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Xie Y, Fang X, Wang A, Xu S, Li Y, Xia W. Association of cord plasma metabolites with birth weight: results from metabolomic and lipidomic studies of discovery and validation cohorts. ULTRASOUND IN OBSTETRICS & GYNECOLOGY : THE OFFICIAL JOURNAL OF THE INTERNATIONAL SOCIETY OF ULTRASOUND IN OBSTETRICS AND GYNECOLOGY 2024. [PMID: 38243991 DOI: 10.1002/uog.27591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Revised: 11/29/2023] [Accepted: 01/15/2024] [Indexed: 01/22/2024]
Abstract
OBJECTIVE Birth weight is a good predictor of fetal intrauterine growth and long-term health, and several studies have evaluated the relationship between metabolites and birth weight. The aim of this study was to investigate the association of cord blood metabolomics and lipidomics with birth weight, using a two-stage discovery and validation approach. METHODS Firstly, a pseudotargeted metabolomics approach was applied to detect metabolites in 504 cord blood samples in the discovery set enrolled from the Wuhan Healthy Baby Cohort, China. Metabolome-wide association scan analysis and pathway enrichment were applied to identify metabolites and metabolic pathways that were significantly associated with birth weight adjusted for gestational age Z-score (BW Z-score). Logistic regression models were used to analyze the association of metabolites in the most significantly associated pathways with small-for-gestational age (SGA) at delivery and low birth weight (LBW). Subsequently, 350 cord blood samples in a validation cohort were subjected to targeted analysis to validate the metabolites identified by screening in the discovery cohort. RESULTS In the discovery set, of 2566 metabolites detected, 2418 metabolites were retained for subsequent analysis after data preprocessing. Of these, 513 metabolites were significantly associated with BW Z-score (P-value adjusted for false discovery rate (PFDR) < 0.05), of which 298 Kyoto Encyclopedia of Genes and Genomes (KEGG)-annotated metabolites were included in the pathway analysis. The primary bile acid biosynthesis pathway was the most relevant metabolic pathway associated with BW Z-score. Elevated cord plasma primary bile acids were associated with lower BW Z-score and higher risk of SGA or LBW in the discovery and validation cohorts. In the validation set, a 2-fold increase in taurochenodeoxycholic acid (TCDCA) and in taurocholic acid (TCA) was associated with a decrease in BW Z-score (estimated β coefficient, -0.10 (95% CI, -0.20 to 0.00) and -0.18 (95% CI, -0.31 to -0.04), respectively), after adjusting for covariates. In addition, a 2-fold increase in cord plasma TCDCA and of cord plasma TCA was associated with an increased risk of SGA (adjusted odds ratio (OR), 1.52 (95% CI, 1.00-2.30) and 1.77 (95% CI, 1.05-2.98), respectively). The adjusted OR for LBW, for a 2-fold increase in TCDCA and TCA concentration, were 2.39 (95% CI, 1.00-5.71) and 3.21 (95% CI, 0.96-10.74), respectively. CONCLUSIONS These results indicate a significant association of elevated primary bile acids, particularly TCDCA and TCA, in cord blood with lower BW Z-score, as well as increased risk of SGA and LBW. Abnormalities of primary bile acid metabolism may play an important role in restricted fetal development. © 2024 International Society of Ultrasound in Obstetrics and Gynecology.
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Affiliation(s)
- Y Xie
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, State Key Laboratory of Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - X Fang
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, State Key Laboratory of Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - A Wang
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, State Key Laboratory of Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - S Xu
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, State Key Laboratory of Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- School of Environmental Science and Engineering, Hainan University, Haikou, Hainan, China
| | - Y Li
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, State Key Laboratory of Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - W Xia
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, State Key Laboratory of Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
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Hall AM, Fleury E, Papandonatos GD, Buckley JP, Cecil KM, Chen A, Lanphear BP, Yolton K, Walker DI, Pennell KD, Braun JM, Manz KE. Associations of a Prenatal Serum Per- and Polyfluoroalkyl Substance Mixture with the Cord Serum Metabolome in the HOME Study. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:21627-21636. [PMID: 38091497 DOI: 10.1021/acs.est.3c07515] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/27/2023]
Abstract
Per- and polyfluoroalkyl substances (PFAS) are ubiquitous and persistent chemicals associated with multiple adverse health outcomes; however, the biological pathways affected by these chemicals are unknown. To address this knowledge gap, we used data from 264 mother-infant dyads in the Health Outcomes and Measures of the Environment (HOME) Study and employed quantile-based g-computation to estimate covariate-adjusted associations between a prenatal (∼16 weeks' gestation) serum PFAS mixture [perfluorooctanesulfonic acid (PFOS), perfluorooctanoic acid (PFOA), perfluorohexanesulfonic acid (PFHxS), and perfluorononanoic acid (PFNA)] and 14,402 features measured in cord serum. The PFAS mixture was associated with four features: PFOS, PFHxS, a putatively identified metabolite (3-monoiodo-l-thyronine 4-O-sulfate), and an unidentified feature (590.0020 m/z and 441.4 s retention time; false discovery rate <0.20). Using pathway enrichment analysis coupled with quantile-based g-computation, the PFAS mixture was associated with 49 metabolic pathways, most notably amino acid, carbohydrate, lipid and cofactor and vitamin metabolism, as well as glycan biosynthesis and metabolism (P(Gamma) <0.05). Future studies should assess if these pathways mediate associations of prenatal PFAS exposure with infant or child health outcomes, such as birthweight or vaccine response.
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Affiliation(s)
- Amber M Hall
- Department of Epidemiology, Brown University, Providence, Rhode Island 02912, United States
| | - Elvira Fleury
- Department of Epidemiology, Brown University, Providence, Rhode Island 02912, United States
| | - George D Papandonatos
- Department of Biostatistics, Brown University, Providence, Rhode Island 02912, United States
| | - Jessie P Buckley
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, United States
| | - Kim M Cecil
- Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio 45229, United States
- Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio 45229, United States
| | - Aimin Chen
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
| | - Bruce P Lanphear
- Faculty of Health Sciences, Simon Fraser University, Burnaby, British Columbia V5A 1S6, Canada
| | - Kimberly Yolton
- Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio 45229, United States
| | - Douglas I Walker
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia 30322, United States
| | - Kurt D Pennell
- School of Engineering, Brown University, Providence, Rhode Island 02912, United States
| | - Joseph M Braun
- Department of Epidemiology, Brown University, Providence, Rhode Island 02912, United States
| | - Katherine E Manz
- School of Engineering, Brown University, Providence, Rhode Island 02912, United States
- Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, Michigan 48109, United States
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Midya V, Alcala CS, Rechtman E, Gregory JK, Kannan K, Hertz-Picciotto I, Teitelbaum SL, Gennings C, Rosa MJ, Valvi D. Machine Learning Assisted Discovery of Interactions between Pesticides, Phthalates, Phenols, and Trace Elements in Child Neurodevelopment. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:18139-18150. [PMID: 37595051 PMCID: PMC10666542 DOI: 10.1021/acs.est.3c00848] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 08/10/2023] [Accepted: 08/10/2023] [Indexed: 08/20/2023]
Abstract
A growing body of literature suggests that developmental exposure to individual or mixtures of environmental chemicals (ECs) is associated with autism spectrum disorder (ASD). However, investigating the effect of interactions among these ECs can be challenging. We introduced a combination of the classical exposure-mixture Weighted Quantile Sum (WQS) regression and a machine-learning method termed Signed iterative Random Forest (SiRF) to discover synergistic interactions between ECs that are (1) associated with higher odds of ASD diagnosis, (2) mimic toxicological interactions, and (3) are present only in a subset of the sample whose chemical concentrations are higher than certain thresholds. In a case-control Childhood Autism Risks from Genetics and Environment (CHARGE) study, we evaluated multiordered synergistic interactions among 62 ECs measured in the urine samples of 479 children in association with increased odds for ASD diagnosis (yes vs no). WQS-SiRF identified two synergistic two-ordered interactions between (1) trace-element cadmium (Cd) and the organophosphate pesticide metabolite diethyl-phosphate (DEP); and (2) 2,4,6-trichlorophenol (TCP-246) and DEP. Both interactions were suggestively associated with increased odds of ASD diagnosis in the subset of children with urinary concentrations of Cd, DEP, and TCP-246 above the 75th percentile. This study demonstrates a novel method that combines the inferential power of WQS and the predictive accuracy of machine-learning algorithms to discover potentially biologically relevant chemical-chemical interactions associated with ASD.
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Affiliation(s)
- Vishal Midya
- Department
of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, New York 10029, United States
| | - Cecilia Sara Alcala
- Department
of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, New York 10029, United States
| | - Elza Rechtman
- Department
of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, New York 10029, United States
| | - Jill K. Gregory
- Instructional
Technology Group,Icahn School of Medicine
at Mount Sinai, New York, New York 10029, United States
| | - Kurunthachalam Kannan
- Department
of Pediatrics and Department of Environmental Medicine, New York University School of Medicine, New York, New York 10016, United States
| | - Irva Hertz-Picciotto
- Department
of Public Health Sciences, School of Medicine, University of California at Davis, Davis, California 95616, United States
- UC
Davis MIND (Medical Investigations of Neurodevelopmental Disorders)
Institute, University of California at Davis, Sacramento, California 95817, United States
| | - Susan L. Teitelbaum
- Department
of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, New York 10029, United States
| | - Chris Gennings
- Department
of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, New York 10029, United States
| | - Maria J. Rosa
- Department
of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, New York 10029, United States
| | - Damaskini Valvi
- Department
of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, New York 10029, United States
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Naik VD, Ramadoss J. Untargeted and Targeted Blood Lipidomic Signature Profile of Gestational Alcohol Exposure. Nutrients 2023; 15:1411. [PMID: 36986141 PMCID: PMC10051993 DOI: 10.3390/nu15061411] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Revised: 03/08/2023] [Accepted: 03/13/2023] [Indexed: 03/17/2023] Open
Abstract
Alcohol consumption has a close relationship with blood lipid levels in a nonpregnant state, with a myriad of effects on the liver; however, little is known about the interaction of alcohol and lipids in the context of fetal alcohol spectrum disorders (FASD). We herein aimed to determine the effect of alcohol on the lipid profile in a pregnant rat model, with a focus on FASD. Dry blood spots (50 µL) were obtained from rat maternal blood collected on gestational day (GD) 20, two hours after the last binge alcohol exposure (4.5 g/kg, GD 5-10; 6 g/kg, GD 11-20). The samples were then analyzed using high-throughput untargeted and targeted lipid profiling via liquid chromatography-tandem mass spectrometry (LC-MS/MS). In untargeted lipidomics, 73 of 315 identified lipids were altered in the alcohol group compared to the pair-fed controls; 67 were downregulated and 6 were upregulated. In targeted analysis, 57 of the 260 studied lipid subspecies were altered, including Phosphatidylcholine (PC), Phosphatidylethanolamine (PE), Phosphatidylglycerol (PG), Phosphatidic Acid (PA), Phosphatidylinositol (PI), and Phosphatidylserine (PS); 36 of these were downregulated and 21 lipid subspecies were upregulated. These findings suggest alcohol-induced dysregulation of lipids in the maternal blood of rats and provide novel insights into possible FASD mechanisms.
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Affiliation(s)
- Vishal D. Naik
- Department of Obstetrics & Gynecology, C.S. Mott Center for Human Growth and Development, School of Medicine, Wayne State University, Detroit, MI 48201, USA
| | - Jayanth Ramadoss
- Department of Obstetrics & Gynecology, C.S. Mott Center for Human Growth and Development, School of Medicine, Wayne State University, Detroit, MI 48201, USA
- Department of Physiology, School of Medicine, Wayne State University, Detroit, MI 48201, USA
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Yeum D, Gilbert-Diamond D, Doherty B, Coker M, Stewart D, Kirchner D, McRitchie S, Sumner S, Karagas MR, Hoen AG. Associations of maternal plasma and umbilical cord plasma metabolomics profiles with birth anthropometric measures. Pediatr Res 2023:10.1038/s41390-022-02449-2. [PMID: 36627359 DOI: 10.1038/s41390-022-02449-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 10/11/2022] [Accepted: 12/15/2022] [Indexed: 01/11/2023]
Abstract
BACKGROUND The metabolomics profiles of maternal plasma during pregnancy and cord plasma at birth might influence fetal growth and birth anthropometry. The objective was to examine how maternal plasma and umbilical cord plasma metabolites are associated with newborn anthropometric measures, a known predictor of future health outcomes. METHODS Pregnant women between 24 and 28 weeks of gestation were recruited as part of a prospective cohort study. Blood samples from 413 women at enrollment and 787 infant cord blood samples were analyzed using the Biocrates AbsoluteIDQ® p180 kit. Multivariable linear regression models were used to examine associations of cord and maternal metabolites with infant anthropometry at birth. RESULTS In cord blood samples from this rural cohort from New Hampshire of largely white residents, 13 metabolites showed negative associations, and 10 metabolites showed positive associations with birth weight Z-score. Acylcarnitine C5 showed negative association, and 4 lysophosphatidylcholines showed positive associations with birth length Z-score. Maternal blood metabolites did not significantly correlate with birth weight and length Z-scores. CONCLUSIONS Consistent findings were observed for several acylcarnitines that play a role in utilization of energy sources, and a lysophosphatidylcholine that is part of oxidative stress and inflammatory response pathways in cord plasma samples. IMPACT The metabolomics profiles of maternal plasma during pregnancy and cord plasma at birth may influence fetal growth and birth anthropometry. This study examines the independent effects of maternal gestational and infant cord blood metabolomes across different classes of metabolites on birth anthropometry. Acylcarnitine species were negatively associated and glycerophospholipids species were positively associated with weight and length Z-scores at birth in the cord plasma samples, but not in the maternal plasma samples. This study identifies lipid metabolites in infants that possibly may affect early growth.
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Affiliation(s)
- Dabin Yeum
- Department of Epidemiology, The Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.
| | - Diane Gilbert-Diamond
- Department of Epidemiology, The Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.,Children's Environmental Health and Disease Prevention Center at Dartmouth, Hanover, NH, USA
| | - Brett Doherty
- Department of Epidemiology, The Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
| | - Modupe Coker
- Department of Oral Biology, Rutgers School of Dental Medicine, Rutgers State University of New Jersey, Newark, NJ, USA
| | - Delisha Stewart
- Department of Nutrition, Gillings School of Global Public Health, Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC, USA
| | - David Kirchner
- Department of Nutrition, Gillings School of Global Public Health, Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC, USA
| | - Susan McRitchie
- Department of Nutrition, Gillings School of Global Public Health, Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC, USA
| | - Susan Sumner
- Department of Nutrition, Gillings School of Global Public Health, Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC, USA
| | - Margaret R Karagas
- Department of Epidemiology, The Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.,Children's Environmental Health and Disease Prevention Center at Dartmouth, Hanover, NH, USA
| | - Anne G Hoen
- Department of Epidemiology, The Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.,Department of Biomedical Data Science, Geisel School of Medicine, Lebanon, NH, USA
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Colicino E, Cowell W, Foppa Pedretti N, Joshi A, Youssef O, Just AC, Kloog I, Petrick L, Niedzwiecki M, Wright RO, Wright RJ. Maternal steroids during pregnancy and their associations with ambient air pollution and temperature during preconception and early gestational periods. ENVIRONMENT INTERNATIONAL 2022; 165:107320. [PMID: 35700570 PMCID: PMC10140184 DOI: 10.1016/j.envint.2022.107320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 04/29/2022] [Accepted: 05/23/2022] [Indexed: 06/15/2023]
Abstract
Hormones play critical roles in facilitating pregnancy progression and the onset of parturition. Several classes of environmental contaminants, including fine particulate matter (PM2.5) and ambient temperature, have been shown to alter hormone biosynthesis or activity. However, epidemiologic research has not considered PM2.5 in relation to a broader range of steroid hormones, particularly in pregnant women. Using metabolomics data collected within 20-40 weeks of gestation in an ethnically diverse pregnancy cohort study, we identified 42 steroid hormones that we grouped into five classes (pregnenolone, androgens, estrogens, progestin, and corticosteroids) based on their biosynthesis type. We found that exposure to PM2.5 during the pre-conception and early prenatal periods was associated with higher maternal androgen concentrations in late pregnancy. We also detected a positive association between early pregnancy PM2.5 exposure and maternal pregnenolone levels and a marginal positive association between early pregnancy PM2.5 exposure and progestin levels. When considering each hormone metabolite individually, we found positive associations between early pregnancy PM2.5 exposure and five steroids, two of which survived multiple comparison testing: 11beta-hydroxyandrosterone glucuronide (a pregnenolone steroid) and adrosteroneglucuronide (a progestin steroid). None of the steroid classes were statistically significant associated with ambient temperature. In sex-stratified analyses, we did not detect any sex differences in our associations. This is the first study showing that exposure to fine particulate matter during the pre-conception and early prenatal periods can lead to altered steroid adaptation during the state of pregnancy, which has been shown to have potential consequences on maternal and child health.
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Affiliation(s)
- Elena Colicino
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Whitney Cowell
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Nicolo Foppa Pedretti
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Anu Joshi
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Oulhote Youssef
- Department of Epidemiology, University of Massachusetts Amherst, Amherst, MA, USA
| | - Allan C Just
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Itai Kloog
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Geography and Environmental Development, Ben-Gurion University of the Negev, P.O.B. Beer Sheva, Israel; Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Lauren Petrick
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Megan Niedzwiecki
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Robert O Wright
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Rosalind J Wright
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Kravis Children's Hospital, Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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Barupal DK, Mahajan P, Fakouri-Baygi S, Wright RO, Arora M, Teitelbaum SL. CCDB: A database for exploring inter-chemical correlations in metabolomics and exposomics datasets. ENVIRONMENT INTERNATIONAL 2022; 164:107240. [PMID: 35461097 PMCID: PMC9195052 DOI: 10.1016/j.envint.2022.107240] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 04/01/2022] [Accepted: 04/08/2022] [Indexed: 05/18/2023]
Abstract
Inter-chemical correlations in metabolomics and exposomics datasets provide valuable information for studying relationships among chemicals reported for human specimens. With an increase in the number of compounds for these datasets, a network graph analysis and visualization of the correlation structure is difficult to interpret. We have developed the Chemical Correlation Database (CCDB), as a systematic catalogue of inter-chemical correlation in publicly available metabolomics and exposomics studies. The database has been provided via an online interface to create single compound-centric views. We have demonstrated various applications of the database to explore: 1) the chemicals from a chemical class such as Per- and Polyfluoroalkyl Substances (PFAS), polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), phthalates and tobacco smoke related metabolites; 2) xenobiotic metabolites such as caffeine and acetaminophen; 3) endogenous metabolites (acyl-carnitines); and 4) unannotated peaks for PFAS. The database has a rich collection of 35 human studies, including the National Health and Nutrition Examination Survey (NHANES) and high-quality untargeted metabolomics datasets. CCDB is supported by a simple, interactive and user-friendly web-interface to retrieve and visualize the inter-chemical correlation data. The CCDB has the potential to be a key computational resource in metabolomics and exposomics facilitating the expansion of our understanding about biological and chemical relationships among metabolites and chemical exposures in the human body. The database is available at www.ccdb.idsl.me site.
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Affiliation(s)
- Dinesh Kumar Barupal
- Department of Environmental Medicine and Public Health, Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, 17 E 102nd St, CAM Building, New York 10029, USA.
| | - Priyanka Mahajan
- Department of Environmental Medicine and Public Health, Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, 17 E 102nd St, CAM Building, New York 10029, USA
| | - Sadjad Fakouri-Baygi
- Department of Environmental Medicine and Public Health, Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, 17 E 102nd St, CAM Building, New York 10029, USA
| | - Robert O Wright
- Department of Environmental Medicine and Public Health, Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, 17 E 102nd St, CAM Building, New York 10029, USA
| | - Manish Arora
- Department of Environmental Medicine and Public Health, Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, 17 E 102nd St, CAM Building, New York 10029, USA
| | - Susan L Teitelbaum
- Department of Environmental Medicine and Public Health, Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, 17 E 102nd St, CAM Building, New York 10029, USA
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