Mutagenesis vol. 26 no. 3 pp. 385–391, 2011
Advance Access Publication 30 December 2010
doi:10.1093/mutage/geq104
Seasonal variations in the levels of PAH–DNA adducts in young adults living
in Mexico City
W. A. Garcı́a-Suástegui, A. Huerta-Chagoya,
K. L. Carrasco-Colı́n, M. M. Pratt1, K. John1, P. Petrosyan,
J. Rubio, M. C. Poirier1 and M. E. Gonsebatt*
Departamento de Medicina Genómica y Toxicologı́a Ambiental, Instituto de
Investigaciones Biomédicas, Universidad Nacional Autónoma de México, A.P.
70-228, Ciudad Universitaria 04510, Mexico City, México and 1CarcinogenDNA Interactions Section, LCBG, Bldg.37 Rm 4032, National Cancer
Institute, National Institutes of Health, 37 Convent Dr. MSC-4255, Bethesda,
MD 20892, USA
*
To whom correspondence should be addressed. Tel: þ52 55 56229179; Fax:
þ52 55 56229182; Email [email protected]
Received on May 10, 2010; revised on October 29, 2010;
accepted on November 4, 2010
Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous
components of polluted air. The Mexico City Metropolitan
Area (MCMA), one of the most densely populated areas in
the world, is 2240 m above sea level. At this altitude, less
oxygen is available, making combustion less efficient and
therefore producing more PAH pollutants. According to the
Automatic Monitoring Network in Mexico City (RAMA, for
its Spanish initials; http://www.sma.df.gob.mx/simat2/informaciontecnica/index.php?opcion=5&opciondifusion_bd=90),
which performs environmental monitoring, the critical air
pollutants in Mexico City are ozone and particulate matter
(PM). PM emissions increase during the dry season (winter
to spring) and decrease during the rainy season (summer to
autumn). The bioactivation of some PAHs produces reactive
metabolites that bind to DNA, and the presence of elevated
levels of PAH–DNA adducts in tissues such as blood
lymphocytes represents an elevated risk for the development
of cancer. We have compared the levels of PAH–DNA
adducts and the percentage of cells with chromosomal
aberrations (CWAs) using a matched set of peripheral blood
lymphocytes obtained on two separate occasions from young
non-smoking inhabitants of the MCMA (n 5 92) during
the 2006 dry season and the following rainy season. PAH–
DNA adducts were analysed using the r7, t8-dihydroxy-t-9,
10-oxy-7,8,9,10-tetrahydrobenzo[a]pyrene (BPDE)–DNA
chemiluminescence immunoassay (CIA). The percentages
of CWA were determined in cultured lymphocytes from the
same individuals. Both DNA adduct levels and chromosomal
aberrations were tested for correlation with lifestyle and the
polymorphisms of cytochromes P450 CYP1A1 and CYP1B1
as well as glutathione-S-transferases GSTM1 and GSTT1.
The levels of PAH–DNA adducts were significantly higher (P
< 0.001) in the dry season (10.66 6 3.05 per 109 nt, n 5 92)
than during the rainy season (9.50 6 2.85 per 109 nt, n 5 92)
and correlated with the seasonal levels of particulate matter
with a diameter of £10 mm (PM10). The percentage of CWA
was not seasonally related; however, significant associations
between the number of risk alleles and adduct levels in the dry
(R 5 0.298, P 5 0.048) and in the wet seasons (R 5 0.473, P 5
0.001) were observed.
Introduction
One of the most densely populated cities in the world, the
Mexico City Metropolitan Area (MCMA), has 20 million
inhabitants, representing 18.6% of the national total according
to the 2nd Count of Population and Housing (1). The MCMA
is an elevated basin 2240 m above sea level. At this altitude,
23% less oxygen is available than at sea level, which makes
combustion less efficient and produces more polycyclic
aromatic hydrocarbon (PAH) pollutants (2). Additionally, the
MCMA is surrounded on the south, west and east by mountains
that inhibit the dispersion of pollutants. Climate conditions
vary during the year, with precipitation occurring mainly
between the months of May and October (rainy season) and
very scarcely from November until May (dry season). Thus,
critical air pollutants, such as volatile organic compounds
(VOC), which include PAHs and particulate matter (PM)
emissions, increase during the dry season and decrease during
the rainy season (2).
Studies designed to investigate the health risks associated
with PM emissions in the MCMA have reported that an increase
of 10 lg/m3 of PM caused an increment in mortality of 1.83 or
1.48% for particles with aerodynamic diameters of 10 lm
(PM10) or 2.5 lm (PM2.5), respectively (3,4). In addition,
epidemiological studies performed in US cities suggest an
increase in lung cancer risk in association with exposure to urban
air pollutants, particularly PM10 or PM2.5 (5).
Particulate emissions are by-products of fuel combustion,
motor vehicle use and industrial processing. Organic extraction
and analysis of PM in the southwest (SW) region of Mexico
City have shown that benzo[ghi]perylene, coronene and
indeno[1,2,3-cd]pyrene are the most abundant PAHs of the
17 analysed (6). These observations and those from samples
obtained 4 years later (7) indicate that the main emission
sources for PAHs in the airborne particle phase in the MCMA
are vehicles utilising the combustion of gasoline and diesel and
not the combustion of wood.
PAHs include a wide variety of genotoxic agents, result from
the incomplete combustion of organic matter, such as wood,
diesel or tobacco, and are ubiquitous components of environmental air pollution. Some PAHs have been classified as
carcinogenic agents by the US Environmental Protection
Agency (8) and the International Agency for Research on
Cancer (9). The weight of experimental evidence indicates that
binding of carcinogenic PAHs to DNA is a critical initiating
event in the process of tumour formation (10). PAH–DNA
adducts formation in white blood cells is considered to be
a biomarker of exposure to these compounds as well as an
indicator of cancer risk (11–15).
In previous studies, PAHs present in airborne PM collected
from industrial and residential regions of the MCMA were
significantly associated with concentration-related induction of
micronuclei in A549 human alveolar epithelial cells (16). In
addition, the direct-acting mutagenicity observed in Salmonella
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385
W. A. Garcı́a-Suástegui et al.
typhimurium strains TA98 and YG1021 correlated with the
monthly concentrations of PM10 in SW Mexico City. Emission
of direct-acting mutagens occurred mainly in the coldest
months of the year, and December showed the highest
mutagenicity (6).
PAHs require metabolic activation to interact with DNA and
form adducts. This activation is mainly accomplished by
members of the cytochrome P450 (CYP) superfamily like the
products of the CYP1A1 and CYP1B1 genes. Alternatively,
elimination of PAHs occurs by interaction with phase II
enzymes, such as the glutathione-S-transferases. There is
evidence from a number of studies that polymorphic variants
in these genes confer altered capacity to activate or detoxify
genotoxic compounds (17). Indeed, exposed individuals have
shown significant associations between the allelic variants
CYP1A1*2A, CYP1A1*2C, CYP1B1*3, GSTM1 null and
GSTT1 null and increased risk for chromosome aberrations
and/or PAH–DNA adducts (14,18–27).
Although the levels of VOC have been determined daily in
the MCMA (2), there have been no estimations of the levels
of PAHs present in these emissions. Estimations of
PAH–PM10 in the northern area of the MCMA demonstrate
seasonal variations (28). On the other hand, high levels of
particulate PAHs were found on the roadways of the MCMA
due to vehicle traffic (7). To estimate PAH exposures to
inhabitants of the MCMA, we performed a longitudinal
study in young non-smoking adults, determining the levels of
PAH–DNA adducts and the frequency of chromosomal
aberrations in peripheral blood lymphocytes during the dry
and rainy seasons, as well as their association with the risk
allelic variants of the cytochromes CYP1A1 (*2A, *2C and
*4) and CYP1B1 (*3) and the phase II enzymes GSTM1 null
and GSTT1 null.
Overall, we observed significant differences between the
average levels of PAH–DNA adducts, but not cells with
chromosomal aberrations (CWAs), during the dry and rainy
seasons. Correlation analysis revealed that some allelic variants
showed no seasonal differences. Also, the levels of PAH–DNA
adducts correlated with the seasonal levels of PM and with risk
alleles in some of the areas. These results are consistent with
the fact that inhabitants of the MCMA are exposed to higher
levels of PAHs and other xenobiotic compounds in the dry
season and lower levels in the rainy season.
Materials and methods
Study subjects
One hundred thirteen unrelated apparently healthy non-smoking 19- to
40-year-old volunteers, who remained in the MCMA for at least 6 months
prior to the study and through the next rainy season, were recruited for this
study. After a signed informed consent was obtained, the volunteers were
asked to complete a questionnaire concerning their age, residence area,
general health conditions, medications, smoking habits and exposure to Xrays and other genotoxic agents in the preceding 6 months. Peripheral venous
blood and urine samples were collected from each volunteer during the dry
season (March 1–31, 2006) and during the rainy season (August 22 to
September 27, 2006). Questionnaires, blood and urine samples were coded on
site for an unbiased analysis.
Determination of cotinine
Exposure of study participants to tobacco products within the past 48 h was
assessed by semi-quantitative determination of cotinine and hydroxycotinine
levels in urine using the Accutest NicAlert strip test (Jant Pharmaceutical Corp.,
Encino, CA, USA), according to the manufacturer’s protocol. Individuals
showing levels of cotinine and hydroxycotinine .100 ng/ml were considered
smokers and excluded from the analysis.
386
Extraction of DNA
DNA was extracted from buffy coat cells as described by Daly et al. (29). DNA
was dissolved in TE (10 mM Tris–HCl and 1 mM EDTA, pH 7.4) and stored at
20° C until use for the quantification of PAH–DNA adducts and genotyping.
Detection of DNA adducts
PAH–DNA adducts were analysed using the highly sensitive 10-oxy-7,8,9,10tetrahydrobenzo[a]pyrene (BPDE)–DNA chemiluminescence immunoassay
(CIA) (30), which has a limit of detection of 1.5 adducts/109 nt, using 20 lg
DNA. Samples collected from the same subjects in different seasons were
assayed on the same enzyme-linked immunosorbent assay plate to minimise
batch effects.
Lymphocyte cultures and analysis of chromosomal aberrations
Chromosomal aberrations were scored in the metaphase of whole-blood
lymphocyte cultures. Cells were grown in RPMI 1600 culture media
supplemented with L-glutamine (Sigma, St. Louis, MO, USA), nonessential
amino acids (Sigma) and 0.2 ml phytohaemagglutinin (Invitrogen, Carlsbad,
CA, USA) for 72 h, as described elsewhere (31). The cultures were arrested in
metaphase by the addition of 2 lg/ml demecolcine (Sigma) and further
incubated for 90 min. The cells were centrifuged, treated with 7.4 mM KCl
hypotonic solution for 20 min and washed three times with methanol:glacial
acetic acid (3:1) fixing solution. The pellets were finally re-suspended in 400 ll
of the fixing solution, and drops of the cell suspensions were placed on glass
slides and air dried. After staining with phosphate-buffered 2% Giemsa
solution, pH 7.2, the metaphases were observed under a microscope. In
successful cultures, 100 well-defined metaphases with .45 chromosomes were
analysed from each individual. The results of the analysis were expressed as the
percentage of cells containing chromatid and chromosomal gaps and breaks per
individual (CWA).
Genotyping
GSTM1 and GSTT1 deletion polymorphisms were determined simultaneously
after multiplex polymerase chain reaction, as described by Abdel-Rahman et al.
(32). Polymerase chain reaction–restriction fragment length polymorphism
assay analysis was used to identify CYP1A1*2A (33), CYP1A1*2C (34),
CYP1A1*4 (35) and CYP1B1*3 (36) polymorphisms. All primers were
obtained from Invitrogen.
Environmental monitoring
Data on PM10 and PM2.5 concentrations recorded at five monitoring stations,
representing the northwest (NW, Tlalnepantla), northeast (NE, Xalostoc), central
(C, Merced), southwest (SW, PM10 Pedregal and PM2.5 Coyoacan) and southeast
(SE, PM10 Cerro de la Estrella and PM2.5 UAM Iztapalapa) regions of the
MCMA, were collected from the RAMA database (37) to estimate 24-h average
mass concentrations in these regions during the 2006 dry and rainy seasons.
Statistical analysis
Allele and genotype frequencies among the study samples were calculated, and
deviation from Hardy–Weinberg equilibrium was examined with the v2 test.
The paired t test and the non-parametric Wilcoxon paired-sample test were
applied to compare the differences between the dry and the rainy seasons for
PAH–DNA adduct levels and the %CWA in subjects grouped by genotype,
respectively. To compare PAH–DNA adduct levels and %CWA between
genotypes during both seasons, the Mann–Whitney U test was used. Multiple
linear regression analyses were performed to evaluate the relationship between
the PAH–DNA adduct levels from the 92 paired samples (both in dry and rainy
seasons) and the PM emissions. To investigate the relationship between PAH–
DNA adduct levels, the different allelic variants were grouped by genotype and
place of residence (NW, NE, etc) and coded as follows: 0 (wild type
homozygous), 1 (heterozygous, one variant allele) and 2 (mutant homozygous).
In the case of GSTM1 and GSTT1, the presence of allele was coded 0 and the
null genotype was coded 2 since the presence of GSTM1 or GSTT1 in
homozygous or heterozygous condition has not been associated with increased
adduct levels (19,21,38–40). To explore the additive effect of risk alleles and
adduct levels, the sum of risk alleles was computed for each individual and
a linear regression was performed. In all statistical tests, P , 0.05 was
considered statistically significant. The analysis was performed using Stata for
Windows (version 10.1).
Results
Study population
Of the initial 113 volunteers, 12 were absent during the second
sampling period and 9 who showed levels of cotinine in
PAH-DNA adducts in young adults living in Mexico City
urine .100 ng/ml indicative of smoking were excluded from
the study. The total number of paired samples analysed in the
longitudinal study was 92. The volunteers were unrelated 42
males and 50 females, between 19 and 40 years of age, with
a mean weight of 65.02 12.82 kg, a median height of 1.66 0.09 m and a body mass index of 23.32 3.22 kg/m2 (Table I).
No significant effects on the levels of adducts or the % of
CWAs were observed due to residence location, age, body
mass index, consumption of vitamins or medical drugs (data
not shown).
Particles and air quality data
The data collected from RAMA (37) were used to estimate the
24-h average PM2.5 and PM10 mass concentrations. The 24-h
averages at five representative residential locations (northwest,
northeast, central, southwest and southeast) of the MCMA
were analysed during the dry and rainy seasons and the results
are shown in Figure 1. During the dry season, higher PM10 and
PM2.5 concentration measurements were reported (see median
values in Figure 1).
The highest median values (P , 0.05) for PM10 were
observed at Xalostoc in the NE portion: PM10 5 101 (47–224)
lg/m3 in the dry season and PM10 5 51 (20–123) lg/m3 in the
rainy season. At this monitoring station, the levels of PM10
during the dry season sometimes exceeded the 120 lg/m3
standard of the Official Mexican Norm (NOM). This is
consistent with the heaviest density of industrial activity and
mobile sources being in the NE portion of the Mexico City
basin. Central, SE and NW portions of the basin showed more
mid-range median concentrations. The variability in daily
PM2.5 mass concentrations observed was low compared with
daily PM10 concentrations. Central and NW portions showed
the highest values (P , 0.05) and variability.
PAH–DNA adducts
Significant differences were observed when the mean levels of
PAH–DNA adducts in both seasons were compared (10.66 3.05 dry season versus 9.50 2.85 rainy season, P 5 0.0001,
Table I and Figure 2). The larger and significant seasonal
changes in adduct levels were observed in those volunteers
who showed .9.9 adducts per 109 nt during the winter (dry
Table I. Demographic variables stratified by sex
Number of volunteers
Male
Dry season
53
Rainy season
42
Smokers (excluded)
7
Non-smokers, both seasons
42
Age
24.10 4.24
Weight (kg)
72.29 12.95
Height (m)
1.72 0.08
BMI
23.34 3.25
PAH–DNA
Dry season
10.61 3.22*
Rainy season
9.29 3.03
a
%CWA (without gaps)
Dry season
0.47 0.71 (N 5 40)
Rainy season
0.62 0.80 (N 5 41)
Female
60
50
2
50
25.65 58.72 1.61 22.48 5.37
8.95
0.07
2.86
10.93 2.85**
9.9 2.58
0.48 0.73 (N 5 39)
0.67 0.82 (N 5 48)
Average SD of age, weight, height and body mass index (BMI), PAH–DNA
adducts and %CWA (excluding gaps). Paired Student t-test.
a
The types of chromosomal aberrations included in this analysis were
chromatid and isochromatid breaks and exchanges (21).
*P , 0.001; **P 5 0.012.
season). This amounted to 50 of 92 subjects, representing 54%
of the studied population. Those showing 9.90 adducts per
109 nt during the dry season showed the smallest variation in
the level of adducts for dry and rainy seasons (8.64 versus 8.31
per 109 nt, respectively), which was not statistically significant.
When individuals were grouped according to their region of
residence (NE, NW, etc), the levels of PAH–DNA adducts
were not statistically different during the same season, but
adduct levels were higher during the dry season (Figure 2) for
all regions of residence except for those volunteers living in the
central region of the MCMA.
The mean values for PAH–DNA adduct levels observed
among different genotypes (wild type homozygotes versus
mutant homozygotes) are shown in Table II. No significant
seasonal differences were observed in the case of the allelic
variants CYP1A1*4 þ/ (n 5 6), GSTT1 null (n 5 6) or the
combination of GSTM1 null and CYP1A1*4 þ/ (n 5 5),
probably due to the small sample size (six or five subjects in
each group). However, the carriers of CYP 1B1*3 þ/ (n 5
42), CYP1A1*2A (n 5 18) and *2C (n 5 18) also did not show
significant seasonal differences, despite the large sample size.
A multiple linear regression analysis of the 92 paired samples
showed a significant correlation between the PAH–DNA
adduct levels and the level of PM10 during the dry season
but not with the %CWA (Table III). When risk alleles were
taken into consideration to explain PAH–DNA adduct
formation, we observed significant associations between
PM10 and PM2.5 levels and GSTM1 null individuals living in
the SE region portion. In addition, there was a significant
association between to PM2.5 and CYP1B1*3 (n 5 9) in
individuals living in the NW during the dry season.
When the additive effect of risk alleles was investigated, we
observed a relationship between the sum of the risk alleles and
PAH–DNA adduct levels in those individuals with four or
more risk variants in the dry (R 5 0.298, P 5 0.048) and wet
seasons (R 5 0.473, P 5 0.001; Figure 3).
Chromosomal aberrations
Using conventional cytogenetic analysis, we analysed the
percentage of cells with chromatid and chromosome aberrations in the metaphase of peripheral blood lymphocyte cultures.
The analysis was performed in 79 duplicate successful cultures
from samples obtained in the dry season and in 89 from the
rainy season. Although recorded during the analysis, chromatid
and chromosomal gaps were excluded from the %CWA. We
did not observe significant seasonal differences in the %CWA
(Table I).
Chromosomal damage was also correlated with genotypes.
The mean values for chromosomal aberrations observed among
groups with different genotypes are shown in Table II. No interactions were observed between polymorphisms in xenobioticmetabolising enzymes and the frequency of chromosomal
aberrations among seasons. In the rainy season, the combination
GSTM1 homozygotes or heterozygotes plus CYP1B1*3 heterozygotes showed a higher marginally significant %CWA than
GSTM1 null/CYP1B1*3 heterozygotic individuals (P 5 0.06;
Table II).
Discussion
In this study, we observed a seasonal variation in the levels of
PAH–DNA adducts in white blood cells from non-smokers
living in the MCMA. Higher levels of adducts were found in
387
W. A. Garcı́a-Suástegui et al.
Fig. 1. Box plot distribution of PM2.5 and PM10 mass concentration average 24 h during the sampling period, at five monitoring stations representatives of the five
regions of the MCMA [northwest (NW), northeast (NE), central (C), southwest (SW) and southeast (SE)]. Panels correspond to (A) PM10 dry season; (B) PM10
rainy season; (C) PM2.5 dry season; (D) PM2.5 rainy season. The plot represents the minimum and maximum values (whiskers), the first and third quartiles (box) and
the median value (midline). For PM10, the NW monitoring station reported higher (P , 0.05) median levels of emissions than the other four monitoring stations
while the SW region had the lowest levels. For PM2.5, the NW and C monitoring stations reported the highest (P , 0.05) levels of emissions. Initials above each box
indicate the regions that are significantly different from the data for that box.
Fig. 2. Box plot distribution of PAH–DNA adducts between subjects residing
in the five regions of the MCMA. The plot shows the minimum and maximum
values (whiskers), the first and third quartiles (box) and the median values
(midline). The levels of adducts were higher in dry season for individuals with
residence in NW, NE, SW and SE regions (P , 0.05).
blood samples obtained during the dry season (winter, Table I;
Figure 2), and this coincided with the presence of higher levels
of air pollutants (2) and PM (Figure 1). Moreover, the presence
of adducts correlated significantly with the estimated levels of
PM10 (Table III), suggesting that the adduct levels show a close
relationship with the intensity of environmental pollution
exposure. Because the antiserum used in the CIA recognises
DNA modified with several different PAHs (10,41), our results
suggest that during the dry season (November to May)
residents of the MCMA are exposed to higher levels of PAHs
than during the rainy season (June to October). This is in
agreement with PAH concentrations measured in PM10 and in
the gas phase in Mexico City’s atmosphere during 2005 (28).
The benzo[a]pyrene in PM10 was almost three times higher
during the dry season (winter) than during the rainy season
(0.81 versus 0.29 ng/m3, respectively).
On the other hand, the increased exposure to PAH during the
winter was not associated with chromatid or chromosome
388
damage (Table I). Similar negative results were observed when
chromosomal aberrations were compared, using conventional
cytogenetic analysis, between a group of policemen working
.8 h outdoors in the downtown area of Prague and age- and
sex-matched healthy volunteers spending .90% of each day
indoors (42). Nevertheless, previous in vitro studies have
documented the presence of clastogenic and mutagenic PAHs
in airborne PM from industrial and residential areas in the
MCMA (6,16), which emphasises the potential health risk
associated with exposure to air pollution in Mexico City.
Furthermore, respiratory and systemic effects of chronic air
pollution exposure have been reported in children living in
Mexico City (43), and long-term exposure to ozone, PM10 and
NO2 have been associated with significant deficits in lung
function growth (forced vital capacity and forced expiratory
volume in 1 second) among school-age children living in
Mexico City (44).
Besides the seasonal differences, we also observed a wide
range of variation in the levels of PAH–DNA adducts and
%CWA in the study population (Table I; Figure 2). Interindividual variations in DNA adduct levels have been
reported in other studies (17,18,45). The range of individual
exposure biomarker levels in study populations is affected by
factors such as accumulative exposure that could be related to
the region of residence in the MCMA, and to polymorphisms
in metabolic enzymes that convert PAHs to electrophilic
metabolites able to damage DNA or polymorphisms in
enzymes that conjugate these compounds to render them
hydrophilic and therefore able to be excreted.
Age was also investigated as a possible confounding factor
because positive correlations between age and levels of PAH–
DNA adducts in experimental animals (46) and in human brain
tissue from individuals with ages ranging from birth to 100
years (47) have been reported. The age range among donors in
PAH-DNA adducts in young adults living in Mexico City
Table II. Distribution of polymorphisms on metabolic PAHs enzymes in the studied population and their effect on the PAH–DNA adduct levels and %CWA in
each season
Gene
CYP1A1*2A, Msp I
CYP1A1*2C, Ile462Val
CYP1A1*4, Thr461Asn
CYP1B1*3, Leu432Val
GSTM1
GSTT1
GSTM1/CYP1B1*3
GSTM1/CYP1A1 *4
Genotype
N
þ/þ
þ/
/
þ/þ
þ/
/
þ/þ
þ/
þ/þ
þ/
/
Active
Null
Active
Null
Active (þ/þ, þ/)
Null (þ/, /)
Active/(þ/þ, þ/)
Null/(þ/)
18
49
25
18
57
17
87
7
44
42
6
51
41
86
6
48
25
51
5
N
Dry season
Adductsa (SD)
Pb
N
%CWAa (SD)
Pb
11.04
10.45
10.80
11.02
10.48
10.87
10.59
11.74
10.72
10.51
11.28
10.46
10.91
10.69
10.27
10.43
11.22
10.46
10.50
0.42
17
41
22
17
49
14
75
5
38
37
5
46
34
76
4
44
22
46
4
0.33
0.63
0.31
0.35
0.57
0.35
0.40
0.49
0.63
0.37
0.20
0.54
0.41
0.51
0.00
0.38
0.36
2.22
1.25
0.16
(3.56)
(2.76)
(3.28)
(3.57)
(2.97)
(2.84)
(2.94)
(4.47)
(2.90)
(3.30)
(2.62)
(2.87)
(3.27)
(2.94)
(4.65)
(2.95)
(3.55)
(2.87)
(3.64)
0.41
0.24
0.22
0.31
0.33
0.22
0.44
(0.59)
(0.79)
(0.64)
(0.60)
(0.76)
(0.74)
(0.54)
(0.74)
(0.81)
(0.63)
(0.44)
(0.80)
(0.60)
(0.73)
(0.00)
(0.69)
(0.59)
(1.87)
(1.26)
0.38
0.92
0.28
0.74
0.28
0.93
0.16
18
49
25
18
57
17
87
7
44
42
6
51
41
86
4
48
25
51
5
Rainy season
Adductsa (SD)
Pb
N
%CWAa (SD)
Pb
9.69
9.31
9.75
9.66
9.47
9.45
9.51
9.38
9.28
10.02
7.48
9.29
9.76
9.49
9.65
9.48
9.72
9.29
8.50
0.39
18
49
23
19
56
16
84
7
44
40
7
51
40
85
4
47
25
51
5
0.42
0.65
0.65
0.47
0.71
0.43
0.57
0.61
0.72
0.52
0.42
0.61
0.61
0.63
0.25
0.77
0.31
1.61
2.00
0.41
(3.10)
(2.69)
(3.05)
(3.12)
(2.83)
(2.67)
(2.89)
(2.38)
(2.89)
(2.70)
(2.91)
(2.93)
(2.76)
(2.84)
(3.18)
(2.90)
(2.49)
(2.93)
(1.09)
0.45
0.47
0.08
0.11
0.39
0.22
0.38
(0.76)
(0.77)
(0.88)
(0.77)
(0.84)
(0.62)
(0.78)
(0.80)
(0.92)
(0.64)
(0.78)
(0.75)
(0.86)
(0.81)
(0.50)
(0.73)
(0.47)
(1.55)
(1.58)
0.34
0.95
0.59
0.78
0.41
0.06
0.24
þ, wild type alleles;, variant type. Marginally significant differences are shown in bold values.
a
Arithmetic mean per 109 nt or mean percentage for aberrant cells.
b
Derived from Mann–Whitney U test between the two homozygote groups (e.g. þ/þ and /).
Table III. Multiple regression analysis between the reported levels of PM,
PAH–DNA adducts, %CWA, MCMA regions (NW, NE, C, SW and SE) and
allelic variants
Variables
Dry season
PAH–DNA adducts (n 5 92)
SE, GSTM1 null (n 5 23)
NW, CYP1B1*3 (n 5 9)
Rainy season
PAH–DNA adducts (n 5 92)
SE, GSTM1 null (n 5 23)
NW, CYP1B1*3 (n 5 9)
%CWA
Dry season (n 5 80)
Rainy season (n 5 91)
R
P
PM10
PM2.5
0.209
0.533
0.845
0.048
0.035
0.116
0.216
0.013
0.023
0.169
0.311
0.285
0.528
0.362
0.780
0.128
0.215
0.775
0.132
0.043
0.669
0.709
0.399
0.843
Significant associations are shown in bold values.
this study was relatively small (19–43 years), and we did not
find any correlation between adduct levels and age. On the
other hand, gender-based differences in adduct formation or
removal have been reported (48). We were not able to observe
gender differences, possibly due to the relatively low exposure
levels in both groups. For this study, samples were collected
from the same individuals in the two seasons so that each
individual acted as their own control. Thus, we eliminated or
minimised some potential confounders, such as lifestyles,
genetic polymorphisms, diets and other confounding factors
that arise when different cohorts are analysed.
When the presence of risk alleles was investigated, we
observed that GSTM1 null individuals living in the SE portion
showed an association between PM and PAH–DNA adduct
levels during the dry season (Table III). This association is
significant probably because of the large number of volunteer
living in the SE region and the higher levels of PM in the same
region as compared with a similar number of individuals living
in the SW portion who were exposed to significantly lower
levels of PM. This was previously observed in individuals
occupationally exposed (49), smokers (50) and in a population
exposed to urban air pollution (14). We found that volunteers
living in the NW region showed a significant correlation
between PM2.5, PAH–DNA adduct levels and the CYP1B1*3
genotype. Although the sample size in this group was small, this
association probably reflects the impact of exposure due to
commuting since this group of volunteers, according to the data
collected from questionnaires, travelled through a traffic corridor
where very high levels of PAHs have been reported (7). These
observations suggest that GSTM1 null and CYP1B1*3 are
relevant polymorphisms for leucocyte PAH–DNA adduct levels.
GSTM1 is involved in the conjugation of PAH diols to
glutathione (41); thus, the existence of a null allele is associated
with the lack of expression of a functional protein (42–53) that
could result in increased concentrations of epoxide intermediates
and hence higher DNA adduct levels. Indeed, the presence of
GSTM1 in homozygous or heterozygous condition has been
associated with lower levels of DNA adducts when compared
with GSTM1 null phenotype (19,21,38–40).
CYP1B1 enzyme plays a significant role in the oxidation of
a variety of carcinogens, such as PAHs and arylamines (54).
An amino acid change from leucine to valine at Codon 432
(CYP1B1*3) has been associated with elevated levels of DNA
adducts in white blood cells (49).
Similar to reports by Matullo et al. (55) and Ketelslegers
et al. (50), we also observed an additive effect of risk alleles on
PAH–DNA adduct formation when the levels of adducts were
correlated with the sum of risk alleles (Figure 3). These results
emphasise the importance of studying the simultaneous
contribution of many genotypes.
Several reports (14,17,19, 49,50,55) suggest that a single
gene (or polymorphism) will never completely explain the
interindividual variations in DNA adduct levels. Therefore, we
focused on a combination of CYP1A1*2A, CYP1A1*2C,
389
W. A. Garcı́a-Suástegui et al.
Fig. 3. Relationship between PAH–DNA adduct levels and the sum of risk alleles in inhabitants of MCMA during the dry and the rainy seasons. Points represent
median values, the minimum and maximum values (whiskers), N 5 number of individuals. The sum of risk alleles per individual was estimated by adding the
number of polymorphisms that putatively increase the risk for formation of PAH–DNA adducts. We found an effect of the sum of risk alleles on adduct levels
among the carriers of more than four risk alleles both in the dry (R 5 0.298, P 5 0.048) and the wet (R 5 0.473, P 5 0.001) seasons.
CYP1A1*4, CYP1B1*3, GSTM1 and GSTT1 polymorphisms,
which were found in the majority of cases to be non-significant
in the univariate analysis, but they were significant when
investigating multiple polymorphisms simultaneously in the
multivariate analysis, as a consequence of interactions. Our
data indicate that assessing multiple genetic polymorphisms
can explain part of the interindividual variations in DNA
adduct levels and that the analysis of many genotypes
simultaneously is important to obtain better insights in the
mechanisms that modulate DNA adduct levels.
Our data are based on observations made in a relatively
small number of individuals and clearly show that the
individual value of PAH–DNA adducts between groups are
overlapping, even considering markers supposedly relevant to
PAHs metabolism. However, there were clear and significant
seasonal differences in the levels of adducts estimated in most
of the polymorphisms analysed (CYP1A1*2A, CYP1A1*2C,
CYP1A1*4, CYP1B1*3, GSTM1 and GSTT1 and a positive
correlation between PAH–DNA adducts levels and the sum of
risk alleles in both seasons was evident.
On the other hand, in Mexico City, there are no air quality
standards related to PAH or benzo[a]pyrene. Moreover,
information regarding the presence of these pollutants in the
MCMA is scarce. Our longitudinal study correlates exposure to
these carcinogenic compounds with a higher health risk during
the dry season (November to May), which is due in part to the
higher presence of PM10 in ambient air (Table III). These
observations should contribute to the improvement of preventive measures, such as minimising vehicle emissions, the
main source of PM PAH (7).
Funding
This work was supported by a grant from CONACYT [46341-M]
and in part by the intramural research programme of the Center
for Cancer Research, National Cancer Institute, National
Institutes of Health. W.A.G.S. received a scholar fellowship
from CONACYT No. 182429.
Acknowledgements
We thank Marı́a de la Luz Velasco Hernandez for helping us with the
metaphase preparation, and Rosa Campos Sanchez and Laura Asenjo Garcı́a for
390
compilation of particular matter emissions for the two analysed seasons. In
addition, we owe a great deal to our study subjects.
Conflict of interest statement: None declared.
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