Interaction of fluoride exposure and CREB1 gene polymorphisms on thyroid function in school-age children

Does fluoride exposure affect thyroid function? A systematic review and dose-response meta-analysis

INTRODUCTION

Fluoride exposure may have various adverse health effects, including affecting thyroid function and disease risk, but the pattern of such relation is still uncertain.

METHODS

We systematically searched human studies assessing the relation between fluoride exposure and thyroid function and disease. We compared the highest versus the lowest fluoride category across these studies, and we performed a one-stage dose-response meta-analysis for aggregated data to explore the shape of the association.

RESULTS

Most retrieved studies (27 of which with a cross-sectional design) were conducted in Asia and in children, assessing fluoride exposure through its concentrations in drinking water, urine, serum, or dietary intake. Twenty-four studies reported data on thyroid function by measuring thyroid-related hormones in blood (mainly thyroid-stimulating-hormone - TSH), 9 reported data on thyroid disease, and 4 on thyroid volume. By comparing the highest versus the lowest fluoride categories, overall mean TSH difference was 1.05 μIU/mL. Dose-response curve showed no change in TSH concentrations in the lowest water fluoride exposure range, while the hormone levels started to linearly increase around 2.5 mg/L, also dependending on the risk of bias of the included studies. The association between biomarkers of fluoride exposure and TSH was also positive, with little evidence of a threshold. Evidence for an association between fluoride exposure and blood concentrations of thyroid hormones was less evident, though there was an indication of inverse association with triiodothyronine. For thyroid disease, the few available studies suggested a positive association with goiter and with hypothyroidism in both children and adults.

CONCLUSIONS

Overall, exposure to high-fluoride drinking water appears to non-linearly affect thyroid function and increase TSH release in children, starting above a threshold of exposure, and to increase the risk of some thyroid diseases.

G × E interactions as a basis for toxicological uncertainty

To transfer toxicological findings from model systems, e.g. animals, to humans, standardized safety factors are applied to account for intra-species and inter-species variabilities. An alternative approach would be to measure and model the actual compound-specific uncertainties. This biological concept assumes that all observed toxicities depend not only on the exposure situation (environment = E), but also on the genetic (G) background of the model (G × E). As a quantitative discipline, toxicology needs to move beyond merely qualitative G × E concepts. Research programs are required that determine the major biological variabilities affecting toxicity and categorize their relative weights and contributions. In a complementary approach, detailed case studies need to explore the role of genetic backgrounds in the adverse effects of defined chemicals. In addition, current understanding of the selection and propagation of adverse outcome pathways (AOP) in different biological environments is very limited. To improve understanding, a particular focus is required on modulatory and counter-regulatory steps. For quantitative approaches to address uncertainties, the concept of "genetic" influence needs a more precise definition. What is usually meant by this term in the context of G × E are the protein functions encoded by the genes. Besides the gene sequence, the regulation of the gene expression and function should also be accounted for. The widened concept of past and present "gene expression" influences is summarized here as Ge. Also, the concept of "environment" needs some re-consideration in situations where exposure timing (Et) is pivotal: prolonged or repeated exposure to the insult (chemical, physical, life style) affects Ge. This implies that it changes the model system. The interaction of Ge with Et might be denoted as Ge × Et. We provide here general explanations and specific examples for this concept and show how it could be applied in the context of New Approach Methodologies (NAM).