tomatoes, inhibit NOS expression and decrease NO production. Soyasaponins (48), which are found in soybeans, garlic and its derivatives (49, 50), dietary soy isoflavones (51), and onion (52) activate NOS expression leading to an increase in NO. Sulforaphane, which is rich in cruciferous vegetables, inhabits hypoxia-inducible factor 1, which regulates NOS2 expression in cancer cells (53).

In addition to the components of vegetables and fruit, other factors such as contamination during cooking or processing, could also modulate NOS expression and affect NHL risk. For example, 3-monochloro-1,2-propanediol, a contaminant of acid-hydrolyzed vegetables which can be formed during the cooking process, was recently found to inhabit NOS1 expression and increase NOS2 expression (54). Our finding of an interaction between NOS1 and NOS2A SNPs and red vegetables (including fresh tomato, cooked tomatoes, and tomato sauce) supports this explanation.

Our finding of the risk associated with NOS1 SNPs suggests that in addition to the known role of NOS1 in cellular communication, it may also be involved in lymphomagenesis and development, and its role could be strongly modified by the intake of vegetables, especially tomatoes, carrots, and other yellow/orange vegetables. NOS1 are constitutively expressed in neurons and endothelial cells (37) and polymorphisms in NOS1 have previously been associated with many diseases and disorders in nervous system, such as Parkinson's disease (55), achalasia (56), restless legs syndrome (57), depression (58), schizophrenia (59), and suicidal behavior (60), whereas demonstrating few associations with cancer. Moreover, none of the risks we identified in NOS1 polymorphisms were functional, implying a need for further exploration on this gene's role in tumor biology. There is, however, evidence of an association between the NOS2 isoform and NHL. Investigators have previously shown that the isoform NOS2 is inducible and expressed in many cell types including macrophage (61), B-lymphocytes (39), lymphoid neoplasms (62-64), and other tumor cells (65-68).

To our knowledge, there is no functional evidence for any of the risk SNPs we identified. NOS1 (rs2293054) is a synonymous mutation on exon 13, although theoretically, this type of mutation may affect splicing and protein structure and function, no evidence is shown for this specific SNP. All the other SNPs are intron variations or found in the cap or tail, which was generally thought to be “junk DNA.” Our findings support the dispute against it, and suggest that more exploration and investigation is needed for these mutations. Specifically, our results suggest that these mutations might affect human health by interacting with common environmental exposure or lifestyle factors such as diet, and were subsequently maintained through evolution.

We did not include specific antioxidant nutrients in our analysis because the major source of antioxidants for human beings is natural plants other than supplements, and more likely, it is the combination of the antioxidants in vegetables and fruit which confers the protection against cancer.

Although we adjusted for multiple comparisons, it is still possible that some of the interactions we identified were due to chance. Our results should be confirmed in future studies with large sample sizes. Three NOS1 SNPs (rs545654, rs7298903, and rs11068446) were significant in the multiple vegetable and/or fruit comparison groups, suggesting a strong likelihood that the association is true and should be investigated in future studies.

In summary, our study supports a role for the modification of oxidative stress pathway genetic variations in the association between vegetable and fruit intake and NHL subtypes. Our results warrant replication in further studies and suggest that future research on the role of nonfunctional variants in lymphoma tumor biology should be explored.

No potential conflicts of interest were disclosed.

Grant support: NIH grant CA62006, the Intramural Research Program of the NIH, National Cancer Institute, and the NIH Fogarty Training Grant 1D43TW007864-01. This publication was made possible by CTSA grant no. UL1 RR024139 from the National Center for Research Resources, a component of the NIH, and the NHL Roadmap for Medical Research. Its contents are solely the responsibility of the authors and do not necessarily represent the official view of the National Center for Research Resources.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

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