Title: Intrauterine multi-metal exposure is associated with reduced fetal growth through modulation of the placental gene network.
Authors: Deyssenroth, Maya A; Gennings, Chris; Liu, Shelley H; Peng, Shouneng; Hao, Ke; Lambertini, Luca; Jackson, Brian P; Karagas, Margaret R; Marsit, Carmen J; Chen, Jia
Published In Environ Int, (2018 11)
Abstract: BACKGROUND: Intrauterine metal exposures and aberrations in placental processes are known contributors to being born small for gestational age (SGA). However, studies to date have largely focused on independent effects, failing to account for potential interdependence among these markers. OBJECTIVES: We evaluated the inter-relationship between multi-metal indices and placental gene network modules related to SGA status to highlight potential molecular pathways through which in utero multi-metal exposure impacts fetal growth. METHODS: Weighted quantile sum (WQS) regression was performed using a panel of 16 trace metals measured in post-partum maternal toe nails collected from the Rhode Island Child Health Study (RICHS, n = 195), and confirmation of the derived SGA-related multi-metal index was conducted using Bayesian kernel machine regression (BKMR). We leveraged existing placental weighted gene coexpression network data to examine associations between the SGA multi-metal index and placental gene expression. Expression of select genes were assessed using RT-PCR in an independent birth cohort, the New Hampshire Birth Cohort Study (NHBCS, n = 237). RESULTS: We identified a multi-metal index, predominated by arsenic (As) and cadmium (Cd), that was positively associated with SGA status (Odds ratio = 2.73 [1.04, 7.18]). This index was also associated with the expression of placental gene modules involved in "gene expression" (β = -0.02 [-0.04, -0.01]) and "metabolic hormone secretion" (β = 0.02 [0.00, 0.05]). We validated the association between cadmium exposure and the expression of GRHL1 and INHBA, genes in the "metabolic hormone secretion" module, in NHBCS. CONCLUSION: We present a novel approach that integrates the application of advanced bioinformatics and biostatistics methods to delineate potential placental pathways through which trace metal exposures impact fetal growth.
PubMed ID: 30125854
MeSH Terms: Adult; Bayes Theorem; Birth Weight; Cohort Studies; Environmental Pollutants/analysis*; Female; Fetal Development*; Gene Expression Regulation, Developmental; Gene Regulatory Networks*; Humans; Infant, Newborn; Infant, Small for Gestational Age*; Inhibin-beta Subunits/genetics; Male; Maternal Exposure; Maternal-Fetal Exchange; Metals/analysis*; Nails/chemistry; Placenta/metabolism*; Pregnancy; Repressor Proteins/genetics