Inflammatory Marker Levels in Children with Tobacco Smoke Exposure.

Mahabee-Gittens EM, Matt GE, Mazzella M, Doucette JT, Ratnani P, Merianos AL.Cytokine.Vol 173. Jan 2024

Urinary fluoride levels and metal co-exposures among pregnant women in Los Angeles, California.

Malin AJ, Hu H, Martínez-Mier EA, Eckel SP, Farzan SF, Howe CG, Funk W, Meeker JD, Habre R, Bastain TM, Environ Health. 2023 Oct 26;22(1):74.

Exposures to Organophosphate Esters and Respiratory Morbidity among School-Aged Children with Asthma.

Louis L, Buckley J, Kuiper J, Meeker J, Hansel N, McCormack M, Diette G, Quirós-Alcalá L. Environ Sci Technol.
2023 Apr 25;57(16):6435-6443.

Tobacco smoke exposure, the lower airways microbiome and outcomes of ventilated children.

Leroue M, Williamson K, Curtin P, Sontag M, Wagner B, Ambroggio L, Bixby M, Busgang S, Murphy S,Peterson L, Vevang K, Sipe C, Harris K, Reeder R, Locandro C, Carpenter T, Maddux A, Simões E, Osborne C, Robertson C, Langelier C, Carcillo J, Meert K, Pollack M, McQuillen P, Mourani P. Pediatr Res. 2023 Feb 7;1-8.

Early childhood exposure to environmental phenols and parabens, phthalates, organophosphate pesticides, and trace elements in association with attention deficit hyperactivity disorder (ADHD) symptoms in the CHARGE study.

Oh J, Kim K, Kannan K, Parsons P, Mlodnicka A, Schmidt R, Schweitzer J, Hertz-Picciotto I, Bennett D. Res Sq. 2023 Feb 10.

Concentrations of Per- and Polyfluoroalkyl Substances in Paired Maternal Plasma and Human Milk in the New Hampshire Birth Cohort .

Criswell R, Wang Y, Christensen B, Botelho, Calafat A, Peterson L, Huset C, Karagas M, Romano M. Environ Sci Technol. 2023 Jan 10; 57(1): 463–472.

Early pregnancy essential and non-essential metal mixtures and maternal antepartum and postpartum depressive symptoms.

Rokoff LB, Cardenas A, Lin PD, Rifas-Shiman SL, Wright RO, Bosquet Enlow M, Coull BA, Oken E, Korrick SA.Neurotoxicology. 2023 Jan;94:206-216.

Childhood exposure to per- and polyfluoroalkyl substances and neurodevelopment in the CHARGE case-control study

Oh J, Shin H, Kannan K, Busgang S, Schmidt R, Schweitzer J, Hertz-Picciotto I, Bennett D, Environ Res. 2022 Dec;215(Pt 2):114322.

Variability in urinary phthalates, phenols, and parabens across childhood and relation to adolescent breast composition in Chilean girls

Yoon L, Binder A, Pereira A , Calafat A, Shepherd J, Corvalán C , Michels K. Environ Int . 2022 Oct 19, 170:107586.

Maternal Serum and Placental Metabolomes in Association with Prenatal Phthalate Exposure and Neurodevelopmental Outcomes in the MARBLES Cohort

Parenti M, Schmidt R , Ozonoff S, Shin H, Tancredi D, Krakowiak P, Hertz-Picciotto I , Walker C, Slupsky C ,  Metabolites . 2022 Sep 2;12(9):829.

Phthalate biomarkers and associations with respiratory symptoms and healthcare utilization among low-income urban children with asthma.

Fandino-Del-Rio M, Matsui E, Peng R, Meeker J, Quiros-Alcala L.Environ Res. 2022 Sep;212(Pt B):113239.

Cross-Sectional Study of Urinary Biomarkers of Environmental Tobacco and E-Cigarette Exposure and Asthma Morbidity.

Ruran H, Maciag M, Murphy S, Phipatankul W, Hauptman M. Ann Allergy Asthma Immunol. 2022 Jun 7;S1081-1206(22)00499-9.

Prenatal Exposures to Common Phthalates and Prevalent Phthalate Alternatives and Infant DNA Methylation at Birth.

Petroff R, Padmanabhan V, Dolinoy D, Watkins D, Ciarelli J, Haggerty D, Ruden D, Goodrich J, Front Genet 2022 Mar 31;13:793278.

Assessing tobacco smoke exposure in pregnancy from self-report, urinary cotinine and NNAL: a validation study using the New Hampshire Birth Cohort Study

Peacock J, Palys T, Halchenko Y, Sayarath V,Takigawa C, Murphy S, Peterson L, Baker E, Karagas M. BMJ Open. 2022 Feb 7;12(2)

Environmental exposures to pesticides, phthalates, phenols and trace elements are associated with neurodevelopment in the CHARGE study.

Bennett D , Busgang S, Kannan K, Parsons P, Takazawa M, Palmer C, Schmidt R , Doucette J , Schweitzer J , Gennings C, Hertz-Picciotto I. Environ Int. 2022 Jan 24;161:107075.

Randomized trial of a portable HEPA air cleaner intervention to reduce asthma morbidity among Latino children in an agricultural community.

Dreiling R, Sampson P, Krenz J, French M, Jansen K, Massey A, Farquhar S , Min E, Perez A, Riederer A, Torres E, Younglove L, Aisenberg E, Andra S, Kim-Schulze S, Karr C. Environ Health. 2022 Jan 3;21(1):1.

Variability of Urinary Concentrations of Phenols, Parabens, and Triclocarban during Pregnancy in First Morning Voids and Pooled Samples.

Shin H, Oh J, Kim K, Busgang S, Barr D, Panuwet P, Schmidt R, Hertz-Picciotto I, Bennett D.Environ Sci Technol. 2021 Dec 7;55(23):16001-16010.

The Association Between Breast Density and Gut Microbiota Composition at 2 Years Post-Menarche: A Cross-Sectional Study of Adolescents in Santiago, Chile.

Yoon L, Jacobs J, Hoehner J, Periera A , Gana J, Corvalan C, Michels K. Front Cell Infect Microbiol. 2021 Dec 17;11:794610.

Early pregnancy exposure to metal mixture and birth outcomes - A prospective study in Project Viva.

Rahman ML, Oken E, Hivert MF, Rifas-Shiman S, Lin PD, Colicino E, Wright RO, Amarasiriwardena C, Claus Henn BG, Gold DR, Coull BA, Cardenas A. Environ Int. 2021 Jun 17;156:106714. doi: 10.1016/j.envint.2021.106714. Online ahead of print.

Prospective Associations of Early Pregnancy Metal Mixtures with Mitochondria DNA Copy Number and Telomere Length in Maternal and Cord Blood.

Smith A, Lin P, Rifas- Shiman S, Rahman M, Gold D, Baccarelli A, Henn B, Amarasiriwardena C, Wright R, Colu B, Hivert M,Oken E,Cardenas A. Environ Health Perspect. 2021 Nov;129(11):117007.

Urinary metals and maternal circulating extracellular vesicle microRNA in the MADRES pregnancy cohort.

Howe C, Foley H, Farzan S, Chavez T, Johnson M, Meeker J, Bastain T, Marsit C, Breton C. Epigenetics.2021 Oct 30;1-15.

Maternal Plasma Metabolic Profile Demarcates a Role for Neuroinflammation in Non-Typical Development of Children.

Schmidt RJ, Liang D, Busgang SA, Curtin P, Giulivi C. Metabolites. 2021 Aug 18;11(8):545.

Temporal Trends of Phenol, Paraben, and Triclocarban Exposure in California Pregnant Women during 2007-2014.

Shin H, Oh J, Kim K, Busgang S, Barr D, Panuwet P, Schmidt R, Hertz-Picciotto I, Bennett D.Environ Sci Technol. 2021 Aug 17;55(16):11155-11165.

Diet and erythrocyte metal concentrations in early pregnancy-cross-sectional analysis in Project Viva.

Lin P, Cardenas A, Rifas- Shiman S, Hivert M, James-Todd T, Amarasiriwardena C, Wright R, Rahman M, Oken E., Am J Clin Nutr. 2021 Aug 2;114(2):540-549.

DNA methylation at birth potentially mediates the association between prenatal lead (Pb) exposure and infant neurodevelopmental outcomes.

Rygiel C, Dolinoy D, Bakulski K, Aung M, Perng W,Jones T, Solano-Gonzalez M, Hu H, Tellez-Rojo M, Schnaas L, Marcela E, Peterson K, Goodrich J, Environ Epigenet. 2021 Jun 16;7(1).

Prenatal Metal Mixtures and Fetal Size in Mid-Pregnancy in the MADRES Study.

Caitlin G Howe , Birgit Claus Henn , Shohreh F Farzan , Rima Habre , Sandrah P Eckel , Brendan H Grubbs, Thomas A Chavez, Dema Faham , Laila Al-Marayati, Deborah Lerner , Alyssa Quimby , Sara Twogood , Michael J Richards , John D Meeker , Theresa M Bastain , Carrie V Breton. Environ Research Oct 28, 2020.

Comparison of Liquid Chromatography Mass Spectrometry and Enzyme-Linked Immunosorbent Assay Methods to Measure Salivary Cotinine Levels in Ill Children.

Mahabee-Gittens EM, Mazzella MJ, Doucette JT, Merianos AL, Stone L, Wullenweber CA, A Busgang S, Matt GE. Int J Environ Res Public Health. 2020 Feb 12;17(4).

Prenatal metal mixtures and birth weight for gestational age in a predominately lower income Hispanic pregnancy cohort in Los Angeles.

MJ, Meeker JD, Bastain TM, Breton CV. Environ Health Perspect. 2020 Nov;128(11).

A Parental Smoking Cessation Intervention in the Pediatric Emergency Setting: A Randomized Trial.

Mahabee-Gittens M, Ammerman R, Khoury J, Tabangin M, Ding L, Merianos A , Stone L, Gordon J, 2020 Nov 4;17(21):8151.

Dysregulated lipid and fatty acid metabolism link perfluoroalkyl substances exposure and impaired glucose metabolism in young adults.

Chen Z, Yang T, Walker DI, Thomas DC, Qiu C, Chatzi L, Alderete TL, Kim JS, Conti DV, Breton CV, Liang D, Hauser ER, Jones DP, Gilliland FD. Environ Int. 2020 Sep 3;145.

Prospective Association Between Manganese in Early Pregnancy and the Risk of Preeclampsia.

Liu T , Hivert , M, Rifas-Shiman S, Rahman M ,Oken E , Andres Cardenas A , Mueller N. Epidemiology. 2020 Sep;31(5):677-680.

Trimester-Specific Associations of Prenatal Lead Exposure With Infant Cord Blood DNA Methylation at Birth.

Rygiel C, Dolinoy D, Perng W, Jones T, Solano M, Hu H, Téllez-Rojo M, Peterson K Goodrich J.
Epigenetic Insights. Jul 2020. Vol 13. 1-11.

Quantitative methods for metabolomic analyses evaluated in the Children's Health Exposure Analysis Resource (CHEAR).

CHEAR Metabolomics Analysis Team, Mazzella M, Sumner SJ, Gao S, Su L, Diao N, Mostofa G, Qamruzzaman Q, Pathmasiri W, Christiani DC, Fennell T, Gennings C. J Expo Sci Environ Epidemiol. 2020 Jan;30(1):16-27.

Prenatal phenol and paraben exposures in relation to child neurodevelopment including autism spectrum disorders in the MARBLES study.

Barkoski JM, Busgang SA, Bixby M, Bennett D, Schmidt RJ, Barr DB, Panuwet P, Gennings C, Hertz-Picciotto
Environ Research. 2019 Dec;179(Pt A):108719.

Epidemiologic Advances Generated by the Human Health Exposure Analysis Resource Program.

Mervish N, Valle C, Teitelbaum S. Current Epidemiology Reports. Sept 2023. Volume 10, pages 148–157.

Machine Learning Assisted Discovery of Interactions between Pesticides, Phthalates, Phenols, and Trace Elements in Child Neurodevelopment.

Eggers S, Midya V, Bixby M, Gennings C, Torres-Olascoaga LA, Walker RW, Wright RO, Arora M, Téllez-Rojo MM. Environ Sci Technol. 2023 Aug 18. doi: 10.1021/acs.est.3c00848.

Machine Learning Assisted Discovery of Interactions between Pesticides, Phthalates, Phenols, and Trace Elements in Child Neurodevelopment.

Midya V, Alcala CS, Rechtman E, Gregory JK, Kannan K, Hertz-Picciotto I, Teitelbaum SL, Gennings C, Rosa MJ, Valvi D. Environ Sci Technol. 2023 Aug 18;57(46):18139–50.

A cross-validation based approach for estimating specific gravity in elementary-school aged children using a nonlinear model.

Busgang S, Andra SS, Curtin P, Colicino E, Mazzella M, Bixby M, Sanders A,Meeker J, Hauptman M,Yelamanchili S, Phipatanakul W, Meeker J, Gennings C. Environ Res.Vol 217, 15 Jan 2023

Biomarkers of maternal lead exposure during pregnancy using micro-spatial child deciduous dentine measurements.

Gerbi L, Austin C, Pedretti NF, McRae N, Amarasiriwardena CJ, Mercado-García A, Torres-Olascoaga LA, Tellez-Rojo MM, Wright RO, Arora M, Elena C. Environ Int. 2022 Sep 16;169:107529.

A Machine Learning Based Approach for Estimating Specific Gravity in Elementary-School Aged Children.

Busgang S, Andra SS, Curtin P, Colicino E, Mazzella M, Bixby M, Sanders A, Hauptman M,Yelamanchili S, Phipatanakul W, Meeker J, Gennings C.

IDSL.IPA Characterizes the Organic Chemical Space in Untargeted LC/HRMS Data Sets.

Fakouri-Baygi S, Kumar Y, Barupal D. J Proteome Res. 2022 Jun 3;21(6):1485-1494.

CCDB: A database for exploring inter-chemical correlations in metabolomics and exposomics datasets.

Barupal D, Mahajan P, Fakouri-Baygi S, Wright R, Arora M, Teitelbaum S. Environ Int. 2022 Jun;164:107240.

Selecting External Controls for Internal Cases Using Stratification Score Matching Methods.

Busgang S, Waller L, Colicino E, D'Agostino R, Hertz-Picciotto I Gennings C. Int. J. Environ. Res. Public Health Feb. 2022, 19(5), 2549.

Non-linear and non-additive associations between the pregnancy exposome and birthweight.

Colicino E, Ferrari F, Cowell W, Niedzwiecki MM, Pedretti NF, Joshi A, Wright RO, Wright RJ. Environ Int. 2021 Nov. 156:106750.

A method for the analysis of 121 multi-class environmental chemicals in urine by high-performance liquid chromatography-tandem mass spectrometry.

Zhu H, Chinthakindi S, Kannan K. J Chromatogr A. 2021 Jun 7;1646:462146.

Human Health Exposure Analysis Resource (HHEAR): A model for incorporating the exposome into health studies.

Viet S,  Falman J, Merrill L , Faustman E,  Savitz D , Mervish N ,  Barr D,  Peterson L,Wright R ,  Balshaw B,  O'Brien B.Int J Hyg Environ Health. 2021 Jun;235:113768.

Quality assurance and harmonization for targeted biomonitoring measurements of environmental organic chemicals across the Children's Health Exposure Analysis Resource laboratory network.

Kannan K, Stathis A, Mazzella MJ, Andra SS, Barr DB, Hecht SS, Merrill LS, Galusha AL, Parsons PJ. Int J Hyg Environ Health. 2021 May;234:113741.

Evaluating inter-study variability in phthalate and trace element analyses within the Children's Health Exposure Analysis Resource (CHEAR) using multivariate control charts.

Mazzella MJ, Barr DB, Kannan K, Amarasiriwardena C, Andra SS, Gennings C. J Expo Sci Environ Epidemiol. 2021 Mar;31(2):318-327.

The Semantic Data Dictionary - An Approach for Describing and Annotating Data.

Rashid S, McCusker J, Pinheiro P, Bax M, Santos H, Das A, Stingone J, McGuinness D. The Semantic Data Dictionary - An Approach for Describing and Annotating Data.Data Intell. Fall 2020;2(4):443-486.

Lagged WQS regression for mixtures with many components.

Gennings C, Curtin P, Bello G, Wright R, Aurora M, Austin C. Environ Res. 2020 Jul;186:109529.

Environmental mixtures and children's health: identifying appropriate statistical approaches.

Tanner E, Lee A, Colicino E. Curr Opin Pediatr. 2020 Apr;32(2):315-320.

Per- and poly-fluoroalkyl substances and bone mineral density: Results from the Bayesian weighted quantile sum regression.

Colicino E, Pedretti N, Busgang S, Gennings C. Environ Epidemiol. 2020.Apr 30;4(3).

Toward Greater Implementation of the Exposome Research Paradigm within Environmental Epidemiology.

Stingone JA, Buck Louis GM, Nakayama SF, Vermeulen RC, Kwok RK, Cui Y, Balshaw DM, Teitelbaum SL. Annu Rev Public Health. 2017 Mar 20;38:315-327. Review.

Quality of Prenatal and Childhood Diet Predicts Neurodevelopmental Outcomes among Children in Mexico City.

Malin AJ, Busgang SA, Cantoral AJ, Svensson K, Orjuela MA, Pantic I, Schnaas L, Oken E, Baccarelli AA, Téllez-Rojo MM, Wright RO, Gennings C. Nutrients. 2018 Aug 15;10(8).

Lagged kernel machine regression for identifying time windows of susceptibility to exposures of complex mixtures.

Liu SH, Bobb JF, Lee KH, Gennings C, Claus Henn B, Bellinger D Austin C, Schnaas L, Tellez-Rojo MM, Hu H, Wright RO, Arora M, Coull BA. Biostatistics, 2018 Jul 1;19(3):325-341.

Recurrence quantification analysis to characterize cyclical components of environmental elemental exposures during fetal and postnatal development.

Curtin, P, Curtin, A, Austin, C., Gennings, C, Arora, M PLOS ONE. (2017)

Prenatal exposure to PM2.5 and birth weight: A pooled analysis from three North American longitudinal pregnancy cohort studies.

Rosa, MJ, Pajak, A, Just, AC, Sheffield, PE, Kloog, I, Schwartz, J , Coull, B, Enlow, MB , Baccarelli, AA, Huddleston, K, Niederhuber, JE, Téllez-Rojo, MM, Wright, RO, Gennings, C, Wright, RJ Environmental International. (2017) 107:173-180.

Extending the distributed lag model framework to handle chemical mixtures.

Bello GA, Arora M, Austin C, Horton MK, Wright RO, Gennings C. Environmental Research; 2017 156:253-264.

Big and disparate data: considerations for pediatric consortia.

Stingone JA, Mervish N, Kovatch P, McGuinness DL, Gennings C, Teitelbaum SL.
Curr Opin Pediatr. 2017 Apr;29(2):231-239. Review.

Software Packages

R Package ‘gWQS’

Description: Fits Weighted Quantile Sum (WQS) regressions for continuous or binomial outcomes.
Usage: gwqs(formula, mix_name, data, q = 4, validation = 0.6, valid_var = NULL, b = 100, b1_pos = TRUE, family = "gaussian", seed = NULL, wqs2 = FALSE, plots = FALSE, tables = FALSE)


HHEAR SID-PID Mapping Tutorial

This tutorial provides instructions for a HHEAR approved investigator on how to map the HHEAR participants’ IDs (PIDs) to the sample specimen IDs (SIDs) in order to create a file that links the participant to their corresponding samples. This list will be used to create a manifest for shipping the samples to the HHEAR lab(s).

A workshop on the HHEAR ontology and harmonized dataset

Maximizing reuse of existing environmental health data: Introducing the HHEAR Data Repository. A workshop to present the updated HHEAR ontology and harmonized dataset to the wider research community. Jeanette Stingone. ISEE Webinar Series. Dec. 1, 2020

Metabolomics Tutorial

Metabolomics involves the identification and measurement of small-molecule metabolites of endogenous and exogenous origin in a biospecimen. These metabolites represent a diverse group of low-molecular-weight structures, such as lipids, amino acids, peptides, nucleic acids, organic acids, vitamins, thiols, carbohydrates, environmental chemicals, and dietary compounds. Different approaches and analytical platforms are used to detect, characterize, and quantify metabolites and related metabolic pathways, including untargeted and targeted liquid chromatography-mass spectrometry (LC-MS), gas chromatography-MS (GC-MS), and nuclear magnetic resonance (NMR). In CHEAR, most metabolomics studies use a LC-MS platform to perform untargeted metabolomics. Therefore, the purpose of the tutorial is to provide a basic overview for non-experts of how LC-MS-based untargeted metabolomics datasets are generated, which should aid in data analysis and interpretation.

HHEAR Data Submission and Review Portal - User Manual for HHEAR PI

This User Manual outlines the Major Functions and Processes supported by the HHEAR Data Submission and Review Portal, and how to use them. This manual is intended for use by Primary Investigators (i.e., “PIs”) and their Co-Investigators. These users will be accessing the portal to upload their study results data, generate HHEAR Participant IDs (PIDs) and Specimen IDs (SIDs), map HHEAR SIDs to PIDs, retrieving lab result data, and other related activities.

HHEAR Data Submission and Review Portal - User Manual for HHEAR LH

This User Manual outlines the Laboratory Data Upload Processes supported by the HHEAR Data Submission and Review Portal. This manual is solely intended for use by HHEAR Lab Hub members.

HHEAR Targeted Data Template for LHs

File Hash Checker

If you are not sure how to verify the SHA-512 hash of the file that you downloaded or uploaded, you can use this in-browser file hasher. This will calculate the hash without uploading.


The Data Center is responsible for creating and maintaining the HHEAR Ontology—a common vocabulary for use in the HHEAR program. The Ontology is evolving with the program and will connect to best-in-class existing vocabularies, thus facilitating the integration of data from multiple studies.

Services include:

  • Facilitating the mapping of variables from data dictionaries into terms consistent with the HHEAR Ontology

  • Incorporating the study's data into the HHEAR Ontology to support collaborative research across the HHEAR consortium, including pooled analyses from health research studies participating in CHEAR and HHEAR

  • Developing methods and services for comparing similar variables from different data dictionaries, starting with very basic mappings of equivalent terms and moving into more sophisticated analyses of relationships among variables

  • Providing tools and services to manage the HHEAR Ontology evolution


QC Pool Authorization

As a supplement to the rigorous Quality Assurance and Quality Control (QA/QC) program within HHEAR, which ensures the integrity of the individual analyte assessments and equivalence/combinability across Lab Hubs [Kannan et al., 2021], the HHEAR Data Center provides direct access to the QC pool data from program-related lab assessments. This data can be used to help determine combinability across studies and Lab Hubs using multivariate control charts [Mazzella et al., 2021] or by assessing across-study distributions and RSD. These data can be linked to the lab result data from the HHEAR project using unique Batch IDs.

In order to access the study level search:

For those with existing accounts, log in to HHEAR Data Center, then select Study level Search.

If you do not have an account, please click on this link to register .