Cancer Epidemiology Biomarkers & Prevention Vol. 9, 217-219, February 2000
© 2000 American Association for Cancer Research
NAT1*10 and NAT1*11 Polymorphisms and Breast Cancer Risk1
Robert C. Millikan2
Department of Epidemiology, School of Public Health, Lineberger Comprehensive Cancer Center, School of Medicine, University of North Carolina, Chapel Hill, North Carolina 27599-7400
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Abstract
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Several recent epidemiological studies examined the association of
N-acetyltransferase (NAT) 1 and 2
genotypes and breast cancer risk. Taken together, these studies do not
support a strong role for the most common NAT alleles in
etiology of breast cancer. Only one study estimated odds ratios (ORs)
for the relatively rare NAT1*11 allele: a strong
positive association for the NAT1*11 allele and breast
cancer was reported, as well as strong combined effects for
NAT1*11-containing genotypes and two environmental
factors, smoking and red meat consumption. To further address the
association of NAT1*11 and breast cancer, an analysis
was performed using previously collected data from the Carolina Breast
Cancer Study, a population-based, case-control study conducted in North
Carolina. The OR for NAT1*11-containing genotypes and
breast cancer was 0.5 (95% confidence interval, 0.2–1.3) among white
women; ORs were not calculated among African Americans because only one
participant exhibited the NAT1*11 allele. There was no
evidence for combined effects of NAT1*11 and smoking.
Unfortunately, the results of both studies of NAT1*11
are imprecise and lack sufficient statistical power to address fully
the potential contribution of NAT1*11 to breast cancer.
These results illustrate that the limitations imposed by sample size,
as well as incomplete knowledge of biological function, need to be
considered when planning and interpreting studies of genetic
polymorphisms and environmental exposures.
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Introduction
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A recent study by Zheng et al. (1)
examined the role of
NAT3
genetic polymorphisms and breast cancer risk. NAT1 and
NAT2 are involved in detoxication of aryl amines found in
tobacco smoke and in activation of heterocyclic amines found in cooked
meat. The relationship between NAT genotype and breast
cancer risk has been examined in several recent studies
(2, 3, 4, 5, 6, 7)
. Several of these studies reported interactions
between NAT genotype and environmental factors (smoking or
diet), but these interactions were observed among subgroups
(e.g., pre- or postmenopausal women). The results are not
consistent across studies, and, taken together, they do not support a
strong role for NAT1 or NAT2 genotypes in risk of
breast cancer.
Zheng et al. (1)
reported a positive
association between the NAT1*11 allele and breast cancer
risk, as well as strong combined effects for NAT1*11
genotype and two environmental exposures, cigarette smoking and red
meat consumption. NAT1 encodes a variety of alleles,
including NAT1*3, NAT1*4, NAT1*10, and
NAT1*11. Correlations between NAT1 genotype and
metabolic phenotype are poorly understood (reviewed in Ref.
5
). However, recent evidence suggests that the enzyme
encoded by the NAT1*11 allele exhibits increased metabolic
activation of N-hydroxy aromatic amines, relative to protein
products of the NAT1*3 and NAT1*4 alleles
(reviewed in Ref. 1
). In the study of Zheng et
al. (1)
, the OR for NAT1*11/any genotype
(presence of one or more copy of the NAT1*11 allele)
compared to NAT1*3- or NAT1*4 -containing
genotypes (the more common alleles) was 3.9 (95% CI, 1.5–10.5). This
OR is based on 11 cases and 7 controls with NAT1*11/any
genotypes, out of a total of 154 cases and 328 controls. The OR for the
combination of NAT1*11/any genotype and ever smoking
(compared with the combination of NAT1*3- or
NAT1*4-containing genotypes and never smoking) was 13.2
(95% CI, 1.5–116.0), based on five cases and one control with
both exposures. The OR for the combination of NAT1*11/any
genotype and the highest tertile of red meat consumption (compared with
the combination of NAT1*3- or NAT1*4-containing
genotypes and the lowest tertile of meat consumption) was 6.1 (95% CI,
1.1–33.2), based on five cases and two controls with both exposures.
In contrast, the OR for NAT1*10/any genotype (compared with
NAT1*3- or NAT1*4-containing genotypes) was 1.3
(95% CI, 0.8 - 1.9). The OR for the combination of
NAT1*10/any genotype and smoking (compared with the
combination of NAT1*3- or NAT1*4- containing
genotypes and never smoking) was 1.4 (95% CI, 0.7–2.9), and the OR
for the combination of NAT1*10/any genotype and high levels
of red meat consumption was 1.6 (95% CI, 0.6–3.1). This study is the
first to report a positive association between the NAT1*11
allele and risk of cancer of any site and is also the first to
investigate interactions with environmental exposures.
To further examine the association of NAT1*11 and
NAT1*10 genotypes and breast cancer, previously collected
data from the Carolina Breast Cancer Study, a population-based,
case-control study of breast cancer, were used (5)
.
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Materials and Methods
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The study design of the Carolina Breast Cancer Study and methods
for genotyping of NAT1 and NAT2 have been
described previously (5)
. ORs for breast cancer and 95%
CI were calculated using unconditional logistic regression models to
examine associations for NAT1*10 and NAT1*11
alleles. PROC GENMOD of the software package SAS (version 6.11; SAS
Institute, Cary, NC) was used to incorporate offset terms derived from
sampling probabilities used to identify eligible participants and to
adjust for age (as an 11-level ordinal variable reflecting
5-year age categories) and family history (defined as the presence of
one or more first-degree relatives with breast cancer). Definitions of
smoking and menopausal status were used as described previously, and
race was classified according to self-report (5)
.
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Results
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ORs for NAT1*10/any and NAT1*11/any
genotypes and breast cancer, adjusted for age and family history of
breast cancer using logistic regression, are presented in Table 1
. There was no association for NAT1*10/any genotype and
breast cancer in African Americans or whites, and an inverse
association for NAT1*11/any genotype and breast cancer was
seen in whites. The latter estimate was very imprecise due to the low
frequency of the NAT1*11 allele. ORs for the joint effects
of genotype and smoking are presented in Table 2
. An inverse association with breast cancer for the combination of
NAT1*11/any genotype and smoking was observed among whites,
although the estimate was imprecise. The role of red meat intake was
not addressed because this information was not collected in our study.
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Discussion
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Our results do not support a role for NAT1*10 or
NAT1*11 alleles in breast cancer risk. Both our study and
the study of Zheng et al. (1)
observed ORs
close to the null value for NAT1*10/any genotype and for the
combined effects of NAT1*10/any genotype and ever smoking.
However, in contrast to Zheng et al. (1)
, we
did not observe strong main effects for NAT1*11/any genotype
or evidence of combined effects of smoking and NAT1*11/any
genotype.
There are several possible explanations for the differences between our
results and those of Zheng et al. (1)
. First,
there may be differences in the populations studied. Our study
population included African Americans (n = 391) and
whites (n = 563). We categorized as "white" seven
Native Americans, three Asian Americans, and three women who listed
their race as "multiracial." ORs for whites did not differ after
excluding these 13 individuals. The study population of Zheng et
al. (1)
was reported as "virtually all"
Caucasian. In our study, frequencies of the NAT1*10 allele
differed by race, but ORs for NAT1*10 genotype and breast
cancer were similar in African Americans and whites (Table 1)
. The
NAT1*11 allele was observed in only one African American.
Our study population was approximately half premenopausal and half
postmenopausal (5)
, whereas that of Zheng et
al. (1)
was entirely postmenopausal. We conducted
additional analyses stratifying on the basis of menopausal
status. ORs did not differ substantially in premenopausal
versus postmenopausal women, although estimates were
extremely imprecise. For example, in postmenopausal white women, the
adjusted OR for NAT1*11/any genotype (compared with
NAT1*3- or NAT1*4-containing genotypes) was 0.6
(95% CI, 0.1–2.7), and the OR for the combination of
NAT1*11/any genotype and ever smoking (compared with the
combination of NAT1*3- or NAT1*4-containing
genotypes and never smoking) was 0.4 (95% CI, 0.04 - 4.41).
Distributions of most traditional risk factors and associations with
breast cancer were similar in the two studies (1
, 5)
, and
the time period for case ascertainment in the study of Zheng et
al. (Ref. 1
; 1992–1994) overlapped that of our study
(1993–1996).
A second source of potential differences in results is that the methods
for genotyping NAT1 differed in the two studies. Both
studies used PCR/RFLP-based methods, but the assay of Zheng et
al. (1)
detected several alleles not detected by our
study: (a) NAT1*14; (b)
NAT1*15; (c) NAT1*17; and
(d) NAT1*22. These four alleles were quite rare
in the study of Zheng et al. (1)
, and failure
to include them in our analysis would not affect ORs for
NAT1*10/any genotype and NAT1*11/any genotype.
Allele frequencies (q) for NAT1*10 and
NAT1*11 did not differ significantly among controls across
the two studies. For NAT1*10, q = 0.17 for
controls in Zheng et al. (1)
and 0.21 for white
controls in our study (P = 0.18,
2 test). For NAT1*11,
q = 0.01 for controls in Zheng et al.
(1)
and 0.02 for white controls in our study
(P = 0.28). The similarity in allele frequencies among
controls suggests that the laboratory methods were comparable for
detecting these alleles. Methods for classifying dose and duration of
smoking differed in the two studies, but similar definitions for
"ever" and "never" smoking were used. Odds in both studies were
adjusted for age and family history (defined in both studies as "one
or more first-degree relatives with breast cancer").
The most plausible explanation for the difference in results
between our study and that of Zheng et al. (1)
is random error. The difference in ORs for NAT1*11/any
genotype is due to different estimates of allele frequency for
NAT1*11 among cases [q = 0.04 for cases in
Zheng et al. (1)
, and q = 0.01
among white cases in our study (P = 0.01)]. Because
NAT1*11 alleles are rare, differences in allele frequencies
among cases could have arisen due to chance. Assuming random error as
an explanation for differences in results, homogeneity Ps
(8)
were calculated comparing CIs derived from the study
of Zheng et al. (1)
and postmenopausal whites
in our study. These tests provide strong evidence for heterogeneity:
the P comparing CIs for the OR for NAT1*11/any
genotype (compared with NAT1*3- or
NAT1*4-containing genotypes) was 0.06; and the P
comparing CIs for the OR for NAT1*11/any genotype and
smoking (compared with NAT1*3- or
NAT1*4-containing genotypes and never smoking) was 0.03. The
sample sizes [308 cases and 656 controls for Zheng et al.
(1)
and 290 white cases and 273 white controls in our
study] yield roughly 80% power to detect an OR of 3.0 or greater
(0.33 or less) for genotypes with a frequency of 4% at a significance
level of 0.05 (9)
. However, neither study had adequate
power to estimate combined effects for NAT1*11 genotype and
environmental factors. Several methods for estimating sample size for
case-control studies of gene-environment interaction have been
developed (10, 11, 12)
. Even the most optimistic of these
methods suggest that over 2000 cases and 2000 controls would be needed
to investigate interactions between NAT1*11/any genotype and
smoking or red meat consumption. In addition, Rothman et al.
(13)
showed that the presence of even small amounts of
genotype or exposure misclassification can increase sample size
requirements substantially. Smith and Day (14)
remind us
that when sample size is limiting, "very many of the reported
‘significant’ interaction effects are no more than chance
observations." Thus, as concluded by Zheng et al.
(1)
, studies of gene-environment interaction based on
small numbers of participants should properly be regarded as
"preliminary."
The need for large sample sizes is an important challenge for
epidemiologists studying gene-environment interaction. The advent of
high throughput techniques will allow investigators to conduct
genotyping assays on large numbers of participants and increase power
to estimate gene-environment interactions (15)
. Empirical
Bayes’ methods may prove useful for addressing data sparseness and
associations arising due to chance (16
, 17)
. However, for
loci such as NAT1, where knowledge of biological function
and toxokinetics is incomplete, studies of gene-environment interaction
will continue to present significant challenges in interpretation.
Repetition in multiple study populations may contribute little to
causal inference. Thus, in addition to the problems of sample size and
statistical power, the limitations imposed by incomplete knowledge of
biological function need to be considered when planning and
interpreting studies that estimate joint effects for genetic
polymorphisms and environmental exposures.
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Acknowledgments
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I thank Drs. Christine Ambrosone, National Center for
Toxicological Research, Jefferson, AR, Andy Olshan, University of North
Carolina, Chapel Hill, NC, Charles Poole, University of North Carolina,
Chapel Hill, NC, and Nat Rothman, National Cancer Institute,
Bethesda, MD, for many useful discussions, as well as two anonymous
reviewers for helpful comments on the manuscript.
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Footnotes
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The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
1 Supported by Specialized Program of Research
Excellence in Breast Cancer, NIH/National Cancer Institute Grant
P50-CA58223. 
2 To whom requests for reprints should be
addressed, at Department of Epidemiology, CB #7400, School of Public
Health, University of North Carolina, Chapel Hill, NC 27599-7400.
3 The abbreviations used are: NAT,
N-acetyltransferase; CI, confidence interval; OR, odds
ratio.
Received 7/28/99;
revised 11/ 2/99;
accepted 11/30/99.
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Top
Abstract
Introduction
