Electrocardiogram (ECG) Abnormality Among Residents in Arseniasis-Endemic and Non-Endemic Areas of Southwestern Taiwan – A Study of Gene-Gene and Gene-Environment Interactions

Natural occurrence of arsenic in groundwater is found in the Americas, European, Western Africa, and Asia including Taiwan, Japan, southern Thailand and China where in some areas, drinking water supplies are primarily based on groundwater resources 2. For general population in southwestern coast Taiwan, the major arsenic exposure resource is the ingestion of arsenic contaminated groundwater. The residents have used high-arsenic contaminated well water for drinking and cooking for many decades since early 1910s. The tap water supply system was implemented in the early 1960s, however artesian well water has not been used for drinking or cooking until mid-1970s 3. Because arsenic toxicity operates in a highly nonlinear manner and different levels of exposure measurements applied result in large discrepancy across studies and made it difficult to come up a reliable dose-response relationship for arsenic hazard. There is a long-standing observation of individual variability in susceptibility to arsenic toxicity 4 and this variation may be partly due to differences in age and sex distribution across areas, and also individual arsenic metabolism capabilities 5,6. Inter-individual differences in the speciation and amounts of arsenic metabolites have been reported among subjects chronically exposed to arsenic 7 and significant genetic determinants of arsenic metabolism was supported by epidemiological study 8. Toenail and hair arsenic has been reported to provided an integrated measure of internal arsenic exposure 9. However epidemiologic studies showed that external contamination lead to overestimation of internal dose and urinary arsenic concentration seems to be a better marker than concentrations in drinking water10. Growing epidemiological evidence also suggests that some factors such as age, sex and genetic susceptibility are related to its metabolism and can be important predictors for arsenic-related health hazard 11,12.


Introduction
Natural occurrence of arsenic in groundwater is found in the Americas, European, Western Africa, and Asia including Taiwan, Japan, southern Thailand and China where in some areas, drinking water supplies are primarily based on groundwater resources 2 .For general population in southwestern coast Taiwan, the major arsenic exposure resource is the ingestion of arsenic contaminated groundwater.The residents have used high-arsenic contaminated well water for drinking and cooking for many decades since early 1910s.The tap water supply system was implemented in the early 1960s, however artesian well water has not been used for drinking or cooking until mid-1970s 3 .Because arsenic toxicity operates in a highly nonlinear manner and different levels of exposure measurements applied result in large discrepancy across studies and made it difficult to come up a reliable dose-response relationship for arsenic hazard.There is a long-standing observation of individual variability in susceptibility to arsenic toxicity 4 and this variation may be partly due to differences in age and sex distribution across areas, and also individual arsenic metabolism capabilities 5,6 .Inter-individual differences in the speciation and amounts of arsenic metabolites have been reported among subjects chronically exposed to arsenic 7 and significant genetic determinants of arsenic metabolism was supported by epidemiological study 8 .Toenail and hair arsenic has been reported to provided an integrated measure of internal arsenic exposure 9 .However epidemiologic studies showed that external contamination lead to overestimation of internal dose and urinary arsenic concentration seems to be a better marker than concentrations in drinking water 10 .Growing epidemiological evidence also suggests that some factors such as age, sex and genetic susceptibility are related to its metabolism and can be important predictors for arsenic-related health hazard 11,12 .
Epidemiology studies have showed that the population attributable fractions to CHD of subclinical disease was 36.8% and 42.5% for men and women respectively, which is much higher than for most of the known risk factors or combination of risk factors and further documents the importance of subclinical disease as a contributor to subsequent incident clinical disease 45 .Among coronary artery disease (CAD) patients, the preoperative electrocardiogram (ECG) is shown to be predictive of long-term outcome independent of clinical findings and perioperative ischemia 47 .Moreover, unrecognized silent myocardial infarction as diagnosed by electrographic changes is a major risk factor for subsequent myocardial infarction and coronary disease deaths 48 , and it is also a useful additional tool for differentiating the x-lined form of hereditary cardiac myopathies 49 .Subclinical disease and clinical disease shared similar risk factors and thus aggressive interventions to prevent clinical disease should be oriented to individuals with subclinical disease 50 .Various ECG abnormalities have been observed among cases of acute arsenic poisoning and in acute promyelocytic leukemia patients treated with arsenic trioxide.Individuals exposed to excess arsenic through drinking water showed some of the ECG abnormalities 51 .QT prolongation and dispersion have been implicated in the genesis of ventricular arrhythmia and directly predictors of cardiovascular and all-cause mortality 52,53 .The gradient relationship of chronic arsenic poisoning and prolonged QT interval and increased QT dispersion has been reported recently 54,55 and arsenic-induced QT dispersion was associated with atherosclerosis disease and predicted cardiovascular mortality.However, evidence was based on risk assessment on subjects with previous exposure to high arsenic level and biomarkers for methylation metabolism were not considered.Besides, the accuracy and reproducibility of ECG reading including QT dispersion measurement have been restricted by difficulties with reliable determination of T-waves offset.Further study with a standardize measurement of ECG reading is warranted for a reliable assessment of ECG abnormality.Although an association between chronic arsenic exposure and CVD has been found in many studies, nearly all of these studies were limited by use of cross-sectional data, and longitudinal evidence by follow-up study was still limited.Besides, majority of previous studies were focus on the clinical arsenic-related cardiovascular disease, instead of the manifest of preclinical or subclinical detections.Morbidity and mortality from peripheral vascular disease, ischemic heart disease, and cerebral infarction are relative late clinical manifestations of chronic arsenic damage.These health effects may be the consequence of the interactions between predisposing and precipitating factors for cardiovascular diseases.The risk assessment based on these late cardiovascular events may be underestimated due to competing causes of death and the correctness in the diagnosis of the sudden death from cardiovascular diseases.Studies based on subclinical finding including ECG abnormality are needed to detect the early sign of chronic poisoning.Furthermore, the variation in distribution of arsenic in human urine across areas 31 suggested that there are genetic factors in the regulation of the enzymes that metabolize arsenic, which may lead to difference in toxicity related to arsenic exposure.Association studies based on genetic polymorphisms have not provided consensus data that could generate a viable hypothesis on the molecular mechanism that determines the genetic basis of arsenic toxicity.The major objective of this study is to investigate the joint contribution of genetic factors including PON1, AS3MT, and GSTO gene families and the long-term arsenic impacts on cardiovascular disease through measuring ECG abnormality as subclinical phenotypes and to evaluate whether the arsenic methylation patterns modifies the association between cumulative arsenic exposure and the risk of CVD.

Study area and population
The study included a community-based cohort from previous arseniasis-endemic area in southwestern Taiwan and a non-exposed population recruited from documented nonendemic area in the same county with similar age, gender contribution and ecological status in 2002.The arseniasis-endemic area included Homei, Fusin and Hsinming villages in Putai Township on the southwestern coast of Taiwan which had been described previously [56][57][58] .In short, residents in the study area consumed high-arsenic contaminated well water for decades since the 1910s because of the high salinity in shallow village wells 23 .The arsenic concentration of artesian well water measured in the early 1960s was from 0.035 to 1.14 ppm, with a median of 0.78 ppm 59,60 .An estimated total daily amount of arsenic ingested by local residents was as high as 1 mg, mainly from drinking water 61 .A tap water supply system was implemented in the area in the early 1960s and the entire arseniasis-endemic area has been supplied with municipal water since the early 1970s.The arsenic concentration of tap water supplied in the study area was less than 0.01 ppm 62 .The original cohort established in 1989 including 1571 residents and 1081 subjects provided informed consents and enrolled in the study cohort.In 1993, 732 residents from the villages had a 12lead baseline Electrocardiogram (ECG) recorded.In 2002, after an average follow up period of eight years, 216 out of 380 subjects recruited provided a second ECG recording; 141 of them provided blood and urine specimens without an ECG recording; 229 were dead and their mortality determined through linkage with the national database; and the remaining 146 were lost to follow-up.Among the 121 residents with normal baseline ECGs, 42 developed an ECG abnormality at follow up.The non-exposed area was Chiali Township where the arsenic concentration of well water was very low according to the results of surveys conducted in 1960s and 1970s 60,63 .Climate, ethnic background (Han Chinese), urbanization degree and socioeconomic status were similar between Putai and Chiali.Frequency matching by age strata and gender were conducted for recruitment of resident and a total of 303 subjects were recruited.

Measurement of arsenic exposure
Arsenic level of well water for this study area was measured by the National Taiwan University group 60 .The water-contained arsenic recovery efficiencies were 95 percent or greater and were obtained using a PerkinElmer UV-VIS Spectrophotometer incorporating with Klett-Summerson Colorimeter.Detail validations of the water arsenic levels have been presented previously 57,64 .For villages which used more than one artesian well as a source of potable water, the medial levels of water arsenic contamination across those wells were assigned.The arsenic levels in artesian well water in this study area have been reported to be stable 65 .An index of cumulative arsenic exposure (micrograms per liter-years) were defined as the summation of products derived by multiplying the arsenic concentration (in micrograms per liter) in well water by duration of water consumption (in years) during consecutive periods of living in the defacement villages.Both cumulative arsenic exposure and average arsenic concentrations in drinking water were calculated only for subjects who had complete information on arsenic exposure from drinking water throughout his or her lifetime.

Questionnaire interview
At both baseline and follow-up, well trained public health nurses carried out the standardized personal interview based on a structured questionnaire to acquire information regarding demographic and socioeconomic characteristics, artesian well water usage, residential history, lifestyle variables, personal and family disease history of hypertension, diabetes, and cardiovascular diseases.Cumulative arsenic exposure (in ppm-years) was derived from the median arsenic concentration in artesian well water (ppm) in the village where the subject lived and the duration of consuming the artesian well water (years)while residing in the village.The human Ethical Committee of the National Health Research Institutes in Taiwan approved the study protocol which based on the ethical standards formulated from the Helsinki Declarations of 1964 and revised in 2000 66 .Informed consent was provided to each subject before participation.

Biochemical measurements
Fasting plasma was used for quantitative determination of blood glucose, cholesterol, triglycerides, high-and low-density lipoproteins, and urine acid were analyzed using the same instrument.Urinary samples were collected from each subject for arsenic species analyses.Subjects were asked not to consume seafood three days before urine collection.Arsenic species in urine including arsenite (AsIII), arsenate (AsV), monomethyl arsenical (MMA) and dimethyl arsenical (DMA) were quantified using high-performance liquid chromatography (HPLC) coupled with flow injection atomic absorption spectrometry.The HPLC system consisted of a solvent delivery pump (PU-1580, Jasco, Tokyo, Japan) and a silica-based anion-exchange column (Nucleosil 10 SB, 250 mm×4.6 mm; Phenomenex, CA, USA) with a guard column packed with the same material.A flow injection analysis system (FIAS-400, PerkinElmer, CT, USA) was designed as the on-line interface to the continuous hydride generation system (Analyst 100, PerkinElmer, CT, USA) used in this study.With this method, the within-say and between-day precision (coefficient of variance, CV%) for AsIII, AsV, MMA, and DMA determinations ranged from 1.0 to 3.7% were observed.Furthermore, the recoveries for AsIII, AsV, MMA, and DMA were 99.0, 98.9, 99.0, and 99.0% while the detection limits were 0.75, 1.47, 1.19, and 0.76 μg/L, respectively.The primary methylation index (PMI) was defined as the ratio between MMA and iAs levels, and the secondary methylation index (SMI) was defined as the ratio between DMA and MMA.

Genotyping
Eight functional polymorphisms: C-108T (promoter), L55M (exon 3) and Q192R (exon 6) of PON1, A148G (exon 5) and C311S (exon 9) of PON2, M287T (exon 9) of AS3MT, A140D (exon 4) of GSTO1, and N142D (exon 5) of GSTO2.SNPs were selected from NCBI's SNP database based on prior implication in disease and minor allele frequency.Genomic DNA was extracted from whole blood using standard techniques.The AS3MT M287T polymorphism was EElectrocardiogram (ECG) Abnormality Among Residents in Arseniasis-Endemic and Non-Endemic Areas of Southwestern Taiwan -A Study of Gene-Gene and… 303 determined using a commercially designed TaqMan SNP Genotyping Assay (Applied Biosystems, USA).All other genotypes will be conducted by PCR amplification followed by polymorphism-specific restriction enzyme digestion and gel analysis.

Physical examination
Resting twelve-lead conventional ECG recording was performed at the Beimen Branch, Shinyin Hospital.Minnesota standardized code classification 1 was evaluated for both baseline and follow-up ECG readings at Epidemiological Cardiology Research Center (EPICARE), Department of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA (blinded to all other study data).ECG readings were classified into normal and abnormal (including minor and major abnormality) according to the definition of cardiac function by myocardial infarction or ischemia (Q wave and STT change) (MC_1, MC_4, MC_5, MC_92), conduction defect (MC_7), arrhythmias (MC_6, MC_81~MC_88), atrial enlargement or ventricular hypertrophy (LVH_MC3/LVH_CV), and prolonged ventricular repolarization.Fasting plasma was analyzed for blood glucose, cholesterol, triglycerides, high-and low-density lipoproteins, and urine acid by Beckmen SYNCHRON LX20 System (Beckman Coulter, Fullerton, CA).

Statistical analysis
Differences in demographic characteristics and cardiovascular risk factors between ECG normal and abnormal subjects were assessed.Continuous variables were expressed as mean  standard deviation (SD) and evaluated by student's t or Wilcoxon rank-sum test.Categorical variables were expressed as proportions and compared using chi-square test or Fisher's exact test.Allele frequencies, genotype frequencies, and Hardy-Weinberg equilibrium were assessed separately in ECG abnormal and normal groups using SAS-genetics package.Relative distribution of polymorphisms in the ECG abnormal and ECG normal groups was assessed by chi-square analyses.Linkage disequilibrium (LD) as measured by D ' was assessed using Haploview 4.0 (http://www.broad.mit.edu/mpg/haploview/). Haplotypes and tag SNPs were inferred using SAS.Logistic regression analysis was used to assess the effect of cardiovascular risk factors and genetic polymorphisms in relation to ECG abnormality.Arsenic exposure and ECG abnormality in between study subjects in Putai and Chiali areas were also compared.Arsenic exposure in Putai area were stratified into two categories by median levels and subjects in Chiali area were used as reference group, and a trend test was conducted to evaluate the dose-relationship.ANOVA was conducted to evaluate urinary arsenic species between subjects with normal and abnormal ECG reading.A p value <0.05 was considered statistically significant.Permutation test, a significance test used to obtain the unknown reference distribution by calculating all possible values of the test statistic under random rearrangements of the disease status on the observed study subjects , was used to control for type 1 error for multiple testing due to the limited sample size, and the empirical pvalues were reported 67 .Statistical analyses were conducted using SAS version 9.1 (SAS, Inc., Cary, NC).

Results
Baseline characteristics of arsenic exposure and cardiovascular risk factors among study subjects are summarized in Table 1.A total of 42 incident cases among the 121 baselinewww.intechopen.comAdvances in Electrocardiograms -Clinical Applications 304 normal study subjects showed ECG deterioration at follow-up.Compared to ECG normal subjects, those with an ECG abnormality had significantly higher arsenic exposure as shown by both years of drinking artesian water and cumulative arsenic exposure index.Age and proportion of cigarette smoking in the ECG abnormal group tended to be higher but did not reach statistical significance.No differences were observed in other cardiovascular risk factors including gender, alcohol consumption, BMI, serum lipids, blood pressure, and plasma glucose.Figure 1 shows the related position and linkage disequilibrium (LD) between SNPs in the PON and GSTO gene clusters.Two SNPs within PON2 (C311S and A148G) and GSTO1-A140D and GSTO2-N142 were in high LD but SNPs within PON1 or adjacent SNPs between PON1 and PON2 (C-108T and C311s) had low LD measurements, implying they were not in the same LD block.Q192R, C-108T, C311S and A140D were identified as tag-SNPs.

Haplotype analysis and association with ECG abnormality
Haplotypes of PON1, PON2, GSTO1, GSTO2 and tag-SNPs of the PON gene cluster were constructed, and those whose frequencies were <5% were excluded from association analysis (Table 3).Overall, the effects of these haplotypes on ECG abnormality were not statistically significant after 10,000 permutations; however, the haplotype R-C-S constructed by Q192R, C-108T and C311S had the highest odds,  The relative odds of lipid profiles for PON-haplotype R-C-S carrier compared with noncarriers are shown in Figure 2. The R-C-S haplotype was positively correlated with higher serum HDL-cholesterol, LDL-cholesterol, and triglyceride levels without statistical significance, but was significantly associated with increased total cholesterol levels (OR=2.91,95% CI: 1.13-7.70).

Synergistic association of PON haplotype and arsenic on ECG abnormality
The synergistic associations between PON haplotype and arsenic exposure are summarized in Table 4.The PON R-C-S haplotype carrier with higher cumulative arsenic exposure (greater than the median value of 14.7 ppm-years) showed a >14.66 (95% CI: 1.83-117.64)increased risk for ECG abnormality compared to non-RCS haplotype carriers with low cumulative arsenic exposure (<14.7 ppm-years) (Table 4a).The PON R-C-S haplotype carrier with more years of drinking artesian water (greater than the median of 21 years) had a 10.83-fold (95% CI: 1.83-64.03)increased risk (Table 4b).These associations were even stronger after adjusting for age, gender, and cigarette smoking, when the odds increased to 19.19 (95% CI: 1.86-197.76)and 21.09 (95% CI: 2.77-160.35)for cumulative exposure index and drinking years, respectively.Table 5 showed the correlation between cumulative arsenic exposure and urinary arsenic species from arsenic endemic and non-endemic areas in southwestern Taiwan.Subjects with higher cumulative arsenic exposure had significantly higher levels of As (III), iAs, MMA, Summation of iAs and MMA.However, DMA levels and SMI were significantly lower among subjects with high arsenic exposure.Similar pattern was observed when urinary arsenic was analyzed in percentage.Subjects with higher cumulative arsenic exposure had higher percentages of As(III), iAs and MMA in urinary and lower DMA percentage.Distribution between levels of cumulative arsenic exposure and ECG abnormality was summarized in Table 6.Significant dose-response relationships were observed between higher levels of cumulative arsenic exposure and ECG reading regarding abnormalities, myocardial infarction or ischemia disease, and also atrial enlargement and ventricular hypertrophy.Increased cumulative arsenic exposure was also correlated with a higher proportion of abnormality in prolonged ventricular repolarization however not reach statistical significance.

Discussion
Various ECG abnormalities have been observed among cases of acute arsenic poisoning and in acute promyelocytic leukemia patients treated with arsenic trioxide.Individuals exposed to excess arsenic through drinking water showed some of the ECG abnormalities 51 .Several epidemiologic studies showed that QT prolongation and increased CVD mortality among high levels of arsenic-exposed subjects.However, the results might not be applicable in subjects with low to moderate arsenic.Our data replicated this association in an arseniasisendemic area and a well-matched control area which no previous history of water contamination.We highlighted the correlation between previous chronic arsenic exposure and ECG abnormalities after cessation of arsenic-contaminated water consumption for decades.
The major strength of this study was to apply a standardized Minnesota coding classification of ECG reading that ensures good quality assurance and control.Furthermore, detailed parameters regarding ECG abnormalities allowed us to evaluate the minor changes due to arsenic toxicity.In current analyses, higher duration of arsenic water consumption was associated with ECG abnormality, myocardial infarction or ischemia, atrial enlargement or ventricular hypertrophy in a dose-response relationship.Besides, it was also positively correlated to arrhythmia and prolonged ventricular repolarization without reached the statistical significance.Moreover, higher levels of cumulative arsenic exposure were also associated with ECG parameters including higher PR duration, QRS duration and QRS axis and smaller JT duration, JT index and RaVL (data not shown).There were still some limitations for this study.First, results from this study were based on a population with history of arsenic exposure.Insignificant association between urinary methylation capabilities might due to attrition of high-level arsenic exposed subjects, competing risks for CVD mortality was not considered in current analysis.Another limitation of the present study was that the measurement of urinary metabolism species and physical evaluation were conducted at a cross-sectional design.The causal-relationship between urinary species of arsenic and ECG abnormality could not be inferred given current evidence.However, the previous exposure status was significantly correlated with current urinary arsenic species implied it was more efficient among subjects after cessation of longterm exposure to high levels of arsenic.These results may have implications for arsenic mediation strategies in areas currently exposed to potentially harmful levels of arsenic in drinking water.Furthermore, CVD usually took years for disease development.Correlation may be biased due to unmeasured factors during a relative short follow-up period.Longer d u r a t i o n o f f o l l o w -u p w i t h s e r i a l c h a n ges for ECG abnormality would help better understand the underlying mechanism regarding arsenic-induced hazards.
The major significance by this study was the assessment of arsenic risk from subjects without exposure of inorganic arsenic to moderate and relatively high levels of cumulative arsenic exposure.Causal inference can be strengthened by the dose-response relationship by the stronger effect in a susceptible subgroup of the population.Besides, this study demonstrated significant gene-gene and gene-environment interactions by showing PON1 gene cluster including polymorphisms of PON1: Q192R, PON1: C-108T, and PON2: C311S and latent effect of arsenic exposure on incidence of ECG abnormality.Besides, PON2: C311S was independently associated with LDH elevation and further predicted future CVD mortality independent to other conventional risk factors including age, gender, cigarette smoking, hypertension and diabetes mellitus.After cessation of arsenic-contaminated water consumption for decades, biomarkers for CVD mortality and morbidity was still associated with reduced risks for arsenic and attributable to underlying genetic predisposition.Such data may also help risk assessment in the population and provide knowledge about the underlying mechanisms.HDL has been shown to prevent atherogenesis in vivo and in vitro through anti-oxidative and anti-inflammatory activities 35 .The major part of anti-atherogenic properties associated with HDL is explained by the activity of Paraoxonase 1 68 .Both PON1 and PON2 belong to the protein family of Paraoxonase 1 that includes PON3 which has been suggested that involved in CVD 69 .PON1 directly form part of HDL particles whereas PON2 found in endothelial cells, smooth muscle cells and macrophages that possesses antioxidant properties similar to PON1 by delays cellular oxidative stress and prevents apoptosis in vascular endothelial cells 70,71 .Regarding three common polymorphisms in coding region of the human PON1 gene, the frequencies of Q192R, L55M, and C-108T for Taiwanese population were similar to those reported in the literature for the Chinese population 72,73 .Besides, we confirmed that paraoxonase, diazoxonase and arylesterase activities were directly influenced by the Q192R and C-108T polymorphisms.Previous studies had also shown that 311 C allele in PON2 was associated with increased risks of coronary artery disease, MI and also diabetic nephropathy [74][75][76] .Our data confirmed the significance of PON2: C311S polymorphism during pathogenesis of CVD among chronic arsenic exposed subject.This finding could help to identify subjects at higher risk of cardiovascular damage for arsenic toxicity.However, some other factors that might have influenced the arsenic methylation profiles were not considered.Nutritional status and dietary intake may also be uncontrollable factors.Besides, we could not obtain the accurate data on allele distribution three polymorphisms: PON1: C-108T, GSTO1:A140D, and AS3MT: L55M in our samples.We still could not rule out the intra-and inter-individual variability to arsenic methylation and also their impacts on pathogenesis of CVD morbidity and mortality.Besides, the arsenic levels in rice growing in the arsenic contaminated area or inorganic arsenic from fish intake may be elevated.This might potentially increase arsenic exposure in the endemic area [77][78][79][80] .Future study of exposure assessment is needed.In addition, arsenic exposure has also been shown to alter the methylation level of both global DNA and certain genes in studies that analyzed a limited number of epigenetic endpoints 81 .Therefore, it is necessary to enlarge sample size for the evaluation of genetic association and ECG abnormality and other confounders that may be directly related to arsenic risks.Genome-wide association studies (GWAS) have been applied in the search for suscepitibility genes to coronary artery disease, myocardial infarction and heart failure [82][83][84] .However, none of the candidate regions and genes showed a powerful association with CVD at genomewide significance and the molecular and biological mechanisms remains unclear.
Atherosclerosis is a multifactorial disease that may lead to myocardial infarction or heart failure.A conservative estimate would be that at least 100 genes have the potential to affect the modifying factors including atherosclerosis, myocardial infarction and congestive heart failure with each having a genetic contribution of as much as 2% to the phenotype 84 .Since CVD usually took years to develop, correlation may be biased due to unmeasured factors during a relative short follow-up period or relatively underestimated by competing risk.
Our studies with longer duration of follow-up with serial changes for ECG abnormality did help better understand the underlying mechanism and duration regarding arsenic-induced hazards.These findings emphasize the importance of long term arsenic effect, along with the necessity of intensive follow-up for preclinical or subclinical phenotypes such as ECG abnormality for preventing excessive CVD mortality.

Fig. 1 .
Fig. 1.Linkage disequilibrium (LD) plot of PON1 and GSTO gene clusters in 121 study subjects.The measure of LD (D') among all possible pairs of SNPs is shown graphically.Dark red represents high D' while white represents low D'

Table 1 .
Baseline characteristics of arsenic and CVD risk factors among baseline-normal study participants classified by ECG status at follow-up Data are reported as mean ± SD or counts (%) HDL: high density lipoprotein; LDL: low density lipoprotein; CHOL: total cholesterol levels; SBP: systolic blood pressure; DBP: diastolic blood pressure, AC: ante cibum, PC: post cibum

Table 2 .
Association of SNPs and Hardy-Weinberg equilibrium test

Table 3 .
Estimated haplotype frequencies and haplotypes association analysis with ECG abnormality

Table 5 .
Correlation of cumulative arsenic exposure and urinary metabolism capacity a Permutation analysis adjusted by age, gender and cigarette smoking DAW: Drinking artesian water (years) RCS: Q192R, C-108T & C311S R-C-S haplotype Table 4b.Synergistic effects of Q192R, C-108T, and C311S R-C-S haplotypes carrier and more years of drinking artesian water (DAW) (> mean of 21 years) on ECG abnormality www.intechopen.com

Table 6 .
Distribution of ECG reading by cumulative arsenic exposure