Arsenic, diabetes-related genes and diabetes prevalence in a general population from Spain: The Hortega Study

Abstract

Background Several studies suggest that inorganic arsenic exposure may be associated with diabetes, but the evidence is not sufficient, especially in populations exposed at low-moderate levels. Polymorphisms (SNPs) in diabetes-related genes have been clearly involved in diabetes risk. We evaluated the interaction of 256 polymorphisms in diabetes-related genes with inorganic arsenic exposure on diabetes risk in the Hortega Study, a representative sample of a general population from Valladolid, Spain. Methods Total urine arsenic was measured in 1451 men and women from Valladolid, Spain. Urine arsenic species (inorganic and methylated arsenic species and arsenobetaine (Asb)) were available in 295 randomly selected participants. To account for the confounding introduced by seafood arsenic (mostly Asb) in total arsenic, we designed a multiple imputation model to predict the missing Asb levels. Prevalent type 2 diabetes (T2D) was defined as fasting glucose levels ≥ 126 mg/dL, non-fasting glucose levels ≥ 200 mg/dL, by physician diagnosis or by diabetes treatment use. Results 108 (7.4%) participants had prevalent T2D. The overall geometric mean of total arsenic was 65.9 μg/g (99.1 and 64.4 μg/g in participants with and without T2D, respectively). The adjusted odds ratios (95% confidence intervals) for T2D comparing the highest with the lowest tertile of total arsenic were 1.71 (0.94 3.13) and 2.52 (1.68 3.80) before and after adjusting for Asb, respectively. Several genotypes were marginally associated with higher risk of diabetes. Top 3 SNPs were rs4135168 (p-value=0.003), rs4135225 (p-value=0.007) in gene TXN and rs9435739 (p-value=0.008) in gene SDHB. Conclusions The findings support the role of arsenic as a diabetogenic factor and the importance of controlling for seafood arsenic in populations with high seafood intake. These preliminary arsenic-gene interaction results require confirmation but provide support to evaluate gene-environment interactions in larger studies.