Genetics of Maternal
Cigarette Smoking, Metabolic Gene Polymorphism, and Infant Birth Weight
Wang, MD, MPH, ScD; Barry Zuckerman, MD; Colleen Pearson, BA; Gary
Kaufman, MD; Changzhong Chen, MD; Guoying Wang, MD, PhD; Tianhua Niu, ScD;
Paul H. Wise, MD, MPH; Howard Bauchner, MD; Xiping Xu, MD, PhD, MS
Context Little is known about genetic susceptibility
to cigarette smoke in relation to adverse pregnancy outcomes.
Objective To investigate whether the association
between maternal cigarette smoking and infant birth weight differs by
polymorphisms of 2 maternal metabolic genes: CYP1A1 and GSTT1.
Design, Setting, and Participants Case-control study
conducted in 1998-2000 among 741 mothers (174 ever smokers and 567 never
smokers) who delivered singleton live births at Boston Medical Center. A
total of 207 cases were preterm or low-birth-weight infants and 534 were
non–low-birth-weight, full-term infants (control).
Main Outcome Measure Birth weight, gestation, fetal
growth by smoking status and CYP1A1 MspI (AA vs Aa
and aa, where Aa and aa were combined because of
small numbers of aa and similar results), and GSTT1 (present
vs absent) genotypes.
Results Without consideration of genotype, continuous
maternal smoking during pregnancy was associated with a mean reduction of
377 g (SE, 89 g) in birth weight (odds ratio [OR], 2.1; 95% confidence
interval [CI], 1.2-3.7). When CYP1A1 genotype was considered, the
estimated reduction in birth weight was 252 g (SE, 111 g) for the AA
genotype group (n = 75; OR, 1.3; 95% CI, 0.6-2.6), but was 520 g (SE, 124
g) for the Aa/aa genotype group (n = 43 for Aa, n = 6
for aa; OR, 3.2; 95% CI, 1.6-6.4). When GSTT1 genotype was
considered, the estimated reduction in birth weight was 285 g (SE, 99 g)
(OR, 1.7; 95% CI, 0.9-3.2) and 642 g (SE, 154 g) (OR, 3.5; 95% CI,
1.5-8.3) for the present and absent genotype groups, respectively. When
both CYP1A1 and GSTT1 genotypes were considered, the
greatest reduction in birth weight was found among smoking mothers with
the CYP1A1 Aa/aa and GSTT1 absent genotypes (-1285 g; SE,
234 g; P<.001). Among never smokers, genotype did not
independently confer an adverse effect. A similar pattern emerged in
analyses stratified by maternal ethnicity and in analyses for gestation.
Conclusions In our study, maternal CYP1A1 and GSTT1
genotypes modified the association between maternal cigarette smoking and
infant birth weight, suggesting an interaction between metabolic genes and
In the United States, 65% of all infant deaths occur among
low-birth-weight (LBW) infants (<2500 g); LBW infants account for 7.6%
of all live-born infants.1
The etiology of LBW is largely unknown, but both environmental and genetic
factors may play a role.2
Numerous studies have shown that maternal cigarette smoking during
pregnancy is associated with reduced birth weight or increased risk of LBW.3-8
In 1997, 13.2% of US women reported smoking cigarettes during pregnancy.1
Maternal cigarette smoking is identified as the single largest modifiable
risk factor for intrauterine growth restriction in developed countries.9,
10 However, not all women who smoke cigarettes
during pregnancy have LBW infants. The reason for this variability is
largely unknown, but may be related to maternal genetic susceptibility.
Tobacco smoke contains approximately 4000 compounds11;
the most important carcinogens in tobacco smoke are polycyclic aromatic
hydrocarbons (PAHs), arylmines, and N-nitrosamines.12
The ability of an individual to convert toxic metabolites of cigarette
smoke to less harmful moieties is important for minimizing the adverse
health effects of these compounds. Using PAHs as an example, the metabolic
processing of PAHs in humans involves 2 phases. The phase 1 metabolism is
an activation process, in which the inhaled, hydrophobic PAHs are
converted mainly through aryl hydrocarbon hydroxylase activity into
hydrophilic, reactive, electrophilic intermediates that can bind
covalently to macromolecules, especially DNA.13
These intermediates may be more toxic than the original form. Aryl
hydrocarbon hydroxylase, encoded by the CYP1A1 gene, is a
well-studied phase 1 enzyme and is particularly relevant to the metabolism
of chemicals in cigarette smoke. The phase 2 metabolism is a
detoxification process, in which these metabolic intermediates are
detoxified by enzymes such as glutathione S-transferases (GSTs) or uridine
diphosphate (UDP)-glucuronosyltransferase through transformation into
conjugated forms that are sufficiently polar to be excreted from the body.14
GSTT1, encoded by the GSTT1 gene, is a major phase 2 enzyme. There
is evidence that the adverse health effects of cigarette smoke may depend
on the combined effects of phase 1 and phase 2 metabolism.15-17
Both CYP1A1 and GSTT1 genes are highly polymorphic in the
and their polymorphisms have been associated with their encoded enzyme
22 The expression of different host genotypes may
explain varying susceptibility to the adverse health effects of cigarette
We hypothesized that the association between maternal cigarette smoking
during pregnancy and reduced birth weight or increased risk of LBW is
modified by maternal genetic susceptibility. In this report, CYP1A1
and GSTT1 gene polymorphisms are used to characterize genetic
susceptibility and to assess the interaction between metabolic genes and
cigarette smoking. We chose to focus on these specific gene polymorphisms
not only because such an interaction is biologically plausible, but also
in light of previous research that found evidence of interaction between
these gene polymorphisms and benzene exposure on gestation duration.23
In addition, these gene variants are common in our study population,
permitting us to examine gene–cigarette smoke interactions.
Study Site and Population
Between 1998 and 2000, we conducted a molecular epidemiological study on
environmental and genetic determinants of LBW (<2500 g) and preterm
birth (<37 weeks' gestation) among mothers who delivered at Boston
Medical Center, using a case-control design. Boston Medical Center serves
a multi-ethnic population of pregnant women, many of whom are from the
inner city. The overall rates of LBW and preterm birth are approximately
12% and 15% in this population compared with the national average of 7.6%
and 11.8%, respectively.1 More than 80% of
study mothers had at least 1 prenatal ultrasound examination; most
examinations were performed prior to 20 weeks' gestation. Cases were
defined as women who delivered singleton, live, LBW or preterm infants
regardless of birth weight; controls were matched for age and ethnicity
and were defined as women who delivered singleton, live, term infants with
birth weight 2500 g or more. Three controls were identified for every
case. Multiple-gestation pregnancies (eg, twins, triplets) or newborns
with major birth defects were excluded. The study protocol was approved by
the Boston Medical Center Institutional Review Board and by the
Massachusetts Department of Public Health.
Data Collection Procedures
All eligible cases, including those women who delivered on weekends and
holidays, were approached postpartum by our research staff. The
participation rate was 90% and 85% among approached eligible cases and
controls, respectively. There was no significant difference between
participants and nonparticipants in infant birth weight, maternal
ethnicity, or other sociodemographic characteristics. After informed
consent was obtained, a questionnaire interview was conducted to obtain
relevant information including demographic characteristics, cigarette
smoking, alcohol consumption, and medical and reproductive history.
Maternal and infant medical records were reviewed to obtain clinical data
including prenatal care, pregnancy complications, and birth outcomes
(infant's sex, gestational age, and birth weight). A maternal blood sample
was obtained and DNA was extracted according to standard protocol.24
The information on maternal smoking was based on maternal self-reporting
and was obtained for 4 time periods: 3 months before the index pregnancy
and the first, second, and third trimesters of the index pregnancy. In our
study sample, mothers' data were clustered in 3 groups in terms of
cigarette smoking: those who did not smoke throughout the index pregnancy;
those who smoked during early pregnancy but quit smoking during the first
trimester; and those who smoked continuously during the index pregnancy.
Only 1 woman who did not smoke in the 3 months before pregnancy or in the
first trimester began smoking in later pregnancy. None of the women who
continued to smoke cigarettes in the second trimester quit smoking in the
third trimester. Therefore, in the analysis, we defined "never
smoker" as those women who did not smoke cigarettes during any of the
4 time periods and used never smoker as the reference group. We defined
"ever smoker" as those who smoked any number of cigarettes
during any of the 4 time periods. We further divided ever smokers into 2
subgroups: quitter, only smoked in the 3 months before pregnancy or during
the first trimester; and continuous smokers, smoked continuously from
prepregnancy to delivery. We are unable to adequately evaluate the timing
of smoking in relation to birth weight given the smoking pattern in our
study sample. Maternal passive smoke exposure was grouped into 2
categories based on maternal self-reporting: unexposed or exposed to 1 or
more smokers at home during the index pregnancy.
The detailed method for detection of the CYP1A1 MspI polymorphism
can be found elsewhere.21 This method is
able to detect all 3 possible genotypes for the polymorphism: AA
(homozygous wild type), Aa (heterozygous variant type), and aa
(homozygous variant type). In our preliminary analysis, we evaluated 4
possible genetic models: dominant (AA = 0, Aa = 1, aa
= 1), recessive (AA = 0, Aa = 0, aa = 1), additive (AA
= 0, Aa = 1, aa = 2), and no restriction (no assumption
made). We found that the associations between maternal smoking and infant
birth weight differed considerably between the AA and Aa
genotype groups (mean, -234 g; SE, 99 g vs -577 g; SE, 126 g) but were
similar for the Aa and aa genotype groups (-577 g; SE, 126 g
vs -508 g; SE, 238 g). Thus, our data did not suggest a recessive model.
We combined the Aa and aa genotypes in the data analysis due
to the small number of enrolled mothers with the aa genotype.
The detailed method on detection of the GSTT1 deletion
polymorphism can be found elsewhere.20 This
method is only able to detect the present (at least 1 allele present, AA
or Aa) or absent (complete deletion of both alleles, aa)
Outcomes of Interest
Infant birth weight was evaluated as both a continuous and a binary
(<2500 g vs 2500
g) variable. Gestational age was assessed in 2 ways: time since the first
day of the last menstrual period and an algorithm based on last menstrual
period and the result of early ultrasound (<20 weeks' gestation). This
approach has been used in a large hospital-based preterm study.25
Briefly, the last menstrual period estimate was used only if confirmed by
an ultrasound within 7 days or if no ultrasound estimate was obtained;
otherwise, the ultrasound estimate was used. Gestational age was analyzed
both as a continuous and a binary (<37 vs 37
weeks' gestation) variable. Since the results were similar for gestational
age based on last menstrual period vs the algorithm, we present the
results based on the latter approach. We used birth weight ratio (observed
birth weight/mean birth weight for gestational age) as a continuous
measure of fetal growth and defined intrauterine growth restriction as
birth weight ratio less than 85%, an approach used in a previous study.26
We used multiple linear and logistic regression models to estimate the
individual and combined associations of maternal cigarette smoking and CYP1A1
and GSTT1 genotypes in relation to infant birth weight, gestation,
and fetal growth with adjustment of major covariates. We first examined
the association between maternal cigarette smoking and infant birth weight
without consideration of maternal genotypes. Then we investigated whether
the association between maternal cigarette smoking and birth weight was
modified by maternal genotypes by estimating the association between
maternal cigarette smoking and birth weight in maternal genotype groups of
each gene, respectively. Furthermore, we examined the combined association
of maternal cigarette smoking and maternal genotypes with birth weight in
8 subgroups. These subgroups were defined by maternal smoking status
during pregnancy (never vs continuous; the quitters were excluded from the
analysis due to small sample size) and by maternal genotype for CYP1A1
(AA, Aa/aa) and GSTT1 (present, absent).
Gene–cigarette smoke interaction was also tested by adding a product
term to the regression model. Similar analysis was applied to gestational
age and fetal growth. Finally, to address potential confounding by
population stratification, we performed the analysis stratified by
All the analyses were adjusted for the following potential confounders:
maternal ethnicity (white, black, Hispanic, other), age (<20, 20-24,
25-29, and 30
years), education (middle
school, = high school, and >high school), parity (0, 1, and 2),
marital status (married, other), prepregnant weight and height in both
linear and quadratic terms, passive smoking (no, yes), maternal
self-reported alcohol use (nonusers, current users), and infant sex. All P
values were 2-sided and defined as P = .05 for statistical
significance. We used statistical software SAS (SAS Institute Inc, Cary,
NC) for all analyses.
Our analysis included a total of 741 mothers: 567 never smokers and 174
ever smokers. A total of 207 cases were preterm or LBW infants (125 were
both preterm and LBW, 34 were LBW only, and 48 were preterm only) and 534
were non–LBW, full-term infants (control). As shown in Table
1, the never- and ever-smoking groups were similar in CYP1A1
and GSTT1 genotype frequencies, age distribution, maternal
prepregnancy weight and height, and infant sex. However, the 2 groups
differed in ethnicity, education, parity, marital status, passive smoke
exposure, and alcohol use. For the ever smokers, the mean birth weight was
280 g lower (95% confidence interval [CI], -413 to -147) and the odds
ratio (OR) for LBW was higher (OR, 1.8; 95% CI, 1.3-2.7) compared with the
never smokers. The mean gestational age for ever smokers was 0.8 weeks
shorter (95% CI, -1.3 to -0.2) and the OR of preterm birth was higher (OR,
1.8; 95% CI, 1.3-2.7).
As shown in Table
2, without consideration of genotype, continuous maternal smoking
during pregnancy was associated with an OR of 2.1 (95% CI, 1.2-3.7) for
LBW and a mean reduction of 377 g (SE, 89 g) in birth weight compared with
the never smokers. When CYP1A1 genotype was considered, the
association between continuous maternal smoking and LBW differed
remarkably by the genotype: the OR for LBW was 1.3 (95% CI, 0.6-2.6) among
mothers with the AA genotype (n = 75) but 3.2 (95% CI, 1.6-6.4)
among mothers with the Aa/aa genotypes (n = 43 for Aa
and n = 6 for aa). A similar pattern emerged when GSTT1
genotype was considered: the OR was 1.7 (95% CI, 0.9-3.2) and 3.5 (95% CI,
1.5-8.3) for the present and absent genotypes, respectively. Consistently,
when birth weight was analyzed as a continuous variable, continuous
maternal smoking was associated with a mean reduction of 252 g (SE, 111 g)
vs 520 g (SE, 124 g) in birth weight for the CYP1A1 AA and Aa/aa
genotypes, respectively; and a mean reduction of 285 g (SE, 99 g) vs 642 g
(SE, 154 g) in birth weight for GSTT1 present and absent genotypes,
We found a similar pattern for gestational age (Table
3). Without consideration of genotype, continuous maternal smoking was
associated with an OR of 1.8 (95% CI, 1.1-3.1) for preterm birth and a 1.0
week (SE, 0.4-week) shortening in gestation. When CYP1A1 genotype
was considered, the OR was 1.5 (95% CI, 0.8-2.8) and 2.2 (95% CI, 1.1-4.4)
for the AA and Aa/aa genotypes, respectively. When GSTT1
genotype was considered, the OR was 1.4 (95% CI, 0.8-2.6) and 2.8 (95% CI,
1.2-6.7) for the present and absent genotypes, respectively. When
gestational age was analyzed as a continuous variable, there were
reductions in mean gestational age of 0.6 (SE, 0.5) and 1.5 (SE, 0.5)
weeks for the CYP1A1 AA and Aa/aa genotypes,
respectively; and reductions of 0.5 (SE, 0.4) and 2.1 (SE, 0.7) week for GSTT1
present and absent genotypes, respectively.
We also examined the association of continuous maternal smoking and
maternal genotype with birth weight ratio (Table
4). When CYP1A1 genotype was considered, the OR of intrauterine
growth restriction was 1.9 (95% CI, 0.9-4.1) and 4.1 (95% CI, 2.0-8.6) for
continuous smokers with AA and Aa/aa genotypes,
respectively. The pattern was similar when birth weight ratio was analyzed
as a continuous variable. However, this pattern was not found with
stratification by GSTT1 genotype.
5 presents the combined association of maternal cigarette smoking and CYP1A1
and GSTT1 genotypes with infant birth weight, gestational age, and
birth weight ratio. There was a common pattern for the 3 outcomes. Among
nonsmoking mothers, genotype alone did not confer a significant adverse
effect. In the presence of maternal smoking, the greatest reduction in
mean birth weight (-1285 g; SE, 234 g), gestational age (-5.2 weeks; SE,
1.0 week), and birth weight ratio (-0.120; SE, 0.048) was found among the
group with the CYP1A1 Aa/aa and GSTT1 absent
genotypes. A test of interaction between maternal smoking and maternal CYP1A1
and GSTT1 genotypes was statistically significant for birth weight
and for gestational age, but not for birth weight ratio.
We performed separate analyses for blacks and whites, the 2 largest
ethnic subgroups in our sample with adequate numbers of smokers. The
percentages of CYP1A1 AA, Aa, and aa genotypes were
58.0%, 36.3%, and 5.8%, respectively, for blacks; 73.8%, 24.6%, and 1.6%,
respectively, for whites (2
test, P = .005). The percentage of GSTT1 absent genotype was
22.5% for blacks and 18.9% for whites (2
test, P = .39). As shown in Table
6 without consideration of maternal genotype, the association between
maternal smoking and infant birth weight was comparable for blacks and
whites. However, when the genotype was considered, the estimated smoking
effects were different between the 2 groups and gene-smoking interactions
were only statistically significant in blacks.
There were 38 mothers with either gestational diabetes or diabetes
mellitus in our study. Neither adjustment for diabetic status in the
regression model nor exclusion of diabetic mothers from the analysis
altered our results. Our data did not show significant differences in
pregnancy complications (preeclampsia, eclampsia, chronic hypertension,
diabetes, abruptio placentae, placenta previa, incompetent cervix,
oligohydramnios, polyhydramnios, meconium in amniotic fluid) nor
differences in method of delivery (vaginal vs cesarean) between never and
ever smokers. Further adjustment of pregnancy complications and type of
delivery in the regression analyses did not alter our results.
It has long been recognized that many human diseases arise from the
complex interplay of environmental exposures and host susceptibilities.
Our study represents the first step in investigating how genetic
susceptibility modulates risk of adverse reproductive outcomes from
environmental exposures such as cigarette smoke. Consistent with previous
studies, we found that maternal cigarette smoking was associated with
reduced birth weight and an increased risk of LBW,3-8
shortened gestation and an increased risk of preterm birth,8,
27-29 and intrauterine growth restriction.3,
9, 10 Our data indicate that
maternal cigarette smoking likely affects infant birth weight via both
reduced fetal growth and shortened gestation. More importantly, our study
shows consistent evidence that the adverse effects of maternal cigarette
smoking on infant birth weight and gestational age were modified by
maternal CYP1A1 and GSTT1 genotypes. Our data demonstrate
that a subgroup of pregnant women with certain genotypes appeared to be
particularly susceptible to the adverse effect of cigarette smoke,
suggesting an interaction between metabolic genes and cigarette smoking.
Although there are few published data on genetic susceptibility to
cigarette smoke in relation to birth weight or gestation, this
susceptibility is biologically plausible. Both CYP1A1 and GSTT1
genes are highly polymorphic in our study population. These gene
polymorphisms have been associated with their encoded enzyme activity; CYP1A1
MspI variant genotypes may increase enzyme activity,30
while the deletion type of GSTT1 leads to an absence of enzyme
There is evidence that increased CYP1A1 enzyme activity associated
with MspI variant genotype or absence of GSTT1 enzyme activity
associated with deletion genotype can be detrimental to pregnancy outcomes
in the presence of cigarette smoke exposure.
Major classes of carcinogens present in cigarette smoke are converted
into DNA-reactive metabolites by cytochrome P450–related enzymes and
some cytochrome P450 variants have been associated with increased risk of
various cancers.12 On the other hand, the GSTT1
enzyme is important in protecting against certain genotoxic damages, such
as sister chromatid exchanges32,
33 and the formation of hemoglobin adducts due to
ethylene oxide present in tobacco smoke.34
Everson et al35
tested human placental specimens for DNA adducts and found that DNA
adducts were almost exclusively present in those specimens from mothers
who were smokers. Positive dose-response relationships were shown between
levels of the smoking-related adducts and biochemical doses of maternal
tobacco smoke exposure during pregnancy. Alexandrov et al36
further demonstrated that the levels of benzo(a)pyrene diol-epoxide–DNA
adducts and bulky DNA adducts were significantly and positively correlated
with CYP1A1 enzyme activity. A similar finding was demonstrated in
another independent study.37
Furthermore, Perera et al38
found that newborns with elevated levels of PAH-DNA adducts had
significantly decreased birth weight (P = .05), birth length (P
= .02), and head circumference (P<.001) compared with newborns
with lower adducts (n = 135). Consistently, our study found that smoking
mothers who had CYP1A1 MspI variant genotypes or GSTT1
deletion genotype had lower birth weight and birth weight ratio and
shorter gestational age compared with the reference groups. Furthermore,
our study found that smoking mothers who had both CYP1A1 MspI
variant genotype and GSTT1 deletion genotype had the greatest
reduction in birth weight, gestation, and birth weight ratio.
A number of methodological limitations should be considered when
interpreting our results. Maternal smoking was based on self-report and
thus may be subject to reporting bias. Nevertheless, studies have shown
fair agreement between self-reported smoking amount and serum or urinary
level of cotinine (a biochemical marker of cigarette smoke).5,
39, 40 Our results are
consistent with the vast body of literature that demonstrates a
detrimental effect of cigarette smoke on the fetus. Maternal genotypes
were objective measurements and neither the mothers nor the research
staffs were aware of maternal genotypes at the time of interview and
medical record review.
Second, smoking mothers differed from never smokers in terms of
ethnicity, education, parity, marital status, passive smoke exposure, and
alcohol use. In the regression analyses, we adjusted for these variables.
However, we cannot exclude the possibility of confounding effects by
uncontrolled or inadequately controlled risk factors. For example, no
attempt was made to assess nutritional status. There could be comorbidity
between alcohol or illicit drug and tobacco use. Exclusion of alcohol or
illicit drug users from the analysis did not significantly alter the
Third, cigarette smoke is a complex mixture of chemicals3
and other metabolic genes may be involved. This study only examined CYP1A1
and GSTT1 genotypes. The relative role of metabolic genes vs other
genes in determining genetic susceptibility to adverse reproductive
outcomes of cigarette smoking is yet to be understood. Furthermore, there
is a possibility of unrecognized linkage disequilibrium between the
candidate marker and another gene that is the real susceptibility locus.
Population stratification is a potential issue in genetically
heterogeneous populations like that of the United States. This is an
inherent weakness of a case-control study design. A family-based
association study, such as transmission/disequilibrium testing, is more
desirable to address this issue. Assessing the confounding of interactions
is an evolving area of epidemiology. Factors that may not be confounders
in a regular analysis may still change the estimate of the effect of the
gene polymorphism–smoking interaction. In addition, we only examined
maternal genotypes, and the role of fetal genotypes in modifying the
adverse effect of cigarette smoke and maternal-fetal gene interaction
remains to be determined.
The rapid advances in the Human Genome Project, bioinformatics, and
biotechnology have provided unprecedented opportunities as well as
challenges in understanding the genetic basis for individual differences
in susceptibility to environmental exposures.41
As discussed in a recent commentary,42
much work remains to be done and many methodological challenges remain to
be addressed in this research area. A coherent gene-environment approach,
with attention to genetically susceptible populations who are
disproportionately exposed to environmental reproductive hazards, may
provide further insights into the etiology of intrauterine growth
restriction and preterm birth and may help identify high-risk
subpopulations for clinical or public health interventions.
Author Affiliations: Department of Pediatrics (Drs X. Wang,
Zuckerman, Wise, and Bauchner and Ms Pearson) and Department of Obstetrics
and Gynecology (Dr Kaufman), Boston University School of Medicine and
Boston Medical Center, and Program for Population Genetics, Harvard School
of Public Health (Drs Chen, Niu, and Xu), Boston, Mass; and Center for
Ecogenetics and Reproductive Health, Beijing Medical University, Beijing,
China (Dr G. Wang).
Author Contributions: Study concept and design: X. Wang,
Zuckerman, Pearson, Kaufman, Niu, Wise, Bauchner, Xu.
Acquisition of data: X. Wang, Zuckerman, Pearson, Kaufman, G.
Analysis and interpretation of data: X. Wang, Zuckerman, Chen,
Niu, Wise, Xu.
Drafting of the manuscript: X. Wang, Niu, Xu.
Critical revision of the manuscript for important intellectual
content: X. Wang, Zuckerman, Pearson, Kaufman, Chen, G. Wang, Niu,
Wise, Bauchner, Xu.
Statistical expertise: Chen, Niu, Xu.
Obtained funding: X. Wang, Zuckerman, Wise.
Administrative, technical, or material support: X. Wang,
Zuckerman, Pearson, Kaufman, Chen, Niu, Bauchner, Xu.
Study supervision: X. Wang, Zuckerman, Pearson, Kaufman.
Funding/Support: This study was supported in part by the
Department of Pediatrics of Boston University School of Medicine and
Boston Medical Center and by grant 20-FY98-0701 from the March of Dimes
Birth Defects Foundation.
Acknowledgment: We thank the nursing staff of Labor and Delivery
at the Boston Medical Center for their assistance in data collection, Ann
Ramsey, for administrative support, and Weili Chang, for blood sample
processing and data entry. We are grateful to Phillip Stubblefield, MD,
Michael Kramer, MD, and Richard Johnston, MD, for critical review of the
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