The correlation between single and mixed trace elements exposure in systemic lupus erythematosus: A case-control study

Rong-Gui Huang; Kai-Di Li; Hong Wu; Yi-Yu Wang; Ya Xu; Xue Jin; Yu-Jie Du; Yi-Yuan Wang; Jing Wang; Zhang-Wei Lu; Bao-Zhu Li

doi:10.1016/j.jtemb.2024.127524

The correlation between single and mixed trace elements exposure in systemic lupus erythematosus: A case-control study

J Trace Elem Med Biol. 2024 Sep 12:86:127524. doi: 10.1016/j.jtemb.2024.127524. Online ahead of print.

Authors

Rong-Gui Huang¹, Kai-Di Li¹, Hong Wu¹, Yi-Yu Wang¹, Ya Xu², Xue Jin¹, Yu-Jie Du¹, Yi-Yuan Wang¹, Jing Wang¹, Zhang-Wei Lu¹, Bao-Zhu Li³

Affiliations

¹ Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China.
² School of Clinical Medicine, Anhui Medical University, Hefei, Anhui, China.
³ Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China. Electronic address: lbz88730@163.com.

PMID: 39293108
DOI: 10.1016/j.jtemb.2024.127524

Abstract

Background: Recent studies have shown an association between trace elements and systemic lupus erythematosus (SLE), but the relationship between trace elements and SLE is still unclear. This study aims to determine the distribution of plasma trace elements in newly diagnosed SLE patients and the association between these essential and toxic element mixtures and SLE.

Methods: In total, 110 SLE patients and 110 healthy controls were included. Blood samples were collected. 15 plasma trace elements were quantified using an inductively coupled plasma mass spectrometer (ICP-MS). Multivariate logistic regression, restricted cubic spline (RCS), weighted quantile sum (WQS) regression, quantile g-computation (qgcomp), and Bayesian kernel machine regression (BKMR) are used to analyze the association between single and mixed exposure of elements and SLE.

Results: The logistic regression model shows that, plasma lithium (Li) [OR (95 % CI): 1.963 (1.49-2.586)], vanadium (V) [OR (95 % CI): 2.617(1.645-4.166)] and lead (Pb) [OR (95 % CI): 1.603(1.197-2.145)] were positively correlated with SLE, while selenium (Se) [OR (95 % CI): 0.055(0.019-0.157)] and barium (Ba) [OR (95 % CI): 0.792(0.656-0.957)] had been identified as protective factors for SLE. RCS results showed a non-linear correlation between the elements Li, V, Ni, copper, Se, rubidium and SLE. In addition, WQS regression, qgcomp, and BKMR models consistently revealed significant positive effects of plasma Li and Pb on SLE, as well as significant negative effects of plasma Se.

Conclusions: Exposure to heavy metals such as Li and Pb is significantly positively correlated with SLE, but Se may be protective factors for SLE. In addition, there is a nonlinear correlation between the elements Li and Se and SLE, and there are complex interactions between the elements. In the future, larger populations and prospective studies are needed to confirm these associations.

Keywords: Essential trace elements; Heavy metal; ICP-MS; Mixed exposure; Plasma; Systemic lupus erythematosus.