标题：HFE Gene Variants Modify the Association between Maternal Lead Burden and Infant Birthweight: A Prospective Birth Cohort Study in Mexico City, Mexico
期刊名称：Environmental Health - a Global Access Science Source
印刷版ISSN：1476-069X
电子版ISSN：1476-069X
出版年度：2010
卷号：9
期号：1
页码：43
DOI：10.1186/1476-069X-9-43
语种：English
出版社：BioMed Central
摘要：Neonatal growth is a complex process involving genetic and environmental factors. Polymorphisms in the hemochromatosis (HFE) iron regulatory genes have been shown to modify transport and toxicity of lead which is known to affect birth weight. We investigated the role of HFE C282Y, HFE H63 D, and transferrin (TF) P570 S gene variants in modifying the association of lead and infant birthweight in a cohort of Mexican mother-infant pairs. Subjects were initially recruited between 1994-1995 from three maternity hospitals in Mexico City and 411 infants/565 mothers had archived blood available for genotyping. Multiple linear regression models, stratified by either maternal/infant HFE or TF genotype and then combined with interaction terms, were constructed examining the association of lead and birthweight after controlling for covariates. 3.1%, 16.8% and 17.5% of infants (N = 390) and 1.9%, 14.5% and 18.9% of mothers (N = 533) carried the HFE C282Y, HFE H63D, and TF P570 S variants, respectively. The presence of infant HFE H63 D variants predicted 110.3 g (95% CI -216.1, -4.6) decreases in birthweight while maternal HFE H63 D variants predicted reductions of 52.0 g (95% CI -147.3 to 43.2). Interaction models suggest that both maternal and infant HFE H63 D genotype may modify tibia lead's effect on infant birthweight in opposing ways. In our interaction models, maternal HFE H63 D variant carriers had a negative association between tibia lead and birthweight. These results suggest that the HFE H63 D genotype modifies lead's effects on infant birthweight in a complex fashion that may reflect maternal-fetal interactions with respect to the metabolism and transport of metals.
关键词：Birth Weight ; Multiple Linear Regression Model ; Iron Status ; Lead Exposure ; Blood Lead Level
