Maria Grau-Pérez1,2, Chin-Chi Kuo3,4,5, Miranda Spratlen3, Kristina A Thayer6, Michelle A Mendez7, Richard F Hamman8, Dana Dabelea8, John L Adgate9, William C Knowler10, Ronny A Bell11, Frederick W Miller12, Angela D Liese13, Chongben Zhang7, Christelle Douillet7, Zuzana Drobná7,14, Elizabeth J Mayer-Davis7,15, Miroslav Styblo7, Ana Navas-Acien1,16. 1. Department of Environmental Health Sciences, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD mgraupe1@jhu.edu anavasa1@jhu.edu. 2. Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY. 3. Department of Environmental Health Sciences, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD. 4. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD. 5. Kidney Institute and Division of Nephrology, Department of Internal Medicine, China Medical University Hospital and College of Medicine, China Medical University, Taichung, Taiwan. 6. Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC. 7. Department of Nutrition, University of North Carolina Gillings School of Global Public Health, Chapel Hill, NC. 8. Department of Epidemiology, Colorado School of Public Health, University of Colorado Denver, Aurora, CO. 9. Department of Environmental and Occupational Health, Colorado School of Public Health, University of Colorado Denver, Aurora, CO. 10. Diabetes Epidemiology and Clinical Research Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ. 11. Wake Forest School of Medicine, Winston-Salem, NC. 12. National Institute of Environmental Health Sciences, National Institutes of Health, Bethesda, MD. 13. Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC. 14. Department of Biological Sciences, North Carolina State University, Raleigh, NC. 15. Deparment of Medicine, University of North Carolina Gillings School of Global Public Health, Chapel Hill, NC. 16. Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Medical Institutions, Baltimore, MD.
Abstract
OBJECTIVE: Little is known about arsenic and diabetes in youth. We examined the association of arsenic with type 1 and type 2 diabetes in the SEARCH for Diabetes in Youth Case-Control (SEARCH-CC) study. Because one-carbon metabolism can influence arsenic metabolism, we also evaluated the potential interaction of folate and vitamin B12 with arsenic metabolism on the odds of diabetes. RESEARCH DESIGN AND METHODS: Six hundred eighty-eight participants <22 years of age (429 with type 1 diabetes, 85 with type 2 diabetes, and 174 control participants) were evaluated. Arsenic species (inorganic arsenic [iAs], monomethylated arsenic [MMA], dimethylated arsenic [DMA]), and one-carbon metabolism biomarkers (folate and vitamin B12) were measured in plasma. We used the sum of iAs, MMA, and DMA (∑As) and the individual species as biomarkers of arsenic concentrations and the relative proportions of the species over their sum (iAs%, MMA%, DMA%) as biomarkers of arsenic metabolism. RESULTS: Median ∑As, iAs%, MMA%, and DMA% were 83.1 ng/L, 63.4%, 10.3%, and 25.2%, respectively. ∑As was not associated with either type of diabetes. The fully adjusted odds ratios (95% CI), rescaled to compare a difference in levels corresponding to the interquartile range of iAs%, MMA%, and DMA%, were 0.68 (0.50-0.91), 1.33 (1.02-1.74), and 1.28 (1.01-1.63), respectively, for type 1 diabetes and 0.82 (0.48-1.39), 1.09 (0.65-1.82), and 1.17 (0.77-1.77), respectively, for type 2 diabetes. In interaction analysis, the odds ratio of type 1 diabetes by MMA% was 1.80 (1.25-2.58) and 0.98 (0.70-1.38) for participants with plasma folate levels above and below the median (P for interaction = 0.02), respectively. CONCLUSIONS: Low iAs% versus high MMA% and DMA% was associated with a higher odds of type 1 diabetes, with a potential interaction by folate levels. These data support further research on the role of arsenic metabolism in type 1 diabetes, including the interplay with one-carbon metabolism biomarkers.
OBJECTIVE: Little is known about arsenic and diabetes in youth. We examined the association of arsenic with type 1 and type 2 diabetes in the SEARCH for Diabetes in Youth Case-Control (SEARCH-CC) study. Because one-carbon metabolism can influence arsenic metabolism, we also evaluated the potential interaction of folate and vitamin B12 with arsenic metabolism on the odds of diabetes. RESEARCH DESIGN AND METHODS: Six hundred eighty-eight participants <22 years of age (429 with type 1 diabetes, 85 with type 2 diabetes, and 174 control participants) were evaluated. Arsenic species (inorganic arsenic [iAs], monomethylated arsenic [MMA], dimethylated arsenic [DMA]), and one-carbon metabolism biomarkers (folate and vitamin B12) were measured in plasma. We used the sum of iAs, MMA, and DMA (∑As) and the individual species as biomarkers of arsenic concentrations and the relative proportions of the species over their sum (iAs%, MMA%, DMA%) as biomarkers of arsenic metabolism. RESULTS: Median ∑As, iAs%, MMA%, and DMA% were 83.1 ng/L, 63.4%, 10.3%, and 25.2%, respectively. ∑As was not associated with either type of diabetes. The fully adjusted odds ratios (95% CI), rescaled to compare a difference in levels corresponding to the interquartile range of iAs%, MMA%, and DMA%, were 0.68 (0.50-0.91), 1.33 (1.02-1.74), and 1.28 (1.01-1.63), respectively, for type 1 diabetes and 0.82 (0.48-1.39), 1.09 (0.65-1.82), and 1.17 (0.77-1.77), respectively, for type 2 diabetes. In interaction analysis, the odds ratio of type 1 diabetes by MMA% was 1.80 (1.25-2.58) and 0.98 (0.70-1.38) for participants with plasma folate levels above and below the median (P for interaction = 0.02), respectively. CONCLUSIONS: Low iAs% versus high MMA% and DMA% was associated with a higher odds of type 1 diabetes, with a potential interaction by folate levels. These data support further research on the role of arsenic metabolism in type 1 diabetes, including the interplay with one-carbon metabolism biomarkers.
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