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Meat intake, polymorphisms in the NER and MMR pathways and colorectal cancer risk
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Meat intake, polymorphisms in the NER and MMR pathways and colorectal cancer risk
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Content
MEAT INTAKE, POLYMORPHISMS IN THE NER AND MMR PATHWAYS AND
COLORECTAL CANCER RISK
by
Amit Joshi
A Thesis Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF SCIENCE
(MOLECULAR EPIDEMIOLOGY)
May 2008
Copyright: 2008 Amit Joshi
ii
DEDICATION
To my parents,
Dr. Dolarray S. Joshi and Mrs. Hasumatiben D. Joshi
iii
ACKNOWLEDGEMENTS
This work would not have been possible without the critical input, invaluable insight,
encouragement and inspiration from my supervisor and committee chair Dr. Mariana C.
Stern. She introduced me to this field and provided a very stimulating environment to work
and learn. I very much appreciate her support and patience while writing this manuscript and
during graduate studies in general. I am also indebted to Dr. Kimberly D. Siegmund, Dr.
David V. Conti and Dr. Sue Ingles who have been of great help at various stages of this
thesis and provided me with a lot of great ideas to analyze the data.
I am grateful to Román Corral who has helped me a lot with genotyping and made working
in lab a pleasant experience. He is extremely resourceful and always ready to help. I also
wish to thank Dr. Charlotte Onland-Moret, currently at UMC Utrecht in The Netherlands for
assistance with data cleaning and Therese F. Teitsch at Darmouth University for data
management.
In addition, I would like to thank my family and friends for supporting me during the course
of my studies – especially my parents, who provided encouragement at all times. My best
friend, Siddharth Bhavsar, was amazingly selfless and invariably helped me in even the most
subtle situations and my house-mates Sagar Shah and Prasanth Nittala relieved me of many
responsibilities to facilitate my work. Special thanks to Manasvi Shah who bore the brunt of
my mood fluctuations and helped me with a quick review and correction of my thesis.
Lastly, I would like to thank Aaron and Stephanie Glenn for helping international students at
USC and creating a home away from home to help us with the transition.
iv
TABLE OF CONTENTS
DEDICATION ii
ACKNOWLEDGEMENTS iii
LIST OF TABLES v
ABBREVIATIONS vi
ABSTRACT vii
INTRODUCTION 1
METHODS 5
Study Subjects 5
Exposure Assessment 6
Genotyping 6
Data Analysis 7
RESULTS 10
Meat Intake and CRC Risk 10
NER and MMR SNPs and CRC Risk 14
Joint Analyses of NER and MMR SNPs and CRC Risk 18
Figure 1 AIC values for joint effects of MMR and NER SNPs 19
NER and MMR SNPS, Red Meat Intake, and CRC Risk 20
NER and MMR SNPS, Poultry Intake, and CRC Risk 22
DISCUSSION 24
BIBLIOGRAPHY 30
v
LIST OF TABLES
Table 1: Demographic characteristics of probands and siblings 12
Table 2. Red meat and poultry intake CRC risk 13
Table 3. Nucleotide excision repair SNPs and colorectal cancer risk 15
Table 4. Heterogeneity by Gender - Gene main Effects. 17
Table 5. Case-only analyses of interactions of XPD polymorphisms with red meat
level of doneness 21
vi
ABBREVIATIONS
AIC = Akaike Information Criteria.
DiMeIQx = 2-amino-3,4,8-trimethylimidazo[4,5-f]quinoxaline.
EM algorithm = expectation-maximization algorithm.
HCAs = heterocyclic amines.
MeIQx = 2-amino-3,8-dimethylimidazo[4,5-f]quinoxaline.
MMR = mismatch repair.
NER = nucleotide excision repair.
NOCs = N-nitroso compounds.
PAHs = polycyclic aromatic hydrocarbons.
PhIP = 2-amino-1-methyl-6-phenyl-imidazo[4,5-b] pyridine .
SCID = severe combined immunodeficiency.
vii
ABSTRACT
Red meat intake has been associated with colorectal cancer (CRC) risk with some
consistency and may result in exposure to carcinogens which can cause DNA damage. We
investigated whether variation in NER and MMR (DNA repair) pathways affect CRC risk
and modify the effect of meat intake, in a case-sibling study. We used conditional logistic
regression models to assess CRC risk – using the following exposure variables: frequency of
red meat, cooked red meat and poultry, level of doneness of red meat from inside and
outside and level of doneness of poultry. We tested for GxE interactions for all nine tested
SNPs and exposure variables. Consumption of more than 3 servings of red meat or cooked
red meat per week statistically significantly increased the risk of CRC. Case-only analysis
suggested that the effect of red meat heavily brown in the inside or outside was modified by
XPD-Lys751Gln SNP.
1
INTRODUCTION
A review of the epidemiological literature shows that consumption of red meat and
processed meat may be relevant risk factors in the etiology of colorectal cancer. The recent
World Cancer Research Fund and American Institute for
Cancer Research report on diet,
physical activity and cancer, elevated the strength of evidence – that red meat (“beef, pork,
lamb and goat from domesticated animals”) and processed meat (“preserved by smoking,
curing, or salting, or addition of chemical preservatives”) increase the risk of colorectal
cancer, to “convincing” (2007). A pooled analysis of prospective studies reported a
significant positive association between diets high in meat (defined as red meat and
processed meat, excluding poultry), red meat (defined as lamb, beef and pork) and
processed meat (such as sausages, meat burgers, ham and bacon) and risk of colorectal
cancer (Sandhu, White et al. 2001). A meta-analysis of case-control and cohort studies
published through 1999 reported a similar association for red meat (defined as beef, veal,
mutton, pork and lamb) and processed meat, but failed to find an effect of total meat (mostly
red meat) consumption (Norat and Riboli 2001). More recently, a meta-analysis of
prospective studies found a positive association between consumption of both red meat and
processed meat in colon cancer as well as rectal cancer (Larsson and Wolk 2006).
Various mechanisms, including exposure to carcinogens formed during the cooking
and processing of meats, have been hypothesized to explain the link between red meat
consumption and colorectal cancer (Potter 1999). The process of cooking, processing or
curing of meats results in the formation of three known carcinogens: heterocyclic amines
(Sugimura, Nagao et al. 1981; Nagao, Fujita et al. 1983; Wakabayashi, Nagao et al. 1992),
2
polycyclic aromatic hydrocarbons (Larsson, Sahlberg et al. 1983; Larsson 1986;
Wakabayashi, Nagao et al. 1992) and N-nitroso compounds (Panalaks, Iyengar et al. 1973;
Sen, Iyengar et al. 1976). HCAs can be found in dishes commonly consumed in North
America and Europe, with the highest yields observed at higher cooking temperatures for
PhIP, MeIQx and DiMeIQx (Layton, Bogen et al. 1995; Skog, Steineck et al. 1995; Knize,
Salmon et al. 1999). PAHs can be formed by fat pyrolisis when meat or fish are exposed to
direct flame. Well done grilled/barbecued red meat and poultry (Kazerouni, Sinha et al.
2001) can lead to high concentration of PAHs in food. NOCs can form in foods that have
been preserved using nitrates or nitrites (e.g. cured meats/sausages), or processed by
smoking or fire-drying (e.g. smoked/salted fish). NOCs can also be endogenously produced
in the colon lumen by the reaction of amines and amides with nitrosating agents such as
nitrites, which are present in many dietary factors (Forman 1987). Colonic flora contributes
to the accumulation of amines and amides which increases with high intake of meat-derived
protein (Bingham, Pignatelli et al. 1996). Human feeding studies have shown that increasing
amounts of red meat intake can increase intestinal N-nitrosation (Bingham, Pignatelli et al.
1996; Bingham, Hughes et al. 2002) and excretion of N-nitroso compounds and nitrites
(Hughes, Cross et al. 2001; Lewin, Bailey et al. 2006).
A few epidemiological studies have taken into account cooking methods and
doneness levels when investigating the role of red meat and poultry intake in colorectal
cancer. Some of them (Nowell, Coles et al. 2002; Butler, Sinha et al. 2003; Navarro, Munoz
et al. 2004) found a modest positive relationship between diets high in heavily brown red
meats and colorectal cancer; however, others reported no association (Le Marchand, Hankin
et al. 2002). Studies that have taken into account estimated levels of HCAs (Le Marchand,
3
Hankin et al. 2002; Nowell, Coles et al. 2002; Butler, Sinha et al. 2003), overall support a
role for HCAs in colorectal cancer risk, although results are not conclusive.
Different HCAs have been shown to induce colorectal tumors in animal models (Ito,
Hasegawa et al. 1991; Ohgaki, Takayama et al. 1991; Hasegawa, Sano et al. 1993; Ito,
Hasegawa et al. 1997). PAHs were shown to increase the spontaneous mutation frequency in
lacZ mice (Hakura, Tsutsui et al. 1998), and human colon epithelial cells treated with both
PAH and HCAs were able to form tumors at the site of injection in SCID mice (Herbst,
Fuchs et al. 2006). NOCs, such as nitrosamines, nitrosamides, and nitrosoguanidines also
can induce tumors in animal models (Forman 1987). These three activated carcinogens can
induce a variety of DNA damage that contributes to colon carcinogenesis, either in its
initiation phase and/or later in tumor progression. Specifically, HCAs can form DNA
adducts in the colon, considered the main extra-hepatic target of HCA adduct formation and
carcinogenicity, where they mostly induce G:T transversion (Turesky 2002). In addition,
HCAs have been reported to induce frame-shift mutations, microsatellite instability, strand
breaks and oxidative base damage (Turesky 2002; Pfau, Martin et al. 1999). There is
evidence that cells that have a deficiency in the mismatch repair enzymes tend to accumulate
more mutations after exposure to PhiP (Leong-Morgenthaler, Duc et al. 2001). Similarly,
PAHs can also induce bulky adducts, which have been associated with G:T and A:T
transversions (Miller and Ramos 2001), and have been detected in human colon
(Alexandrov, Rojas et al. 1996). Furthermore, PAH metabolism generates free radicals
which can induce base damages and strand breaks (Ramesh, Walker et al. 2004). NOCs can
alkylate DNA bases, which can lead to DNA miscodings and the spontaneous accumulation
of apurinic (AP) sites that can block DNA processes (Kyrtopoulos 1998). Aldehydes
generated by NOC metabolism can also induce DNA strand breaks (Sierra, Tosal et al.
4
2001). These types of DNA damage are repaired by different pathways. Bulky DNA-adducts
are repaired by the nucleotide excision repair (NER) pathway, whereas free radical induced
base damage and single strand breaks are repaired by the base excision repair pathway.
Mismatched bases are repaired by the mismatch repair (MMR) pathway and double strand
breaks are repaired by either the homologous recombination repair or the non-homologous
end-joining pathway. NOC-induced O
6
-mehtylguanine is removed by MGMT (Lawley
1990).
Given the potential role of carcinogens formed in cooked meats in colorectal
carcinogenesis through the formation of mutations in the colorectal lumen, a role for DNA
repair gene variants as susceptibility genes and effect modifiers is plausible. In the present
study, we report results of our investigations on the role of single nucleotide polymorphisms
(SNPs) in genes that participate in the NER (ERCC1 3’UTR G/T, XPD Asp312Asn, XPD
Lys751Gln, XPC Intron 11 C/A, XPA 5’UTR – C/T, ERCC4 Arg415Gln, ERCC5
Asp1104His) and MMR (MLH1 Ile219Val, MSH2 Gly322Asp) pathways. These SNPs were
selected based on their putative impact on protein function and/or previous evidence of
cancer risk associations. We report here the role of these SNPs in colorectal cancer (CRC)
and their role as potential modifiers of the effect of red meat and poultry intake.
5
METHODS
Study Subjects
We conducted a family-based case-control association study with subjects recruited
from the USC consortium of the Colon Cancer Family Registry (Colon-CFR)(Newcomb,
Baron et al. 2007). Briefly, incident cases with colorectal cancer were recruited through
population-based registries in either of the component centers of the USC consortium:
Arizona Cancer Center, Dartmouth College, University of Colorado, University of
Minnesota, University of North Carolina, and University of Southern California. A two stage
sampling approach was employed in which 33% of white subjects diagnosed with colorectal
cancer and 66% of subjects from other races were contacted in the first stage and screened
using a family history questionnaire. In the second stage of the study approximately 16% of
single-case families and all multiple case families were invited to participate in the study.
This approach was designed to increase the efficiency of finding a gene-environment
interaction(Haile, Siegmund et al. 1999). Unaffected siblings and cousins in the family of the
probands were selected as controls. Preference was given to older and same-sex controls. All
subjects
signed a written informed consent approved by the Institutional
Review Board of
each institution, donated a blood sample, and completed a risk factor questionnaire that
provided demographic
information, red meat, poultry, and vegetable intake and physical
activity among other factors, during an in-person interview. In our analyses, we only
included subjects recruited from the population-based registries; therefore, 51 probands and
40 siblings were excluded as they were recruited from Cleveland Clinic foundation, which
maintains a clinic based registry. We had risk factor data and biospecimens available for
genotyping for 577 probands, 371 siblings, and 364 cousins. In addition, 87.54% subjects
also completed a mailed food frequency questionnaire.
6
Exposure Assessment
For this study we used data collected with the baseline risk factor questionnaire,
which collected information regarding number of servings of red meat (beef, steak,
hamburger, prime rib, ribs, veal, lamb, bacon, pork, pork in sausages or venison) per week,
number of servings of red meat cooked by pan-frying, oven-broiling or grilling per week,
doneness of red meat from outside (lightly browned, medium browned and heavily
browned), level of doneness from inside (red, pink, brown), number of servings of poultry
(chicken, turkey, fowl) cooked by pan-frying, oven-broiling or grilling, and doneness of
poultry from outside (lightly browned, medium browned, level of doneness from outside).
In our analyses we defined “cooked” red meat or poultry as those cooked with either pan-
frying, oven broiling or grilling/barbecuing, which serve as surrogates for “high
temperature” methods, which are known sources of HCA and PAH formation.
Genotyping
DNA was extracted from peripheral blood lymphocytes by standard
methods,
resuspended in Tris-EDTA buffer (10 mM Tris, 1 mM EDTA),
and frozen until use.
Genotype analyses of all SNPs were done using Taqman assays from Applied Biosystems
(Foster City, CA). For quality control, approximately 6% randomly selected samples were
duplicated using a unique identification numbers and were blinded to laboratory personnel.
In addition there were 12 blank wells, serving as negative controls. We used an ABI 7900HT
Sequence Detection and Scoring System for allele scoring. We observed 100% concordance
between all duplicate samples. The calling rate for all assays ranged from 97.45% to
99.86%.
7
Data Analysis
We checked among siblings for differences between the observed
genotypic
frequencies and those expected under the Hardy-Weinberg
law using chi-square tests. These
tests were restricted to Caucasians who made up 82.6% of all siblings. Proband – sibling
comparisons were done using a 1: N matched conditional logistic regression approach. For
42.28% of probands (N=244), we had data collected on first degree cousins (N = 355). We
used data on these cousins to determine the median value for all exposure variables which
we used to dichotomize all variables, as we assumed that the distribution of these variables
among cousins would be more representative of the general population than among the
siblings. For analyses of meat intake, we tested for potential confounding with the
following variables: age at the time of interview (continuous), gender , past history of
Crohn’s disease (No/Yes), past history ulcerative colitis (No/Yes), past history irritable
bowel syndrome (No/Yes), past history diverticulitis (No/Yes), past history diabetes
(No/Yes), past history high cholesterol (No/Yes), Marital status (never married/ currently
married/ others) ,folate supplements (ever / never), weight-2 years before interview (tertiles),
weight at the age of 20 years (tertiles), height (tertiles), no of years in USA, BMI (tertiles),
aspirin/ibuprofen use (current/ former/ never) , physical activity (tertiles) ,fruits per week
(tertiles), vegetables per week (tertiles), level of education (high school or less/ vocational,
technical, some college or university/ bachelor's degree or graduate degree), income (4
categories) . Adjustment for any of the potential confounders did not change any of the odds
ratios of the exposure or gene variables by greater than 15 %. Hence, they were not
considered for further analysis of gene-environment interactions. For 87.54% of subjects we
also had dietary data obtained from FFQ on total caloric intake, total protein and total
saturated fat intake. Among these subjects we considered these variables as potential
8
confounders of meat intake variables and found no evidence that they changed estimates by
more than 7.1%; therefore, they were not included in our final models. For gene main effect
analyses, we assumed a dominant mode of action for all the SNPs and used conditional
logistic regression models, to determine matched ORs. Age and gender did not confound the
association between NER and MMR SNPs and colorectal cancer. Joint effects of more than
one SNP were considered and model selection was done using the Aikake Information
Criteria (AIC), by comparing models containing all the different combinations of the studied
SNPs fitted assuming a dominant mode of action (Akaike 1970). Haplotype probabilities
for SNPs in proximate chromosomal locations were calculated using E-M algorithm for
multi-heterozygous individuals (Excoffier and Slatkin 1995). We then performed a global
test for association using likelihood ratio tests. We tested for G x E interactions for all 9
SNPs and red meat and poultry variables using both a case-only design and proband-sibling
comparisons, using the exposure variables mentioned above. Testing for gene-exposure
interactions was done on a multiplicative scale. Case-only analyses were done using
unconditional logistic regression models and the dichotomized exposure was used as the
outcome variable, whereas individual SNPs were taken as the independent variables.
Proband-sibling analyses were done including in our regression model product terms
between the gene and exposure variables in addition to the terms present in the main effect
model and used likelihood ratio tests to compare these models to models that assumed no
interaction. We collapsed the site of tumors into two major groups: colon cancer (ICD-O-2
C180-C189, n=270) and rectal cancer (ICD-O-2 C199, C209, n = 307). Subjects having
tumors from cecum to the sigmoid colon were classified as having colon cancer and subjects
with the tumors of the recto-sigmoid junction or rectum were classified as having rectal
cancer. We tested for heterogeneity of the gene and exposures main effects across tumor
sites by assigning to controls the same code for tumor site as probands, and then adding a
9
product term between the gene or exposure and tumor site variable in the conditional logistic
regression model, thereby allowing their log odds to differ and testing the null hypothesis
that the log odds did not vary by tumor site. Similarly, we tested for heterogeneity of the
gene main effects between males and females. For case-only analyses of gene-environment
interactions, we tested for heterogeneity across tumor site by adding the product term
between genotype and tumor site, and the tumor site variable and comparing this to a model
that only included the genotype and tumor site using likelihood ratio tests. We controlled our
gene main effect and GxE estimates for multiple comparisons using the false-discovery rate
method (Benjamini and Hochberg 1995). All tests were two-sided and all analyses were
done using the statistical software STATA version 8 (STATA Corporation, College Station,
TX).
10
RESULTS
The demographic characteristics and descriptive statistics of probands and siblings
are shown in Table 1. The mean age at the time of interview was comparable between
siblings and probands (p = 0.364). Males constituted 52.34% of all the colorectal cancer
cases, whereas only 46.13% of the siblings in the study were males (p=0.064). The
proportion of colon cancer cases who were males (47.78%) was similar to siblings
(p=0.682). However, 56.35% of all rectal cancer cases in the study were males which was
statistically significantly different from controls (p=0.008). Despite these differences, gender
did not confound the relationship between any of the exposures in the study and rectal
cancer.
Meat Intake and CRC Risk
The association between the different meat intake variables and colorectal cancer
risk is shown in Table 2. Consumption of more than 3 servings of red meat per week
statistically significantly increased the risk of colorectal cancer (OR=1.8, 95% CI = 1.3-2.5)
as compared to those consuming three or less servings of red meat per week. Similarly, more
than 3 servings of red meat cooked by pan frying, oven broiling or grilling statistically
significantly increased the risk of colorectal cancer (OR =1.6, 95% CI = 1.3-2.5) . The
association between red meat intake and cancer did not vary by tumor site. We observed no
association between the level of doneness of red meat from either the outside or inside of the
meat and colorectal cancer risk. Similarly, we observed no association between intake of
more than 2 servings per week of poultry cooked by pan frying, oven broiling or grilling or
the level of doneness of poultry and colorectal cancer risk. However, intake of more than
11
two servings of poultry cooked by pan frying, oven broiling or grilling was inversely
associated with colon (OR=0.5, 95% CI = 0.3 – 1.0) but not rectal cancer (OR=1.2, 95% CI
= 0.7 – 1.9). This heterogeneity across tumor sites was statistically significant (p = 0.036).
Table 1: Demographic characteristics of probands and siblings
Siblings
( n = 362)
All Probands
( n = 577)
Colon cancer
(n= 270)
Rectal cancer
(n = 307)
Mean age at interview (SD) 59.25 (11.81) 59.95 (11.29) 59.56 (11.27) 60.29 (11.30)
Gender
Males 167(46.13%) 302(52.34%) 129 (47.78%) 173 (56.35%)
Females 195(53.87%) 275(47.66%) 141 (52.22%) 134 (43.65%)
Mean servings of red meat per week (SD) 4.43(4.11) 5.46(6.54) 5.28 (6.45) 5.62 (6.61)
Mean servings of cooked* RM per week (SD) 3.57(3.69) 4.52(6.19) 4.27 (6.10) 4.74 (6.27)
Doneness of red meat from outside (%)
Lightly browned 69 (19.17%) 98 (17.04%) 38 (14.18%) 60 (19.54%)
Medium browned 187 (51.94%) 298 (51.83%) 140 (52.24%) 158 (51.47%)
Heavily browned 104 (28.89%) 179 (31.13%) 90 (33.58%) 89 (28.99%)
Doneness of red meat from inside (%)
Red (rare) 52 (14.40%) 66 (11.48%) 29 (10.82%) 37 (12.05%)
Pink (medium) 139 (38.50%) 231 (40.17%) 114 (42.54%) 117 (38.11%)
Brown (well-done) 170 (47.09%) 278 (48.35%) 125 (46.64%) 153 (49.84%)
Mean servings of cooked* poultry per week (SD) 2.15 (3.14) 2.05 (3.07) 1.91 (3.02) 2.17 (3.11)
Doneness of chicken from outside (%)
Lightly browned 109 (30.19%) 176 (30.66%) 86 (32.09%) 90 (29.41%)
Medium browned 165 (45.71%) 256 (44.60%) 113 (42.16%) 143 (46.73%)
Heavily browned 87 (24.10%) 142 (24.74%) 69 (25.75%) 73 (23.86%)
12
Table 2. Red meat and poultry intake CRC risk
All sites Colon cancer Rectal cancer Hetero-
geneity
Exposure
variables
Co/Ca OR 95% CI p-
value
Co/Ca OR 95% CI p-
value
Co/Ca OR 95% CI p-
value
p-
value
Servings of Red meat
<3 / week 191/131 1.0* 88/56 1.0* 101/75 1.0**
> 3 / week 170/177 1.8 (1.3 - 2.5) 0.001 62/74 2.2 (1.3 - 3.7) 0.005 107/103 1.5 (1.0 - 2.5) 0.078 0.345
Servings of cooked** red meat
<3 / week 233/172 1.0* 98/75 1.0** 133/97 1.0**
> 3 / week 128/134 1.6 (1.1 - 2.2) 0.009 52/53 1.5 (0.9 - 2.6) 0.124 75/81 1.6 (1.0 - 2.5) 0.033 0.888
Doneness of red meat from outside
Light or medium
browned
256/214 1.0* 95/89 1.0** 160/125 1.0**
Heavily browned 104/94 1.1 (0.8 - 1.6) 0.559 54/41 0.8 (0.5 - 1.4) 0.400 48/53 1.5 (0.9 - 2.4) 0.128 0.099
Doneness of red meat from inside
Red/ Pink 191/153 1.0* 78/66 1.0** 113/87 1.0**
Brown 170/155 1.2 (0.8 - 1.6) 0.362 72/64 1.1 (0.6 - 1.9) 0.830 95/91 1.2 (0.8 - 1.9) 0.328 0.676
Servings of cooked** chicken
<2 / week 257/227 1.0* 107/104 1.0** 148/123 1.0**
> 2 / week 104/80 0.9 (0.6 - 1.2) 0.440 43/25 0.5 (0.3 - 1.0) 0.039 60/55 1.2 (0.7 - 1.9) 0.515 0.036
Doneness of chicken from outside
Light or medium
browned
274/238 1.0* 112/100 1.0** 160/138 1.0**
Heavily browned 87/69 0.9 (0.6 - 1.4) 0.765 38/29 0.9 (0.5 - 1.6) 0.747 48/40 1.0 (0.6 - 1.6) 0.910 0.867
* Reference Category
**Pan-fried, oven- broiled or grilled
13
14
NER and MMR SNPs and CRC Risk
We genotyped all probands and siblings for the following SNPs: MLH1 Ile219Val,
MSH2 Gly322Asp, ERCC1 3’UTR G/T, XPD Asp312Asn, XPD Lys751Gln, XPC Intron 11
C/A, XPA 5’UTR – C/T, ERCC4 Arg415Gln, ERCC5 Asp1104His.The minor allele
frequencies for each of the SNPs studied were similar to those reported in previous studies
(Naccarati, Pardini et al. 2007) (Table 3). We compared the observed genotypic frequencies
of the nine SNPs we studied, to those expected under the Hardy Weinberg principle among
siblings and found no statistically significant differences. For all SNPs we assumed a
dominant mode of action. We present in Table 3 ORs and 95% CI for all SNPs investigated
comparing probands (cases) to siblings (controls). We observed no evidence of an
association for any of the nine SNPs and colorectal cancer. However, we observed
statistically significant heterogeneity across tumor sites for the XPA 5’UTR SNP. The T
allele was inversely associated with colon cancer (OR = 0.4, 95% CI = 0.2 – 0.8) but not
rectal cancer (OR = 1.1, 95% CI = 0.7 – 2.0) (p-value for heterogeneity = 0.016). We also
observed a statistically significant heterogeneity between the effect of both the XPD SNPs
on risk of colorectal cancer among males and females (Table 4). Male cases were more
likely to carry at least one variant allele for both the SNPs, whereas females were more
likely to be homozygous for the more frequent alleles (p-for heterogeneity in XPD 751 SNP
= 0.0403, XPD 312 SNP = 0.0325).
We estimated haplotype probabilities for the two SNPS studied in the XPD gene
Asp312Asn (rs1799793) and Lys751Gln (rs13181) which are approximately 12kb apart. We
estimated that 98.10% of all double heterozygotes had Asp-Lys and Asn-Gln alleles and the
remaining 1.90% were formed by the combination of Asp-Gln and Asn-Lys alleles.
Table 3. Nucleotide excision repair SNPs and colorectal cancer risk
All sites Colon cancer Rectal cancer
Hetero-
geneity
Gene MAF Co/Ca OR 95% CI
p-
value Co/Ca OR 95% CI
p-
value Co/Ca OR 95% CI
p-
value
p-
value
MLH1 IIle219Val
Ile/Ile 0.288 194/161 1.0* 80/69 1.0* 111/92 1.0*
Ile/Val + Val/ Val 160/140 1.1 0.7 - 1.6 0.678 67/59 1.0 0.6 - 1.9 0.915 93/81 1.1 0.7 - 1.9 0.650 0.830
MSH2 Gly322Asp
Gly/Gly 0.021 348/291 1.0* 144/124 1.0* 201/167 1.0*
Gly/Asp + Asp/Asp 13/16 3.6 0.7 - 17.6 0.113 5/6 2.0 0.2 - 22.1 0.571 8/10 5.3
0.6 -
46.2 0.134 0.559
ERCC1 3'UTR
G/G 0.269 206/162 1.0* 82/69 1.0* 124/93 1.0*
G/T + T/T 153/142 1.3 0.8 - 1.9 0.255 66/59 1.2 0.6 - 2.2 0.622 84/83 1.4 0.8 - 2.4 0.275 0.704
XPD Asp312Asn
Asp/Asp 0.330 161/142 1.0* 73/65 1.0* 87/77 1.0*
Asp/Asn + Asn/Asn 200/165 1.0 0.6 - 1.4 0.813 76/65 1.0 0.5 - 1.9 0.911 122/100 0.9 0.6 - 1.6 0.831 0.962
XPD Lys751Gln
Lys/Lys 0.341 153/124 1.0* 62/56 1.0* 90/68 1.0*
Lys/Gln+Gln/Gln 209/184 1.2 0.8 - 1.8 0.447 88/74 0.9 0.5 - 1.8 0.778 119/110 1.4 0.8 - 2.4 0.229 0.325
XPC INTRON 11
C/C 0.388 139/117 1.0* 64/52 1.0* 74/65 1.0*
C/A+A/A 222/191 1.0 0.7 - 1.5 0.862 85/78 1.1 0.6 - 2.1 0.748 135/113 1.0 0.6 - 1.7 0.968 0.784
XPA 5'UTR
C/C 0.331 149/136 1.0* 52/61 1.0* 94/75 1.0*
C/T + T/T 200/166 0.8 0.5 - 1.2 0.211 91/66 0.4 0.2 - 0.8 0.011 109/100 1.1 0.7 - 2.0 0.641 0.016
ERCC4 Arg415Gln
Arg/Arg 0.098 313/265 1.0* 129/112 1.0* 181/153 1.0*
Arg/Gln + Gln/Gln 47/40 1.0 0.5 - 1.9 0.978 19/17 0.9 0.3 - 2.7 0.851 28/23 1.0 0.5 - 2.3 0.919 0.832
15
Table 3. Nucleotide excision repair SNPs and colorectal cancer risk (contd)
All sites Colon cancer Rectal cancer
Hetero-
geneity
Gene MAF Co/Ca OR 95% CI
p-
value Co/Ca OR 95% CI
p-
value Co/Ca OR 95% CI
p-
value
p-
value
ERCC5 Asp1104His
Asp/Asp 0.223 213/183 1.0* 85/75 1.0* 126/108 1.0*
Asp/His + His/His 148/125 1.0 0.7 - 1.6 0.950 65/55 0.9 0.5 - 1.9 0.835 82/70 1.1 0.6 - 1.9 0.807 0.753
* Unadjusted
** Reference category
16
Table 4. Heterogeneity by Gender - Gene main Effects.
Males Females
Heterogeneity
p-value
SNP Co/Ca OR* 95% CI p-value Co/Ca OR* 95% CI p-value
XPD Asp312Asn
Asp/Asp 79/65 1.0
REF
82/77 1.0
REF
Asp/Asn+Asn/Asn 87/95 1.9 0.8-4.3 0.1219 113/70 0.5 0.2-1.1 0.0826 0.0325
XPDLys751Gln
Lys/Lys 78/60 1.0
REF
75/64 1.0
REF
Lys/Gln+Gln/Gln 89/101 2.6 1.1-6.2 0.0302 120/83 0.7 0.3-1.5 0.3395 0.0403
* Unadjusted OR
17
18
The haplotype analysis was restricted to Caucasians. D-prime between the two loci
was calculated to be 0.793 and the R
2
was 0.549., which were similar to corresponding
values in the hapmap data. The global test for association between the XPD haplotypes and
colorectal cancer was not statistically significant (p=0.884). We next calculated similar
haplotype probabilities by adding a third SNP in the ERCC1 gene which is also in close
proximity to the XPD SNPs. There was no evidence of strong LD between the ERCC1
3’UTR G/T SNP and any of the two XPD SNPs or of association between XPD-ERCCI
haplotypes and disease status p-value for global test of association = 0.831).
Joint Analyses of NER and MMR SNPs and CRC Risk
To gain insight into the joint contribution of all candidate SNPs, we examined
models with all multivariate combinations of the 9 NER and MMR SNPs, ranked by AIC
(Conti and Gauderman 2004). Of the 512 different models tested, the rank of the null model
was eighth (AIC = 466.22). The model with the lowest AIC value (AIC = 464.601)
contained only the MSH2 Gly322Asp SNP. The maximum number of SNPs in a model that
ranked higher than the null model (fourth, AIC = 465.557) was 3 and it included MSH2
Gly322Asp, ERCC1 3’UTR G/T and XPA 5’UTR C/T (Figure 1).
Next we considered gene-gene interactions for all possible pairwise combinations of
the nine candidate SNPs (except for those in LD). We used a case only design for increased
statistical power. We observed statistically significant gene-gene interactions for the
following SNP combinations: ERCC4 Arg415Gln and MLH1 Ile219Val (IOR=1.9,
p=0.013), ERCC1 3’UTR G/T and MLH1 Ile219Val (IOR=0.7, =0.019), ERCC5
Asp1104His and ERCC4 Arg415Gln (IOR=0.5, p=0.009) and XPD Lys751Gln and XPA
Figure 1: AIC values for joint effects of MMR and NER SNPs (only SNPs with the lowest 25 AIC
values are shown).
MSH2 Gly322Asp
MSH2, XPA
MSH2, ERCC1
MSH2, ERCC1, XPA
NULL
464.5
465
465.5
466
466.5
467
AIC
0 5 10 15 20 25
Rank
19
5'UTR C/T (IOR= 0.7, p=0.018). Neither of these interactions remained statistically
significant after correcting for multiple comparisons.
NER and MMR SNPS, Red Meat Intake, and CRC Risk
We conducted analyses of gene-environment interactions using a case-only design,
for which we had higher statistical power and next compared our statistically significant
findings to those obtained using sibships. Provided that genes and exposure are independent,
ORs obtained from a case-only analyses can be used as estimates of interaction ORs
(Khoury and Flanders 1996) . We tested this assumption of independence between the genes
and exposures among the subset of cousins from the probands, and did not find any
statistically significant association between any of the SNPs and the exposures, after
correction for multiple comparisons. For our case-only interaction analyses we considered
total red meat intake, total red meat cooking by pan-frying, oven-broiling or grilling, level of
doneness of red meat on the inside, and level of doneness of red meat in the inside. We did
not find evidence that any of the nine SNPs modified the association between total red meat
intake, or total red meat cooked by pan-frying, oven-broiling or grilling and colorectal
cancer risk, or colon or rectum cancer separately. However, our data suggested that the effect
of red meat heavily brown in the inside or outside was modified by the XPD Lys751Gln
SNP (p < 0.001 for level of doneness inside and p = 0.006 for level of doneness outside,
case-only analyses) (Table 5). These findings remained statistically significant after
correcting for multiple comparisons. Similar findings, albeit with less statistical significance,
20
Table 5. Case-only analyses of interactions of XPD polymorphisms with red meat level of doneness
Test for Heterogeneity p-value
Colorectal cancer cases OR* 95% CI p-value Colon vs. Rectum Male vs. Female
Level of doneness outside Light or Medium/Heavy
XPD Asp312Asn
Asp/Asp 181|95 1.0
REF
Asp/Asn+Asn/Asn 215|83 0.7 0.5-1.0 0.0896 0.9742 0.5276
XPDLys751Gln
Lys/Lys 148|89 1.0
REF
Lys/Gln+Gln/Gln 247|90 0.6 0.4-0.9 0.0059 0.9759 0.9839
Level of doneness inside Red or Pink/Brown
XPD Asp312Asn
Asp/Asp 123|153 1.0
REF
Asp/Asn+Asn/Asn 174|124 0.6 0.4-0.8 0.0009 0.3786 0.4352
XPDLys751Gln
Lys/Lys 102|135 1.0
REF
Lys/Gln+Gln/Gln 194|143 0.6 0.4-0.8 0.0006 0.2794 0.7718
*Unadjusted
21
22
were observed for the XPD Asp312Asn, which is in high LD with Lys751Gln (p < 0.001 for
level of doneness inside, p = 0.0896 for level of doneness outside, case-only analyses). We
did not find evidence that the interaction between either XPD SNP differ by tumor site
(colon vs. rectum), or by gender (Table 5). We next compared the statistically significant
findings we observed for the Lys751Gln SNP to results of gene-environment interaction
analyses done using sib-pairs, for which we had slightly lower statistical power due to the
reduced number of cases. Our results for level of doneness of red meat in the inside showed
a weak similar trend, supporting an effect of internal heavily brown red meat only among
carriers of the XPD codon 751 Lys/Lys genotypes, although effects were modest (interaction
OR = 0.8, p = 0.539). Analyses of level of doneness of red meat level in the outside showed
stronger support for the case-only findings and an interaction of similar magnitude
(interaction OR = 0.6, p = 0.13), suggesting that intake of red meat heavily browned in the
outside is only associated with colorectal cancer among carriers of the XPD codon 751
Lys/Lys genotype (intake of heavily browned OR = 1.6; 95 % CI = 0.9-2.9 among carriers of
the Lys/Lys genotype and OR = 0.9; 95% CI = .6-1.4 among carriers of Lys/Gln or Gln/Gln
genotypes).
NER and MMR SNPS, Poultry Intake, and CRC Risk
Using case-only comparisons we observed that cases who consumed heavily
browned poultry were less likely to have the XPD codon 751 Gln allele (interaction OR =
0.6, p = 0.016) or the `A’ allele at the XPC intron 11 C/A locus (Interaction OR = 0.7, p =
0.031). Furthermore, cases who consumed greater than 2 servings of poultry cooked by pan-
frying, oven-broiling or grilling were less likely to be carriers of at least one copy of the `A’
allele in XPC intron 11(Interaction OR = 0.7, p = 0.040). These interactions” did not remain
23
statistically significant after correcting for multiple comparisons. However, it is worth noting
that case-sibling gene-environment interaction analyses for the XPC intron 11 SNP showed
interaction ORs of similar direction and magnitude of borderline statistical significance
(interaction OR = 0.5, p = 0.054 for cooked poultry, and interaction OR = 0.5, p = 0.084 for
poultry level of doneness). We did not find evidence of effect modification of high intake of
cooked poultry or its level of doneness by any of the other SNPs. Overall, results did not
differ by tumor site (colon vs. rectum).
24
DISCUSSION
In this study, we observed that consumption of more than 3 servings of red meat per
week increased the risk of colorectal cancer by 80% compared to intake of less than 3
servings per week. When considering only red meat cooked by pan frying, oven broiling or
grilling we observed a 60% increase in risk for above median consumption of red meat. In
our questionnaire, one serving was defined as 2-3 ounces of meat or a piece of meat about
the size of deck of cards. Assuming 1 serving to be 3 ounces, the difference in mean
between the two groups of red meat consumption (6.24 servings per week) is equivalent to
approximately 75 grams/ day. In other words, an increase in the consumption of about 75
grams/ day conferred an 80% increase in risk. The magnitude of this odds ratio (1.8) is
higher than the pooled summary statistic of 1.30 for every 100 grams/ day increase in
consumption of red meat reported in a pooled analysis of prospective studies (Sandhu et al
2001). When we modeled servings of red meat per week continuously, we observed an OR
of 1.4 for an increase in 75 grams / day of red meat consumption (approximately 1.6 for
every 100gm/ day increase). This increase in the magnitude of OR compared to the
previously reported pooled analyses can be due to various reasons: Firstly, it could be
attributed to the case-control study design used in our study which may lead to a recall bias.
Secondly, though this is a population based study, ascertainment was done using a sampling
scheme whereby subjects with a family history of colorectal cancer had a higher chance of
being recruited in the study. This could potentially result in biased estimates because of
disease heterogeneity. Thirdly, given that subjects in our study answered the food frequency
questionnaire and the risk factor questionnaire at different points in time we could not adjust
our models for some other dietary and nutrient factors that may have been potential
confounders of the relationship between meat and poultry and colorectal cancer, such as total
25
calorie intake, saturated fat, etc. The main objective of our study was to identify potential
effect modifiers among SNPs in the NER and MMR pathways. Given that potential
confounders of an exposure are unlikely to be confounders of the gene-exposure
relationship, lack of all potential confounding variables in our models is unlikely to
influence our findings. Nonetheless, our estimates for meat and poultry intake and colorectal
cancer need to be interpreted with caution due to the potential influence of unmeasured
confounders.
We did not find an association between consumption of heavily browned red meat or
poultry or between frequency of consumption of cooked poultry and colorectal cancer. In
contrast to our findings, a few other studies (Nowell, Coles et al. 2002; Butler, Sinha et al.
2003; Navarro, Munoz et al. 2004) reported a positive association between diets high in
heavily brown red meat and colorectal cancer; whereas other studies reported no association
(Le Marchand, Hankin et al. 2002). Studies done on colorectal adenomas, precursors of
colorectal cancer, are also inconclusive, with one prospective study that reported an
association between doneness of red meat and risk of adenomas (Sinha, Peters et al. 2005),
whereas two other case-control studies failed to find an association (Tiemersma, Voskuil et
al. 2004; Gunter, Probst-Hensch et al. 2005). Similarly association studies that took into
account different cooking methods and colorectal adenoma/cancer risk were inconclusive
(Butler, Sinha et al. 2003; Murtaugh, Ma et al. 2004; Navarro, Munoz et al. 2004; Gunter,
Probst-Hensch et al. 2005).
The results of our study suggest that the two SNPs that we studied in the XPD gene
may modify the effects of level of doneness inside and outside of red meat (beef, pork, lamb
and sausage). Our analyses using sibships supported these findings, albeit with less statistical
power. In particular, our main finding was that subjects who frequently ate heavily browned
26
red meat were at a higher risk of developing colorectal cancer if they were carriers of two
copies of Lys allele but not if they carried at least one copy of the Gln. To our knowledge,
few previous studies have looked into potential interactions between nucleotide excision
repair genes and intake of meat or poultry in colorectal cancer risk or colorectal adenoma
risk. In a Danish prospective study, Hansen et. al. reported no interactions between intake of
red meat, processed meat and white meat (fish and poultry) and genetic variants in the NER
pathway on colorectal cancer risk. Interestingly, they also reported heterogeneity by gender
between XPD Lys751Gln and colorectal cancer (Hansen, Sorensen et al. 2007). Berndt et. al.
did not report any statistically significant interaction between consumption of red meat and
NER variants in the causation of colorectal cancer (Berndt, Platz et al. 2006). However, both
these studies did not consider level of doneness or cooking methods.
It is biologically plausible that the XPD Lys751Gln could modify the effect of well-
done meats and colorectal cancer. The XPD protein functions in NER as an ATP dependent
5’ to 3’ DNA helicase. Its C terminal domain (CTD amino acids 478-759 which include
codon 751) interacts with the p53 protein (Seker, Butkiewicz et al. 2001). It is possible that
this polymorphism is in linkage disequilibrium with another polymorphism that may affect
the interaction of XPD with p53. In the same study, the authors reported that XPD
polymorphism at the 312 codon, but not the 751 codon, is associated with a 2.5 fold increase
in UV induced apoptosis lymphoblastoid cell lines from CEPH pedigree individuals from
Utah. Interaction with p53 is known to reduce the helicase activity of the XPD gene. Wang
et. al, hypothesized that inhibition of helicase activity may allow a stable formation of the
complex of the damaged DNA and the NER machinery, resulting in a more efficient
repair(Wang, Yeh et al. 1995). The literature for genotype-phenotype association studies for
XPD SNPs have been inconsistent, though more studies have reported higher DNA adduct
27
levels with the presence of the variant Gln allele (Matullo, Palli et al. 2001; Palli, Russo et
al. 2001; Pastorelli, Cerri et al. 2002; Benhamou and Sarasin 2005).
The inherent advantage in this family based study design was that we did not need to
control for population stratification in the analysis stage of the study when analyzing gene
effects. We did not find any main effect for the SNPs considered in our study. We found that
the effects of both the XPD SNPs were heterogeneous among males and females, and this
difference was not confounded by gender specific exposures such as smoking and alcohol.
Hansen et. al. reported a statistically significant heterogeneity in the same direction in their
study with the XPD Lys751Gln SNP, where male colorectal cancer cases were more likely to
carry at least one allele variant allele compared as opposed to being homozygous for the
more frequent allele, whereas females were less likely (Hansen, Sorensen et al. 2007). They
failed to see a similar interaction with the XPD Asp312Asn polymorphism. In contrast Zhou
et. al, found a borderline statistically significant interaction for the XPD Asp312Asn
polymorphism and gender and lung cancer risk. Though they failed to see an interaction
between the XPD Lys751Gln polymorphism and gender, the ORs among males and females
were in the same direction as our study (Zhou, Liu et al. 2002). Hansen et al. interpreted this
finding as a potential false positive, given that they did not see any differences on hormone
replacement therapy status or gender specific exposures such as smoking and alcohol. Since
this interaction is being reported in more than one study, we think that it deserves some
further attention.
For the SNP that had the highest minor allelic frequency in our study (MAF = 0.39),
we had 80% power to detect ORs as low as 2.0 (Gauderman 2002). We had a higher
representation of familial cases of colorectal cancer among our study subjects (34.97% of
cases with positive family history). It is widely known that genetic and epigenetic alterations
28
in the mismatch repair pathway leading to genomic instability have been associated with
HNPCC (Peltomaki 1994; Kuismanen, Holmberg et al. 2000), one of the familial forms of
the disease. While testing for the best joint effects model, it was encouraging to find that the
top-ranked model involved just one single SNP, a functional variant in the MSH2 gene. Our
family-based design using sibships, combined with modest number of sibships and the low
frequency of the minor allele for MSH2 Gly322Asp SNP (MAF = 2.1%), may have led to an
insufficient power to find a statistically significant association for the SNP. There was an
interaction between the ERCC4 and the ERCC5 polymorphisms in our study, but after
correction for multiple comparisons, it was not statistically significant.
Our study had several limitations. First, we only considered SNPs presumed to
impact protein function based on prior knowledge, rather than a comprehensive tag SNP-
based approach that would capture most of the genetic variation in each gene. This, coupled
with the modest sample size of our study, implies that we cannot completely discard the role
of these genes in colorectal cancer or their modification of the effect of meat and poultry
intake. Another limitation is that in these analyses, we did not utilize summary measures of
HCAs, PAHs and NOCs to determine which one might explain the association between
consumption of cooked meat and colorectal cancer. The formation of these compounds is a
function of temperature on the surface and the inside of the meat, cooking time, the type of
meat cooking or processing methods. Instead, we used data on frequency of intake of red
meat or poultry cooked by pan-frying, oven-broiling and grilling, which serves as a surrogate
measure for the formation of either HCAs or PAHs. The two variables that assessed level of
doneness in the inside or outside of the meat helped us capture a combination of cooking
temperature and time. A subset of the subjects in our study completed a food frequency
questionnaire that provides more detailed information on meat intake and cooking methods,
29
including estimates of HCAs and PAHs. Further analyses in this subset will help us confirm
and expand our findings. Additional studies using a more comprehensive genetic approach in
a larger study population are needed to confirm our preliminary findings.
30
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Abstract (if available)
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Asset Metadata
Creator
Joshi, Amit
(author)
Core Title
Meat intake, polymorphisms in the NER and MMR pathways and colorectal cancer risk
School
Keck School of Medicine
Degree
Master of Science
Degree Program
Molecular Epidemiology
Publication Date
03/10/2008
Defense Date
12/18/2007
Publisher
University of Southern California
(original),
University of Southern California. Libraries
(digital)
Tag
colorectal neoplasms,cooked meat,genetic variation,mismatch repair,nucleotide excision repair,OAI-PMH Harvest,proband-sibling study,single nucleotide polymorphisms
Language
English
Advisor
Stern, Mariana C. (
committee chair
), Conti, David V. (
committee member
), Ingles, Sue A. (
committee member
)
Creator Email
amitjosh@usc.edu
Permanent Link (DOI)
https://doi.org/10.25549/usctheses-m1040
Unique identifier
UC1279472
Identifier
etd-Joshi-20080310 (filename),usctheses-m40 (legacy collection record id),usctheses-c127-23063 (legacy record id),usctheses-m1040 (legacy record id)
Legacy Identifier
etd-Joshi-20080310.pdf
Dmrecord
23063
Document Type
Thesis
Rights
Joshi, Amit
Type
texts
Source
University of Southern California
(contributing entity),
University of Southern California Dissertations and Theses
(collection)
Repository Name
Libraries, University of Southern California
Repository Location
Los Angeles, California
Repository Email
cisadmin@lib.usc.edu
Tags
colorectal neoplasms
cooked meat
genetic variation
mismatch repair
nucleotide excision repair
proband-sibling study
single nucleotide polymorphisms