Plasma folate level, urinary arsenic methylation profiles, and urothelial carcinoma susceptibility.

Plasma folate level, urinary arsenic methylation profiles, and

urothelial carcinoma susceptibility

Yung-Kai Huang

, Yeong-Shiau Pu

, Chi-Jung Chung

, Horng-Sheng Shiue

,

Mo-Hsiung Yang

, Chien-Jen Chen

, Yu-Mei Hsueh

a_{Graduate Institute of Medical Sciences, College of Medicine, Taipei Medical University, Taipei, Taiwan} b_{Department of Urology, National Taiwan University College of Medicine, Taipei, Taiwan}

c_{Graduate Institute of Public Health, Taipei Medical University, Taipei, Taiwan} d_{Department of Chinese Medicine, Chang Gung Memorial Hospital, Taipei, Taiwan}

e_{Department of Nuclear Science, National Tsing-Hua University, Hsinchu, Taiwan} f_{Genomic Research Center, Academia Sinica, Taipei, Taiwan}

g_{Graduate Institute of Epidemiology, National Taiwan University, Taipei, Taiwan}

h_{Department of Public Health, School of Medicine, Taipei Medical University, No. 250 Wu-Hsing Street, Taipei 110, Taiwan} Received 27 June 2007; accepted 18 October 2007

Abstract

To elucidate the influence of folate concentration on the association between urinary arsenic profiles and urothelial carcinoma (UC)

risks in subjects without evident arsenic exposure, 177 UC cases and 488 controls were recruited between September 2002 and May 2004.

Urinary arsenic species including inorganic arsenic, monomethylarsonic acid (MMA

_{) and dimethylarsinic acid (DMA}

_{) were determined}

by employing a high performance liquid chromatography-linked hydride generator and atomic absorption spectrometry procedure. After

adjustment for suspected risk factors of UC, the higher indicators of urinary total arsenic levels, percentage of inorganic arsenic,

percent-age of MMA

, and primary methylation index were associated with increased risk of UC. On the other hand, the higher plasma folate

levels, urinary percentage of DMA

and secondary methylation index were associated with decreased risk of UC. A dose–response

rela-tionship was shown between plasma folate levels or methylation indices of arsenic species and UC risk in the respective quartile strata. The

plasma folate was found to interact with urinary arsenic profiles in affecting the UC risk. The results of this study may identify the

sus-ceptible subpopulations and provide insight into the carcinogenic mechanisms of arsenic even at low arsenic exposure.

 2007 Elsevier Ltd. All rights reserved.

Keywords: Plasma folate level; Urinary arsenic species; Interaction; Urothelial carcinoma

1. Introduction

A urinary bladder cancer in Asia is considered a minor

incidence cancer compared to the US and other Western

countries. Urothelial carcinoma (UC) is a heterogeneous

disease influenced by both environmental exposure and

genetic factors. Folate is a water soluble B vitamin, and

present in cells as a family of structurally related derivatives

comprised of 2-amino-4-hydroxypteridine linked through a

methylene carbon to p-amino-benzoylpolyglutamate and it

is the donor of one-carbon groups in both DNA

methyla-tion and DNA synthesis (

Suh et al., 2001; Stanger, 2002

).

0278-6915/$ - see front matter  2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.fct.2007.10.017

Abbreviations: SAM, S-adenosylmethionine; UC, urothelial carci-noma; InAs, inorganic arsenic (AsIII_{+ As}V_{); MMA}V_{, monomethylarsonic} acid; DMAV_{, dimethylarsinic acid; %InAs, inorganic arsenic percentage;} %MMAV_{, monomethylarsonic acid percentage; %DMA}V_{, dimethylarsinic} acid percentage; PMI, primary methylation index; SMI, secondary methylation index; FFQ, food-frequency questionnaire; OR, odds ratio; CI, confidence interval.

*

Corresponding author. Tel.: +886 2 27361661x6513; fax: +886 2 27384831.

E-mail address:ymhsueh@tmu.edu.tw(Y.-M. Hsueh).

www.elsevier.com/locate/foodchemtox Food and Chemical Toxicology 46 (2008) 929–938

The epidemiologic evidence relating folate intake and the

risk of bladder cancer is contradictory and limited (

Bruem-mer et al., 1996; Michaud et al., 2000; Zeegers et al., 2001;

Schabath et al., 2005

). These studies used the

food-fre-quency questionnaire (FFQ) to estimate the folate content

from food intake and to assess the relationship between

folate intake and risk of bladder cancer. The estimation of

folate from FFQ may influence by the recall and

informa-tion bias; therefore, plasma folate of subjects used as an

exposure marker is the one of methods to prevent recall bias

(

Szklo and Nieto, 2007

). Because plasma folate reflects the

dietary folate intake (

Stanger, 2002

), quantification of

folate in biological samples may be a more reliable index

for cancer risk than estimated folate from the FFQ.

Arsenic is widely distributed in nature and is spread in

the environment mainly by water. Ingestion of inorganic

arsenic from arterial well water increases the worldwide

bladder cancer risk (

Chen et al., 1985, 1992; Bates et al.,

1992; Abernathy et al., 2003

). The metabolism of inorganic

arsenic involves reduction and oxidative methylation (

Kit-chin, 2001; Thomas et al., 2001, 2004; Vahter, 2002; Styblo

et al., 2002

). After ingestion of inorganic arsenic, the

pen-tavalent inorganic arsenic (arsenate, As

) is readily reduced

to trivalent inorganic arsenic (arsenite, As

) in red blood

cells (

Vahter, 1981

) and subsequently methylated to

monomethylarsonic acid (MMA

), and to dimethylarsinic

acid (DMA

) in the liver (

Buchet et al., 1981a,b

).

Evalua-tion of arsenic methylaEvalua-tion efficiency is mainly based on the

relative amounts of the different metabolites present in

urine. Previous epidemiological studies from Taiwan were

reported that higher cumulative arsenic exposure and less

efficient methylation activities were detected in skin and

bladder cancer patients than in healthy controls (

Hsueh

et al., 1995, 1997; Yu et al., 2000; Chen et al., 2003b, 2005

).

The evidence for nutritional regulation of arsenic

meth-ylation and excretion in humans is limited and rarely

con-sidered as a disease risk. A case–control study in West

Bengal showed a modestly increased risk of arsenic related

skin lesions for individuals with the lowest quintiles of

die-tary folate intake than those with higher quintiles (

Mitra

et al., 2004

). A recent study found that high plasma folate

levels were associated with efficient arsenic methylation

pattern (

Gamble et al., 2005

). These studies all focused

on subjects who had high arsenic exposure. The arsenic

concentration allowance in public water supplies in Taiwan

was 50 lg/L and a new standard of 10 lg/L was announced

in 2000. We designed a case–control study to assess the

association between individual plasma folate levels and

arsenic methylation capability on UC risk among a

popu-lation having no evident arsenic exposure in Taiwan.

2. Materials and methods

2.1. Study subjects

One hundred and seventy-one patients, age range 24–93 years, with pathologically proven UC were recruited from the Department of Urol-ogy, National Taiwan University Hospital, between September 2002 and

May 2004. Pathological verification of UC was done by routine urological methods including endoscopic biopsy or surgical resection of urinary tract tumors followed by histopathological examination by board-certified pathologists. A total of 488 control subjects with no evidence of UC or any other malignancy were recruited from a hospital-based pool, including those receiving senior citizen health examinations at Taipei Medical University Hospital and those receiving health examinations at Taipei Municipal Wan Fang Hospital. These three hospitals are medical center and their clinical clients’ bases are similar and located in Taipei approxi-mately 200–300 km away from the arsenic-contaminated areas in Taiwan. In this study, no case subjects or controls have lived in the arsenic-con-taminated areas in southwestern (Chen et al., 2003b) or northeastern Taiwan (Chiou et al., 2001). Although we only collected tap water from 37 UC cases and determined the total arsenic levels, the mean ± standard error was 17.14 ± 0.55 lg/L. However, urinary total arsenic levels in cases and controls were 24.47 ± 2.56 lg/L and 24.85 ± 1.06 lg/L, respectively (p-value is 0.89 for Student’s t-test). These results may indicate no differ-ence in arsenic exposure between cases and controls.

2.2. Questionnaire interview and specimens collection

Well-trained personnel carried out standardized personal interviews based on a structured questionnaire. Information collected included demographic and socioeconomic characteristics, general potential risk factors for malignancies such as lifestyle, quantified details of alcohol consumption, cigarette smoking, exposure to potential occupational and environmental carcinogens such as hair dyes and pesticides, chronic medication history, consumption of conventional and alternative medi-cines, and personal and family history of urological diseases. Regular alcohol drinkers referred to those who consumed alcohol three or more days per week, continuing for at least six months. The Research Ethics Committee of National Taiwan University Hospital, Taipei Medical University Hospital and Taipei Municipal Wan Fang Hospital approved the study. All subjects provided informed consent forms before specimen’s collection and questionnaire interview. The study was consistent with the World Medical Association Declaration of Helsinki.

After the questionnaire interview, a 10-mL blood sample was drawn into an EDTA-treated tube and centrifuged at 3000 rpm for 15 min at room temperature after collection. Plasma was separated and stored at 80 C until analysis. Urine samples were collected simultaneously and drawn into a 1% nitric acid rinsed PE bottle, and stored at20 C until used for urinary arsenic speciation. Because questionnaire and biospeci-mens were obtained before UC cases’ acceptance with surgery, radio-therapy, or chemoradio-therapy, any influence of treatment is unlikely.

2.3. Plasma folate assays

Plasma folate levels were determined using a competitive immunoassay kit (Diagnostic Products Corporation, Los Angeles, CA) according to the manufacturer’s instructions. All plasma samples were processed under dim yellow light. Laboratory personnel were unaware of the case–control status. The coefficient of variation was used to test the reliability and the mean coefficient of variation for 23 pairs of replicate plasma samples was 8.8%.

2.4. Determination of urinary arsenic species

It has been shown that urinary arsenic species are stable for at least six months when preserved at20 C (Chen et al., 2002); thus, the urine assay was performed within six months post-collection. Frozen urine samples were thawed at room temperature, dispersed by ultrasonication, filtered through a Sep-Pak C18 column (Mallinckrodt Baker Inc., NJ) and the levels of AsIII_{, As}V_{, MMA}V_{and DMA}V_{were determined. A 200 lL} ali-quot of urine was used for the determination of arsenic species by high performance liquid chromatography (Hitachi 7110, Naka, Japan) using columns obtained from Phenomenex (Nucleosil, Torrance, CA). The contents of inorganic arsenic and their metabolites were quantified by

hydride generator-atomic absorption spectrometry (Hsueh et al., 1998). The concentrations of the four arsenic species in a standard solution, a sample, and a sample spiked standard solution were determined by using

on-line HPLC-HG-AAS, respectively. Recovery rates of the four arsenic species were estimated according to the following calculation: [(sample spiked standard solution concentration) sample concentration]/ Table 1

Demographic characteristics, urothelial carcinoma risk variables, plasma folate level, and odds ratio of urothelial carcinoma in UC patients and controls Cases (N = 171) Controls (N = 488) Odds ratio (95% CI)

Gender, n (%) Male 116 (67.84) 286 (58.61) 1.00 Female 55 (32.16) 202 (41.39) 0.67 (0.46–0.97)* Education, n (%) Elementary school 78 (45.61) 136 (27.87) 1.00 High school 60 (35.09) 171 (35.04) 0.61 (0.41–0.92)* University 33 (19.30) 181 (37.09) 0.32 (0.20–0.51)** Smoking, n (%) Non-smokers 93 (54.39) 335 (68.65) 1.00

Light smokers (<22 pack-years) 21 (12.28) 77 (15.78) 0.98 (0.58–1.68)

Heavy smokers (P22 pack-years) 57 (33.33) 76 (15.57) 2.70 (1.79–4.08)**

Alcohol consumption, n (%) Never 111 (64.91) 288 (59.02) 1.00 1.00 Occasional 22 (12.87) 136 (27.87) 0.42 (0.25–0.69)** Regular 38 (22.22) 64 (13.11) 1.54 (0.97–2.43)*** _{1.89 (1.21–2.96)}** Age Mean ± SE 64.60 ± 0.99 63.51 ± 0.69 p = 0.37a Folate level (ng/mL) Mean ± SE 7.31 ± 0.41 12.29 ± 0.25 p < 0.01a

SE: standard error. * _{p < 0.05.} ** _{p < 0.01.} ***_{0.1 > p > 0.05.}

a _{p-Value for student’s t-test.}

Table 2

Distribution of the plasma folate level and urinary arsenic profile among subgroups of demographic characteristics N Folate level (ng/mL) Urinary arsenic level

(lg/g creatinine)

InAs (%) MMA (%) DMA (%)

Mean ± SE Mean ± SE Mean ± SE Mean ± SE Mean ± SE

Gender Male 402 10.75 ± 0.30 27.25 ± 1.34 6.21 ± 0.36 9.96 ± 0.49a _{83.83 ± 0.63}a Female 257 11.41 ± 0.38 31.01 ± 1.57 5.60 ± 0.51 6.48 ± 0.48 87.92 ± 0.72 Education Elementary school 214 10.91 ± 0.43 34.94 ± 1.57 5.1 ± 0.38 8.31 ± 0.55 86.59 ± 0.71 High school 231 11.23 ± 0.39 27.63 ± 1.84b 6.58 ± 0.61 9.45 ± 0.59 83.97 ± 0.91 University 214 10.86 ± 0.40 23.65 ± 1.78b _{6.18 ± 0.51 7.99 ± 0.72 85.83 ± 0.86} Smoking status Non-smokers 428 11.21 ± 0.28c _{28.96 ± 1.29 5.46 ± 0.35 7.69 ± 0.42}c _{86.86 ± 0.56} Light smokers (<22 pack-years) 98 12.13 ± 0.67c _{24.63 ± 1.52 6.58 ± 0.83 9.21 ± 1.11 84.21 ± 1.30} Heavy smokers (P22 pack-years) 133 9.53 ± 0.49 30.94 ± 2.68 7.17 ± 0.72 11.12 ± 0.78 81.71 ± 1.19 Alcohol consumption Never 399 11.07 ± 0.29 29.51 ± 1.50 5.72 ± 0.38 8.26 ± 0.47 86.02 ± 0.63 Occasional 158 11.65 ± 0.51d _{26.90 ± 1.43 5.56 ± 0.57 8.86 ± 0.76 85.58 ± 1.04} Regular 102 9.75 ± 0.63 28.41 ± 2.00 7.58 ± 0.81 9.57 ± 0.80 82.86 ± 1.06

SE: standard error.

a _{p-Value for student’s t-test, p < 0.0001.}

b _{Significant different (p < 0.05) from elementary school group by ANOVA and Scheffe’s test.} c _{Significant different (p < 0.05) from heavy smokers group by ANOVA and Scheffe’s test.}

standard solution concentration· 100. Recovery rates for AsIII_{, DMA}V_, MMAV_{and As}V_{ranged between 93.8% and 102.2% with detection limits} of 0.02, 0.06, 0.07 and 0.10 lg/L, respectively. Urinary concentration of the sum of inorganic arsenic, MMAV_{and DMA}V_{was normalized against} urinary creatinine levels (lg/g creatinine). The tap water was digested by 65% nitric acid and determined the total arsenic by HG-AAS. The stan-dard reference material, SRM 2670, containing 480 ± 100 lg/L inorganic arsenic was obtained from the National Institute of Standards and Technology (NIST, Gaithersburg, MD), and was used as a quality stan-dard and analyzed along with urine samples. The mean value of arsenic of SRM 2670 determined by our system was 507 ± 17 (SD) lg/L (n = 4). Arsenic methylation indices were assessed as the percentages of various urinary arsenic species in the sum of inorganic arsenic, MMAV and DMAV. The primary methylation index (PMI) was defined as the ratio between MMAV and inorganic arsenic (AsIII+ AsV) levels and the sec-ondary methylation index (SMI) was defined as the ratio between DMAV and MMAV(Hsueh et al., 1998; Vahter, 2002).

3. Statistical methods

Student’s t-test was used to compare the differences in

continuous variables between UC cases and controls.

Logistic regression models were used to estimate the

uni-variate and multiuni-variate-adjusted odds ratio (OR) and

the 95% confidence interval (CI). Cutoff points for

contin-uous variables were the respective quartiles of the controls.

For the joint effect analysis, the cutoff points for the plasma

folate levels and arsenic methylation indices were the

medi-ans of the controls, respectively. The joint effects of

ciga-rette smoking and plasma folate and urinary arsenic

methylation indices, or plasma folate levels and urinary

arsenic methylation indices on the UC risk were evaluated

by estimating the synergy index. An observed synergy

index value that departs substantially from the expected

additive null, i.e., synergy index greater than 1, suggests

an additive interaction effect. The OR values and their

var-iance covarvar-iance matrix were then used to calculate synergy

index and 95% CIs (

Hosmer and Lemeshow, 1992

). SAS

version 8.2 was used for all statistical analyses.

4. Results

The UC risks were significantly influenced by gender,

education level, cigarette smoking status, alcohol

consump-tion and plasma folate levels strata (

Table 1

). Males or

Table 3

Multivariate-adjusted ORs and 95% CI for associations of plasma folate levels and arsenic methylation capability with the risk of urothelial carcinoma

Quartiles p-Value for trenda

Q1 Q2 Q3 Q4

Folate (ng/mL)

Range <7.89 7.90–11.49 11.50–15.99 P16.00

Case/control 104/121 33/120 24/123 10/124

OR (95% CI)b _{1.00 0.33 (0.20–0.54)}*** _{0.22 (0.13–0.38)}*** _{0.09 (0.04–0.19)}*** _<0.0001

Total arsenic (lg/g creatinine)

Range <13.09 13.10–20.29 20.30–30.59 P30.60

Case/control 13/121 21/121 47/122 90/123

OR (95% CI)b 1.00 1.48 (0.69–3.12) 3.22 (1.62–6.27)*** 6.26 (3.21–12.22)*** <0.0001 Percentage of inorganic arsenic (%)

Range <1.49 1.50–3.69 3.70–6.29 P6.30 Case/control 24/121 40/122 41/122 66/123 OR (95% CI)b _{1.00 1.67 (0.93–3.00) 1.67 (0.93–3.01) 2.52 (1.44–4.41)}** _0.002 Percentage of MMA (%) Range <0.89 0.9–5.89 5.90–10.89 P10.90 Case/control 25/121 27/122 39/121 80/124 OR (95% CI)b 1.00 0.98 (0.53–1.82) 1.41 (0.79–2.51) 2.75 (1.61–4.71)** <0.0001 Percentage of DMA (%) Range <81.89 81.90–89.19 89.20–94.39 P94.40 Case/control 73/121 49/122 33/121 16/124 OR (95% CI)b _{1.00 0.66 (0.42–1.05) 0.46 (0.27–0.76)}** _{0.22 (0.12–0.42)}*** _<0.0001

Primary methylation index

Range <0.29 0.30–1.39 1.40–2.79 P2.80

Case/control 73/121 49/122 33/121 16/124

OR (95% CI)b 1.00 1.05 (0.57–1.93) 1.44 (0.87–2.57) 1.99 (1.13–2.48)* 0.0063

Secondary methylation index

Range <6.59 6.60–10.59 10.60–19.29 P19.30 Case/control 26/105 32/106 44/106 57/106 OR (95% CI)b _{1.00 0.51 (0.30–0.85)}** _{0.32 (0.18–0.57)}** _{0.28 (0.15–0.51)}** _<0.0001 * _{p < 0.05.} **_{p < 0.01.} *** _{p < 0.001.}

a _{p-Value for trend for category variables.}

lower education or regular alcohol drinkers or lower

plasma folate levels subjects had significantly higher UC

risk than females or higher education or alcohol

non-drink-ers or higher plasma folate levels subjects. There was no

significant difference of the mean age of cases at 64.60 years

and controls at 63.51 years. Folate (7 lmol/L) in plasma

was recommended as normal standard by

Institute of

Med-icine (1998)

. In this study, the proportion under 7 lmol/L

plasma folate levels was 57% (98/171) and 18% (88/488)

in UC cases and controls, respectively.

The distribution of the plasma folate levels and urinary

arsenic profiles among subgroups of gender, education,

cig-arette smoking, and alcohol consumption was shown in

Table 2

. Male had a higher urinary %MMA

and a lower

%DMA

than female. The higher total urinary arsenic

lev-els were observed for subjects who had education level of

elementary school than those had high school and

univer-sity. Compared to heavy smokers, non-smokers had a

higher folate levels and a lower %MMA

. Light smokers

had a higher folate levels than heavy smokers. Occasional

alcohol drinkers had a higher folate levels than regular

alcohol drinkers. The results of

Table 2

suggested that

male, lower education level, heavy smokers, and regular

alcohol drinkers may have an inefficient methylation

pro-cess of metabolizing arsenic to DMA

.

Table 3

presents the multivariate-adjusted ORs for the

associations between plasma folate levels or arsenic

methyl-ation indices and UC risk. In general, there was a dose–

response association between the quartile of plasma folate

levels or arsenic methylation indices and UC risk after

adjustment for suspected UC risk factors. The plasma

folate levels appeared to have an inverse association with

the risk of UC having OR of quartiles strata of 1.0, 0.33,

0.22, and 0.09, respectively (p < 0.0001 for the trend test).

The creatinine-adjusted total arsenic levels appeared to

have an increased UC risk, the OR of quartiles strata were

1.0, 1.48, 3.22, and 6.26, respectively (p < 0.0001 for the

trend test). Subjects with either lower %MMA

, or lower

%InAs, or lower PMI, or higher %DMA

or higher SMI

were suggested a more efficient capacity to methylate

inor-ganic arsenic to DMA

, and the more efficient capacity

was the less risk of UC.

Table 4

examined the joint effects of the plasma folate

levels in combination with various arsenic methylation

profiles. The folate concentrations were divided into two

categories based on the median values of controls. Subjects

with a higher plasma folate levels and possessing efficient

arsenic methylation profiles were the reference group.

The OR was 5.24 (95% CI, 1.93–14.20) for individuals with

a higher plasma folate levels and a higher total arsenic

lev-els. The OR was 5.93 (95% CI, 2.19–16.01) for individuals

with a lower folate levels and lower total arsenic levels as

compared to those with a higher folate and a lower total

arsenic levels. The highest risk group occurred in those

with a lower folate levels and a higher total arsenic levels

having an adjusted OR 19.58 and 95% CI, 7.63–50.23.

Table 4

Joint effects of plasma folate level and arsenic methylation capability index on urothelial carcinoma risk

Arsenic methylation profiles Folate (ng/mL) S index (95% CI)

P11.5 <11.5

Case/control OR (95% CI) Case/control OR (95% CI)

Total arsenic (lg/g creatinine)

<20.30 5/118 1.00 29/125 5.93 (2.19–16.01)** 2.02 (1.24–3.28)**

P20.30 29/129 5.24 (1.93–14.20)** 108/116 19.58 (7.63–50.23)***

Percentage of inorganic arsenic (%)

<3.70 10/124 1.00 54/119 5.78 (2.77–12.03)*** _{1.18 (0.71–1.98)} P3.70 24/123 2.37 (1.07–5.23)* _{83/122 8.30 (4.02–17.12)}*** Percentage of MMA (%) <5.90 17/122 1.00 35/121 2.12 (1.10–4.08)* 4.43 (1.18–16.57)* P5.90 12/125 0.92 (0.44–1.91) 102/120 5.61 (3.10–10.16)** Percentage of DMA (%) P89.20 19/105 1.00 39/106 3.10 (1.54–6.24)** _{2.51 (1.25–5.03)}** <89.20 12/106 1.68 (0.97–3.57) 89/106 7.98 (4.15–15.35)***

Primary methylation index

<1.40 19/105 1.00 39/106 2.10 (1.12–3.96)* 4.64 (0.74–29.07)

P1.40 12/106 0.60 (0.27–1.33) 89/106 4.25 (3.38–7.58)***

Secondary methylation index

P10.60 13/98 1.00 29/89 2.40 (1.16–4.98)* _{3.77 (1.29–10.96)}*

<10.60 14/90 1.19 (0.52–2.71) 91/96 7.00 (3.58–13.67)**

Adjusted for age, sex, educational attainment, smoking status (pack-year), and alcohol consumption. * _{p < 0.05.}

** _{p < 0.01.} ***_{p < 0.001.}

Furthermore, the interaction between plasma folate levels

and urinary total arsenic levels were statistically significant

on the additive scale (S index 2.02, p < 0.01). The

phenom-ena were identical to the %InAs, %MMA

, %DMA

, PMI

and SMI. Except for %InAs and PMI, interactions between

arsenic methylation profiles and folate on additive scale

were statistically significant.

Table 5

examined the joint effects of cigarette smoking

and plasma folate levels or cigarette smoking and various

arsenic methylation indices for UC risk. The reference

group was the non-smokers or light smokers with a high

plasma folate levels or an efficient arsenic methylation

pro-files. Heavy smokers with a higher plasma folate levels had

2.52-fold (95% CI, 1.08–5.85) risk of UC. A 4.51-fold UC

risk (95% CI, 2.71–7.51) for non-smokers or light smokers

with a lower plasma folate levels, and the risk increased to

8.25 (95% CI, 1.23–16.09) for heavy smokers with a lower

plasma folate levels. Similar results were obtained for the

various arsenic methylation profiles. For example,

non-smokers or light non-smokers with the higher total arsenic levels

had an OR of 4.27 (95% CI, 2.39–7.31), heavy smokers with

the lower total arsenic levels had an OR of 2.95 (95% CI,

1.32–6.61). The highest risk was found in heavy smokers

with the higher total arsenic levels (adjusted OR 8.89;

95% CI, 4.38–18.03). The joint effect was shown statistically

insignificant between cigarette smoking and plasma folate

levels or between cigarette smoking and urinary arsenic

indices. Comparing

Tables 4 and 5

, the interaction was

sta-tistically significant between the plasma folate levels and the

arsenic methylation indices on UC risk but not between the

plasma folate levels and cigarette smoking on UC risk.

5. Discussion

High folate levels and efficient arsenic methylation

profiles are associated with a decreased risk of UC. Both

factors exhibited a strong interaction on UC risk. More

interestingly, the marked interaction between folate and

arsenic methylation indices was greater than that between

cigarette smoking and folate or between cigarette smoking

and arsenic methylation indices. This study demonstrated

that the UC risk is enhanced by a synergistic interaction

between low plasma folate levels and inefficient arsenic

methylation capability among a population having no

evident arsenic exposure in Taiwan.

Numerous

epidemiological

studies

had

conflicting

results between folate intake and bladder cancer risk. In

a folate supplement case–control study, total folate intake

was inversely related with bladder cancer, OR 0.54, 95%

CI, 0.31–0.93 for the highest quartile compared to the

Table 5

Joint effects of smoking status, and plasma folate level or arsenic methylation capability index on urothelial carcinoma risk Folate and arsenic methylation

profiles

Smoking status S index (95% CI)

Non-smokers or light smokers (<22 pack years) Heavy smokers (>22 pack years)

Case/control OR (95% CI) Case/control OR (95% CI)

Plasma folate level (ng/mL)

P11.50 23/123 1.00 11/34 2.52 (1.08–5.85)* 1.44 (0.72–2.87)

<11.50 91/199 4.51 (2.71–7.51)*** 46/42 8.25 (1.23–16.09)***

Total arsenic (lg/g creatinine)

<20.30 20/104 1.00 14/39 2.95 (1.32–6.61)** _{1.51 (0.76–2.99)}

P20.30 94/208 4.27 (2.49–7.31)*** _{43/37 8.89 (4.38–18.03)}***

Percentage of inorganic arsenic (%)

<3.70 46/211 1.00 18/32 2.16 (1.05–4.45)* 1.32 (0.46–3.74) P3.70 68/201 1.55 (1.00–2.93)* 39/44 3.26 (1.76–6.03)*** Percentage of MMA (%) <5.90 37/217 1.00 15/26 2.79 (1.25–6.24)* _{1.03 (0.44–2.42)} P5.90 77/195 2.25 (1.43–3.54)*** _{42/50 4.16 (2.24–7.73)}*** Percentage of DMA (%) P89.20 26/216 1.00 13/29 2.33 (1.02–5.37)* 1.34 (0.58–3.08) <89.20 78/196 2.44 (1.52–3.89)*** 44/47 4.75 (2.52–8.90)***

Primary methylation index

<1.40 37/183 1.00 21/28 3.21 (1.53–6.72)** 0.70 (0.28–1.75)

P1.40 67/167 1.94 (1.21–3.11)** _{34/45 3.22 (1.69–6.14)}***

Secondary methylation index

P10.60 34/163 1.00 8/24 1.38 (0.53–3.63) 1.97 (0.68–6.71)

<10.60 65/146 2.24 (1.37–3.65)** _{40/40 4.22 (2.19–8.11)}***

Adjusted for age, sex, educational attainment, and alcohol consumption. * p < 0.05. ** p < 0.01. *** p < 0.001.

lowest quartile (

Sharp and Little, 2004; Schabath et al.,

2005

). Other studies did not observe any association

between folate and bladder cancer risk (

Michaud et al.,

2002; Holick et al., 2005

). The evidence for a relationship

between folate and bladder cancer from epidemiological

studies is limited and mainly focused on the folate ingested

from dietary food rather than the concentration in the

body. Plasma folate is a precise marker to reflect dietary

folate intake (

Stanger, 2002

) and the result of this study

found that the UC risk was raised with the plasma folate

levels decreasing. Other nutrition such as methionine,

vita-mins B-6 and B-12, which interacted metabolically with

folate in the one-carbon metabolism processes, may also

influence cancer risk (

Bailey, 2003

). Dark-green vegetables

and certain other fruits and vegetables are rich sources of

folate and B vitamins (

Gebhardt et al., 2007

), and

epidemi-ological study suggested that high fruits and vegetables

intake reduced the risk of bladder cancer (

Steinmaus

et al., 2000

).

Besides nutrition, life styles such as cigarette smoking or

regular alcohol drinking also influenced the bioavailability

of folate. In accordance with previous studies (

Piyathilake

et al., 1994; Schabath et al., 2005

), reduced plasma folate

level was observed with either heavy cigarette smoking or

regular alcohol drinking in our study. Recently a study

showed that cigarette smoking might result in localized

deficiencies of folate coenzymes, tetrahydrofolate and

5,10-methylenetetrahydrofolate (

Gabriel et al., 2006

).

On the other hand, alcohol drinking also affected the

folate-dependent

metabolism

including

inhibition

of

enzymes central to one-carbon metabolism (methionine

synthase, methylenetetrahydrofolate reductase, methionine

adenosyltransferase 1A, glycine N-methyltransferase, and

S-AdoHcyst hydrolase), and stimulation of serine synthesis

and inhibition of thymidine synthesis (

Mason and Choi,

2005

). These evidences suggested that the folate

bioavail-ability was influenced by cigarette smoking and alcohol

drinking.

A recent study showed that bladder cancer mortality

declined gradually after eliminating arsenic exposure from

artesian well water by improving the drinking water supply

system in southwest Taiwan (

Yang et al., 2005

). This

find-ing substantiates the association between arsenic exposure

and bladder cancer risk. A previous study evaluated the

relationship between UC risk and arsenic exposure by

focusing on the total arsenic levels in drinking water

(

Chiou et al., 2001

). It would be more relevant if urinary

arsenic species were used as indicators of arsenic

metabo-lism (

Francesconi and Kuehnelt, 2004; Steinmaus et al.,

2005

). The order of toxicity in arsenic species by oral

expo-sure in mice was As

> DMA

> MMA

(

Shiomi, 1994

).

Humans excreted appreciable amounts of MMA

in the

urine compared with other mammals. The methylated

metabolites were virtually undetectable in the urine of

mar-moset monkeys that were administered with inorganic

arsenic (

Vahter et al., 1995; Vahter, 2002

). Studies

indi-cated that marmoset, tamarin monkeys and guinea-pigs

were deficient in methyltransferase activity (

Zakharyan

et al., 1996; Healy et al., 1997

). Rat revealed significantly

high methylating activity and it is the only species that

excreted significant amounts of TMAO (

Aposhian, 1997;

Cohen et al., 2006

). The variation in the metabolism of

inorganic arsenic between human and other animals

may result in variant susceptibility to inorganic arsenic

carcinogenesis.

This study demonstrated that the profile of urinary

arsenic metabolites was significantly associated with the

risk of UC. A high PMI and low SMI indicated an

accumu-lation of MMA

by an increased upstream input and a

reduced downstream output of the arsenic methylation

pathway metabolites. In addition to bladder cancer, our

previous study reported that skin cancer patients had

higher indicators of %InAs and %MMA

, and had lower

indicators of %DMA

, and PMI than healthy controls

(

Hsueh et al., 1997

). These results are compatible with

the study of

Chen et al. (2003a,b)

that showed skin and

bladder cancer patients had a lower SMI in high chronic

arsenic exposure area. Arsenic methylated metabolites in

urine have been reported to be biomarkers for disease

states and disease susceptibility in other ethnicities (

Valen-zuela et al., 2005

). The key metabolic intermediates,

MMA

and DMA

, have been identified in human urine

(

Mandal et al., 2001

), and these trivalent methylated

arsen-icals are more toxic than inorganic arsenic compounds

(

Styblo et al., 2000; Petrick et al., 2001

). Levels of trivalent

methylated metabolites in the urine are expected to be

sig-nificantly low, since these metabolites have short half-lives

and, therefore, were considered not to be suitable markers

for arsenic methylation at the present time (

Mass et al.,

2001; Gong et al., 2001; Nesnow et al., 2002; Francesconi

and Kuehnelt, 2004

). The arsenic methylation pattern

may remain stable over time and be influenced by factors

such as methylation related enzymes, genes, environmental

exposure, smoking habits and diet (

Francesconi and

Kueh-nelt, 2004; Steinmaus et al., 2005

).

This study discovered the synergy indices of the plasma

folate and urinary methylation profiles ranged from 1.18 to

4.64, revealing significant synergistic interactions between

folate and total arsenic levels, %MMA

, %DMA

, or

SMI. Another study also reported that %DMA

was

sig-nificantly positive and %MMA

was negatively related to

the plasma folate levels (

Gamble et al., 2005

). Recently, a

clinical

study

showed

that

folate

supplementation

improved the arsenic methylation efficiency, such as a

low urinary %MMA

and a high %DMA

in the

supple-mented group compared to the placebo group (

Gamble

et al., 2006

). These observations suggested that subjects

with low folate levels were at a high disease risk especially

when they had low arsenic methylation capability. Indeed,

the arsenic methylation profiles may be altered by the

folate status in the body.

Previous animal studies provided evidence that folate

can influence arsenic methylation, excretion, and toxicity.

(

Kim, 2000; Moyers and Bailey, 2001; Townsend et al.,

2004

). Folate is essential for methylation in the human

body and its metabolism is important for the biosynthesis

of S-adenosylmethionine (SAM), a substrate for

methyla-tion including DNA methylamethyla-tion (

Choi and Mason, 2000;

Gregory and Quinlivan, 2002; Choi and Friso, 2005

) and

arsenic methylation (

Vahter, 1981, 2002

). Inorganic arsenic

is enzymatically methylated and consumes SAM in the

bio-transformation process. The molecular mechanism of

arsenic carcinogenesis may cause DNA damage or alter

the methylation status of DNA (

Zhao et al., 1997; Okoji

et al., 2002; Huang et al., 2004; Reichard et al., 2007

); this

process is similar to folate deficiency. In human colon

epithelial cells, a folate deficiency increased uracil

mis-incorporation 2–3-fold and lowered the cells’ capacity for

DNA repair in response to oxidation or alkylation (

Choi

et al., 1998; Duthie et al., 2000b

). Uracil mis-incorporation

or DNA strand breakage was significantly increased in rat

lymphocytes after 4–8 weeks or 10 weeks of folate deficient

diet intake (

Duthie et al., 2000a,b,c

). The individual

sus-ceptibility may result from the differences in the genes

con-trolling the metabolism of xenobiotics, DNA repair, cell

transport, immune responses, antioxidant defenses and cell

cycle control (

Huang et al., 2004

). Several animal studies

reported that folate binding or transport gene knock-out

mice or rabbits decreased biotransformation and excretion

of arsenic, and these animals were more susceptible to

arsenic and induced the defects (

Vahter and Marafante,

1987; Spiegelstein et al., 2003, 2005a,b; Spuches et al.,

2005

). Based on these observations, the interaction between

folate and the arsenic methylation pathways may cause UC

risk through the DNA methylation or DNA repair

systems.

One limitation of this study is that the UC cases are

pre-valent cases and we cannot rule out the possibility that

folate and/or arsenic methylation patterns changed after

the participants became UC cases. Dietary habits lacked

from the questionnaires are another limitation of this

study; however, the plasma folate levels are a good

bio-marker to reflect the dietary folate intake (

Piyathilake

et al., 1994; Stanger, 2002

).

Inorganic arsenic is a human carcinogen; however, a

good animal model has not yet been found. The arsenic

methylation process may be less efficient and leads to more

severe toxicity in humans than in several other species

(

Cohen et al., 2006

). In this study, we established the

dose–response relationships among two credible markers,

plasma folate levels and arsenic methylation indices, and

UC risk. It was indicated that folate interacted with urinary

arsenic profiles in affecting the UC risk. These results may

identify the susceptible subpopulations and provide insight

into the carcinogenic mechanisms of arsenic even at low

arsenic exposure.

Acknowledgement

This study was supported by Grants

NSC91-3112-B-038-0019,

NSC92-3112-B-038-001,

NSC93-3112-B-038-001,

NSC94-2314-B-038-023,

NSC95-2314-B-038-007,

and

NSC-96-2314-B-002-311 from the National Science

Coun-cil, Executive Yuan, ROC. We thank Dr. Ying-Chin Lin

of the Health Management Center, Taipei Medical

Univer-sity Municipal Wan Fang Hospital for recruitment of the

healthy controls.

References

Abernathy, C.O., Thomas, D.J., Calderon, R.L., 2003. Health effects and risk assessment of arsenic. J. Nutr. 133, 1536S–1538S.

Aposhian, H.V., 1997. Enzymatic methylation of arsenic species and other new approaches to arsenic toxicity. Annu. Rev. Pharmacol. Toxicol. 37, 397–419.

Bailey, L.B., 2003. Folate, methyl-related nutrients, alcohol, and the MTHFR 677C!T polymorphism affect cancer risk: intake recom-mendations. J. Nutr. 133, 3748S–3753S.

Bates, M.N., Smith, A.H., Hopenhayn-Rich, C., 1992. Arsenic ingestion and internal cancers: a review. Am. J. Epidemiol. 135, 462–476. Bruemmer, B., White, E., Vaughan, T.L., Cheney, C.L., 1996. Nutrient

intake in relation to bladder cancer among middle-aged men and women. Am. J. Epidemiol. 144, 485–495.

Buchet, J.P., Lauwerys, R., Roels, H., 1981a. Comparison of the urinary excretion of arsenic metabolites after a single oral dose of sodium arsenite, monomethylarsonate, or dimethylarsinate in man. Int. Arch. Occup. Environ. Health 48, 71–79.

Buchet, J.P., Lauwerys, R., Roels, H., 1981b. Urinary excretion of inorganic arsenic and its metabolites after repeated ingestion of sodium metaarsenite by volunteers. Int. Arch. Occup. Environ. Health 48, 111–118.

Chen, C.J., Chuang, Y.C., Lin, T.M., Wu, H.Y., 1985. Malignant neoplasms among residents of a blackfoot disease-endemic area in Taiwan: high-arsenic artesian well water and cancers. Cancer Res. 45, 5895–5899.

Chen, C.J., Chen, C.W., Wu, M.M., Kuo, T.L., 1992. Cancer potential in liver, lung, bladder and kidney due to ingested inorganic arsenic in drinking water. Br. J. Cancer 66, 888–892.

Chen, Y.C., Amarasiriwardena, C.J., Hsueh, Y.M., Christiani, D.C., 2002. Stability of arsenic species and insoluble arsenic in human urine. Cancer Epidemiol. Biomarkers Prev. 11, 1427–1433.

Chen, Y.C., Guo, Y.L., Su, H.J., Hsueh, Y.M., Smith, T.J., Ryan, L.M., Lee, M.S., Chao, S.C., Lee, J.Y., Christiani, D.C., 2003a. Arsenic methylation and skin cancer risk in southwestern Taiwan. J. Occup. Environ. Med. 45, 241–248.

Chen, Y.C., Su, H.J., Guo, Y.L., Hsueh, Y.M., Smith, T.J., Ryan, L.M., Lee, M.S., Christiani, D.C., 2003b. Arsenic methylation and bladder cancer risk in Taiwan. Cancer Causes Control 14, 303–310.

Chen, Y.C., Su, H.J., Guo, Y.L., Houseman, E.A., Christiani, D.C., 2005. Interaction between environmental tobacco smoke and arsenic meth-ylation ability on the risk of bladder cancer. Cancer Cause Control 16, 75–81.

Chiou, H.Y., Chiou, S.T., Hsu, Y.H., Chou, Y.L., Tseng, C.H., Wei, M.L., Chen, C.J., 2001. Incidence of transitional cell carcinoma and arsenic in drinking water: a follow-up study of 8,102 residents in an arseniasis-endemic area in northeastern Taiwan. Am. J. Epidemiol. 153, 411–418.

Choi, S.W., Friso, S., 2005. Interactions between folate and aging for carcinogenesis. Clin. Chem. Lab Med. 43, 1151–1157.

Choi, S.W., Mason, J.B., 2000. Folate and carcinogenesis: an integrated scheme 1–3. J. Nutr. 130, 129–132.

Choi, S.W., Kim, Y.I., Weitzel, J.N., Mason, J.B., 1998. Folate depletion impairs DNA excision repair in the colon of the rat. Gut 43, 93–99. Cohen, S.M., Arnold, L.L., Eldan, M., Lewis, A.S., Beck, B.D., 2006.

Methylated arsenicals: the implications of metabolism and carcinoge-nicity studies in rodents to human risk assessment. Crit. Rev. Toxicol. 36, 99–133.

Duthie, S.J., Grant, G., Narayanan, S., 2000a. Increased uracil misincor-poration in lymphocytes from folate-deficient rats. Br. J. Cancer 83, 1532–1537.

Duthie, S.J., Narayanan, S., Blum, S., Pirie, L., Brand, G.M., 2000b. Folate deficiency in vitro induces uracil misincorporation and DNA hypomethylation and inhibits DNA excision repair in immortalized normal human colon epithelial cells. Nutr. Cancer 37, 245–251. Duthie, S.J., Narayanan, S., Brand, G.M., Grant, G., 2000c. DNA

stability and genomic methylation status in colonocytes isolated from methyl-donor-deficient rats. Eur. J. Nutr. 39, 106–111.

Francesconi, K.A., Kuehnelt, D., 2004. Determination of arsenic species: a critical review of methods and applications, 2000–2003. Analyst 129, 373–395.

Gabriel, H.E., Crott, J.W., Ghandour, H., Dallal, G.E., Choi, S.W., Keyes, M.K., Jang, H., Liu, Z., Nadeau, M., Johnston, A., Mager, D., Mason, J.B., 2006. Chronic cigarette smoking is associated with diminished folate status, altered folate form distribution, and increased genetic damage in the buccal mucosa of healthy adults. Am. J. Clin. Nutr. 83, 835–841.

Gamble, M.V., Liu, X., Ahsan, H., Pilsner, R., Ilievski, V., Slavkovich, V., Parvez, F., Levy, D., Factor-Litvak, P., Graziano, J.H., 2005. Folate, homocysteine, and arsenic metabolism in arsenic-exposed individuals in Bangladesh. Environ. Health Perspect. 113, 1683–1688.

Gamble, M.V., Liu, X., Ahsan, H., Pilsner, J.R., Ilievski, V., Slavkovich, V., Parvez, F., Chen, Y., Levy, D., Factor-Litvak, P., Graziano, J.H., 2006. Folate and arsenic metabolism: a double-blind, placebo-con-trolled folic acid-supplementation trial in Bangladesh. Am. J. Clin. Nutr. 84, 1093–1101.

Gebhardt, S.E., Pehrsson, P.R., Cutrufelli, R.L., Lemar, L.E., Howe, J.C., Haytowitz, D.B., Nickle, M.S., Holcomb, G.T., Showell, B.A., Thomas, R.G., Exler, J., Holden, J.M., 2007. USDA National Nutrient Database for Standard Reference, Release 20. USDA National Nutrient Database for Standard Reference. Available on the NDL Home Page:www.ars.udsda.gov/nutrientdata.

Gong, Z.L., Lu, X.F., Cullen, W.R., Le, X.C., 2001. Unstable trivalent arsenic metabolites, monomethylarsonous acid and dimethylarsinous acid. J. Anal. At. Spectrom. 16, 1409–1413.

Gregory III, J.F., Quinlivan, E.P., 2002. In vivo kinetics of folate metabolism. Annu. Rev. Nutr. 22, 199–220.

Healy, S.M., Zakharyan, R.A., Aposhian, H.V., 1997. Enzymatic meth-ylation of arsenic compounds: IV. In vitro and in vivo deficiency of the methylation of arsenite and monomethylarsonic acid in the guinea pig. Mutat. Res. – Rev. Mutat. Res. 386, 229–239.

Holick, C.N., De, V.I., Feskanich, D., Giovannucci, E., Stampfer, M., Michaud, D.S., 2005. Intake of fruits and vegetables, carotenoids, folate, and vitamins A, C, E and risk of bladder cancer among women (United States). Cancer Causes Control 16, 1135–1145.

Hosmer, D.W., Lemeshow, S., 1992. Confidence interval estimation of interaction. Epidemiology 3, 452–456.

Hsueh, Y.M., Cheng, G.S., Wu, M.M., Yu, H.S., Kuo, T.L., Chen, C.J., 1995. Multiple risk factors associated with arsenic-induced skin cancer: effects of chronic liver disease and malnutritional status. Br. J. Cancer 71, 109–114.

Hsueh, Y.M., Chiou, H.Y., Huang, Y.L., Wu, W.L., Huang, C.C., Yang, M.H., Lue, L.C., Chen, G.S., Chen, C.J., 1997. Serum beta-carotene level, arsenic methylation capability, and incidence of skin cancer. Cancer Epidemiol. Biomarkers Prev. 6, 589–596.

Hsueh, Y.M., Huang, Y.L., Huang, C.C., Wu, W.L., Chen, H.M., Yang, M.H., Lue, L.C., Chen, C.J., 1998. Urinary levels of inorganic and organic arsenic metabolites among residents in an arseniasis-hyperen-demic area in Taiwan. J. Toxicol. Environ. Health A 54, 431– 444.

Huang, C., Ke, Q., Costa, M., Shi, X., 2004. Molecular mechanisms of arsenic carcinogenesis. Mol. Cell. Biochem. 255, 57–66.

Institute of Medicine, 1998. Folate. In: Dietary Reference Intakes for Thiamin, Riboflavin, Niacin, Vitamin B6, Folate, Vitamin B12, Pantothenic Acid, Biotin, and Choline, National Academy Press, Washington, DC, pp. 196–305.

Kim, Y.I., 2000. Methylenetetrahydrofolate reductase polymorphisms, folate, and cancer risk: a paradigm of gene–nutrient interactions in carcinogenesis. Nutr. Rev. 58, 205–209.

Kitchin, K.T., 2001. Recent advances in arsenic carcinogenesis: modes of action, animal model systems, and methylated arsenic metabolites. Toxicol. Appl. Pharmacol. 172, 249–261.

Mandal, B.K., Ogra, Y., Suzuki, K.T., 2001. Identification of dimethy-larsinous and monomethylarsonous acids in human urine of the arsenic-affected areas in West Bengal, India. Chem. Res. Toxicol. 14, 371–378.

Mason, J.B., Choi, S.W., 2005. Effects of alcohol on folate metabolism: implications for carcinogenesis. Alcohol 35, 235–241.

Mass, M.J., Tennant, A., Roop, B.C., Cullen, W.R., Styblo, M., Thomas, D.J., Kligerman, A.D., 2001. Methylated trivalent arsenic species are genotoxic. Chem. Res. Toxicol. 14, 355–361.

Michaud, D.S., Spiegelman, D., Clinton, S.K., Rimm, E.B., Willett, W.C., Giovannucci, E., 2000. Prospective study of dietary supplements, macronutrients, micronutrients, and risk of bladder cancer in US men. Am. J. Epidemiol. 152, 1145–1153.

Michaud, D.S., Pietinen, P., Taylor, P.R., Virtanen, M., Virtamo, J., Albanes, D., 2002. Intakes of fruits and vegetables, carotenoids and vitamins A, E, C in relation to the risk of bladder cancer in the ATBC cohort study. Br. J. Cancer 87, 960–965.

Mitra, S.R., Mazumder, D.N., Basu, A., Block, G., Haque, R., Samanta, S., Ghosh, N., Smith, M.M., von Ehrenstein, O.S., Smith, A.H., 2004. Nutritional factors and susceptibility to arsenic-caused skin lesions in West Bengal, India. Environ. Health Perspect. 112, 1104–1109. Moyers, S., Bailey, L.B., 2001. Fetal malformations and folate

metabo-lism: review of recent evidence. Nutr. Rev. 59, 215–224.

Nesnow, S., Roop, B.C., Lambert, G., Kadiiska, M., Mason, R.P., Cullen, W.R., Mass, M.J., 2002. DNA damage induced by methylated trivalent arsenicals is mediated by reactive oxygen species. Chem. Res. Toxicol. 15, 1627–1634.

Okoji, R.S., Yu, R.C., Maronpot, R.R., Froines, J.R., 2002. Sodium arsenite administration via drinking water increases genome-wide and Ha-ras DNA hypomethylation in methyl-deficient C57BL/6J mice. Carcinogenesis 23, 777–785.

Petrick, J.S., Jagadish, B., Mash, E.A., Aposhian, H.V., 2001. Monom-ethylarsonous acid (MMA(III)) and arsenite: LD(50) in hamsters and in vitro inhibition of pyruvate dehydrogenase. Chem. Res. Toxicol. 14, 651–656.

Piyathilake, C.J., Macaluso, M., Hine, R.J., Richards, E.W., Krumdieck, C.L., 1994. Local and systemic effects of cigarette smoking on folate and vitamin B-12. Am. J. Clin. Nutr. 60, 559–566.

Reichard, J.F., Schnekenburger, M., Puga, A., 2007. Long term low-dose arsenic exposure induces loss of DNA methylation. Biochem. Biophys. Res. Commun. 352, 188–192.

Schabath, M.B., Spitz, M.R., Lerner, S.P., Pillow, P.C., Hernandez, L.M., Delclos, G.L., Grossman, H.B., Wu, X., 2005. Case-control analysis of dietary folate and risk of bladder cancer. Nutr. Cancer 53, 144– 151.

Sharp, L., Little, J., 2004. Polymorphisms in genes involved in folate metabolism and colorectal neoplasia: a huge review. Am. J. Epidemiol. 159, 423–443.

Shiomi, K., 1994. Arsenic in marine organisms: chemical forms and toxicology aspects. In: Nriagu, J.O. (Ed.), Arsenic in Environment. Part II: Human Health and Ecosystem Effect. John Wiley & Sons Inc., New York, pp. 261–282.

Spiegelstein, O., Lu, X., Le, X.C., Troen, A., Selhub, J., Melnyk, S., James, S.J., Finnell, R.H., 2003. Effects of dietary folate intake and folate binding protein-1 (Folbp1) on urinary speciation of sodium arsenate in mice. Toxicol. Lett. 145, 167–174.

Spiegelstein, O., Gould, A., Wlodarczyk, B., Tsie, M., Lu, X.F., Le, C., Troen, A., Selhub, J., Piedrahita, J.A., Salbaum, J.M., Kappen, C., Melnyk, S., James, J., Finnell, R.H., 2005a. Developmental consequences of in utero sodium arsenate exposure in mice with folate transport deficiencies. Toxicol. Appl. Pharma-col. 203, 18–26.

Spiegelstein, O., Lu, X.F., Le, X.C., Troen, A., Selhub, J., Melnyk, S., James, S.J., Finnell, R.H., 2005b. Effects of dietary folate intake and folate binding protein-2 (Folbp2) on urinary speciation of sodium arsenate in mice. Environ. Toxicol. Pharmacol. 19, 1–7.

Spuches, A.M., Kruszyna, H.G., Rich, A.M., Wilcox, D.E., 2005. Thermodynamics of the As(III)-thiol interaction: arsenite and monom-ethylarsenite complexes with glutathione, dihydrolipoic acid, and other thiol ligands. Inorg. Chem. 44, 2964–2972.

Stanger, O., 2002. Physiology of folic acid in health and disease. Curr. Drug Metab. 3, 211–223.

Steinmaus, C.M., Nunez, S., Smith, A.H., 2000. Diet and bladder cancer: a meta-analysis of six dietary variables. Am. J. Epidemiol. 151, 693– 702.

Steinmaus, C., Yuan, Y., Kalman, D., Atallah, R., Smith, A.H., 2005. Intraindividual Variability in Arsenic Methylation in a U.S. Popula-tion. Cancer Epidemiol. Biomarkers Prev. 14, 919–924.

Styblo, M., Del Razo, L.M., Vega, L., Germolec, D.R., LeCluyse, E.L., Hamilton, G.A., Reed, W., Wang, C., Cullen, W.R., Thomas, D.J., 2000. Comparative toxicity of trivalent and pentavalent inorganic and methylated arsenicals in rat and human cells. Arch. Toxicol. 74, 289– 299.

Styblo, M., Drobna, Z., Jaspers, I., Lin, S., Thomas, D.J., 2002. The role of biomethylation in toxicity and carcinogenicity of arsenic: a research update. Environ. Health Perspect. 110, 767–771.

Suh, J.R., Herbig, A.K., Stover, P.J., 2001. New perspectives on folate catabolism. Annu. Rev. Nutr. 21, 255–282.

Szklo, M., Nieto, F.J., 2007. Understanding lack of validity: bias. Epidemiology. Beyond the Basic. Jones and Bartlett Publishers Inc., pp. 109–150.

Thomas, D.J., Styblo, M., Lin, S., 2001. The cellular metabolism and systemic toxicity of arsenic. Toxicol. Appl. Pharmacol. 176, 127–144. Thomas, D.J., Waters, S.B., Styblo, M., 2004. Elucidating the pathway for

arsenic methylation. Toxicol. Appl. Pharmacol. 198, 319–326. Townsend, D.M., Tew, K.D., Tapiero, H., 2004. Sulfur containing amino

acids and human disease. Biomed. Pharmacother. 58, 47–55.

Vahter, M., 1981. Biotransformation of trivalent and pentavalent inorganic arsenic in mice and rats. Environ. Res. 25, 286–293. Vahter, M., 2002. Mechanisms of arsenic biotransformation. Toxicology,

211–217.

Vahter, M., Marafante, E., 1987. Effects of low dietary intake of methionine, choline or proteins on the biotransformation of arsenite in the rabbit. Toxicol. Lett. 37, 41–46.

Vahter, M., Couch, R., Nermell, B., Nilsson, R., 1995. Lack of methylation of inorganic arsenic in the chimpanzee. Toxicol. Appl. Pharmacol. 133, 262–268.

Valenzuela, O.L., Borja-Aburto, V.H., Garcia-Vargas, G.G., Cruz-Gonzalez, M.B., Garcia-Montalvo, E.A., Calderon-Aranda, E.S., Del Razo, L.M., 2005. Urinary trivalent methylated arsenic species in a population chronically exposed to inorganic arsenic. Environ. Health Perspect. 113, 250–254.

Yang, C.Y., Chiu, H.F., Chang, C.C., Ho, S.C., Wu, T.N., 2005. Bladder cancer mortality reduction after installation of a tap-water supply system in an arsenious-endemic area in southwestern Taiwan. Environ. Res. 98, 127–132.

Yu, R.C., Hsu, K.H., Chen, C.J., Froines, J.R., 2000. Arsenic methylation capacity and skin cancer. Cancer Epidemiol. Biomarkers Prev. 9, 1259–1262.

Zakharyan, R.A., Wildfang, E., Aposhian, H.V., 1996. Enzymatic methylation of arsenic compounds. III. The marmoset and tamarin, but not the rhesus, monkeys are deficient in methyl-transferases that methylate inorganic arsenic. Toxicol. Appl. Pharmacol. 140, 77–84.

Zeegers, M.P., Goldbohm, R.A., van den Brandt, P.A., 2001. Are retinol, vitamin C, vitamin E, folate and carotenoids intake associated with bladder cancer risk? Results from the Netherlands Cohort Study. Br. J. Cancer 85, 977–983.

Zhao, C.Q., Young, M.R., Diwan, B.A., Coogan, T.P., Waalkes, M.P., 1997. Association of arsenic-induced malignant transformation with DNA hypomethylation and aberrant gene expression. Proc. Natl. Acad. Sci. USA 94, 10907–10912.