Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2017 Aug 1;125(8):087001.
doi: 10.1289/EHP577.

The Association of Arsenic Metabolism with Cancer, Cardiovascular Disease, and Diabetes: A Systematic Review of the Epidemiological Evidence

Chin-Chi Kuo  1   2   3   4 , Katherine A Moon  1   2   3 , Shu-Li Wang  5 , Ellen Silbergeld  2 , Ana Navas-Acien  1   2   3   6
Affiliations
Review

The Association of Arsenic Metabolism with Cancer, Cardiovascular Disease, and Diabetes: A Systematic Review of the Epidemiological Evidence

Chin-Chi Kuo et al. Environ Health Perspect. .

Abstract

Background: The available evidence on the role of arsenic metabolism in individual susceptibility to the development of cancer, cardiovascular disease, and diabetes has not been formally and comprehensively reviewed.

Objectives: Our goal was to systematically investigate the association of arsenic metabolism with cancer, cardiovascular disease, and diabetes-related outcomes in epidemiologic studies. As a secondary objective, we characterized the variation of arsenic metabolism in different populations worldwide.

Methods: We searched Medline/PubMed and EMBASE from inception to January 2016 and applied predetermined exclusion criteria. Compositional data analysis was used to describe the distribution of arsenic metabolism biomarkers and evaluate the association between arsenic exposure and metabolism.

Results: Twenty-eight studies met the inclusion criteria, 12 on cancer, nine on cardiovascular disease, and seven on diabetes-related outcomes. The median (interquartile range) for mean iAs%, MMA%, and DMA% was 11.2 (7.8-14.9)%, 13.0 (10.4-13.6)%, and 74.9 (69.8-80.0)%, respectively. Findings across studies suggested that higher arsenic exposure levels were associated with higher iAs% and lower DMA% and not associated with MMA%. For cancer, most studies found a pattern of higher MMA% and lower DMA% associated with higher risk of all-site, urothelial, lung, and skin cancers. For cardiovascular disease, higher MMA% was generally associated with higher risk of carotid atherosclerosis and clinical cardiovascular disease but not with hypertension. For diabetes-related outcomes, the pattern of lower MMA% and higher DMA% was associated with higher risk of metabolic syndrome and diabetes.

Conclusions: Population level of iAs% and DMA%, but not MMA%, were associated with arsenic exposure levels. Overall, study findings suggest that higher MMA% was associated with an increased risk of cancer and cardiovascular disease, while lower MMA% was associated with an increased risk of diabetes and metabolic syndrome. Additional population-based studies and experimental studies are needed to further evaluate and understand the role of arsenic exposure in arsenic metabolism and the role of arsenic metabolism in disease development. https://doi.org/10.1289/EHP577.

PubMed Disclaimer

Figures

Triplot
Figure 1.
The distribution of urine arsenic metabolism profile across enrolled populations worldwide on ternery plot diagram. Three-axis graph (triplot) representing the compositional mean of arsenic metabolism biomarkers (iAs%, MMA%, and DMA%) in different study populations. The circles represent each study population and the country of the study is indicated with an acronym (AR, Argentina; BD, Bangladesh; CL, Chile; CN, China; MX, Mexico; TW, Taiwan; US, USA). The size of the circle corresponds to the study population size. The color of the circles reflects the estimated urine arsenic concentrations (eAs, μg/L) as indicated in the top left legend (the highest two countries: BD and CN; while the lowest two: US and MX. For exact ranking of eAs, please refer to the top panel of Figure 2). The bottom side of the triplot represents iAs%, the right side represents MMA%, and the left side represents DMA%. For each population, the mean iAs%, MMA%, and DMA% can be estimated along parallel lines to the dashed green lines for iAs%, dashed red lines for MMA% and dashed blue lines for DMA%. For instance for the study from Chile (CL), the arsenic metabolism profile was 9.6% for iAs%, 10.8% for MMA% and 79.6% for DMA%. In this graph, we can observe that population means ranged between 5.9% and 16.1% for iAs%, between 9.4 and 14.6% for MMA%, and between 69.3% and 84.2% for DMA%.
Top panel plots country/region (y-axis) across percentage of arsenic metabolism biomarkers (x-axis). Middle panel is a violin plot showing proportions of arsenic metabolites (y-axis) across percentage (x-axis). The bottom panel is a scatter plot with a regression line plotting concentration of eAs in micrograms per liter (y-axis) across percentage (x-axis).
Figure 2.
Variability of arsenic metabolism biomarkers in the study populations. Top panel: The distribution of each arsenic metabolism biomarker (iAs%, MMA%, DMA%) is plotted for each study listed in increasing order (from bottom to top) of the estimated urine arsenic levels in (eAs, μg/L) in the study area. Middle panel, violin plot showing the median (open circle) with interquartile range (horizontal bar) and the kernel probability density for each arsenic metabolism biomarker (iAs%, MMA%, DMA%) across all studies. Bottom panel, the prediction curve (line) (right for iAs%, central for MMA%, and left for DMA%) derived from the compositional regression of each arsenic metabolism biomarker based on estimated urine arsenic levels (eAs, μg/L). The right increasing curve supports that iAs% increases as eAs increases and the left decreasing curve supports that DMA% decreases as eAs increases. The central curve supports that MMA% does not change with changes in eAs concentrations as the line is vertical.
Tabular representation summarizing health outcomes and their corresponding associations with eAs in micrograms per liter, iAs%, MMA%, DMA%, PMI, and SMI.
Figure 3.
Summary of the associations of arsenic methylation patterns with cancer, cardiovascular disease, and diabetes-related outcomes based on the estimated relative risk (eRR) and 95% confidence interval (CI) shown in Tables 1–3. Studies are sorted by estimated arsenic exposure (eAs) within each health outcome. The triangles indicate the direction of the association. An upward-pointing triangle stands for positive association while a downward-pointing triangle stands for a negative association. An upward-pointing triangle indicates a positive and statistically significant association (eRR above 1 and 95% CI not overlapping 1) and a lighter upward-pointing triangle indicates a positive but not statistically significant increase (eRR above 1 but 95% CI overlapping 1). A downward-pointing triangle indicates a negative and statistically significant association (eRR below 1 and 95% CI not overlapping 1) and a lighter downward-pointing triangle indicates a negative but not statistically significant association (eRR below 1 but 95% CI not overlapping 1). A horizontal arrow (↔) indicates a null association (eRR equal to 1). Gray open circles with no arrows indicate the data were not reported in the study. All the associations represented in this figure are also shown in Tables 1–3 as eRR and 95% CI.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Agusa T, Fujihara J, Takeshita H, Iwata H. 2011. Individual variations in inorganic arsenic metabolism associated with AS3MT genetic polymorphisms. Int J Mol Sci 12(4):2351–2382, PMID: 21731446, 10.3390/ijms12042351. - DOI - PMC - PubMed
    1. Aitchison J. 1981. A new approach to null correlations of proportions. Math Geol 13:175–189, 10.1007/BF01031393. - DOI
    1. Aitchison J. 1986. The Statistical Analysis of Compositional Data. London, UK:Chapman & Hall, Ltd.
    1. ATSDR (Agency for Toxic Substances and Disease Registry). 2011. “Priority List of Hazardous Substances.” Atlanta, GA:ATSDR.
    1. Baccarelli A, Rienstra M, Benjamin EJ. 2010. Cardiovascular epigenetics: basic concepts and results from animal and human studies. Circ Cardiovasc Genet 3(6):567–573, PMID: 21156932, 10.1161/CIRCGENETICS.110.958744. - DOI - PMC - PubMed