Severson, Richard K.

Abstract Some autoimmune disorders are increasingly recognized as risk factors for non-Hodgkin lymphoma (NHL) overall, but large-scale systematic assessments of risk of NHL subtypes are lacking. We performed a pooled analysis of self-reported autoimmune conditions and risk of NHL and subtypes, including 29 423 participants in 12 case-control studies. We computed pooled odds ratios (OR) and 95% confidence intervals (CI) in a joint fixed-effects model. Sjögren syndrome was associated with a 6.5-fold increased risk of NHL, a 1000-fold increased risk of parotid gland marginal zone lymphoma (OR = 996; 95% CI, 216-4596), and with diffuse large B-cell and follicular lymphomas. Systemic lupus erythematosus was associated with a 2.7-fold increased risk of NHL and with diffuse large B-cell and marginal zone lymphomas. Hemolytic anemia was associated with diffuse large B-cell NHL. T-cell NHL risk was increased for patients with celiac disease and psoriasis. Results for rheumatoid arthritis were heterogeneous between studies. Inflammatory bowel disorders, type 1 diabetes, sarcoidosis, pernicious anemia, and multiple sclerosis were not associated with risk of NHL or subtypes. Thus, specific autoimmune disorders are associated with NHL risk beyond the development of rare NHL subtypes in affected organs. The pattern of associations with NHL subtypes may harbor clues to lymphomagenesis.

Abstract 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]

AbstractRecent gene-expression data have suggested that host immune genetic signatures may predict outcomes in patients with follicular lymphoma. We evaluated the hypothesis that germ line common variation in candidate immune genes is associated with survival. Cox models were used to estimate hazard ratios (HR) and corresponding 95% confidence intervals for individual SNPs after accounting for age, clinical, and other demographic factors. The median age at diagnosis of the 278 patients was 57 years, and 59 (21%) of the patients died during follow-up, with a median follow-up of 59 months (range, 27-78 months) for surviving patients. SNPs in IL8 (rs4073; HRTT = 2.14, 1.26-3.63), IL2 (rs2069762; HRGT/TT = 1.80, 1.06-3.05), IL12B (rs3212227; HRAC/CC = 1.83, 1.06-3.06), and IL1RN (rs454078; HRAA = 1.93, 1.11-3.34) were the most robust predictors of survival. A summary score of the number of deleterious genotypes from these genes was strongly associated with survival (P = .001). A risk score that combined the 4 SNPs with the clinical and demographic factors was even more strongly associated with survival (P < .001); the 5-year Kaplan-Meier survival estimates were 96% (93%-100%), 72% (62%-83%), and 58% (48%-72%) for groups at low, intermediate, and high risk, respectively. Common variation in host immune genes warrants further evaluation as a promising class of prognostic factors in follicular lymphoma.

AbstractA role for genetic susceptibility in non-Hodgkin lymphoma (NHL) is supported by the accumulating evidence of common genetic variations altering NHL risk. However, the pattern of NHL heritability remains poorly understood. We conducted a pooled analysis of 10 211 NHL cases and 11 905 controls from the International Lymphoma Epidemiology Consortium (InterLymph) to evaluate NHL risk among those with hematopoietic malignancies in first-degree relatives. Odds ratios (ORs) and 95% confidence intervals (CIs) of NHL and its subtypes were estimated from unconditional logistic regression models with adjustment for confounders. NHL risk was elevated for individuals who reported first-degree relatives with NHL (OR = 1.5; 95% CI = 1.2-1.9), Hodgkin lymphoma (OR = 1.6; 95% CI = 1.1-2.3), and leukemia (OR = 1.4; 95% CI = 1.2-2.7). Risk was highest among individuals who reported a brother with NHL (OR = 2.8; 95% CI = 1.6-4.8) and was consistent for all NHL subtypes evaluated. If a first-degree relative had Hodgkin lymphoma, NHL risk was highest if the relative was a parent (OR = 1.7; 95% CI = 1.0-2.9). If a first-degree relative had leukemia, NHL risk was highest among women who reported a sister with leukemia (OR = 3.0; 95% CI = 1.6-5.6). The pattern of NHL heritability appeared to be uniform across NHL subtypes, but risk patterns differed by specific hematopoietic malignancies and the sex of the relative, revealing critical clues to disease etiology.

Abstract Profound disruption of immune function is an established risk factor for non-Hodgkin lymphoma. We report here a large-scale evaluation of common genetic variants in immune genes and their role in lymphoma. We genotyped 57 single nucleotide polymorphisms (SNP) from 36 candidate immune genes in 1,172 non-Hodgkin lymphoma cases and 982 population-based controls from a US multicenter study. We calculated odds ratios (OR) and 95% confidence intervals (95% CI) for the association between individual SNP and haplotypes with non-Hodgkin lymphoma overall and five well-defined subtypes. A haplotype comprising SNPs in two proinflammatory cytokines, tumor necrosis factor-α and lymphotoxin-α (rs1800629, rs361525, rs1799724, rs909253, and rs2239704), increased non-Hodgkin lymphoma risk overall (OR, 1.31; 95% CI, 1.06-1.63; P = 0.01) and notably for diffuse large B cell (OR, 1.64; 95% CI, 1.23-2.19; P = 0.0007). A functional nonsynonymous SNP in the innate immune gene Fcγ receptor 2A (FCGR2A; rs1801274) was also associated with non-Hodgkin lymphoma; AG and AA genotypes were associated with a 1.26-fold (95% CI, 1.01-1.56) and 1.41-fold (95% CI, 1.10-1.81) increased risk, respectively (Ptrend = 0.006). Among non-Hodgkin lymphoma subtypes, the association with FCGR2A was pronounced for follicular and small lymphocytic lymphomas. In conclusion, common variants in genes influencing proinflammatory and innate immune responses were associated with non-Hodgkin lymphoma risk overall and their effects could vary by subtype. Our results require replication but potentially provide important clues for investigating common genetic variants as susceptibility factors and in disease outcomes, treatment responses, and immunotherapy targets. (Cancer Res 2006; 66(19): 9771-80)

Abstract Polychlorinated biphenyls (PCB) have been suspected as possible contributors to increasing non-Hodgkin's lymphoma incidence during the latter half of the 20th century based on their toxicologic properties and provocative epidemiologic reports. We investigated PCBs and other organochlorines and risk of non-Hodgkin's lymphoma in a population-based case-control study in the United States. Congeners of PCBs (including coplanar congeners), dioxins, furans and pesticides or pesticide metabolites were measured in plasma of 100 untreated cases and 100 control subjects. We used a multiple imputation procedure to fill in missing values of levels determined to be below the detection limits. Risks of non-Hodgkin's lymphoma associated with each analyte were estimated using conditional logistic regression for the continuous measure, exposure quartiles, trend across quartile categories, and exposures above the 95th percentile. Certain PCB congeners were associated with increased risk of non-Hodgkin's lymphoma, including coplanar PCBs 156, 180, and 194, with odds ratios for the highest versus lowest quartile ranging from 2.7 to 3.5, and significant trends. Each of the furan congeners was associated with risk of non-Hodgkin's lymphoma, as were total furans, with 3.5-fold increased risk for the highest versus lowest quartile and a significant trend across quartiles (P = 0.006). The toxic equivalency quotient (TEQ), a summed metric that weights congeners by their dioxin-like potency, was associated with non-Hodgkin's lymphoma, with 35% increased risk per 10 TEQ pg/g lipid (95% confidence interval, 1.02-1.79). Our results add to existing literature, which suggests that exposure to organochlorines contributes to non-Hodgkin's lymphoma risk; these risks were most apparent for certain PCBs and furans.

Abstract Context: Environmental exposure to herbicides has been hypothesized to contribute to the long-term increase in non-Hodgkin lymphoma (NHL). Objective: To estimate the effects of residential herbicide exposure on NHL risk. Design: Population-based case-control study. Setting: Iowa and metropolitan Detroit, Los Angeles, and Seattle, 1998 to 2000. Participants: NHL patients ages 20 to 74 years and unaffected residents identified by random digit dialing and Medicare eligibility files. Main Outcome Measures: Computer-assisted personal interviews (1,321 cases, 1,057 controls) elicited data on herbicide use at each home occupied since 1970. Levels of 2,4-dichlorophenoxy-acetic acid and dicamba were measured in dust taken from used vacuum cleaner bags in the current home (679 cases, 510 controls who had owned at least half of their carpets for ≥5 years). Results: Herbicide use on the lawn or garden was similar among cases and controls (adjusted relative risk, 1.02; 95% confidence interval, 0.84-1.23). Estimated risk did not increase with greater duration, frequency, or total number of applications of herbicides to the lawn, the garden, or to both combined. Risk was not elevated for respondents who applied the herbicides themselves and not for those exposed during the 1970s, 1980s, or 1990s. We detected 2,4-dichlorophenoxy-acetic acid equally often in homes of cases and controls (78%). We found dicamba in homes of 15% of cases and 20% of controls. We also found no elevation in risk among the respondents who had the highest dust levels and highest self-reported exposures. We found no consistent patterns for specific histologies. Conclusions: We found no detectable excess associated with residential exposures. Residential herbicide exposures are unlikely to explain the long-term increase in NHL.

Abstract Background: The International Lymphoma Epidemiology Consortium (InterLymph) provides an opportunity to analyze the relationship between cigarette smoking and non-Hodgkin lymphoma with sufficient statistical power to consider non-Hodgkin lymphoma subtype. The results from previous studies of this relationship have been inconsistent, likely due to the small sample sizes that arose from stratification by disease subtype. To clarify the role of cigarette smoking in the etiology of non-Hodgkin lymphoma, we conducted a pooled analysis of original patient data from nine case-control studies of non-Hodgkin lymphoma conducted in the United States, Europe, and Australia. Methods: Original data were obtained from each study and uniformly coded. Risk estimates from fixed-effects and two-stage random-effects models were compared to determine the impact of interstudy heterogeneity. Odds ratios (OR) and 95% confidence intervals (95% CI) were derived from unconditional logistic regression models, controlling for study center, age, sex, and race. Results: In our pooled study population of 6,594 cases and 8,892 controls, smoking was associated with slightly increased risk estimates (OR, 1.07; 95% CI, 1.00-1.15). Stratification by non-Hodgkin lymphoma subtype revealed that the most consistent association between cigarette smoking and non-Hodgkin lymphoma was observed among follicular lymphomas (n = 1452). Compared with nonsmokers, current smokers had a higher OR for follicular lymphoma (1.31; 95% CI, 1.12-1.52) than former smokers (1.06; 95% CI, 0.93-1.22). Current heavy smoking (≥36 pack-years) was associated with a 45% increased OR for follicular lymphoma (1.45; 95% CI, 1.15-1.82) compared with nonsmokers. Conclusions: Cigarette smoking may increase the risk of developing follicular lymphoma but does not seem to affect risk of the other non-Hodgkin lymphoma subtypes we examined. Future research is needed to determine the biological mechanism responsible for our subtype-specific results.

Abstract A possible role for SV40, a macaque polyomavirus, in non-Hodgkin lymphoma (NHL) in humans was raised recently by the reported detection of SV40 DNA in tumor tissue. Animals with SV40-induced tumors frequently produce high-level antibodies against T antigen, the SV40 oncoprotein. In this study, we assessed whether SV40 T antibody measured in humans supported a relationship between SV40 and NHL. Subjects were sampled from a U.S. population-based case-control study of NHL, according to presence of antibodies against capsids of SV40 and BK, a related human polyomavirus (n = 85 cases, n = 95 controls). T antibody was measured by enzyme immunoassay. We also evaluated serum specimens from SV40-infected and SV40-uninfected macaques (n = 19 and n = 8, respectively), SV40-uninfected hamsters (n = 5), and hamsters with SV40-induced tumors (n = 10). Hamsters with SV40-induced tumors all produced robust SV40 T antibody [median absorbance, 0.99), whereas SV40-uninfected hamsters and macaques had much lower levels (median absorbance, 0.05 and 0.04, respectively). NHL cases, controls, and SV40-infected macaques resembled these latter two groups, generally showing only low-level T antibody (median absorbance, 0.03, 0.04, and 0.04, respectively). Overall, only five cases (6%) and five controls (5%) had T antibody responses classified as seropositive (odds ratio, 1.2; 95% confidence interval, 0.3-4.6). Interestingly, all 10 humans with T antibody responses also showed antibody responses to BK capsid. We found no association between the presence of T antibody and NHL, arguing against SV40 as a cause of NHL. Infrequent and low-level T antibody responses among humans could represent cross-reactivity to BK virus T antigen.

Abstract Quantitative measurements of environmental factors greatly improve the quality of epidemiologic studies but can pose challenges because of the presence of upper or lower detection limits or interfering compounds, which do not allow for precise measured values. We consider the regression of an environmental measurement (dependent variable) on several covariates (independent variables). Various strategies are commonly employed to impute values for interval-measured data, including assignment of one-half the detection limit to nondetected values or of “fill-in” values randomly selected from an appropriate distribution. On the basis of a limited simulation study, we found that the former approach can be biased unless the percentage of measurements below detection limits is small (5–10%). The fill-in approach generally produces unbiased parameter estimates but may produce biased variance estimates and thereby distort inference when 30% or more of the data are below detection limits. Truncated data methods (e.g., Tobit regression) and multiple imputation offer two unbiased approaches for analyzing measurement data with detection limits. If interest resides solely on regression parameters, then Tobit regression can be used. If individualized values for measurements below detection limits are needed for additional analysis, such as relative risk regression or graphical display, then multiple imputation produces unbiased estimates and nominal confidence intervals unless the proportion of missing data is extreme. We illustrate various approaches using measurements of pesticide residues in carpet dust in control subjects from a case–control study of non-Hodgkin lymphoma.