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Cancer Research 67, 5042-5054, May 15, 2007. doi: 10.1158/0008-5472.CAN-06-4752
© 2007 American Association for Cancer Research
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Epidemiology and Prevention

Immune Mechanisms in Non–Hodgkin Lymphoma: Joint Effects of the TNF G308A and IL10 T3575A Polymorphisms with Non–Hodgkin Lymphoma Risk Factors

Sophia S. Wang1, Wendy Cozen2, James R. Cerhan3,4, Joanne S. Colt1, Lindsay M. Morton1, Eric A. Engels1, Scott Davis5, Richard K. Severson6, Nathaniel Rothman1, Stephen J. Chanock1,7 and Patricia Hartge1

1 Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Rockville, Maryland; 2 University of Southern California, Los Angeles, California; 3 Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, Minnesota; 4 University of Iowa, Iowa City, Iowa; 5 Fred Hutchinson Cancer Research Center and the University of Washington, Seattle, Washington; 6 Karmanos Cancer Institute and Department of Family Medicine, Wayne State University, Detroit, Michigan; and 7 Core Genotyping Facility, Advanced Technology Corporation, National Cancer Institute, Gaithersburg, Maryland

Requests for reprints: Sophia S. Wang, Division of Cancer Epidemiology and Genetics, National Cancer Institute, 6120 Executive Boulevard, EPS MSC# 7234, Bethesda, MD 20892-7234. Phone: 301-402-5374; Fax: 301-402-0916; E-mail: wangso{at}mail.nih.gov.


   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
Two common single nucleotide polymorphisms in immunoregulatory genes (TNF G308A, rs1800629 and IL10 T3575A, rs1800890) have been recently reported as risk factors for non–Hodgkin lymphoma (NHL) in a large pooled analysis. We systematically investigated the effects of other established NHL risk factors in relation to the tumor necrosis factor (TNF) G308A or interleukin 10 (IL10) T3575A genotypes. We calculated odds ratios (OR) and 95% confidence intervals (95% CI) from 1,172 cases and 982 population-based controls in a U.S. multicenter study. We investigated NHL overall and two common subtypes [diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma]. NHL risks were increased among those with both an autoimmune condition and the TNF G308A GA/AA (ORNHL, 2.1; 95% CI, 1.0–4.2) or the IL10 T3575A TA/AA genotype (ORNHL, 1.6; 95% CI, 0.9–2.6) compared with individuals without an autoimmune condition and with the common TNF G308A GG or IL10 T3575A TT genotype, respectively; results were similar for DLBCL and follicular lymphoma. We found that elevated DLBCL risk associated with last-born status was more pronounced among those with TNF G308A GA/AA (ORDLBCL, 2.7; 95% CI, 1.1–6.4) or IL10 T3575A TA/AA (ORDLBCL, 2.9; 95% CI, 1.6–5.2). Similarly, elevated DLBCL risk associated with obesity (body mass index, ≥35 versus <25 kg/m2) was observed only among those with TNF G308A GA/AA (ORDLBCL, 2.5; 95% CI, 1.1–5.7) or IL10 T3575A TA/AA genotypes (ORDLBCL, 2.0; 95% CI, 1.1–3.5). These exploratory results require replication but provide evidence that autoimmune conditions, late birth order, and obesity act partly through a common inflammatory pathway, posing a greater risk to individuals with variant TNF and IL10 genotypes than those with wild-type alleles. [Cancer Res 2007;67(10):5042–54]


   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
Immune alteration is a major risk factor for non–Hodgkin lymphoma (NHL), but the specific immune mechanisms responsible remain unresolved. Immunologic response is often driven by specific environmental/infectious agents that are influenced by inherited human genetic variation and the host's capacity to elicit immunologic memory. As evidence mounts for inherited genetic variations and other risk factors in NHL, evaluation of their joint effects should provide clues to the specific immune pathways critical for lymphomagenesis.

NHL risk is increased in the presence of autoimmune conditions (e.g., Sjogren's syndrome and lupus; ref. 1), certain infectious agents (e.g., HIV, Helicobacter pylori, human T lymphotropic virus I, human herpesvirus 8, and hepatitis C virus; refs. 2–6), and family history of lymphoma (7). Recent pooled analyses within the International Lymphoma Epidemiology Consortium (InterLymph) have also showed increased NHL risk with smoking (8) and decreased NHL risk with alcohol intake (9). A growing body of evidence indicates that organochlorine pesticides (10, 11) and other organochlorines increase NHL risk (12), and that sunlight decreases risk (13). Evidence for decreased NHL risk with atopic conditions (e.g., allergies and asthma; refs. 14–16) and vitamin B6 (17) and increased risk with obesity, height (18), and later birth order (14) has also been reported, but these associations require further replication.

In a large consortial study within InterLymph, we recently showed an increased risk for NHL, especially the major lymphoma subtype diffuse large B-cell lymphoma (DLBCL), with genetic variations in the tumor necrosis factor (TNF) and interleukin 10 (IL10) immunoregulatory cytokines that mediate inflammation (19–21). There is laboratory-based evidence that the TNF G308A promoter polymorphism elevates expression of the TNF{alpha} protein (22), whereas the IL10 T3575A polymorphism results in lower production of IL-10 (23). Because IL-10 is a potent down-regulator of TNF{alpha}, decreased IL-10 may suppress TNF{alpha} levels less efficiently, resulting in an overall elevated expression of TNF{alpha}. Both polymorphisms are therefore hypothesized to increase TNF{alpha} levels and thus contribute to a shift in the Th1/proinflammatory immune response. As TNF{alpha} activates the nuclear factor-{kappa}B pathway, a central mechanism for inflammation (24), it is plausible that these genetic factors contribute to further chronic inflammation that ultimately lead to lymphomagenesis (20).

To probe the specific immune mechanisms relevant for NHL, we evaluated jointly the TNF G308A and IL10 T3575A polymorphisms and other risk factors associated with NHL in a U.S.-based multicenter case-control study. Specifically, we assessed (a) which risk factors are themselves related to the polymorphisms, (b) the effects of these factors on NHL risk according to the presence or absence of the polymorphisms, and (c) the joint effects between key risk factors and polymorphisms on NHL risk.


   Materials and Methods
Top
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
Study Population
The study population has previously been described in detail (25). We included 1,321 newly diagnosed NHL cases identified in four Surveillance, Epidemiology, and End Results registries (Iowa; Detroit, MI; Los Angeles, CA; and Seattle, WA) ages 20 to 74 years between July 1998 and June 2000 without evidence of HIV infection; 1,057 population controls were identified by random digit dialing (<65 years) and from Medicare eligibility files (≥65 years). Overall participation rates were 76% in cases and 52% in controls; overall response rates were 59% and 44%, respectively. Written informed consent was obtained from each participant before interview.

Histopathology
Each registry provided NHL pathology and subtype information derived from abstracted reports by the local diagnosing pathologist. All cases were histologically confirmed and have been coded according to the International Classification of Diseases for Oncology, 2nd Edition (ICD-O-2; ref. 26) and updated to the WHO/ICD-O-3. We evaluated the histologic subtypes DLBCL and follicular lymphoma.

Questionnaire Data
To accommodate a large number of questions, we used a split-sample design, with a core set of questions given to all respondents and the remainder given to participants in either group A (all African-American participants and 50% of non–African-American participants) or group B (50% of non–African-American participants). Before the in-person interview, participants were mailed a form for listing residential and job history and either a family and medical history questionnaire (group A) or a diet and lifestyle questionnaire (group B). During the home visit, the interviewer administered a computer-assisted personal interview that included core questions on demographics, height, weight, occupational history, pesticide use history, and hair dye use and separate sets of questions for group A and group B respondents.

From all participants, we queried on family history any first-degree family member having NHL or lymphoma not otherwise specified (25). We asked about a history of immune-related disorders including Sjogren's syndrome, lupus, Crohn's disease, ulcerative colitis, rheumatic heart disease, polymyalgia rheumatica, sarcoidosis, multiple sclerosis, uveitis, myasthenia gravis, polymyositis, dermatomyositis, and/or celiac disease (1). We also asked about blood transfusions. We asked about all surgeries since birth, which we summed for a lifetime total. We asked about birth order and characterized it as first- or middle-born child compared with last born. We asked about height and weight and calculated body mass index (BMI) as weight (kg) divided by height (m) squared (18). Height was categorized according to tertile cut points in the control group. We asked about termite treatment via a detailed history of pesticide use in each residence occupied for 2 years since 1970 (10). The interviewer asked when the termite treatments occurred and noted particularly whether they occurred before or after 1988, when the termiticide chlordane was banned in the United States. We categorized the responses as no treatment before 1988 (reference), one or more treatments between 1988, or uncertain whether there was treatment in one or more homes. From group A participants, we asked about asthma.

From the self-administered diet and lifestyle questionnaire given to group B participants, we estimated vitamin B6 intake and dichomotomized it by the median among controls (17). We asked about regular cigarette smoking for at least 6 months. We asked about alcohol intake, defining nondrinkers as those who consumed alcohol less than once per month as an adult. Intensity of ethanol consumption (grams per week) was calculated by number of servings x ethanol per serving (beer, 12.9 g; wine, 9.3 g; and liquor, 15.9 g) and categorized as quartiles according to the distribution among controls. Because of the previously reported protective association between alcohol and NHL, we used the highest level of alcohol intensity (≥60 g/wk) as the reference group. During the interviews with group B participants, sunlight exposures also were ascertained, including an estimate of hours per week in teen years and in the past 10 years (27). Because increased sun was found to decrease NHL risk, we assigned the highest level as the reference group. In addition, eye color was ascertained as an indicator of UV susceptibility and categorized as dark brown, light brown, hazel, blue, and green/blue-green. We also asked about hay fever and other allergies to food, animals, insects, medications, dust, and other triggers. We excluded food allergies as these typically were intolerance rather than allergy.

Environmental Samples
{alpha}-Chlordane and PCB180 were measured from 682 cases and 513 controls from whom dust samples were collected and analyzed (11, 28). A multiple-imputation procedure was used to assign values to missing data (29); in the present analyses, we used values from one of the imputations. Individuals with detectable levels of {alpha}-chlordane or PCB180 (ng/g) were grouped into tertiles based on the control distribution ({alpha}-chlordane: not detectable (reference), 20.8–60.1, 60.3–5,870 ng/g; PCB180: 0–20.7 (reference), 20.8–44.3, >44.3 ng/g).

Serum Samples
PCB180 and total furans were further evaluated in serum samples in a subset of 100 untreated cases and 100 controls (12). A multiple-imputation procedure was also used to assign values to missing data determined to be below the detection limits; in the present analyses, we used one of the imputations. Levels for both analyses were categorized as quartiles according to distribution among controls.

DNA Extraction and Genotyping
All study participants were asked to provide a venous blood or mouthwash buccal cell sample. Overall, 1,172 cases (89%) and 982 controls (93%) for whom biological samples were obtained were genotyped. There was virtually no variation in the availability of DNA between cases and controls or according to availability of risk factor data, except that most of the subjects with serum also had DNA that could be genotyped. As previously described (20), DNA was extracted from blood clots or buffy coats (BBI Biotech) using Puregene Autopure DNA extraction kits (Gentra Systems). DNA was extracted from buccal cell samples by phenol-chloroform extraction methods (30). Genotyping was conducted at the National Cancer Institute Core Genotyping Facility (Gaithersburg, MD) using the Taqman platform. Forty replicate samples from two blood donors each and duplicate samples from 100 participants processed in an identical fashion were interspersed for all assays and blinded from the laboratory. Agreement for quality control replicates and duplicates was >99% for all assays. Successful genotyping was achieved for >99% of DNA samples, and both TNF G308A and IL10 T3575A were in Hardy-Weinberg equilibrium.

Statistical Analysis
Independence of risk factors. Among controls, we calculated odds ratios (OR) and 95% confidence intervals (95% CI) for each risk factor with dichotomized genotype, comparing the presence of a variant allele with the absence of the allele (e.g., TNF –308 AA or AG genotypes versus GG; IL10 3575 AA or TA genotypes versus TT; Table 1 ). For ordinal risk factors with at least three values, we calculated the Ptrend for a linear model.


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  		Table 1. Risk factor distribution by TNF G308A and IL10 T3575A genotypes among controls in the National Cancer Institute-Surveillance Evaluation, Epidemiology, and End Results NHL multicenter case-control study (associations are adjusted for the following study design variables: age, education, sex, race, and study center)

 
Effects of risk factors by genotype. For all NHL cases and for DLBCL and follicular lymphoma, we calculated OR and 95% CI for the joint effect of each risk factor with dichotomized genes as described above (Tables 2 and 3 ). For these analyses, we report the risk estimates for each risk factor stratified by genotype. In general, we chose as the reference group the category with the lowest NHL risk. We calculated Pinteraction based on the scored variable for each risk factor and for genotype; in these calculations, we scored the genotype using the tri-level categorization to assess risk by each additional risk allele.


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  		Table 2. Associations (OR and 95% CI) for NHL, DLBCL, and follicular lymphoma for NHL-relevant risk factors, stratified by TNF G308A genotypes and adjusted for age, education, sex, race, and study center

 

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  		Table 3. Associations (OR and 95% Ci) for NHL, DLBCL, and follicular lymphoma for NHL-relevant risk factors, stratified by IL10 T3575A genotypes and adjusted for age, education, sex, race, and center

 
In the presentation of our results, we have specifically highlighted those risk factors for which risk is statistically significant only within the variant TNF G308A or IL10 T3575A genotypes or where risk elevation within the variant TNF G308A or IL10 T3575A genotypes is equivalent or greater than that reported in the original manuscript.

Joint effects. For selected risk factors, we also calculated risk estimates with a common reference group so that the risk factor category and genotype that confers the least NHL risk is the singular reference group.

All risk estimates are adjusted for the following study design variables: sex, age (<45, 45–64, ≥65 years), race (White, other/unknown), education (<12, 12–15, >15 years), and study center (Detroit, Iowa, Los Angeles, Seattle). All logistic regression models were unconditional and conducted using SAS 9.1.3 (SAS Institute).


   Results
Top
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
We evaluated the independence of all risk factors from TNF G308A and IL10 T3575A genotypes among the controls (Table 1). No consistent statistically significant associations were observed between any risk factor and the TNF G308A or IL10 T3575A genotypes. However, we note a moderate, albeit not statistically significant, association between family history and TNF G308A (OR, 1.7; 95% CI, 0.8–3.8). We also note no association between either genotype with the presence of an autoimmune condition or with obesity. Other elevated but not statistically significant ORs were observed for age, height, and PCB180 as measured from blood with TNF G308A and for eye color and total furans as measured from blood with IL10 T3575A genotypes.

Effects stratified by TNF genotype. We evaluated the risk for NHL, DLBCL, and follicular lymphoma for all risk factors by TNF G308A genotypes (Table 2). Of the family and medical history variables evaluated, autoimmune conditions and status as last-born showed evidence of conveying differential risk by genotype. We observed elevated NHL risks with autoimmune conditions only among those with the TNF GA/AA genotype (OR, 1.7; 95% CI, 0.8–3.5); this risk elevation was consistent for both DLBCL (OR, 1.5; 95% CI, 0.6–3.9) and follicular lymphoma (OR, 3.0; 95% CI, 1.1–8.5). We found elevated NHL risk among those with TNF GA/AA genotypes but not TNF GG genotype for being the last born (OR, 2.0; 95% CI, 1.1–3.8; Table 2). This elevated risk for late birth order among TNF GA/AA genotypes was statistically significant for DLBCL (OR, 2.7; 95% CI, 1.1–6.4) but not follicular lymphoma.

Of the anthropometric and diet variables evaluated, BMI showed the most notable effect. We observed elevated NHL risk among TNF GA/AA genotypes but not GG genotypes for BMI of ≥35 kg/m2 compared with <25 kg/m2 (OR, 1.8; 95% CI, 0.9–3.4). Risk seemed specific for DLBCL (OR, 2.5; 95% CI, 1.1–5.7) and was not observed for follicular lymphoma.

Elevated NHL risks among TNF GA/AA genotypes but not GG genotypes was also evident for eye color for NHL, DLBCL, and follicular lymphoma. Risk increased with darker eye color and was highest for those with dark brown eyes (ORNHL, 3.7; 95% CI, 1.2–11.0; ORDLBCL, 2.4; 95% CI, 0.6–10.1; ORfollicular, 7.3; 95% CI, 1.2–44.5).

All other risk factors associations with NHL were either present only among those with the TNF GG genotype (family history, surgeries, B6 intake, termite treatment, PCB180 in dust or blood) or no different between TNF GG or GA/AA genotypes (asthma, allergies, transfusion, height, smoking, ethanol, sunlight, {alpha}-chordane, total furans). On balance, those patterns suggest no evidence of further risk increase or modification for these risk factors due to the presence of the TNF G308A GA/AA genotype.

Joint effects with TNF. Compared with individuals without an autoimmune condition and with the common TNF genotype, risks for NHL, DLBCL, and follicular lymphoma were highest among those with both the TNF GA/AA genotype and autoimmune conditions (ORNHL, 2.1; 95% CI, 1.0–4.2; ORDLBCL, 2.4; 95% CI, 1.0–5.8; ORfollicular, 2.4; 95% CI, 1.0–6.2; Table 4 ). Similarly, highest risks were observed for those with both the TNF GA/AA genotype and status as last-born child or a BMI of ≥35 kg/m2 compared with those with the TNF GG genotype and status as the first/middle child or BMI of <25 kg/m2, respectively.


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  		Table 4. Selected joint effects with TNF for NHL, DLBCL, and follicular lymphoma, adjusted for age, education, sex, race, and study center

 
Effects stratified by IL10 genotype. Similarly arranged estimates for all risk factor variables by IL10 T3575A genotype are shown in Table 3. Of family and medical history variables evaluated, the presence of an autoimmune condition was associated with elevated NHL (OR, 1.5; 95% CI, 0.9–2.4), DLBCL (OR, 1.4; 95% CI, 0.7–2.9), and follicular lymphoma risk (OR, 1.9; 95% CI, 0.9–3.9) among IL10 TA/AA genotypes but not IL10 TT genotypes. Individuals who reported that they were the last-born also had elevated risks among IL10 TA/AA genotypes for NHL (OR, 1.7; 95% CI, 1.1–2.5) and DLBCL (OR, 2.9; 95% CI, 1.6–5.2) but not among IL10 TT genotypes or for follicular lymphoma (Table 3).

For those reporting having had a blood transfusion, mild elevations in risk for NHL (OR, 1.4; 95% CI, 1.0–1.9) were also observed among IL10 TA/AA genotypes but not IL10 TT genotypes. Although Pinteraction was statistically significant, we note the decreased risk among IL10 TT genotypes, which likely contributed to this statistic.

Of anthropometric and diet variables evaluated, elevated DLBCL risk was observed only among individuals with IL10 TA/AA with BMI ≥35 kg/m2 (OR, 2.0; 95% CI, 1.1–3.5) compared with BMI <25 kg/m2 and not among those with IL10 TT genotypes.

Of environmental exposures evaluated, termite treatment showed differential effects by IL10 genotypes. We observed elevated NHL risks among IL10 TA/AA genotypes but not IL10 TT genotypes for those who had termite treatment before 1988 (OR, 1.4; 95% CI, 1.0–2.0) or the highest tertile of {alpha}-chlordane levels from dust (OR, 1.6; 95% CI, 1.0–2.4). Associations for {alpha}-chlordane, but not termite treatment, seemed pronounced for DLBCL.

All other associations with NHL were either present only among those with the IL10 T3575A TT genotypes (family history, vitamin B6, sunlight in past 10 years, eye color) or no different between IL10 T3575A TT or TA/AA genotypes (asthma, allergy, surgeries, height, smoking, ethanol, PCB180, total furans), suggesting no further risk increase or modification in the presence of the IL10 T3575A TA/AA genotype.

Joint effects with IL10. Highest risks were observed for individuals with both the IL10 TA/AA genotype and autoimmune conditions (ORNHL, 1.6; 95% CI, 0.9–2.6; ORDLBCL, 1.5; 95% CI, 0.8–3.1; ORfollicular, 2.1; 95% CI, 1.0–4.3) when compared with a common reference group of IL10 TT genotype and no autoimmune condition (Table 5 ). Similarly, DLBCL risks were highest for individuals with the IL10 TA/AA genotype and a BMI of ≥35 kg/m2 (OR, 1.8; 95% CI, 1.0–3.2) or with the highest tertile of {alpha}-chlordane levels (OR, 1.8; 95% CI, 1.0–3.4) when compared with a common reference group of IL10 TT genotype and a BMI of <25 kg/m2 or no {alpha}-chlordane exposure, respectively.


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  		Table 5. Selected joint effects with IL10 for NHL, DLBCL, and follicular lymphoma, adjusted for age, education, sex, race, and center

 

   Discussion
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
To our knowledge, this is the first evaluation of recognized NHL risk factors and (a) their association with TNF G308A or IL10 T3575A variant alleles, (b) their risks in the presence and absence of a chronic inflammatory state resulting from TNF G308A or IL10 T3575A variants, and (c) their joint effects. From this broad exploration of the combined effects of genetic and non-genetic factors, several provocative findings have emerged. Family history of NHL is of interest because inherited TNF or IL10 variants could be a genetic basis for familial risk, but our findings suggest that neither variant fully explains the family history association with NHL. On the other hand, history of medical conditions, such as autoimmune conditions and exposure to childhood infections, might be expected to be associated with the variant TNF or IL10 alleles, but we found virtually no association between these risk factors and presence of the variant TNF or IL10 allele among the controls.

Our evaluation of risk factors, stratified by genotype and acting jointly with genotypes, suggests that common genetic variants in TNF and IL10 may potentiate the risk associated with autoimmune conditions, late birth order, and obesity for NHL, specifically in the DLBCL subtype. Different mechanisms could be posited for these risk factors, but we infer that they act through a common pathway that results in chronic antigen stimulation and inflammation. Potential joint effects with termite exposure and {alpha}-chlordane were apparent only with IL10 T3575A variants and NHL, suggesting that although these risk factors may also act on the immunoregulatory pathway, immunosuppression rather than inflammation may be a culpable pathway of interest.

Autoimmune conditions are a well-established risk factor for NHL as shown in this and other studies (1, 31, 32). In the present analysis, we find the increased risk restricted to individuals with either the TNF G308A or IL10 T3575A variant alleles. Although associations between TNF G308A with some autoimmune conditions (e.g., rheumatoid arthritis; ref. 33) have been reported, this variant was not associated with autoimmune conditions (or any individual condition) among our control group. These conditions entail chronic stimulation and proliferation of lymphocytes (34, 35) and an active Th1/proinflammatory immune response (34, 36); thus, the apparent synergy between an already present chronic inflammatory state as induced by TNF G308A or IL10 T3575A and the presence of an autoimmune condition that increases NHL risk strongly suggests that chronic inflammation explains the effect of autoimmune conditions.

Birth order has not yet been firmly established as a risk factor for NHL, although several well-conducted studies recently showed that later-born children have the highest risks for NHL (14, 37, 38) and particularly for DLBCL as recently reported in our population (38). A Th2 immune response predominates in utero (39–41) and shifts to a Th1 response in childhood upon exposure to infectious agents. Because birth order is thought to be a surrogate for general exposure to infectious agents, an individual with a larger number of older siblings likely would be exposed to infectious agents earlier in life. The shift to a Th1 immune response earlier in life may thus correspond to a higher likelihood of having life-long chronic B-cell stimulation (38). Our observation of increased risk among later-born individuals with TNF or IL10 variant genotypes supports the hypothesis that longer periods of prolonged Th1/proinflammatory response or chronic antigenic stimulation, especially early in development, could increase risk of NHL, and especially DLBCL. Later birth order may mark a specific infectious agent or general exposure, but there certainly exists evidence for interaction between TNF and IL10 with infectious agents, including delayed EBV seroconversion and resistance to herpesvirus infection with increased IL10 production (42) and protection against cytomegalovirus with the TNF G308A polymorphism (43).

The association between obesity as defined by a BMI of ≥35 kg/m2 and NHL has been reported (44) and specifically for DLBCL (18, 45). A number of mechanisms have been posited for the observed associations between obesity and cancer (including NHL). These mechanisms include the effects of obesity on endogenous hormone metabolism, DNA damage via production of reactive oxygen species, and inflammation (18). Although our observed association between obesity and risk only in the presence of TNF G308A and IL10 T3575A variants does not disprove any of the alternative explanations, it does support the hypothesis that an obesity-related chronic inflammatory response (46) likely plays an important role in the etiology of NHL and DLBCL. This may contribute to some of the inconsistency in the literature on obesity and NHL.

The previously observed association between termite treatment before 1988 and {alpha}-chlordane with NHL (10) seemed to be restricted to individuals with variant genotypes for IL10 T3575A. The lack of an association among the TNF G308A polymorphism suggests that these risk factors may not act primarily through a proinflammatory pathway. It has been suggested that chlordane has immunosuppressing effects (47). We hypothesize that decreased IL10 expression and exposure to certain termiticides may have a synergistic effect that results in immune suppression and a reduced capacity for the host to counter other environmental agents/infections.

It is unclear why elevated risks for eye color were present only among TNF G308A variants, particularly as no consistent association was observed with our sunlight exposure variables. For other risk factors, such as smoking and height, we infer that different mechanisms may be relevant because we did not observe elevated NHL risks among subjects with variant TNF or IL10 genotypes. Indeed, we recently reported the joint effect between the N-acetyltransferase 1 and 2 phenotypes with smoking in follicular lymphoma (48), which supports a role for diarylamines or heterocyclic amines in lymphomagenesis. We observed no consistent joint effect between TNF G308A and IL10 T3575A polymorphisms and those risk factors previously found to decrease NHL risk, including the Th2-type risk factors (e.g., asthma and allergy), ethanol, vitamin B6 intake, and sunlight. These results suggest that the mechanisms by which asthma, allergies, sunlight, and other risk factors reduce the risk of lymphomagenesis do not necessarily act through diminution of inflammation via TNF{alpha} or IL10.

Strengths of our study include the systematic approach we took to evaluating the joint effects of two important genetic polymorphisms with a wide range of other risk factors observed in the present study (1, 10, 11, 18, 20, 25, 27, 38) that have been replicated in large pooled analyses (7–9, 19) or consistent with the literature (13, 14, 31, 37, 45, 49, 50).

The major limitation was low statistical power for estimating the combined effects of TNF or IL10 polymorphisms and less common risk factors for specific lymphoma subtypes. In this broad exploration, we identified an interesting pattern, but these results require replication, such as within the InterLymph Consortium. Other limitations include that genetic variability of inflammatory/immune pathways is not completely explained by TNF or IL10, and that childhood infections and other risk factors were imperfectly assessed. Finally, our study analyzed two polymorphisms already identified as risk factors for NHL, but it is possible that one or both polymorphisms are in linkage disequilibrium with another variant that could confer the observed biological effect.

In summary, our results provide suggestive evidence that autoimmune conditions, obesity, and later birth order could contribute to lymphomagenesis through an alteration of the proinflammatory pathway, specifically involving common genetic variants in TNF and IL10. Furthermore, these data suggest that this pathway may be particularly important for DLBCL. Further studies are needed to investigate the joint effects between risk factors and common genetic variations in these and other genes that regulate the inflammatory response.


   Acknowledgments
 
Grant support: Intramural Research Program at the NIH National Cancer Institute and USPHS contracts N01-PC-65064, N01-PC-67008, N01-PC-67009, N01-PC-67010, and N02-PC-71105.

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.

We thank Lonn Irish (Information Management Services, Inc., Silver Spring, MD) for programming support and Geoffrey Tobias for research assistance.


   Footnotes
 
Note: Written informed consent was obtained from all participants in accordance with U.S. Department of Health and Human Services guidelines. This study was approved by the institutional review boards at the NIH and at each participating Surveillance Evaluation, Epidemiology, and End Results site (Iowa, Seattle, Los Angeles, and Detroit).

Received 12/27/06. Revised 3/ 1/07. Accepted 3/ 6/07.


   References
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 

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