Performance of urine, blood, and integrated metal biomarkers in relation to birth outcomes in a mixture setting.


Journal

Environmental research
ISSN: 1096-0953
Titre abrégé: Environ Res
Pays: Netherlands
ID NLM: 0147621

Informations de publication

Date de publication:
09 2021
Historique:
received: 08 03 2021
revised: 07 05 2021
accepted: 27 05 2021
pubmed: 8 6 2021
medline: 7 9 2021
entrez: 7 6 2021
Statut: ppublish

Résumé

Studies on the health effects of metal mixtures typically utilize biomarkers measured in a single biological medium, such as blood or urine. However, the ability to evaluate mixture effects are limited by the uncertainty whether a unified medium can fully capture exposure for each metal. Therefore, it is important to compare and assess metal mixtures measured in different media in epidemiology studies. The aim of this study was to examine the mixture predictive performance of urine and blood metal biomarkers and integrated multi-media biomarkers in association with birth outcomes. In our analysis of 847 women from the Puerto Rico PROTECT Cohort, we measured 10 essential and non-essential metals in repeated and paired samples of urine and blood during pregnancy. For each metal, we integrated exposure estimates from paired urine and blood biomarkers into multi-media biomarkers (MMBs), using intraclass-correlation coefficient (ICC) and weighted quantile sum (WQS) approaches. Using Ridge regressions, four separate Environmental risk scores (ERSs) for metals in urine, blood, MMB Pb was the most important contributor of blood ERS as well as the two integrated multi-media biomarker ERSs. Individuals with high ERS (3rd tertile) showed increased odds of preterm birth compared to individuals with low ERS (1st tertile), with 2.8-fold (95% CI, 1.49 to 5.40) for urine (specific gravity corrected); 3.2- fold (95% CI, 1.68 to 6.25) for blood; 3.9-fold (95% CI, 1.72 to 8.66) for multi-media biomarkers composed using ICC; and 5.2-fold (95% CI, 2.34 to 11.42) for multi-media biomarkers composed using WQS. The four ERSs had comparable predictive performances (AUC ranging from 0.64 to 0.68) when urine is examined with specific gravity corrected concentrations. Within a practical metal panel, measuring metals in either urine or blood may be an equally good approach to evaluate the metals as a mixture. Applications in practical study design require validation of these methods with other cohorts, larger panels of metals and within the context of other adverse health effects of interest.

Sections du résumé

BACKGROUND
Studies on the health effects of metal mixtures typically utilize biomarkers measured in a single biological medium, such as blood or urine. However, the ability to evaluate mixture effects are limited by the uncertainty whether a unified medium can fully capture exposure for each metal. Therefore, it is important to compare and assess metal mixtures measured in different media in epidemiology studies.
OBJECTIVES
The aim of this study was to examine the mixture predictive performance of urine and blood metal biomarkers and integrated multi-media biomarkers in association with birth outcomes.
METHODS
In our analysis of 847 women from the Puerto Rico PROTECT Cohort, we measured 10 essential and non-essential metals in repeated and paired samples of urine and blood during pregnancy. For each metal, we integrated exposure estimates from paired urine and blood biomarkers into multi-media biomarkers (MMBs), using intraclass-correlation coefficient (ICC) and weighted quantile sum (WQS) approaches. Using Ridge regressions, four separate Environmental risk scores (ERSs) for metals in urine, blood, MMB
RESULTS
Pb was the most important contributor of blood ERS as well as the two integrated multi-media biomarker ERSs. Individuals with high ERS (3rd tertile) showed increased odds of preterm birth compared to individuals with low ERS (1st tertile), with 2.8-fold (95% CI, 1.49 to 5.40) for urine (specific gravity corrected); 3.2- fold (95% CI, 1.68 to 6.25) for blood; 3.9-fold (95% CI, 1.72 to 8.66) for multi-media biomarkers composed using ICC; and 5.2-fold (95% CI, 2.34 to 11.42) for multi-media biomarkers composed using WQS. The four ERSs had comparable predictive performances (AUC ranging from 0.64 to 0.68) when urine is examined with specific gravity corrected concentrations.
CONCLUSIONS
Within a practical metal panel, measuring metals in either urine or blood may be an equally good approach to evaluate the metals as a mixture. Applications in practical study design require validation of these methods with other cohorts, larger panels of metals and within the context of other adverse health effects of interest.

Identifiants

pubmed: 34097892
pii: S0013-9351(21)00729-5
doi: 10.1016/j.envres.2021.111435
pmc: PMC8403638
mid: NIHMS1713802
pii:
doi:

Substances chimiques

Biomarkers 0
Metals 0

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

111435

Subventions

Organisme : NIMHD NIH HHS
ID : U54 MD007600
Pays : United States
Organisme : NIEHS NIH HHS
ID : R01 ES031591
Pays : United States
Organisme : NIEHS NIH HHS
ID : P30 ES017885
Pays : United States
Organisme : NIH HHS
ID : UH3 OD023251
Pays : United States
Organisme : NIEHS NIH HHS
ID : R01 ES032203
Pays : United States
Organisme : NIEHS NIH HHS
ID : P42 ES017198
Pays : United States
Organisme : NIEHS NIH HHS
ID : P50 ES026049
Pays : United States

Informations de copyright

Copyright © 2021 Elsevier Inc. All rights reserved.

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Auteurs

Pahriya Ashrap (P)

University of Michigan School of Public Health, Department of Environmental Health Sciences, Ann Arbor, MI, United States.

Deborah J Watkins (DJ)

University of Michigan School of Public Health, Department of Environmental Health Sciences, Ann Arbor, MI, United States.

Bhramar Mukherjee (B)

University of Michigan School of Public Health, Department of Biostatistics, Ann Arbor, MI, United States.

Zaira Rosario-Pabón (Z)

University of Puerto Rico Graduate School of Public Health, UPR Medical Sciences Campus, San Juan, PR, USA.

Carmen M Vélez-Vega (CM)

University of Puerto Rico Graduate School of Public Health, UPR Medical Sciences Campus, San Juan, PR, USA.

Akram Alshawabkeh (A)

College of Engineering, Northeastern University, Boston, MA, United States.

José F Cordero (JF)

Department of Epidemiology and Biostatistics, University of Georgia, Athens, Georgia, United States.

John D Meeker (JD)

University of Michigan School of Public Health, Department of Environmental Health Sciences, Ann Arbor, MI, United States. Electronic address: meekerj@umich.edu.

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