Biomarkers of Methylmercury Exposure Immunotoxicity among Fish Consumers in Amazonian Brazil
Bibliographic record
Abstract
BACKGROUND: Mercury (Hg) is a ubiquitous environmental contaminant with neurodevelopmental and immune system effects. An informative biomarker of Hg-induced immunotoxicity could aid studies on the potential contribution to immune-related health effects. OBJECTIVES: Our objectives were to test the hypothesis that methylmercury (MeHg) exposures affect levels of serum biomarkers and to examine interactions between Hg and selenium (Se) in terms of these responses. METHODS: This cross-sectional epidemiological study assessed adults living along the Tapajós River, a system long affected by MeHg. We measured antinuclear (ANA) and antinucleolar (ANoA) autoantibody levels and eight cytokines in serum samples (n = 232). Total Hg (including MeHg) and Se were measured in blood, plasma, hair, and urine. RESULTS: The median (range) total Hg concentrations were 14.1 μg/g (1.1-62.4), 53.5 μg/L (4.3-288.9), 8.8 μg/L (0.2-40), and 3.0 μg/L (0.2-16.1) for hair, blood, plasma, and urine, respectively. Elevated titers of ANA (but not ANoA) were positively associated with MeHg exposure (log-transformed, for blood and plasma), unadjusted [odds ratio (OR) = 2.6; 95% confidence interval (CI): 1.1, 6.2] and adjusted for sex and age (OR = 2.9; 95% CI: 1.1, 7.5). Proinflammatory [interleukin (IL)-6 and interferon (IFN)-γ], anti-inflammatory (IL-4), and IL-17 cytokine levels were increased with MeHg exposure; however, in the subset of the population with elevated ANA, proinflammatory IL-1β, IL-6, IFN-γ, and tumor necrosis factor (TNF)-α and anti-inflammatory (IL-4) cytokine levels were decreased with MeHg exposure. Although Se status was associated with MeHg level (correlation coefficient = 0.86; 95% CI: 0.29, 1.43), Se status was not associated with any changes in ANA and did not modify associations between Hg and ANA titers. CONCLUSIONS: MeHg exposure was associated with an increased ANA and changes in serum cytokine profile. Moreover, alterations in serum cytokine profiles differed based on ANA response, suggesting a specific phenotype of MeHg susceptibility. Further research on the potential health implications of these observed immunological changes is warranted.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".