Maya A Deyssenroth1, Chris Gennings1, Shelley H Liu2, Shouneng Peng3, Ke Hao3, Luca Lambertini4, Brian P Jackson5, Margaret R Karagas6, Carmen J Marsit7, Jia Chen8. 1. Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA. 2. Center for Biostatistics, Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY 20019, USA. 3. Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA. 4. Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Obstetrics, Gynecology and Reproductive Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA. 5. Department of Earth Sciences, Dartmouth College, Hanover, NH 03755, USA. 6. Department of Epidemiology, Geisel School of Medicine at Dartmouth, USA. 7. Department of Environmental Health, Emory University, Atlanta, GA 30322, USA. 8. Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Medicine, Hematology and Medical Oncology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA. Electronic address: jia.chen@mssm.edu.
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.
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.
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