Multibiomarker approach to assess the magnitude of occupational exposure and effects induced by a mixture of metals

Andrade, Vanda; Serrazina, Daniela; Mateus, M.L.; Batoreu, Camila; Aschner, Michael; Santos, A.P. Marreilha dos

doi:10.1016/j.taap.2021.115684

Cited by 4 publications

(2 citation statements)

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“…The specific threshold values that distinguish NM-exposed populations and normal controls (or pre- and post-exposure) and predict the poor outcomes remain unclear for these biomarkers [ 78 , 81 ]. Which one (or which combination) [ 82 ] is the optimal biomarker remains under-investigated. These two issues need to be resolved by the receiver operating characteristic curve analysis and multivariate regression analysis [ 78 , 79 , 81 , 82 ].…”

Section: Discussionmentioning

confidence: 99%

“…Which one (or which combination) [ 82 ] is the optimal biomarker remains under-investigated. These two issues need to be resolved by the receiver operating characteristic curve analysis and multivariate regression analysis [ 78 , 79 , 81 , 82 ]. The reference ranges of significant oxidative stress and inflammatory biomarkers we identified also should be calculated to better explain the biomarker roles of them in different disease settings [ 74 , 75 , 83 , 84 ].…”

Section: Discussionmentioning

confidence: 99%

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Oxidative Stress and Inflammatory Biomarkers for Populations with Occupational Exposure to Nanomaterials: A Systematic Review and Meta-Analysis

Luo

Xie

et al. 2022

Antioxidants

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Exposure to nanomaterials (NMs) is suggested to have the potential to cause harmful health effects. Activations of oxidative stress and inflammation are assumed as main contributors to NM-induced toxicity. Thus, oxidative stress- and inflammation-related indicators may serve as biomarkers for occupational risk assessment. However, the correlation between NM exposure and these biomarkers remains controversial. This study aimed to perform a meta-analysis to systematically investigate the alterations of various biomarkers after NM exposure. Twenty-eight studies were found eligible by searching PubMed, EMBASE and Cochrane Library databases. The pooled results showed NM exposure was significantly associated with increases in the levels of malonaldehyde (MDA) [standardized mean difference (SMD) = 2.18; 95% confidence interval (CI), 1.50–2.87], 4-hydroxy-2-nonhenal (HNE) (SMD = 2.05; 95% CI, 1.13–2.96), aldehydes C6-12 (SMD = 3.45; 95% CI, 2.80–4.10), 8-hydroxyguanine (8-OHG) (SMD = 2.98; 95% CI, 2.22–3.74), 5-hydroxymethyl uracil (5-OHMeU) (SMD = 1.90; 95% CI, 1.23–2.58), o-tyrosine (o-Tyr) (SMD = 1.81; 95% CI, 1.22–2.41), 3-nitrotyrosine (3-NOTyr) (SMD = 2.63; 95% CI, 1.74–3.52), interleukin (IL)-1β (SMD = 1.76; 95% CI, 0.87–2.66), tumor necrosis factor (TNF)-α (SMD = 1.52; 95% CI, 1.03–2.01), myeloperoxidase (MPO) (SMD = 0.25; 95% CI, 0.16–0.34) and fibrinogen (SMD = 0.11; 95% CI, 0.02–0.21), and decreases in the levels of glutathione peroxidase (GPx) (SMD = −0.31; 95% CI, −0.52–−0.11) and IL-6 soluble receptor (IL-6sR) (SMD = −0.18; 95% CI, −0.28–−0.09). Subgroup analysis indicated oxidative stress biomarkers (MDA, HNE, aldehydes C6-12, 8-OHG, 5-OHMeU, o-Tyr, 3-NOTyr and GPx) in exhaled breath condensate (EBC) and blood samples were strongly changed by NM exposure; inflammatory biomarkers (IL-1β, TNF-α, MPO, fibrinogen and IL-6sR) were all significant in EBC, blood, sputum and nasal lavage samples. In conclusion, our findings suggest that these oxidative stress and inflammatory indicators may be promising biomarkers for the biological monitoring of occupationally NM-exposed workers.

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