Xiao-Wen Zeng1, Caroline J Lodge2, Shyamali C Dharmage2, Michael S Bloom3, Yunjiang Yu4, Mo Yang5, Chu Chu5, Qing-Qing Li5, Li-Wen Hu5, Kang-Kang Liu5, Bo-Yi Yang5, Guang-Hui Dong6. 1. Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China; Allergy and Lung Health Unit, Centre for Epidemiology and Biostatistics, School of Population & Global Health, The University of Melbourne, Melbourne, VIC 3052, Australia. 2. Allergy and Lung Health Unit, Centre for Epidemiology and Biostatistics, School of Population & Global Health, The University of Melbourne, Melbourne, VIC 3052, Australia. 3. Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China; Departments of Environmental Health Sciences & Epidemiology and Biostatistics, University at Albany, State University of New York, Rensselaer, NY 12144, USA. 4. State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Environmental Protection, Guangzhou 510655, China. 5. Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China. 6. Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China. Electronic address: donggh5@mail.sysu.edu.cn.
Abstract
BACKGROUND: Greater levels of serum per- and polyfluoroalkyl substances (PFAS) are known to be associated with higher uric acid which itself leads to a number of chronic diseases. However, whether this association varies across PFAS isomers which recently have been found to be associated with human health remains unknown. OBJECTIVES: To address this research gap, we explored isomer-specific associations between serum PFAS and uric acid in Chinese adults. METHODS: We conducted a cross-sectional study of associations between serum PFAS isomer and serum uric acid in 1612 participants from the Isomer of C8 Health Project. We used multivariable linear and logistic regression models to analyze serum isomers of perfluorooctanoate (PFOA), perfluorooctane sulfonate (PFOS), and other PFASs as continuous and categorical predictors of uric acid, adjusted for confounders. The association was also stratified by kidney function stage based on estimated glomerular filtration rate (GF-1, GF-2, GF-3a, and GF-3b/4). RESULTS: We found positive associations between serum PFAS isomer concentrations and uric acid. Uric acid levels were greater for each log-unit increase in branched PFOA (β = 0.30, 95% CI: 0.21, 0.40), linear PFOA (β = 0.18, 95% CI: 0.09, 0.26), branched PFOS (β = 0.09, 95% CI: 0.02, 0.17) and linear PFOS (β = 0.06, 95% CI: -0.01, 0.14) concentration. The associations between PFAS and uric acid showed an inverted 'U' shaped pattern across kidney function stages. For example, uric acid level was greater with each log-unit increase in total-PFOA among GF-1 (β = 0.21, 95% CI: 0.06, 0.37), this relationship was greater in GF-3a (β = 0.49, 95% CI: 0.09, 0.89) and decreased in GF-3b/4 (β = -0.22, 95% CI: -0.83, 0.39). We also found the odds of hyperuricemia increased linearly with increasing branched PFOA in quartiles (odds ratio = 2.67, 95% CI: 1.86, 3.85 at the highest quartile). CONCLUSION: We report novel results in which PFAS associations with uric acid varied according to isomer and adult kidney function. Besides, our findings are consistent with previous epidemiologic studies in finding a positive association between serum PFAS concentrations and serum uric acid, especially for PFOA. Our results indicate that more research is needed to more clearly assess the impact of PFAS isomers on human health, which will help to refine regulation policies for PFAS.
BACKGROUND: Greater levels of serum per- and polyfluoroalkyl substances (PFAS) are known to be associated with higher uric acid which itself leads to a number of chronic diseases. However, whether this association varies across PFAS isomers which recently have been found to be associated with human health remains unknown. OBJECTIVES: To address this research gap, we explored isomer-specific associations between serum PFAS and uric acid in Chinese adults. METHODS: We conducted a cross-sectional study of associations between serum PFAS isomer and serum uric acid in 1612 participants from the Isomer of C8 Health Project. We used multivariable linear and logistic regression models to analyze serum isomers of perfluorooctanoate (PFOA), perfluorooctane sulfonate (PFOS), and other PFASs as continuous and categorical predictors of uric acid, adjusted for confounders. The association was also stratified by kidney function stage based on estimated glomerular filtration rate (GF-1, GF-2, GF-3a, and GF-3b/4). RESULTS: We found positive associations between serum PFAS isomer concentrations and uric acid. Uric acid levels were greater for each log-unit increase in branched PFOA (β = 0.30, 95% CI: 0.21, 0.40), linear PFOA (β = 0.18, 95% CI: 0.09, 0.26), branched PFOS (β = 0.09, 95% CI: 0.02, 0.17) and linear PFOS (β = 0.06, 95% CI: -0.01, 0.14) concentration. The associations between PFAS and uric acid showed an inverted 'U' shaped pattern across kidney function stages. For example, uric acid level was greater with each log-unit increase in total-PFOA among GF-1 (β = 0.21, 95% CI: 0.06, 0.37), this relationship was greater in GF-3a (β = 0.49, 95% CI: 0.09, 0.89) and decreased in GF-3b/4 (β = -0.22, 95% CI: -0.83, 0.39). We also found the odds of hyperuricemia increased linearly with increasing branched PFOA in quartiles (odds ratio = 2.67, 95% CI: 1.86, 3.85 at the highest quartile). CONCLUSION: We report novel results in which PFAS associations with uric acid varied according to isomer and adult kidney function. Besides, our findings are consistent with previous epidemiologic studies in finding a positive association between serum PFAS concentrations and serum uric acid, especially for PFOA. Our results indicate that more research is needed to more clearly assess the impact of PFAS isomers on human health, which will help to refine regulation policies for PFAS.
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