Arsenic exposure is associated with diminished insulin sensitivity in non-diabetic Amish adults Arsenic exposure is associated with diminished insulin sensitivity in non-diabetic Amish adults Sung Kyun Park1,2* Qing Peng1 Lawrence F. Bielak1 Kristi D. Silver3 Patricia A. Peyser1 Braxton D. Mitchell3,4 1Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA 2Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI, USA 3Departments of Medicine and Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD, USA 4Department of Veterans Affairs and Veterans Affairs Medical Center Baltimore Geriatric Research Education and Clinical Center (GRECC), Baltimore, MD, USA *Correspondence to: Sung Kyun Park, Department of Epidemiology, University of Michigan School of Public Health, 1415 Washington Heights, Ann Arbor, MI, 48109, USA. E-mail: sungkyun@umich.edu Abstract Background Substantial evidence supports an association between diabetes and arsenic at high exposure levels, but results are mixed at low exposure levels. The aetiology of diabetes involves insulin resistance and β-cell dysfunc- tion. However, only a few epidemiologic studies have examined measures of insulin resistance and β-cell function in relation to arsenic exposure, and no studies have tested for associations with the oral glucose tolerance test (OGTT). We examined the association between urinary total arsenic and OGTT-based markers of insulin sensitivity and β-cell function. Methods We studied 221 non-diabetic adults (mean age = 52.5 years) from the Amish Family Diabetes Study. We computed OGTT-based validated measures of insulin sensitivity and β-cell function. Generalized estimating equations accounting for sibship were used to estimate associations. Results After adjusting for age, sex, waist-to-hip ratio and urinary creatinine, an interquartile range increase in urinary total arsenic (6.24 μg/L) was significantly, inversely associated with two insulin sensitivity measures (Stumvoll metabolic clearance rate= �0.23 mg/(kg min), (95% CI: �0.38, �0.089), p = 0.0015; Stumvoll insulin sensitivity index= �0.0029 μmol/(kg min pM), (95% CI: �0.0047, �0.0011), p= 0.0015). Urinary total arsenic was also significantly associated with higher fasting glucose levels (0.57 mg/dL (95% CI: 0.06, 1.09) per interquartile range increase, p = 0.029). No significant associ- ations were found between urinary total arsenic and β-cell function measures. Conclusions This preliminary study found that urinary total arsenic was associated with insulin sensitivity but not β-cell function measures, suggesting that low-level arsenic exposure may influence diabetes risk through impairing insulin sensitivity. Copyright © 2015 John Wiley & Sons, Ltd. Keywords arsenic; β-cell function; insulin sensitivity; oral glucose tolerance test Introduction Arsenic is the top hazard that poses the most important potential threat to human health including diabetes on the priority list of the US Agency for Toxic Substances and Disease Registry [1]. The main sources of arsenic are contaminated drinking water and food [2,3]. Potential biological mechanisms by which arsenic influences diabetes include high affinity of arsenic with sulfhydryl groups in insulin, insulin receptor and glucose transporters; increased RESEARCH ARTICLE Received: 17 July 2015 Revised: 30 October 2015 Accepted: 26 November 2015 Copyright © 2015 John Wiley & Sons, Ltd. DIABETES/METABOLISM RESEARCH AND REVIEWS Diabetes Metab Res Rev 2016; 32: 565–571. Published online 14 January 2016 in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/dmrr.2769 oxidative stress that can lead to formation of amyloid in pan- creatic islet cells, causing β-cell dysfunction; interference with gene expression involving signal transduction and gene transcription related to insulin pathways [nuclear factor-κB (NF-κB), tumor necrosis factor α (TNFα), IL-6, peroxisome proliferator-activated receptor gamma (PPARγ)], leading to insulin resistance [4–6]. Substantial evidence supports an association between arsenic and diabetes at high exposure levels, but results are mixed at low exposure levels [7,8]. The aetiology of diabetes involves insulin resistance and β-cell dysfunction [9,10]. However, only a few epidemiologic studies have examined measures of insulin resistance and β-cell function in relation to arsenic exposure, and such studies utilized indices derived from fasting glucose and insulin [11,12]. No studies have tested for associations with the oral glucose tolerance test (OGTT). We examined the association between urinary total arsenic and the OGTT-based markers of insulin sensitivity and β-cell function. Materials and methods Study population This is a preliminary study of the association between uri- nary arsenic and glucose homeostasis measures, con- ducted in the Amish Family Diabetes Study (AFDS), a genetic epidemiology study of type 2 diabetes in the Old Order Amish living in Lancaster, Pennsylvania [13]. In to- tal, the AFDS included 953 subjects aged ≥18 years from 45 multigenerational families recruited between 1995 and 1998. Detailed participant recruitment procedures of the AFDS can be found elsewhere [13]. All participants gave written informed consent and underwent a detailed clinical examination at the Amish Research Clinic. Participants were instructed to fast for 12 h before their appointment and to bring a first morning void urine sample. This preliminary study was based on 221 AFDS partici- pants with normal (n= 164) or impaired (n = 57) glucose tolerance. Subjects were sampled from non-diabetic indi- viduals who had undergone a 2-h OGTT (n = 823 subjects: 668 with normal; 155 impaired glucose tolerance) and who had sufficient volumes (7 mL) of stored urines remaining in our biorepository for the heavy metal assay. The mean (±SD) age of this sample (52.9± 13.2 years) was slightly higher than that of the full AFDS (49.2 ±17.0 years). Outcome assessment After acquisition of a fasting blood sample, a 75-g OGTT was administered. Blood samples were then drawn for de- termination of glucose and insulin values at 30-min intervals for 3 h. Glucose and insulin concentrations were assayed with a Beckman glucose analyser (Beckman Coulter, Fullerton, CA) and radioimmunoassay (Linco, St. Louis, MO), respectively. Using OGTT results, we computed three validated mea- sures of insulin sensitivity (Stumvoll estimated metabolic clearance rate (Stumvoll MCR) [14], Stumvoll insulin sen- sitivity index (Stumvoll ISI) [14] and Matsuda index [15]) and three validated measures of β-cell function (Stumvoll insulin secretion, phase 1 and phase 2 [14] and insulin- ogenic index [16] (refer to detailed formula in Table 1)). As secondary measures, we also computed one fasting state-based index of insulin sensitivity (homeostatic model assessment-insulin resistance (HOMA-IR)) and one fasting state-based index of β-cell function (HOMA-%β) [17]. De- tails of each measure including mathematical formula and clinical significances are provided in Table 1. Arsenic assessment Urinary total arsenic concentrations were determined using inductively coupled plasma-mass spectrometry by the University of Michigan Environmental Health Sciences Core Center’s Trace Metals Laboratory. All arsenic concen- trations among participants were above the limit of detection (0.1 μg/L). We conducted quality control proce- dures including analysis of urine-based reference mate- rials before, during and after every analytical run and use of calibration standards, procedural blanks, duplicate samples and spiked samples. The coefficient of variation was 5%. Urinary creatinine was measured in the AFDS and used to adjust for urine dilution. Data analysis To account for correlations among participants in the same sibship, we used generalized estimating equations with an exchangeable correlation structure where pair-wise correlations between participants from the same sibship were equal, to estimate differences for an interquartile range (IQR) increase in urinary arsenic (6.24 μg/L). All models were adjusted for age and sex (model 1) and further adjusted for waist-to-hip ratio and BMI (model 2). In model 2 for Stumvoll MCR and Stumvoll ISI, however, BMI was not included because BMI is used in the formula to calculate each of these indices. Both models were also adjusted for urinary creatinine to account for urine dilution [18]. How- ever, adjustment for urinary creatinine may introduce bias if creatinine production is influenced by diabetes and/or arsenic [8]. We, therefore, report regression results for both models without urinary creatinine adjustment as well. Two- sided p < 0.05 was considered statistically significant. 566 S. K. Park et al. Copyright © 2015 John Wiley & Sons, Ltd. Diabetes Metab Res Rev 2016; 32: 565–571. DOI: 10.1002/dmrr Results The mean (SD) age was 52.9 (13.2) years, and 115 parti- cipants (52%) were female (Table 2). The means (SDs) of insulin sensitivity and β-cell function measures were 7.8 (2.6) mg/(kg min) for Stumvoll MCR, 0.091 (0.032) μmol/(kg min pM) for Stumvoll ISI, 4.9 (2.2) for Matsuda index, 2.6 (1.8) for HOMA-IR, 153.9 (124.6) for HOMA-%β, 960.9 (461.6) pM for Stumvoll insulin secretion phase 1, 265.1 (104.4) pM for Stumvoll insulin secretion phase 2 and 89.7 (81.9) for insulinogenic index. The median urinary total arsenic concentration was 5.5 μg/L (IQR: 3.1–9.4) (Table 3). The creatinine-adjusted median concen- tration was 6.1 μg/g (IQR: 4.1–10.2). Participants aged 60 and older had higher concentrations (both crude- and creatinine-adjusted) than younger participants. Men had higher crude total arsenic concentrations than women (6.4 vs. 4.2 μg/L) but lower creatinine-adjusted total arsenic concentrations (5.4 vs. 7.0 μg/g). Participants with im- paired glucose tolerance had higher crude- and creatinine- adjusted urinary total arsenic concentrations than those with normal glucose tolerance. Table 1. The meaning and equation of each fasting state measure and OGTT-derived index Index Definition/clinical significance Equation Reference Measures of insulin sensitivity Stumvoll metabolic clearance rate Correlates with the metabolic clearance rate (MCR) derived from the hyperinsulinaemic-euglycaemic clamp that measures the rate of glucose uptake into tissues (primarily muscle and adipose tissue). MCR from clamp studies is calculated as the average glucose infusion rate divided by the average plasma glucose concentration during the last hour of a hyperinsulinaemic-euglycaemic clamp. Higher levels indicate greater insulin sensitivity. 18.8 � 0.271 × BMI � 0.0052 × I120 � 0.27 × G90 14 Stumvoll insulin sensitivity index Correlates with the insulin sensitivity index (ISI) derived from the hyperinsulinaemic-euglycaemic clamp and represents the amount of glucose metabolized per unit of plasma insulin. ISI from clamp studies is calculated as the metabolic clearance rate divided by the mean insulin concentration during the same period of the clamp. Higher levels indicate greater insulin sensitivity. 0.226 � 0.0032 × BMI � 0.0000645 × I120 � 0.0037 × G90 14 Matsuda index Correlates with the rate of whole-body glucose uptake into tissues (primarily muscle and adipose tissue) during the hyperinsulinaemic-euglycaemic clamp. Higher levels indicate greater insulin sensitivity. 10000 / ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi G0�I0�Gmean�Imean p (glucose in ‘mg/dL’ and insulin in ‘μU/mL’) 15 Measures of β-cell function Stumvoll insulin secretion, phase 1 Correlates with first-phase insulin secretion (rise in insulin levels during the 10 min immediately after starting the glucose infusion that rapidly raises glucose levels) during a hyperglycaemic clamp. Higher levels indicate greater insulin secretion capacity. 1283 + 1.829 × I30 � 138.7 × G30 + 3.772 × I0 14 Stumvoll insulin secretion, phase 2 Correlates with second-phase insulin secretion, the steady-state insulin levels during the last hour of the hyperglycaemic clamp. Higher levels indicate greater insulin secretion capacity. 287 + 0.4164 × I30 � 26.07 × G30 + 0.9226 × I0 14 Insulinogenic index Measure of early phase insulin secretion. For a given rise in plasma glucose during the first 30 min of an OGTT, a larger index indicates greater insulin secretion. (I30 � I0) / (G30 � G0) 16 Fasting-state measures HOMA-IR Insulin resistance index calculated from fasting glucose and insulin based on a physiologic model of the glucose and insulin relationship in vivo (homeostasis model). Lower levels indicate greater insulin sensitivity. (G0 × I0) / 22.5 (insulin in μU/mL) 17 HOMA-%β Beta-cell function index calculated from the homeostasis model. It is expressed as a percent of normal β-cell function. (20 × I0) / (G0 � 3.5)% 17 Body mass index (BMI) in kg/m2. Insulin in pmol/L and glucose in mmol/L unless stated otherwise. G0, fasting glucose; G30/G90, glucose 30 and 90 min after the administration of 75 g glucose; Gmean, mean glucose during oral glucose tolerance test (OGTT); I0, fasting insulin; I30/I120, insulin 30 and 120 min after the administration of 75 g glucose; Imean, mean insulin during OGTT. Arsenic and Insulin Sensitivity/β-Cell 567 Copyright © 2015 John Wiley & Sons, Ltd. Diabetes Metab Res Rev 2016; 32: 565–571. DOI: 10.1002/dmrr Urinary total arsenic was significantly and inversely asso- ciated with all insulin sensitivity indices with adjustment for age, sex and urinary creatinine (model 1, Table 4). After further adjusting for adiposity (model 2), associations remained significant for two of the three OGTT-based insu- lin sensitivity measures; an IQR increase in urinary total ar- senic (6.24 μg/L) was significantly, inversely associated with Stumvoll MCR (�0.23 mg/(kg min), 95% confidence interval (CI): �0.38, �0.09; p= 0.0015) and Stumvoll ISI (�0.0029 μmol/(kg min pM), 95% CI: �0.0047, �0.0011; p= 0.0015). Urinary total arsenic was also significantly as- sociated with higher glucose levels (0.57 (95% CI: 0.06, 1.09) mg/dL per IQR increase; p = 0.029). No significant associations were found between urinary arsenic and measures of β-cell function. The results remained un- changed in the models without urinary creatinine ad- justment (Table 4). Discussion This is the first epidemiologic study to examine arsenic ex- posure and OGTT-based measures of insulin sensitivity and β-cell function. In this preliminary study of non- diabetic Amish adults, urinary total arsenic was inversely associated with OGTT-based insulin sensitivity measures. Notably, these associations were stronger and remained statistically significant following covariate adjustment compared with the widely used index of insulin resis- tance, HOMA-IR, which is based on fasting measures of insulin and glucose. Possibly, the previous mixed results [11,12,19–21] may be partly because of low sensitivity of HOMA-IR. The OGTT-based insulin sensitivity measures, such as Stumvoll MCR, showed better correlations with the hyperinsulinaemic-euglycaemic clamp-based insulin sensitivity than the fasting indices, such as HOMA-IR [22]. We did not observe significant associations of uri- nary total arsenic with any measures of β-cell function. To our knowledge, only two human studies have ex- amined arsenic exposure and measures of both insulin sensitivity and β-cell function [12,19]. In 72 Mexican subjects with mean urinary total arsenic concentrations of 133.4 (SD = 67) μg/L for non-diabetic (n = 32) and 100.9 (SD = 65.2) μg/L for type 2 diabetic subjects (n = 40), urinary total arsenic was inversely associated with HOMA2-%β but was not significantly associated with HOMA2-IR [12]. A national survey conducted in Korea (n = 3602; median urinary total arsenic concentra- tions= 117.7 μg/g creatinine) also reported a significant in- verse association of urinary total arsenic with HOMA2-%β but no significant association with HOMA2-IR [19]. Their arsenic exposure levels were much higher than those found in our study (5.4 μg/L), which is comparable with that found in non-Hispanic white, non-fish eating, never- smoker adults from NHANES 2003–2008 data (5.7 μg/L (IQR: 3.2–11.0), unpublished data). A recent National Tox- icology Program (NTP) workshop review suggested that the arsenic effects on β-cell function are concentration de- pendent [8]: Low concentrations (in the submicromolar range) may lead to impaired glucose-stimulated insulin se- cretion through adaptive cellular responses to arsenic- induced oxidative stress, whereas high concentrations may lead to apoptosis or necrosis via irreversible oxidative dam- age to β-cells. The NTP workshop review also suggested that low concentrations may inhibit insulin signalling and Table 2. Population characteristics (N = 221) Mean ± SD or otherwise specified Age (years) 52.9 ± 13.2 Female, N (%) 115 (52) BMI (kg/m2) 27.5 ± 5.0 Waist-to-hip ratio 0.87 ± 0.066 Fasting glucose (mg/dL) 91.4 ± 8.0 Fasting insulina (μU/mL) 11.4 ± 8.3 Glucose 120 min (mg/dL) 119.4 ± 31.8 Stumvoll MCRb (mg/(kg min)) 7.8 ± 2.6 Stumvoll ISIb (μmol/(kg min pM)) 0.091 ± 0.032 Matsuda indexa 4.9 ± 2.2 Stumvoll insulin secretion, phase 1c (pM) 960.9 ± 461.6 Stumvoll insulin secretion, phase 2c (pM) 265.1 ± 104.4 Insulinogenic indexc 89.7 ± 81.9 HOMA-IRa 2.6 ± 1.8 HOMA-%βa 153.9 ± 124.6 aN = 219. bN = 215. cN = 216. Table 3. Distributions (median and interquartile range (Q1 and Q3)) of urinary total arsenic by covariates N Creatinine unadjusted (μg/L) Creatinine adjusted (μg/g) All 221 5.45 (3.14, 9.37) 6.12 (4.10, 10.15) Age (years) 20–39 32 4.83 (2.38, 6.34) 4.60 (3.70, 9.26) 40–59 122 4.95 (2.45, 8.80) 5.70 (3.88, 9.24) ≥60 67 7.48 (4.59, 11.37) 7.44 (5.25, 13.16) Sex Male 106 6.43 (4.72, 10.08) 5.42 (3.95, 9.31) Female 115 4.17 (2.17, 8.47) 7.02 (4.45, 11.99) BMI (kg/m2) <25 72 6.03 (2.90, 8.64) 6.06 (4.37, 10.59) 25–29 88 5.09 (3.02, 9.00) 6.06 (4.00, 8.25) ≥30 61 5.83 (3.42, 11.15) 6.48 (3.79, 12.94) High waist-to-hip ratioa No 119 4.96 (2.33, 8.34) 6.00 (3.87, 9.31) Yes 102 6.06 (3.94, 10.94) 6.60 (4.24, 11.80) OGTT Normal 164 5.11 (2.55, 8.75) 5.71 (3.90, 9.59) Impaired 57 6.32 (4.58, 11.24) 7.08 (4.81, 11.99) aHigh waist-to-hip ratio was defined as waist-to-hip ratio ≥0.9 for men and ≥0.85 for women [34]. 568 S. K. Park et al. Copyright © 2015 John Wiley & Sons, Ltd. Diabetes Metab Res Rev 2016; 32: 565–571. DOI: 10.1002/dmrr insulin-dependent glucose uptake by adipocytes or skeletal muscle cells. Although it is unclear why our findings are in- consistent with the previous ones, low-level arsenic expo- sure found in the present study may result in insulin resistance through inhibition of insulin signalling and insulin-dependent glucose uptake [8,23,24]. More epi- demiologic studies with a wide range of exposure levels and measures of insulin sensitivity and β-cell function are warranted to investigate concentration-dependent mechanisms. Non-significant associations between urinary total arse- nic and fasting state-based measures seem to be because of confounding by adiposity. The age- and sex-adjusted as- sociation between urinary total arsenic and HOMA-IR was statistically significant (model 1, Table 4), but the effect estimate was substantially attenuated after adjustment for adiposity (BMI and waist-to-hip ratio) (model 2, Table 4). In this population, urinary total arsenic concentrations were modestly correlated with BMI and waist-to-hip ratio (Pearson correlation coefficient for both measures = 0.17). Adiposity is a well-known risk factor for insulin resistance and diabetes [25]. Given that drinking water and diet are major environmental sources of arsenic exposure [2] and more food and water consumption is expected in obese in- dividuals, adiposity may play a role as a positive con- founder, and therefore, reduced effect estimates are expected with adiposity adjustment. However, previous lit- erature has reported an inverse association between BMI and arsenic biomarkers [26–28]. This is because obese individuals are more likely to consume more methyl donors, such as methionine, folic acid and vitamin B12, that facili- tate arsenic methylation, resulting in faster arsenic ex- cretion [26]. Gruber et al. found an inverse association between toenail arsenic and dietary fat intake, suggesting that dietary fat may inhibit arsenic absorption [29]. Differ- ent population characteristics including dietary habits, life- style and genetic variations may explain the inconsistency observed in our population, but our study is limited to fully understand plausible links between adiposity and arsenic metabolism and excretion because of the lack of arsenic species data. Future studies of the role of adiposity in arse- nic metabolism and in the arsenic diabetes association in the Amish population are needed. There are several limitations. We did not measure arse- nic species. Total urinary arsenic reflects all arsenic spe- cies including inorganic forms of arsenic and their methylated metabolites and the organic forms. A NTP workshop recommended arsenic speciation analysis because it is assumed that the inorganic arsenic and methylated metabolites, but not the organic forms, may be associated with type 2 diabetes [8]. It is also important to consider the organic forms of arsenic (e.g. arsenobetaine), a less-toxic species of arsenic found in seafood, in data anal- ysis. However, it is unresolved whether the organic species of arsenic should be adjusted as a covariate or subtracted from total arsenic concentrations [30–32]. Given that expo- sure to the organic forms of arsenic occurs through fish con- sumption and fish is not a common component of the Amish Table 4. Differences in OGTT-based insulin measures per interquartile range (6.24 μg/L) increase in urinary total arsenic (n = 221) With creatinine adjustment Without creatinine adjustment Model 1a Model 2b Model 1 Model 2 Fasting glucose (mg/dL) 0.82 (0.30, 1.34)* 0.57 (0.059, 1.09)** 0.81 (0.29, 1.32)* 0.54 (0.030, 1.05)** Glucose (120 min) (mg/dL) 1.12 (�0.33, 2.57) 0.74 (�0.77, 2.25) 1.63 (0.27, 3.00)** 1.17 (�0.26, 2.59) Measures of insulin sensitivity Stumvoll MCR (mg/(kg min)) �0.27 (�0.42, �0.11)* �0.23 (�0.38, �0.089)* �0.30 (�0.45, �0.15)* �0.27 (�0.41, �0.13)* Stumvoll ISI (μmol/(kg min pM)) �0.0033 (�0.0052, �0.0014)* �0.0029 (�0.0047, �0.0011)* �0.0037 (�0.0055, �0.0019)* �0.0034 (�0.0051, �0.0017)* Matsuda index (percent difference) �3.8 (�6.2, �1.3)* �1.5 (�4.3, 1.2) �4.3 (�6.6, �1.9)* �1.8 (�4.5, 0.95) Measures of β-cell function Stumvoll insulin secretion, phase 1 (pM) 19.4 (�22.5, 61.3) 4.8 (�37.1, 46.8) 24.9 (�14.5, 64.2) 7.9 (�32.2, 47.9) Stumvoll insulin secretion, phase 2 (pM) 4.9 (�4.5, 14.3) 1.5 (�7.9, 10.9) 6.3 (�2.5, 15.1) 2.3 (�6.6, 11.3) Insulinogenic index (percent difference) 0.51 (�6.7, 8.3) �1.8 (�8.8, 6.0) 0.81 (�6.1, 8.2) �1.8 (�8.7, 5.6) Fasting-state measures HOMA-IR (percent difference) 3.1 (0.79, 5.4)* 0.72 (�1.8, 3.3) 3.7 (1.4, 6.1)* 1.1 (�1.5, 3.7) HOMA-%β (percent difference) �0.64 (�3.2, 2.0) �1.8 (�4.6, 1.1) �0.10 (�2.7, 2.5) �1.4 (�4.2, 1.4) aModel 1 adjusted for age and sex in generalized estimating equations accounting for sibship. bModel 2 additionally adjusted for waist-to-hip ratio and BMI. BMI was not adjusted when modeling Stumvoll MCR and Stumvoll ISI because BMI is used to calculate those indices. For both models 1 and 2, results when urine creatinine was included as a covariate and when it was not are presented separately. *p value <0.01. **0.01 ≤ p value < 0.05. Arsenic and Insulin Sensitivity/β-Cell 569 Copyright © 2015 John Wiley & Sons, Ltd. Diabetes Metab Res Rev 2016; 32: 565–571. DOI: 10.1002/dmrr diet, the contribution of the organic forms to the urinary to- tal arsenic concentrations might be minimal in our study. Al- though the study participants are not diabetic subjects, they have a family history of diabetes given the study design of AFDS; thus, they may be at higher risk of diabetes than those without a family history. Our study was conducted in a cross-sectional setting that raises concerns of the validity of causal inferences between urinary arsenic and insulin sensitivity. This preliminary study suggests several future direc- tions. Given that arsenic metabolism, such as arsenic methylation efficiency, has been associated with diabetes in several studies including prospective evidence with in- cident diabetes [33], it will be important to evaluate the associations between arsenic metabolism and OGTT- based measures of insulin sensitivity and β-cell function. Future studies will also need to evaluate potential sources of arsenic exposure in this population of the Amish. Al- though the exposure level found in this preliminary study was low, given that all of the Amish use well-water for drinking and they adhere to traditional lifestyle and dietary habits, it will be important to identify main sources of arse- nic (especially inorganic arsenic) in this community. In conclusion, this preliminary study using OGTT-based measures of insulin sensitivity and β-cell function suggests that low-level arsenic exposure may influence diabetes risk through impairing insulin sensitivity rather than insu- lin secretion through pancreatic β-cells. Acknowledgements This study was supported by the National Institutes of Health P30ES017885, P30DK020572 and P60DK079637 and the Univer- sity of Michigan Office of the Vice President for Research, Faculty Grants and Awards Program. Conflicts of interest The authors have no conflicts of interest. Statements All of the authors have read and approved the article, and it has not been published previously nor is it being consid- ered by any other peer-reviewed journal. All authors have agreed to submit the article to Diabetes/Metabolism Re- search and Reviews. References 1. Priority list of hazardous substances [article online], 2014. Available from http://www.atsdr.cdc.gov/spl/. Accessed June 22 2015. 2. 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