University of Southern California Dissertations and Theses

Common immune-related factors and risk of non-Hodgkin lymphomy

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Common immune-related factors and risk of non-Hodgkin lymphomy

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COMMON IMMUNE-RELATED FACTORS AND RISK OF
NON-HODGKIN LYMPHOMA

by

Jun Wang

A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(EPIDEMIOLOGY)

December 2012

Copyright 2012 Jun Wang
ii

Acknowledgements

This dissertation would not have been possible without the guidance and the help
of my dissertation committee. First of all, I am truly and deeply indebted to my
mentor, Dr. Wendy Cozen, for her encouragement and advice she has provided
throughout my time as her student. I have been extremely lucky to have a
supervisor who cared so much about my work, and who responded to my
questions so promptly. The members of my dissertation committee, Drs.
Thomas Mack, Mariana Stern, Kiros Berhane and Omid Akbari have generously
given their time and expertise to better my work. I am deeply grateful for their
kind support and invaluable advice. Finally, I would like to thank my family and
friends who have supported me during my Ph.D. journey.

iii

Table of Contents

Acknowledgements ii

List of Tables vi

List of Figures viii

Abstract ix

Chapter 1. Introduction 1
Chapter 1 References 6

Chapter 2. Biology and Pathogenesis of Non-Hodgkin
Lymphoma

Introduction 8
B-cell Development 8
T-cell Development 10
Cellular Origin of B-cell NHL 12
Molecular Pathogenesis of B-cell NHL 13
Cellular Origin and Molecular Pathogenesis of
T-cell NHL
15
Mechanism of NHL 18
Chapter 2 References 21

Chapter 3. Descriptive Epidemiology of Non-Hodgkin
Lymphoma

Introduction and Classification 26
Trends in Incidence and Mortality 27
Age 32
Sex 33
Race/Ethnicity 34
Geographic Distribution 37
Chapter 3 References 40

Chapter 4. Altered Immunity and Risk of Non-Hodgkin
Lymphoma

Introduction 43
Immune Deficiency 43
iv

Autoimmune Rheumatic Diseases 48
Infectious Agents 51
Atopic Diseases 56
Infectious Mononucleosis 61
Birth Order and Sibship Size 63
Summary 67
Chapter 4 References 69

Chapter 5. Immune-related Genes and Risk of Non-Hodgkin
Lymphoma

Introduction 82
Proinflammatory and Immunoregulatory Genes 83
Genes in Innate Immunity 86
Human Leukocyte Antigen Region 89
Conclusion 93
Chapter 5 References 95

Chapter 6. Household Endotoxin Levels and Risk of
Non-Hodgkin Lymphoma

Abstract 101
Introduction 102
Methods 104
Study Population and Self-reported Exposures 104
Endotoxin Assessment 105
Statistical Analysis 107
Results 109
Discussion 119
Acknowledgements 122
Chapter 6 References 124

Chapter 7. Common Immune-related Factors and Risk of
Non-Hodgkin Lymphoma in Twins

Abstract 127
Introduction 128
Methods 130
Study Population 130
Exposure Assessment 131
Statistical Analysis 132
Results 134
Discussion 143
Chapter 7 References 151
v

Chapter 8. Atopic Diseases, Immune-response Genes, and
Risk of Non-Hodgkin Lymphoma

Abstract 155
Introduction 156
Methods 158
Study Population and Self-reported Exposures 158
Genotyping 159
Statistical Analysis 159
Results 162
Discussion 179
Chapter 8 References 185

Chapter 9. Summary 189
Chapter 9 References 195

Comprehensive References 196

vi

List of Tables

Table 6.1. Characteristics of cases and controls 112

Table 6.2. Endotoxin levels in carpet dust and
risk of NHL, DLBCL, and Follicular
lymphoma, with endotoxin levels
modeled as a continuous variable

117
Table 6.3. Endotoxin levels in carpet dust and
risk of NHL, DLBCL, and Follicular
lymphoma, with endotoxin levels
modeled as a categorical variable

118
Table 7.1. Characteristics of the like-sexed twin
pairs discordant for NHL

136
Table 7.2. Atopic disease and NHL risk in
like-sexed twin pairs discordant for
NHL

138
Table 7.3. Prior medical conditions or surgical
history and NHL risk in like-sexed twin
pairs discordant for NHL

140
Table 7.4. Behaviors associated with risk of
infection in childhood and NHL risk in
double-respondent twin pairs

141
Table 8.1. Characteristics of pooled study
participants

163

Table 8.2. Interactions of LTA and IL10 with a
history of atopic disease on risk of
B-cell NHL
177

Supplementary Table 6.1. Comparison of participants with and
without endotoxin measurements, by
case-control status

110
vii

Supplementary Table 6.2. Comparisons of Ln(endotoxin) levels
(EU/mg) by case-control status and
sociodemographic characteristics

115
Supplementary Table 7.1. Results of significant exposures for
risk of NHL in MZ twin pairs and
like-sexed DZ twin pairs

142
Supplementary Table 8.1. Pearson correlation coefficients
between atopic diseases among
controls

164
Supplementary Table 8.2. Prevalence of atopic diseases among
controls in each participating study

165
Supplementary Table 8.3a. A history of individual atopic disease
and risk of all NHL or major subtypes

166
Supplementary Table 8.3b. A history of combined atopic diseases
and risk of all NHL or major subtypes

167
Supplementary Table 8.4. TNF-alpha, LTA and IL10 and risk of
all NHL and major subtypes

168
Supplementary Table 8.5. P-values for test of interaction
heterogeneity across studies

171
Supplementary Table 8.6. Interactions of LTA and a history of
atopic disease on risk of all NHL,
DLBCL and Follicular lymphoma

175

viii

List of Figures

Figure 3.1. Trends in age-adjusted incidence of NHL by sex in
the U.S., 9 SEER registries, 1975-2009

28
Figure 3.2a. Trends in age-adjusted incidence of NHL by age
range in males in the U.S., 9 SEER registries,
1975-2009

29
Figure 3.2b. Trends in age-adjusted incidence of NHL by age
range in females in the U.S., 9 SEER registries,
1975-2009

30
Figure 3.3. Age-specific incidence rates of NHL by sex in the
U.S., 13 SEER registries, 1992-2009

33
Figure 3.4. Trends in age-adjusted incidence of NHL by race
and sex in the U.S., 9 SEER registries, 1975-2009

36
Figure 3.5. Age standardized rate (ASR) by regions for NHL.
Source: IARC GLOBOCAN

39
Figure 8.1a. Interaction P-values for atopic disease and IL10
-3575T>A, LTA 252A>G, and TNF -308G>A on
risk of All NHL

172
Figure 8.1b. Interaction P-values for atopic disease and IL10
-3575T>A, LTA 252A>G, and TNF -308G>A on
risk of major subtypes of B-cell NHL

173
Figure 8.2a. Odds ratios for risk of DLBCL in relation to number
of variant alleles for LTA 252A>G and asthma

178
Figure 8.2b. Odds ratios for risk of CLL/SLL in relation to
number of variant alleles for IL10 -3575T>A and a
history of both specific allergy and eczema
178

ix

Abstract

Non-Hodgkin lymphoma (NHL) is a highly heterogeneous group of neoplasms
originating from B- or T- lymphocytes, with the vast majority of B-cell origin. It is
believed that immune dysregulation plays an important role in the etiology of NHL.
Currently, the strongest risk factor is immune deficiency, including primary or
acquired immune deficiency, and immunosuppressive therapy after organ
transplant. However, these conditions are rare in the general population and
therefore do not account for the majority of the cases. A remaining key question
is whether mild to moderate immune dysregulation could also contribute to NHL
risk given that immune deficiency, especially severe immune deficiency, has
been established as a strong risk factor.
Extensive epidemiological studies have investigated the association
between common immune-related diseases/conditions and NHL risk.
Autoimmune or atopic diseases and infections are among those most studied.
Autoimmune rheumatic conditions have been shown to increased NHL risk
despite the debate regarding whether immunosuppressive therapy for
autoimmune disease may also contribute to the development of NHL. Atopic
diseases, on the other hand, have been consistently reported to be inversely
associated with NHL risk in case-control studies although a disease effect cannot
be ruled out: NHL may interfere with B-cell’s ability to produce immunoglobulin E
x

(IgE). Surrogates for early life infections, such as later birth order and large
sibship size, have been shown to be positively associated with NHL risk.
Progress has also been made on understanding genetic susceptibility to
NHL. Currently, the most consistent findings come from immune response
genes, with evidence from both candidate gene and genome wide association
studies. Particularly, tumor necrosis factor – alpha (TNF-α), interleukin-10 (IL-10),
and lymphotoxin alpha (LTA) are among the best characterized and validated
genes.
The full spectra of the biologic mechanisms for NHL are not understood.
However, the critical role of chronic antigenic stimulation in lymphomagenesis
has been largely appreciated. Nevertheless, the nature of the immune
dysfunction in terms of lymphomagenesis is still puzzling, e.g. both immune
suppression (severe immunodeficiency) and stimulation (chronic B-cell activation)
have been implicated in the pathogenesis of NHL. The objective of this
dissertation was to understand how common immune-altering factors, including
environmental stimulant (e.g. household endotoxin) and immune-related medical
history, would affect risk for NHL in the general populations, with emphasis on
atopic diseases and infections.
We did not find any association between household endotoxin levels,
measured from dust samples collected from participants’ vacuum cleaner bags,
and NHL risk in a NCI/SEER multi-center population based case-control study.
xi

The null finding could be due to the nature of cross-sectional measurement of
endotoxin or a single measurement which may not reflect a long term exposure.
In a case-control study involving like-sexed twins discordant for NHL,
common-immune related diseases or conditions were evaluated in terms of NHL
risk. We found a strong inverse association between atopic disease, especially
seasonal hay fever (OR = 0.28, 95%CI = 0.10-0.75) or allergy to specific
substance (OR = 0.29, 95%CI = 0.13-0.68), and NHL risk. The inverse
association was even stronger among dizygotic twins than monozygotic twins,
which may suggest a potential gene-environment interaction in NHL etiology. A
history of infectious mononucleosis was found inversely associated with NHL risk
(OR = 0.35, 95%CI = 0.14-0.90). Childhood behaviors associated with risk of
infection was positively associated with later life NHL risk, which is consistent
with the finding of the positive association between later birth order / large sibship
and NHL in current literature.
Finally, to further clarify the true atopy-NHL association, we evaluated the
interactions between atopic disease and established NHL-related immune
response genes, including TNF-α, IL10 and LTA, on NHL risk. After taking into
account of multiple testing, we did not find any significant interactions for all NHL
combined. However, significant interactions were observed in subtype analysis
after Bonferroni correction. LTA 252A>G may modify the association between
asthma and Diffuse Large B-cell Lymphoma (P
Interaction
= 0.0004) and there was
a significant interaction between IL10 -3575T>A and a history of both allergy and
xii

eczema on Chronic Lymphocytic Leukemia/Small Lymphocytic Lymphoma risk
(P
Interaction
= 0.002).
In conclusion, this dissertation has provided some evidence that mild to
moderate immune-altering factors, particularly atopic diseases, may also affect
risk of NHL. Future studies are needed to understand the underlying
mechanisms.

1

Chapter 1. Introduction

Non-Hodgkin lymphoma (NHL) is the most commonly occurring hematologic
cancer and was considered as a single entity until Henry Rappaport proposed
two major patterns – nodular and diffuse (Rappaport, 1966). With the increasing
NHL incidence and mortality over the last half a century, classification has
become more complex and diagnosis and treatment more effective. NHL is now
considered to be a highly heterogeneous group of neoplasms originating from B-
or T- lymphocytes, with the majority of B-cell origin (approximately 85%).
The striking increase in the incidence rates of NHL from 1970s through the
late 1990s stimulated extensive research on etiology. The cumulative
epidemiological data supported a strong role for immune dysregulation in the
etiology of NHL (Grulich, Vajdic, & Cozen, 2007). Today, the best characterized
and strongest risk factor is immune deficiency, including primary and acquired
immune deficiency and immunosuppressive therapy after organ transplant.
However, these conditions are relatively rare in the general population and
therefore do not account for the majority of the cases. A pivotal remaining
question is whether mild or moderate immune dysfunction could also contribute
to NHL risk given that immune deficiency, especially severe immune deficiency,
has been established as a risk factor.
A growing number of epidemiologic studies have investigated immune-
related diseases and conditions, such as autoimmune or atopic diseases and
2

both acute and chronic infection. Autoimmune diseases, particularly autoimmune
rheumatic conditions, such as Rheumatoid Arthritis (RA), Systemic Lupus
Erythematosis (SLE), and Sjögren's Syndrome (SS), have consistently been
shown to increase NHL risk although some of the immunosuppressive drugs
used to treat autoimmune rheumatic diseases are associated with the
development of lymphoma (Dias & Isenberg). Atopic conditions have also drawn
attention because of the apparent modestly protective effect reported in many
case-control studies of NHL (Martínez-Maza, Moreno, Cozen, Penichet, &
Jensen-Jarolim) and other cancers including glioma and pancreas cancer
(Turner, ; Turner, Chen, Krewski, & Ghadirian, 2006). The most solid evidence
for a link between atopy and NHL comes from a large pooled InterLymph
analysis that reported a 20% decreased risk of NHL associated with allergy to
specific antigens and a 15% decreased risk of B-cell NHL associated with hay
fever (Vajdic et al., 2009). Nevertheless, the limitations of the case-control study
design make it difficult to completely rule out a disease effect. B-cell NHL may
interfere with B-cell’s ability to produce immunoglobulin E (IgE), a biomarker of
atopy, thereby decreasing allergic symptoms. This controversy has not yet been
resolved.
Since the first discovery of Epstein Bar Virus (EBV) in Burkitt’s lymphoma
(BL) about half century ago (Epstein, Achong, & Barr, 1964), a few more
infectious agents have been identified to be associated with some rare subtypes
of NHL, for example, the human T-cell lymphotrophic virus-1 (HTLV-1) and adult
3

T-cell lymphoma/leukemia (Manns, Hisada, & La Grenade, 1999), or human
herpes virus 8 (HHV8) and primary effusion lymphoma. However, for the
majority of NHL, no consistent association with infection has been established
yet, except some evidence of the association between hepatitis C virus (HCV)
and NHL (de Sanjose et al., 2008; Giordano et al., 2007). Another line of
research has focused on the effect of early life exposure to microbial substances
which might affect immune system development (Strachan, 1989). Because
these exposures are hard to measure, proxies such as birth order and family size
have been evaluated instead. Nevertheless, no definite conclusion has been
reached.
Although the biologic mechanisms for NHL are not fully understood, the
role of immune stimulation, particularly B-cell activation, on lymphomagenesis
has been noted. Because B-cell development has several distinct molecular
processes involving gene rearrangements, such as Ig V-region gene
recombination, somatic hypermutation (SHM) and class switch recombination
(CSR), the chance of errors occurring during these processes can increase when
B-cells under chronic antigenic stimulation. These mistakes could result in
chromosomal translocation involving Ig loci which are believed to be a hallmark
of many types of B-cell lymphoma, and also mutations of oncogenes (Kuppers,
2005). The concept of chronic antigenic stimulation may also be supported by
the observation of a positive association between autoimmune rheumatic
4

diseases and NHL provided that autoantigens can stimulate reactive B-cells
(Ekstrom Smedby et al., 2008).
In addition to the environmental factors, specific genetic susceptibility
factors have also been identified (Skibola, Curry, & Nieters, 2007). The strongest
genetic variants associated with NHL are located in a group of immune-related
genes, particularly those involved in inflammatory and immunoregulatory
pathways, and human leukocyte antigen (HLA) region genes, with evidence from
candidate-gene association studies (Skibola et al., 2007) and genome wide
association studies (Conde et al., ; Smedby et al.). Tumor necrosis factor - alpha
(TNF-α), interleukin (IL)10 (IL10), and lymphotoxin alpha (LTA) are the candidate
gene variants most consistently associated with NHL risk (Rothman et al., 2006;
Skibola et al.).
While a role for altered immunity in etiology of NHL is now accepted, the
mechanism is puzzling because both immune suppression (e.g. severe
immunodeficiency) and stimulation (e.g. chronic antigenic stimulation) have been
implicated in the pathogenesis. To further explore the impact of dysfunctional
immunity on NHL risk, this dissertation focuses on understanding how common
immune-altering factors, including an environmental immune stimulant (e.g.
household endotoxin) and immune-related medical history, especially atopic
conditions, might modify the risk of NHL. We conducted the first analysis to
directly evaluate the effect of household endotoxin on NHL risk based on the
rationale that endotoxin is a strong immune modulator (Paper # 1, Chapter 6).
5

An evaluation of the association with atopic conditions without considering the
host genetic background could obscure the true association. Therefore, two
analyses were conducted that take genetics into account. A case-control
analysis was completed of NHL immune-related risk factors in disease-
discordant twins (Paper #2, Chapter 7). In addition, the interaction between
immune-related genes (particularly TNF-α, IL10 and LTA) and atopic disease on
NHL risk was evaluated in a large pooled analysis using data from studies
participating in a lymphoma consortium (InterLymph) (Paper #3, Chapter 8).
Taken together, this dissertation aims to provide insight into the role of immune
dysfunction in NHL etiology, with an emphasis on possible mechanism of chronic
antigenic immune stimulation.

6

Chapter 1 References

Conde, L., Halperin, E., Akers, N. K., Brown, K. M., Smedby, K. E., Rothman, N.,
et al. Genome-wide association study of follicular lymphoma identifies a
risk locus at 6p21.32. Nat Genet, 42(8), 661-664.

de Sanjose, S., Benavente, Y., Vajdic, C. M., Engels, E. A., Morton, L. M., Bracci,
P. M., et al. (2008). Hepatitis C and non-Hodgkin lymphoma among 4784
cases and 6269 controls from the International Lymphoma Epidemiology
Consortium. Clin Gastroenterol Hepatol, 6(4), 451-458.

Dias, C., & Isenberg, D. A. Susceptibility of patients with rheumatic diseases to
B-cell non-Hodgkin lymphoma. Nat Rev Rheumatol, 7(6), 360-368.

Ekstrom Smedby, K., Vajdic, C. M., Falster, M., Engels, E. A., Martinez-Maza, O.,
Turner, J., et al. (2008). Autoimmune disorders and risk of non-Hodgkin
lymphoma subtypes: a pooled analysis within the InterLymph Consortium.
Blood, 111(8), 4029-4038.

Epstein, M. A., Achong, B. G., & Barr, Y. M. (1964). Virus Particles in Cultured
Lymphoblasts from Burkitt's Lymphoma. Lancet, 1(7335), 702-703.

Giordano, T. P., Henderson, L., Landgren, O., Chiao, E. Y., Kramer, J. R., El-
Serag, H., et al. (2007). Risk of non-Hodgkin lymphoma and
lymphoproliferative precursor diseases in US veterans with hepatitis C
virus. Jama, 297(18), 2010-2017.

Grulich, A. E., Vajdic, C. M., & Cozen, W. (2007). Altered immunity as a risk
factor for non-Hodgkin lymphoma. Cancer Epidemiol Biomarkers Prev,
16(3), 405-408.

Kuppers, R. (2005). Mechanisms of B-cell lymphoma pathogenesis. Nat Rev
Cancer, 5(4), 251-262.

Manns, A., Hisada, M., & La Grenade, L. (1999). Human T-lymphotropic virus
type I infection. Lancet, 353(9168), 1951-1958.

Martínez-Maza, O., Moreno, A. D., Cozen, W., Penichet, M. L., & Jensen-Jarolim,
E. Epidemiological Evidence: IgE, Allergies, and Hematopoietic
Malignancies. Cancer and IgE. In (pp. 79-136): Humana Press.

Rappaport, H. (1966). Tumors of the hematopoietic system. In: Atlas of Tumor
Pathology, Section 3, Fasicle 8. In (pp. 97- I96I). Washington, DC: Armed
Forces Institute of Pathology.
7

Rothman, N., Skibola, C. F., Wang, S. S., Morgan, G., Lan, Q., Smith, M. T., et al.
(2006). Genetic variation in TNF and IL10 and risk of non-Hodgkin
lymphoma: a report from the InterLymph Consortium. Lancet Oncol, 7(1),
27-38.

Skibola, C. F., Bracci, P. M., Nieters, A., Brooks-Wilson, A., de Sanjose, S.,
Hughes, A. M., et al. Tumor necrosis factor (TNF) and lymphotoxin-alpha
(LTA)

polymorphisms and risk of non-Hodgkin lymphoma in the InterLymph Consortium.
Am J Epidemiol, 171(3), 267-276.

Skibola, C. F., Curry, J. D., & Nieters, A. (2007). Genetic susceptibility to
lymphoma. Haematologica, 92(7), 960-969.

Smedby, K. E., Foo, J. N., Skibola, C. F., Darabi, H., Conde, L., Hjalgrim, H., et
al. GWAS of follicular lymphoma reveals allelic heterogeneity at 6p21.32
and suggests shared genetic susceptibility with diffuse large B-cell
lymphoma. PLoS Genet, 7(4), e1001378.

Strachan, D. P. (1989). Hay fever, hygiene, and household size. Bmj, 299(6710),
1259-1260.

Turner, M. C. Epidemiology: allergy history, IgE, and cancer. Cancer Immunol
Immunother.

Turner, M. C., Chen, Y., Krewski, D., & Ghadirian, P. (2006). An overview of the
association between allergy and cancer. Int J Cancer, 118(12), 3124-3132.

Vajdic, C. M., Falster, M. O., de Sanjose, S., Martinez-Maza, O., Becker, N.,
Bracci, P. M., et al. (2009). Atopic disease and risk of non-Hodgkin
lymphoma: an InterLymph pooled analysis. Cancer Res, 69(16), 6482-
6489.

8

Chapter 2. Biology and Pathogenesis of
Non-Hodgkin Lymphoma

Introduction
It might be surprising at first that B-cell NHL accounts for the majority of all NHL
(~85%) while T-cell NHL only a small proportion (~15%) given much higher
frequency of T-cells (blood: 70-75%; lymph node: about 80%) than B-cells
(blood: 10-15%; lymph node: 20-25%) in the human body (Abbas, Lichtman, &
Pillai). Both T and B cells undergo gene rearrangement in their receptors,
however only B-cell receptors experience the extensive DNA remodeling of SHM
and CSR that occur as part of the B-cell developmental stages. Starting with the
normal B- and T-cell development, this chapter will discuss molecular
pathogenesis of NHL.

B-cell Development
B-cell development includes three distinct stages: generation of mature naïve B-
cells, activation of naïve B-cells when encountering antigens, and differentiation
of activated B-cells into plasma cells and memory B-cells.
B-cell development begins in the bone marrow as lymphoid-lineage
precursors differentiate into progenitor B-cells. Maturation depends on
successful heavy- and light- chain gene rearrangement in Ig variable (V) region,
9

which occurs in a sequential order: heavy-chain first followed by light-chain.
Upon completion of both heavy- and light- chain gene rearrangement, progenitor
B-cells differentiate into immature B-cells. These B-cells leave bone marrow and
circulate in the blood, and are carried into a secondary lymphoid organ. The final
maturation of B-cells relies on the expression of functional Ig (IgD and IgM) on
the cell membrane. Precursor B-cells which fail to express functional Ig undergo
apoptosis (Rajewsky, 1996).
Mature naïve B-cells in the periphery die unless they encounter antigens.
Antigen-driven activation and differentiation of mature B-cells generates an
antibody response. For most antigens (e.g. protein antigens), the response
requires T helper cells; for non-protein antigens, such as lipopolysaccharide
(LPS), T helper cells are not necessary. The interaction between CD40 on B-
cells and its ligand CD154 (CD40L) expressed on activated T helper cells is the
key to activate mature naïve B-cells by protein antigens. However, this process
still requires signals generated from cytokines that are released from activated T
helper cells. Upon activation, B-cells start to express membrane receptors for
cytokines, including IL 2, IL4 and IL5.
Antigen-activated B-cells differentiate into centroblasts in germinal centers
which are formed at about 7-10 days after initial exposure to T-cell dependent
antigens. SHM and isotype CSR, the distinct DNA remodeling events of the Ig
genes, occur in germinal centers of lymph nodes. SHM takes place when
centroblasts are proliferating, which results in “affinity maturation” (Berek, Berger,
10

& Apel, 1991). Centroblasts that have Ig receptors with increased affinity for the
antigen will be selected and differentiate into centrocytes. A subset of
centrocytes undergoes Ig CSR, a molecular process of switching from IgM and
IgD to IgA, IgE or IgG. However, CSR can occur outside germinal centers in
both T-cell-dependent and independent responses (Toellner, Gulbranson-Judge,
Taylor, Sze, & MacLennan, 1996). Specific cytokines and co-stimulatory
molecules affect the Ig class selection. For example, IL4 can induce the switch
to IgE. Antigen-selected centrocytes which receive signals from T helper cells
eventually differentiate into plasma cells or memory B-cells. It has been
generally accepted that germinal center microenvironment is the principal source
of memory B-cells and plasma cells (MacLennan, 1994).

T-cell Development
While B-cell receptors can directly recognize and bind to antigens, T cell
receptors (TCRs) can only recognize peptide antigens bound to MHC complex
major histocompatibility complex (MHC). This MHC restriction influences several
processes in T-cell maturation and activation. Another feature is the variety of
the subclasses of effector T-cells generated during T-cell differentiation, in
contrast to B-cells.
Derived from the common lymphoid progenitors in bone marrow which also
give rise to progenitor B-cells, T-cell progenitors then migrate to thymus where
11

they complete their maturation. In a process similar to that of B-cell maturation,
T-cell maturation involves rearrangement of the germ-line TCR genes, namely
V(D)J recombination. The β chain of the TCR is arranged first, followed by the α
chain. The majority of circulating T-cells (>95%) express α β TCR, only a small
minority of T-cells rearrange γδ TCR. Upon completion of β chain gene
rearrangement, developing T-cells, also known as thymocytes, begin to express
membrane markers of CD4 (T-helper cells) or CD8 (T-suppressor cells). The
involvement of MHC in antigen recognition results in two distinct processes of
thymocyte selection: during ‘positive selection’, thymocytes which cannot
recognize self-MHC are eliminated; during ‘negative selection’, thymocytes that
bear high-affinity receptors for self-MHC alone or self antigens with self MHC are
not selected. The negative selection leads to the generation of T-cells that are
self-tolerant. The final stages in the T-cell maturation produce CD4+ or CD8+
subpopulations that recognize antigens associated with either class II or class I
MHC complex, respectively.
Mature T-cells export to the periphery, where they undergo antigen-
induced activation. The activation is initiated by interaction between the TCR-
CD3 complex and an antigen binding to the MHC complex on an antigen
presenting cell (APC). However, full T-cell activation requires a co-stimulatory
signal, provided by interaction of CD28 on T-cell with B7 family members on the
APC. If this co-stimulatory signal is absent, the T-cells will not be able to
12

proliferate, a state called clonal anergy. T-cell activation also produces a wide
range of signal transduction pathways, including nuclear factor - kβ (NF-kβ).
Activated T-cells then generate effector and memory T-cells. Effector T-
cells perform specialized functions, depending on the effector cell lineage. CD4+
effector T-cells, functioning of cytokine production and B-cell help, form distinct
subgroups identified by their cytokines profiles. Initially, it was thought CD4+ T-
cells differentiate into either T helper (Th)1 or Th2 subtypes, with Th1 releasing
interferon-γ (IFN-γ) and Th2 producing IL4, IL5 and IL13. The dichotomous
paradigm has been expanded with the discovery of regulatory T-cells (Treg)
(Sakaguchi, Sakaguchi, Asano, Itoh, & Toda, 1995) which produce IL10 and
transforming growth factor-β (TGF-β). Notably, Tregs play an important role in
dampening immune activation and function, and are through to alter both Th1
and Th2 immunity (Belkaid, 2007). A fourth CD4+ T-cell subclass – Th17 has
been discovered recently (Harrington et al., 2005) characterized by expression of
IL17A, IL17F and IL22; these cytokines are associated with autoimmune disease.
CD8+ T-cell differentiate into cytotoxic T lymphocytes (CTLs) that mediate
cytotoxic killing activity.

Cellular Origin B-cell NHL
The majority of the B-cell NHL arises during the differentiation stage of activated
B-cells (germinal center or post germinal center B-cells) (Kuppers, Klein,
13

Hansmann, & Rajewsky, 1999; Stevenson et al., 1998). Germinal centers are
formed by proliferating B-cells in primary B-cell follicles in secondary lymphoid
organs (e.g. lymph nodes) during the T-cell dependent antibody response. The
exceptions are mantle cell lymphoma (MCL) which originates from mantle zone
B-cells, marginal-zone associated lymphoma (e.g. mucosa-associated lymphoid
tissue [MALT] lymphoma or marginal zone lymphoma [MZL]), and B-cell chronic
lymphoblastic leukemia (CLL)/small cell lymphoma whose cellular origin has
remained unclear. Thus, it appears that compared to early B-cell development
stages, the germinal center stage plays an important role in the pathogenesis of
B-cell NHL (Greaves, 1986; Shaffer, Rosenwald, & Staudt, 2002).
Diffuse large B-cell lymphoma (DLBCL), the most common subtype of NHL,
arises from germinal center or post - germinal center B-cells. Gene-expression
profiling of DLBCL tumors has revealed two distinct subgroups: one group shows
a gene expression profile consistent with germinal center B-cells while the other
group resembles in vitro activated peripheral B-cells (Alizadeh et al., 2000).
Follicular lymphoma tumor cells are somewhat morphologically and
phenotypically similar to germinal center B-cells.

Molecular Pathogenesis of B-cell NHL
Chromosomal translocations involving the Ig loci are the molecular hallmarks of
most of B-cell NHL (Kuppers, 2005). Translocations can occur as mistakes
14

occur during Ig heavy- and light- chain V(D)J recombination, SHM or CSR.
Nevertheless, the cause of Ig-associated translocations is not fully understood
(Kuppers & Dalla-Favera, 2001).
Follicular lymphoma often has a t(14;18) chromosomal translocation
involving the heavy (H) chain of the Ig and B-cell lymphoma 2 (BCL2) protein,
found in approximately 90% of the cases (Jager et al., 2000; Tsujimoto, Gorham,
Cossman, Jaffe, & Croce, 1985). This translocation results in dysregulation and
over-expression of BCL2 by joining it with the regulatory region of IgH located on
chromosome 14 (Bende, Smit, & van Noesel, 2007). The breakpoint occurs
during V(D)J recombination that takes place in early B-cell developmental stage,
which is inconsistent with the fact that follicular lymphoma cells morphologically
and phenotypically resemble germinal center B-cells. Thus, this BCL2-IgH has
been considered as an initial molecular lesion but not sufficient to cause
lymphomagenesis, based on findings that this translocation is also seen in
healthy individuals (Janz, Potter, & Rabkin, 2003; Schuler et al., 2009). In
addition, studies with animal models show that transgenic mice with BCL2 driven
by an IgH enhancer did not develop follicular lymphoma (McDonnell et al., 1989;
Strasser, Harris, & Cory, 1993). B-cells bearing the BCL2-IgH translocation may
not directly result in lymphomagenesis unless they encounter antigens and
become involved in germinal center reactions. These B-cells have a growth
advantage over normal B-cells because BCL2 expression may interfere with
15

selection of B-cells with high affinity to antigen and prevent apoptosis of B-cells
with DNA damage (Bende et al., 2007).
Several molecular lesions involving Ig-associated chromosomal
translocations have been identified for DLBCL as well, with the t(3;14) BCL6-IgH
accounting for the highest proportion (approximately 35%) (Bastard et al., 1994;
Lo Coco et al., 1994). The t(14:8) IgH-BCL2 translocation is also found in about
15-30% DLBCL cases (Weiss, Warnke, Sklar, & Cleary, 1987). About 15% of
the DLBCL cases show chromosomal translocation involving t(8;14) MYC-IgH or
t(8;22) MYC-IgL (Ladanyi, Offit, Jhanwar, Filippa, & Chaganti, 1991). SHM or
CSR have been implicated in the translocations other than IgH-BCL2 in DLBCL
(Bende et al., 2007).
As for other types of B-cell NHL, it is notable that BL cases have at least
one of three translocations: t(8;14) MYC-IgH and t(8;22) MYC-Igλ and t(2;8)
MYC-Igk(Dalla-Favera, Martinotti, Gallo, Erikson, & Croce, 1983; Taub et al.,
1982).

Cellular Origin and Molecular Pathogenesis of T-cell NHL
Unlike the counterpart of B-cell NHL, some subtypes of T-cell NHL lack distinct
immunophenotypic profiles and overlap in terms of morphology and
immunophenotype across different subtypes exists (de Leval & Gaulard). Thus,
the delineation of T-cell NHL subtypes is less well-characterized. In general, T-
16

cell NHL can be roughly divided into two subgroups according to their clinical
features and anatomical locations: peripheral T-cell NHL (PTCL) and cutaneous
T-cell NHL (CTCL).
PTCL arises from post - thymic T-cells at various stages of differentiation
and natural killer (NK) cells (Savage). In a broad sense, all the PTCLs derive
from mature T-cells or NK cells, except lymphoblastic lymphoma, the lymphoma
counterpart of T-cell acute lymphoblastic leukemia (ALL) which arises from
precursor T-cells (intra-thymic T-cells) (Uckun et al., 1997).
It is generally believed that CTCL is a group of malignancies of skin
homing mature T-cells (Girardi, Heald, & Wilson, 2004). The two most common
subtypes of CTCL - mycosis fungoides and Sézary syndrome, however, have
been suggested as distinct diseases and may have different cellular origins
(Campbell, Clark, Watanabe, & Kupper, ; J. Shin et al., 2007; van Doorn et al.,
2009). Specifically, in a study examining the tumors from these two subtypes,
the authors suggested that Sézary syndrome derives from central memory T-
cells while mycosis fungoides arises from skin resident mature memory T-cells
(Campbell et al.).
In contrast to B-cell NHL in which chromosomal translocation involving Ig
is a molecular hallmark for many subtypes (Kuppers, 2005), T-cell NHL appears
to lack characteristic genetic alterations for most of the subtypes, with some
exceptions (de Leval & Gaulard). Currently, the best characterized recurrent
genetic alteration has been observed in anaplastic lymphoma kinase (ALK) -
17

positive anaplastic large cell lymphoma (ALCL), in which a t (2,5) Nucleophosmin
- ALK translocation has been found in 75-80% of the tumors (Chiarle, Voena,
Ambrogio, Piva, & Inghirami, 2008). Another exception is T- ALL in which a
translocation involving TCR genes with oncogenes or fusion genes has been
reported; however, this translocation is present in only ~35% of all T- ALL cases
(Aifantis, Raetz, & Buonamici, 2008). Notably, while the B-cell receptor (Ig) has
an active role in B-cell lineage lymphomagenesis (e.g. via chromosomal
translocation), no solid evidence has suggested an active role of TCR in T-cell
NHL development. In addition, TCR development does not have the same
complex DNA modifying processes as B-cell receptor (e.g. SHM and CSR),
which explain the preponderance of B-cell, compared to T-cell, NHL.
In summary, the current understanding of the biology and pathology of T-
cell NHL is poor. The rarity of T-cell NHL (especially in North America and
Europe), the ambiguity of delineating subtypes due to the morphological and
immunophenotypic overlap among subtypes, and the lack of featured genetic
alterations contribute to the relative lack of progress on understanding the
pathogenesis of T-cell NHL. Nonetheless, recent genome-wide gene expression
profiling has provided some clues in molecular signatures of T-cell NHL subtypes
(de Leval & Gaulard), which could help in the diagnosis and treatment.

18

Mechanisms of NHL
The full spectra of the biological mechanisms for NHL are not completely
understood. Altered immunity, but not extensive antigen exposure, has been
implicated as an essential factor affecting both B- and T-cell risk (Grulich, Vajdic
et al., 2007). However, the mechanism of action is not completely consistently
associated with the risk factors, given that both immune suppression and
stimulation appear to play an etiological role.
The establishment of immune suppression as a NHL risk factor has been
strongly supported by the fact that immune deficiency, including primary immune
deficiency, immunosuppressive therapy after solid organ transplant, and
HIV/AIDS associated immune deficiency, are the strongest known risk factors for
NHL (Grulich, Vajdic et al., 2007). Solid organ transplant or HIV/AIDS-
associated immunosuppression is characterized predominantly by a T-cell
deficiency while primary immune deficiency is highly heterogeneous and can
include both B- and/or T- cell dysfunction, with antibody deficiency as the most
common individual manifestation. EBV is usually implicated in
immunodeficiency-associated NHL, such as primary central nervous system NHL
in HIV/AIDS patients (Tran et al., 2008). Therefore, the EBV-positive NHL
reflects an uncontrolled proliferation of EBV-transformed B-cells in the absence
of effective T-cell surveillance prominent in immunodeficiency-associated NHL.
Immune stimulation (especially B-cell activation) has also been proposed
as an important mechanism (Fisher & Fisher, 2004). When B-cells undergo
19

chronic antigenic stimulation, the probability of random genetic errors during B-
cell development stages, particularly the molecular processes that remodel
immunoglobulin gene (e.g. V(D)J recombination, SHM and CSR), can increase.
These molecular lesions could ultimately lead to chromosomal translocation
involving immunoglobulin loci and also mutations of oncogenes (Kuppers, 2005).
Several lines of evidence have supported the etiological role of B-cell activation
in lymphomagenesis. Autoimmune rheumatic disease (e.g.RA, SLE and SS),
diseases in which auto-antigens stimulate reactive B-cells, have consistently
been associated with an increased risk of NHL (Dias & Isenberg). Biomarkers of
B-cell stimulation, including cytokines (e.g. IL6 and IL10) or other proposed
markers (e.g. soluble CD30, soluble CD23), are associated with an increased
risk of NHL in either HIV/AIDS population (Breen et al.) or in the general
population (De Roos et al., ; Purdue et al., ; Purdue, Lan, Martinez-Maza et al.,
2009; Vermeulen et al.). Most of the studies measured these biomarkers several
years before NHL occurrence (Breen et al., ; Purdue et al., ; Purdue, Lan,
Martinez-Maza et al., 2009; Vermeulen et al.), further supporting a true etiological
association between B-cell activation and NHL risk.
In summary, it appears that B- and/or T-cell dysfunction play a pivotal role
in NHL development. Nevertheless, the underlying biological pathways have not
been completely elucidated and the possible mechanism(s) are likely to be more
complex than is currently understood. Based on the above models, it would be
expected that atopic disease would result in an increased risk of NHL because of
20

chronic immune stimulation, however, many case-control studies have reported
an inverse association between atopic disease and NHL risk (Martínez-Maza et
al.). A possible explanation lies in IgE, a biomarker of atopy, which can reduce
B-cell activity through the interaction with soluble CD23 (a cytokine-like B-cell
stimulating factor) and may also mediate anti-tumor immunity. However, cohort
studies failed to prove the protective effect from atopic disease due to limited
power, and thus the true relationship between atopic condition and NHL requires
further investigation.
Another remaining question is whether and how mild to moderate immune
dysfunction contributes to the burden of NHL. Severe immune deficiency is rare
in the general population and it only accounts for a small proportion of all cases.
Thus, it is appealing to explore the impact of mild to moderate altered immunity
on NHL risk in the general population. A variety of environmental or genetic
factors may affect immunity at various stages in life by varying degree. Common
immune-related conditions (e.g., infectious mononucleosis, IM) or proxies for
them (e.g. birth order), should be examined as possible risk factors. Immune-
related gene variants may also serve as markers for variation in immune function.
Future investigation of how variation in immune function contributes to NHL
susceptibility should also take into account the histological subtypes to the extent
possible.

21

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26

Chapter 3. Descriptive Epidemiology of Non-Hodgkin Lymphoma

Introduction and Classification
Non Hodgkin lymphoma (NHL) is currently the 7
th
most commonly diagnosed
cancer in both men and women in the United States (Cancer Facts and Figures
2012, 2012). The projected number of new cases and deaths in 2012 in the U.S.
is 70,130 and 18,940, respectively, which will account for approximately 4.3% of
all cancer diagnoses and 3.3% of all cancer deaths in the U.S (Cancer Facts and
Figures 2012, 2012). According to the latest World Health Organization (WHO)
classification of hematologic neoplasms, there are 32 subtypes of B-cell and 22
T-cell NHL (E. S. Jaffe, 2009). Major subtypes of B-cell NHL include DLBCL,
follicular lymphoma, MCL, CLL/SLL, precursor B-lymphoblastic lymphoma, MZL,
and Burkitt’s lymphoma (BL). DLBCL and follicular lymphoma are the two most
common subtypes of B-cell NHL: the former accounts for approximately 40% of
all NHL and the latter accounts for about 20% (Muller, Ihorst, Mertelsmann, &
Engelhardt, 2005). T-cell NHL only constitutes ~15% of all NHL and can be
roughly divided into two major subgroups: PTCL and CTCL. The most common
subtypes of PTCL include peripheral T-cell lymphoma not otherwise specified,
angioimmunoblastic type, natural killer/T-cell lymphoma, and adult T-cell
leukemia/lymphoma (Vose, Armitage, & Weisenburger, 2008). The most
common types of CTCL are mycosis fungoides and Sézary syndrome. Overall,
the distribution of NHL subtypes varies by geographic regions: higher proportion
27

of DLBCL and follicular lymphoma in North America and Europe while higher
proportion of T-cell NHL in Asia, and endemic BL in some areas of Africa (Muller
et al., 2005).

Trends in Incidence and Mortality
Incidence rates in many areas increased dramatically from the 1970s until the
late 1990s. In the U.S, the age-adjusted incidence rate of all NHL combined
increased by 3-4% annually during 1970s and 1980s, resulting in an almost
doubled incidence rate, particularly in men. However, it stabilized during the late
1990s (Clarke & Glaser, 2002) (Figure 3.1). When stratified by age, the
increasing incidence rates were more pronounced in older age groups, especially
in both men and women aged 65 years or older (Figure 3.2). Although overall
incidence rates have been stable since 1990s, the incidence rates continued to
rise in older men and women (e.g. >75 years) until about 2000. Some of the
increase during 1970s and 1980s among younger and middle-aged men was
due to the HIV/AIDS epidemic (Harnly, Swan, Holly, Kelter, & Padian, 1988).
However, the overall increase could also be partially attributable to artifacts such
as improved diagnostic techniques and changes in disease classification (e.g.
changes in definition of NHL to include more cases previously considered as
other diseases). The increase in the incidence rates has also been observed
worldwide; NHL incidence rose globally during 1970s and mid-1980 (Hartge,
28

Devesa, & Fraumeni, 1994) but have stabilized in recent years, with little change
in the ranking by geography.

Figure 3.1. Trends in age-adjusted incidence of NHL by sex in the U.S., 9 SEER
registries, 1975-2009

*All incidence rates are age adjusted to the 2000 United States population.

29

Figure 3.2a. Trends in age-adjusted incidence of NHL by age range in males in the
U.S., 9 SEER registries, 1975-2009

* All incidence rates are age adjusted to the 2000 United States population.
Note: line breaks due to case <16.

30

Figure 3.2b. Trends in age-adjusted incidence of NHL by age range in females in
the U.S., 9 SEER registries, 1975-2009

* All incidence rates are age adjusted to the 2000 United States population.
Note: line breaks due to case <16.

The changing classification schemes make it difficult to compare the long-
term time trends of NHL subtypes. By using a more comprehensive classification
scheme introduced by WHO in 2001 (E.S. Jaffe, Harris, Stein, & Vardiman, 2001),
31

Morton and colleagues evaluated incidence patterns of major NHL subtypes in
the U.S. based on data from 12 Surveillance, Epidemiology, and End Results
(SEER) registries during 1992-2001 (Morton et al., 2006). They reported that the
incidence rates rose significantly for MZL(21.3% per year), MCL (8.1% per year),
BL (8.4% per year) and T/NK lymphoma (4% per year) but declined slightly for
the most common subtype DLBCL (-0.5% per year) and for CLL/SLL (-2.7% per
year). Nevertheless, among people older than 74 years, DLBCL and follicular
lymphoma incidence rates still increased by 1.4% and 1.8% per year,
respectively (Morton et al., 2006). Between 2001 and 2008, Evens et al.
reported that incidence rates continued to increase for MZL (2.6% per year)
(although the rate of increase was not as steep as previously) and NK/T-cell
lymphoma (5.7% per year) but decreased for CLL/SLL (-1.5% per year) (Evens
et al., 2011).
Mortality rates also increased significantly during the 1970s until the late
1990s in some regions. The age-adjusted mortality rates in the U.S. increased
almost by 50% from 1979 to 1996, with more pronounced increase among men
than women: 53% and 39% increase in men and women, respectively. HIV/AIDS
had a substantial effect on the mortality rate during this period but the effect is
now attenuated with the introduction of highly active anti-retroviral therapy
(HAART) (Hooper, Holman, Clarke, & Chorba, 2001). In a study examining
mortality rates in the U.S., the European Union and Japan from 1969 to 1998,
similar rates were found among these regions until the late 1970s; however,
32

since then, mortality rates increased steeply in the U.S. while the European
Union had a steady increase and Japan showed a relatively slow increase in
mortality (Levi, Lucchini, Negri, & La Vecchia, 2002).

Age
Overall, advancing age is a major risk factor for NHL. In general, the risk begins
to increase at about age 25 but the rate of increase becomes steeper at age 50
(Figure 3.3), regardless of sex and race/ethnicity (Clarke & Glaser, 2002). NHL
is very rare in children. For instance, the incidence rate is only 1.2 per 100,000
for children aged 10-14, according to SEER 1992-2009 data. According to the
data from SEER program of National Cancer Institute (NCI), during 2005-2009,
approximately 74% cases were diagnosed among persons older than 55 years,
with a median age at diagnosis of all NHL combined of 65 years (Howlader et al.,
2012). The age-specific increasing risk has been observed for most of the major
NHL subtypes, including DLBCL and follicular lymphoma, with the exception of
BL and B- and T- cell lymphoblastic leukemia/lymphoma (Morton et al., 2006),
based on SEER data during the period 1992-2001.

33

Figure 3.3. Age-specific incidence rates of NHL by sex in the U.S., 13 SEER
registries, 1992-2009

*All incidence rates are age adjusted to the 2000 United States population.

Sex
NHL incidence has been higher among males than females across all age
groups for decades (Devesa & Fears, 1992). In the U.S., from 2005 to 2009, the
age-adjusted incidence rate was approximately 31.5% higher in men than in
women (23.8 and 16.3 per 100,000, respectively); a similar pattern was observed
for age-adjusted mortality rate (Howlader et al., 2012). Secular trends in
incidence rates showed a more steep increase among men during 1970s until
34

early 1990. Since then, the increase in rates have leveled off among men
(annual percentage change during early 1990 - 2009: 0.3%), however, the
incidence among women continued to rise by 1.2% per year until the mid-2000s
and has remained stable since (Howlader et al., 2012) (Figure 3.1).
Although males have higher incidence rates for most subtypes, there are
some variations. The most pronounced male predominance has been observed
for BL, with a male to female incidence rate ratio (IRR) exceeding 3.0. Male
incidence rates of MCL and CLL/SLL are about doubled that of females, while a
moderate male predominance has been seen in DLBCL (IRR = 1.6, 1.8 and 1.4
in White, Black and Asians). MZL and follicular lymphoma affect males and
females roughly similarly. FL shows an approximately equal incidence rate
between male and female in whites and Asians but a modest male predominance
in blacks (Morton et al., 2006). NHL in thyroid gland is much more common in
women than in men (the male to female IRR: 0.4) (R. Newton, Ferlay, Beral, &
Devesa, 1997).

Race/Ethnicity
NHL incidence rates vary substantially across racial/ethnic groups (Figure 3.4).
Rates of all NHL combined are higher among Whites and lower among Blacks
and Asians. According to SEER data, during 2005-2009, age-adjusted incidence
35

rates (per 100,000 persons per year) were 24.8 and 17.1 in white men and
women, 19.5 and 15.4 in Hispanic men and women, 17.5 and 11.8 in black men
and women, and 16.3 and 10.9 in Asian men and women, respectively (Howlader
et al., 2012). Incidence rates by subtype also vary dramatically by racial/ethnic
groups. According to SEER data collected during 1992-2001, Whites had higher
incidence rates than Blacks for most B-cell subtypes, with the most significant
disparity observed for follicular lymphoma (White to Black [W/B] IRR in males
and females: 2.1 and 2.8, respectively) and B-cell lymphoblastic
leukemia/lymphoma (W/B IRR in males and females: both 2.3), followed by
DLBCL (W/B IRR in males and females: 1.5 and 1.6, respectively). On the other
hand, T/NK-cell NHL was slightly more common in Blacks than in Whites (W/B
IRR in males and females: 0.9 and 0.7, respectively) (Morton et al., 2006). The
largest disparity was seen when White incidence rates of CLL/SLL were
compared to those of Asians (white to Asian [W/A] IRR in males and females: 4.4
and 4.3, respectively), followed by follicular lymphoma (W/A IRR in males and
females: both 2.4) and MCL (W/A IRR in males and females: 2.6 and 1.9,
respectively). However, rates were similar between whites and Asians for
DLBCL,MCL and BL (W/A IRR ranged from 0.8-1.3) (Morton et al., 2006).
Disproportionate increases in incidence rates between racial groups have
also been observed. Although Whites have an overall higher incidence rate
compared to that of Blacks, in some age groups the increase among Blacks
exceeded that in Whites (Clarke & Glaser, 2002). For example, among males
36

aged 25-34, a non-significant increase in incidence rates were observed among
Whites (1.3% per year) during 1973-1984, in contrast to a more pronounced
increase in Blacks (11.6% per year) during the same period. In addition,
incidence rates in Black females continue to increase, while a decrease in rates
among White females started at early 2000s.

Figure 3.4. Trends in age-adjusted incidence of NHL by race and sex in the U.S., 9
SEER registries, 1975-2009

*All incidence rates are age adjusted to the 2000 United States population.

37

Geographic Distribution
Significant differences in incidence rate across regions worldwide have been
observed (Figure 3.5) (Ferlay et al., 2010). The incidence rate is higher in North
America, Europe, Australia and Israel than in most of the countries in Asia and
Africa. According to data from Cancer Incidence, Mortality and Prevalence
Worldwide in 2008 of International Agency for Research on Cancer (IARC), the
highest rate was observed in Israel (age standardized rate [ASR]: 16.6 per
100,000), with the US having the second highest rate (ASR: 13.7 per 100,000),
while the lowest rates were seen in Eastern (ASR: 2.7 per 100,000) and South-
Central Asia (ASR: 2.8 per 100,000) (Ferlay et al., 2010).
The distribution of NHL subtypes also varies from region to region. It was
reported that follicular lymphoma comprises a higher proportion of NHL in North
America, London and Capetown, South Africa (31%), in comparison to 14% in
regions from Western Europe and Eastern Asia (J. R. Anderson, Armitage, &
Weisenburger, 1998). T- and NK- cell NHL are relatively rare in North America
and Europe, only accounting for less than 10% of all NHL (J. R. Anderson et al.,
1998); however, they comprise 15-25% of all lymphomas in Asia (Au et al., 2005).
HTLV-1 - associated adult T-cell lymphoma/leukemia occurs much more
frequently in regions where HTLV-1 is endemic, such as southwestern Japan, the
Caribbean islands, sub-Saharan African countries, Iran and Melanesia, though it
occurs sporadically in South America (e.g. Brazil) and North America (Proietti,
Carneiro-Proietti, Catalan-Soares, & Murphy, 2005).
38

BL, a relatively rare subtype of B-cell NHL, has a distinct epidemiologic
distribution in terms of its clinical subtypes. Endemic BL occurs almost
exclusively in Africa and Papua New Guinea where malaria is endemic and
Epstein Barr Virus (EBV) is found in almost all tumors (Young & Rickinson, 2004).
Endemic BL is the most common childhood cancer in these areas, with an
estimate incidence rate at 40-50 per 1,000,000 children <18 years and a male
predominance (Orem, Mbidde, Lambert, de Sanjose, & Weiderpass, 2007).
Sporadic BL mainly occurs in North America and Europe, with the estimated
annual incidence rate for children under 18 years of only 2 per 1,000,000
(Molyneux et al.) and EBV is rarely found in sporadic BL.
In summary, despite a striking increase in incidence worldwide during the
1970s and 1990s, the rates have been stabilized in recent years. NHL incidence
rates vary substantially by age, sex, race/ethnicity and regions. Rates increase
dramatically with advancing ages, as with other cancers. In general, males have
higher rates than females for all NHL combined and many of the subtypes.
Race/ethnicity is an important determinant as well, with the highest rates in
Whites and lowest in Asians. The incidence and distribution of all NHL combined
and subtypes also vary by geographical regions: rates are higher in North
America, Europe and Australia than most areas in Africa and Asia; B-cell NHL
accounts for the majority of the cases in the former while T-cells for the latter.

39

Figure 3.5. Age standardized rate (ASR) by regions for NHL. Source: IARC
GLOBOCAN

40

Chapter 3 References

American Cancer Society: Cancer Facts and Figures 2012. (2012). Atlanta, Ga:
American Cancer Society.

Anderson, J. R., Armitage, J. O., & Weisenburger, D. D. (1998). Epidemiology of
the non-Hodgkin's lymphomas: distributions of the major subtypes differ by
geographic locations. Non-Hodgkin's Lymphoma Classification Project.
Ann Oncol, 9(7), 717-720.

Au, W. Y., Ma, S. Y., Chim, C. S., Choy, C., Loong, F., Lie, A. K., et al. (2005).
Clinicopathologic features and treatment outcome of mature T-cell and
natural killer-cell lymphomas diagnosed according to the World Health
Organization classification scheme: a single center experience of 10 years.
Ann Oncol, 16(2), 206-214.

Clarke, C. A., & Glaser, S. L. (2002). Changing incidence of non-Hodgkin
lymphomas in the United States. Cancer, 94(7), 2015-2023.

Devesa, S. S., & Fears, T. (1992). Non-Hodgkin's lymphoma time trends: United
States and international data. Cancer Res, 52(19 Suppl), 5432s-5440s.

Evens, A. M., Winter, J. N., Gordon, L. I., Chiu, B. C.-H., Tsang, R., & Rosen, S.
T. (2011). Non-Hodgkin Lymphoma. In D. G. Haller, L. D. Wagman, K. A.
Camphausen & W. J. Hoskins (Eds.), Cancer Management: A
Multidisciplinary Approach Medical, Surgical, & Radiation Oncology.

Ferlay, J., Shin, H. R., Bray, F., Forman, D., Mathers, C., & Parkin, D. M. (2010).
GLOBOCAN 2008 v1.2, Cancer Incidence and Mortality Worldwide: IARC
CancerBase No. 10 [Internet]. (Publication. Retrieved Available from:
http://globocan.iarc.fr, from Lyon, France: International Agency for
Research on Cancer:

Harnly, M. E., Swan, S. H., Holly, E. A., Kelter, A., & Padian, N. (1988). Temporal
trends in the incidence of non-Hodgkin's lymphoma and selected
malignancies in a population with a high incidence of acquired
immunodeficiency syndrome (AIDS). Am J Epidemiol, 128(2), 261-267.

Hartge, P., Devesa, S. S., & Fraumeni, J. F., Jr. (1994). Hodgkin's and non-
Hodgkin's lymphomas. Cancer Surv, 19-20, 423-453.

41

Hooper, W. C., Holman, R. C., Clarke, M. J., & Chorba, T. L. (2001). Trends in
non-Hodgkin lymphoma (NHL) and HIV-associated NHL deaths in the
United States. Am J Hematol, 66(3), 159-166.

Howlader, N., Noone, A. M., Krapcho, M., Neyman, N., Aminou, R., Altekruse, S.
F., et al. (2012). SEER Cancer Statistics Review, 1975-2009 (Vintage
2009 Populations) (Publication., from Bethesda, MD:National Cancer
Institute. http://seer.cancer.gov/csr/1975_2009_pops09/:

Jaffe, E. S. (2009). The 2008 WHO classification of lymphomas: implications for
clinical practice and translational research. Hematology Am Soc Hematol
Educ Program, 523-531.

Jaffe, E. S., Harris, N. L., Stein, H., & Vardiman, J. W. e. (2001). World Health
Organization Classification of Tumours. Pathology and genetics of
tumours of haematopoietic and lymphoid tissues. Paper presented at the
International Agency for Research on Cancer, Lyon.

Levi, F., Lucchini, F., Negri, E., & La Vecchia, C. (2002). Trends in mortality from
non-Hodgkin's lymphomas. Leuk Res, 26(10), 903-908.

Molyneux, E. M., Rochford, R., Griffin, B., Newton, R., Jackson, G., Menon, G.,
et al. Burkitt's lymphoma. Lancet, 379(9822), 1234-1244.

Morton, L. M., Wang, S. S., Devesa, S. S., Hartge, P., Weisenburger, D. D., &
Linet, M. S. (2006). Lymphoma incidence patterns by WHO subtype in the
United States, 1992-2001. Blood, 107(1), 265-276.

Muller, A. M., Ihorst, G., Mertelsmann, R., & Engelhardt, M. (2005). Epidemiology
of non-Hodgkin's lymphoma (NHL): trends, geographic distribution, and
etiology. Ann Hematol, 84(1), 1-12.

Newton, R., Ferlay, J., Beral, V., & Devesa, S. S. (1997). The epidemiology of
non-Hodgkin's lymphoma: comparison of nodal and extra-nodal sites. Int J
Cancer, 72(6), 923-930.

Orem, J., Mbidde, E. K., Lambert, B., de Sanjose, S., & Weiderpass, E. (2007).
Burkitt's lymphoma in Africa, a review of the epidemiology and etiology.
Afr Health Sci, 7(3), 166-175.

Proietti, F. A., Carneiro-Proietti, A. B., Catalan-Soares, B. C., & Murphy, E. L.
(2005). Global epidemiology of HTLV-I infection and associated diseases.
Oncogene, 24(39), 6058-6068.

42

Vose, J., Armitage, J., & Weisenburger, D. (2008). International peripheral T-cell
and natural killer/T-cell lymphoma study: pathology findings and clinical
outcomes. J Clin Oncol, 26(25), 4124-4130.

Young, L. S., & Rickinson, A. B. (2004). Epstein-Barr virus: 40 years on. Nat Rev
Cancer, 4(10), 757-768.

43

Chapter 4. Altered Immunity and Risk of
Non-Hodgkin Lymphoma

Introduction
Immune dysfunction plays a critical role in the etiology of NHL. Extensive
research has been performed investigating the impact of immune-related factors
on NHL risk. However, with the exception of severe immune deficiency, no
definite conclusion has been reached for a variety of suspected immune-related
factors. This chapter focuses on a review of both established and hypothesized
immune-related factors. The best characterized and strongest factor - immune
deficiency, will be discussed first followed by moderate to modest factors, such
as autoimmune rheumatic conditions, and more common immune conditions
hypothesized to affect NHL risk, including atopic disease, infectious
mononucleosis and birth order/sibship size, will also be discussed.

Immune Deficiency
The best established and strongest risk factor for NHL is primary, acquired and
iatrogenic immune deficiency (Grulich, Vajdic et al., 2007). Although
immunodeficiency associated lymphomas are clinically and pathologically
heterogeneous, there are several common features, including origins of
extranodal sites, diffuse histology, involvement of EBV and rapid clinical
progression (Knowles, 1999).
44

Primary Immune Deficiency. Primary or congenital immunodeficiencies
are a heterogeneous group of genetically determined disorders comprise more
than 150 distinct entities with a varying degree of dysfunction of B- and/or T-cells
(Notarangelo et al., 2009). Up to 25% of individuals with congenital immune
deficiency disorders will develop cancer during lifetime, with NHL as the
predominant cancer (Filipovich, Mathur, Kamat, & Shapiro, 1992). The
subgroups of primary immunodeficiencies commonly associated with
lymphoproliferative diseases include: predominantly antibody deficiencies, e.g.
Common Variable Immunodeficiency (CVID); immune dysregulation, e.g. X-
linked Lymphoproliferative Syndrome (XLP); auto-inflammatory disorders, e.g.
Autoimmune Lymphoproliferative Disorder (ALPS); combined T- and B-cell
immunodeficiencies, such as Severe Combined Immunodeficiency (SCID) and X-
linked Hyper-IgM Syndrome (XHIGM); and other well-defined immunodeficiency
syndromes, such as Wiskott-Aldrich Syndrome (WAS) and Ataxiatelangectasia
(A-T) (Geha et al., 2007). The rarity of primary immunodeficiencies and poor
survival of affected individuals make it difficult to estimate the risk of cancer in
these populations. Previous studies reported a strikingly increased risk of NHL
(relative risk ranged from 6.0 to over 100) among patients with primary
immunodeficiencies (L. J. Kinlen et al., 1985; Mellemkjaer et al., 2002; Morrell,
Cromartie, & Swift, 1986; Olsen et al., 2001; Taskinen et al., 2008); however,
most of the studies had a really small sample size and were non-population
based. Recently, in a large population based study conducted in Australia,
45

primary immunodeficiencies were found associated with an approximately 8-fold
increased risk of NHL (SIR = 8.82, 95%CI =5.04-14.30) (a much smaller
magnitude of relative risk compared to previous studies), and the excess risk was
observed primarily in the major subgroup of antibody deficiencies (Vajdic et al.).
DLBCL is the most common NHL subtype observed in the setting of primary
immunodeficiencies; some specific congenital immunodeficiencies have also
been associated with T-cell leukemia/lymphoma, such as A-T (Tran et al., 2008).
EBV is frequently found in the tumors (Immunosurveillance, Immunodeficiencies
and Lymphoproliferations:Lymphoproliferative Disorders in Congenital and
Acquired Immunodeficiencies, 2002).
Iatrogenic Immune Deficiency. Recipients of solid organ transplant have
a remarkably increased risk of NHL due to the immunosuppressive therapy after
transplantation. A dramatic increase in organ transplants since the 1990s and
improvements in long-term survival of solid organ transplant patients have led to
an absolute rise in the incidence of post-transplant lymphoma. Compared to
non-transplanted population, recipients have a relative risk up to 10-50
(Boubenider et al., 1997; L. Kinlen, 1992). Post-transplant lymphoma risk
depends on the intensity of immunosuppression, recipient age, and the organ
transplanted. Incidence is usually highest during the first year after transplant
when the immunosuppressive therapy is most intense. Recipients aged <10
years have the highest relative risk of lymphoma compared to recipients of other
age groups probably because the background incidence of lymphoma for this
46

age group is low (Opelz & Dohler, 2004). Combined heart and lung transplants
have the highest risk of developing NHL during a 5-year period following
transplantation (relative risk = 239.5) compared to other solid organ transplants
(Opelz & Dohler, 2004). In a large population-based cohort of solid organ
transplant recipients registered at the US Scientific Registry of Transplant
Recipients during 1987 - 2008, NHL incidence was highest in lung recipients
(SIR = 18.73, 95%CI = 15.59-22.32) followed by heart (SIR = 7.79, 95%CI =
6.89-8.79), liver (SIR = 7.77, 95%CI = 6.99-8.61) and kidney (SIR = 6.05, 95%CI
= 5.59-6.54) (Engels et al.).
The tumors are characterized by B-cell origin (about 90%), EBV-
associated (~80%), extranodal sites (~80%), and a more aggressive clinical
course and poorer outcome (Tran et al., 2008). The high frequency of EBV
identified in the tumors reflects a critical role of reduced cellular immunity against
EBV in the pathogenesis in post-transplant lymphoma.
Acquired Immune Deficiency. NHL has been recognized as an AIDS-
defining condition for more than two decades and it is one of the most common
malignancies associated with human immunodeficiency virus (HIV) infection.
Approximately 4% of all AIDS cases had NHL as their AIDS-defining illness (Dal
Maso & Franceschi, 2003). Compared to the general population, individuals with
HIV/AIDS had an about 76-fold increased risk of NHL (Grulich, van Leeuwen,
Falster, & Vajdic, 2007). Since the introduction of highly active antiretroviral
therapy (HAART) from 1996, the incidence of AIDS-defining NHL appeared to
47

significantly decline ("Highly active antiretroviral therapy and incidence of cancer
in human immunodeficiency virus-infected adults," 2000) and HIV/AIDS related
deaths were reduced by 50% in the U.S.(Palella et al., 1998). The incidence
cases of AIDS-defining NHL continued to decrease: the estimated number during
2001 and 2005 was only about half of the number during 1991-1995 even though
the HIV/AIDS population increased approximately 3-fold from 1991 to 2005
(Shiels et al.).
As early as the 1980s, U.S. Centers for Disease Control and Prevention
(CDC) had defined three major subtypes of AIDS associated NHL: primary
central nervous system (PCNS) NHL, immunoblastic NHL and BL ("Centers for
Disease Control and Prevention. Revision of the case definition of acquired
immunodeficiency syndrome for national reporting - United States," 1985). HIV is
not considered as an oncogenic virus; instead, EBV has been found in AIDS-
defining NHL tumors. PCNS NHL occurs in individuals with profound immune
deficiency and EBV is found virtually in all tumors; immunoblastic NHL or DLBCL
tends to occur in moderately immune deficiency and EBV is found in 80% of the
tumors; 30% of the cases with BL are positive for EBV (Tran et al., 2008). A
multi-factorial pathogenesis, including chronic antigenic stimulation with B-cell
activation, impaired T-cell immunosurveillance and genetic transformations by
EBV, has been suggested in the pathogenesis of AIDS-defining NHL (Grulich et
al., 2000).
48

Conclusions. One of the notable features shared by immune deficiency
associated NHL is the high frequency of EBV identified in tumors. EBV-positive
NHL reflects uncontrolled proliferation of EBV-transformed B-cells in the absence
of effective T-cell surveillance, especially under T-cell predominant deficiency,
such as solid organ transplant patients (Hanto, Frizzera, Gajl-Peczalska, &
Simmons, 1985) and HIV infected individuals (Grulich et al., 2000). Nevertheless,
the majority of EBV-negative NHL cases suggest that alternative pathways may
exist.

Autoimmune Rheumatic Diseases
Autoimmune diseases comprise a heterogeneous group of conditions
characterized by dysregulation in various components of the immune responses
which leads to the failure of tolerance to self-antigens. Overall, women are more
predisposed to autoimmune diseases than men while the reverse is true for the
majority of lymphoproliferative diseases, including NHL (Ansell et al.).
Autoimmune inflammatory and rheumatic diseases, such as Rheumatoid
Arthritis (RA), Systemic Lupus Erythematosis (SLE), and Sjögren's Syndrome
(SS) are among the most studied autoimmune conditions in relation to NHL.
Cumulative data arising from population based case-control and cohort studies
have generally supported an increased risk of NHL associated with autoimmune
rheumatic diseases, especially SS, SLE and RA (Dias & Isenberg, ; Grulich,
49

Vajdic et al., 2007). Observational studies examining the association between
autoimmune conditions and NHL are usually hampered by a small number of
exposed individuals with autoimmune rheumatic conditions. Nevertheless, a
meta-analysis of cohort studies (published up to 2005) has provided supporting
evidence: primary SS was found as a strong risk factor for NHL (SIR = 18.8,
95%CI = 9.5-37.3) and SLE and RA were moderate to modest risk factors for
NHL (SLE: SIR = 7.4, 95%CI = 3.3-17.0; RA: SIR = 3.9, 95%CI = 2.5-5.9)
(Zintzaras, Voulgarelis, & Moutsopoulos, 2005). Complimentary to this meta-
analysis, a large pooled analysis of case-control studies involving over 12,000
cases and 16,000 controls by the InterLymph Consortium also found an
increased risk associated with SS (OR = 6.6, 95%CI =3.1-13.9) and SLE (OR =
2.7, 95%CI = 1.7-4.3) despite no association for RA, and the similar risk patterns
were observed for B-cell NHL (Ekstrom Smedby et al., 2008).
Autoimmune conditions are more likely to be associated with aggressive B-
cell lymphomas, particularly DLBCL, than indolent B-cell lymphomas, such as
follicular lymphoma. Several population based case-control studies in addition to
the InterLymph pooled analysis reported a significantly increased risk of DLBCL
associated with SS (OR ranged from 2.0 to 11.0) and SLE (OR ranged from 1.4
to 6.2) (L. A. Anderson et al., 2009; Ekstrom Smedby et al., 2008; Smedby et al.,
2006). RA was associated with a modest increased risk of DLBCL in a few
population based case-control studies (OR = 1.4 - 2.6) (L. A. Anderson et al.,
2009; Ansell et al., ; Smedby et al., 2006) though it was not associated in the
50

InterLymph pooled-analysis (Ekstrom Smedby et al., 2008). An increased risk of
follicular lymphoma was associated with only SS (OR = 3.9, 95%CI = 1.4-11.0)
but not other rheumatic conditions in the InterLymph pooled analysis (Ekstrom
Smedby et al., 2008), while a slightly increased risk of follicular lymphoma
associated with RA was reported by another study (OR = 1.3, 95%CI = 1.1-1.5)
(L. A. Anderson et al., 2009). However, marginal zone lymphoma, another
indolent type of NHL, was strikingly linked to SS in the InterLymph pooled
analysis (OR = 30.6, 95%CI = 12.3-76.1) (Ekstrom Smedby et al., 2008) and
other population- based case-control studies (OR = 28, 95%CI = 4.4-176.0; OR =
75, 95%CI = 9.1-610) (Engels et al., 2005; Smedby et al., 2006).
Nonetheless, there has been a debate over whether immunosuppressive
therapy used to treat autoimmune rheumatic diseases plays a role in
lymphomagenesis (Goldin & Landgren, 2009), although current epidemiological
is inconclusive (Hakulinen, Isomaki, & Knekt, 1985; Mariette et al., 2002;
Toussirot & Wendling, 2007). However, in a case-cohort study within an
international SLE cohort, risk of developing hematological cancer among SLE
patients treated with immunosuppressive drugs (e.g. methotrexate or
cyclophosphamide) doubled when the duration of using these drugs exceeded 5
years (Bernatsky et al., 2008). In addition, use of immunosuppressive drugs may
also result in infection caused by reactivation of EBV, which could contribute to
the development of lymphoma under the immunosuppressant status.
51

Chronic immune stimulation caused by autoimmune process is
hypothesized as the mechanism for lymphomagenesis (Dias & Isenberg).
Autoimmune stimulation results in overstimulation and defective apoptosis of B-
cells and also generates a secondary inflammation (Kristinsson et al., 2009).
Hyperactivity and dysregulation of B-cells along with impaired T-cell control has
been proposed as a possible mechanism of lymphomagenesis in patients with
autoimmune diseases (Hansen, Lipsky, & Dorner, 2007). Goodnow et al.
proposed that multi-step processes that disregard the checkpoints which prevent
uncontrolled B-cell growth, including the self-reactive B-cells, lead to both
autoimmune diseases and lymphoproliferative diseases (Goodnow, 2007). In
addition, autoimmunity also leads to activation of other immune cells and results
in release of cytokines and chemokines which could have a pro-B cell growth
affect (Kristinsson et al., 2009). The role of cytokines is supported by a finding
that the joint effect of TNF-alpha (pro-inflammatory cytokine) and IL-10
(immunoregulatory cytokine), both involved in mediating inflammation, modified
the association between autoimmune diseases and NHL (Wang, Cozen et al.,
2007).

Infectious Agents
A few infectious agents have been established as risk factors for particular
subtypes of NHL (Engels, 2007). These known infectious agents can be further
52

classified into three groups: lymphocyte transforming viruses, including EBV,
Human herpes virus 8 (HHV 8), HTLV- 1; agents that cause immunosuppression,
such as HIV; and agents that cause chronic immune stimulation, such as
Helicobacter pylori (H. pylori) or hepatitis C virus (HCV) (Engels, 2007).
EBV, a herpes virus with B-cell transforming activity, was first identified in
BL cells about 40 years ago (Epstein et al., 1964). In sub-Saharan Africa and
Papua New Guinea, BL is endemic, typically affecting children with a peak age of
tumor occurrence at 7 years a male predominance (Morrow, Gutensohn, & Smith,
1976; Olweny et al., 1977). The etiologic role of EBV in Endemic BL has been
supported by the findings that EBV is found in nearly all the tumors
(approximately 95%) and antibody titers against the EBV capsid antigen are
elevated several years before diagnosis (de-The et al., 1978). On the other hand,
EBV is rarely identified in sporadic BL (about 15%) in North America and Europe
(P. H. Levine et al., 1982; Philip et al., 1982). Despite the huge difference in EBV
positivity between Endemic and sporadic BL, the hallmark of all types of BL is
characterized by a chromosomal translocation involving c-myc oncogene and Ig
heavy- or light- chain (Dalla-Favera et al., 1983; Taub et al., 1982). EBV is also
strongly implicated in NHL occurring in immune deficiency states: it is frequently
found in primary immunodeficiency associated NHL (Immunosurveillance,
Immunodeficiencies and Lymphoproliferations:Lymphoproliferative Disorders in
Congenital and Acquired Immunodeficiencies, 2002) and post-transplant
53

associated NHL (Tran et al., 2008). In addition, EBV is always detected in
extranodal natural killer/T-cell NHL (Harabuchi et al., 1990).
The other two viruses able to transform lymphocytes are HHV8 and HTLV-
1. HHV 8, also known as Kaposi’s Sarcoma herpes virus, was first discovered
about two decades ago (Y. Chang et al., 1994) and is the causal agent for
Kaposi’s Sarcoma. It has also been found associated with two rare subtypes of
NHL - primary effusion lymphoma, a body-cavity-based lymphoma (Cesarman,
Chang, Moore, Said, & Knowles, 1995) and multicentric Castleman disease
associated plasmablastic NHL (Oksenhendler et al., 2002). HTLV-1 has been
established as the causal virus for ATLL (Manns et al., 1999). It occurs much
more frequently in regions where HTLV-1 is endemic, such as southwestern
Japan, the Caribbean islands, sub-Saharan African countries, Iran and
Melanesia, though it occurs sporadically in South America (e.g. Brazil) and North
America (Proietti et al., 2005).
HIV infection is characterized by a specific depletion of CD4+ T cells,
which leads to a profound cell-mediated immunodeficiency and further
dysregulation of B cells. As CD4+ T cell counts decrease, risk of primary central
nervous system NHL and DLBCL rises dramatically in AIDS patients due to
decreased immunosurveillance and control of B-cells (Mbulaiteye, Biggar,
Goedert, & Engels, 2003). HIV itself is not an oncogene; in fact, HIV sequences
have never been found within the neoplastic lymphoid cells (IARC Working
Group on the Evaluation of Carcinogenic Risks to Humans. Human
54

Immunodeficiency riruses and human T-cell lymphotropic viruses, 1996). On the
other hand, other oncogenic viral infections are implicated in lymphomagenesis:
EBV is usually involved in AIDS-defining NHL.
H. pylorus, a gastric pathogen, is a typical infectious agent that causes
chronic immune stimulation. It is now considered a causal agent for gastric
mucosal associated lymphoid tissue (MALT) lymphoma. A history of H. pylori
infection was associated with an increased risk of gastric MALT lymphoma (OR =
6.3, 95%CI = 2.0-19.9) but not with lymphomas at other sites (Parsonnet et al.,
1994). Several lines have supported the causal relationship between H. pylori
and gastric MALT lymphoma: Wotherspoon et.al. reported that H. pylori infection
was found in almost all cases of gastric MALT lymphoma (92%) (Wotherspoon,
Ortiz-Hidalgo, Falzon, & Isaacson, 1991); in vitro studies further confirmed the
importance of H. pylori in the pathogenesis of gastric lymphoma (Hussell,
Isaacson, Crabtree, & Spencer, 1993); finally, and most importantly, eradication
of H. pylori resulted in regression of low-grade gastric MALT lymphoma
(Wotherspoon et al., 1993).
Although not considered as an oncogenic virus, Hepatitis C virus is known
to cause chronic immune stimulation and contributes to the development of
chronic hepatitis, cirrhosis, and hepatocellular carcinoma (Lauer & Walker, 2001).
Prevalence of HCV infection varies substantially by geographic regions: countries
with the highest reported prevalence rates (~10%) are in Africa and Asia; areas
with lower prevalence (~ 2%) include North America, northern and western
55

Europe, and Australia (Shepard, Finelli, & Alter, 2005). Because of the large
variation in prevalence of HCV infection, inconsistent results regarding the
association between HCV and NHL have been reported by epidemiologic studies,
with significantly positive association observed in regions where HCV prevalence
is high (e.g. Italy or Japan) (Ferri et al., 1994; Izumi, Sasaki, Miura, & Okamoto,
1996; Mizorogi et al., 2000; Silvestri et al., 1997) while studies in North America
and Europe failed to find any association (Collier et al., 1999; Germanidis et al.,
1999; Rabkin et al., 2002; Shariff et al., 1999). In a meta-analysis of both case-
control and cohort studies, an increased risk associated with HCV infection was
observed (OR = 2.5, 95%CI = 2.1-3.0); however, a significant heterogeneity in
the magnitude of the association was found as well, with the stronger association
observed in regions with higher HCV prevalence (Dal Maso & Franceschi, 2006).
In an InterLymph pooled analysis in which all participating studies had low HCV
prevalence with exception of the one from Italy, HCV prevalence was significantly
positively associated with an overall NHL risk (OR = 1.78, 95%CI = 1.40-2.25)
and also with MZL risk (OR = 2.47, 95%CI = 1.44-4.23) and DLBCL risk (OR =
2.24, 95%CI = 1.68-2.99) but not with Follicular lymphoma; no significant
heterogeneity across the 7 participating studies was observed in the pooled
analysis (de Sanjose et al., 2008). Overall, whether HCV is a causal factor for
NHL or subtypes of NHL still needs further investigation.

56

Atopic Diseases
Extensive epidemiological studies have investigated the association between
atopic disease history, particularly allergies, and cancer risk, with a strong
inverse association found for glioma, pancreatic cancer and childhood leukemia
(Turner, ; Turner et al., 2006). Although a definite conclusion has not been
drawn regarding the association between atopic disease and NHL, it is
biologically plausible to hypothesize that atopic disease may affect NHL risk
because it is a disease of immune response cells. Results from current literature
are mixed: while many of the case-control studies generally support an inverse
association, cohort studies have not confirmed this association, although most of
the current cohort studies have limited power because they followed young
populations for a short time (Martínez-Maza et al.).
Atopic conditions have become common diseases in the U.S. A national
survey reported that more than half (54.3%) of the population in the U.S. had
positive test response to at least one allergen (Arbes, Gergen, Elliott, & Zeldin,
2005). Hay fever or allergic rhinitis affects up to 10-30% of the population in the
US annually (Wallace et al., 2008). Asthma prevalence was estimated at
approximately 8.4% in 2010 (Akinbami et al.). Eczema or atopic dermatitis is
more common in children than in adults; a national survey conducted in 2003 in
U.S. found that approximately 10.7% children (under 18 years) was diagnosed of
eczema during the past year (Shaw, Currie, Koudelka, & Simpson).
57

Overall, hay fever (allergic rhinitis) has been reported to decrease risk of
all NHL combined by approximately 15-35% in several population based case-
control studies (Bracci, Dalvi, & Holly, 2006; Cozen et al., 2007; Grulich et al.,
2005; Melbye et al., 2007; Vineis, Crosignani et al., 2000); however, other
epidemiologic studies did not find a significant association (Briggs, Levine, &
Brann, 2002; Doody et al., 1992; Soderberg, Hagmar, Schwartzbaum, &
Feychting, 2004; Turner et al., 2005; Zhang et al., 2004). The association also
differed by major subtypes of NHL. A few studies reported a significantly
decreased risk for DLBCL (OR [95%CI] = 0.60 [0.4-0.9] and 0.83 [0.68-1.00],
respectively) but not for follicular lymphoma (Cozen et al., 2007; Melbye et al.,
2007). An even stronger inverse association has been reported for mantle cell
lymphoma (MCL) and lymphoplasmacytic lymphoma (OR = 0.58, 95%CI = 0.34-
0.99; OR = 0.61, 95%CI = 0.38-0.98, respectively) (Melbye et al., 2007).
The association between specific allergy (e.g. animal, plant or food
allergy, etc) and NHL has also been examined in several epidemiological studies.
However, it is difficult to compare results between studies because of a wide
variation in the definition of specific allergies used in each study. An
approximately 30-70% decreased risk of all NHL combined (Becker et al., 2007;
Grulich et al., 2005) or B-cell NHL (Becker et al., 2007) was found to be
associated with unspecified food allergy, and another study reported that allergy
to nuts or berries was inversely associated with NHL in women (OR = 0.45,
95%CI = 0.20-0.99) (Bernstein & Ross, 1992). Animal and plant allergy have
58

also been reported to be protective factors for certain subtypes of NHL,
respectively, including diffuse large cell lymphoma and small lymphocytic
lymphoma (Holly & Bracci, 2003). However, three other studies did not find any
association between specific allergy and NHL risk (Briggs et al., 2002; Cozen et
al., 2007; Holly, Lele, Bracci, & McGrath, 1999).
Currently, the strongest support for the inverse association between hay
fever / specific allergy and NHL comes from an InterLymph pooled analysis of 13
case-control studies involving over 13,000 cases and 16,000 controls: hay fever
was a modest protective factor for B-cell NHL (OR = 0.85, 95%CI = 0.77-0.95)
and follicular lymphoma (OR = 0.78, 95%CI = 0.66-0.92); any specific allergy
was inversely associated with all NHL combined (OR = 0.80, 95%CI = 0.68-0.94)
and B-cell NHL (OR = 0.78, 95%CI = 0.67-0.90) (Vajdic et al., 2009). More
importantly, such inverse association persisted when hay fever or specific allergy
occurred 10 years or more before NHL diagnosis, which supports an etiological
effect. Another piece of supporting evidence comes from our case-control study
involving like-sexed twin pairs discordant for NHL, in which a much stronger
protective effect from hay fever was found (OR = 0.28, 95%CI = 0.10-0.75),
persisting when we examined MZ twin pairs alone (0.50, 95%CI = 0.15-1.66)
(though not significant.) Controlling for genetic and early childhood background
increased the magnitude of the association.
In general, there is no previous evidence of an association between
asthma and NHL risk (Cozen et al., 2007; Fabbro-Peray, Daures, & Rossi, 2001;
59

Melbye et al., 2007; Soderberg, Jonsson, Winqvist, Hagmar, & Feychting, 2006;
Zhang et al., 2004). An inconsistent association between eczema and NHL has
been reported: a significant protective effect in two population based case-control
studies (OR ranged from 0.5 to 0.6) (Bernstein & Ross, 1992; Fabbro-Peray et al.,
2001) but an increased risk from childhood eczema in a cohort study (OR = 2.3,
95%CI = 1.0-5.3) (Soderberg et al., 2004), while no significant association in
other epidemiologic studies (Cozen et al., 2007; Doody et al., 1992; Melbye et al.,
2007; Vineis, Crosignani et al., 2000; Zhang et al., 2004). There is more
heterogeneity by NHL subtype: a positive association has been reported between
childhood eczema and diffuse large cell lymphoma (OR = 1.6, 95%CI = 1.1-2.6)
(Holly & Bracci, 2003), and a history of eczema and follicular lymphoma (OR =
2.3, 95%CI = 1.1-4.2) (Cozen et al., 2007), eczema and T-cell NHL (OR = 2.5,
95%CI = 1.1-5.7) among women (Zhang et al., 2004).
Most of the case-control studies used self-report from questionnaires to
obtain information regarding history of atopic diseases, while only a few cohort
studies used an objective measurement, such as skin prick test or biomarker of
atopy – serum immunoglobulin E (IgE) antibody. In a large population based
case-control study, Melbye et al. found that individuals who tested positive for
serum specific IgE had an approximately 30% decreased risk of all NHL
combined (OR = 0.68, 95%CI = 0.58-0.80) and even lower risk for CLL (OR =
0.36, 95%CI = 0.26-0.51). In addition, an increasing serum IgE level was
significantly associated with a decreasing risk of all NHL combined and CLL (P-
60

trend: <0.001 for both) (Melbye et al., 2007). Nevertheless, in a parallel analysis
of IgE levels measured before NHL diagnosis where blood samples were
collected from pregnant women enrolled in a Finnish Maternity Cohort, no
association between serum specific IgE levels and NHL was found, except a
possible association when blood samples were collected within 1 year before
NHL diagnosis (OR = 0.27, 95%CI = 0.03-2.31). Also, the effect of specific IgE
reactivity diminished as the time prior to diagnosis increased (OR = 1.00, 95%CI
= 0.48-2.09 when time before diagnosis ≥ 10 years) (Melbye et al., 2007). Serum
total IgE levels were not associated with NHL risk in another prospective study
(standardized incidence ratio = 0.98, 95%CI = 0.92-1.04) despite its limited
follow-up time (Lindelof, Granath, Tengvall-Linder, & Ekbom, 2005). Two cohort
studies used skin prick test to assess atopy (Eriksson, Holmen, Hogstedt,
Mikoczy, & Hagmar, 1995; Eriksson, Mikoczy, & Hagmar, 2005); however, these
two studies had very limited power. Therefore, studies with objective
measurement of atopy generally do not support such an inverse association.
In summary, cumulative data from case-control studies have suggested a
modest protective effect from atopic conditions, mostly hay fever and allergies,
but little evidence has been found in prospective studies. The failure to replicate
the inverse association in longitudinal studies has led to the debate whether such
an association is merely due to the disease effect given NHL status may affect B-
cell ability to produce normal levels of immunoglobulin, including IgE. Future
large-scale cohort studies with repeated measurement are needed to clarify this
61

association. Particularly, it is important to incorporate an objective measurement
of atopy, such as skin prick test or serum IgE antibody, in addition to self-report.

Infectious Mononucleosis
Infectious (EBV-related) mononucleosis (IM) is the clinically apparent syndrome
of primary EBV infection (Henle, Henle, & Diehl, 1968). While more than 90% of
the human population is infected with EBV, the age at primary infection varies
worldwide: the childhood infection rate is much higher in developing countries
than in developed countries (de-The et al., 1975; Kangro et al., 1994). Infection
during childhood, however, is usually subclinical without disease manifestation.
When the primary EBV infection is delayed to adolescence or young adulthood,
IM may occur. IM incidence usually peaks at age 15-19 years in developed
countries (Auwaerter, 1999). Thus IM can be considered a proxy for relative
childhood isolation from infections.
Inconsistent results regarding the association between IM and NHL have
been generated from current literature body of epidemiological studies: several
case-control studies along with a hospital-based cohort study found a
significantly increased risk (Becker et al., 2009; Goldacre, Wotton, & Yeates,
2009; R. Levine et al., 1998; Vineis, Crosignani et al., 2000) while others
reported no association (Hjalgrim et al., 2000; Zhang et al., 2004). In a recently
published pooled analysis involving over 12,000 cases and 15,000 controls, a
62

self-reported history of IM was associated with a modest increased risk of NHL
(OR=1.26, 95%CI=1.01-1.57) (Becker et al.). In two studies with a positive
association, the strength of the association decreased or even disappeared as
the time interval between IM and NHL increased (Goldacre et al., 2009; Vineis,
Crosignani et al., 2000). Vineis et al. also found that the association was much
stronger in participants with higher education (Vineis, Crosignani et al., 2000). In
our case-control study involving like-sexed NHL-discordant twin pairs, a
protective effect rather than an increased risk was found (OR = 0.35, 95%CI =
0.14-0.90), similar when limited to discordant MZ twin pairs (OR = 0.27, 95%CI =
0.08-0.98). The positive associations were found in standard case-control studies
that did not control for genetic background and may be hampered by recall bias,
which is unlikely to occur in our study (e.g. inverse association is unlikely to be
explained by recall bias).
Although the true IM-NHL association remains elusive, there appears to be
biological explanation for such an association. The clinical features of IM include
an altered immune response, with B- and T-lymphocyte proliferation and cytokine
production. IM is characterized by antigen-driven clonal expansions of CD8+ T-
cells in response to primary EBV infection (Cohen, 2000). Upon activation, CD8+
T cells can stimulate the release of cytokines, including TNF-α, IL1β, IL2, and
IFNγ (Biglino et al., 1996; Foss et al., 1994). EBV-encoded proteins may also
have close interactions with B cells and cytokines. One of the important proteins
encoded by EBV - latent membrane protein 1 (LMP-1) is functionally similar to
63

CD40 and can partially replace CD40 in vivo, generating signals for B-cell growth
and differentiation (Uchida et al., 1999). Similarly, LMP-2A is able to mimic the
signaling of B-cell receptor, which contributes to the long-term survival of B-cells
(Portis, Cooper, Dennis, & Longnecker, 2002). Cytokines, including IL-4 and IL-6,
are responsible for the induction of LMP-1 in EBV infected latent B-cells (Kis,
Takahara, Nagy, Klein, & Klein, 2006). Therefore, given the profound impact of
IM on the B- and T- cell immunity, the association between IM and NHL appears
to be plausible, but effects could be dependent on age at infection. For example,
Hepatitis B contracted vertically as an infant is asymptomatic at birth but results
in more severe consequences (hepatocellular carcinoma) than when acquired
later (Feitelson, 1992). More importantly, the involvement of immune response
genes, especially cytokines, in the clinical pathology of IM may provide clues
about the cytokine-related pathways exist in the IM-NHL relationship. Future
studies investigating the interactions of IM and immune response genes on NHL
risk may uncover the true association between IM and NHL.

Birth Order and Sibship Size
Increasing birth order and large sibship size have been considered as a proxy for
early life exposure to infectious agents (Strachan, 2000). Infections during early
life may critically modulate immune function. One of the examples is the
observation of the inverse association between atopic conditions and later birth
64

order and large family size, which can be explained by the ‘hygiene hypothesis’
(Strachan, 1989). Overall, the ‘hygiene hypothesis’ states that improvement in
sanitation and decline in family size results in later and fewer exposures to
infectious agents and thus alters immune function which increases the risk of
immune-related disorders.
Numerous epidemiological studies have investigated the association
between birth order, family size and NHL. Overall, results have been
inconsistent. Several population- based case-control studies reported that
increasing birth order was significantly associated with a linear increase in NHL
risk (Becker et al., 2007; Bracci et al., 2006; Cozen et al., 2007; Grulich et al.,
2005; Smedby et al., 2007), while other case-control studies did not find any
association (Becker, Deeg, & Nieters, 2004; Mensah, Willett, Simpson, Smith, &
Roman, 2007). A few population-based case-control studies found that
increasing sibship size was associated with an increased NHL risk (Bracci et al.,
2006; Holly et al., 1999; Smedby et al., 2007) while others did not (Becker et al.,
2004; Cozen et al., 2007; Mensah, Willett, Simpson et al., 2007; Vineis, Miligi et
al., 2000). Altieri et al. found no association between birth order or sibship size
and NHL risk in a Swedish population-based cohort (Altieri, Castro, Bermejo, &
Hemminki, 2006); however, Crump et.al. reported a significant positive
association between birth order and NHL (P-trend = 0.02) in another birth cohort
in Sweden (Crump, Sundquist, Sieh, Winkleby, & Sundquist). The latter cohort
study was based on a relatively younger population with the age ranging from 0-
65

37 years while NHL typically occurs in older people. In a recent InterLymph
pooled analysis involving 18 case-control studies of over 13,000 cases and
16,000 controls, no significant association between either later birth order or
larger sibship size and NHL overall was found; however, significant associations
were observed for some B- or T-cell subtypes (Grulich et al.). Nevertheless,
increasing birth order was found significantly associated with an increased NHL
risk in several subgroups. For instance, the significantly positive association was
observed in population based case-control studies where response rates in
cases and controls were low, but not in hospital based case-control studies
where response rates were relatively high. The similar positive association was
also observed in stratum of participants with high socioeconomic status (SES)
but not in strata of participants with low to medium SES. These findings led the
authors to attribute the apparent association to selection bias related to SES,
given the known correlation between later birth order and low SES. However, in
another case-control study conducted in the UK, the authors assessed the
selection bias by comparing observed distribution of birth order with expected
reference distributions derived using national birth statistics from the UK; after
taking into account potential selection bias in the analysis, they concluded that
although no association between birth order and NHL risk overall was found,
there was little evidence suggesting an influence of selection bias on the results
(Mensah, Willett, Simpson et al., 2007).
66

Overall, results from epidemiological studies are inconclusive.
Nevertheless, there appears to be possible biological mechanisms for the
positive association between birth order/sibship size and NHL. One of the
possible explanations is that infection during early life may be a risk factor of NHL.
Later birth order and large sibship size typically favor earlier exposures to
infectious agents because younger siblings are exposed to infections earlier
through their older siblings while first-born or second-born children are usually
exposed to common infections after enrollment at school (Green & Zaaide, 1989;
Hsieh et al., 1992). Previous epidemiologic studies have reported several
infectious agents may be transmitted in families, including EBV, Helicobacter
pylori (Santos et al., 2005), hepatitis A virus (Green & Zaaide, 1989), hepatitis B
virus (Hsieh et al., 1992), Meningococci (Goldacre, 1977) and parvovirus B19
(Valeur-Jensen et al., 1999). However, except a few infectious agents which
have been considered as causal factors for rare subtypes of NHL (Engels, 2007),
very few infectious agents have been identified as the culprit for the majority of
NHL. Therefore, the unresolved issue is which infectious agent(s) might be
involved in the pathogenesis of NHL if exposed at early life. Alternatively, it does
not matter which particular infectious agent plays an etiologic role in the
lymphomagenesis; instead, it is the commensal infections (e.g. commensal gut
microflora) during the very early life that impact the immune system (Wills-Karp,
Santeliz, & Karp, 2001).
67

One potential concern is most of the studies did not examine sibship birth
intervals. It is generally thought that transmission of infections is more likely to
occur among closely spaced siblings. In a population based case-control study,
Ponsonby et al. found that compared to individuals without a younger sibling,
individuals with a younger sibling within 2 years of their age had an
approximately 70% decreased risk of multiple sclerosis while there was no
association for individuals with a younger sibling born more than 6 years earlier
(Ponsonby et al., 2005). Thus, it is also important for future studies to take into
account sibship birth interval.

Summary
Overall, current literature body has provided strong evidence of the role of altered
immunity in NHL etiology. It is no doubt that profound immune deficiency
dramatically increases NHL risk. Autoimmune rheumatic conditions are now
considered to be moderate risk factors. However, these conditions are, overall,
rare in the general population and may not explain the large increase in NHL
incidence, especially during the 1970s and 1990s. The remaining question
would be whether moderate or mild alteration in immunity also contributes to
NHL risk in immunocompetent individuals, with more common immune related
conditions, such as atopic diseases and IM, of special interest. As most of the
evidence for common immune related conditions comes from case-control
68

studies, reverse causality as an explanation for the observed inverse association
may not be completely ruled out, particularly for the atopy-NHL association.
However, birth order and sibship size, a proxy of early life exposure to infections,
may not suffer from the ambiguity of the temporal relationship. An always ideal
study design is a large longitudinal study with repeatedly measured biomarkers
and relatively long follow-up. Alternatively, immune related genes which reflect
genetically determined immune functions can be used as a marker of variation in
immune functions. In fact, some gene variants involved in immunity have already
been established as risk factors of NHL (Chapter 5). Therefore, the assessment
of interactions between immune-related genes and conditions may provide
insightful information regarding biologically relevant pathways involved in
lymphomagenesis.

69

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82

Chapter 5. Immune-related Genes and Risk of
Non-Hodgkin Lymphoma

Introduction
Several lines of evidence have shown a genetic contribution to NHL. Individuals
with a history of hematopoietic malignancy in first-degree relatives had an
elevated risk of NHL in multiple studies (Altieri, Bermejo, & Hemminki, 2005; E. T.
Chang et al., 2005; Chiu et al., 2004; Goldin et al., 2005; Mensah, Willett, Ansell,
Adamson, & Roman, 2007; Wang, Slager et al., 2007; Zhang et al., 2007; Zhu et
al., 1998), with no distinct pattern of heritability by NHL subtypes (Altieri et al.,
2005; E. T. Chang et al., 2005; Wang, Slager et al., 2007; Zhang et al., 2007).
However, many of the studies suggested a stronger familial association among
siblings than parents (E. T. Chang et al., 2005; N. Chatterjee et al., 2004; Wang,
Slager et al., 2007; Zhang et al., 2007). This could suggest that a commonly
shared environment during childhood and young adolescence. A number of
case-controls studies have investigated candidate gene polymorphisms and NHL
risk, with a major group focusing on the genes that alter immunity, especially
those affecting B-cell growth and survival (Skibola et al., 2007). Current genome
wide association studies also support the role of immune-related genes in
lymphomagenesis.

83

Proinflammatory and Immunoregulatory Genes
SNPs in proinflammatory and immunoregulatory cytokines are the most studied
and best characterized candidate gene variants associated with NHL risk. A
recent pooled analysis involving 7999 cases and 8452 controls by the
InterLymph Consortium (Skibola et al.), the largest candidate genetic association
study of NHL to date, reported that variant allele of TNF -308G>A was
significantly associated with an increased risk of all NHL combined and DLBCL in
non-Hispanic whites, consistent with a previous InterLymph pooled analysis
(Rothman et al., 2006). The increasing number of variant alleles was associated
with an increasing risk of all NHL combined (per allele OR = 1.13, P
trend
= 0.0001)
and DLBCL (per allele OR = 1.25, P
trend
= 3.7 X 10
-6
); however, no significant
association was observed for follicular lymphoma or CLL/SLL (Skibola et al.).
TNF-alpha, typically produced by macrophage/monocytes but also by mast cells,
T- and B- cells, is a potent cytokine which induces a wide range of
proinflammatory effects (Vassalli, 1992). The -308A variant allele is closely
associated with a major histocompatibility complex (MHC) haplotype HLA-A1-B8-
DR3 (Wilson et al., 1993) which in turn increases serum level of TNF-alpha
(Abraham, French, & Dawkins, 1993; Jacob et al., 1990) and also has been
reported to affect risk of autoimmune diseases, including SLE (Price et al., 1999).
Then the question is whether the positive association between TNF -308G>A and
NHL is partially or completely due to its association with the HLA-A1-B8-DR3
haplotype. Nevertheless, the -308A variant allele has been reported to directly
84

enhance TNF-alpha gene transcription (Abraham & Kroeger, 1999; Wilson,
Symons, McDowell, McDevitt, & Duff, 1997) and responsible for elevated TNF-
alpha levels (Abraham & Kroeger, 1999). An important biological function of
TNF-alpha is the activation of the nuclear factor (NF)-κB pathway which has an
essential role in T- and B- cell proliferation, differentiation and survival (Li &
Verma, 2002). Aberrant NF- κB signaling has been implicated in the
pathogenesis of T- and B- cell NHLs and Hodgkin Lymphoma (HL) (Jost &
Ruland, 2007). NF- κB has anti-apoptotic properties and thus induces survival
signals among cells with malignant potential; it also elicits T- and B- cell
proliferation and survival indirectly by inducing proinflammatory cytokines,
lymphokines or other ligands (Jost & Ruland, 2007).
The same InterLymph pooled analysis (Skibola et al.) also found that two
IL10 Single Nucleotide Polymorphisms (SNPs) were associated with an
increased risk of certain subtypes of NHL including IL10 -3575 T>A with DLBCL
(per-allele OR = 1.10) and extra-nodal marginal zone lymphoma (MZL) (per-allele
OR = 1.30); and IL10 -1082 A>G with mantle cell lymphoma (per-allele OR =
1.30). However, there was no association between either of the SNPs and risk of
all NHL combined. Haplotype analysis of IL10 -1082 A>G and -3575 T>A
showed that the increased risk was restricted to the GA haplotype (both variant
alleles) but not the GT haplotype (only the -1082 G variant allele), which
suggests that -3575 A allele may be more important than -1082 G allele in
lymphomagenesis (Skibola et al.). The IL10 -3575 A allele has been found to
85

decrease IL10 production (Gibson et al., 2001). IL10, an anti-inflammatory
cytokine produced by monocytes and lymphocytes, is a potent down-regulator of
TNF-alpha (Wanidworanun & Strober, 1993). Therefore, -3575 A allele could
potentially lead to less suppression of TNF-alpha, resulting in a strong
proinflammatory milieu. The increased risk associated with both genetic variants
in TNF-alpha (-308 G>A) and IL10 (-3575 T>A) implies that an alteration in
proinflammatory pathways may contribute to the lymphomagenesis, especially
for DLBCL.
Lymphotoxin-alpha (LTA), a member of the tumor necrosis factor
superfamily, has similar biologic activity to TNF-alpha (Nedwin et al., 1985). LTA
252 A>G has been reported to be associated with an increased risk of DLBCL in
an InterLymph pooled analysis (Skibola et al.). However, LTA 252 A>G is in LD
with TNF -308 G>A (r
2
= 0.34). A haplotype analysis of TNF/LTA revealed that
this haplotype was significantly associated with risk of all NHL combined and
DLBCL, respectively (Skibola et al.). The haplotype analysis failed to separate
effects of the two variants. LTA 252 G allele is strongly associated with
increased LTA production (Messer et al., 1991), which implicates that this gene
variant may also contribute to lymphomagenesis through promoting
proinflammatory milieu.
Gene variants in TNF receptor (TNFR) superfamily have also been
hypothesized to affect NHL risk. Particularly, a functional TNFRSF5
polymorphism (-1C>T) has been reported to be associated with an increased risk
86

of all NHL combined and DLBCL and follicular lymphoma in a pooled analysis of
data from case-control studies conducted in Europe and the U.S.(Nieters et al.).
TNFRSF5 encodes CD40 which is a member of the TNFR superfamily; the
TNFRSF5 -1 T allele is associated with reduced circulating levels of soluble
CD40 (Skibola et al., 2008). The ligation between CD40 expressed on B-cells
and its ligand (CD40L) is essential for B-cell differentiation in the Germinal
Center (GC) through down-regulating B-cell lymphoma 6 (BCL6) protein (Saito et
al., 2007). Activated B-cells with low signals from CD40-CD40L have an
impaired B-cell function (O'Connor, Gleeson, Noelle, & Erickson, 2003).
Therefore, the association between TNFRSF5 and NHL is compatible with the
fact that the majority of B-cell NHL, including DLBCL and follicular lymphoma,
has the cellular origin in germinal center B-cells (Kuppers, 2005).

Genes in Innate Immunity
The innate immune system, the first line of defense against invading organisms,
reacts to non-specific antigens. Pattern recognition receptors play an essential
role in the innate immune response by recognizing pathogen associated
molecular patterns (PAMPs) derived from a variety of microbial pathogens. Toll
like receptors (TLRs), the best characterized pattern recognition receptors,
contribute to the bridging between the innate and adaptive immune responses by
activation and maturation of dendritic cells (DCs) (Kabelitz & Medzhitov, 2007).
87

TLR-mediated signaling pathways leading to activation of NF-κB (Kawai & Akira,
2006). A pooled analysis of three case-control studies reported two variants in
the TLR10–TLR1–TLR6 region (a 57-kb region on chromosome 4p14) were
significantly associated with an overall NHL risk, with one variant linked to an
increased risk (rs10008492) while another one associated with an decreased risk
(rs4833103) (Purdue, Lan, Wang et al., 2009). In addition, the same study
reported that TLR2 Ser450Ser was a significant risk factor for MZL. However, no
study has ever studied the association between the TLR10–TLR1–TLR6 region
and NHL risk, although genetic variation in this region has been reported to affect
asthma risk (Lazarus et al., 2004; Tantisira et al., 2004). On the other hand,
TLR4, the principal receptor for endotoxin recognition, has been studied in
several case-control studies. However, results are inconsistent: TLR4
Asp299Gly was inversely associated with risk of gastric MALT lymphoma
(Hellmig et al., 2005) and diffuse large cell lymphoma (Forrest et al., 2006) in two
epidemiologic studies but was associated with an increased risk of MALT
lymphoma in another case-control study (Nieters, Beckmann, Deeg, & Becker,
2006) while no association was found in a pooled analysis (Purdue, Lan, Wang
et al., 2009). Although no definite conclusion can be drawn from current body of
literature, there appears to be a possible biological mechanism linking TLRs and
NHL risk. Nearly half of the TLR family members, including TLR1, TLR6 and
TLR10, are expressed on human B-cells. Along with TLR ligands (e.g.
lipopolysaccharides for TLR4 and CpG-containing DNAs for TLR9), TLRs are
88

now considered to be important regulators in multiple stages of B-cell activation
and differentiation as well as B-cell tolerance (e.g. autoreactive B-cell response)
(Peng, 2005).
In addition to TLRs, NOD-like receptors are another important class of
pattern recognition receptors. NOD2, also known as caspase recruitment
domain-containing protein 15 (CARD15), regulates anti-microbial activity via a
NF-κB mediated pathway (Chamaillard et al., 2003). NOD2 gene variants have
been identified as definite risk factors for Crohn’s disease (Hugot et al., 2001;
Ogura et al., 2001). A rare CARD15 cytosine insertion at nucleotide 3020 at
exon 11 resulting in a premature stop codon was also assessed in an InterLymph
pooled analysis in terms of its association with NHL risk (Rothman et al., 2006);
however, its rarity made the estimation imprecise (95%CI = 0.12-135) despite a
more than doubled risk associated with the cytosine insertion. Another NOD2
polymorphism Arg702Trp was found to be associated with an increased risk of
gastric MALT lymphoma among H. pylori infected individuals (Rosenstiel et al.,
2006); however, results were not replicated in another study (Ture-Ozdemir et al.,
2008).
Cytokines (e.g. IL1 family and IL6), chemokines (e.g. IL8) and adhesion
molecules (e.g. Fc region receptor II-a) are also involved in the innate immunity
and they participate in the activation of NF-κB pathway as well. In an InterLymph
pooled analysis, no association was found between either IL1 family, including
IL1A, IL1B and IL1RN, or IL6 and NHL risk (Rothman et al., 2006). Overall,
89

current literature is lacking epidemiologic studies of genes involved in innate
immunity and NHL risk.

Human Leukocyte Antigen Region
The human Major Histocompatibility Complex (MHC), also known as human
leukocyte antigen (HLA), is located on the short arm of the chromosome 6 at
6p21.3 and spans approximately 3500 kilobases (kb). More than 200 genes
have been identified in the HLA region, with over 40 encoding leukocyte antigens
(Klein & Sato, 2000a). HLA genes that are involved in the immune response can
be grouped into classes, I and II, although some proinflammatory cytokines are
located in the Class III region, such as TNF-alpha, LTA and LTB. The function of
HLA class I and II molecules is to bind peptide antigens and display them for
recognition by T-cells. In general, peptide antigens associated with class I
molecules, including HLA-A, HLA-B, and HLA-C, are recognized by CD8+ T-cells
while class II molecules (HLA-DR, HLA-DP, HLA-DQ) associated peptide
antigens are recognized by CD4+ T-cells. HLA class I and II genes are the most
polymorphic genes in the genome, presumably driven by the need to maximize
peptide biding diversity, which may reflect the evolutionary selection of resistance
to highly mutable pathogens. It is not until recent years that HLA region has
been investigated for its association with NHL; however, HLA system is known to
be associated with transplantation, autoimmune diseases, and host defense to
90

infectious agents (Klein & Sato, 2000b), all of which are known as risk factors for
NHL.
Currently, the strongest evidence supporting the association between HLA
region and NHL risk come from genome-wide association studies of NHL, of
which all suggest that HLA class II region plays a critical role in NHL, particularly
for follicular lymphoma. Skibola et al. reported that gene variant on 6p21.33
(rs6457327, located near the psoriasis susceptibility region 1 - PSORS1) was
associated with risk of follicular lymphoma (OR
allelic
= 0.59, 95%CI = 0.50-0.70, P
allelic
= 4.7X10
-11
) (Skibola et al., 2009). However, pooled DNA rather than
individual based genotyping was used in this study, which may result in
experimental and technical noise. Thus, another ‘follow-up’ GWAS using
individual genotyping and including more participants was carried out, which still
identified two gene variants on 6p21.32 (rs10484561 and rs7755224, r
2
= 1.0)
associated with risk of follicular lymphoma. SNP rs10484561 was associated with
an almost doubled risk of follicular lymphoma (OR
combined
= 1.95, 95%CI = 1.72-
2.22, P
combined
= 1.12X10
-29
) (Conde et al.). In a third independent genome wide
scan of follicular lymphoma, a second independent marker on 6p21.32
(rs2647012) was found associated with risk of follicular lymphoma (OR
combined
=
0.64, 95%CI = 0.58-0.70, P
combined
= 2X10
-21
) (Smedby et al.). This variant is
located 962 bp away from SNP rs10484561, and the two SNPs remained
genome-wide significant after mutual adjustment (rs10484561: OR
combined
= 1.64,
95%CI = 1.45-1.86, P
combined
= 5X10
-15
; rs2647012: OR
combined
= 0.70, 95%CI =
91

0.67-0.78, P
combined
= 4X10
-12
). Notably, when validating the top follicular
lymphoma associated SNPs identified in the genome wide scan on other types of
NHL, the same study revealed that rs10484561 was also associated with DLBCL
(OR
combined
= 1.36, 95%CI = 1.21-1.52, P
combined
= 1.4X10
-7
) (Smedby et al.),
which may imply a shared genetic etiology at some point.
In parallel with genome wide association studies, candidate genetic
association studies also support a role for HLA region in NHL etiology. Wang et
al reported that HLA-DRB1*0101 was associated with a more than double risk of
follicular lymphoma, while HLA-DRB1*13 was associated with an approximately
50% decreased risk of follicular lymphoma and HLA-DRB1*0401 with a 55%
decreased risk of DLBCL (Wang et al.). In another case-control study of
follicular lymphoma, HLA-DQB1*05 was identified as a risk factor (OR = 1.70,
95%CI = 1.28-2.27) while HLA-DQB1*06 was inversely associated with risk of
follicular lymphoma (OR = 0.51, 95%CI = 0.38-0.69) (Akers et al.). These
findings are consistent with those from a GWAS which identified a novel risk
allele in 6p21.32 (rs10484561) given that this risk variant appeared to be part of
an extended haplotype which includes HLA-DRB1*0101-HLA-DQA1*0101-HLA-
DQB1*0501. Taken together, genetic variation in the HLA class II region is
strongly associated with risk of follicular lymphoma and more importantly, gene
variants in the HLA region may differentially affect the susceptibility of NHL
subtypes.
92

TNF-alpha, a gene variant consistently found as a risk factor for all NHL
combined and DLBCL in candidate gene studies and large pooled analyses, is
also located in HLA region. Specifically, it is located within the class III locus,
approximately 200-250 kb centromeric to the HLA-B locus and 850 kb telomeric
to the HLA-DR locus. The TNF -308A allele is part of the 8.1 ancestral haplotype
HLA-A1-B8-TNF-308A-DR3-DQ2 which has been found associated with
susceptibility to autoimmune diseases in white population, including SLE and SS
(Candore, Lio, Colonna Romano, & Caruso, 2002; J. L. Newton et al., 2004;
Schotte et al., 2005). Given the evidence from genome wide association studies
of the association between HLA region and NHL (particularly, follicular
lymphoma), it is unclear whether the effect of TNF -308G>A is an independent
risk factor or is due to linkage with HLA alleles or haplotypes. In a candidate
gene study assessing the joint effect of HLA-A1-B8-DR3 haplotype (8.1 ancestral
haplotype) and TNF -308G>A, the association between TNF -308A and NHL risk,
particularly DLBCL, was independent of either the HLA-A1-B8-DR3 alleles or
haplotype, and the association between HLA-B*08 allele and DLBCL was
independent of TNF -308A risk alleles (Abdou et al.). These findings appear to
support a separate effect of TNF -308G>A and the 8.1 ancestral haplotype. In an
earlier study, TNF -308G>A along with HLA-DRB1*02 were independent
predictors of the clinical outcome of NHL, including freedom from progression
and overall survival (Juszczynski et al., 2002). However, there are few functional
93

studies that have delineated the effects of TNF -308G>A and HLA class region;
future studies are required to confirm these results.
Chronic B-cell stimulation may be one of the mechanisms by which HLA
class II alleles affect NHL susceptibility. Polymorphisms in HLA class II genes
may influence binding and presentation of peptide antigens and thus further
affect activation of CD4+ T helper cells. The altered interactions between HLA
class II bound peptide antigens and CD4+ T helper cell may result in abnormal B-
cell activation and proliferation. However, future studies may further probe into
the specific pathways associated with follicular lymphoma as current GWAS
evidence supports a role of HLA class II alleles in follicular lymphoma
susceptibility.

Conclusion
Genome wide association studies along with large pooled case-control studies
have provided strong evidence that HLA region, specifically HLA class II and III,
play a critical role in NHL etiology. Notably, etiological heterogeneity appears for
major subtypes of NHL, with GWAS hits generally supporting a role of HLA class
II in follicular lymphoma while large pooled analyses showing HLA class III (e.g
TNF-alpha and LTA) essential in DLBCL etiology. Future meta-analyses of
GWAS data may provide more robust results. Coupled with ongoing agnostic
approaches in discovery of novel risk alleles, parallel efforts of a priori regions,
94

such as HLA regions, is warranted. Potential interactions of loci in HLA regions
with environmental factors in NHL risk may also provide insight into the
biologically relevant pathways.

95

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101

Chapter 6. Household Endotoxin Levels and Risk of
Non-Hodgkin Lymphoma

Abstract
Endotoxin, a component of the outer membrane of gram-negative bacteria, is
common in the indoor environment. It elicits a strong innate and inflammatory
immune response associated with secretion of pro-inflammatory cytokines,
including tumor necrosis factor-alpha (TNF-α). Because TNF-α polymorphisms
that increase TNF-α production are associated with an increased risk of non-
Hodgkin lymphoma (NHL), we hypothesized that increased levels of household
endotoxin are associated with an increased NHL risk. We evaluated the
association between household endotoxin levels and NHL risk in the National
Cancer Institute/Surveillance, Epidemiology and End Result (NCI/SEER) NHL
multi-center population-based case-control study. Used vacuum cleaner bags
were collected from participants during a home interview. Dust samples from the
bags of 594 cases and 442 controls were analyzed for endotoxin using the
kinetic chromogenic Limulus amebocyte lysate assay. Multivariable logistic
regression was used to estimate the effect of endotoxin on NHL risk adjusted for
age, sex, race, education, study center, and farming status. Endotoxin was not
associated with NHL overall (odds ratio [OR] per Ln(Endotoxin) Unit [EU]/mg of
dust= 0.96, 95% confidence interval [CI] = 0.83-1.11), or with diffuse large B-cell
lymphoma (OR= 0.93, 95% CI= 0.75, 1.16) or follicular lymphoma (OR= 0.99, 95%
102

CI=0.79, 1.24) subtypes. Both working and living on a farm were associated with
higher household endotoxin levels compared to never working (P=0.009) and
never living (P=0.01) on a farm. Excluding farmers from the main effects
analysis did not change the results. We found no evidence of a role for
household endotoxin in NHL etiology.

Introduction
Non-Hodgkin lymphoma (NHL) is a highly heterogeneous group of tumors
composed of B or T lymphocytes at various stages of development. The
incidence of NHL in the U.S. doubled between 1970 and 1990 but has stabilized
since the 1990s (Morton et al., 2006). The etiology of NHL is not fully understood
but altered immunity, especially acquired or inherited severe immune
suppression, is an accepted risk factor (Grulich AE, Vajdic CM, & Cozen W,
2007). In a large pooled analysis study of over 11,000 NHL patients and almost
12,000 controls, a functional polymorphism in the gene encoding for TNF-α,
associated with increased TNF-α secretion, was associated with a 13%
increased risk of NHL overall and a 29% increased risk of diffuse large B-cell
lymphoma (DLBCL) (Skibola CF et al., ; Skibola CF, Curry JD, & Nieters A,
2007).
Endotoxin is a component of the outer membrane of gram-negative
bacteria. It is common in the indoor environment and is principally associated
103

with cigarette smoke, crowding, pets, household cleanliness, and geography in
relation to the use of certain types of air conditioners and heating devices
(Thorne PS, Cohn RD, Mav D, Arbes SJ, & Zeldin DC, 2009). Endotoxin is a
protective factor for allergy (Basinas et al.), which is in turn a protective factor for
NHL (Vajdic et al., 2009). Farming is associated with very high occupational
exposures to endotoxin, and farm homes also have higher levels of endotoxin
than non-farm homes (Thorne PS & Duchaine C, 2007). Exposures related to
farming are suspected risk factors for NHL (Grulich & Vajdic, 2005). In a multi-
center population-based case control study, we found that specific types of
farming exposures, especially those related to animal process, were associated
with an increased risk of NHL (Schenk et al., 2009).
Endotoxin induces B-cell activation through a variety of pathways including
stimulation of TNF-α production in monocytes and macrophages (Morrison &
Ryan, 1987), although there is individual variation (Mozes et al.). In a
comprehensive literature review, Lundin and Checkoway found evidence of a
strong and consistent inverse association between endotoxin exposure and lung
cancer risk that was dose dependent, along with provocative evidence that risks
for other cancers may be similarly reduced (Lundin JI & Checkoway H, 2009).
However, we hypothesized that endotoxin might increase the risk of NHL
because of its capacity to induce TNF-α secretion (Kehrl, Miller, & Fauci, 1987)
and B-cell stimulation (the cell of origin of the majority of lymphomas). We
104

evaluated the association between endotoxin exposure and NHL risk in a multi-
center case-control study designed to evaluate multiple NHL risk factors.

Methods
Study Population and Self-Reported Exposures
The study design has been reported in detail elsewhere (Colt JS et al., 2006;
Cozen W et al., 2007). In brief, we conducted a population-based case-control
study in four areas covered by Surveillance, Epidemiology and End Results
(SEER) cancer registries: Detroit, Iowa, Los Angeles and Seattle. Eligible case
patients were aged 20-74 years when newly diagnosed with NHL between July 1,

1998 and June 30, 2000. All cases were histologically confirmed and coded at
each participating SEER registry according to the International Classification of
Diseases – Oncology, 2
nd
edition and updated to the 3
rd
edition (Fritz A et al.,
2000; Percy C, van Holten V, & Muir C, 1990). Controls were selected from the
general population, and random digit dialing was used to identify potential control
participants under age 65 years and Center for Medicare and Medicaid Services
files were used to identify potential control participants 65 years of age or older.
Controls had no NHL diagnosis and were frequency-matched to cases by age (in
five-year age groups), sex, race/ethnicity, and study center. Overall response
rates were 59% for cases and 44% for controls, resulting in 1,321 cases and
1,057 controls enrolled in the parent study. All participants signed a written
105

informed consent approved by the human subjects review board of each
participating institution according to the Declaration of Helsinki in 1964 and
modified in 2004.
Trained interviewers conducted a computer-assisted personal interview in
each participant’s home. A core set of questions administered to all participants
ascertained information about demographics, height and weight, pesticide use,
occupational history, hair dye use, number of siblings and birth order.
Participants were also asked about whether they ever lived or worked on a farm
and the number of years they lived on a farm.

Endotoxin Assessment
We took advantage of household dust collection for a sub-study with the
objective to assess the association between organochlorine compounds,
including organochlorine pesticides and PCBs, and NHL risk (Colt JS et al.,
2005). Details of household dust collection, shipment, processing and storage
are presented elsewhere (Colt JS et al., 2005). Briefly, during the in-person
interview, permission to remove the used bag from the household vacuum
cleaner was obtained from participants who had possessed at least half of their
carpets or rugs for 5 years or more (to avoid situations in which dust samples
reflect only recent exposures that are unlikely to be etiologically relevant) and
who had used their vacuum cleaner on these carpets or rugs within the past year
(Colt JS et al., 2005). Out of 1,233 cases and 1,004 controls who gave
106

permission, 695 cases and 521 controls were eligible for dust collection (Colt JS
et al., 2006). Some participants with dust samples had insufficient dust
remaining for this analysis as a result of previous analyses for organochlorine
compounds and a small number of bags were lost during shipping, resulting in
618 cases and 460 controls providing vacuum cleaner bags with dust from which
endotoxin levels were successfully measured. Because response rates were
extremely low among Hispanics (Shen M et al., 2008), dust samples from this
group were excluded, leaving 594 cases and 443 controls samples for this
analysis.
Dust samples were sent to the University of Iowa to be analyzed at the
Pulmonary Toxicology Facility (PTF). The details of the endotoxin protocol have
been reported elsewhere (Thorne PS, 2000; Thorne PS et al., 2009; Vojta PJ et
al., 2002). Briefly, dust was sieved (425 μm), aliquoted into 100-mg lots, and
frozen at –80°C. A 50-mg subsample of each dust sample was extracted with
1.0 ml pyrogen-free water containing 0.05% Tween-20 and analyzed for
endotoxin using a modification of the kinetic chromogenic Limulus amebocyte
lysate assay with a 12-point standard curve. Five blank wells were included as
negative controls for the purpose of quality control. Approximately 10% of the
samples were selected randomly for a blinded replication and the Pearson’s
correlation coefficient between samples analyzed from two different aliquots was
0.89. We also examined the geometric mean and standard deviation of
107

endotoxin levels among controls by assay batch using analysis of variance, and
found that endotoxin levels did not significantly differ (P=0.60).

Statistical Analysis
To evaluate potential selection bias, sociodemographic characteristics were
compared between cases with and without endotoxin measurements, and the
same comparisons were done between controls with and without endotoxin
measurement. Because farming exposures (occupational/residential) are
associated with increased levels of endotoxin (Thorne PS & Duchaine C, 2007)
and are suspected risk factors of NHL (Grulich & Vajdic, 2005), we also
evaluated whether farming exposures were different between cases with and
without endotoxin measurement, and between controls with and without
measurement. In our study population with endotoxin measurements,
sociodemographic characteristics, farming exposures (occupational/residential)
and vacuuming behavior were compared in cases and controls using either
independent t-tests (for continuous variables) or Pearson’s chi-squared tests (for
proportions). Because the distribution of endotoxin concentrations in dust was
log normal, the geometric mean and geometric standard deviation were used to
indicate central tendency and variability. A two-factor analysis of variance was
applied to test whether log-transformed endotoxin levels differed by case-control
status or by socio-demographic factors (e.g. sex, race/ethnic, or study center),
and whether there was an interaction between case-control status and the
108

demographic characteristic. One control subject with extremely high endotoxin
levels was excluded from the analysis due to likely sampling error (e.g., bacterial
growth in the vacuum bag), leaving 594 cases and 442 controls for this analysis.
Unconditional multivariable logistic regression was used to estimate odds
ratios (OR) and 95% confidence intervals (CI) as a measure of association
between endotoxin levels considered as a continuous measure (per unit change
in Ln(endotoxin) EU/mg) and risk of NHL. In order to examine a possible
threshold effect, endotoxin concentrations among controls were categorized into
tertiles, with the highest tertile further split into two equal groups and proportions
compared in cases and controls. Median endotoxin concentrations in controls
within each endotoxin category were used to conduct tests for linear trend. The
analysis was adjusted for age (<45, 45-54, 55-64, ≥65 years), sex, education
(≤12, 13-15, ≥16 years), race (white, black, Asian or other), farming occupation
(current, former and never), and study center (Detroit, Iowa, Seattle, and Los
Angeles). Additional potential confounders (e.g., smoking (Thorne PS et al.,
2009), allergy/asthma (Basinas et al., ; Thorne et al., 2005), occupational and
residential farming (Thorne PS & Duchaine C, 2007) were considered by
assessing whether their inclusion changed the association with endotoxin
exposure by at least 10%; only occupational farming and frequency-matched
variables were retained in the model. The effect of season of dust collection on
endotoxin levels was also examined as there can be seasonal differences in
household levels (Abraham JH et al., 2005; Hyvarinen A et al., 2006). The
109

association between endotoxin and NHL risk was examined separately by sex,
study site and major histological subtype (first for all NHL subtypes combined,
and then separately for DLBCL and follicular lymphoma). Endotoxin levels were
assessed in cases and controls exposed and unexposed to farming. The
associations were examined again excluding participants who had ever lived or
worked on a farm to circumvent confounding by this exposure. Statistical
significance was defined as having a P less than 5% for a two-sided hypothesis.
All statistical analyses were conducted using the SAS Version 9.0 (SAS Institute,
Inc., Cary, NC) statistical software package.

Results
Cases and controls with endotoxin measurements were older and more likely to
be white than cases and controls without measurements (Supplementary Table
6.1). Seattle and Iowa had the highest proportion of eligible cases and controls,
respectively; Detroit had the lowest. There was no evidence of an effect of
season of specimen collection on endotoxin levels (data not shown). Controls
with endotoxin measurements included in this sub-study were more likely to be
current farmers (4.5%) or to have lived on a farm (40.7%) than controls without
measurements (1.8% and 34.1%, respectively); there were no such differences
for cases.

110
Supplementary Table 6.1. Comparison of participants with and without endotoxin measurements, by
case-control status

Cases Controls

Endotoxin
measurement
(N=594)
No endotoxin
measurement
(N=727) P

Endotoxin
measurement
(N=442)
No endotoxin
measurement
(N=615) P
Age (years)

<0.0001

<0.0001
<45 75 (12.6) 172 (23.7)

44 (9.9) 118 (19.2)

45-54 126 (21.2) 163 (22.4)

73 (16.5) 123 (20.0)

55-64 165 (27.8) 185 (25.4)

101 (22.9) 152 (24.7)

≥65 228 (38.4) 207 (28.5)

224 (50.7) 222 (36.1)

Mean age (years) 58.8 ± 11.3 54.5 ± 13.2 <0.0001

60.6 ± 10.8 56.4 ± 13.1 <0.0001

Sex

0.89

0.83
Male 321 (54.0) 390 (53.7)

230 (52.0) 316 (51.4)

Female 273 (46.0) 337 (46.3)

212 (48.0) 299 (48.6)

Race/Ethnicity
Non-Hispanic white 531 (89.4) 547 (75.2)

389 (88.0) 426 (69.3)

African Americans 36 (6.1) 74 (10.2)

38 (8.6) 113 (18.4)

Others 27 (4.6) 106 (14.6)

15 (3.4) 76 (12.3)

Education (years)
1

0.59

0.81
≤12 223 (37.5) 284 (39.1)

164 (36.9) 231 (37.6)

13-15 205 (34.5) 231 (31.8)

143 (32.6) 189 (30.7)

≥16 166 (28.0) 211 (29.1)

135 (30.5) 195 (31.7)

111
Supplementary Table 6.1, continued

Cases Controls

Endotoxin
measurement
(N=594)
No endotoxin
measurement
(N=727) P

Endotoxin
measurement
(N=442)
No endotoxin
measurement
(N=615) P
Study Centers <0.0001 <0.0001
Detroit 113 (19.0) 206 (28.3)

57 (12.9) 157 (25.5)

Iowa 175 (29.5) 186 (25.6)

135 (30.5) 141 (22.9)

Los Angeles 133 (22.4) 186 (25.6)

107 (24.2) 166 (27.0)

Seattle 173 (29.1) 149 (20.5)

143 (32.4) 151 (24.6)

Occupational farming
1

0.43

0.02
Never 536 (90.5) 669 (92.3)

393 (88.9) 570 (93.1)

Former 42 (7.1) 39 (5.4)

29 (6.6) 31 (5.1)

Current 14 (2.4) 17 (2.3)

20 (4.5) 11 (1.8)

Ever lived on a farm

0.24

0.03
No 382 (64.3) 490 (67.4)

262 (59.3) 405 (65.9)

Yes 212 (35.7) 237 (32.6)

180 (40.7) 210 (34.1)

Histology

0.62

Follicular 137 (23.1) 181 (24.9)

DLBCL 182 (30.6) 235 (32.3)

T-cell 40 (6.7) 42 (5.8)

Others/Unknown 235 (39.6) 269 (37.0)

1
Total may vary due to missing values.
112

Cases were, on average, almost 2 years younger than controls (P= 0.008).
Controls were more likely to live or work on a farm, formerly or currently, and for
a longer time (>10 years, P=0.03) than cases (Table 6.1). Endotoxin levels
ranged from 1.5 EU/mg to 1011.1 EU/mg in our samples; median levels in cases
and controls were 60.7 EU/mg and 62.6 EU/mg, respectively.

Table 6.1. Characteristics of cases and controls
1

Cases Control
P N=594 N=442
Mean Age (years) 58.8 ± 11.3 60.6 ± 10.8 0.008

Age (years)

0.001
<45 75 (12.6) 44 (9.9)

45-54 126 (21.2) 73 (16.5)

55-64 165 (27.8) 101 (22.9)

≥65 228 (38.4) 224 (50.7)

Sex

0.52
Male 321 (54.0) 230 (52.0)

Female 273 (46.0) 212 (48.0)

Race/Ethnicity

0.21
Non-Hispanic White 531 (89.4) 389 (88.0)

African American 36 (6.1) 38 (8.6)

Others 27 (4.6) 15 (3.4)

Study Centers

0.07
Detroit 113 (19.0) 57 (12.9)

Iowa 175 (29.5) 135 (30.5)

Los Angeles 133 (22.4) 107 (24.2)

Seattle 173 (29.1) 143 (32.4)

113

Table 6.1, continued

Cases Control P

N=594 N=442

Education (years)

0.64
≤12 223 (37.5) 164 (36.9)

13-15 205 (34.5) 143 (32.6)

≥16 166 (28.0) 135 (30.5)

Occupational farming b

0.15
Never 536 (90.5) 393 (88.9)

Former 42 (7.1) 29 (6.6)

Current 14 (2.4) 20 (4.5)

Years lived on a farm

0.03
Never 382 (64.4) 262 (59.3)

0-5 60 (10.1) 37 (8.4)

6-10 27 (4.6) 16 (3.6)

>10 124 (20.9) 127 (28.7)

Histology

Follicular 137 (23.1)

DLBCL 182 (30.6)

T-cell 40 (6.7)

Others/Unknown 235 (39.6)

Last change of vacuum cleaner bag
2

0.66
< 1 month 220 (37.5) 152 (35.0)

1 month ≤ range < 6 months 305 (52.0) 238(54.8)

≥ 6 months 62 (10.6) 44 (10.1)

Last use of vacuum cleaner

0.92
<1 week 429 (72.2) 322 (72.8)

1 week ≤ range < 1 month 142 (23.9) 105 (23.8)

≥ 1 month 23 (3.9) 15 (3.4)

1
Mean (SD) was presented for continuous variable and N (%) for categorical variables.
2
Total may vary due to missing values.

As expected (Thorne PS & Duchaine C, 2007), both working and living on
a farm were associated with higher household endotoxin levels compared to
114

never working (P=0.009) and never living (P=0.01) on a farm (Supplementary
Table 6.2), with the highest levels observed among current farmers. Endotoxin
levels were significantly different across the four study centers (P<0.0001) with
Seattle homes having the highest levels for both cases and controls
(Supplementary Table 6.2). Overall, there was no significant difference in
geometric mean endotoxin levels between cases and controls (P=0.38,
Supplementary Table 6.2).

115

Supplementary Table 6.2. Comparisons of Ln(endotoxin) levels (EU/mg) by case-
control status and sociodemographic characteristics
1

Cases

N=594
Controls

N=442
Ca v. Co Characteristic
variable
P
2
P
3

All participants 58.9 (2.4) 61.8 (2.4) 0.38

Sex

0.41 0.21

Males 56.7 (2.2) 60.3 (2.5)

Females 61.7 (2.6) 63.6 (2.3)

Race/ethnicity

0.36 0.84
Non-Hispanic Whites 59.4 (2.4) 62.0 (2.3)

African Americans 57.5 (2.5) 56.6 (3.1)

Asian/Other/Unknowns 52.7 (2.5) 70.7 (2.5)

Study center

0.79 <0.0001
Detroit 45.8 (2.5) 43.1 (2.6)

Iowa 57.0 (2.3) 64.9 (2.1)

Los Angeles 53.4 (2.5) 55.3 (2.6)

Seattle 77.7 (2.3) 74.1 (2.2)

Farming status

0.67 0.009
Never farmer 57.1 (2.4) 60.6 (2.4)

Former farmer 72.0 (2.0) 64.9 (2.4)

Current farmer 95.8 (2.3) 85.7 (2.4)

Lived on a farm

0.84 0.01
Never 54.9 (2.5) 58.2 (2.3)

Lived on a farm

>0-5 years 73.2 (2.2) 73.4 (2.8)

6-10 years 75.5 (2.2) 73.0 (3.0)

>10 years 62.6 (2.2) 65.3 (2.2)

1
Geometric mean (geometric standard deviation) is presented.
2
P-value tested difference in endotoxin levels by case-control status.
3
P-values tested for difference in endotoxin levels by the variable.
2,3
P-values obtained by two-factor analysis of variance.

116

No association was found between endotoxin levels and NHL, DLBCL or
follicular lymphoma risk when endotoxin was modeled as either a continuous
(Table 6.2) or categorical variable (Table 6.3). Exclusion of participants who had
ever lived or worked on a farm did not alter the results (Tables 6.2 and 6.3).
There were no major differences in risk between males and females (data not
shown). When stratified by study center, a non-significant 18% decreased risk
per 1 unit increase in Ln(endotoxin) level was observed in Iowa (OR = 0.82, 95%
CI = 0.60-1.11, data not shown), but not in the other centers (non-significant
OR’s from 0.92-1.10). The decrease in risk persisted in Iowa when participants
exposed to farming by occupation or residence were excluded (OR =0.71, 95%
CI=0.40-1.25).

117

Table 6.2. Endotoxin levels in carpet dust and risk of NHL, DLBCL, and Follicular lymphoma, with endotoxin levels
modeled as a continuous variable

Controls All NHL cases DLBCL Cases Follicular Cases
N N OR (95% CI) N OR (95% CI) N OR (95%CI)

All Participants
1,2

442 594 0.96 (0.83, 1.11) 182 0.93 (0.75, 1.16) 137 0.99 (0.79, 1.24)

Excluding Participants Who Ever Lived or Worked on a Farm
2,3

261 377 0.94 (0.78, 1.14) 121 0.95 (0.72, 1.26) 82 1.00 (0.73, 1.35)

1
Adjusted for age (<45, 45-54, 55-64, ≥65), sex, race/ethnicity (non-Hispanic white, African American, others), education (≤12, 13-15, ≥16), study center
(Seattle/Detroit/Iowa/Los Angeles), and farming occupation status (never/former/current).
2
Adjusted for age (<45, 45-54, 55-64, ≥65), sex, race/ethnicity (non-Hispanic white, African American, others), education (≤12, 13-15, ≥16), and study
center (Seattle/Detroit/Iowa/Los Angeles).

3
Natural log transformed values were used (OR presented as per unit Ln(endotoxin)).

118

Table 6.3. Endotoxin levels in carpet dust and risk of NHL, DLBCL, and Follicular lymphoma, with endotoxin
levels modeled as a categorical variable

Controls All NHL cases

DLBCL Cases

Follicular Cases
Endotoxin (EU/mg) N

N OR (95% CI)
1

N OR (95% CI)
1

N OR (95% CI)
1

<47.08 147

220 1

65 1

53 1
≥47.08 and <90.47 147

194 0.89 (0.66, 1.22)

58 0.85 (0.54, 1.32)

38 0.74 (0.45, 1.22)
≥90.47 and <140.11 74

95 0.94 (0.64, 1.37)

38 1.24 (0.74, 2.09)

18 0.73 (0.39, 1.36)
≥140.11 74

85 0.81 (0.55, 1.20)

21 0.63 (0.34, 1.16)

28 1.07 (0.61, 1.89)
P for trend 0.35 0.31 0.73
Excluding Participants Who Ever Lived or Worked on a Farm

<47.08 93

115 1

49 1

33 1
≥47.08 and <90.47 90

114 0.77 (0.52, 1.14)

36 0.73 (0.42, 1.27)

22 0.68 (0.36, 1.30)
≥90.47 and <140.11 41

60 0.98 (0.60, 1.61)

22 1.15 (0.59, 1.26)

12 0.90 (0.40, 2.01)
≥140.11 37

48 0.83 (0.49, 1.40)

14 0.80 (0.37, 1.71)

15 1.19 (0.55, 2.56)
P for trend 0.65 0.83 0.53

1
Adjusted for age (<45, 45-54, 55-64, ≥65), sex, race/ethnicity (non-Hispanic white, African American, others), education (≤12, 13-15, ≥16), study
center (Seattle/Detroit/Iowa/Los Angeles), and (for first set of results only) farming occupation status (never/former/current).
119

Discussion
This is the first epidemiologic study to investigate the association between
measured levels of endotoxin in households and NHL risk. Because endotoxin
stimulates B-cell activity, via an increase in TNFα and other cytokines (Morrison
& Ryan, 1987), and B-cell activation is a presumed risk factor for NHL (Purdue et
al., ; Skibola CF et al., ; Skibola CF et al., 2007), we expected that endotoxin
exposure would also increase NHL risk. Instead, we observed no association
between home dust endotoxin levels and risk of all subtypes of NHL combined,
DLBCL, or follicular lymphoma. There are several possible reasons for our null
finding. Endotoxin levels in house dust do not reflect exposures in the workplace,
which are likely important sources of endotoxin exposure (Basinas et al.). In
addition, the response of lymphocytes and macrophages to endotoxin is variable
and depends on host factors, such as age, that affect the ability of endotoxin to
activate B-cells (Frasca et al., ; Mozes et al.).
We found the highest levels of endotoxin in homes in Seattle and the
lowest in Detroit. The reason for this difference by study center is not known.
The comparatively moist weather in Seattle relative to the other centers probably
does not account for the higher endotoxin levels since outdoor moisture is not a
significant predictor of endotoxin levels (Thorne PS et al., 2009). Another
possible explanation for the difference is endotoxin exposure from dogs, since
dog ownership has been associated with higher home endotoxin levels
(McConnell R et al., 2006), and Washington state has the highest prevalence of
120

households with dogs compared to the other study center locations (US Pet
Ownership & Demographic Sourcebook, 2007, www.avma.org) (information on
dog ownership was not collected in our study). The geometric mean (GM)
household endotoxin concentration of 61.8 EU/mg in our study is comparable
with the value for family room floors in the National Survey of Endotoxin in U.S.
Housing (GM=71.1 EU/mg; 95% CI=64.3-78.7 EU/mg) (Thorne PS et al., 2009).
Samples from both studies were analyzed in the same laboratory according to
the same protocol but comparisons are difficult to make because we used dust
collected from participants’ vacuum cleaner bags in a cross-sectional sampling
and the National Survey used room-specific dust collected from a designated
area into sampling thimbles by field technicians.
There was a weak inverse association among cases and controls in Iowa,
where 94% of the current and 73% of the former farmers were located. Dust
endotoxin levels were higher among both cases and controls exposed to farming.
However, farmers were over-represented in the study as a whole and among
eligible controls compared to cases (Supplementary Table 1). Nevertheless,
results were unchanged when lifetime farmers were excluded from the analysis
restricted to Iowa, and from the analysis for the combined study centers, so it is
unlikely that this potential confounder actually biased the results.
The strengths of our study include gold standard laboratory methods for
measuring endotoxin levels in dust by the group that performed the only US
nationwide study (Thorne PS et al., 2009; Thorne PS & Duchaine C, 2007;
121

Thorne PS et al., 2005), a population-based ascertainment of participants, and a
relatively large sample size. However, our study has several limitations. We
used a single measurement of endotoxin using dust collected from vacuum
cleaner bags. From contemporaneous sampling in five locations within
households, Thorne et al. (Thorne PS et al., 2005) demonstrated low correlations
for paired samples, with Pearson correlation coefficients ranging from 0.12 to
0.44 (N=2,469); thus reproducibility could be poor and misclassification
introduced. However, because we did not specify the locations (e.g. living room,
kitchen, or bedroom) where vacuum cleaners were used, endotoxin levels
measured from dust in vacuum cleaner bags may represent an integrated
measurement representative of the entire home, which could be less subject to
measurement variability due to different sampling locations. A single sampling
may be used as a reasonable proxy to reflect about 1-year household endotoxin
exposure (Abraham JH et al., 2005; Heinrich et al., 2003) while it may fail to
reflect long-term exposure (e.g. up to 6 years) (Topp et al., 2003). Thus, a single
measurement would be an invalid measure of historical exposure if endotoxin
levels changed over time. Dust samples were collected from NHL cases after
diagnosis, and it is possible that disease led to changes in lifestyle that, in turn,
led to changes in household endotoxin levels. We tried to minimize these
potential problems by limiting the dust analysis to people who had owned their
carpets or rugs for at least 5 years. Seasonal variation in endotoxin
concentrations sampled from dust has also been reported (Abraham JH et al.,
122

2005; Hyvarinen A et al., 2006), but we found no evidence of an effect of season
of specimen collection on endotoxin levels in our study. As above, the lack of
information on occupational endotoxin exposure could have led to null results via
nondifferential misclassification, however the majority of the jobs listed in our
questionnaires are not significantly linked to endotoxin exposure, and thus it was
not possible to correct for occupationally related endotoxin exposure.
In summary, we did not find an association between endotoxin levels in
carpet dust measured at the time of diagnosis and risk of NHL. Cohort studies
with pre-diagnosis dust specimens, multiple longitudinal measurements and
detailed residential and occupational histories may help to clarify the relationship.

Acknowledgements
This study was supported by the National Cancer Institute Division of Cancer
Epidemiology and Genetics and the Surveillance, Epidemiology and End Results
Program under contracts N01-PC-35139, N01 PC065064, NO1-PC-67008, N01-
PC-71105, and N01-PC67009 awarded to the University of Southern California,
Wayne State University, University of Washington and Mayo Clinic. This study
was also supported by grants P01 CA17054, P30 ES07048, and the Norris
Comprehensive Cancer Center Support Grant P30 CA014089, funded by the
National Cancer Institute from the National Institutes of Health awarded to the
University of Southern California. Additional funding from NIEHS supported
123

exposure assessment at the University of Iowa (P30 ES005605). The collection
of cancer incidence data in Los Angeles County was supported by the California
Department of Health Services as part of the statewide cancer reporting program
mandated by California Health and Safety Code Section 103885 and the Centers
for Disease Control and Prevention's National Program of Cancer Registries,
under agreement #U55/CCR921930-02 awarded to the Public Health Institute.
The ideas and opinions expressed herein are those of the authors and
endorsement by the State of California, Department of Health Services, the
National Cancer Institute, and the Centers for Disease Control and Prevention or
their Contractors and Subcontractors is not intended nor should be inferred.
124

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127

Chapter 7. Common Immune-related Factors and Risk of
Non-Hodgkin Lymphoma in Twins

Abstract
Some common immune-related diseases or conditions, such as atopic disease or
early life infections, have been suggested to affect NHL risk. We evaluated
common immune-altering factors in a case-control study involving twin pairs
discordant for NHL. One hundred sixty two like-sexed NHL-discordant twin pairs
were identified from the International Twin Study. History of infectious disease
(e.g. IM) or surgical conditions associated with infection (e.g., tonsillectomy or
appendectomy), behaviors associated with risk of infection in early life and
history of atopic diseases was ascertained through a standardized questionnaire
mailed to each twin of the pair. Conditional logistic regression was used to
compute odds ratios along with 95% confidence intervals. A strong inverse
association between atopic disease, especially seasonal hay fever (OR = 0.28,
95%CI = 0.10-0.75) or allergy to specific substance (OR = 0.29, 95%CI = 0.13-
0.68), and NHL risk was observed. An increasing number of different types of
atopic disease was significantly associated with decreased NHL risk (P trend =
0.0003). A history of IM was inversely associated with NHL risk (OR = 0.35,
95%CI = 0.14-0.90). An increase in behavioral exposures linked to risk of
infection during early life was significantly associated with increased NHL risk (P
trend = 0.04). Stratified analysis by sex did not show substantial difference
128

between male-male and female-female NHL-discordant pairs. However,
stratified analysis by zygosity showed an even stronger inverse association
between atopic disease and NHL risk among DZ twins than MZ twins. Our
observations support that common immune-related diseases, especially atopic
disease may also contribute to NHL development.

Introduction
Primary, acquired or iatrogenic immunodeficiency is the strongest known risk
factor for non-Hodgkin lymphoma (NHL). An estimated 25% of patients with a
primary immunodeficiency will develop lymphoma (Filipovich et al., 1992). Prior
to the introduction of highly active retroviral therapy (HAART), HIV/AIDS patients
had a relative risk for NHL of up to 77. However, diseases associated with more
modest immune alterations, such as autoimmune disease, atopic conditions and
chronic infections, may also affect NHL risk. A decreased risk associated with
atopic diseases is suggested by case-control studies although generally not
supported in longitudinal studies (Martínez-Maza et al.). In a recent pooled
analysis involving 13 case-control studies and over 13,000 cases and 16,000
controls, a modest but statistically significant 20% inverse association with hay
fever and other allergies was found (Vajdic et al., 2009). Various mechanisms
have been proposed to explain an etiologic effect on NHL risk (Martínez-Maza et
al.) but an alternative hypothesis is that NHL itself affects immunoglobulin (Ig)
129

production and therefore expression of the allergic phenotype, supported by the
fact that IgE levels are inversely correlated with stage (Ellison-Loschmann et al.,
2007). In addition, a small nested case-control study showed that IgE levels
were initially similar in pregnant women who did and did not develop NHL, but
that levels in the cases decreased steadily as the diagnosis date approached
(Melbye et al., 2007). Data in support of an etiologic effect include reports of a
similar inverse association with glioma and pancreas cancer (Turner, ; Turner et
al., 2006), malignancies derived from cells other than B-lymphocytes and
therefore not subject to the same possible disease effect.
Early life immune-related exposures, including early contact with other
children and exposure to infections, are known to affect immune function
(Strachan, 1989, 2000; Wills-Karp et al., 2001) and may also affect lymphoma
risk in later life. Family size and birth order are surrogates for early childhood
exposure to microbes (Gutensohn & Cole, 1981). Some studies have reported a
positive association between family size, birth order and NHL (Cozen et al., 2007;
Grulich et al., 2005; Holly et al., 1999; Smedby et al., 2007), although an
InterLymph pooled study analysis found an association between late birth order
and risk only in the top socioeconomic status suggesting that selection bias could
explain these associations (Grulich et al.). Alternatively, infection in early life
could be a consequence of a subtle immunodeficiency. Support for this
hypothesis was demonstrated by a cohort study of infants in Israel in which those
that were hospitalized with an infection in the first year of life had a 2.5-fold
130

increased risk of NHL by age 40 (Paltiel et al., 2006); the results were confirmed
in a Swedish population (Goldin, Landgren, Kristinsson, Bjorkholm, & Paltiel).
The majority of the evidence for an association between common
immune-related disease and NHL risk is based upon results from standard case-
control studies. However, genes encoding proteins that regulate the immune
response have been implicated as risk factors of NHL (Skibola et al., 2007).
Twins discordant for NHL are an ideal population in which to study immune-
related risk factors because they are matched on family structure and partially or
wholly matched on genome, and they can recall differences in early life
experiences having been compared all their lives. We therefore conducted a
matched case-control study of early life and immune-related risk factors in twin
pairs discordant for NHL.

Methods
Study Population
Twin pairs were ascertained from the volunteer-based International Twin Registry
(ITS) , a registry of twins with cancer or other chronic diseases recruited via
advertisement in newspaper or magazines throughout North America from 1980
to 1991 (Mack, Deapen, & Hamilton, 2000). A 35-page questionnaire was mailed
to at least one member of two hundred and seventy-nine twin pairs discordant for
NHL in whom at least one member was living. Twin pairs in whom both
131

members were living were asked to complete the questionnaire independently.
Completed questionnaires were received from both members of 76 twin pairs
(double respondent pairs) and from one member of 124 twin pairs (single
respondent pairs) (response rate = 72%). The study was limited to the
responses from 162 like-sexed pairs (64 single and 98 double respondent pairs)
to minimize confounding by sex. The majority (81%) of the single respondents
were unaffected co-twins of NHL cases deceased at the time of study contact.
Pathology reports and histopathologic slides were requested and reviewed for
230 case-twins by a single pathologist (B.N.N) and the diagnosis of NHL was
confirmed in 227 using the accepted NHL classification of the period
(International Working Formulation). There was not enough information on the
additional three cases for a definitive diagnosis. The study was approved by the
Institutional Review Board of the Keck School of Medicine of the University of
Southern California and all subjects provided signed written informed consent.

Exposure Assessment
A wide range of exposures were covered in the questionnaire, including
demographic information, weight and height at different ages, behaviors
associated with risk of infection in childhood, infectious diseases, medical and
pharmacologic history, reproductive history, occupational history, and tobacco
and alcohol history. A subset of questions used a reference date which was set
132

as 5 years prior to diagnosis of case twin. We excluded exposures with fewer
than 19 discordant pairs (i.e. case more or twin more). Exposures that met this
criteria included medical or surgical conditions associated with infection (e.g.
infectious mononucleosis, tonsillectomy, appendectomy), behaviors associated
with risk of infection in early life, and lifetime history of atopic diseases.
Comparisons of immune-related medical history or surgery were made
using absolute comparisons with dichotomous yes/no answers. Twins were
asked to respond about their twins’ experiences as well as their own (e.g. “Did
you have a tonsillectomy?” and “Did your twin have a tonsillectomy?”).
Comparisons of early life risk behaviors were framed as relative questions (e.g.
“Which twin used a pacifier more as an infant and toddler?”). For these
questions, twins were asked to select the following responses: ‘me, much more;
me, more; same; my twin, more; my twin, much more; don’t know’ which were
each collapsed to ‘me more, my twin more, same, don’t know).

Statistical Analysis
For lifetime history of atopic diseases, the reference group was defined as having
none of the following atopic diseases: animal or egg allergy, plant allergy,
seasonal hay fever, other allergies, allergic asthma and eczema. Seasonal hay
fever and eczema were the conditions with sufficient exposure-discordant pairs
to be analyzed separately. In order to evaluate the joint effect of several atopic
diseases, a variable including multiple atopic diseases was generated as follows:
133

no atopic diseases (reference); 1 atopic disease; ≥ 2 atopic diseases. Summary
variables of any allergy (animal or egg allergy, plant allergy, seasonal hay fever
or other allergy) and any atopic disease (any allergy, asthma or eczema) were
generated for this analysis.
Differences in exposures related to opportunities for microbial and
infectious exposures in infancy/toddlerhood and childhood were assessed by
relative comparisons within the twin pair. The twin who reported that he or she
was more exposed than their co-twin was exposed (coded as ‘1’) and other twin
was unexposed (coded as ‘0’). To evaluate the quantitative effect of such
behaviors, a summary variable was generated based on the following seven
behavioral exposure variables: sucked a pacifier/a thumb/fingers more as an
infant/young child, put things into their mouth more as an infant/young child, bit
their nails more as a young child, kissed people more often as a young child, had
more close contact with family pets as a young child, had contact with more
children before age 10, and spent more time with younger children in elementary
school. The reference group consisted of the twin who reported fewer of each of
the behavioral exposures described above. The first, second and third exposure
levels were defined as having any one, two or greater than two behavioral
exposures. Conditional logistic regression was used to estimate odds ratios
(ORs) and 95% confidence interval (95%CI). For double-respondent pairs, self-
reports were used; for single-respondents pairs, proxy responses were used for
the twin who did not respond (usually the deceased case twin). To test whether
134

results from double- and single- respondent pairs were significantly different, an
interaction term of exposure of interest and respondent status (double or single)
was added to the conditional logistic regression. If the test showed no
statistically significant interaction, double- and single- respondent pairs were
pooled together into a single analysis. Otherwise, only results from double-
respondent pairs were reported. Adjustment of known confounders, including
age, sex, race/ethnicity was unnecessary since twins were matched on these
variables. Education was evaluated as a potential confounder in the conditional
logistic regression but it did not change the effect estimate significantly (OR
change less than 10%), so it was not included in the final model.
Results were repeated among MZ twins alone to evaluate whether genetic
effects also contributed to NHL risk. Analyses were also repeated among male-
male and female-female pairs separately. Due to the changing criteria for
diagnosis of NHL and the fact that the case twins were diagnosed primarily in the
1980’s when the International Working Formulation was standard classification
scheme, stratification analysis by histological types is not feasible in our study.

Results
The major difference between double- and single- respondent pairs was the sex
and zygosity distribution (Table 7.1). MZ female-female pairs comprised the
majority of double-respondent pairs, while single-respondent pairs were more
135

evenly distributed among the sex-zygosity categories. Single-respondents
tended to be younger at participation but the distribution of age at diagnosis was
similar between the two types of respondents. Approximately half of the case
twins were diagnosed before 50 years old, compared to the median of 66 in the
general population.

136

Table 7.1. Characteristics of the like-sexed twin pairs discordant for NHL

Double respondent Single respondent Total pairs
Characteristic N % N % N %
Total twin pairs 64 98 162 100
Age at participation
<40 23 35.9 48 49.0 71 44.7
40-49 17 26.6 18 18.4 35 22.0
50-59 14 21.9 24 24.5 38 23.9
>60 10 15.6 8 8.1 18 11.3
Sex
Male-male 13 20.3 50 51.0 63 39.6
Female-female 51 79.7 48 49.0 99 62.3
Age at diagnosis
<40 19 29.7 36 36.7 55 34.6
40-49 12 18.8 19 19.4 31 19.5
50-59 18 28.1 23 23.5 41 25.8
>60 15 23.4 20 20.4 35 22.0
Zygosity
MZ
Male-male 9 14.1 27 27.6 36 22.6
Female-female 31 48.4 22 22.4 53 33.3
DZ
Male-male 3 4.7 20 20.4 23 14.5
Female-female 17 26.6 24 24.5 41 25.8
Unknown 4 6.3 5 5.1 9 5.7
137

Within-pair percentages of agreement among the double-respondent pairs
ranged from 85% to 97% for medical conditions or surgical history with the
highest percentage of agreement seen for a lifetime history of atopic diseases
(data not shown). The percentage of agreement was slightly lower for reports of
early life differences in behaviors associated with risk of infection, ranging from
76% to 96%.
Every measure of atopy was associated with an OR less than 1.0 (Table
7.2). A history of seasonal hay fever, any allergy or any atopic disease was
associated with decreased risk of NHL (OR = 0.28 [95%CI = 0.10-0.75], OR =
0.29 [95%CI = 0.13-0.68], and OR = 0.31 [95%CI = 0.15-0.64] for seasonal hay
fever, any allergy, and any atopic disease respectively, in total twin pairs). The
effect estimates from double-respondent twin pairs were similar to those
observed in all pairs but power was reduced and thus the results were not
statistically significant. Eczema diagnosed least 5 years before NHL diagnosis
decreased NHL risk (OR = 0.36, 95% CI= 0.13-0.99). A history of an increasing
number of atopic diseases was inversely associated with NHL (p-trend = 0.0003
in all twin pairs), with an OR of 0.08 (95%CI = 0.02-0.41) for two or more atopic
diseases relative to none.

138

Table 7.2. Atopic disease
1
and NHL risk in like-sexed twin pairs discordant for NHL

Response status
Exposure
discordant
pairs
5
OR 95%CI P-value
Individual variable
Seasonal hay fever Double 3|7 0.43 0.11-1.66 0.22
Double + single 5|18 0.28 0.10-0.75 0.01

Eczema Double 1|8 0.13 0.02-1.00 0.05
Double + single 5|14 0.36 0.13-0.99 0.05

Summary variable
Any allergy
2
Double 5|9 0.56 0.19-1.66 0.29
Double + single 7|26 0.29 0.13-0.68 0.004

Any atopic disease
3
Double 5|14 0.36 0.13-0.99 0.05
Double + single 10|32 0.31 0.15-0.64 0.001

Multiple atopic diseases
4

In double-respondent pairs
None Ref
1 atopic diseases 0.43 0.15-1.21 0.11
≥ 2 atopic diseases 0.08 0.01-0.75 0.03
P-trend 0.02

In total twin pairs
None Ref
1 atopic diseases 0.37 0.18-0.77 0.01
≥ 2 atopic diseases 0.08 0.02-0.41 0.002
P-trend 0.0003

1
Except eczema which was inquired as diagnosed before reference date, other atopic conditions were
inquired as a lifetime condition.
2
Any specific allergy defined as having any of hay fever, animal or egg allergy, plant allergy, other allergy.
3
Any atopic disease defined as having any of any specific allergy, allergic asthma, and eczema.
4
Multiple atopic diseases defined as having any combination of any allergy, allergic asthma, and eczema.
5
Total number of twin pairs in which case-twin was exposed and the unaffected co-twin was
unexposed/total number of twin pairs in which unaffected co-twin was exposed and the case-twin was
unexposed.

139

Table 7.3 shows the effects of medical conditions or surgeries related to
infections occurring at least 5 years before the case-twins’ diagnosis. A
statistically significant inverse association was observed between infectious
mononucleosis and NHL among both double-respondent and all twin pairs
combined (Table 7.3.). A history of tonsillectomy was associated with a non-
significant 2-fold risk while appendectomy had no effect on NHL risk.

140

Table 7.3. Prior medical conditions or surgical history and NHL risk in like-sexed twin pairs discordant for NHL

Response status
Exposure
discordant pairs
1
OR 95%CI P-value
Infectious mononucleosis Double 4|8 0.50 0.15-1.66 0.26
Double + single 6|17 0.35 0.14-0.90 0.03

Tonsillectomy Double 6|3 2.00 0.50-8.00 0.33
Double + single 13|7 1.86 0.74-4.65 0.19

Appendectomy Double 10|8 1.25 0.49-3.17 0.64
Double + single 22|19 1.16 0.63-2.14 0.64

1
Total number of twin pairs in which case-twin was exposed and the unaffected co-twin was unexposed/total number of twin
pairs in which unaffected co-twin was exposed and the case-twin was unexposed.

141

An increasing number of behaviors associated with opportunities for
infection during childhood was positively associated with an increasing risk of
NHL (p-trend=0.04) (Table 7.4). Specifically, three or more childhood risk
behaviors were associated with an OR of 3.45, although the 95% confidence
intervals included 1.0.

Table 7.4. Behaviors associated with risk of infection in childhood and NHL risk in
double-respondent twin pairs

OR 95%CI P-value
Behavioral exposures associated with risk of infection
1

None 1.00 (Ref)
Any one exposure 1.48 0.65-3.38 0.35
Any two exposure 2.57 0.72-9.09 0.14
≥ 3 exposure 3.45 0.67-17.66 0.14
P-trend 0.04

1
Behavioral exposures include: sucked a pacifier/a thumb/fingers more as an infant/young child, put things
into their mouth more as an infant/young child, bit their nails more as a young child, kissed people more
often as a young child, more close contact with family pets as a young child, contacted with more children
before age 10, and spent more time with younger children in grammar school.

Effect estimates for eczema, seasonal hay fever, a lifetime history of any
allergy or any atopic disease and childhood behavioral exposures associated
with risk of infection were consistent in both MZ and like-sex DZ twin pairs,
however the magnitude of the ORs was stronger in DZ compared to MZ twins
(Supplementary Table 7.1). No substantial difference was observed when
models were stratified by sex (male-male vs. female-female twin pairs, data not
shown).

142 Supplementary Table 7.1. Results of significant exposures for risk of NHL in MZ twin pairs and like-sexed DZ
twin pairs

MZ twin pairs DZ twin pairs

Response
status
Exposure
discordant
pairs
4
OR 95%CI P-value

Exposure
discordant
pairs
4
OR 95%CI P-value
Infectious
mononucleosis Double 2|7 0.29 0.06-1.38 0.12

2|1 2.00 0.18-22.06 0.57

Double + single 3|11 0.27 0.08-0.98 0.05

2|6 0.33 0.07-1.65 0.18

Eczema Double 1|3 0.33 0.04-3.21 0.34

0|5 NA NA NA

Double + single 4|5 0.80 0.21-2.96 0.74

1|9 0.11 0.01-0.88 0.04

Seasonal hay fever Double 3|4 0.75 0.17-3.35 0.71

0|2 NA NA NA

Double + single 4|8 0.50 0.15-1.66 0.26

1|9 0.11 0.01-0.88 0.04

Any allergy
1
Double 4|5 0.80 0.21-2.98 0.74

1|3 0.33 0.03-3.20 0.34

Double + single 5|11 0.45 0.16-1.31 0.14

2|12 0.17 0.04-0.74 0.02

Any atopic disease
2
Double 4|8 0.50 0.15-1.66 0.26

1|5 0.20 0.02-1.71 0.14

Double + single 8|14 0.57 0.24-1.36 0.21

2|17 0.12 0.03-0.51 0.004

1
Any allergy: any of seasonal hay fever, animal or egg allergy, plant allergy, or other allergy.
2
Any atopic disease: any of any allergy, allergic
asthma, or eczema.
3
Behavioral exposures include: sucked a pacifier/a thumb/fingers more as an infant/young child, put things into their
mouth more as infant/young child, bit their nails more as a young child, kissed people more often as a young child, more close contact with family
pets as a young child, contacted with more children before age 10, and spent more time with younger children in grammar school.
4
Total number of
twin pairs in which case-twin was exposed and the unaffected cotwin was unexposed/total number of twin pairs in which unaffected cotwin was
exposed and the case-twin was unexposed.
5
Not applicable.
143

Discussion
We confirmed the inverse association between atopic disease and NHL
suggested by previous case-control studies, however, the magnitude of the ORs
was much stronger in our study. Only one epidemiological study has
investigated the association between immune-related factors and NHL in twins
(Soderberg et al., 2004); this longitudinal study using the Swedish and Finnish
twin cohorts ignored the twin pair status and considered all twins together as one
cohort. They found elevated ORs for hay fever (OR = 1.3, 95% CI = 0.8-2.2) and
eczema (OR = 2.3, 95%CI = 1.0-5.3), based on 22 and 6 exposed cases,
respectively, and 112 NHL cases in total. Another (non-twin) cohort study
generally found a null association (Turner et al., 2005). These two studies
notwithstanding, the inverse association with seasonal hay fever and specific
allergy has generally been consistent (Martínez-Maza et al.). The largest study
to date was a pooled analysis of over 13,000 cases and controls from the
InterLymph consortium that found a modest 15% decreased risk of B-cell NHL
associated with hay fever and a 20% decreased risk of NHL overall associated
with any specific allergy (Vajdic et al., 2009). Self-reported hay fever is more
highly correlated with physician-diagnosed disease and a relatively better
predictor of IgE levels (though poor on an absolute scale) than other atopic
conditions (Hoppin, AJE, 2011), which probably explains the more consistent
findings for this exposure across studies. In our study, double-respondent twins
agreed on the diagnosis of hay fever in their twin over 81% of the time (data not
144

shown). Mixed results have been reported when examining allergies to foods,
insects, etc. as risk factors, possibly because of misclassification resulting from
misunderstanding the entity (e.g., reporting lactose intolerance as a food allergy).
Inconsistent results have also been found for eczema and asthma (Martínez-
Maza et al.), again perhaps because of poor reporting. We did not have
sufficient numbers of exposure-discordant pairs to examine these entities
separately, however when we examined them together with hay fever and other
allergies, we observed a statistically significant and substantial decreased risk,
up to 92% in persons with 2 or more atopic diseases.
There are two possible explanations for the increased magnitude of effect
observed in our study. First, the reference group in our study had no other atopic
conditions, whereas commonly multiple atopic conditions in the unexposed is
permitted and controlled in the analysis by adjustment. Although the atopic
conditions examined were only modestly correlated (~r=0.3), a clean reference
group may offer a more robust comparison. Second, the twin comparison design
controls for sex, age, ethnicity, major early childhood and environmental and
genetic risk factors that could contribute to confounding in studies of non-related
individuals. The stronger effect DZ compared to MZ twins suggests a potential
interaction between atopic diseases and genetic variation in immune response
genes (Wang & Nieters).
Atopic diseases are characterized by Type I hypersensitivity, involving Th2
cells, immunoglobulin E (IgE) antibodies, mast cells and eosinophils. IgE-
145

mediated immune responses have a clear potential to exert anti-tumor effects.
These include the promotion of IgE-mediated antibody-dependent anti-tumor
cellular cytotoxicity, antibody-dependent cellular phagocytosis, enhanced antigen
presentation, and tumor inhibiting mast cell responses (Jensen-Jarolim et al.,
2008) (Jensen-Jarolim et al., 2008; Strik et al., 2007). Therefore, IgE-mediated
effector mechanisms have the potential to protect from cancer via enhanced anti-
tumor cell immune responses.
Additionally, IgE has biological effects that are specific to B cells, which
are the cell of origin for most NHL. The B cell activation drives DNA-modifying
molecular events, mediated by activation-induced cytidine deaminase (AID),
which can result in the genesis of NHL (Pasqualucci et al., 2008). Therefore,
dampening B cell activation would be expected to decrease the accrual of such
lymphomagenic lesions, and to lead to decreased risk for NHL. CD23 is the low
affinity Fc receptor for IgE. Binding of IgE to CD23 may prevent CD23 from
cleaving to generate soluble CD23 (sCD23), a molecule that has B-cell
stimulatory properties (Gordon, 1992). Indeed, elevated sCD23 levels have been
observed prior to the diagnosis of AIDS defining NHL (Breen et al., ; Schroeder
et al., 1999; Yawetz, Cumberland, van der Meyden, & Martinez-Maza, 1995). In
addition to this, binding of Ig to Fc receptors on B cells results in negative
signaling, preventing B cell activation. Therefore, binding of IgE to CD23 on B
cells has the potential to dampen B cell activation, indirectly by complexing with
146

and stabilizing cell surface CD23, preventing the release of sCD23, and directly,
by inducing signaling that prevents B cell activation.
Epidemiological studies of NHL have not found direct evidence supporting
a mechanism involving anti-tumor immunity mediated by IgE. Cohort studies in
which IgE levels were measured long before NHL diagnosis found no association
between IgE levels and NHL risk (Breen et al., ; Melbye et al., 2007). IgE levels
are higher in advanced vs. low stage disease and increases after chemotherapy
(Ellison-Loschmann et al., 2007), supporting a mechanism by which
lymphomagenesis interferes with the ability of B cells to produce normal levels of
IgE, resulting in an apparent deficit of allergies. The long-known inverse
relationship between allergy and glioma was also recently found to be associated
with a specific treatment, again suggesting a disease effect (Wiemels, 2009).
However, the strong and consistent inverse association between allergy and
pancreas cancer, originating from non-hematologic cells, offers some support for
an independent etiological association (Turner, ; Turner et al., 2006). In addition,
because this and other studies have found an inverse association with atopic
conditions occurring in childhood long before diagnosis, the timing is consistent
with an etiologic, rather than a disease effect.
We found eczema 5 years prior to diagnosis to be inversely associated
with NHL. Eczema is generally more common in children than adults with a
prevalence among children younger than18 of 8.1-18.7% across the U.S (Shaw
et al.) while the prevalence in adults was reported around 2-10% in industrialized
147

countries (Bieber, 2008). There was also an inverse associate between an
allergic reaction (generally) at least 5 years prior to the case-twin’s diagnosis and
NHL risk. Taking the cumulative evidence together, it is likely that there is both
an etiological pre-disease effect of atopy not necessarily mediated by IgE, and a
post-disease effect of NHL which decreases IgE production and therefore the
expression of atopy.
Several other immune-related medical conditions prior to NHL occurrence
were found to be associated with NHL risk in our twin study. Interestingly,
several of these showed effects in the opposite direction of those we previously
found for adolescent/young adult Hodgkin lymphoma (AYAHL) (Cozen et al.,
2009). IM is the occasional clinical consequence that occurs when primary
Epstein-Barr virus (EBV) infection is delayed from early childhood (when it is
asymptomatic or non-specific and mild) to adolescence or young adulthood. IM
may reflect a childhood with relatively less opportunity for exposure to EBV at an
earlier age. While a history of IM at least 5 years before diagnosis was a risk
factor for AYAHL (Cozen et al., 2009), it was inversely related to NHL risk. In a
recently published pooled analysis involving over 12,000 cases and 15,000
controls, a self-reported history of IM was associated with a modest increased
risk of NHL (OR=1.26, 95%CI=1.01-1.57) (Becker et al.). Inconsistent results
could be due to poor reporting since symptoms that lead to the diagnosis are
highly variable in severity and recall bias could explain a positive association in
unrelated cases and controls, but could also be due to confounding by genetic
148

susceptibility which has been demonstrated for IM (Hwang et al.). Because
agreement on which twin had IM was over 90% in our study, the report is more
likely to be real, and because the association was inverse, it is less likely to be
due to recall bias. In addition, the use of the discordant twin design partially or
completely controls for genome and thus confounding by genetics.
Relatively more behaviors that increase risk of infection during childhood
were associated with an increased risk of NHL in our study, the inverse of what
we observed for AYAHL (Cozen et al., 2009). The finding is consistent with
earlier studies showing a positive association between late birth order (a
surrogate for childhood crowding and early life exposures) and increased NHL
risk (Cozen et al., 2007; Grulich et al., 2005; Holly et al., 1999; Smedby et al.,
2007). A pooled InterLymph study concluded that the association was subject to
selection bias (Grulich et al.), but that would not explain our current findings
because the comparison is within members of a twin pair. The association is
unlikely to be due to misclassification because agreement on relative exposure in
the pair was high (above 84% for each variable except relatively more kissing
people as a young child, 77%, and relatively more biting nails, 78%). Recall bias
is also unlikely because none reported early childhood behaviors as a possible
explanation for the disease when asked an open-ended question and thus the
hypothesis was not known to the twins.
Tonsillectomy was associated with an increased risk of NHL, while
appendectomy was not. These surgeries have not been extensively evaluated
149

as risk factors, however, three case-control studies failed to find a link between
NHL and tonsillectomy (Cozen et al., 2007; Silingardi, Venezia, Tampieri, &
Gramolini, 1982; Vineis, Crosignani et al., 2000). Inconsistent results have also
been reported regarding the association between appendectomy and NHL
(Bernstein & Ross, 1992; Cope et al., 2003; Mellemkjaer, Johansen, Linet,
Gridley, & Olsen, 1998; Silingardi et al., 1982).
Although the sample size is relatively small for a standard case-control
study, this is the only study to use NHL-discordant twin pairs in a case-control
design, with nearly twice as many NHL cases as the only other study of NHL in
twins (Soderberg et al., 2004). A major limitation is the inability to examine
subtype-specific associations as there is known to be heterogeneity across
subtypes (Morton et al., 2008). The small number of exposure-discordant pairs
prevented analysis of allergic asthma separately. Ascertainment and selection
bias are not a concern because the comparison is within twin pairs. Females
and MZ twins were over-represented and the participation age in our study is
relatively young compared to other epidemiological studies of NHL considering
the incidence of NHL peaks after 65 years, thus generalizability could be an
issue. However, risk estimates would not be affected unless the distribution of
exposure-discordant pairs was differentially affected by ascertainment, which
seems implausible. A key strength is the use of the twin design to control
confounding, including both genetic and non-genetic factors. Restriction to like-
sex twin pairs further reduces confounding due to behavior differences by sex.
150

Accurate recall of childhood experiences is usually a concern in typical case-
control study, but the mutual comparisons within twin pairs provides a unique
way to validate exposures. Because this study was based solely on a priori
hypotheses from other studies, multiple comparisons is not a concern.
In summary, a strongly inverse and significant association between
seasonal hay fever / allergy and NHL was found in our case-control study NHL-
discordant twins consistent with the largest case-control study likely to ever be
conducted (Vajdic et al., 2009). Larger longitudinal studies, ideally with
biomarker measurements of atopy, are needed to elucidate a possible
mechanism. Several risk factors, including atopic disease, IM and childhood
behaviors increasing infectious exposures, showed the opposite association from
those in twins with AYAHL, supporting highly distinct etiologies of these two
hematologic neoplasms.
151

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155

Chapter 8: Atopic Disease, Immune-response Genes and
Non-Hodgkin Lymphoma Risk

Abstract
An inverse association between atopic disease, particularly hay fever or allergy,
and NHL risk has been consistently reported to be inversely associated with NHL
risk in case-control studies. However, an alternative hypothesis is that NHL itself
may affect Ig production, including IgE and therefore expression of the allergic
phenotype. To help understand the nature of atopy-NHL association, we
evaluated interactions between established NHL-related immune response
genes and atopic disease on NHL risk in an InterLymph pooled analysis involving
six population based case-control studies. Self reported atopic diseases
diagnosed at least 2 years before NHL diagnosis (cases) or interview (controls)
were ascertained through structured questionnaire. Three gene polymorphisms,
including TNF -308G>A (rs1800629), LTA 252A>G (rs909253) and IL10 -
3575T>A were assessed. Unconditional logistic regression was used to
calculate odds ratios along with 95%CI, adjusted for age, sex, socioeconomic
status and study. After taking into account of multiple testing, we did not find any
significant atopy-gene interaction for all NHL combined. However, significant
interactions were observed in subtype analysis after Bonferroni correction. LTA
252A>G may modify the association between asthma and Diffuse Large B-cell
Lymphoma (P
Interaction
= 0.0004) and there was a significant interaction between
156

IL10 -3575T>A and a history of both allergy and eczema on Chronic Lymphocytic
Leukemia/Small Lymphocytic Lymphoma risk (P
Interaction
= 0.002). Our results
suggest possible interactions between NHL-related immune response genes and
atopic disease on risk of certain NHL subtypes but future studies need to
replicate these results.

Introduction
Cumulative evidence from case-control studies has suggested a modest
protective effect of atopic disease, particularly allergy and hay fever, on non-
Hodgkin lymphoma (NHL) risk (Martínez-Maza et al.). In an InterLymph pooled
analysis involving 13 case-control studies, allergy to specific substances was
associated with a 20% decreased risk of NHL overall and hay fever was
associated with a 15% reduced risk of B-cell NHL (Vajdic et al., 2009). However,
cohort studies have not reported similar results (Eriksson et al., 2005; Lindelof et
al., 2005; Soderberg et al., 2004; Turner et al., 2005; Vesterinen, Pukkala,
Timonen, & Aromaa, 1993). In addition, there has been a concern that the
apparent protective effect from atopic disease is actually due to the lymphoma as
the target B-cell may lose the ability to produce antibodies, including IgE. For
example, in a Finnish cohort of pregnant women who provided blood samples
during pregnancy, the inverse association between immunoglobulin E (IgE), a
biomarker of atopy, and NHL was only observed within one year of disease
157

diagnosis, and the association diminished as the time prior to NHL diagnosis
increased (Melbye et al., 2007). To further understand the biological pathways
underlying the association between atopic disease and NHL, we examined gene-
environment interaction with a focus on immune response genes implicated in
NHL etiology. In two large pooled analyses by International Lymphoma
(InterLymph) Epidemiology Consortium, one of which is the largest candidate
gene association study of NHL to date (Skibola et al.), tumor necrosis factor-α
(TNF-α), lymphotoxin-α (LTA) and interleukin 10 (IL10) gene variants have been
reported associated with an increased risk of NHL overall or subtypes of NHL
(Rothman et al., 2006; Skibola et al.). These gene variants have also been
implicated in susceptibility to atopic conditions, particularly asthma. For example,
the A allele of TNF -308G>A alone (Munthe-Kaas et al., 2007; Winchester,
Millwood, Rand, Penny, & Kessling, 2000; Witte, Palmer, O'Connor, Hopkins, &
Hall, 2002) or in haplotype with the G allele of LTA 252A>G (Moffatt, James,
Ryan, Musk, & Cookson, 1999; Randolph, Lange, Silverman, Lazarus, & Weiss,
2005; Sharma, Sharma, Kumar, Sharma, & Ghosh, 2006), has been reported to
be associated with an increased risk of asthma. IL10 polymorphisms have been
suggested associated with asthma (R. Chatterjee et al., 2005), IgE levels in
individuals with atopic dermatitis (H. D. Shin, Park, Kim, Kim, & Kim, 2005), and
IgE levels in adults with asthma (Karjalainen et al., 2003). We performed an
analysis to assess the effect of interactions between TNF -308G>A, LTA 252A>G
158

and IL10 -3575T>A genotypes and atopic disease on NHL risk in a subset of
studies from the InterLymph Consortium.

Materials and Methods
Study Population and Self-reported Exposures
Six population based case-control studies identified through InterLymph
Consortium met the following eligibility criteria: collection of data on all four major
atopic conditions, including hay fever, specific allergy, asthma and eczema, and
genotyping data of at least one SNPs from TNF -308G>A (rs1899629), IL10 -
3575T>A (rs1800890), and LTA 252A>G (rs909253). Participating studies
included NHL study in British Columbia, Canada (Spinelli et al., 2007); NHL study
in Mayo Clinic (Cerhan et al., 2007); lymphoma study in New South Wales,
Australia (Hughes et al., 2004); the Scandinavian Lymphoma Etiology (SCALE)
study in Denmark and Sweden (Melbye et al., 2007); lymphoma study in York,
United Kingdom (Willett et al., 2005); lymphoma study from Germany as part of a
multicenter European study (Epilymph) (Becker et al., 2004). Recipients of organ
transplant and individuals with HIV infection were excluded. Eligible cases were
aged ≥ 18 years and diagnosed with incident NHL between 1989 and 2005.
Histological types of all cases were classified according to the pathology coding
scheme based on current World Health Organization (WHO) classification of
tumors of hematopoietic and lymphoid tissues (Morton et al., 2007). Self-
159

reported history of atopic disease was obtained from each of the participating
study center, while participants with occurrence of atopic condition less than 2
years to NHL diagnosis (cases) or interview date (controls) were excluded.
Analysis was restricted to non-Hispanic White participants.

Genotyping
SNPs were genotyped using either TaqMan platform (Applied Biosystems, Foster
City, CA, USA) or Pyrosequencing (Qiagen NV, Hilden, Germany) which was
used in Epilymph – Germany study or matrix-assisted laser desorption/ionization-
time of flight mass spectrometry (Sequenom Inc., San Diego, CA) which was
used in SCALE study. Sequence data and assay conditions for Taqman assays
are available on the NCI SNP500 website (http://snp500cancer.nci.nih.gov). To
ensure that genotyping results were consistent across studies, every laboratory
analyzed the same set of DNA samples from 102 ethnically diverse individuals
that had previously been sequenced and genotyped on one or more platforms.
Genotyping accuracy was assessed and verified across laboratories.

Statistical Analysis
For each participating study, departure from Hardy-Weinberg equilibrium (HWE)
was assessed in controls using chi-squared tests. With the exception of LTA
(rs909253) in the samples from the SCALE study (P<0.01), there was no
evidence of departure from HWE. Because the results of interaction testing
160

remained similar after excluding these data, the SCALE study was not excluded
in the pooled analysis. Minor allele frequency (MAF) among controls was
comparable across studies for all the SNPs.
Only participants with data of all four types of atopic diseases contributed to
the analysis. Correlation between atopic diseases was evaluated among
controls using Pearson chi-squared tests. Because the conditions were
significantly correlated (Supplemental Table 1) and there is a known common
genetic basis for allergic diseases, a common reference group was used, defined
as participants free of any atopic disease assessed, including hay fever, allergy
to specific substances (“specific allergy”), asthma and eczema. The comparison
group was defined as participants who had a single atopic disease of interest
without any other atopic conditions. To evaluate a joint effect of specific atopic
diseases, variables representing multiple atopic diseases were generated based
on their correlations, including combinations of hay fever and specific allergy,
specific allergy and eczema, hay fever and asthma, and specific allergy and
asthma. Only the first two combinations were evaluated due to the small number
of NHL cases with the other combinations of atopic conditions (N<100,
respectively).
For each SNP, genotype was coded as an ordinal variable (0, 1, 2) based
on the number of variant alleles. To test for interaction, we fitted a model with
atopic condition and genotype as well as an interaction term and examined the
statistical significance of interaction by means of a likelihood ratio test comparing
161

the full model against a model without the interaction term (test degree of
freedom = 2). After screening for significant interactions (P < 0.05), the effect
estimate (OR) was calculated for strata of genotyping and atopic condition using
individuals homozygous for the major allele and without any atopic condition as
the common reference group. Odds ratios along with 95% confidence interval
(CI) were computed using unconditional logistic regression models adjusting for
age (5-year category), sex, study center and tertiles of socioeconomic status
(SES).
To test for heterogeneity of the interaction, likelihood ratio test was applied
in the multivariable logistic regression by comparing models with and without the
three way interaction term of atopic disease and genotype of SNP and study
center. If significant heterogeneity was observed (P<0.05), study-specific G-E
interaction effects were evaluated in order to identify the studies with significantly
different interaction effect. The interaction analyses were repeated by excluding
outlying studies. However, if exclusion of data from outlier studies resulted in
small changes in odds ratio estimates when compared to models including all the
studies in the interaction analysis, the outlier studies were not excluded from the
analysis.
Analysis was stratified by T-cell NHL and major subtypes of B-cell NHL,
including diffuse large B-cell lymphoma (DLBCL), follicular lymphoma, chronic
lymphocytic leukemia (CLL) / small lymphocytic lymphoma (SLL). To account for
multiple testing, a Bonferroni correction was applied. Interaction p-values were
162

corrected within the disease categories of all NHL combined and each subtype,
with the threshold for a significant p-value as 0.0028. All statistical analyses
were conducted using R, version 2.15.1.

Results
Mean ages were similar among cases and controls (59.0 [standard deviation
(SD): 11.8] and 58.5 [SD: 13.0] years in case and control groups, respectively).
There were more male than females among both the cases and controls groups,
consistent with the higher incidence rate of NHL among males (Table 8.1). The
distribution by socioeconomic status (SES) was significantly different between
case and control groups. Among cases, there was a higher proportion of low
SES participants compared the other SES groups, while among controls, the
three SES groups (low, medium and high) were almost evenly distributed. The
SCALE study center contributed to the largest proportion to both the pooled case
and control groups. Based on InterLymph pathology group classification of NHL
subgroups (Morton et al., 2007), the vast majority of the cases was of B-cell
lineage, of which DLBCL and Follicular lymphoma contributed to the similar
proportions.

163

Table 8.1. Characteristics of pooled study participants

Demographic Factor Case Control
N %

N % P-value
Pooled total 4875

5037

Age

<0.0001
<50 914 18.7

1118 22.2

50-54 630 12.9

550 10.9

55-59 802 16.5

760 15.1

60-64 772 15.8

729 14.5

65-69 808 16.6

835 16.6

70-74 709 14.5

693 13.8

≥75 240 4.9

352 7.0

Sex

0.0001
Male 2827 58.0

2718 54.0

Female 2048 42.0

2319 46.0

SES (tertile)

0.0005
Low 1763 36.2

1630 32.4

Medium 1557 31.9

1713 34.0

High 1494 30.6

1611 32.0

Unknown/Other 61 1.3

83 1.6

Subtypes of NHL

B-cell NHL 4488 92.1

DLBCL 1396 28.6

Follicular lymphoma 1212 24.9

CLL/SLL 922 18.9

MZL 273 5.6

Others 685 14.1

T-cell NHL 257 5.3

Missing or NOS 130 2.7

Participating study

<0.0001
New South Wales, Australia 461 9.5

424 8.4

British Columbia, Canada 577 11.8

589 11.7

York, United Kingdom 515 10.6

521 10.3

Epilymph Germany 434 8.9

618 12.3

Scandinavian Lymphoma Etiology Study 2242 46.0

1839 36.5

Mayo clinic, U.S. 646 13.3 1046 20.8

164

Correlation between atopic diseases was evaluated among controls using
Pearson chi-squared test and correlation coefficients (r
2
) were presented in
Supplementary Table 8.1. The highest correlation coefficient was observed for
hay fever and specific allergy (r
2
= 0.50). Specific allergy and eczema, hay fever
and asthma, and specific allergy and asthma all showed a slight correlation (r
2
ranged from 0.20 to 0.24), while there was barely a correlation between asthma
and eczema. Participants in NSW, Australia had the highest prevalence of all
four major atopic conditions while those in the York, UK study had an overall low
prevalence of atopic diseases, especially specific allergy (Supplemental Table
8.2.). Epilymph – Germany and Mayo study participants had a mixed pattern
with a low prevalence of some, but not other atopic conditions (asthma in
Epilymph – Germany and Eczema in Mayo, respectively).

Supplementary Table 8.1. Pearson correlation coefficients between atopic
diseases among controls

Hay fever Specific allergy Asthma Eczema
Hay fever

Specific allergy 0.50

Asthma 0.23 0.20

Eczema 0.10 0.24 0.07

165

Supplementary Table 8.2. Prevalence of atopic diseases among controls in each
participating study

Study
Specific
allergy Hay fever Asthma Eczema
NSW 0.51 0.58 0.35 0.27
British Columbia 0.43 0.37 0.21 0.24
UK 0.17 0.22 0.14 0.15
Epilymph - Germany 0.33 0.20 0.08 0.22
SCALE 0.43 0.32 0.14 0.21
Mayo 0.27 0.23 0.14 0.10

We observed the expected inverse association between hay fever and all
NHL combined as well as most NHL subtypes (Supplementary Table 8.3 a and
b). A history of both specific allergy and hay fever together was also inversely
associated with all NHL combined and DLBCL, but specific allergy alone was not.

166

Supplementary Table 8.3a. A history of individual atopic disease and risk of all NHL or major subtypes

No atopic
disease Hay fever Specific allergy
Ca Co

Ca Co OR
2
95%CI
2

Ca Co OR
2
95%CI
2

All NHL 2840 2771

210 245 0.71 0.58 0.87

455 457 0.89 0.77 1.03
B-cell NHL

DLBCL 820 2771

78 245 0.75 0.56 0.99

130 457 0.87 0.70 1.08
Follicular 679 2771

53 245 0.56 0.40 0.77

127 457 0.93 0.74 1.16
CLL/SLL
1
584 2456

20 186 0.71 0.42 1.16

67 415 0.81 0.60 1.08
T-cell NHL
1
143 2456 5 186 0.41 0.14 0.94 20 415 0.74 0.44 1.19

No atopic
disease

Asthma Eczema
Ca Co

Ca Co OR
2
95%CI
2

Ca Co OR
2
95%CI
2

All NHL 2840 2771

140 133 1.00 0.78 1.28

170 196 0.91 0.73 1.13
B-cell NHL

DLBCL 820 2771

40 133 0.93 0.63 1.33

52 196 0.87 0.62 1.20
Follicular 679 2771

41 133 1.08 0.74 1.56

45 196 0.85 0.60 1.19
CLL/SLL
1
584 2456

18 106 0.73 0.42 1.19

23 162 0.85 0.52 1.32
T-cell NHL
1
143 2456

10 106 1.64 0.78 3.13 16 162 2.00 1.09 3.48

1
York, UK study excluded because no CLL/SLL or T-cell NHL cases.
2.
Adjusted for age (5-year category), sex, SES (low, medium and high) and study center.

167

Supplementary Table 8.3b. A history of combined atopic diseases and risk of all
NHL or major subtypes

No atopic
disease
Specific allergy and
hay fever Specific allergy and eczema

Ca Co

Ca Co OR
2
95%CI
2

Ca Co OR
2
95%CI
2

All NHL 2840 2771

452 525 0.83 0.72 0.95

181 182 0.86 0.69 1.07
B-cell NHL

DLBCL 820 2771

105 525 0.74 0.58 0.93

49 182 0.87 0.61 1.21
Follicular 679 2771

115 525 0.88 0.70 1.11

45 182 0.97 0.68 1.37
CLL/SLL
1
584 2456

100 517 0.88 0.69 1.12

31 179 0.75 0.49 1.11
T-cell NHL
1
143 2456 27 517 0.79 0.50 1.20 8 179 0.55 0.24 1.08

1.
York, UK study excluded because no CLL/SLL or T-cell NHL cases.
2.
Adjusted for age (5-year category), sex, SES (low, medium and high) and study center.

Supplementary table 8.4 shows the effect of the three gene polymorphisms
on risk of all NHL combined and major histological subtypes. TNF -308A allele
was positively associated with risk of all NHL and T-cell NHL, and a borderline
significant association with DLBCL (P
trend
= 0.06). The IL10 -3575A allele was
positively associated only with DLBCL risk (per allele OR = 1.12, P
trend
= 0.01).
With exception of T-cell NHL, there was no evidence of association between LTA
252A>G and all NHL combined or subtypes of B-cell NHL.

168

Supplementary Table 8.4. TNF-alpha, LTA and IL10 and risk of all NHL and major subtypes

All NHL DLBCL Follicular lymphoma

Co
1

Ca OR 95%CI

Ca OR 95%CI

Ca OR 95%CI
TNF -308 G>A

GG 3061

3064 1.00

850 1.00

807 1.00

GA 1301

1378 1.05 0.96 1.16

415 1.12 0.98 1.29

305 0.89 0.76 1.03
AA 143

190 1.29 1.03 1.62

53 1.21 0.86 1.68

37 0.90 0.61 1.30
Per-allele

1.09 1.01 1.17

1.11 0.99 1.25

0.91 0.80 1.03
P for trend

0.04

0.06

0.13

LTA 252A>G

AA 1740

1734 1.00

488 1.00

44 1.00

AG 1780

1866 1.06 0.96 1.16

547 1.09 0.95 1.26

470 1.01 0.87 1.17
GG 525

602 1.11 0.97 1.27

179 1.18 0.96 1.44

124 0.89 0.71 1.12
Per-allele

1.05 0.99 1.12

1.09 0.99 1.19

0.96 0.87 1.07
P for trend

0.11

0.09

0.48

IL10 -3575 T>A

TT 1773

1672 1.00

446 1.00

428 1.00

TA 2280

2230 1.03 0.94 1.13

678 1.18 1.03 1.36

519 0.94 0.81 1.09
AA 778

805 1.09 0.96 1.23

244 1.23 1.02 1.47

196 1.03 0.85 1.25
Per-allele

1.04 0.98 1.10

1.12 1.03 1.22

1.00 0.91 1.10
P for trend 0.17 0.01 0.99

169
Supplementary Table 8.4, continued

CLL/SLL
3
T-cell NHL

Co
2

Ca OR 95%CI

Ca OR 95%CI
TNF -308 G>A

GG 2746

596 1.00

154 1.00

GA 1140

257 1.02 0.86 1.21

71 1.13 0.84 1.51
AA 114

31 1.28 0.82 1.94

16 2.54 1.40 4.35
Per-allele

1.06 0.92 1.22

1.33 1.05 1.67
P for trend

0.43

0.01

LTA 252 A>G

AA 1547

365 1.00

75 1.00

AG 1529

377 1.06 0.89 1.25

93 1.27 0.92 1.75
GG 462

122 1.06 0.83 1.35

41 1.80 1.19 2.68
Per-allele

1.04 0.93 1.16

1.33 1.09 1.62
P for trend

0.51

0.005

IL10 -3575 T>A

TT 1586

333 1.00

93 1.00

TA 2056

427 0.98 0.83 1.16

122 1.01 0.76 1.34
AA 698

136 0.92 0.73 1.16

36 0.88 0.58 1.30
Per-allele

0.97 0.87 1.08

0.95 0.79 1.15
P for trend 0.53 0.62

1
Same control group for all NHL, DLBCL and Follicular lymphoma.
2
Same control group for CLL/SLL and T-cell NHL.
3
York, UK study excluded because of no CLL/SLL or T-cell NHL cases.
4
Adjusted for age (5-year category), sex, SES (low, medium and high) and study center.
170

There was no statistically significant study heterogeneity with respect to
interaction between TNF -308G>A and any of the atopic conditions
(Supplementary Table 8.5). However, for between IL10 and LTA and specific
allergy with eczema, the York, UK study had a significant different interaction
effect compared to other studies. The heterogeneity could have been caused by
the low prevalence of atopic conditions among those participants compared to
those in other studies. Nonetheless, exclusion of data from York, UK study
resulted in only marginal changes in odds ratio estimates compared to models
including all the studies for interaction analysis; therefore, all studies were
retained in the pooled interaction analysis.

171

Supplementary Table 8.5. P-values for test of interaction heterogeneity across
studies

Specific
allergy
Hay
fever Asthma Eczema
Specific
allergy and
hay fever
Specific
allergy and
eczema
All NHL combined

IL10 0.14 0.37 0.26 0.64 0.59 0.04
TNF-alpha 0.90 0.60 0.69 0.83 0.15 0.62
LTA 0.73 0.45 0.38 0.64 0.35 0.05

DLBCL

IL10 0.29 0.70 0.32 0.64 0.61 0.37
TNF-alpha 0.88 0.30 0.74 0.59 0.51 0.50
LTA 0.91 1.00 0.83 0.62 0.53 0.27

Follicular lymphoma

IL10 0.44 0.14 0.70 0.30 0.83 0.02
TNF-alpha 0.36 0.53 0.43 0.55 0.97 0.72
LTA 0.11 0.45 0.81 0.15 0.26 0.15

CLL/SLL

IL10 0.36 0.64 0.79 0.41 0.35 0.05
TNF-alpha 0.94 0.62 0.98 0.69 0.53 0.99
LTA 0.76 1.00 0.51 0.93 0.72 0.98

There was no statistically significant (P <0.05) effect of interaction between
TNF -308G>A and any of the atopic conditions on risk of all NHL or major
subtypes of B-cell NHL (Figure 8.1 a and b). However, we did observe
significant interactions between LTA 252A>G and IL10 -3575T>A and a history of
atopic conditions for both all NHL and specific NHL subtypes (Figure 8.1 a and b).

172
Figure 8.1a. Interaction P-values for atopic disease and IL10 -3575T>A, LTA 252A>G, and TNF -308G>A on risk of
All NHL

Dots above the red dash line indicate interaction P-value < 0.05 while dots above the red solid line indicate significant interaction P-values after
Bonferroni correction (P-value < 0.0028).

173
Figure 8.1b. Interaction P-values for atopic disease and IL10 -3575T>A, LTA 252A>G, and TNF -308G>A on risk of
major subtypes of B-cell NHL

Dots above the red dash line indicate interaction P-value < 0.05 while dots above the red solid line indicate significant interaction P-values after
Bonferroni correction (P-value < 0.0028).
174

An interaction between IL10 -3575T>A and a history of both specific allergy
and eczema was observed for overall NHL (P
interaction
= 0.02, Supplementary
Table 8.6), CLL/SLL risk (P
interaction
= 0.002, Table 8.2) and follicular lymphoma
(P
interaction
= 0.004, Supplementary Table 6). The effect of an interaction between
LTA 252A>G and specific allergy (P
interaction
= 0.005, Supplementary Table 8.6)
was also observed for follicular lymphoma.

175

Supplementary Table 8.6. Interactions of LTA and a history of atopic disease on
risk of all NHL, DLBCL and Follicular lymphoma

All NHL

No atopic disease

Specific allergy and eczema
IL10 -3575T>A Ca Co OR
1
95%CI
1

Ca Co OR
1
95%CI
1

TT 990 1006 1.00
Ref

67 57 1.07 0.74, 1.55
TA 1290 1247 1.04 0.92, 1.17

87 77 1.01 0.73, 1.40
AA 473 416 1.14 0.97, 1.34

22 37 0.51 0.30, 0.88
P-interaction 0.02
DLBCL

No atopic disease Specific allergy
LTA 252 A>G Ca Co OR
1
95%CI
1

Ca Co OR
1
95%CI
1

AA 293 972 1.00
Ref

30 150 0.56 0.36, 0.84
AG 329 1006 1.07 0.88, 1.28

62 160 1.16 0.84, 1.62
GG 91 279 1.05 0.79, 1.38

20 46 1.25 0.72, 2.17
P-interaction 0.02
Follicular lymphoma

No atopic disease Specific allergy
LTA 252 A>G Ca Co OR
1
95%CI
1

Ca Co OR
1
95%CI
1

AA 252 972 1.00
Ref

38 150 0.71 0.47, 1.05
AG 262 1006 0.97 0.80, 1.19

60 160 1.19 0.84, 1.67
GG 75 279 0.99 0.73, 1.33

5 46 0.29 0.11, 0.75
P-interaction 0.005
Follicular lymphoma

No atopic disease

Specific allergy and eczema
IL10 -3575 T>A Ca Co OR
1
95%CI
1

Ca Co OR
1
95%CI
1

TT 253 1006 1.00
Ref

9 57 0.61 0.28, 1.22
TA 270 1247 0.82 0.68, 1.00

28 77 1.46 0.91, 2.33
AA 120 416 1.12 0.86, 1.44

5 37 0.47 0.18, 1.22
P-interaction 0.004

1
Adjusted for age (5-year category), sex, SES (low, medium and high) and study center.

176

LTA 252A>G significantly modified the association between asthma (P
interaction
= 0.0004, Table 2) and specific allergy (P
interaction
= 0.02, Supplementary
Table 8.6) and DLBCL risk. No significant interaction was observed between any
of the SNPs and any atopic conditions on T-cell NHL risk (data not shown). After
accounting for multiple testing using the Bonferroni correction, only two
interactions remained statistically significant: an interaction between LTA
252A>G and asthma on DLBCL risk and between IL10 -3575T>A and specific
allergy and eczema together on CLL/SLL risk.
Risk estimates by genotype and atopic condition for the two significant
interactions are presented in Table 8.2 and Figure 8.2. The reference group is
individuals with no atopic condition and carrying the common homozygous. The
most dramatic and significant interaction was between asthma and the LTA allele
on DLBCL risk (P= 0.0004). Compared to the reference group, a history of
asthma was significantly associated with approximately 55% decreased DLBCL
risk among carriers of AG genotype, but increased 3.7-fold among carriers of
variant homozygous GG. CLL/SLL risk was significantly decreased among
participants with specific allergy and eczema and carrying the any A allele (Table
8.2, Figure 8.2).

177

Table 8.2. Interactions of LTA and IL10 with a history of atopic disease on risk
of B-cell NHL

DLBCL

No atopic disease Asthma
LTA 252 A>G Ca Co OR
1
95%CI
1

Ca Co OR
1
95%CI
1

AA 293 972 1.00
Ref

12 45 0.79 0.39, 1.49
AG 329 1006 1.06 0.88, 1.28

8 59 0.44 0.21, 0.95
GG 91 279 1.04 0.78, 1.37

16 12 3.68 1.68, 8.04
P-interaction 0.0004

CLL/SLL
2

No atopic disease

Specific allergy and eczema
IL10 -3575 T>A Ca Co OR
1
95%CI
1

Ca Co OR
1
95%CI
1

TT 207 893 1.00
Ref

19 56 1.59 0.89, 2.76
TA and AA 363 1478 1.05 0.86, 1.28

12 112 0.45 0.24, 0.84
P-interaction 0.002

1
Adjusted for age (5-year category), sex, SES (low, medium and high) and study center.
2
York, UK study excluded because no CLL/SLL cases.

178

Figure 8.2a. Odds ratios for risk of DLBCL in relation to number of variant alleles
for LTA 252A>G and asthma

Figure 8.2b. Odds ratios for risk of CLL/SLL in relation to number of variant alleles
for IL10 -3575T>A and a history of both specific allergy and eczema

Note: odds ratios fitted for 0, 1, 2 variant alleles are shown for participants with atopic condition (solid square)
and participants with no atopic condition (open diamond). The reference group was individuals with no
atopic condition and 0 variant allele.

179

Discussion
We evaluated interactions between inflammatory gene variants, including TNF -
308G>A, LTA 252A>G and IL10 -3575T>A, and atopic conditions on NHL risk in
InterLymph Consortium pooled analysis, the first well-powered study to evaluate
such interaction. The main gene and environmental effects in our subset of
InterLymph studies were similar to, or even stronger than those found when the
entire Consortium was included (Skibola; Vajdic). In this analysis, many different
comparisons were performed and thus chance could account for some results.
After taking into account Bonferroni correction for multiple testing, there was
some evidence that variants in the LTA and IL10 genes may modify the effect of
asthma and a combination of specific allergy and eczema on B-cell NHL
subtypes, but not on overall NHL risk.
The strongest interaction was the LTA 252A>G variant in combination with
asthma on DLBCL risk. LTA, a member of the tumor necrosis factor superfamily,
has biologic activity similar to TNFα (Nedwin et al., 1985) and is also considered
to be a potent proinflammatory cytokine. The G allele is strongly associated with
increased LTA production (Messer et al., 1991), which implies that this gene
variant may directly contribute to the promotion of a proinflammatory milieu. The
G allele has also been associated with both increased risk of asthma (Moffatt &
Cookson, 1997; Witte et al., 2002) and DLBCL (Skibola et al.). Therefore, the
modification role of LTA 252A>G on asthma effect on DLBCL risk appears
plausible. The interaction risk pattern appeared to suggest a recessive model
180

with some cross-over. A history of asthma among carriers of the common allele
A was associated with a significantly decreased DLBCL risk (OR = 0.58, 95%CI
= 0.34-0.94, data not shown). Compared to subjects without any atopic disease
who carried the common A allele, subjects with asthma who were homozygous
for the G allele had a dramatically increased 3.56-fold risk for DLBCL Indeed,
when assuming a recessive model, similar results were found with a slightly
stronger statistical interaction (P for interaction = 0.0002, data not shown).
Given the close relationship between LTA 252A>G and TNF -308G>A (in
linkage disequilibrium: D’ = 1.0, r
2
= 0.34) and previous reports of increased
asthma risk associated with TNF 308G>A (Gao, Shan, Sun, Thompson, & Gao,
2006) or the haplotype of the two variants (Moffatt & Cookson, 1997; Randolph et
al., 2005), one might expect a modifier effect from TNF -308G>A of asthma effect
on DLBCL risk as well. In fact, a similar modifying effect by TNF -308G>A was
observed in our study with an even stronger positive association between asthma
and DLBCL among subjects homozygous for the minor allele genotype (4.60,
95%CI = 1.64, 16.97), however there was only a borderline significance of
interaction (P = 0.08). (The borderline significance could be due to lower power
caused by lower MAF prevalence of TNF -308G>A compared to LTA 252A>G
(MAF = 0.18 and 0.36, respectively). The fact the LTA allele is associated with a
functional change in protein secretion adds plausibility to a causal association
with this gene but still may not be definitive without further functional studies.
181

The other significant interactions involved IL10 -3575T>A and a history of
both specific allergy and eczema on the risk of CLL/SLL. A history of specific
allergy and eczema together was positively associated with risk of CLL/SLL
(Supplementary Table 2b). When the IL10 polymorphism is considered, an
approximately 50-55% decreased risk was observed for follicular lymphoma and
CLL/SLL among those homozygous and heterozygous for the variant allele,
respectively. However, there was no interaction between the IL10 polymorphism
and either specific allergy or eczema alone. Allergy, specifically food allergy, and
eczema often occur together, typically among infants and young children in
whom prevalence of food allergy among eczema can be estimated at 40% (Hauk,
2008). Children with eczema triggered by food allergens demonstrate an altered
immune response: an early impairment of IL10 production in response to food
allergen stimulation (Dunstan et al., 2005). Although laboratory and clinical
studies have suggested that food allergy plays a pathogenic role in infants and
children with eczema (Sicherer & Sampson, 1999), there is lack of studies
examining the role of food allergy in eczema among adults. However, if the
assessment of the history of the combination of specific allergy and eczema
tends to reflect a childhood exposure in our study, the interaction is more likely to
be a true etiological effect rather than NHL effect. The fact that there was no
interaction with either entity alone could reflect a lack of power or that the
combination phenotype represents a different disease than either alone.
182

Evidence of an association between IL10 3575T>A and specific allergy or
eczema is suggested by a report of that a four-locus IL10 haplotype, including
the 3575 T allele, was significantly associated with increased IgE levels among
atopic dermatitis patients (Lacy, Archer, Wood, & Bidwell, 2009). The variant A
allele has been found to decrease IL10 production (Gibson et al., 2001). The
biological characteristics of IL10 make it a possible effect modifier. IL10 is an
anti-inflammatory cytokine produced by monocytes and lymphocytes that has
inhibitory effects of both Th1 and Th2 cytokines (Rosenwasser & Borish, 1997).
In contrast to its inhibitory effects, IL10 also functions as an activating factor
enhancing B-cell proliferation, differentiation and antibody production (Lalani,
Bhol, & Ahmed, 1997). Although the role of IL-10 in allergic inflammation and
allergic disease is not yet conclusive, there is growing interest in its potential role
in regulating or inhibiting allergic responses and the expression of the allergic
phenotypes (Dunstan et al., 2005).
Our study has several strengths. The large sample size allowed us to
evaluate NHL subtype-specific interactions, which is important in understanding
etiological heterogeneity of NHL. Another strength lies in the analytical approach
applied to atopic conditions. Independent of the specific clinical phenotypes (e.g.
hay fever, allergy, asthma, or eczema), there is a common basis responsible for
this group of atopic conditions - total IgE. Common genetic elements underlying
the group of allergic disease have also been suggested (Barnes, 2000).
Therefore, a common reference group excluding all of the major atopic conditions
183

was used in our analysis. In addition, unlike mutual adjustment of atopic
conditions typically used in most epidemiological studies, the comparison group
in our study only had one single atopic disease of interest; thus, no adjustment of
other atopic diseases is necessary. Our reference and comparison groups made
it possible to delineate the individual interaction effect of each of the atopic
condition with the least possible confounding. In addition, we were able to
assess the possible effect modifier role by specific combinations of atopic
diseases, including combination of hay fever and specific allergy and another one
of specific allergy and eczema. This analysis could provide insights into possible
common pathways involved in the interaction. Finally, even though our study is
hypothesis-driven, correction of multiple testing using Bonferroni was still
performed to provide the most conservative conclusions.
A major limitation of our study is the retrospective collection of self-
reported atopic condition history. Recall bias is unlikely to be an issue given that
protective effects from atopic disease associated with NHL were found.
Misclassification, however, could occur. According to a U.S. national survey
aiming to assess questionnaire’s ability to predict biomarker measures of atopy,
among participants who reported atopic conditions in questionnaire, only 50-72%
of them had tested positive for serum specific IgE, with the lowest test positive for
eczema (50%) and highest for hay fever (72%) (asthma was not assessed in
that study) (Hoppin et al.). However, structured questionnaire used in the studies
contributing data to this analysis included detailed questions on atopic disease
184

history, such as frequency of occurrence over a lifetime or use of allergy
medications, which probably helped reduce the misclassification bias. In addition,
even if misclassification occurs, it is unlikely to be differential among cases and
controls, thus effects would have been underestimated rather than overestimated.
Finally, our study was restricted to non-Hispanic White; future study may expand
to population with different racial backgrounds.
In summary, our study found an effect of several interactions between
immune response genes and atopic diseases on the risk of NHL subtypes, but
not on all NHL combined. Given the current interest in biomarkers associated
with atopic diseases as potential anti-cancer targets, the results will hopefully
stimulate additional research in this area.

185

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189

Chapter 9. Summary

This dissertation evaluated the effect of immune dysfunction on NHL risk, given
that both immune suppression (e.g. severe immunodeficiency) and stimulation
(e.g. chronic antigenic stimulation) have been implicated in the pathogenesis. As
factors causing severe immune deficiency have already been established as risk
factors, this dissertation focused on factors resulting in mild to moderate immune
dysregulation. The first paper assessed the association between household
endotoxin levels, measured from dust samples collected from participants’
homes, and NHL risk. We tested the novel hypothesis that endotoxin could be a
risk factor because it induces B-cell activation through a variety of pathways
including NF-kb and TNF-alpha, which is linked to NHL. However, our study did
not find any association between household endotoxin levels and NHL. The null
finding could be due to the cross-sectional measurement of endotoxin which
makes it difficult to establish a causal relationship or to inaccurate capture of
household endotoxin levels (e.g. only a single measurement). However, this
study, for the first time, directly measured and assessed microbial exposure to
examine surrogates for early environment infectious exposure such as birth order,
family size or SES which have shown an effect on NHL risk. Future studies with
multiple measurements of endotoxin levels before NHL diagnosis are essential to
evaluate this association.
190

The primary research question in this dissertation was to explore the true
association between atopic (allergic) diseases, including allergy to specific
substance, hay fever, asthma and eczema, and NHL risk. Atopic disease has
become a more and more common group of conditions during the past decades,
especially in Western countries, causing increasing morbidity and medical
expenses. Most case-control studies have reported an inverse association
between atopic conditions and NHL overall or subtypes. Nonetheless, failure to
find similar results in cohort studies has raised a concern that the apparent
‘protective’ effect is actually an effect of NHL itself resulting from a decreased
ability of the B cell’s ability to produce normal levels of IgE. With the objective to
clarify the inverse association, we assessed this association in two studies from
different perspectives: one was a case-control study involving twins discordant
for NHL in which the effect of lifetime history of atopic disease on NHL risk was
examined; the other was a pooled analysis of 6 case-control studies in which the
interaction between NHL-related immune response genes and atopic condition
on NHL risk was evaluated. In both studies, an inverse association between
atopic conditions, particularly hay fever, and NHL or B-cell NHL was found. The
twin study design allowed us to control for genetic elements focus on the
environmental contribution of atopy as twins are matched fully (MZ) or partially
(50%) on genome, important because genetic susceptibility has been suggested
involved in both conditions. Therefore, we have provided evidence supporting
the association between atopic conditions and NHL, while genetic background
191

constant. A slightly stronger inverse association was observed in DZ twins than
MZ twins, implying a possible G-E interaction in the allergy-NHL association.
Consistent with the finding from the twin study, several possible G-E
interactions were found in the InterLymph pooled analysis. Out of the three gene
polymorphisms evaluated, LTA 252A>G was found as an effect modifier for
associations of asthma-DLBCL (P
interaction
= 0.0004) and specific allergy-
Follicular lymphoma (P
interaction
= 0.005), while IL10 -3575T>A as a modifier for
the association between a history of allergy and eczema together and Follicular
lymphoma (P
interaction
= 0.004) or CLL/SLL (P
interaction
= 0.002), after taking
account of multiple comparison. If replicated in future studies, these interactions
may provide evidence that the inverse association can be influenced by genetic
variation. More importantly, LTA and IL10 are pro-inflammatory immune-
regulatory genes implicated in NHL overall or subtypes and in allergic diseases.
The biological plausibility of the interaction further lends support to an etiological
association between atopic disease and NHL instead of a disease effect. Future
studies should investigate whether allergy-related genes would modify the
association between atopic condition and NHL as it would provide helpful insights
of the biological pathways involved in the relationship. Candidate genes
associated with allergy or asthma, including clusters of cytokines (e.g. IL4, IL13,
IL5 etc) and MHC class II region genes, are of particular interest (Cookson &
Moffatt, 2000). Several other approaches could be used. A GWAS x E analysis
could be performed, testing the interactions of allergic diseases with over million
192

SNPs. However, the lack of consensus on the most effective statistical approach
of detecting G-E interaction under genome wide scan is one of the major issues
that cause the delay in exploration in this field (Cornelis et al.).
In addition, a G X G analysis could be conducted, examining interaction between
loci of allergic disease identified from GWA studies with those identified from
NHL GWA studies which might provide information on novel.
As questionnaires remain as the best and sometimes the only way to
collect medical history in large epidemiological studies, they may pose practical
challenges in the ascertainment of atopic diseases, principally exposure
misclassification. Nevertheless, the gold standard measurement of atopy, total or
specific IgE levels may not be feasible in large scale studies. In a U.S. national
survey with the objective to assess questionnaire’s ability to predict biochemical
measure of atopy (e.g. IgE), substantial discordance between allergic conditions
self-reported in questionnaires and atopy status measured by total or specific IgE
has been observed (Hoppin et al.). Accurate capture of truly atopic participants
is critical in studying atopy-NHL association; otherwise, it may lead to a null
association or spurious association. Increasing questionnaires’ precision, such
as including questions regarding details of diagnosis of allergic disease,
medication use (both prescribed and over-the-counter medications), family
history of allergic disease may help in reducing misclassification. Nevertheless,
incorporating both questionnaire and biochemical measurement of atopy into
study is always one of the ideal solutions.
193

The large sample size in our pooled analysis made it possible to evaluate
subtype specific G-E interactions. Indeed, the significant interactions found in
the analysis were all B-cell subtype related. Although etiological heterogeneity of
NHL has largely been appreciated (Morton et al., 2008), the rarity of NHL and
thus the relatively small sample size makes it difficult to investigate by subtype,
thus important biological mechanisms might be missed. Therefore, collaboration
on NHL studies, nationally and internationally, with the benefits of sufficiently
large sample size, is increasingly critical to etiologic research. Currently, the
InterLymph Consortium promotes collaboration on case-control studies, while
collaboration on longitudinal studies is being encouraged through the NCI Cohort
Consortium, a future direction under which the investigation of allergy-NHL
association would greatly benefit by clarifying temporality. The current
participating studies in the Consortium come from all of the continents except
Asia (although a study is being planned), where the overall NHL incidence is
relatively low compared to North America, Europe, or Australia but a relatively
high incidence of T-/NK-cell NHL. Although T-cell NHL is much rarer than B-cell
NHL, it is clinically more aggressive and less incurable compared to some of the
indolent B-cell NHL. Understanding of T-cell etiological factors and molecular
pathogenesis will not only contribute to research depth but also benefit clinical
interventions.
In summary, although severe immune deficiency is more likely to be an
established risk factor for NHL, it only accounts for a very small proportion of all
194

the cases. This dissertation has provided support for a role of some common
immune-relation conditions, especially atopic conditions, on NHL susceptibility.
Next steps must be to search for underlying mechanisms and if possible, to
harness these for anti-lymphoma therapies and possibly prevention.

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Abstract (if available)

Abstract Non-Hodgkin lymphoma (NHL) is a highly heterogeneous group of neoplasms originating from B- or T- lymphocytes, with the vast majority of B-cell origin. It is believed that immune dysregulation plays an important role in the etiology of NHL. Currently, the strongest risk factor is immune deficiency, including primary or acquired immune deficiency, and immunosuppressive therapy after organ transplant. However, these conditions are rare in the general population and therefore do not account for the majority of the cases. A remaining key question is whether mild to moderate immune dysregulation could also contribute to NHL risk given that immune deficiency, especially severe immune deficiency, has been established as a strong risk factor. ❧ Extensive epidemiological studies have investigated the association between common immune-related diseases/conditions and NHL risk. Autoimmune or atopic diseases and infections are among those most studied. Autoimmune rheumatic conditions have been shown to increased NHL risk despite the debate regarding whether immunosuppressive therapy for autoimmune disease may also contribute to the development of NHL. Atopic diseases, on the other hand, have been consistently reported to be inversely associated with NHL risk in case-control studies although a disease effect cannot be ruled out: NHL may interfere with B-cell’s ability to produce immunoglobulin E (IgE). Surrogates for early life infections, such as later birth order and large sibship size, have been shown to be positively associated with NHL risk. ❧ Progress has also been made on understanding genetic susceptibility to NHL. Currently, the most consistent findings come from immune response genes, with evidence from both candidate gene and genome wide association studies. Particularly, tumor necrosis factor – alpha (TNF-α), interleukin-10 (IL-10), and lymphotoxin alpha (LTA) are among the best characterized and validated genes. ❧ The full spectra of the biologic mechanisms for NHL are not understood. However, the critical role of chronic antigenic stimulation in lymphomagenesis has been largely appreciated. Nevertheless, the nature of the immune dysfunction in terms of lymphomagenesis is still puzzling, e.g. both immune suppression (severe immunodeficiency) and stimulation (chronic B-cell activation) have been implicated in the pathogenesis of NHL. The objective of this dissertation was to understand how common immune-altering factors, including environmental stimulant (e.g. household endotoxin) and immune-related medical history, would affect risk for NHL in the general populations, with emphasis on atopic diseases and infections. ❧ We did not find any association between household endotoxin levels, measured from dust samples collected from participants’ vacuum cleaner bags, and NHL risk in a NCI/SEER multi-center population based case-control study. The null finding could be due to the nature of cross-sectional measurement of endotoxin or a single measurement which may not reflect a long term exposure. ❧ In a case-control study involving like-sexed twins discordant for NHL, common-immune related diseases or conditions were evaluated in terms of NHL risk. We found a strong inverse association between atopic disease, especially seasonal hay fever (OR = 0.28, 95%CI = 0.10-0.75) or allergy to specific substance (OR = 0.29, 95%CI = 0.13-0.68), and NHL risk. The inverse association was even stronger among dizygotic twins than monozygotic twins, which may suggest a potential gene-environment interaction in NHL etiology. A history of infectious mononucleosis was found inversely associated with NHL risk (OR = 0.35, 95%CI = 0.14-0.90). Childhood behaviors associated with risk of infection was positively associated with later life NHL risk, which is consistent with the finding of the positive association between later birth order / large sibship and NHL in current literature. ❧ Finally, to further clarify the true atopy-NHL association, we evaluated the interactions between atopic disease and established NHL-related immune response genes, including TNF-α, IL10 and LTA, on NHL risk. After taking into account of multiple testing, we did not find any significant interactions for all NHL combined. However, significant interactions were observed in subtype analysis after Bonferroni correction. LTA 252A>G may modify the association between asthma and Diffuse Large B-cell Lymphoma (P Interaction = 0.0004) and there was a significant interaction between IL10 -3575T>A and a history of both allergy and eczema on Chronic Lymphocytic Leukemia/Small Lymphocytic Lymphoma risk (P Interaction = 0.002). ❧ In conclusion, this dissertation has provided some evidence that mild to moderate immune-altering factors, particularly atopic diseases, may also affect risk of NHL. Future studies are needed to understand the underlying mechanisms.

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Asset Metadata

Creator Wang, Jun (author)

Core Title Common immune-related factors and risk of non-Hodgkin lymphomy

School Keck School of Medicine

Degree Doctor of Philosophy

Degree Program Epidemiology

Publication Date 11/19/2012

Defense Date 10/08/2012

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag atopy,endotoxin,Epidemiology,Etiology,immune-response genes,immunity,non-Hodgkin lymphoma,OAI-PMH Harvest

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Cozen, Wendy (committee chair), Akbari, Omid (committee member), Berhane, Kiros T. (committee member), Mack, Thomas M. (committee member), Stern, Mariana C. (committee member)

Creator Email jun.wang73@gmail.com,junw@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c3-115680

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