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Original Contribution
Urinary Melatonin Concentration and the Risk of Breast Cancer in Nurses’Health
Study II
Susan B. Brown*, Susan E. Hankinson, A. Heather Eliassen, Katherine W. Reeves, Jing Qian,
Kathleen F. Arcaro, Lani R. Wegrzyn, Walter C. Willett, and Eva S. Schernhammer
*Correspondence to Dr. Susan B. Brown, Division of Biostatistics and Epidemiology, University of Massachusetts, Amherst, 424 Arnold House,
715 North Pleasant Street, Amherst, MA 01003 (e-mail: snboyer@schoolph.umass.edu).
Initially submitted May 15, 2014; accepted for publication September 3, 2014.
Experimental and epidemiologic data support a protective role for melatonin in breast cancer etiology, yet studies
in premenopausal women are scarce. In a case-control study nested within the Nurses’Health Study II cohort, we
measured the concentration of melatonin’s major urinary metabolite, 6-sulfatoxymelatonin (aMT6s), in urine sam-
ples collected between 1996 and 1999 among 600 breast cancer cases and 786 matched controls. Cases were
predominantly premenopausal women who were diagnosed with incident breast cancer after urine collection and
before June 1, 2007. Using multivariable conditional logistic regression, we computed odds ratios and 95% confi-
dence intervals. Melatonin levels were not significantly associated with total breast cancer risk (for the fourth (top)
quartile (Q4) of aMT6s vs. the first (bottom) quartile (Q1), odds ratio (OR) = 0.91, 95% confidence interval (CI): 0.64,
1.28; P
trend
= 0.38) or risk of invasive or in situ breast cancer. Findings did not vary by body mass index, smoking
status, menopausal status, or time between urine collection and diagnosis (all P
interaction
values ≥0.12). For exam-
ple, the odds ratio for total breast cancer among women with ≤5 years between urine collection and diagnosis was
0.74 (Q4 vs. Q1; 95% CI: 0.45, 1.20; P
trend
= 0.09), and it was 1.20 (Q4 vs. Q1; 95% CI: 0.72, 1.98; P
trend
= 0.70) for
women with >5 years. Our data do not support an overall association between urinary melatonin levels and breast
cancer risk.
breast cancer; melatonin; 6-sulfatoxymelatonin
Abbreviations: aMT6s, 6-sulfatoxymelatonin; BMI, body mass index; CI, confidence interval; ER, estrogen receptor; NHS II,
Nurses’Health Study II; OR, odds ratio; ORDET, Hormones and Diet in the Etiology of Breast Cancer Risk; PR, progesterone
receptor; Q, quartile.
Recent meta-analyses of epidemiologic studies suggest
that women who work the night shift have a 19%–51% in-
creased risk of breast cancer (1–3). Decreased melatonin
production due to greater light exposure at night is a poten-
tial biological mechanism underlying this relationship.
Melatonin (N-acetyl-5-methoxytryptamine) is a naturally
occurring hormone produced primarily by the pineal gland
(4). The synthesis and release of melatonin is stimulated
by darkness and suppressed by light, with low circulating
levels observed during the day and the highest levels being
found at night between 2 AM and 4 AM (4). Melatonin is
metabolized through the liver and excreted in the urine,
and 6-sulfatoxymelatonin (aMT6s) is the main metabolite
of melatonin measured in urine for estimation of circulating
melatonin levels (4).
Multiple lines of evidence support potential antiestro-
genic, antioxidant, and antiproliferative properties of melato-
nin (4–6). Melatonin may influence estrogen signaling directly
at the tissue level through interaction with estrogen receptor or
indirectly via down-regulation of the hypothalamic-pituitary-
gonadal axis, resulting in reduced levels of circulating estrogens
(7,8). Further, melatonin has been shown to down-regulate
aromatase expression, thereby reducing local estrogen pro-
duction and suppressing tumor growth (8).
In addition to the potential estrogen-mediated pathways,
the activation of melatonin receptors, which bind melatonin,
155 Am J Epidemiol. 2015;181(3):155–162
American Journal of Epidemiology
© The Author 2015. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of
Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Vol. 181, No. 3
DOI: 10.1093/aje/kwu261
Advance Access publication:
January 13, 2015
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has been shown to inhibit breast tumor initiation, growth, and
cell proliferation (9). Further, in an in vitro study, melatonin
receptor 1 was associated with suppressed breast tumor growth
(10). Finally, the antioxidant properties of melatonin may
combat oxidative stress by suppressing tumor initiation and
promoting apoptosis (11).
Eight prospective epidemiologic studies (12–19)haveex-
amined this relationship, with conflicting results, due in part
to the relatively small sample sizes and short follow-up peri-
ods in prior studies, as well as the variation in methods of as-
sessing aMT6s levels. We conducted a prospective nested
case-control study of urinary aMT6s levels and breast cancer
risk among predominantly premenopausal women in the
Nurses’Health Study II (NHS II) cohort. The current analysis
was an extension of our previous report (13), with 6 addi-
tional years of follow-up and triple the sample size.
METHODS
Study population
NHS II is an ongoing prospective cohort study of 116,430
US female registered nurses aged 25–42 years at baseline in
1989. Self-administered questionnaires are completed bi-
ennially to update information on lifestyle factors, health be-
haviors, medical history, and incident disease. Between 1996
and 1999, a total of 29,611 women aged 32–54 years pro-
vided blood and urine samples and completed a short ques-
tionnaire to record the date and time of urine collection, the
number of night shifts worked in the past 2 weeks, and the
participant’s current weight, smoking status, and other life-
style variables. Among these women, 18,521 premenopausal
women who had not used oral contraceptives, been pregnant,
or breastfed within the past 6 months and had no personal his-
tory of cancer provided a single urine sample and 2 blood
samples timed with their menstrual cycle. The remaining
11,090 women (e.g., postmenopausal, using hormonal con-
traception, or not able to provide timed samples) contributed
an untimed sample. Urine samples were collected without
preservatives and were shipped overnight on ice to our labo-
ratory. Ninety-three percent of samples were received within
26 hours of collection, and we have previously demonstrated
that levels of urinary aMT6s remain stable when processing is
delayed for 24–48 hours (20). Samples have been stored in
the vapor phase of liquid nitrogen freezers (≤−130°C) since
collection.
Follow-up of the blood and urine substudy cohort was
close to 95%. The institutional review boards of Brigham
and Women’s Hospital (Boston, Massachusetts) and the Uni-
versity of Massachusetts, Amherst (Amherst, Massachusetts)
approved this analysis.
Assessment of breast cancer cases
We identified incident invasive and in situ breast cancer
cases by self-report on biennial questionnaires. Deaths were
reported by family members, reported by the US Postal
Service, or ascertained through the National Death Index.
A study physician performed medical record review to
confirm breast cancer cases and to abstract information on
invasiveness and hormone receptor status. If medical record
confirmation was not possible, the nurse participant con-
firmed her diagnosis, and these cases (n= 19) were included
in this analysis given that 99% of self-reported breast cancer
cases in this cohort are confirmed upon medical record re-
view. A total of 600 breast cancer cases were diagnosed
after urine collection and before June 1, 2007. As previously
reported (13), participants diagnosed with breast cancer by
June 2001 (n= 192) were matched with 2 controls, and the
present study additionally included case women diagnosed
after June 2001 (n= 408) who were matched with 1 control.
All cases were matched with controls by year of birth (±2
years), menopausal status at urine collection (premenopausal
vs. not), month/year (±2 months) and time (±2 hours) of urine
sample collection, luteal day of the menstrual cycle at urine
collection if the sample was timed (±1 day), fasting status at
urine collection (yes, no), and ethnicity (African-American,
Asian, Caucasian, Hispanic, or other).
Assessment of melatonin secretion
Nocturnal melatonin secretion was estimated by measur-
ing the concentration of the major urinary metabolite of mel-
atonin, aMT6s, in urine samples (80% first morning void;
20% randomly timed spot urine sample). In 2001, urinary
aMT6s was measured at the Endocrine Core Laboratory of
Dr. M. Wilson (Yerkes National Primate Research Center,
Emory University, Atlanta, Georgia) using a competitive
enzyme-linked immunosorbent assay (ALPCO Diagnostics,
Windham, New Hampshire) with a lower detection limit of
0.8 ng/mL. Urinary creatinine concentration was measured
in the same laboratory using a modified Jaffe method. From
2003 through 2007, urinary melatonin was measured at the
Ricchuiti Laboratory (now the Carroll Laboratory, Boston,
Massachusetts) using commercially available enzyme-linked
immunosorbent assay kits with a lower detection limit of
0.8 ng/mL (IBL International GmbH, Hamburg, Germany),
and urinary creatinine levels were measured using the COBAS
Integra 400 assay (Roche Diagnostics, Indianapolis, Indi-
ana). For each participant, urinary aMT6s was divided by
the urinary creatinine level to account for differences in urine
concentration, resulting in normalized urinary aMT6s values
expressed as ng/mg creatinine.
Assays were conducted in a total of 3 batches: 1 at Emory
University (2001) and 2 at Carroll Laboratory (2003/2005
and 2007 samples). Because the original data showed consid-
erable differences in absolute levels of aMT6s across batches,
we completed a drift recalibration project. A total of 45 urine
samples (15 control participants from each cycle: 2001,
2003/2005, and 2007) that represented low (n= 5), medium
(n= 5), and high (n= 5) tertiles of melatonin values per cycle
were sent to the Carroll Laboratory in 2013 and assayed as
described above. The correlation between the original assay
results and the reanalyzed results (samples analyzed in 2013)
was greater than 0.90 for all follow-up cycles, indicating that
the different assays were measuring the same analyte, though
with differing absolute levels. We used samples from the
original batches and the reanalyzed set of 45 samples to sta-
tistically account for laboratory drift over time. As described
elsewhere (21), we performed linear regression within each
156 Brown et al.
Am J Epidemiol. 2015;181(3):155–162
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batch to regress the rerun values on the original laboratory
values, and the resulting intercept and slope were used to pre-
dict recalibrated values for participants in that batch. Using
the recalibrated data, we created quartiles of creatinine-
adjusted melatonin levels based on the distribution in con-
trols for all analyses.
Masked replicate quality control samples (10% of sam-
ples) were included in each batch to assess the coefficient
of variation. Within-batch coefficients of variation in 3 total
batches ranged from 2.4% to 13.9% for melatonin and from
1.2% to 9.2% for creatinine. Samples for cases and controls
were treated identically, case-control sets were assayed to-
gether, and laboratory personnel were masked to the case/
control status of all specimens.
Statistical analysis
For this study, we selected NHS II participants who were
cancer-free at the time of urine collection (1996–1999) and
diagnosed with breast cancer between urine collection and
June 2007, as well as their matched controls. A total of
1,386 participants were eligible for this analysis after exclu-
sion of 6 observations that were either missing melatonin or
creatinine values or were identified as statistical outliers on
the log scale using the extreme Studentized deviate many-
outlier procedure (22). Urinary aMT6s measurements below
the lower detection limit of the assay (n= 10) were set equal
to the detection limit to produce conservative estimates.
We used conditional logistic regression to estimate odds
ratios and 95% confidence intervals in our primary analyses.
For subanalyses, we used conditional logistic regression if
the stratification variable was a case characteristic (i.e., inva-
sive breast cancer vs. in situ breast cancer) and sufficient
numbers were available (i.e., estrogen receptor (ER)-positive/
progesterone receptor (PR)-positive (ER+/PR+) status, time
between urine collection and diagnosis). Forother subanalyses
with limited numbers (i.e., ER+/PR−status, ER−/PR−status,
and stratification by smoking, body mass index (BMI; weight
(kg)/height (m)
2
), and menopausal status), we used uncondi-
tional logistic regression with adjustment for matching factors
to maximize statistical power. Tests for trend were performed
using melatonin as a continuous variable, and Pvalues were
calculated using the Wald statistic.
Data on lifestyle factors and other characteristics were
taken from the biennial questionnaire completed closest to
the time of urine collection, as well as the questionnaire com-
pleted at the time of blood and urine collection. In addition to
the matching factors (i.e., simple models), multivariable
models adjusted for age at menarche (≤11, 12, 13, or ≥14
years); parity and age at first birth combined (nulliparous,
1–2childrenand<25yearsatfirst birth, 1–2 children and
25–29 years at first birth, 1–2childrenand≥30 years at
first birth, ≥3 children and <25 years at first birth, or ≥3 chil-
dren and ≥25 years at first birth); age at menopause (premeno-
pausal, ≤45 years, or >45 years); alcohol intake (none, <5 g/day,
5–9 g/day, or ≥10 g/day); family history of breast cancer
(yes, no); history of benign breast disease (yes, no); and BMI
(continuous). To explore whether there were differing influ-
ences of BMI on premenopausal women and postmenopausal
women, we included an interaction term for BMI (<25, ≥25)
and menopausal status (premenopausal, postmenopausal)
in our model; however, this did not significantly affect our
estimates, and therefore the term was not retained in our
final models. Additional adjustment for oral contraceptive use
(never, past, or current), hormone replacement therapy (never,
past, or current), physical activity (metabolic equivalents/
week), chronotype (morning type, evening type, or neither),
smoking status (never, past, orcurrent), breastfeeding (ever or
never), and current use of antidepressant medication (yes, no)
did not alter our estimates; thus, these variables were not re-
tained in our final models.
To evaluate whether the association between melatonin
levels and breast cancer risk varied across strata of smoking
status at urine collection (never smoker or past/current
smoker), BMI at urine collection (<25, ≥25), menopausal
status at diagnosis (premenopausal or postmenopausal),
and time between urine collection and diagnosis (dichoto-
mized at the median as ≤5 years or >5 years), we added
an interaction term for each potential effect modifier (mul-
tiplying the dichotomous effect modifier by the midpoint
of each quartile of melatonin) to our model and used the
likelihood ratio test for interaction to determine statistical
significance.
All statistical tests were 2-sided; P< 0.05 was used to de-
fine statistical significance. Analyses were conducted in SAS,
version 9.2 (SAS Institute, Inc., Cary, North Carolina).
Table 1. Baseline Characteristics of 600 Cases and 786 Matched
Controls in Nurses’Health Study II, 1996–2007
Characteristic
a
Cases (n= 600) Controls (n= 786)
Mean (SD) % Mean (SD) %
Urinary aMT6s
concentration,
ng/mg creatinine
48.9 (31.8) 47.9 (29.6)
Age, years
b
43.9 (4.2) 44.0 (4.1)
Age at menarche,
years
12.4 (1.3) 12.4 (1.4)
Body mass index
c
25.0 (5.0) 25.7 (5.9)
Alcohol consumption,
g/day
4.2 (7.2) 3.6 (6.3)
Age at first birth, years
d
26.7 (4.7) 26.3 (4.6)
Parity
d
2.2 (0.9) 2.3 (0.9)
Nulliparous 21.4 19.1
Caucasian ethnicity
b
96.5 97.5
History of benign
breast disease
27.4 19.2
Family history of breast
cancer
16.5 10.1
Premenopausal at
urine collection
b
78.8 79.5
Abbreviations: aMT6s, 6-sulfatoxymelatonin; SD, standard deviation.
a
Values are standardized to the age distribution of the study
population. All characteristics except age were adjusted for age.
b
Matching variables included age, ethnicity, and menopausal
status at the time of urine collection.
c
Weight (kg)/height (m)
2
.
d
Among parous women only.
Urinary Melatonin and Breast Cancer Risk 157
Am J Epidemiol. 2015;181(3):155–162
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RESULTS
Our study comprised 1,386 participants, including 600
cases and 786 matched controls. Cases and controls were
similar with regard to most breast cancer risk factors, including
age at menarche, parity, age at first birth, and BMI (Table 1).
However, cases were more likely than controls to have a his-
tory of benign breast disease and a family history of breast
cancer. Participants were predominantly premenopausal at
diagnosis (79%), and the urine sample provided by the ma-
jority of women was a first morning sample (80%).
Among the 786 controls, the distributions of most base-
line characteristics, including age at menarche, age at first
birth, and parity, were similar across quartiles of creatinine-
adjusted aMT6s (Table 2). Controls in the highest quartile
of urinary aMT6s had a lower BMI than controls in the lowest
quartile (24 vs. 27). In addition, compared with those in the
lowest quartile of urinary aMT6s, controls in the highest
quartile were less likely to be past or current smokers (29.5%
vs. 42.5%).
Urinary aMT6s was not associated with the risk of breast
cancer overall (Table 3). Compared with women in the bot-
tom quartile of urinary aMT6s concentrations, the multivar-
iable odds ratio for women in the top quartile was 0.91 (95%
confidence interval (CI): 0.64, 1.28; P
trend
= 0.38). No signif-
icant associations were observed when we examined invasive
and in situ tumors separately. For invasive tumors, the odds
ratio comparing the top quartile of urinary aMT6s levels with
the bottom quartile was 0.94 (95% CI: 0.62, 1.43; P
trend
=
0.52), and for in situ tumors, the comparable odds ratio was
0.96 (95% CI: 0.48, 1.89; P
trend
= 0.67). In secondary analy-
ses, we restricted the data to women providing first morning
urine samples and excluded current night-shift workers, since
night-shift work may alter first morning urinary aMT6s lev-
els; however, our results were unchanged (data not shown).
In analyses stratified by tumor hormone receptor status, we
observed no association between urinary melatonin level and
ER+/PR+ tumors (n= 286 cases; for quartile 4 (Q4) vs. quar-
tile 1 (Q1), odds ratio (OR) = 0.94, 95% CI: 0.56, 1.58; P
trend
=
0.59). Further, no significant association or trend emerged be-
tween urinary melatonin level and ER+/PR−breast cancer risk
(n= 45 cases; for Q4 vs. Q1, OR= 1.07, 95% CI: 0.42, 2.72;
P
trend
= 0.78) or ER−/PR−breast cancer risk (n= 78 cases; for
Q4 vs. Q1, OR = 0.96, 95% CI: 0.47, 1.97; P
trend
= 0.96).
Next, we evaluated the association between urinary aMT6s
and breast cancer risk by duration of follow-up and other fac-
tors (Table 4). A nonsignificant 26% reduced risk of breast
cancer was observed among women diagnosed ≤5years
after urine collection (for Q4 vs. Q1, OR = 0.74, 95% CI:
0.45, 1.20; P
trend
= 0.09), whereas a nonsignificant increase
in risk was observed in women with >5 years between
urine collection and diagnosis (for Q4 vs. Q1, OR = 1.20,
95% CI: 0.72, 1.98; P
trend
= 0.70) (P
interact ion
= 0.12). The
suggestion of an inverse trend emerged among postmeno-
pausal women (for Q4 vs. Q1, OR = 0.71, 95% CI: 0.38,
1.34; P
trend
= 0.08), although the interaction by menopausal
status at diagnosis was not significant (P
interaction
= 0.64). Fi-
nally, no significant variation in the association was observed
across strata of BMI (P
interaction
= 0.33) or smoking status
(P
interaction
= 0.27).
Table 2. Baseline Characteristics of 786 Control Participants by Quartile of Urinary 6-Sulfatoxymelatonin
Concentration in Nurses’Health Study II, 1996–2007
Characteristic
a
Quartile of Urinary aMT6s Concentration
b
Q1 (n= 197) Q2 (n= 196) Q3 (n= 196) Q4 (n= 197)
Mean (SD) % Mean (SD) % Mean (SD) % Mean (SD) %
Age, years
c
44.8 (3.8) 44.1 (4.1) 43.2 (4.3) 43.8 (4.2)
Age at menarche, years 12.3 (1.5) 12.5 (1.4) 12.5 (1.3) 12.4 (1.4)
Body mass index
d
26.9 (6.3) 25.9 (6.5) 25.7 (5.1) 24.0 (4.9)
Alcohol consumption, g/day 3.5 (5.6) 3.9 (6.4) 2.8 (5.5) 4.3 (7.0)
Age at first birth, years
e
26.6 (4.5) 26.3 (4.8) 26.3 (4.7) 26.0 (4.3)
Parity
e
2.3 (0.9) 2.3 (1.0) 2.3 (0.9) 2.4 (0.9)
Nulliparous 18.7 20.6 17.8 16.5
Caucasian ethnicity
c
94.9 98.9 97.6 98.9
History of benign breast disease 17.6 22.1 18.3 19.3
Family history of breast cancer 8.5 10.6 11.3 10.4
Premenopausal at urine
collection
c
77.2 74.9 84.7 80.0
Abbreviations: aMT6s, 6-sulfatoxymelatonin; Q, quartile; SD, standard deviation.
a
Values are standardized to the age distribution of the study population. All characteristics except age were
adjusted for age.
b
Quartile ranges were as follows: Q1, ≤26.6 ng/mg creatinine; Q2, 26.7–42.5 ng/mg creatinine; Q3, 42.6–61.8 ng/
mg creatinine; Q4, ≥61.9 ng/mg creatinine.
c
Matching variables included age, ethnicity, and menopausal status at the time of urine collection.
d
Weight (kg)/height (m)
2
.
e
Among parous women only.
158 Brown et al.
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DISCUSSION
In this prospective study, we did not observe a significant
association between urinary melatonin levels and breast can-
cer risk overall. In our previous report, which included 147
invasive breast cancer cases and 291 matched controls from
the current expanded data set, women with the highest levels
of aMT6s had a 41% reduced risk of invasive breast cancer
(for Q4 vs. Q1, OR = 0.59, 95% CI: 0.36, 0.97) (13). In this
updated analysis with longer follow-up time and a greater
sample size, adding cases that occurred farther from the time
of urine collection, we observed an attenuation of our previ-
ously published results.
In total, 8 prospective studies of the melatonin–breast can-
cer relationship (12–19) have been conducted to date, includ-
ing 2 in premenopausal women (13,16), 3 in postmenopausal
women (14,15,19), and 3 in pre- and postmenopausal
women combined (12,17,18). A meta-analysis of 5 of the
8 previously published studies (18) found that women with
the highest aMT6s levels had a significantly reduced risk of
breast cancer overall (for Q4 vs. Q1, OR = 0.81, 95% CI:
0.66, 0.99), supporting a modest inverse association between
urinary melatonin levels and breast cancer risk based on
studies that used first morning or 12-hour urine collection
methods (18). Further, a significant inverse association
was observed in postmenopausal women (for Q4 vs. Q1,
OR = 0.68, 95% CI: 0.49, 0.92), but no association was re-
ported in premenopausal women (for Q4 vs. Q1, OR = 1.05,
95% CI: 0.71, 1.54) (18).
Among individual prospective studies carried out among
postmenopausal women, a significantly reduced (by 38%–
44%) risk of breast cancer was observed among women
in the highest quartile of melatonin level versus the lowest
quartile in 2 studies (14,15), whereas 1 study found no asso-
ciation (19). However, in the 3 studies that included both pre-
menopausal and postmenopausal women (127–251 cases),
no association between aMT6s levels and breast cancer risk
was observed (12,17,18). Various urine collection methods
were utilized in these studies, including 24-hour urine (12),
randomly timed spot urine (17), and first morning urine sam-
ples (18). Despite the moderate correlation of urinary aMT6s
levels between these methods (e.g., for first morning urine
and 24-hour urine, r=0.66(18)), methods such as 24-hour
urine collection may reduce interindividual variability and
fail to capture the nocturnal melatonin peak (23), resulting
in potential nondifferential exposure misclassification and
accounting, at least in part, for the null findings observed.
As described previously, a significant inverse association
was observed among predominantly premenopausal partici-
pants in our initial report of this relationship in NHS II
(13). In the only other study of premenopausal women, con-
ducted among women in the Hormones and Diet in the Eti-
ology of Breast Cancer Risk (ORDET) cohort (180 cases), a
positive association was observed between melatonin and in-
vasive breast cancer overall ( for Q4 vs. Q1, OR = 1.43, 95%
CI: 0.83, 2.45) (16). However, this association was attenuated
among current nonsmokers (OR = 1.00, 95% CI: 0.52, 1.94)
(16), which suggests that current smoking may alter rates
of metabolization of urinary melatonin. This is of interest, be-
cause cytochrome P450 1A2 is the primary enzyme in the
Table 3. Odds Ratios for Breast Cancer by Cancer Type and
Quartile of Urinary 6-Sulfatoxymelatonin Concentration in Nurses’
Health Study II, 1996–2007
Cancer Type and
Quartile of Urinary
aMT6s Level
a
No. of
Cases
No. of
Controls
Multivariable
OR
b
95% CI
Total breast
cancer
c,d
600 786
Q1 145 197 1.00 Referent
Q2 170 196 1.02 0.75, 1.40
Q3 125 196 0.79 0.56, 1.11
Q4 160 197 0.91 0.64, 1.28
Pfor trend 0.38
Invasive breast
cancer
422 551
Q1 103 138 1.00 Referent
Q2 117 144 0.92 0.64, 1.33
Q3 92 140 0.82 0.55, 1.23
Q4 110 129 0.94 0.62, 1.43
Pfor trend 0.52
In situ breast
cancer
159 193
Q1 36 48 1.00 Referent
Q2 51 38 1.90 0.93, 3.91
Q3 27 47 0.68 0.33, 1.42
Q4 45 60 0.96 0.48, 1.89
Pfor trend 0.67
ER+/PR+ breast
cancer
286 414
Q1 73 105 1.00 Referent
Q2 80 98 0.98 0.62, 1.55
Q3 58 110 0.67 0.41, 1.10
Q4 75 101 0.94 0.56, 1.58
Pfor trend 0.59
Abbreviations:aMT6s, 6-sulfatoxymelatonin; CI, confidence interval;
ER+, estrogen receptor-positive; OR, odds ratio; PR+, progesterone
receptor-positive; Q, quartile.
a
Quartiles were based on the distribution in control subjects.
Ranges were as follows: Q1, ≤26.6 ng/mg creatinine; Q2, 26.7–42.5
ng/mg creatinine; Q3, 42.6–61.8 ng/mg creatinine; Q4, ≥61.9 ng/mg
creatinine.
b
Multivariable conditional logistic regression models, in addition to
matching variables, included adjustment for the following breast
cancer risk factors: age at menarche (≤11, 12, 13, or ≥14 years);
parity and age at first birth combined (nulliparous, 1–2 children and
<25 years at first birth, 1–2 children and 25–29 years at first birth, 1–
2 children and ≥30 years at first birth, ≥3 children and <25years at first
birth, or ≥3 children and ≥25 years at first birth); age at menopause
(premenopausal, ≤45 years, or >45 years); alcohol intake (none, <5
g/day, 5–9 g/day, or ≥10 g/day); family history of breast cancer ( yes,
no); history of benign breast disease (yes, no); and body mass index
(weight (kg)/height (m)
2
; continuous).
c
The “total breast cancer”analysis included 422 invasive cases
and matched controls, 159 in situ cases and matched controls, and
19 self-reported cases and matched controls.
d
Simple OR and 95% CI for total breast cancer by quartile: Q1,
OR = 1.00 (referent); Q2, OR = 1.13 (95% CI: 0.84, 1.52); Q3,
OR = 0.81 (95% CI: 0.58, 1.12); Q4, OR = 0.98 (95% CI: 0.71, 1.34).
Urinary Melatonin and Breast Cancer Risk 159
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metabolism of melatonin to urinary aMT6s, and smoking has
been shown to stimulate cytochrome P450 1A2 activity (24,
25). In the present study, we did not observe substantial varia-
tion in analyses stratified by smoking status; however, the rate
of current smoking in the NHS II cohort (7%) was much lower
than that in the ORDET cohort (24.5%), which limited our
ability to separately explore associations in these subgroups.
Several studies attempted to explore whether preclinical
disease may influence melatonin levels in early follow-up cy-
cles or whether melatonin levels in the more distant past may
be more biologically relevant. Overall, 5 prior prospective
studies examined the impact of time between urine collection
and diagnosis on the association between urinary aMT6s
levels and breast cancer risk (14–16,18,19). Results were
inconclusive, with some investigators suggesting stronger
inverse associations when excluding the first several years
of follow-up after urine collection (14,16), some reporting
stronger positive associations for breast cancer cases that oc-
curred closer to the time of urine collection (19), and others
suggesting no difference in results by time between urine col-
lection and breast cancer diagnosis (15,18). Each of these
lagged analyses was limited by relatively modest numbers
of cases; thus, chance may be the most likely explanation
for the observed inconsistencies. In the present study, with
limited statistical power, we observed a nonsignificant in-
verse relationship between melatonin and breast cancer risk
in women with 5 or fewer years between urine collection
and diagnosis (for Q4 vs. Q1, OR = 0.71, 95% CI: 0.43,
1.17) and a nonsignificant positive association after more
than 5 years (for Q4 vs. Q1, OR = 1.20, 95% CI: 0.72,
2.02). Although these differences by follow-up time were
not significant (P
interaction
= 0.12), they may still serve as a po-
tential explanation for the discrepant findings between our
current updated analyses (overall null results) and our earlier
findings (13), in which aMT6s was significantly inversely
associated with breast cancer risk. Therefore, a detailed re-
evaluation (e.g., a pooled analysis including all prospective
studies) with both longer follow-up and greater power would
be useful.
In line with prior studies (13–16,19), we found that the as-
sociation between urinary aMT6s levels and breast cancer
risk does not vary by tumor estrogen receptor expression. A
Table 4. Odds Ratios for Breast Cancer by Quartileof Urinary 6-Sulfatoxymelatonin Concentration and Potential Effect Modifiers in Nurses’Health
Study II, 1996–2007
Potential Effect Modifier No. of
Cases
No. of
Controls
Quartile of Urinary aMT6s Concentration
a
Pfor
Trend
Pfor
Interaction
Q1 Q2 Q3 Q4
OR 95% CI OR 95% CI OR 95% CI OR 95% CI
Menopausal status at
diagnosis
b,c
536 710 0.64
Premenopausal 355 502 1.00 Referent 1.26 0.84, 1.88 0.86 0.57, 1.30 1.07 0.71, 1.62 0.85
Postmenopausal 181 208 1.00 Referent 1.03 0.56, 1.90 0.81 0.41, 1.58 0.71 0.38, 1.34 0.08
Body mass index
d
at time
of urine collection
c
600 786 0.33
<25 359 444 1.00 Referent 1.01 0.65, 1.57 0.96 0.61, 1.49 1.02 0.67, 1.57 0.95
≥25 241 342 1.00 Referent 1.25 0.79, 1.98 0.61 0.36, 1.01 1.09 0.65, 1.83 0.82
Smoking status at time of
urine collection
c
600 786 0.27
Never smoker 388 537 1.00 Referent 1.02 0.69, 1.50 0.68 0.45, 1.02 1.09 0.73, 1.62 0.95
Past/current smoker 212 249 1.00 Referent 1.21 0.72, 2.04 1.09 0.61, 1.93 0.91 0.53, 1.58 0.61
Time between urine
collection and
diagnosis, years
e
600 786 0.12
≤5 261 447 1.00 Referent 0.93 0.60, 1.45 0.71 0.43, 1.18 0.74 0.45, 1.20 0.09
>5 339 339 1.00 Referent 1.15 0.72, 1.82 0.88 0.54, 1.44 1.20 0.72, 1.98 0.70
Abbreviations: aMT6s, 6-sulfatoxymelatonin; CI, confidence interval; OR, odds ratio; Q, quartile.
a
Quartiles were based on the distribution in control subjects. Ranges were as follows: Q1, ≤26.6 ng/mg creatinine; Q2, 26.7–42.5 ng/mg
creatinine; Q3, 42.6–61.8 ng/mg creatinine; Q4, ≥61.9 ng/mg creatinine.
b
Women with missing or dubious data on menopausal status (n= 140) were excluded.
c
For menopausal status, body mass index, and smoking status, multivariable unconditional logistic regression was used with adjustment for
matching variables and the following breast cancer risk factors: age at menarche (≤11, 12, 13, or ≥14 years); parity and age at first birth
combined (nulliparous, 1–2 children and <25 years at first birth, 1–2 children and 25–29 years at first birth, 1–2childrenand≥30 years at first
birth, ≥3 children and <25 years at first birth, or ≥3 children and ≥25 years at first birth); age at menopause (premenopausal, ≤45 years, or >45
years); alcohol intake (none, <5 g/day, 5–9 g/day, or ≥10 g/day); family history of breast cancer (yes, no); history of benign breast disease (yes, no);
and body mass index (continuous).
d
Weight (kg)/height (m)
2
.
e
For time between urine collection and diagnosis, conditional logistic regression was used with adjustment for matching variables and the breast
cancer risk factors listed above.
160 Brown et al.
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moderate-to-strong inverse association between BMI and uri-
nary melatonin levels has been reported (12,20,26,27), but
this relationship has not been consistently observed (14–18).
In the present study, we found no evidence that the melatonin–
breast cancer risk relationship varied by BMI or menopausal
status (or a combination of the two variables) at diagnosis.
Given that few studies have explored the potential for effect
modification by BMI and/or menopausal status, confirmation
of these findings is warranted.
To our knowledge, this is the largest prospective study to
date to have examined the relationship between urinary
aMT6s levels and breast cancer risk. We were able to account
for most known breast cancer risk factors in our analyses, in-
cluding lifestyle and personal characteristics. First morning
urine measurements of aMT6s normalized to creatinine have
been shown to provide reliable estimates of overnight melato-
nin production (28), and a validated enzyme-linked immuno-
sorbent assay was utilized in this study. Furthermore, we had
excellent laboratory coefficients of variation, and we recali-
brated levels to account for variability in aMT6s levels across
laboratories. Medical records and pathology reports were used
to confirm self-reported breast cancer diagnoses, and 99% of
self-reported breast cancer cases in this cohort are confirmed
upon medical record review. Our study was limited because
aMT6s was measured in urine that was collected only once
per participant. However, the intraclass correlation over 3 years
among premenopausal women from the NHS II cohort was
high (intraclass correlation coefficient = 0.72), which sup-
ports a single morning urinary aMT6s measurement as a rea-
sonable marker for long-term melatonin levels (20).
In summary, we did not observe an association between uri-
nary melatonin levels and breast cancer riskoverall in this large
nested case-control study. Melatonin may play a role in various
phases of carcinogenesis, which may account for the conflict-
ing results observed in prospective studies to date. A pooled
analysis of existing data and additional large prospective stud-
ies with long follow-up and consistent methods of measuring
aMT6s are needed to confirm these findings.
ACKNOWLEDGMENTS
Author affiliations: Division of Biostatistics and Epidemi-
ology, Department of Public Health, School of Public Health
and Health Sciences, University of Massachusetts, Amherst,
Massachusetts (Susan B. Brown, Susan E. Hankinson,
Katherine W. Reeves, Jing Qian); Department of Veterinary
and Animal Sciences, College of Natural Sciences, Univer-
sity of Massachusetts, Amherst, Massachusetts (Kathleen
F. Arcaro); Department of Epidemiology, Harvard School of
Public Health, Boston, Massachusetts (Susan E. Hankinson,
A. Heather Eliassen, Lani R. Wegrzyn, Walter C. Willett,
Eva S. Schernhammer); Channing Division of Network
Medicine, Department of Medicine, Brigham and Women’s
Hospital and Harvard Medical School, Boston, Massachu-
setts (Susan E. Hankinson, A. Heather Eliassen, Walter C.
Willett, Eva S. Schernhammer); and Department of Nutrition,
Harvard School of Public Health, Boston, Massachusetts
(Walter C. Willett).
This research was supported by research grants R01
CA50385, R01 OH009803, and R01 CA67262 from the Na-
tional Institutes of Health. L.R.W. was supported in part by Na-
tional Institutes of Health training grant R25 CA098566.
We thank the following state cancer registries for their
help: Alabama, Arizona, Arkansas, California, Colorado, Con-
necticut, Delaware, Florida, Georgia, Idaho, Illinois, Indiana,
Iowa, Kentucky, Louisiana, Maine, Maryland, Massachusetts,
Michigan, Nebraska, New Hampshire, New Jersey, New
York, North Carolina, North Dakota, Ohio, Oklahoma, Ore-
gon, Pennsylvania, Rhode Island, South Carolina, Tennessee,
Texas, Virginia, Washington, and Wyoming.
Conflict of interest: none declared.
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