A population-based case–control study of lymphomas in England collected height and weight details from 699 non-Hodgkin's lymphoma (NHL) cases and 914 controls. Obesity, defined as a body mass index (BMI) over 30 kg m−2 at five years before diagnosis,, was associated with an increased risk of NHL (OR=1.5, 95% CI 1.1–2.1). The excess was most pronounced for diffuse large B-cell lymphoma (OR=1.9, 95% CI 1.3–2.8). Genetic variants in the leptin (LEP 19G>A, LEP −2548G>A) and leptin receptor genes (LEPR 223Q>R), previously shown to modulate NHL risk, as well as a polymorphism in the energy regulatory gene adiponectin (APM1 276G>T), were investigated. Findings varied with leptin genotype, the risks being decreased with LEP 19AA (OR=0.7, 95% CI 0.5–1.0) and increased with LEP −2548GA (OR=1.3, 95% CI 1.0–1.7) and −2548AA (OR=1.4, 95% CI 1.0–1.9), particularly for follicular lymphoma. These genetic findings, which were independent of BMI, were stronger for men than women.
Apart from a small proportion caused by severe immunosuppression, the cause of the majority of non-Hodgkin's lymphomas (NHL) remains largely unknown. Both over- and undernutrition can suppress immunity via for example leptin, leptin receptor and adiponectin, which are expressed by adipocytes to regulate food intake and energy expenditure (Marti et al, 2001; Samartin and Chandra 2001). Accordingly, it has been suggested that anthropometric measures, reflecting the degree of adiposity, as well as polymorphisms in genes associated with energy homeostasis such as leptin (LEP), leptin receptor (LEPR) and adiponectin (APM1), may increase NHL risk. However, while positive associations have been reported between NHL and anthropometric characteristics (Holly et al, 1999; Calle et al, 2003; Bahl et al, 2004; Pan et al, 2004), others have not (Paffenbarger Jr et al, 1978; Whittemore et al, 1985; Franceschi et al, 1989; La Vecchia et al, 1990; Zhang et al, 1999; Cerhan et al, 2002; Chang et al, 2005). Furthermore, polymorphisms in the LEP (an A to G nucleotide (nt) change at position 19 in the 5′-untranslated region (Hager et al, 1998), and a G to A substitution at nt −2548 upstream of the ATG start site (Mammes et al, 1998)) and LEPR (an A to G transition at nt 668 from the start codon that converts glutamine to arginine at codon 223 (223Q>R) (Gotoda et al, 1997)) genes were recently shown to modulate NHL risk (Skibola et al, 2004).
Anthropometric and genetic findings from a large population-based case–control study of NHL carried out in England during the 1990s are presented here. Specifically, the potential aetiological role of body mass index (BMI) and the polymorphisms LEP 19A>G, LEP −2548G>A, and LEPR 223Q>R, as well as a polymorphism in the APM1 gene (a G to T substitution at nt 276 downstream of the ATG start site denoted APM1 276G>T (Hara et al, 2002)), are investigated.
Materials and methods
Details of this case–control study are described elsewhere (Willett et al, 2004). Briefly, cases were patients aged 18–64 years newly diagnosed with lymphoma between January 1998 and March 2001. Diagnoses were pathologically confirmed and coded to the World Health Organisation Classification (Fritz et al, 2000), and patients were ineligible if they had a previous diagnosis of lymphoma or HIV. One control per case, individually matched on sex and date of birth, was randomly selected from population registers. All participants were interviewed in person, and asked to provide a blood sample for research purposes. Study subjects were assigned an area-based indicator of deprivation by coding the enumeration districts (ED) where subjects resided at diagnosis/reference date to categories of the 1991 census-derived Townsend scores of EDs across England and Wales (Townsend et al, 1988). The study was conducted with the ethical approval of the United Kingdom Multi-Regional Ethical Committee.
At interview, participants were asked what their height and weight was at 5, 10 and 20 years prior to diagnosis/reference date. Body mass index was computed by dividing weight in kilograms by the square of height in metres. Height was categorised based on the observed distributions among controls who were aged 18 years or over at each time point. Body mass index was grouped into underweight (<18.5 kg m−2), normal (18.5–24.99 kg m−2), grade 1 overweight (25–29.99 kg m−2), and grades 2 and 3 overweight (30 kg m−2 or more) (WHO Expert Committee on Physical Status, 1995).
DNA was isolated from peripheral blood mononuclear cells using a modified phenol–chloroform extraction and was quantified using PicoGreen® dsDNA Quantitation kits (Molecular Probes, Eugene, OR, USA), according to the manufacturer's specifications. Samples, blinded to case–control status, were genotyped using Taqman®-based assays designed by Applied Biosystems (ABI) (Applied Biosystems, Foster City, CA, USA). Reactions were performed on an ABI 7700 or GeneAmp PCR 9700 System for 10 min at 95°C, then 40 cycles of 95°C for 15 s and 60°C for 1 min; a post-PCR plate read on the ABI 7700 system was used to determine genotype. Genotyping probes and primers used are listed in Table 1. To ensure reproducibility of the genotyping procedure, replicate quality control samples were included with an agreement rate of over 99%.
Interviews were conducted with 912 lymphoma patients and 919 controls, 75% of cases and 71% of the controls identified, and blood samples were received from 843 (94%) cases and 829 (95%) controls who were interviewed. Among the 820 Caucasian cases and 826 Caucasian controls who gave a blood sample, 736 (90%) cases and 754 (91%) controls had sufficient DNA to genotype all SNPs under investigation; insufficient or no DNA was available to test all four SNPs for 84 (10%) cases and 72 (9%) controls. The analysis presented here for height and BMI are restricted to 699 Caucasian cases with a confirmed diagnosis of NHL and 914 Caucasian controls, all aged 18–59 at 5 years prior to diagnosis/reference date, while the analysis of the genotyping data includes 593 Caucasian cases with a confirmed diagnosis of NHL and 754 Caucasian controls. All analyses include controls matched to NHL and Hodgkin's lymphoma (HL) cases.
Odds ratios (OR) and 95% confidence intervals (CI), adjusted for sex, age and region, were calculated using unconditional logistic regression; risk estimates for matched analyses were also computed using conditional logistic regression (Breslow and Day, 1980). Tests for trend and for interaction were conducted using the likelihood ratio test. Haplotype frequencies were estimated using log-linear modelling embedded within an expectation maximisation algorithm. All analyses were performed using Stata (StataCorp, 2003).
Among interviewed cases with a confirmed diagnosis, 317 (45%) were diagnosed with diffuse large B-cell lymphoma (DLBCL), 228 (33%) with follicular lymphoma (FL), and 154 (22%) with rarer forms of NHL. A higher proportion of men than women were diagnosed with NHL and this increased with age. The majority of controls (76%) were individually matched to cases on sex and age, and although cases tended to be older due to the inclusion of controls matched to patients diagnosed with Hodgkin's lymphoma, there was little difference between the mean ages of cases (53.5 years) and controls (51.8 years). Cases and controls, who were interviewed or those who were genotyped for energy homeostasis SNPs, were similar with respect to deprivation (data not shown).
Table 2 presents the height distributions of cases and controls. Compared to those whose reported height was between 1.74 and 1.80 m, men of taller or shorter stature were not at increased risk of NHL, DLBCL or FL. With the exception of an increased risk for women less than 1.53 m tall (OR=2.2, 95% CI 0.9–5.1, P=0.07), no excess of NHL was observed for women who were over or under 1.58–1.68 m tall. This elevated risk in the smallest females was evident for DLBCL (OR=2.9, 95% CI 0.9–9.0, P=0.07) and not FL, where rather, risks were decreased among women of above average height (1.69–1.73 m: OR=0.5, 95% CI 0.3–1.0, P=0.06; >1.73 m: OR=0.4, 95% CI 0.2–1.0, P=0.06).
Using the WHO categorisation of BMI (Table 3), risks were estimated relative to cases and controls who were of normal weight-for-height. Persons who were underweight were at decreased risk (OR=0.5, 95% CI 0.2–1.5, P=0.22), while those who were grade 1 overweight (OR=1.2, 95% CI 1.0–1.5, P=0.10), or grades 2 or 3 overweight (OR=1.5, 95% CI 1.1–2.1, P=0.01) were at increased risk of NHL. Tests for trend were significant for NHL and DLBCL but not for FL; a 5 kg m−2 rise in BMI increasing the risk of DLBCL by 30% (95% CI 1.2–1.5, P<0.0001). These patterns were similar for men and women (data not shown). With respect to age at diagnosis, there was some suggestion that the risk of NHL associated with being markedly overweight may be more pronounced at younger ages: the OR falling from 2.7 (95% CI 1.2–5.8, P=0.01), to 1.8 (95% CI 1.0–3.3, P=0.04) to 1.2 (95% CI 0.8–1.9, P=0.42) in those aged under 45, 45–54 and 55 years or more, respectively. Further, among the under 45 s, the finding was stronger for DLBCL (OR=3.0, 95% CI 1.2–7.5, P=0.02) than for FL (OR=1.8, 95% CI 0.5–6.3, P=0.33). Within the DLBCL subtype, risks were greater among men aged less than 45 (OR=4.7, 95% CI 1.1–19.4, P=0.03 based on five cases and four controls) than among women of the same age group (OR=2.5, 95% CI 0.7–8.6, P=0.15 based on five cases and 10 controls). Analyses were repeated using anthropometric data at 10 and 20 years before diagnosis/reference date, and using the individually matched controls alone and conditional logistic regression, and the findings were similar (data not shown).
Genotype distributions for cases and controls for the LEP 19G>A, LEP −2548G>A, LEPR 223Q>R and APM1 276G>T polymorphisms are shown in Table 4. Control genotype distributions for all SNPs were in Hardy–Weinberg equilibrium. Relative to LEP 19GG, the LEP 19AA genotype was inversely associated with FL (OR=0.5, 95% CI 0.3–0.8, P=0.01), but not DLBCL (OR=0.9, 95% CI 0.6–1.4, P=0.70). For LEP −2548G>A, an increased risk for NHL was observed among carriers of the LEP −2548GA (OR=1.3, 95% CI 1.0–1.7, P=0.03) and LEP −2548AA genotypes (OR=1.4, 95% CI 1.0–1.9, P=0.04), particularly for FL (LEP −2548GA: OR=1.6, 95% CI 1.1–2.3, P=0.01; LEP −2548AA: OR=1.4, 95% CI 0.9–2.3, P=0.12) when compared to LEP −2548GG carriers. Stratifying by sex revealed that among men, the LEP 19AA genotype was associated with a reduced risk of NHL (OR=0.6, 95% CI 0.4–1.0, P=0.06) and FL (OR=0.3, 95% CI 0.1–0.7, P=0.005), while the LEP −2548AA genotype was associated with an increased risk of NHL (OR=1.6, 95% CI 1.1–2.5, P=0.02), DLBCL (OR=1.6, 95% CI 1.0–2.7, P=0.07) and FL (OR=1.8, 95% CI 0.9–3.5, P=0.10). No associations were found in women with the exception of an increased risk of FL among carriers of the LEP 223RR (OR=1.9, 95% CI 1.0–3.6, P=0.04) relative to the LEP 223QQ genotype. There were no differences in genotype distributions between cases and controls for the APM1 276G>T SNP. Tests for interactions between SNPs were not statistically significant. LEP 19G>A and LEP −2548G>A among controls, with estimated haplotype frequencies of −2548G/19A, 41.5%; −2548G/19G, 18.5%; −2548A/19G, 39.2%; and −2548A/19A, 0.8%, were in linkage disequilibrium (D=0.95), but despite the individual SNP effects, no associations between haplotypes and either NHL as a whole or FL in particular emerged.
Risks associated with BMI among interviewed and genotyped subjects were similar, with the OR of NHL among the 593 cases and 754 controls who were genotyped being 1.2 (95% CI 0.9–1.5, P=0.16) and 1.4 (95% CI 1.0–2.0, P=0.08) for being grade 1 and grades 2 or 3 overweight, respectively. To assess whether the risk associated with the energy homeostasis polymorphisms differed by BMI, analyses were repeated stratifying the genotyping data by WHO categories of BMI. The risks associated with the variant genotypes did not increase with rising grades of obesity; for example, the risk of NHL did not incline among persons carrying the LEP −2548AA genotype with increasing weight-for-height, from normal weight (OR=1.3, 95% CI 0.9–2.0, P=0.19), through grade 1 overweight (OR=1.5, 95% CI 0.9–2.5, P=0.09), to grades 2 and 3 overweight (OR=0.9, 95% CI 0.3–2.5, P=0.88). Similarly, there was no suggestion that the risk estimates associated with the leptin SNPs varied between persons of normal BMI, grade 1, or grades 2 and 3 obesity (data not shown).
Here we present evidence that obesity and variants in the LEP gene may be important in the pathogenesis of NHL. Specifically, we found an association between NHL and excess adiposity estimated using BMI 5 years prior to diagnosis in both men and women, with a greater risk found among patients diagnosed at younger ages (<45 years). Risks were elevated for the two most common NHL subtypes, but the association remained statistically significant only for DLBCL. In contrast, the LEP 19G>A and LEP −2548G>A polymorphisms altered the risk of FL, particularly among men. These SNPs were not associated with risk of DLBCL and, generally, no associations were observed for LEPR 223Q>R and APM1 276G>T. Given the increasing obesity and lymphoma rates worldwide, our findings may have important public health implications.
While several studies have suggested that the risk of NHL associated with BMI varies little with age and sex (Holly et al, 1999; Calle et al, 2003; Pan et al, 2004; Chang et al, 2005), our study is the first to examine risk by disease subtype, sex and age. With respect to the former, we, like others (Cerhan et al, 2002; Skibola et al, 2004; Chang et al, 2005), found that the risk of DLBCL rose with increasing BMI, but patterns for FL were less consistent. Non-Hodgkin's lymphoma, and particularly DLBCL, is more common in men than women and the incidence increases with age above 25 years (Clarke and Glaser, 2002; Cartwright et al, 2005). Our observation for DLBCL in young men is based on small numbers, but if real, could reflect the effects of weight gain early in adulthood. Not only does body fat, and hence BMI, increase with age, but the site of fat deposition may also be important – men being most likely to accumulate abdominal fat than women (WHO Consultation on Obesity, 2000). Better markers of central, rather than total, adiposity would be waist circumference or waist-to-hip ratio (WHO Consultation on Obesity, 2000), which, up to now, have only been reported in one study of women, but no association with NHL was found (Cerhan et al, 2002). If weight gain in early adulthood is not responsible, our results could instead suggest that obesity from childhood is a risk factor for NHL. It seems unlikely however that nutrition during childhood, linked to adult stature (Silventoinen, 2003), increases NHL risk, since generally little evidence of an association with height has been presented either here or elsewhere (Whittemore et al, 1985; La Vecchia et al, 1990; Zhang et al, 1999; Cerhan et al, 2002). Alternatively, it may be that an underlying genetic component of obesity is involved in the pathogenesis of NHL.
Leptin, an adipokine which circulates at levels proportional to adipose tissue mass, regulates immune function as well as nutritional status (Otero et al, 2005). As circulating levels increase, leptin acts to modulate food intake, but in obesity, its rise with increasing body fat has limited effect on satiety, suggesting negative regulators of leptin and insulin signalling, such as leptin receptor and adiponectin, are present (Bell et al, 2005). In the absence of measured plasma levels before the diagnosis of NHL, long-term variation in production of these adiponectins may be indicated by the polymorphisms investigated here, since the LEP 19G, LEP −2548A and LEPR 223R alleles have been associated with elevated leptin levels, and the APM1 276T allele with lower adiponectin levels (Hoffstedt et al, 2002; van Rossum et al, 2003; Filippi et al, 2004). Further, these polymorphisms have been linked with an obese phenotype in some Caucasian populations (Li et al, 1999; Mammes et al, 2000; Quinton et al, 2001; Yiannakouris et al, 2001; Nieters et al, 2002; Filippi et al, 2004; Jiang et al, 2004). Previously, Skibola et al (2004) reported that, relative to the LEP 19AA genotype, carriers of the LEP 19G allele were at increased risk of NHL, particularly FL (OR=1.9, 95% CI 1.0–3.6). Using LEP 19GG as the referent group, the recalculated FL risk estimate for the LEP 19AA genotype is 0.6 (95% CI 0.3–1.3), similar to the OR of 0.5 (95% CI 0.3–0.8) presented here. As has been observed elsewhere, the BMIs of our controls were not correlated with LEP 19G>A (ρ=0.014, P=0.70) (Karvonen et al, 1998; Lucantoni et al, 2000), LEP −2548G>A (ρ=−0.013, P=0.72) (Mammes et al, 1998; Le Stunff et al, 2000), LEPR 223Q>R (ρ=−0.008, P=0.83) (Gotoda et al, 1997; Rosmond et al, 2000; Wauters et al, 2001) or APM1 276G>T (ρ=−0.024, P=0.51) (Menzaghi et al, 2002; Fumeron et al, 2004). Moreover, this and the previous report by Skibola et al found little evidence that risks associated with BMI varied by genotype.
Obesity can induce a state of leptin and insulin resistance, chronic low-grade inflammation, and increased leptin, tumour necrosis factor (TNF)-α, IL-6 and C reactive protein serum levels (Marti et al, 2001). These proinflammatory mediators can activate a number of signalling pathways including nuclear factor (NF)-κB that result in antiapoptotic and proliferative behaviour in B-cells. Recently, DLBCL subtypes have been characterised by NF-κB gene expression signatures, suggesting the significance of activation of this transcription factor in DLBCL pathogenesis (Rosenwald and Staudt, 2003). Increased risk of FL associated with a high leptin producer phenotype (LEP-2548AA), or reduced risk associated with a low leptin producer phenotype (LEP 19AA), may relate to leptin's action in upregulating expression of the antiapoptotic BCL-2 protein in B-cells through the Janus kinase (JAK)/signal transducer and activator of transcription (STAT) pathways. Most FL have a t(14;18) chromosome translocation resulting in BCL-2 dysregulation and overexpression. Leptin also increases expression of matrix metalloproteinases and tissue inhibitors of metalloproteinases, which are associated with aggressive disease, neoplastic growth and angiogenesis in B-cell lymphomas.
This study has a high level of case ascertainment and diagnostic confirmation. As with all case–control studies of this type, however, the possibility that the findings may reflect bias in the case and/or control populations needs to be considered. In our study, participants who resided in affluent areas were, on average, of smaller stature and greater BMI than those who resided in deprived areas. This pattern agrees with that seen in most national surveys (Joint Health Surveys Unit, 2003), and it is possible that the increased risks may have arisen from differential case–control participation. However, adjustment for deprivation did not alter the risk estimates for height or BMI. A further limitation relates to the self-reported nature of the anthropometric data analysed. Compared to a sample of the British population with anthropometric measurements (National Center for Social Research, 2004), our controls were taller and lighter, leading to a reduction in their derived BMI. It is, however, unlikely that cases estimated their height and weight differently from controls, as the hypothesis that obesity is related to NHL is not widely known.
In conclusion, our findings raise the possibility that obesity may increase risk of NHL as a whole, and DLBCL risk in particular. Our findings were most marked among men and those diagnosed at a comparatively young age (<45 years). Although the SNPs involved in energy homeostasis investigated in our study did not modify the risk of NHL associated with obesity, independent effects were seen for FL with the LEP 19G>A and LEP −2548G>A SNPs, irrespective of adiposity. Previous reports of NHL and BMI have been inconsistent, with little investigation of disease subtypes. New initiatives, aimed at pooling data from studies around the world including the one reported here (Boffetta et al, 2003), will hopefully provide further insight into the association between lymphoma and BMI.
Bahl S, Cotterchio M, Kreiger N, Klar N (2004) Antidepressant medication use and non-Hodgkin's lymphoma risk: no association. Am J Epidemiol 160: 566–575
Bell CG, Walley AJ, Froguel P (2005) The genetics of human obesity. Nat Rev Genet 6: 221–234
Boffetta P, Linet M, Armstrong B (2003) The Interlymph collaboration: a consortium of molecular epidemiological studies of non-Hodgkin's lymphoma. Proc Am Assoc Cancer Res 44: 1579
Breslow NE, Day NE (1980) Statistical Methods in Cancer Research. Volume 1 – The Analysis of Case–Control Studies. Lyon: International Agency for Research on Cancer
Calle EE, Rodriguez C, Walker-Thurmond K, Thun MJ (2003) Overweight, obesity, and mortality from cancer in a prospectively studied cohort of U.S. adults. N Engl J Med 348: 1625–1638
Cartwright R, Wood H, Quinn M (2005) Non-Hodgkin's lymphoma. In Cancer Atlas of the United Kingdom and Ireland 1991–2000 Quinn M, Wood H, Cooper N, Rowan S (eds). London: Palgrave Macmillan
Cerhan JR, Janney CA, Vachon CM, Habermann TM, Kay NE, Potter JD, Sellers TA, Folsom AR (2002) Anthropometric characteristics, physical activity, and risk of non-Hodgkin's lymphoma subtypes and B-cell chronic lymphocytic leukemia: a prospective study. Am J Epidemiol 156: 527–535
Chang ET, Hjalgrim H, Smedby KE, Akerman M, Tani E, Johnsen HE, Glimelius B, Adami HO, Melbye M (2005) Body mass index and risk of malignant lymphoma in Scandinavian men and women. J Natl Cancer Inst 97: 210–218
Clarke CA, Glaser SL (2002) Changing incidence of non-Hodgkin lymphomas in the United States. Cancer 94: 2015–2023
Filippi E, Sentinelli F, Trischitta V, Romeo S, Arca M, Leonetti F, Di Mario U, Baroni MG (2004) Association of the human adiponectin gene and insulin resistance. Eur J Hum Genet 12: 199–205
Franceschi S, Serraino D, Bidoli E, Talamini R, Tirelli U, Carbone A, La Vecchia C (1989) The epidemiology of non-Hodgkin's lymphoma in the north-east of Italy: a hospital-based case–control study. Leuk Res 13: 465–472
Fritz A, Percy C, Jack A, Shanmugaratnam K, Sobin L, Parkin DM, Whelan S (2000) International Classification for Diseases for Oncology. Geneva: World Health Organisation
Fumeron F, Aubert R, Siddiq A, Betoulle D, Pean F, Hadjadj S, Tichet J, Wilpart E, Chesnier MC, Balkau B, Froguel P, Marre M (2004) Adiponectin gene polymorphisms and adiponectin levels are independently associated with the development of hyperglycemia during a 3-year period: the epidemiologic data on the insulin resistance syndrome prospective study. Diabetes 53: 1150–1157
Gotoda T, Manning BS, Goldstone AP, Imrie H, Evans AL, Strosberg AD, McKeigue PM, Scott J, Aitman TJ (1997) Leptin receptor gene variation and obesity: lack of association in a white British male population. Hum Mol Genet 6: 869–876
Hager J, Clement K, Francke S, Dina C, Raison J, Lahlou N, Rich N, Pelloux V, Basdevant A, Guy-Grand B, North M, Froguel P (1998) A polymorphism in the 5′ untranslated region of the human ob gene is associated with low leptin levels. Int J Obes Relat Metab Disord 22: 200–205
Hara K, Boutin P, Mori Y, Tobe K, Dina C, Yasuda K, Yamauchi T, Otabe S, Okada T, Eto K, Kadowaki H, Hagura R, Akanuma Y, Yazaki Y, Nagai R, Taniyama M, Matsubara K, Yoda M, Nakano Y, Tomita M, Kimura S, Ito C, Froguel P, Kadowaki T (2002) Genetic variation in the gene encoding adiponectin is associated with an increased risk of type 2 diabetes in the Japanese population. Diabetes 51: 536–540
Hoffstedt J, Eriksson P, Mottagui-Tabar S, Arner P (2002) A polymorphism in the leptin promoter region (−2548 G/A) influences gene expression and adipose tissue secretion of leptin. Horm Metab Res 34: 355–359
Holly EA, Lele C, Bracci PM, McGrath MS (1999) Case–control study of non-Hodgkin's lymphoma among women and heterosexual men in the San Francisco Bay Area, California. Am J Epidemiol 150: 375–389
Jiang Y, Wilk JB, Borecki I, Williamson S, DeStefano AL, Xu G, Liu J, Ellison RC, Province M, Myers RH (2004) Common variants in the 5′ region of the leptin gene are associated with body mass index in men from the National Heart, Lung, and Blood Institute Family Heart Study. Am J Hum Genet 75: 220–230
Joint Health Surveys Unit (2003) Health Survey for England 2003. Summary of key findings
Karvonen MK, Pesonen U, Heinonen P, Laakso M, Rissanen A, Naukkarinen H, Valve R, Uusitupa MI, Koulu M (1998) Identification of new sequence variants in the leptin gene. J Clin Endocrinol Metab 83: 3239–3242
La Vecchia C, Negri E, Parazzini F, Boyle P, D'Avanzo B, Levi F, Gentile A, Franceschi S (1990) Height and cancer risk in a network of case–control studies from northern Italy. Int J Cancer 45: 275–279
Le Stunff C, Le Bihan C, Schork NJ, Bougneres P (2000) A common promoter variant of the leptin gene is associated with changes in the relationship between serum leptin and fat mass in obese girls. Diabetes 49: 2196–2200
Li WD, Reed DR, Lee JH, Xu W, Kilker RL, Sodam BR, Price RA (1999) Sequence variants in the 5′ flanking region of the leptin gene are associated with obesity in women. Ann Hum Genet 63(part 3): 227–234
Lucantoni R, Ponti E, Berselli ME, Savia G, Minocci A, Calo G, de Medici C, Liuzzi A, Di Blasio AM (2000) The A19G polymorphism in the 5′ untranslated region of the human obese gene does not affect leptin levels in severely obese patients. J Clin Endocrinol Metab 85: 3589–3591
Mammes O, Betoulle D, Aubert R, Giraud V, Tuzet S, Petiet A, Colas-Linhart N, Fumeron F (1998) Novel polymorphisms in the 5′ region of the LEP gene: association with leptin levels and response to low-calorie diet in human obesity. Diabetes 47: 487–489
Mammes O, Betoulle D, Aubert R, Herbeth B, Siest G, Fumeron F (2000) Association of the G-2548A polymorphism in the 5′ region of the LEP gene with overweight. Ann Hum Genet 64: 391–394
Marti A, Marcos A, Martinez JA (2001) Obesity and immune function relationships. Obes Rev 2: 131–140
Menzaghi C, Ercolino T, Di Paola R, Berg AH, Warram JH, Scherer PE, Trischitta V, Doria A (2002) A haplotype at the adiponectin locus is associated with obesity and other features of the insulin resistance syndrome. Diabetes 51: 2306–2312
National Centre for Social Research (2004) Health survey for England 2003. Department of Health: London
Nieters A, Becker N, Linseisen J (2002) Polymorphisms in candidate obesity genes and their interaction with dietary intake of n-6 polyunsaturated fatty acids affect obesity risk in a sub-sample of the EPIC-Heidelberg cohort. Eur J Nutr 41: 210–221
Otero M, Lago R, Lago F, Casanueva FF, Dieguez C, Gomez-Reino JJ, Gualillo O (2005) Leptin, from fat to inflammation: old questions and new insights. FEBS Lett 579: 295–301
Paffenbarger Jr RS, Wing AL, Hyde RT (1978) Characteristics in youth predictive of adult-onset malignant lymphomas, melanomas, and leukemias: brief communication. J Natl Cancer Inst 60: 89–92
Pan SY, Johnson KC, Ugnat AM, Wen SW, Mao Y (2004) Association of obesity and cancer risk in Canada. Am J Epidemiol 159: 259–268
Quinton ND, Lee AJ, Ross RJ, Eastell R, Blakemore AI (2001) A single nucleotide polymorphism (SNP) in the leptin receptor is associated with BMI, fat mass and leptin levels in postmenopausal Caucasian women. Hum Genet 108: 233–236
Rosenwald A, Staudt LM (2003) Gene expression profiling of diffuse large B-cell lymphoma. Leuk Lymphoma 44(Suppl 3): S41–S47
Rosmond R, Chagnon YC, Holm G, Chagnon M, Perusse L, Lindell K, Carlsson B, Bouchard C, Bjorntorp P (2000) Hypertension in obesity and the leptin receptor gene locus. J Clin Endocrinol Metab 85: 3126–3131
Samartin S, Chandra RK (2001) Obesity, overnutrition and the immune system. Nutr Res 21: 243–262
Silventoinen K (2003) Determinants of variation in adult body height. J Biosoc Sci 35: 263–285
Skibola CF, Holly EA, Forrest MS, Hubbard A, Bracci PM, Skibola DR, Hegedus C, Smith MT (2004) Body mass index, leptin and leptin receptor polymorphisms, and non-hodgkin lymphoma. Cancer Epidemiol Biomarkers Prev 13: 779–786
StataCorp (2003) Stata Statistical Software: Release 8.2. College Station, TX, Stata Corporation
Townsend P, Phillimore P, Beattie A (1988) Health and Deprivation: Inequality and the North. London: Croom Helm
van Rossum CT, Hoebee B, van Baak MA, Mars M, Saris WH, Seidell JC (2003) Genetic variation in the leptin receptor gene, leptin, and weight gain in young Dutch adults. Obes Res 11: 377–386
Wauters M, Mertens I, Rankinen T, Chagnon M, Bouchard C, Van Gaal L (2001) Leptin receptor gene polymorphisms are associated with insulin in obese women with impaired glucose tolerance. J Clin Endocrinol Metab 86: 3227–3232
Whittemore AS, Paffenbarger Jr RS, Anderson K, Lee JE (1985) Early precursors of site-specific cancers in college men and women. J Natl Cancer Inst 74: 43–51
WHO Consultation on Obesity (2000) Obesity: preventing and managing the global epidemic: report of a WHO consultation. WHO Technical Report Series 894, pp 1–253. Geneva, Switzerland: World Health Organization
WHO Expert Committee on Physical Status (1995) Physical Status: The Use and Interpretation of Anthropometry: Report of a WHO Expert Committee. WHO Technical Report Series 854, pp 1–415. Geneva, Switzerland: World Health Organization
Willett EV, Smith AG, Dovey GJ, Morgan GJ, Parker J, Roman E (2004) Tobacco and alcohol consumption and the risk of non-Hodgkin lymphoma. Cancer Causes Control 15: 771–780
Yiannakouris N, Yannakoulia M, Melistas L, Chan JL, Klimis-Zacas D, Mantzoros CS (2001) The Q223R polymorphism of the leptin receptor gene is significantly associated with obesity and predicts a small percentage of body weight and body composition variability. J Clin Endocrinol Metab 86: 4434–4439
Zhang S, Hunter DJ, Rosner BA, Colditz GA, Fuchs CS, Speizer FE, Willett WC (1999) Dietary fat and protein in relation to risk of non-Hodgkin's lymphoma among women. J Natl Cancer Inst 91: 1751–1758
This work was supported by the Leukaemia Research Fund of Great Britain, NIH Grant RO1-CA104862 from the US National Cancer Institute (MT Smith, PI) and by the National Foundation for Cancer Research. We thank all consultants, hospital staff, general practitioners and interviewees who participated in the study. Our thanks also go to Andrew Jack and Bridget Wilkins for confirming the patients' diagnoses, Sara Rollinson and Heather Kesby for sample management and DNA extraction, and to the study staff.
About this article
Cite this article
Willett, E., Skibola, C., Adamson, P. et al. Non-Hodgkin's lymphoma, obesity and energy homeostasis polymorphisms. Br J Cancer 93, 811–816 (2005). https://doi.org/10.1038/sj.bjc.6602762
This article is cited by
The Association of Pre-diagnostic Inflammatory Markers and Adipokines and the Risk of Non-Hodgkin Lymphoma Development in Egypt
Indian Journal of Hematology and Blood Transfusion (2021)
Lifestyle and risk of follicular lymphoma: a systematic review and meta-analysis of observational studies
Cancer Causes & Control (2020)
Exposure to organochlorine pesticides and non-Hodgkin lymphoma: a meta-analysis of observational studies
Scientific Reports (2016)
Tumor Biology (2014)
Body size in relation to incidence of subtypes of haematological malignancy in the prospective Million Women Study
British Journal of Cancer (2013)