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Associations between co-exposure to multiple metals and renal function: a cross-sectional study in Guangxi, China

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Abstract

The association between co-exposure to multiple metals and renal function is poorly understood. We aimed to evaluate the individual and joint effects of metal exposure on renal function in this study. We performed a cross-sectional study including 5828 participants in Guangxi, China, in 2019. Urine concentrations of 17 metals were detected by inductively coupled plasma mass spectrometry (ICP-MS). Logistic regression model and restricted cubic spline (RCS) were applied to investigate the association of individual metal exposure with renal dysfunction. Weighted quantile sum (WQS) regression and Bayesian kernel machine regression (BKMR) were used to assess the co-exposure effects of the metals. Participants with the highest quartile of urinary Cu were at 1.84-fold (95% confidence interval (CI): 1.20–2.87) increased risk of renal dysfunction compared with the lowest quartile. The highest quartiles of urinary Sr, Cs, V, Ba, and Se were associated with 0.27-fold (95% CI: 0.17–0.43), 0.33 (95% CI: 0.19–0.53), 0.41 (95% CI: 0.25–0.65), 0.58 (95% CI: 0.36–0.90), and 0.33 (95% CI: 0.19–0.56) decreased risk of renal dysfunction compared with their lowest quartile, respectively. Furthermore, urinary Ba and Cu were non-linearly correlated with renal dysfunction. The WQS analysis showed that mixed metal exposure was inversely associated with renal dysfunction (OR = 0.47, 95% CI: 0.35–0.62), and Sr accounted for the largest weight (52.2%), followed by Cs (32.3%) in the association. Moreover, we observed a potential interaction between Cu, Cs, and Ba for renal dysfunction in BKMR model. Exposure to Se, Sr, Cs, V, and Ba is associated with decreased risk of renal dysfunction, whereas an increased risk is associated with Cu exposure. Co-exposure to these metals is negatively associated with renal dysfunction, and Sr and Cs are the main contributors to the associations.

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Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Abbreviations

ICP-MS:

inductively coupled plasma mass spectrometry

LASSO:

least absolute shrinkage and selection operator

RCS:

restricted cubic spline

WQS:

weighted quantile sum

BKMR:

bayesian kernel machine regression

CKD:

chronic kidney disease

GFR:

glomerular filtration rate

MDRD:

modification of diet in renal disease

SCr:

serum creatinine

LOD:

limits of detection

Tl:

thallium

Rb:

rubidium

Mo:

molybdenum

Ti:

titanium

Sn:

stannum

Cr:

chromium

Ni:

nickel

Pb:

plumbum

Se:

selenium

Sr:

strontium

Cs:

cesium

Cu:

copper

V:

vanadium

Ba:

barium

Mn:

manganese

As:

arsenic

Sb:

stibium

BMI:

body mass index

groupPIP:

group posterior inclusion probability

condPIP:

conditional posterior inclusion probability

References

  • Ashrap P, Sánchez BN, Téllez-Rojo MM, Basu N, Tamayo-Ortiz M, Peterson KE, Meeker JD, Watkins DJ (2019) In utero and peripubertal metals exposure in relation to reproductive hormones and sexual maturation and progression among girls in Mexico City. Environ Res 177:108630

    Article  CAS  Google Scholar 

  • Bello AK, Nwankwo E, El Nahas AM (2005) Prevention of chronic kidney disease: a global challenge. Kidney Int 68(Supplement):S11–S17

    Article  Google Scholar 

  • Bobb JF, Valeri L, Claus Henn B, Christiani DC, Wright RO, Mazumdar M, Godleski JJ, Coull BA (2015) Bayesian kernel machine regression for estimating the health effects of multi-pollutant mixtures. Biostatistics (Oxford, England) 16:493–508

    Article  Google Scholar 

  • Bobb JF, Claus Henn B, Valeri L, Coull BA (2018) Statistical software for analyzing the health effects of multiple concurrent exposures via Bayesian kernel machine regression. Environ Health : A global access science source 17:67

    Article  Google Scholar 

  • Boulassel B, Sadeg N, Roussel O, Perrin M, Belhadj-Tahar H (2011) Fatal poisoning by vanadium. Forensic Sci Int 206:79–81

    Article  Google Scholar 

  • Carrico C, Gennings C, Wheeler DC, Factor-Litvak P (2015) Characterization of weighted quantile sum regression for highly correlated data in a risk analysis setting. J Agric Biol Environ Stat 20:100–120

    Article  Google Scholar 

  • Coker E, Chevrier J, Rauch S, Bradman A, Obida M, Crause M, Bornman R, Eskenazi B (2018) Association between prenatal exposure to multiple insecticides and child body weight and body composition in the VHEMBE South African birth cohort. Environ Int 113:122–132

    Article  CAS  Google Scholar 

  • Crowe E, Halpin D, Stevens P (2008) Early identification and management of chronic kidney disease: summary of NICE guidance. BMJ (Clinical research ed) 337:a1530

    Article  Google Scholar 

  • Cui X, Okayasu R (2008) Arsenic accumulation, elimination, and interaction with copper, zinc and manganese in liver and kidney of rats. Food Chem Toxicol : An Int J Publ Br Ind Biol Res Assoc 46:3646–3650

    Article  CAS  Google Scholar 

  • Czarnota J, Gennings C, Wheeler DC (2015) Assessment of weighted quantile sum regression for modeling chemical mixtures and cancer risk. Cancer Informat 14:159–171

    Google Scholar 

  • Diamond GL, Thayer WC, Brown JS, Burgess M, Follansbee MH, Gaines LGT, Klotzbach JM (2019) Estimates of urinary blood lead clearance and its relationship to glomerular filtration rate based on a large population survey. J Toxicol Environ Health Part A 82:379–382

    Article  CAS  Google Scholar 

  • El-Boshy ME, Risha EF, Abdelhamid FM, Mubarak MS, Hadda TB (2015) Protective effects of selenium against cadmium induced hematological disturbances, immunosuppressive, oxidative stress and hepatorenal damage in rats. J Trace Elements Med Biol : Organ Soc Min Trace Elements (GMS) 29:104–110

    Article  CAS  Google Scholar 

  • Fair PH, Dougherty WJ, Braddon SA (1985) Methyl mercury and selenium interaction in relation to mouse kidney gamma-glutamyltranspeptidase, ultrastructure, and function. Toxicol Appl Pharmacol 80:78–96

    Article  CAS  Google Scholar 

  • Fairweather-Tait SJ, Bao Y, Broadley MR, Collings R, Ford D, Hesketh JE, Hurst R (2011) Selenium in human health and disease. Antioxid Redox Signal 14:1337–1383

    Article  CAS  Google Scholar 

  • Hardy G, Hardy I, Manzanares W (2012) Selenium supplementation in the critically ill. Nutr Clin Pract : Off Publ Am Soc Parent Enteral Nutr 27:21–33

    Article  Google Scholar 

  • Ingsathit A, Thakkinstian A, Chaiprasert A, Sangthawan P, Gojaseni P, Kiattisunthorn K, Ongaiyooth L, Vanavanan S, Sirivongs D, Thirakhupt P, Mittal B, Singh AK (2010) Prevalence and risk factors of chronic kidney disease in the Thai adult population: Thai SEEK study. Nephrol Dialysis, Transplant : Official Publ Eur Dialysis Transplant Assoc - Europ Renal Association 25:1567–1575

    Article  Google Scholar 

  • Jin R, Zhu X, Shrubsole MJ, Yu C, Xia Z, Dai Q (2018) Associations of renal function with urinary excretion of metals: Evidence from NHANES 2003-2012. Environ Int 121:1355–1362

    Article  CAS  Google Scholar 

  • Kim NH, Hyun YY, Lee KB, Chang Y, Ryu S, Oh KH, Ahn C (2015) Environmental heavy metal exposure and chronic kidney disease in the general population. J Korean Med Sci 30:272–277

    Article  CAS  Google Scholar 

  • Kumar V, Kalita J, Misra UK, Bora HK (2015) A study of dose response and organ susceptibility of copper toxicity in a rat model. J Trace Elements Med Biol : Organ Soc Min Trace Elements (GMS) 29:269–274

    Article  CAS  Google Scholar 

  • Kumar V, Kalita J, Bora HK, Misra UK (2016) Relationship of antioxidant and oxidative stress markers in different organs following copper toxicity in a rat model. Toxicol Appl Pharmacol 293:37–43

    Article  CAS  Google Scholar 

  • Lei R, Wu C, Yang B, Ma H, Shi C, Wang Q, Wang Q, Yuan Y, Liao M (2008) Integrated metabolomic analysis of the nano-sized copper particle-induced hepatotoxicity and nephrotoxicity in rats: a rapid in vivo screening method for nanotoxicity. Toxicol Appl Pharmacol 232:292–301

    Article  CAS  Google Scholar 

  • Levey AS, Atkins R, Coresh J, Cohen EP, Collins AJ, Eckardt KU, Nahas ME, Jaber BL, Jadoul M, Levin A, Powe NR, Rossert J, Wheeler DC, Lameire N, Eknoyan G (2007) Chronic kidney disease as a global public health problem: approaches and initiatives - a position statement from Kidney Disease Improving Global Outcomes. Kidney Int 72:247–259

    Article  CAS  Google Scholar 

  • Lister LJ, Svendsen C, Wright J, Hooper HL, Spurgeon DJ (2011) Modelling the joint effects of a metal and a pesticide on reproduction and toxicokinetics in Lumbricid earthworms. Environ Int 37:663–670

    Article  CAS  Google Scholar 

  • Liu Y, Yuan Y, Xiao Y, Li Y, Yu Y, Mo T, Jiang H, Li X, Yang H, Xu C, He M, Guo H, Pan A, Wu T (2020) Associations of plasma metal concentrations with the decline in kidney function: a longitudinal study of Chinese adults. Ecotoxicol Environ Saf 189:110006

    Article  CAS  Google Scholar 

  • Liu Y, Dong R, Yang Y, Xie H, Huang Y, Chen X, Wang D, Zhang Z (2021) Protective effect of organic selenium on oxidative damage and inflammatory reaction of rabbit kidney induced by T-2 toxin. Biol Trace Elem Res 199:1833–1842

    Article  CAS  Google Scholar 

  • Ma YC, Zuo L, Chen JH, Luo Q, Yu XQ, Li Y, Xu JS, Huang SM, Wang LN, Huang W, Wang M, Xu GB, Wang HY (2006) Modified glomerular filtration rate estimating equation for Chinese patients with chronic kidney disease. J Am Soc Nephrol : JASN 17:2937–2944

    Article  Google Scholar 

  • Melnikov P, Zanoni LZ (2010) Clinical effects of cesium intake. Biol Trace Elem Res 135:1–9

    Article  CAS  Google Scholar 

  • Nugent RA, Fathima SF, Feigl AB, Chyung D (2011) The burden of chronic kidney disease on developing nations: a 21st century challenge in global health. Nephron Clin Pract 118:c269–c277

    Article  Google Scholar 

  • Oste L, Bervoets AR, Behets GJ, Dams G, Marijnissen RL, Geryl H, Lamberts LV, Verberckmoes SC, Van Hoof VO, De Broe ME, D'Haese PC (2005) Time-evolution and reversibility of strontium-induced osteomalacia in chronic renal failure rats. Kidney Int 67:920–930

    Article  CAS  Google Scholar 

  • Pors Nielsen S (2004) The biological role of strontium. Bone 35:583–588

    Article  CAS  Google Scholar 

  • Rahman HH, Niemann D, Munson-McGee SH (2021) Association of albumin to creatinine ratio with urinary arsenic and metal exposure: evidence from NHANES 2015-2016. Int Urol Nephrol 54:1343–1353

    Article  Google Scholar 

  • Sanders AP, Mazzella MJ, Malin AJ, Hair GM, Busgang SA, Saland JM, Curtin P (2019) Combined exposure to lead, cadmium, mercury, and arsenic and kidney health in adolescents age 12-19 in NHANES 2009-2014. Environ Int 131:104993

    Article  CAS  Google Scholar 

  • Skröder H, Hawkesworth S, Kippler M, El Arifeen S, Wagatsuma Y, Moore SE, Vahter M (2015) Kidney function and blood pressure in preschool-aged children exposed to cadmium and arsenic--potential alleviation by selenium. Environ Res 140:205–213

    Article  Google Scholar 

  • Tsai HJ, Hung CH, Wang CW, Tu HP, Li CH, Tsai CC, Lin WY, Chen SC, Kuo CH (2021) Associations among heavy metals and proteinuria and chronic kidney disease. Diagnostics (Basel, Switzerland), Basel, p 11

    Google Scholar 

  • Valdivielso JM, Jacobs-Cachá C, Soler MJ (2019) Sex hormones and their influence on chronic kidney disease. Curr Opin Nephrol Hypertens 28:1–9

    Article  CAS  Google Scholar 

  • Wang X et al (2020) Exposure to multiple metals in early pregnancy and gestational diabetes mellitus: a prospective cohort study. Environ Int 135:105370

    Article  CAS  Google Scholar 

  • Wanigasuriya KP, Peiris-John RJ, Wickremasinghe R (2011) Chronic kidney disease of unknown aetiology in Sri Lanka: is cadmium a likely cause? BMC Nephrol 12:32

    Article  Google Scholar 

  • Weaver VM, Kotchmar DJ, Fadrowski JJ, Silbergeld EK (2016) Challenges for environmental epidemiology research: are biomarker concentrations altered by kidney function or urine concentration adjustment? J Exposure Sci Environ Epidemiol 26:1–8

    Article  CAS  Google Scholar 

  • Wu W, Zhang K, Jiang S, Liu D, Zhou H, Zhong R, Zeng Q, Cheng L, Miao X, Tong Y, Lu Q (2018) Association of co-exposure to heavy metals with renal function in a hypertensive population. Environ Int 112:198–206

    Article  CAS  Google Scholar 

  • Yang F, Yi X, Guo J, Xu S, Xiao Y, Huang X, Duan Y, Luo D, Xiao S, Huang Z, Yuan H, He M, Shen M, Chen X (2019) Association of plasma and urine metals levels with kidney function: a population-based cross-sectional study in China. Chemosphere 226:321–328

    Article  CAS  Google Scholar 

  • Zhang L et al (2012) Prevalence of chronic kidney disease in China: a cross-sectional survey. Lancet (London, England) 379:815–822

    Article  Google Scholar 

  • Zhang Y, Dong T, Hu W, Wang X, Xu B, Lin Z, Hofer T, Stefanoff P, Chen Y, Wang X, Xia Y (2019) Association between exposure to a mixture of phenols, pesticides, and phthalates and obesity: Comparison of three statistical models. Environ Int 123:325–336

    Article  CAS  Google Scholar 

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Acknowledgements

The authors acknowledge all participants and all staff for their supports and cooperation in this study. We also thank the Guangxi Colleges and Universities Key Laboratory of Prevention and Control of Highly Prevalent Diseases, and Academician Dongxin Lin workstation for providing a good experimental environment.

Funding

This work was funded by National Key Research and Development Program of China (2017YFC09071030).

Author information

Author notes

  1. Xingxi Luo and Dongping Huang are co-first authors and contributed equally to this work.

Authors and Affiliations

  1. Department of Epidemiology and Health Statistics, School of Public Health, Guangxi Medical University, Nanning, 530021, Guangxi, China

    Xingxi Luo, Suyang Xiao, Lei Lei, Kaili Wu, Yu Yang, Meiliang Liu, Xiaoqiang Qiu & Xiaoyun Zeng

  2. Department of Sanitary Chemistry, School of Public Health, Guangxi Medical University, Nanning, 530021, Guangxi, China

    Dongping Huang

  3. Department of Maternal, Child and Adolescent Health, School of Public Health, Guangxi Medical University, Nanning, 530021, Guangxi, China

    Shun Liu

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  1. Xingxi Luo
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Contributions

Xingxi Luo: conceptualization, formal analysis, methodology, writing-original draft, investigation. Dongping Huang: methodology, writing-original draft, formal analysis, investigation, data curation. Suyang Xiao: methodology, validation, investigation, data curation. Lei Lei: methodology, writing-review & editing. Kaili Wu: formal analysis, validation. Yu Yang: investigation, data curation. Meiliang Liu: data curation. Xiaoqiang Qiu: methodology, funding acquisition. Shun Liu: conceptualization, methodology, resources, writing-review & editing, supervision. Xiaoyun Zeng: conceptualization, methodology, resources, data curation, writing-review & editing, supervision, funding acquisition.

Corresponding author

Correspondence to Xiaoyun Zeng.

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This study was approved by the Ethics Review Committee of Guangxi Medical University.

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Luo, X., Huang, D., Xiao, S. et al. Associations between co-exposure to multiple metals and renal function: a cross-sectional study in Guangxi, China. Environ Sci Pollut Res 30, 2637–2648 (2023). https://doi.org/10.1007/s11356-022-22352-x

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