Gene-Environment Interactions between Arsenic Exposure from
Drinking Water and Genetic Susceptibility in Cardiovascular Disease
Risk and Carotid Artery Intima-Media Thickness in Bangladesh
F. Wu, M.L. Liu, X. Cheng, J.Y. Jiang, Y. Chen
New York University, New York, NY, USA
F. Parvez, V. Slavkovich, D. Levy, J.H. Graziano
Columbia University, New York, NY, USA
F. Jasmine, M.G. Kibriya, H. Ahsan
The University of Chicago, Chicago, IL, USA
T. Islam, A. Ahmed, M. Rakibuz-Zaman, S. Roy, R. Paul-Brutus, T. Islam
U-Chicago Research Bangladesh, Ltd., Dhaka, Bangladesh
ABSTRACT:
Arsenic exposure from drinking water has been linked to subclinical and clinical outcomes of cardiovascular
disease (CVD). However, no large-scale studies have evaluated whether the cardiovascular effects of arsenic exposure could be
modified by genetic factors. Using data from the Health Effects of Arsenic Longitudinal Study (HEALS) in Bangladesh, we
evaluated whether the association between arsenic exposure and CVD risk or carotid artery intima-media thickness (cIMT) differs
by single-nucleotide polymorphisms (SNPs) in 18 genes related to arsenic metabolism, oxidative stress, and inflammation and
endothelial dysfunction. We found significant interactions between well-water As and two SNPs in ICAM1 and VCAM1 in CVD
risk, and of both well-water As and urinary As with 3 SNPs in AS3MT in cIMT. Our data provide novel evidence that the
cardiovascular effects of arsenic exposure may vary with some common genetic variants in genes related to arsenic metabolism and
endothelial dysfunction.
1 INTRODUCTION
Arsenic (As) is a naturally occurring element primarily encountered in drinking water and foods, exposing millions of people worldwide to this toxic
agent. Chronic exposure to As from drinking water
has been linked to subclinical and clinical outcomes
of cardiovascular disease (CVD) (Moon et al. 2012).
Carotid artery intima-media thickness (cIMT) is a widely
accepted indicator of subclinical atherosclerosis and a
valid surrogate marker for clinical endpoints. The litera-
ture suggests that As-related health effects may be
modified by genetic factors. However, no large-scale
studies have evaluated whether the cardiovascular
effects of As exposure could be modified by genetic
factors.
2 METHODS
2.1 Gene-environment interactions in CVD risk
Using the resources from the Health Effects of As
Longitudinal Study (HEALS) in Bangladesh, a prospective cohort of more than 20,000 participants recruited in 2000 (Ahsan et al. 2006), we conducted a
case-cohort study of 447 incident fatal and nonfatal
cases of CVD, including 165 stroke cases and 238
cases of coronary heart disease (CHD), and a subcohort of 1,375 subjects randomly selected from the
HEALS to evaluate whether the association between
As exposure and risk of CVD, CHD, and stroke dif-
fers by single-nucleotide polymorphisms (SNPs) in
18 genes related to As metabolism (GSTM1, GSTT1,
GSTO1, GSTP1, MTHFR, CBS, PNP, and AS3MT),
oxidative stress (HMOX1, NOS3, SOD2, and CYBA),
and inflammation and endothelial dysfunction (APOE, TNF, IL6, ICAM1, S1PR1, and VCAM1).
Candidate genes were selected if they 1) are involved in As metabolism, or 2) have been related to
As exposure in animal, in vitro, or epidemiologic
studies and are known to play a key role in CVD risk
in epidemiologic studies. We used a comprehensive
approach to select SNPs in the candidate genes of interest. We first selected tag SNPs from International
Hapmap Project and SeattleSNPs using the r2-based
Tagger program with a pairwise r2 ≥ 0.80 and a minor allele frequency (MAF) ≥ 5%. The selection was
performed for each ethnic group in the Hapmap/SeattleSNPs data separately to compile a list
that includes all the tag SNPs. We also selected validated, non-synonymous SNPs with a MAF ≥ 5%
from SeattleSNPs and potentially functional SNPs
from the F-SNP database (Lee and Shatkay 2008). In
addition, we included SNPs that have been related to
CVD risk and/or phenotypic markers of interest in
the literature. After removing SNPs with genotyping
efficiency < 95%, monomorphic genotype data,
Hardy-Weinberg equilibrium < 0.0001, and an MAF
< 5% in the study population, a total of 170 SNPs in
17 genes were remained for analysis.
We assessed the multiplicative interaction by the
cross-product term of As exposure and each candidate SNP using the Cox proportional hazards models. We also assessed interaction on the additive
scale (synergy) by testing whether the joint effect of
As exposure and a SNP was greater than the sum of
their independent effects.
2.2 Gene-environment interactions in cIMT
We conducted a cross-sectional study of 1078 participants in the subcohort to evaluate gene-environment
interactions between As exposure and the abovementioned SNPs in cIMT. We used the mean of the
near and far walls of the maximum common carotid artery IMT from both sides of the neck (mean of 4 sites) as
the main outcome variable. The multiplicative interaction
between As exposure and each SNP was assessed using
multiple linear regression models. cIMT (β) in relation to
every standard deviation (SD) increase in As exposure
alone, presence of each SNP alone, and the joint effect of
As exposure and each SNP was assessed.
3 RESULTS
3.2 Interactions between As exposure and SNPs in
cIMT
Although not significant after correcting for multiple
testing, nine SNPs in APOE, AS3MT, PNP, and TNF
genes had a nominally significant interaction with
well-water As in cIMT. cIMT in relation to the joint
effect of both higher well-water As exposure and CT
or TT genotype of APOE rs7256173 (β = 46.0 µm,
95% CI = 10.7, 81.3), CC genotype of AS3MT
rs10883790 (β = 35.8 µm, 95% CI = 9.2, 62.4), AA
genotype of rs11191442 (β = 38.3 µm, 95% CI =
12.1, 64.5), and GG genotype of rs3740392 (β =
40.9 µm, 95% CI = 14.4, 67.5), was greater than the
cIMT in relation to the genotype alone (β = -8.1 µm,
-5.4 µm, -5.8 µm, and -5.1 µm, respectively) or As
exposure alone (β = 8.7 µm, 8.0 µm, 7.8 µm, and 7.2
µm, respectively). These SNPs also showed similar
pattern of interactions with urinary As. Additionally,
the at-risk genotypes of the AS3MT SNPs were positively related to increased proportion of
monomethylarsonic acid (MMA) and negatively related to proportion of dimethylarsinic acid (DMA) in
urine, indicators of suboptimal As methylation capacity.
3.1 Interactions between As exposure and SNPs in
risk of CVD, CHD, and stroke
4 CONCLUSIONS
The multiplicative interactions between well-water
As and two SNPs, rs281432 in ICAM1 (Padj =
0.0002) and rs3176867 in VCAM1 (Padj = 0.035) in
CVD risk, were significant after adjustment for multiple testing of all 170 tests. The hazard ration (HR)
for CVD risk was 1.82 [95% confidence interval
(CI): 1.31, 2.54] for every SD increase (101.3 µg/L)
in well-water As among those with GG genotype of
rs281432, much greater than the HR of 0.96 (95%
CI: 0.65, 1.42) associated with GG genotype alone
or the HR of 1.08 (95% CI: 0.94, 1.25) associated
with one SD increase in well-water As alone. The
magnitude of the interaction between well-water As
and rs3176867 in VCAM1 was weaker; the HR for
CVD risk was 1.34 (95% CI: 0.95, 1.87) for one SD
increase in well-water As among those with CC
genotype of rs3176867. These associations were
similar for stroke risk but weaker for CHD risk.
Our data provide novel evidence that genetic variants in genes related to endothelial dysfunction may
modify the risk of CVD associated with As exposure
whereas genetic variants in genes involved in As
metabolism may play a more important role in Asinduced subclinical atherosclerosis.
For main effects of SNPs, AA genotype of NOS3
rs2853792 and GG genotype of SOD2 rs5746088
were associated with a significantly reduced risk of
CVD (HR = 0.51, 95% CI: 0.38, 0.69; and 0.30,
95% CI: 0.17, 0.51, respectively) and CHD (HR =
0.49, 95% CI: 0.34, 0.70; and 0.29, 95% CI: 0.15,
0.58, respectively). CC genotype of MTHFR
rs1801133 was related to a significantly increased
risk of stroke (HR = 2.33; 95% CI: 1.51, 3.61).
ACKNOWLEDGEMENTS
This work is supported by grants R01ES017541,
P42ES010349, P30ES000260, and R01CA107431
from the National Institutes of Health.
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