Open Access

Review

Materials and Methods Top

Search strategy and study selection.

We searched the Medline database (http://www.ncbi.nlm.nih.gov/entrez/query​.fcgi?db=PubMed ) and the TOXNET database [consisting of TOXLINE, GENETOX, and DART/ETIC (Developmental and Reproductive Toxicology/Environmental Teratogen Information Center); http://toxnet.nlm.nih.gov/] from 1966 through July 2005 using free text and the medical subject headings (MeSH) arsenic, arsenite, arsenate, arsenicals, diabetes, glucose, glycosylated hemoglobin, insulin, and mortality. In addition, we manually reviewed the reference lists from relevant original research and review articles.

For experimental studies, we identified in vitro or in vivo studies of the administration of arsenic or arsenic compounds, including inorganic arsenite (trivalent arsenic), inorganic arsenate (pentavalent arsenic), and others, and outcomes related to diabetes status or glucose and insulin metabolism. For epidemiologic studies, we identified studies assessing arsenic exposure through measures of environmental samples, biomarkers, or indirect measures (e.g., job titles reflecting occupational exposure or living in areas with known exposure via drinking water) and diabetes status or markers of glucose metabolism.

The exclusion criteria for experimental and epidemiologic studies were a) no original research (reviews, editorials, nonresearch letters); b) studies performed only on people with diabetes, including case reports; c) lack of outcomes related to diabetes or glucose metabolism; d) no data on arsenic exposure; e) experiments in nonmammalian cells, or noncellular experiments; f) animal studies administering a single dose of arsenic; and g) culture cell experiments using lewisite or oxophenylarsine. Figure 1 summarizes the study selection process.

Two investigators (A.N.-A., R.A.S.) independently abstracted the articles that met the selection criteria. Discrepancies were resolved by consensus. We converted all arsenic concentrations to parts per million (ppm) or parts per billion (ppb), including concentrations from in vitro studies, which were usually reported in molar units of arsenic (1 μM of arsenic = 74.9 μg/L = 74.9 ppb).

Statistical methods.

Measures of association in epidemiologic studies (odds ratios, prevalence ratios, standardized mortality ratios, relative risks, relative hazards, comparisons of means) and their SE values were abstracted or derived using data reported in the articles (Greenland 1987). Within each study, we used the model adjusted for the most covariates. Adjustment did not substantially modify the conclusions of any individual study. For five studies, we used data available in the original articles to derive relative risk estimates. For one study (Lagerkvist and Zetterlund 1994), because there were no cases among the unexposed, we added 0.5 to each cell to estimate the relative risk and the 95% confidence interval (CI). For Jensen and Hansen (1998), we compared the proportion of subjects with glycosylated hemoglobin above 7% across occupational exposure categories. For Ward and Pim (1984) and Ruiz-Navarro et al. (1998), we used the linear discriminant function method to estimate relative risks from comparisons of means (Greenland 1987). Finally, for Lewis et al. (1999), we estimated the relative risk of diabetes mortality comparing the highest with the lowest category of exposure within the cohort from the published standardized mortality ratios.

We grouped the studies in three categories: studies in general populations exposed to high arsenic levels, corresponding to studies in Taiwan and Bangladesh with average levels in drinking water well above 100 ppb; studies in occupational populations exposed to high arsenic levels most commonly in ambient air; and studies in general populations exposed to low or moderate levels of arsenic in drinking water (< 100 ppb), food, or ambient air. Because of substantial heterogeneity and methodologic limitations, we present a qualitative systematic review, and we used only meta-analysis techniques for studies from Taiwan and Bangladesh. For descriptive purposes, we report the range and the unweighted medians of the relative risk of diabetes comparing extreme categories of arsenic exposure in each study.

Results Top

In Vitro Experimental Studies

Nineteen in vitro studies published between 1965 and 2004 met our inclusion criteria (Figure 1, Table 1). None of the experimental studies were conducted in human cell lines. Five experiments investigated the effect of arsenic on insulin signal transduction and gene expression. Three studies were performed in transfected mouse pancreatic β-cells, where exposure to high arsenite concentrations was similar to high glucose in stimulating insulin upstream factor 1 (IUF-1) (Macfarlane et al. 1997) and in stimulating the translocation of IUF-1 from the cytoplasm to the nucleus (Elrick and Docherty 2001; Macfarlane et al. 1999). IUF-1, also called homeodomain transcription factor PDX1, is a transcription factor that binds to the human insulin gene promoter and increases insulin messenger RNA levels in response to glucose. The effect of high glucose or arsenite was prevented by SB 203580, a specific inhibitor of stress-activated protein kinase-2 (SAPK2)/p38, whereas the effect of high glucose but not of arsenite was prevented by substances that specifically inactivate phosphatidylinositol-3 kinase (wortmannin and LY294002). Two other studies (Salazard et al. 2004; Wauson et al. 2002) investigated the role of arsenite in adipocyte differentiation and peroxisome proliferative-activated receptor γ (PPARγ) expression. PPARγ is a transcription factor that regulates key gene expression for insulin sensitivity. These two experiments used different concentrations and lengths of exposure and produced opposite results. In the study by Salazard et al. (2004), the incubation of 3T3-F442A preadipocytes with 1.7 and 3 ppb (0.25 and 0.5 μM) arsenite for 3 days induced the expression of PPARγ and CCAAT/enhancer binding protein. In study by Wauson et al. (2002), the incubation of C3H 101T1/2 cells with 450 ppb (6 μM) arsenite for 2 months prevented adipocyte differentiation through the inhibition of the PPARγ. Arsenite also inhibited the differentiating effect induced by pioglitazone, a PPARγ agonist used to reduce insulin resistance.

The rest of the in vitro studies assessed the effect of arsenic on glucose uptake, typically using very high concentrations of arsenite as general inducers of cellular stress. Ten studies measured basal glucose uptake (in the absence of insulin) in cell lines exposed to arsenite or other compounds (Table 1, Figure 2). Four of the studies also exposed the cells simultaneously to insulin and arsenite (Table 2). Compared with insulin alone, simultaneous exposure to insulin and arsenite decreased glucose uptake in insulin-sensitive cells (Bazuine et al. 2003; Walton et al. 2004). One of the studies (Walton et al. 2004) measured basal and insulin-stimulated glucose uptake in cells exposed to arsenate and to methylated arsenic compounds. Methylarsine oxide (MAs^IIIO) inhibited insulin-stimulated glucose uptake at the concentration of 75 ppb after 4- or 24-hr exposure (Walton et al. 2004). For arsenite, because the concentrations used in glucose uptake studies were extremely high, their relevance to diabetes development in humans is questionable.

Overall, in vitro studies provided limited insight into potential mechanisms that may explain an etiologic role of arsenic on diabetes.

In Vivo Experimental Studies

Ten experimental studies in mice, rats, goats, and guinea pigs published between 1979 and 2004 met our inclusion criteria (Figure 1, Table 3). Arsenite was evaluated in 6 studies (Biswas et al. 2000; Cobo and Castineira 1997; Ghafghazi et al. 1980; Pal and Chatterjee 2004a, 2004b, 2005), and arsenate in 2 studies (Aguilar et al. 1997; Hughes and Thompson 1996). Other compounds were methanearsonate (Judd 1979) and monomethylarsenic (Arnold et al. 2003). Six studies administered arsenic in water or food for lengths of time ranging from 4 weeks to 2 years, and 5 studies involved intraperitoneal exposure to arsenic for 5–30 days. The doses of arsenic were high or very high in most studies, with a lowest dose of 5.55 ppm arsenite (Pal and Chatterjee 2004a) and 0.025 ppm arsenate (Hughes and Thompson 1996).

Although all studies measured glucose levels in blood, plasma, or serum, only one study provided information on potential mechanisms (Cobo and Castineira 1997). In this study, the oral administration of arsenite did not affect insulin levels in vivo. However, a glucose stimulus applied ex vivo produced greater insulin release from the isolated pancreas cells of rats treated with arsenite in vivo compared with the insulin release from isolated pancreas cells of control rats.

Epidemiologic Studies

Study characteristics.

Nineteen epidemiologic studies met our inclusion criteria (Figure 1, Table 4). Three studies were published between 1980 and 1984 (Enterline and Marsh 1982; Mabuchi et al. 1980; Ward and Pim 1984), and the other 15 were reported between 1994 and 2004. Only 2 studies used a prospective cohort design (Lewis et al. 1999; Wang et al. 2003). The rest used cross-sectional, case–control, or retrospective cohort designs. Two studies used the WHO diabetes definition based on oral glucose tolerance tests and/or self-reported medication to define diabetes, whereas the other studies used death certificates, medical or insurance records, urine tests for glucosuria, self-reported diabetes symptoms such as polyuria confirmed by two positive urine tests and a positive oral glucose tolerance test, glycosylated hemoglobin, or self-reported diagnosis. Two studies did not specify the diagnostic criteria. The number of diabetes cases ranged from 2 (Mabuchi et al. 1980) to 27,543 (Wang et al. 2003), but most studies had fewer than 100 cases. Studies in general populations included adult men and women, whereas occupational studies included mostly men.

There were substantial differences in arsenic exposure ascertainment. Most studies in general populations assessed exposure indirectly, using measurements of total arsenic levels in community drinking water sources. Two studies from Taiwan (Lai et al. 1994; Tseng et al. 2000), one from Bangladesh (Rahman et al. 1999), and one from the United States (Lewis et al. 1999) estimated a cumulative arsenic exposure index (ppm-year) by multiplying the number of years that individuals lived in a specific village/area by the average arsenic level in drinking water in that village/area (usually, in each area, several measurements were performed once in time). Other studies in Taiwan and Bangladesh assigned exposure on the basis of residence in an area determined to be endemic for arseniasis (Rahman et al. 1998; Tsai et al. 1999; Wang et al. 2003). None of the studies from Taiwan or Bangladesh obtained individual measures of arsenic exposure either from household tap water measures or more directly by using biomarkers of exposure. None of these studies assessed potential sources of exposure other than drinking water. In occupational studies, exposure was based on job title or on estimated arsenic levels in air for different job categories as assessed by a safety engineer (Rahman and Axelson 1995). One study in an occupationally exposed area assessed arsenic exposure based on years of residence within 4 km of a copper smelter during childhood (Tollestrup et al. 2003). Some occupational studies (Enterline and Marsh 1982; Jensen and Hansen 1998; Lagerkvist and Zetterlund 1994; Lubin et al. 2000) also measured arsenic in urine or air to confirm exposure, but this information was not linked to diabetes in the analyses. Only two studies used biomarkers of exposure: Ward and Pim (1984) measured total arsenic in plasma, and Ruiz-Navarro et al. (1998) measured total arsenic in urine, without speciation of inorganic and methylated compounds.

Quality assessment.

In the epidemiologic studies we abstracted information to evaluate study quality, adapting the criteria proposed for observational studies by Longnecker et al. (1988). As shown in Table 5, most studies failed to fulfill important quality criteria such as individual measures of arsenic exposure using biomarkers, standard criteria to diagnose diabetes, or information on established risk factors for diabetes.

Relative risk estimates.

The relative risk estimates comparing the highest with the lowest arsenic exposure categories are shown in Table 4. Studies in Taiwan and Bangladesh consistently identified an increased risk of diabetes with increased arsenic exposure, with relative risks ranging from 1.46 to 10.1 (median, 2.40) and with a pooled relative risk estimate using and inverse variance weighted random-effects model of 2.52 (95% CI, 1.69–3.75; p heterogeneity < 0.001). Occupational studies were small and showed no consistent pattern, with relative risks ranging from 0.34 to 9.61 (median, 1.40). We identified only 4 studies in general populations from countries with low or moderate arsenic exposure. These studies were small and did not show an increased risk of diabetes with increasing arsenic levels (relative risks ranged from 0.65 to 1.09; median, 0.95).

Five studies provided information on the dose response in diabetes risk by cumulative arsenic exposure in drinking water (Figure 3). Diabetes risk tended to increase with increasing cumulative exposure in studies from Taiwan (Lai et al. 1994; Tseng et al. 2000) and Bangladesh (Rahman et al. 1999). No trend was observed in the U.S. studies (Lewis et al. 1999; Zierold et al. 2004).

Discussion Top

Summary of findings.

The evidence on the association of arsenic exposure with diabetes risk summarized in this systematic review is inconclusive. Evidence from in vitro studies suggests that arsenic interferes with signal transduction and transcription factors that are related to insulin pathways such as IUF-1 in pancreatic cells or PPARγ in preadipocytes. In vitro glucose uptake experiments and in vivo studies did not provide evidence on potential mechanisms that may explain a diabetogenic effect of arsenic. In general, experimental studies were limited by the use of arsenic concentrations that were much higher than those relevant to human exposure. For example, the current U.S. Environmental Protection Agency recommended standard for arsenic in drinking water is 10 ppb. The lowest concentration of arsenite used in studies of cultured cells investigating glucose uptake was 750 ppb (Bazuine et al. 2003), and the lowest concentration of arsenite in animal studies was 5,550 ppb (Pal and Chatterjee 2004a, 2004b).

In epidemiologic studies, the association between arsenic exposure and diabetes across different populations and different sources of exposure was inconsistent. In populations exposed to high arsenic levels via drinking water in Taiwan and Bangladesh, diabetes risk was consistently increased. In occupational settings, diabetes mortality was increased in some studies and decreased in others. Finally, no association with diabetes was observed in four studies of general populations outside of Taiwan or Bangladesh. Overall, the quality of the epidemiologic evidence was limited by methodologic problems, particularly in assessing arsenic exposure and diabetes outcomes.

Mechanisms for arsenic-related diabetes.

Acute arsenite toxicity, including its effects on glucose metabolism, is generally attributed to its reactivity toward thiol (SH) groups (Aposhian 1989; NRC 1999). During acute poisoning, arsenite inhibits pyruvate and α-ketoglutarate dehydrogenases (Aposhian 1989), essential enzymes for gluconeogenesis and glucolysis. The interference of arsenic with pyruvic acid metabolism was described by Krebs in the early 1930s (Krebs 1933). Arsenate, on the other hand, can replace phosphate in energy transfer pathways of phosphorylation and also uncouples oxidative phosphorylation (Kennedy and Lehninger 1949). However, these toxic effects of acute arsenic exposure are unlikely to occur as a result of chronic exposure to environmentally relevant doses (Tseng 2004).

The influence of arsenic on the expression of gene transcription factors may be related to diabetes risk. However, the effects of arsenite on IUF-1 and PPARγ were contradictory in terms of diabetes development. The differential effects may reflect a complex dose–response pattern for arsenic or differences in length of exposure to arsenic across studies. Further studies with wide ranges and durations of arsenic exposure are needed to investigate the effect of arsenic on these and other insulin-related events at the cellular and molecular levels. For instance, interference with the glucocorticoid receptor is another potential mechanism for arsenic-related diabetes that deserves further investigation. Arsenic shows a complex dose–response effect on glucocorticoid receptor mediated transcription (Bodwell et al. 2004), with a stimulatory effect at very low concentrations (6–120 ppb) and an inhibitory effect at doses greater than 120 ppb. The glucocorticoid receptor is a member of the steroid receptor superfamily that among other metabolic processes regulates gluconeogenesis. Reduction of glucocorticoid receptor expression in hepatic and adipose tissue has been shown to improve hyperglycemia in diabetic rodents (Watts et al. 2005).

Experimental studies on glucose uptake showed that arsenite increases uptake independently of the earlier steps of the insulin transduction pathway, although when co-administered with insulin, arsenite inhibited insulin-stimulated glucose uptake in 3T3-L1 adipocytes. The purpose of most of these studies was to investigate the role of stress in glucose uptake, which is unrelated to the possibility that arsenic could affect diabetes risk. Under these designs, cultured cells were exposed to high arsenic levels for a few hours, whereas humans are chronically exposed to lower concentrations. Only one study investigated methylated arsenical compounds and their interference in insulin signaling in adipocytes (Walton et al. 2004). For these reasons, the relevance of in vitro glucose uptake findings to diabetes etiology is uncertain.

Arsenic could influence diabetes development by other mechanisms, including oxidative stress, inflammation, or apoptosis, nonspecific mechanisms that have been implicated in the pathogenesis of type 2 diabetes. Arsenic exposure can enhance the production of reactive oxygen species (Barchowsky et al. 1999; Chen et al. 1998; Tseng 2004; Wang et al. 1996), interfere with the activity of key antioxidant enzymes such as glutathione reductase, glutathione S-transferase, glutathione peroxidase, and glucose 6-phosphate dehydrogenase (Maiti and Chatterjee 2000; Santra et al. 2000), and induce lipid peroxidation (Santra et al. 2000). In individuals from Taiwan, increasing blood levels of arsenic correlated with increasing levels of reactive oxygen species and with decreasing levels of antioxidant capacity in plasma (Wu et al. 2001). Arsenic may also up-regulate interleukin-6 and other inflammatory cytokines (Wu et al. 2003), and it may induce the release of tumor necrosis factor-α from mononuclear cells (Yu et al. 2002). Finally, arsenic is well known for inducing apoptosis in multiple cell lines (Waalkes et al. 2000). Future research should evaluate whether these mechanisms mediate the role of arsenic in diabetes development.

The in vivo experimental studies were mostly uninformative. The diversity of species studied probably reflects that there are no good animal models to study the effects of arsenic on diabetes development. Indeed, the classification of arsenic as a human carcinogen, although recently supported by animal models (Waalkes et al. 2004), was for a long time based on human data. Progress in the study of the role of arsenic in diabetes requires the identification of appropriate animal models.

Arsenic and diabetes in human studies.

Suggestive evidence links chronic exposure to high arsenic levels in drinking water with increased diabetes risk in Taiwan and Bangladesh. Methodologic problems, however, limit the causal interpretation of this association. The use of average drinking water and the lack of individual measures of arsenic make it possible to underestimate exposure due to between-subject variability in water consumption and to other sources of arsenic exposure in these areas, such as contaminated food and cooking water. On the other hand, because arsenic exposure was assessed at the village level and diabetes diagnosis was often not performed according to standard procedures, this ecologic association could reflect the uncertain comparability of exposure groups in terms of socioeconomic development, access to care, study selection factors and other diabetes risk factors. The use of urine tests and of administrative data to identify diabetes makes it likely that only severe or symptomatic cases were identified, and it is uncertain whether the procedures and frequency for diabetes testing were similar across areas with different arsenic exposure. In addition, the use of administrative data can be affected by surveillance and diagnostic biases. For example in Taiwan, arsenic-related health problems in the endemic areas are well known, hence, subjects in these areas may have received different medical care, including different diagnostic services, compared with subjects in areas with lower arsenic levels.

It is also possible that the findings from Taiwan and Bangladesh may not be generalizable to other populations. Some reasons for this include variations in the distribution of polymorphisms in genes involved in arsenic metabolism or response (Loffredo et al. 2003), differences in arsenic species to which populations were exposed (Chen et al. 1995), other co-exposures (Chen et al. 1995), and dietary deficiencies that may interact with arsenic. For example, selenium and zinc levels in Taiwan and Bangladesh are among the lowest worldwide (Lin and Yang 1988), and poor dietary selenium has been suggested as an underlying factor for arsenic and cancer in Bangladesh and West Bengal in India (Spallholz et al. 2004). In guinea pigs, selenium and arsenic counteract each other in glucose metabolism (Das et al. 1989), and the joint effect of high arsenic and low selenium could play a role in diabetes development. Exposure to arsenic, selenium, other nutrients, and other diabetes risk factors were not measured in epidemiologic studies.

We found no reports of diabetes in populations known to be exposed to high levels of arsenic in drinking water in Chile and Argentina. This lack of information on diabetes could reflect a lack of research, but it has also been suggested to be related to publication bias (Longnecker and Daniels 2001).

The evidence from general populations outside of Taiwan or Bangladesh was inconclusive because of the small number of cases, limitations in study design, and misclassification of diabetes status. Occupational studies, on the other hand, could not be interpreted in favor or against an association because of uncertain comparability of study participants with the general population used as reference, limitations in exposure assessment, lack of information on concomitant exposures, lack of information on major diabetes risk factors, and the possibility of a healthy worker survivor effect.

An important conclusion we derived from the epidemiologic review is the limited quality of the evidence base. This finding is consistent with previous reviews, including those by U.S. and international panels (NRC 1999, 2001; Ng 2001; WHO 2001). These panels determined that the available evidence on arsenic and diabetes suffered from uncertainties in study design and exposure assessment. Our review further refines these reports and identifies the lack of biomarker data and the lack of standard criteria for diabetes assessment as major limitations of the evidence base. Current uncertainties in the role of arsenic in diabetes development could be reduced by conducting carefully planned epidemiologic studies in populations exposed to a wide range of arsenic levels. Future studies should a) measure appropriate arsenic biomarkers that integrate all sources of exposure (e.g., urine or toenails); b) carefully collect information on current and past sources of arsenic exposure and on potential confounders and modifiers, including known determinants of diabetes development; c) and prospectively ascertain diabetes using standard definitions.

Conclusion Top

The possibility of an association between chronic arsenic exposure and diabetes has implications for research and public health. Millions of people are exposed worldwide to moderate or high levels of arsenic in drinking water. Because diabetes is also a major public health problem, the public health consequences of a causal association could be serious. Methodologic problems limit the causal interpretation of the moderately strong association between high arsenic exposure and diabetes in Taiwan and Bangladesh. Overall, the experimental and epidemiologic evidence is at present insufficient and inadequate to establish causality. Experimental studies that use arsenic concentrations relevant to human exposures, and high-quality prospective epidemiologic studies that use appropriate methods for exposure assessment as well as rigorous criteria for outcome definitions should be research priorities.

CORRECTION Top

Table 1 has been modified from the original manuscript published online. The table now includes information on the 24-hr study by Walton et al. (2004).

Figures and Tables Top

Figure 1.

Flow diagram of the experimental and epidemiologic study selection process.

Figure 2.

Ratio of basal glucose uptake in peripheral cell lines comparing arsenite versus control. Lines represent the dose response for each independent study. Single points represent the effect for studies using a single dose (1 ppm = 13.35 μM; 0.75 ppm = 10 μM).

Figure 3.

Risk of diabetes by cumulative arsenic exposure in drinking water in epidemiologic studies. Black lines represent the dose response for studies in Taiwan and Bangladesh compared with the baseline category of exposure. Gray lines represent the dose response in studies in the United States. Cumulative exposure: ∑ arsenic levels in drinking water _i × time of exposure i (i indicates specific village). For example, a cumulative exposure of 1 ppm-year is reached after 10 years of residence in a village with an arsenic concentration in drinking water of 0.1 ppm. In the study by Zierold et al. (2004), we assumed 20 years of exposure for all study subjects.

Table 1.

In vitro studies of arsenic exposure and glucose metabolism outcomes.

Table 2.

Experimental characteristics and ratio of glucose uptake in peripheral cell lines exposed to arsenite and insulin compared with insulin and arsenite alone.

Table 3.

In vivo studies of arsenic exposure and glucose metabolism.

Table 4.

Epidemiologic studies of arsenic exposure and diabetes.

Table 5.

Criteria for evaluating the design and data analysis of epidemiologic studies on arsenic and diabetes.^a

References Top

1. Aguilar MV, Martinez-Para MC, Gonzalez MJ 1997. Effects of arsenic (V)-chromium (III) interaction on plasma glucose and cholesterol levels in growing rats Ann Nutr Metab 41:189–195.9286469 Find this article online
2. Aposhian HV 1989. Biochemical toxicology of arsenic. In: Reviews in Biochemical Toxicology (Hodgson E, Bend JR, Philpot RM, eds). Vol 10. Amsterdam:Elsevier, 265–289
3. Arnold LL, Eldan M, van Gemert M, Capen CC, Cohen SM 2003. Chronic studies evaluating the carcinogenicity of monomethylarsonic acid in rats and mice Toxicology 190:197–219.12927375 Find this article online
4. Barchowsky A, Klei LR, Dudek EJ, Swartz HM, James PE 1999. Stimulation of reactive oxygen, but not reactive nitrogen species, in vascular endothelial cells exposed to low levels of arsenite Free Radic Biol Med 27:1405–1412.10641735 Find this article online
5. Bartoli D, Battista G, De Santis M, Iaia TE, Orsi D, Tarchi M, et al. 1998. Cohort study of art glass workers in Tuscany, Italy: mortality from non-malignant diseases Occup Med (Lond) 48:441–445.10024742 Find this article online
6. Bazuine M, Carlotti F, Tafrechi RS, Hoeben RC, Maassen JA 2004. Mitogen-activated protein kinase (MAPK) phosphatase-1 and -4 attenuate p38 MAPK during dexamethasone-induced insulin resistance in 3T3-L1 adipocytes Mol Endocrinol 18:1697–1707.15184525 Find this article online
7. Bazuine M, Ouwens DM, Gomes de Mesquita DS, Maassen JA 2003. Arsenite stimulated glucose transport in 3T3-L1 adipocytes involves both Glut4 translocation and p38 MAPK activity Eur J Biochem 270:3891–3903.14511371 Find this article online
8. Biswas U, Sarkar S, Bhowmik MK, Samanta AK, Biswas S 2000. Chronic toxicity of arsenic in goats: clinicobiochemical changes, pathomorphology and tissue residues Small Rumin Res 38:229–235.11024339 Find this article online
9. Bodwell JE, Kingsley LA, Hamilton JW 2004. Arsenic at very low concentrations alters glucocorticoid receptor (GR)-mediated gene activation but not GR-mediated gene repression: complex dose-response effects are closely correlated with levels of activated GR and require a functional GR DNA binding domain Chem Res Toxicol 17:1064–1076.15310238 Find this article online
10. Brazy PC, Balaban RS, Gullans SR, Mandel LJ, Dennis VW 1980. Inhibition of renal metabolism. Relative effects of arsenate on sodium, phosphate, and glucose transport by the rabbit proximal tubule J Clin Invest 66:1211–1221.7440711 Find this article online
11. Chen CJ, Hsueh YM, Lai MS, Shyu MP, Chen SY, Wu MM, et al. 1995. Increased prevalence of hypertension and long-term arsenic exposure Hypertension 25:53–60.7843753 Find this article online
12. Chen YC, Lin-Shiau SY, Lin JK 1998. Involvement of reactive oxygen species and caspase 3 activation in arsenite-induced apoptosis J Cell Physiol 177:324–333.9766529 Find this article online
13. Cobo JM, Castineira M 1997. Oxidative stress, mitochondrial respiration, and glycemic control: clues from chronic supplementation with Cr3⁺ or As3⁺ to male Wistar rats Nutrition 13:965–970.9433712 Find this article online
14. Das PM, Sadana JR, Gupta RK, Kumar K 1989. Experimental selenium toxicity in guinea pigs: biochemical studies Ann Nutr Metab 33:57–63.2742331 Find this article online
15. Dixit PK, Lazarow A 1967. Effects of metal ions and sulfhydryl inhibitors on glucose metabolism by adipose tissue Am J Physiol 213:849–856.6051180 Find this article online
16. Elrick LJ, Docherty K 2001. Phosphorylation-dependent nucleocytoplasmic shuttling of pancreatic duodenal homeobox-1 Diabetes 50:2244–2252.11574405 Find this article online
17. Enterline PE, Marsh GM 1982. Cancer among workers exposed to arsenic and other substances in a copper smelter Am J Epidemiol 116:895–911.7148816 Find this article online
18. Fladeby C, Serck-Hanssen G 1999. Stress-induced glucose uptake in bovine chromaffin cells: a comparison of the effect of arsenite and anisomycin Biochim Biophys Acta 1452:313–321.10590320 Find this article online
19. Ghafghazi T, Ridlington JW, Fowler BA 1980. The effects of acute and subacute sodium arsenite administration on carbohydrate metabolism Toxicol Appl Pharmacol 55:126–130.7423499 Find this article online
20. Greenland S 1987. Quantitative methods in the review of epidemiologic literature Epidemiol Rev 9:1–30.3678409 Find this article online
21. Hughes MF, Thompson DJ 1996. Subchronic dispositional and toxicological effects of arsenate administered in drinking water to mice J Toxicol Environ Health 49:177–196.8874535 Find this article online
22. Hunder G, Nguyen PT, Schumann K, Fichtl B 1993. Influence of inorganic and organic arsenicals on intestinal transfer of nutrients Res Commun Chem Pathol Pharmacol 80:83–92.8488343 Find this article online
23. Jensen GE, Hansen ML 1998. Occupational arsenic exposure and glycosylated haemoglobin Analyst 123:77–80.9581024 Find this article online
24. Judd FW 1979. Acute toxicity and effects of sublethal dietary exposure of monosodium methanearsonate herbicide to Peromyscus leucopus (Rodentia: Cricetidae) Bull Environ Contam Toxicol 22:143–150.465771 Find this article online
25. Kennedy EP, Lehninger AL 1949. Oxidation of fatty acids and tricarboxylic acid cycle intermediates by isolated rat liver mitochondria J Biol Chem 179:957–972. Find this article online
26. Krebs HA 1933. Untersuchugen über den stoffwechsel der aminosäuren im tierkörper [in German] Z Physiol Chem 218:191–227. Find this article online
27. Lagerkvist BJ, Zetterlund B 1994. Assessment of exposure to arsenic among smelter workers: a five-year follow-up Am J Ind Med 25:477–488.7516623 Find this article online
28. Lai MS, Hsueh YM, Chen CJ, Shyu MP, Chen SY, Kuo TL, et al. 1994. Ingested inorganic arsenic and prevalence of diabetes mellitus Am J Epidemiol 139:484–492.8154472 Find this article online
29. Lewis DR, Southwick JW, Ouellet-Hellstrom R, Rench J, Calderon RL 1999. Drinking water arsenic in Utah: a cohort mortality study Environ Health Perspect 107:359–365.10210691 Find this article online
30. Liebl B, Muckter H, Doklea E, Fichtl B, Forth W 1992. Influence of organic and inorganic arsenicals on glucose uptake in Madin-Darby canine kidney (MDCK) cells Analyst 117:681–684.1580420 Find this article online
31. Lin SM, Yang MH 1988. Arsenic, selenium, and zinc in patients with blackfoot disease Biol Trace Elem Res 15:213–221.2484518 Find this article online
32. Loffredo CA, Aposhian HV, Cebrian ME, Yamauchi H, Silbergeld EK 2003. Variability in human metabolism of arsenic Environ Res 92:85–91.12854687 Find this article online
33. Longnecker MP, Berlin JA, Orza MJ, Chalmers TC 1988. A meta-analysis of alcohol consumption in relation to risk of breast cancer JAMA 260:652–656.3392790 Find this article online
34. Longnecker MP, Daniels JL 2001. Environmental contaminants as etiologic factors for diabetes Environ Health Perspect 109(suppl 6):871–876.11744505 Find this article online
35. Lubin JH, Pottern LM, Stone BJ, Fraumeni JF Jr 2000. Respiratory cancer in a cohort of copper smelter workers: results from more than 50 years of follow-up Am J Epidemiol 151:554–565.10733037 Find this article online
36. Mabuchi K, Lilienfeld AM, Snell LM 1980. Cancer and occupational exposure to arsenic: a study of pesticide workers Prev Med 9:51–77.7360731 Find this article online
37. Macfarlane WM, McKinnon CM, Felton-Edkins ZA, Cragg H, James RF, Docherty K 1999. Glucose stimulates translocation of the homeodomain transcription factor PDX1 from the cytoplasm to the nucleus in pancreatic beta-cells J Biol Chem 274:1011–1016.9873045 Find this article online
38. Macfarlane WM, Smith SB, James RF, Clifton AD, Doza YN, Cohen P, et al. 1997. The p38/reactivating kinase mitogen-activated protein kinase cascade mediates the activation of the transcription factor insulin upstream factor 1 and insulin gene transcription by high glucose in pancreatic beta-cells J Biol Chem 272:20936–20944.9252422 Find this article online
39. Maiti S, Chatterjee AK 2000. Differential response of cellular antioxidant mechanism of liver and kidney to arsenic exposure and its relation to dietary protein deficiency Environ Toxicol Pharmacol 8:227–235.10996542 Find this article online
40. McDowell HE, Walker T, Hajduch E, Christie G, Batty IH, Downes CP, et al. 1997. Inositol phospholipid 3-kinase is activated by cellular stress but is not required for the stress-induced activation of glucose transport in L6 rat skeletal muscle cells Eur J Biochem 247:306–313.9249041 Find this article online
41. Ng J 2001. Arsenic and Arsenic Compounds. 2nd ed. Environmental Health Criteria 224. Geneva:World Health Organization
42. NRC (National Research Council) 1999. Arsenic in Drinking Water. Washington, DC:National Academy Press
43. NRC (National Research Council) 2001. Arsenic in Drinking Water 2001 Update. Washington DC:National Academy Press
44. Pal S, Chatterjee AK 2004a. Protective effect of methionine supplementation on arsenic-induced alteration of glucose homeostasis Food Chem Toxicol 42:737–742.15046819 Find this article online
45. Pal S, Chatterjee AK 2004b. Protective effect of N-acetylcysteine against arsenic-induced depletion in vivo of carbohydrate Drug Chem Toxicol 27:179–189.15198077 Find this article online
46. Pal S, Chatterjee AK 2005. Prospective protective role of melatonin against arsenic-induced metabolic toxicity in Wistar rats Toxicology 208:25–33.15664430 Find this article online
47. Pasternak CA, Aiyathurai JE, Makinde V, Davies A, Baldwin SA, Konieczko EM, et al. 1991. Regulation of glucose uptake by stressed cells J Cell Physiol 149:324–331.1748722 Find this article online
48. Rahman M, Axelson O 1995. Diabetes mellitus and arsenic exposure: a second look at case-control data from a Swedish copper smelter Occup Environ Med 52:773–774.8535499 Find this article online
49. Rahman M, Tondel M, Ahmad SA, Axelson O 1998. Diabetes mellitus associated with arsenic exposure in Bangladesh Am J Epidemiol 148:198–203.9676702 Find this article online
50. Rahman M, Tondel M, Ahmad SA, Chowdhury IA, Faruquee MH, Axelson O 1999. Hypertension and arsenic exposure in Bangladesh Hypertension 33:74–78.9931084 Find this article online
51. Rahman M, Wingren G, Axelson O 1996. Diabetes mellitus among Swedish art glass workers—an effect of arsenic exposure? Scand J Work Environ Health 22:146–149.8738894 Find this article online
52. Ruiz-Navarro ML, Navarro-Alarcon M, Lopez Gonzalez-de la Serrana, Perez-Valero V, Lopez-Martinez MC 1998. Urine arsenic concentrations in healthy adults as indicators of environmental contamination: relation with some pathologies Sci Total Environ 216:55–61.9618928 Find this article online
53. Salazard B, Bellon L, Jean S, Maraninchi M, El Yazidi C, Orsiere T, et al. 2004. Low-level arsenite activates the transcription of genes involved in adipose differentiation Cell Biol Toxicol 20:375–385.15868481 Find this article online
54. Santra A, Maiti A, Das S, Lahiri S, Charkaborty SK, Mazumder DN 2000. Hepatic damage caused by chronic arsenic toxicity in experimental animals J Toxicol Clin Toxicol 38:395–405.10930056 Find this article online
55. Short AL, Wright FE, Whitney JE 1965. Effect of anaerobiosis and cell poisons on glucose uptake of hemidiaphragms and epididymal fat pads in vitro Diabetes 14:128–131.14262219 Find this article online
56. Spallholz JE, Mallory BL, Rhaman MM 2004. Environmental hypothesis: is poor dietary selenium intake an underlying factor for arsenicosis and cancer in Bangladesh and West Bengal, India? Sci Total Environ 323:21–32.15081714 Find this article online
57. Sviderskaya EV, Jazrawi E, Baldwin SA, Widnell CC, Pasternak CA 1996. Cellular stress causes accumulation of the glucose transporter at the surface of cells independently of their insulin sensitivity J Membr Biol 149:133–140.8834120 Find this article online
58. Tollestrup K, Frost FJ, Harter LC, McMillan GP 2003. Mortality among children residing near the American Smelting and Refining Company (ASARCO) copper smelter in Ruston, Washington Arch Environ Health 58:683–691.15702892 Find this article online
59. Tsai SM, Wang TN, Ko YC 1999. Mortality for certain diseases in areas with high levels of arsenic in drinking water Arch Environ Health 54:186–193.10444040 Find this article online
60. Tseng CH 2004. The potential biological mechanisms of arsenic-induced diabetes mellitus Toxicol Appl Pharmacol 197:67–83.15163543 Find this article online
61. Tseng CH, Tai TY, Chong CK, Tseng CP, Lai MS, Lin BJ, et al. 2000. Long-term arsenic exposure and incidence of non-insulin-dependent diabetes mellitus: a cohort study in arseniasis-hyperendemic villages in Taiwan Environ Health Perspect 108:847–851.11017889 Find this article online
62. Tseng CH, Tseng CP, Chiou HY, Hsueh YM, Chong CK, Chen CJ 2002. Epidemiologic evidence of diabetogenic effect of arsenic Toxicol Lett 133:69–76.12076511 Find this article online
63. Waalkes MP, Fox DA, States JC, Patierno SR, McCabe MJ Jr 2000. Metals and disorders of cell accumulation: modulation of apoptosis and cell proliferation Toxicol Sci 56:255–261.10910982 Find this article online
64. Waalkes MP, Liu J, Ward JM, Diwan BA 2004. Animal models for arsenic carcinogenesis: inorganic arsenic is a transplacental carcinogen in mice Toxicol Appl Pharmacol 198:377–384.15276417 Find this article online
65. Walton FS, Harmon AW, Paul DS, Drobna Z, Patel YM, Styblo M 2004. Inhibition of insulin-dependent glucose uptake by trivalent arsenicals: possible mechanism of arsenic-induced diabetes Toxicol Appl Pharmacol 198:424–433.15276423 Find this article online
66. Wang SL, Chiou JM, Chen CJ, Tseng CH, Chou WL, Wang CC, et al. 2003. Prevalence of non-insulin-dependent diabetes mellitus and related vascular diseases in southwestern arseniasis-endemic and nonendemic areas in Taiwan Environ Health Perspect 111:155–159.12573898 Find this article online
67. Wang TS, Kuo CF, Jan KY, Huang H 1996. Arsenite induces apoptosis in Chinese hamster ovary cells by generation of reactive oxygen species J Cell Physiol 169:256–268.8908193 Find this article online
68. Ward NI, Pim B 1984. Trace element concentrations in blood plasma from diabetic patients and normal individuals Biol Trace Elem Res 6:469–487. Find this article online
69. Warren AP, James MH, Menzies DE, Widnell CC, Whitaker-Dowling PA, Pasternak CA 1986. Stress induces an increased hexose uptake in cultured cells J Cell Physiol 128:383–388.3018000 Find this article online
70. Watts LM, Manchem VP, Leedom TA, Rivard AL, McKay RA, Bao D, et al. 2005. Reduction of hepatic and adipose tissue glucocorticoid receptor expression with antisense oligonucleotides improves hyperglycemia and hyperlipidemia in diabetic rodents without causing systemic glucocorticoid antagonism Diabetes 54:1846–1853.15919808 Find this article online
71. Wauson EM, Langan AS, Vorce RL 2002. Sodium arsenite inhibits and reverses expression of adipogenic and fat cell-specific genes during in vitro adipogenesis Toxicol Sci 65:211–219.11812925 Find this article online
72. WHO 2001. United Nations Synthesis Report on Arsenic Drinking Water. Developed on behalf of the United Nations Administrative Committee on Cooperation Sub-Committee on Water Resources, with active participation of UNICEF, UNIDO, IAEA and the World Bank. World Health Organization. Available: http://www.who.int/water_sanitation_heal​th/dwq/arsenic3/en/ [accessed 1 December 2005]
73. Widnell CC, Baldwin SA, Davies A, Martin S, Pasternak CA 1990. Cellular stress induces a redistribution of the glucose transporter FASEB J 4:1634–1637.2156742 Find this article online
74. Wild S, Roglic G, Green A, Sicree R, King H 2004. Global prevalence of diabetes: estimates for the year 2000 and projections for 2030 Diabetes Care 27:1047–1053.15111519 Find this article online
75. Wu MM, Chiou HY, Ho IC, Chen CJ, Lee TC 2003. Gene expression of inflammatory molecules in circulating lymphocytes from arsenic-exposed human subjects Environ Health Perspect 111:1429–1438.12928151 Find this article online
76. Wu MM, Chiou HY, Wang TW, Hsueh YM, Wang IH, Chen CJ, et al. 2001. Association of blood arsenic levels with increased reactive oxidants and decreased antioxidant capacity in a human population of northeastern Taiwan Environ Health Perspect 109:1011–1017.11675266 Find this article online
77. Yu HS, Liao WT, Chang KL, Yu CL, Chen GS 2002. Arsenic induces tumor necrosis factor alpha release and tumor necrosis factor receptor 1 signaling in T helper cell apoptosis J Invest Dermatol 119:812–819.12406325 Find this article online
78. Zierold KM, Knobeloch L, Anderson H 2004. Prevalence of chronic diseases in adults exposed to arsenic-contaminated drinking water Am J Public Health 94:1936–1937.15514231 Find this article online