标题：Fluoride exposure and children’s intelligence: Gene-environment interaction based on SNP-set, gene and pathway analysis, using a case-control design based on a cross-sectional study
摘要：Background Excessive fluoride exposure has been associated with intelligence loss, but little is known about gene-fluoride interactions on intelligence at SNP-set, gene and pathway level. Objectives Here we conducted a population-based study in Chinese school-aged children to estimate the associations of fluoride from internal and external exposures with intelligence as well as to explore the gene-fluoride interactions on intelligence at SNP-set, gene and neurodevelopmental pathway level. Methods A total of 952 resident children aged 7 to 13 were included in the current study. The fluoride contents in drinking water, urine, hair and nail were measured using the ion-selective electrode method. LASSO Binomial regression was conducted to screen the intelligence-related SNP-set. The gene-fluoride interactions at gene and pathway levels were detected by the Adaptive Rank Truncated Product method. Results The probability of high intelligence was inversely correlated with fluoride contents in water, urine, hair and nail (all P < 0.001). The SNP-set based on rs3788319, rs1879417, rs57377675, rs11556505 and rs7187776 was related to high intelligence ( P = 0.001) alone and by interaction with water, urinary and hair fluoride ( P = 0.030, 0.040, 0.010), separately. In gene level, CLU and TOMM40 interacted with hair fluoride (both P = 0.017) on intelligence. In pathway level, Alzheimer disease pathway, metabolic pathway, signal transduction pathway, sphingolipid signaling pathway and PI3K-AKT signaling pathway interacted with fluoride on intelligence in men. Conclusions Our study suggests that fluoride is inversely associated with intelligence. Moreover, the interactions of fluoride with mitochondrial function-related SNP-set, genes and pathways may also be involved in high intelligence loss.
关键词：Fluoride ; Intelligence loss ; Interaction ; SNP panel ; Pathway analysis
