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Association between the levels of toxic heavy metals and schizophrenia in the population of Guangxi, China: A case-control study. | LitMetric

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Article Abstract

The relationship between body levels of heavy metals and the risk of schizophrenia remains unclear. This study investigates the relationship between plasma levels of toxic heavy metals and the risk of schizophrenia among adults in Guangxi, China. Plasma concentrations of lead (Pb), cadmium (Cd), arsenic (As), and chromium (Cr) were measured using inductively coupled plasma mass spectrometry (ICP-MS). To evaluate both the single and combined effects of metal exposure on the risk of schizophrenia, we employed multivariate logistic regression, Bayesian Kernel Machine Regression (BKMR), and generalized Weighted Quantile Sum (gWQS) models. Additionally, we employed the Comparative Toxicogenomics Database (CTD) to analyze the mechanistic pathways through which metal mixtures may induce schizophrenia. Relative mRNA expression levels were measured using Real-Time Quantitative Reverse Transcription Polymerase Chain Reaction (RT-qPCR). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted to predict potential biological functions. In logistic regression models, compared to the lowest exposure group (Q1), the odds ratios (ORs) for Pb in groups Q2, Q3, and Q4 were 2.18 (95% CI: 1.20-3.94), 4.74 (95% CI: 2.52-8.95), and 3.62 (95% CI: 1.80-7.28), respectively. Both BKMR and gWQS models indicated a positive correlation between the combined effects of toxic heavy metal mixtures and the risk of schizophrenia, with Pb demonstrating the most substantial impact, particularly in older adults and females. Elevated levels of tumor necrosis factor (TNF) and interleukin-1 beta (IL-1β) were observed in patients with schizophrenia, while the expression of tumor protein p53 (TP53) was significantly reduced. These findings underscore the critical need to avoid exposure to toxic heavy metals to prevent schizophrenia, highlighting significant public health implications.

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http://dx.doi.org/10.1016/j.envpol.2024.125179DOI Listing

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