Urinary trace metals individually and in mixtures in association with preterm birth

Abstract

One in ten infants born in the United States is born preterm, or prior to 37 weeks gestation. Exposure to elevated levels of metals, such as lead and arsenic, has been linked to higher risk of preterm birth (PTB), but consequences of lower levels of exposure and less studied metals are unclear. We examined the associations between 17 urinary trace metals individually and in mixtures in relation to PTB. The LIFECODES birth cohort enrolled pregnant women at <15 weeks gestation at Brigham and Women’s Hospital in Boston. We selected cases of PTB (n=99) and unmatched controls (n=291) and analyzed urine samples for a panel of trace metals (median: 26 weeks gestation). We used logistic regression models to calculate the odds ratio (OR) for PTB and subtypes of PTB based on presentation at delivery. Subtypes included spontaneous and placental PTB. We used elastic net (ENET) regularization to identify individual metals or pairwise interactions that had the strongest associations with PTB, and principal components analysis (PCA) to identify classes of exposures associated with the outcome. We observed increased odds of PTB (OR: 1.41, 95% Confidence Interval [CI]: 1.12, 1.78) in association with an interquartile range difference in urinary copper (Cu). We also observed an increased OR for selenium (OR: 1.33, 95% CI:0.98, 1.81). ENET selected Cu as the most important trace metal associated with PTB. PCA identified 3 principal components (PCs) that roughly reflected exposure to toxic metals, essential metals, and metals with seafood as a common source of exposure. PCs reflecting essential metals were associated with an increased odds of overall and spontaneous PTB. Maternal urinary copper in the third trimester was associated with increased risk of PTB, and statistical analyses for mixtures indicated that after accounting for correlation this metal was the most important statistical predictor of the outcome.

Prenatal exposure to consumer product chemical mixtures and size for gestational age at delivery

“…The limit of detection (LOD) and proportion of samples below the LOD for each exposure biomarker are included in Additional File 1 : Supplemental Table 1. For biomarker concentrations that were below the limit of detection, machine-read values were used in this analysis [ 44 ]. When reported values were less than zero or blank, the value was imputed as LOD/√2 [ 45 ].…”

Maternal Urinary Metal and Metalloid Concentrations in Association with Oxidative Stress Biomarkers

“…Two different mechanisms have been proposed to explain Cu-induced oxidative damage in the human body: (1) free Cu can catalyze the formation of hydroxyl radicals—powerful reactive oxygen species (ROS) that can damage cellular DNA, membranes and proteins [ 42 , 83 , 84 ]; and (2) increased levels of Cu may suppress the availability of glutathione, a highly abundant cellular antioxidant [ 85 ]. Cu was also associated with higher odds of preterm birth in the Puerto Rican population in our study [ 38 ] and in a pregnant women cohort in Boston [ 48 ], and it is possible that Cu impacted the early parturition through pathways including oxidative damage.…”

“…Analysis was performed at NSF International (Ann Arbor, MI, USA), where concentrations of 21 metals and metalloids were measured: Arsenic (As), barium (Ba), beryllium (Be), cadmium (Cd), cobalt (Co), chromium (Cr), cesium (Cs), copper (Cu), mercury (Hg), manganese (Mn), molybdenum (Mo), nickel (Ni), lead (Pb), platinum (Pt), Sb, tin (Sn), titanium (Ti), tungsten (W), uranium (U), vanadium (V), and zinc (Zn). Metal(loid) concentrations were measured using inductively-coupled plasma mass spectrometry (ICPMS) as described previously [ 48 ]. Considering that biological samples have high levels of carbon and chloride in the matrix, the laboratory selected the appropriate isotopes for the requested elements to best avoid interferences where possible.…”

“…We used linear mixed models (LMM) with a random intercept for subject ID to model each prostanoid measure as the dependent variable, with separate models for each exposure biomarker. The crude models included the metal concentration as the exposure and specific gravity as a covariate to adjust for urinary dilution [ 48 , 59 , 60 ]. The final set of covariates were selected based on a priori knowledge and if their inclusion appreciably changed the effect estimates of metal exposure.…”

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“…Pregnant women are in a critically important state for susceptibility to metal effects because of hemodynamics, hormone changes, and immature immune systems (7), and metals could further affect fetal growth after passing through the placental barrier (8). Studies have found that prenatal exposure to certain ranges of manganese (Mn) (9), copper (Cu) (10), lead (Pb) (11), zinc (Zn) (12), and magnesium (Mg) (13) is linked to adverse birth outcomes, including small-forgestational-age (SGA) births, low birth weight, and preterm delivery. Similarly, low-level prenatal Pb exposure, as well as elevated Mn and Zn levels, might increase the risk of preterm birth and SGA (14).…”