Elevated concentrations of arsenic in groundwater pose a public health threat to millions of people worldwide. While arsenic is an established human carcinogen, a mode of action has yet to be determined for arsenic carcinogenesis. However, the oxidative stress and DNA repair pathways have been implicated in arsenic toxicity and have been hypothesized to underlie arsenic carcinogenesis. To date, few epidemiologic studies have evaluated genetic susceptibility to arsenical skin lesions based on single nucleotide polymorphisms (SNPs) in antioxidant enzyme or DNA repair genes. Utilizing cross-sectional data from the 2000-2002 survey of the Health Effects of Arsenic Longitudinal Study (HEALS) for 610 prevalent arsenical skin lesion cases and 1,079 randomly selected controls, I evaluated the associations of SNPs in genes encoding antioxidant enzymes and DNA repair enzymes on skin lesion prevalence. I also evaluated potential interactions between the SNPS as well as SNP-environment interactions in determining skin lesion prevalence. In the first study of this dissertation (Chapter 2), I assessed the relationship between SNPs in antioxidant enzyme genes and skin lesion prevalence, as well as possible interactions of these associations on the additive scale by various environmental factors. There were no statistically significant associations between these SNPs (SOD2, rs4880; CAT, rs1001179; GPX1, rs1050450; and MPO, rs2333227) and skin lesion prevalence. Additionally, there was no evidence of additive interaction by arsenic exposure levels, body mass index, smoking status, or fruit and vegetable intake with the SNPs in relation to skin lesion prevalence. However, there was marginal evidence that skin lesion prevalence was increased among individuals who carried 4 or more risk alleles compared to individuals carrying 0-3 risk alleles in these SNPs. Additionally, I observed a significant departure from additivity for the risk allele score and primary methylation index on skin lesion prevalence. In the second study of this dissertation (Chapter 3), I assessed the relationship between SNPs in DNA repair genes (OGG1, rs1052133; XRCC1, rs25487 and rs1799782; XRCC3, rs861539; ERCC2, rs1052559; ERCC5, rs17655; and LIG4, rs1805388) and skin lesion prevalence, as well as possible interactions of these associations on the additive scale by various environmental factors. In logistic regression models controlling for sex, age, and well water arsenic concentration, no associations were observed between measured SNPs and skin lesion prevalence. The results did not vary by arsenic exposure levels, body mass index, or smoking status. However, I did observe a significant inverse association of total fruit and vegetable consumption with skin lesion prevalence, and its additive interaction with the polymorphism in ERCC5. In the third study of this dissertation (Chapter 4), I utilized a multi-analytic approach to explore gene-gene, gene-environment, and higher-order interactions among 10 SNPs related to the oxidative stress and DNA repair pathways by MDR, CART, and logistic regression models. As shown in Chapters 2 and 3, none of these SNPs were associated with skin lesion prevalence, however, were evaluated for potential SNP-SNP interactions. MDR and CART modeling approaches were utilized for the selection of potential gene-gene and gene-environment interactions. Considerable overlap of the interactions detected by both these methods was observed, which were further evaluated by logistic regression. Results from logistic regression modeling, provided some evidence of these statistical interactions; however, their biological interpretation was limited. In summary, there was marginal evidence that skin lesion prevalence was increased among individuals who carried 4 or more risk alleles in genotyped SNPs related to the oxidative stress pathway compared to individuals carrying 0-3 risk alleles in these SNPs and, a significant departure from additivity was observed for the risk allele score and primary methylation index on skin lesion prevalence. Additionally, a significant inverse association of total fruit and vegetable consumption with skin lesion prevalence was observed and, a significant interaction between the polymorphism in ERCC5 and total fruit and vegetable intake was observed in relation to skin lesion prevalence on the additive scale. However, these finding require replication in other studies.

Background: In Bangladesh, more than 57 million individuals are exposed to arsenic-contaminated drinking water at concentrations that exceed the World Health Organization guideline for safe drinking water, which is 10 μg/L. Arsenic is a human carcinogen, which has also been associated with numerous non cancer outcomes, including cardiovascular disease. For many arsenic-related health outcomes, susceptibility differs by sex, with some outcomes preferentially afflicting males and others females. Although reducing exposure to arsenic-contaminated drinking water is the primary strategy for preventing arsenic toxicity, cancer risks remain elevated decades after arsenic exposure has been reduced. Therefore, public health approaches which complement arsenic remediation efforts are needed. One potential set of strategies includes nutritional interventions. Deficiencies in one-carbon metabolism (OCM nutrients can cause hyperhomocysteinemia (HHcys), which has been associated with adverse health outcomes, including cancers and cardiovascular disease. In Bangladesh, the prevalence of HHcys is quite high and differs by sex (63% among men, 26% among women). Nutrients involved in the OCM pathway may also protect against arsenic toxicity. Two potential mechanisms include: 1) by enhancing arsenic metabolism and 2) by preventing/reversing arsenic-induced epigenetic dysregulation. Arsenic metabolism facilitates urinary arsenic elimination and depends on two sequential S-adenosylmethionine (SAM)-dependent methylation steps, which yield the mono- and dimethyl arsenical species (MMA and DMA, respectively and S-adenosylhomocysteine (SAH), a potent inhibitor of most methyltransferases. SAM is synthesized via OCM, a pathway with many nutritional influences, including folate and cobalamin. There is substantial evidence from experimental studies that the OCM pathway is important for facilitating arsenic metabolism and elimination. However, the relationships between SAM, SAH, and arsenic methylation may be particularly complex in populations exposed continuously to arsenic, because 1) the arsenic metabolites compete for methylation, since each methylation step is catalyzed by the arsenic (+3) methyltransferase and requires a methyl group from SAM, and 2) folate and cobalamin nutritional status may vary between individuals. Although the mechanisms mediating arsenic toxicity remain largely unclear and are likely multifactorial, there is increasing evidence that arsenic induces epigenetic dysregulation, including alterations in both DNA methylation and posttranslational histone modifications (PTHMs), and these effects may differ by sex. Arsenic has also been shown to alter gene expression in a sex dependent manner. However, the sex-specific effects of arsenic on PTHMs and gene expression have not been confirmed in a large epidemiological study. Since many of the enzymes involved in epigenetic regulation, including DNA methyltransferases and lysine histone methyltransferases, depend on SAM, epigenetic modifications are also influenced by OCM. Previous studies have demonstrated that nutritional methyl donors involved in the OCM pathway buffer against/modify toxicant-induced alterations in DNA methylation. This may also be true for arsenic-induced alterations in PTHMs. However, the relationships between OCM indices and PTHMs have not been characterized in arsenic-exposed populations. Objectives: We had five main objectives: 1) to examine the relationships between SAM, SAH, and arsenic methylation capacity, and potential effect modification by folate and cobalamin nutritional status; 2) to characterize a specific cleavage product of histone H3, which we identified in human peripheral blood mononuclear cells (PBMCs) in our early analyses of PTHMs; 3) to evaluate the effects of arsenic exposure and arsenic removal on three candidate PTHMs (di- and tri-methylation at lysine 36 of histone H3 (H3K36me2 and H3K36me3, respectively) and di-methylation at lysine 79 of histone H3 (H3K79me2)), which were selected because they are dysregulated in cancers and are altered by arsenic and/or nutritional methyl donors in vitro; 4) to examine associations between arsenic exposure and gene-specific DNA methylation and mRNA expression, particularly for genes involved in pathways implicated in arsenic toxicity; and 5) to characterize the relationships between OCM indices and our three candidate PTHMs, and the effect of folic acid (FA) supplementation on these same PTHMs. For objectives 3-5, we also examined potential differences by sex. Methods: To address these objectives, we used data from three epidemiological studies of arsenic-exposed Bangladeshi adults: 1) the Folate and Oxidative Stress (FOX) study, a cross-sectional study of healthy individuals; 2) the Folic Acid and Creatine Trial (FACT), a randomized placebo-controlled trial (duration 24 weeks) in which healthy participants received an arsenic-removal water filter at baseline and were also randomized to one of five nutrition intervention arms: placebo, 400 μg FA/day (FA400), 800 μg FA/day (FA800), 3 g creatine/day (Creatine), and Creatine + FA400; and 3) the Bangladesh Vitamin E and Selenium Trial (BEST), a randomized placebo controlled trial (duration 6 years) in which individuals with arsenicosis were randomized to one of four nutrition intervention arms: placebo, vitamin E (alphatocopheral, 100 mg/day), selenium (L-selenomethionine, 200 μg/day), or a combination of vitamin E and selenium. In Chapter 3, we examined associations between blood SAM and SAH and the proportion (%) of each arsenic metabolite, measured in blood and urine, among FOX participants. We further examined if these associations differed within strata of folate and/or cobalamin nutritional status. In Chapter 4, we characterized a specific cleavage product of histone H3, which we identified in human PBMCs from a subset of FACT participants (n = 32). We also determined the prevalence of H3 cleavage in these samples and the impact of H3 cleavage on the measurement of downstream PTHMs. In Chapter 5, we presented sex-specific associations between pre-intervention measures of blood arsenic and creatinine-adjusted urinary arsenic (uAsCr) and PTHMs, measured in PBMCs collected from FACT participants (n = 317). We also evaluated whether PTHMs were stable for the 12 week duration after FACT participants received arsenic-removal water filters (n = 60 from placebo group). In Chapter 6, we presented associations between pre-intervention uAsCr and gene-specific DNA methylation (whole blood, n = 400) and mRNA expression (PBMCs, n = 1799) for 47 candidate genes involved in arsenic metabolism, OCM, epigenetic regulation, DNA repair, or tumor suppression/oncogenesis, using baseline-collected samples from BEST participants. We also evaluated these associations separately by sex. In Chapter 6, we examined sex-specific associations between baseline circulating concentrations of OCM indices, including folate, cobalamin, choline, betaine, and homocysteine, and PTHMs measured in PBMCs collected from FACT participants (n = 324). We also evaluated whether FA400 (n = 106), compared with placebo (n = 60), for a duration of 12 weeks increased global levels of PTHMs. Results: We observed that folate and cobalamin nutritional status significantly modified associations between SAM and the % arsenic metabolites, as hypothesized (Chapter 3). Among folate and cobalamin deficient individuals, SAM was positively associated with the %MMA, and negatively associated with the %DMA, in blood. In Chapter 4, we determined that H3 cleavage was evident in one third of the FACT PBMC samples examined. We further demonstrated that H3 cleavage impacts the measurement of certain PTHMs. In Chapter 5, we reported that biomarkers of arsenic exposure were associated with H3K36me2 in a sex-dependent manner. In particular, uAsCr was positively associated with H3K36me2 among men, but not women. Furthermore, the use of arsenic-removal water filters was associated with significant reductions in H3K36me2 over a 12 week period, but this did not differ by sex. We also observed that uAsCr was associated with the methylation and expression of several genes involved in OCM, epigenetic regulation, DNA repair, and tumor suppression, and many of these associations differed by sex (Chapter 6). The associations between several OCM indices and PTHMs were also sex-dependent (Chapter 7). Specifically, choline was positively associated with H3K36me2 among men only, while cobalamin was positively associated with H3K79me2 among women only. However, FA400 for 12 weeks did not alter global levels of the PTHMs examined. Conclusions: Given that cancer risks remain elevated decades after arsenic exposure has ceased, public health interventions which complement arsenic remediation efforts are needed. Nutritional interventions may be one promising approach. Previous studies have observed that a higher %MMA, and a lower DMA, in urine is associated with an increased risk of developing adverse health outcomes. Our finding that SAM was positively associated with %MMA, and negatively associated with %DMA, among individuals deficient for folate and cobalamin contributes additional evidence that nutritional status may explain some of the inter-individual differences in arsenic methylation capacity and, consequently, in susceptibility to arsenic toxicity. Our observation that arsenic exposure was positively associated with global levels of H3K36me2 among men, but not women, and that arsenic was associated with gene specific DNA methylation and mRNA expression in a sex-dependent manner, adds to a growing literature that arsenic induces epigenetic dysregulation differentially by sex. Furthermore, these findings suggest that this may have functional consequences, such as alterations in mRNA expression, including for genes involved in pathways implicated in arsenic toxicity. While it is tempting to speculate that this may explain some of the sex differences in susceptibility to arsenic toxicity, the clinical implications of our findings will require additional study. We also provided the first evidence from an arsenic exposed population that choline and cobalamin are associated with PTHMs(H3K36me2 and H3K79me2, respectively) in a sex-dependent manner, and that 12 weeks’ supplementation with FA, at a dose based on the recommended dietary allowance for folate, does not significantly alter global levels of H3K36me2, H3K36me3, or H3K79me2 in human PBMCs. Previous studies have shown that nutrients in the OCM pathway protect against toxicant induced alterations in DNA methylation. Our findings suggest that some OCM nutrients, particularly choline and cobalamin, may also influence PTHMs in human PBMCs. These findings lay the groundwork for future studies which further examine whether these nutrients can protect against or modify arsenic induced alterations in PTHMs.

Arsenic is a naturally occurring toxic metal and its presence in food composites could be a potential risk to the health of both humans and animals. Arseniccontaminated groundwater is often used for food and animal consumption, irrigation of soils, which could potentially lead to arsenic entering the human food chain. Its side effects include multiple organ damage, cancers, heart disease, diabetes mellitus, hypertension, lung disease and peripheral vascular disease. Research investigations, epidemiologic surveys and total diet studies (market baskets) provide datasets, information and knowledge on arsenic content in foods. The determination of the concentration of arsenic in rice varieties is an active area of research. With the increasing capability to measure the concentration of arsenic in foods, there are volumes of varied and continuously generated datasets on arsenic in food groups. Visual analytics, which integrates techniques from information visualization and computational data analysis via interactive visual interfaces, presents an approach to enable data on arsenic concentrations to be visually represented. The goal of this doctoral research in Environmental Science is to address the need to provide visual analytical decision support tools on arsenic content in various foods with special emphasis on rice. The hypothesis of this doctoral thesis research is that software enabled visual representation and user interaction facilitated by visual interfaces will help discover hidden relationships between arsenic content and food categories. The specific objectives investigated were: (1) Provide insightful visual analytic views of compiled data on arsenic in food categories; (2) Categorize table ready foods by arsenic content; (3) Compare arsenic content in rice product categories and (4) Identify informative sentences on arsenic concentrations in rice. The overall research method is secondary data analyses using visual analytics techniques implemented through Tableau Software. Several datasets were utilized to conduct visual analytical representations of data on arsenic concentrations in foods. These consisted of (i) arsenic concentrations in 459 crop samples; (ii) arsenic concentrations in 328 table ready foods from multi-year total diet studies; (iii) estimates of daily inorganic arsenic intake for 49 food groups from multicountry total diet studies; (iv) arsenic content in rice product categories for 193 samples of rice and rice products; (v) 758 sentences extracted from PubMed abstracts on arsenic in rice. Several key insights were made in this doctoral research. The concentration of inorganic arsenic in instant rice was lower than those of other rice types. The concentration of Dimethylarsinic Acid (DMA) in wild rice, an aquatic grass, was notably lower than rice varieties (e.g. 0.0099 ppm versus 0.182 for a long grain white rice). The categorization of 328 table ready foods into 12 categories enhances the communication on arsenic concentrations. Outlier concentration of arsenic in rice were observed in views constructed for integrating data from four total diet studies. The 193 rice samples were grouped into two groups using a cut-off level of 3 mcg of inorganic arsenic per serving. The visual analytics views constructed allow users to specify cut-off levels desired. A total of 86 sentences from 53 PubMed abstracts were identified as informative for arsenic concentrations. The sentences enabled literature curation for arsenic concentration and additional supporting information such as location of the research. An informative sentence provided global “normal” range of 0.08 to 0.20 mg/kg for arsenic in rice. A visual analytics resource developed was a dashboard that facilitates the interaction with text and a connection to the knowledge base of the PubMed literature database. The research reported provides a foundation for additional investigations on visual analytics of data on arsenic concentrations in foods. Considering the massive and complex data associated with contaminants in foods, the development of visual analytics tools are needed to facilitate diverse human cognitive tasks. Visual analytics tools can provide integrated automated analysis; interaction with data; and data visualization critically needed to enhance decision making. Stakeholders that would benefit include consumers; food and health safety personnel; farmers; and food producers. Arsenic content of baby foods warrants attention because of the early life exposures that could have life time adverse health consequences. The action of microorganisms in the soil is associated with availability of arsenic species for uptake by plants. Genomic data on microbial communities presents wealth of data to identify mitigation strategies for arsenic uptake by plants. Arsenic metabolism pathways encoded in microbial genomes warrants further research. Visual analytics tasks could facilitate the discovery of biological processes for mitigating arsenic uptake from soil. The increasing availability of central resources on data from total diet studies and research investigations presents a need for personnel with diverse levels of skills in data management and analysis. Training workshops and courses on the foundations and applications of visual analytics can contribute to global workforce development in food safety and environmental health. Research investigations could determine learning gains accomplished through hardware and software for visual analytics. Finally, there is need to develop and evaluate informatics tools that have visual analytics capabilities in the domain of contaminants in foods. / Environmental Sciences / P. Phil. (Environmental Science)

Arsenic is a naturally occurring toxic metal and its presence in food composites could be a potential risk to the health of both humans and animals. Arseniccontaminated groundwater is often used for food and animal consumption, irrigation of soils, which could potentially lead to arsenic entering the human food chain. Its side effects include multiple organ damage, cancers, heart disease, diabetes mellitus, hypertension, lung disease and peripheral vascular disease. Research investigations, epidemiologic surveys and total diet studies (market baskets) provide datasets, information and knowledge on arsenic content in foods. The determination of the concentration of arsenic in rice varieties is an active area of research. With the increasing capability to measure the concentration of arsenic in foods, there are volumes of varied and continuously generated datasets on arsenic in food groups. Visual analytics, which integrates techniques from information visualization and computational data analysis via interactive visual interfaces, presents an approach to enable data on arsenic concentrations to be visually represented. The goal of this doctoral research in Environmental Science is to address the need to provide visual analytical decision support tools on arsenic content in various foods with special emphasis on rice. The hypothesis of this doctoral thesis research is that software enabled visual representation and user interaction facilitated by visual interfaces will help discover hidden relationships between arsenic content and food categories. The specific objectives investigated were: (1) Provide insightful visual analytic views of compiled data on arsenic in food categories; (2) Categorize table ready foods by arsenic content; (3) Compare arsenic content in rice product categories and (4) Identify informative sentences on arsenic concentrations in rice. The overall research method is secondary data analyses using visual analytics techniques implemented through Tableau Software. Several datasets were utilized to conduct visual analytical representations of data on arsenic concentrations in foods. These consisted of (i) arsenic concentrations in 459 crop samples; (ii) arsenic concentrations in 328 table ready foods from multi-year total diet studies; (iii) estimates of daily inorganic arsenic intake for 49 food groups from multicountry total diet studies; (iv) arsenic content in rice product categories for 193 samples of rice and rice products; (v) 758 sentences extracted from PubMed abstracts on arsenic in rice. Several key insights were made in this doctoral research. The concentration of inorganic arsenic in instant rice was lower than those of other rice types. The concentration of Dimethylarsinic Acid (DMA) in wild rice, an aquatic grass, was notably lower than rice varieties (e.g. 0.0099 ppm versus 0.182 for a long grain white rice). The categorization of 328 table ready foods into 12 categories enhances the communication on arsenic concentrations. Outlier concentration of arsenic in rice were observed in views constructed for integrating data from four total diet studies. The 193 rice samples were grouped into two groups using a cut-off level of 3 mcg of inorganic arsenic per serving. The visual analytics views constructed allow users to specify cut-off levels desired. A total of 86 sentences from 53 PubMed abstracts were identified as informative for arsenic concentrations. The sentences enabled literature curation for arsenic concentration and additional supporting information such as location of the research. An informative sentence provided global “normal” range of 0.08 to 0.20 mg/kg for arsenic in rice. A visual analytics resource developed was a dashboard that facilitates the interaction with text and a connection to the knowledge base of the PubMed literature database. The research reported provides a foundation for additional investigations on visual analytics of data on arsenic concentrations in foods. Considering the massive and complex data associated with contaminants in foods, the development of visual analytics tools are needed to facilitate diverse human cognitive tasks. Visual analytics tools can provide integrated automated analysis; interaction with data; and data visualization critically needed to enhance decision making. Stakeholders that would benefit include consumers; food and health safety personnel; farmers; and food producers. Arsenic content of baby foods warrants attention because of the early life exposures that could have life time adverse health consequences. The action of microorganisms in the soil is associated with availability of arsenic species for uptake by plants. Genomic data on microbial communities presents wealth of data to identify mitigation strategies for arsenic uptake by plants. Arsenic metabolism pathways encoded in microbial genomes warrants further research. Visual analytics tasks could facilitate the discovery of biological processes for mitigating arsenic uptake from soil. The increasing availability of central resources on data from total diet studies and research investigations presents a need for personnel with diverse levels of skills in data management and analysis. Training workshops and courses on the foundations and applications of visual analytics can contribute to global workforce development in food safety and environmental health. Research investigations could determine learning gains accomplished through hardware and software for visual analytics. Finally, there is need to develop and evaluate informatics tools that have visual analytics capabilities in the domain of contaminants in foods. / Environmental Sciences / P. Phil. (Environmental Science)