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Carlin DJ, Rider CV. Combined Exposures and Mixtures Research: An Enduring NIEHS Priority. ENVIRONMENTAL HEALTH PERSPECTIVES 2024; 132:75001. [PMID: 38968090 PMCID: PMC11225971 DOI: 10.1289/ehp14340] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Revised: 04/25/2024] [Accepted: 06/12/2024] [Indexed: 07/07/2024]
Abstract
BACKGROUND The National Institute of Environmental Health Sciences (NIEHS) continues to prioritize research to better understand the health effects resulting from exposure to mixtures of chemical and nonchemical stressors. Mixtures research activities over the last decade were informed by expert input during the development and deliberations of the 2011 NIEHS Workshop "Advancing Research on Mixtures: New Perspectives and Approaches for Predicting Adverse Human Health Effects." NIEHS mixtures research efforts since then have focused on key themes including a) prioritizing mixtures for study, b) translating mixtures data from in vitro and in vivo studies, c) developing cross-disciplinary collaborations, d) informing component-based and whole-mixture assessment approaches, e) developing sufficient similarity methods to compare across complex mixtures, f) using systems-based approaches to evaluate mixtures, and g) focusing on management and integration of mixtures-related data. OBJECTIVES We aimed to describe NIEHS driven research on mixtures and combined exposures over the last decade and present areas for future attention. RESULTS Intramural and extramural mixtures research projects have incorporated a diverse array of chemicals (e.g., polycyclic aromatic hydrocarbons, botanicals, personal care products, wildfire emissions) and nonchemical stressors (e.g., socioeconomic factors, social adversity) and have focused on many diseases (e.g., breast cancer, atherosclerosis, immune disruption). We have made significant progress in certain areas, such as developing statistical methods for evaluating multiple chemical associations in epidemiology and building translational mixtures projects that include both in vitro and in vivo models. DISCUSSION Moving forward, additional work is needed to improve mixtures data integration, elucidate interactions between chemical and nonchemical stressors, and resolve the geospatial and temporal nature of mixture exposures. Continued mixtures research will be critical to informing cumulative impact assessments and addressing complex challenges, such as environmental justice and climate change. https://doi.org/10.1289/EHP14340.
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Affiliation(s)
- Danielle J. Carlin
- Division of Extramural Research and Training, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, USA
| | - Cynthia V. Rider
- Division of Translational Toxicology, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, USA
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Lloyd D, House JS, Akhtari FS, Schmitt CP, Fargo DC, Scholl EH, Phillips J, Choksi S, Shah R, Hall JE, Motsinger-Reif AA. Interactive data sharing for multiple questionnaire-based exposome-wide association studies and exposome correlations in the Personalized Environment and Genes Study. EXPOSOME 2024; 4:osae003. [PMID: 38425336 PMCID: PMC10899804 DOI: 10.1093/exposome/osae003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 11/20/2023] [Accepted: 01/01/2024] [Indexed: 03/02/2024]
Abstract
The correlations among individual exposures in the exposome, which refers to all exposures an individual encounters throughout life, are important for understanding the landscape of how exposures co-occur, and how this impacts health and disease. Exposome-wide association studies (ExWAS), which are analogous to genome-wide association studies (GWAS), are increasingly being used to elucidate links between the exposome and disease. Despite increased interest in the exposome, tools and publications that characterize exposure correlations and their relationships with human disease are limited, and there is a lack of data and results sharing in resources like the GWAS catalog. To address these gaps, we developed the PEGS Explorer web application to explore exposure correlations in data from the diverse North Carolina-based Personalized Environment and Genes Study (PEGS) that were rigorously calculated to account for differing data types and previously published results from ExWAS. Through globe visualizations, PEGS Explorer allows users to explore correlations between exposures found to be associated with complex diseases. The exposome data used for analysis includes not only standard environmental exposures such as point source pollution and ozone levels but also exposures from diet, medication, lifestyle factors, stress, and occupation. The web application addresses the lack of accessible data and results sharing, a major challenge in the field, and enables users to put results in context, generate hypotheses, and, importantly, replicate findings in other cohorts. PEGS Explorer will be updated with additional results as they become available, ensuring it is an up-to-date resource in exposome science.
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Affiliation(s)
- Dillon Lloyd
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Durham, NC, USA
| | - John S House
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Durham, NC, USA
| | - Farida S Akhtari
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Durham, NC, USA
| | - Charles P Schmitt
- Division of Translational Toxicology, National Institute of Environmental Health Sciences, Durham, NC, USA
| | - David C Fargo
- Office of the Director, National Institute of Environmental Health Sciences, Durham, NC, USA
| | | | | | | | | | - Janet E Hall
- Clinical Research Branch, National Institute of Environmental Health Sciences, Durham, NC, USA
| | - Alison A Motsinger-Reif
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Durham, NC, USA
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Lloyd D, House JS, Akhtari FS, Schmitt CP, Fargo DC, Scholl EH, Phillips J, Choksi S, Shah R, Hall JE, Motsinger-Reif AA. Questionnaire-based exposome-wide association studies for common diseases in the Personalized Environment and Genes Study. EXPOSOME 2024; 4:osae002. [PMID: 38450326 PMCID: PMC10914401 DOI: 10.1093/exposome/osae002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Accepted: 01/01/2024] [Indexed: 03/08/2024]
Abstract
The exposome collectively refers to all exposures, beginning in utero and continuing throughout life, and comprises not only standard environmental exposures such as point source pollution and ozone levels but also exposures from diet, medication, lifestyle factors, stress, and occupation. The exposome interacts with individual genetic and epigenetic characteristics to affect human health and disease, but large-scale studies that characterize the exposome and its relationships with human disease are limited. To address this gap, we used extensive questionnaire data from the diverse North Carolina-based Personalized Environment and Genes Study (PEGS, n = 9, 429) to evaluate exposure associations in relation to common diseases. We performed an exposome-wide association study (ExWAS) to examine single exposure models and their associations with 11 common complex diseases, namely allergic rhinitis, asthma, bone loss, fibroids, high cholesterol, hypertension, iron-deficient anemia, ovarian cysts, lower GI polyps, migraines, and type 2 diabetes. Across diseases, we found associations with lifestyle factors and socioeconomic status as well as asbestos, various dust types, biohazardous material, and textile-related exposures. We also found disease-specific associations such as fishing with lead weights and migraines. To differentiate between a replicated result and a novel finding, we used an AI-based literature search and database tool that allowed us to examine the current literature. We found both replicated findings, especially for lifestyle factors such as sleep and smoking across diseases, and novel findings, especially for occupational exposures and multiple diseases.
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Affiliation(s)
- Dillon Lloyd
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Durham, NC, USA
| | - John S House
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Durham, NC, USA
| | - Farida S Akhtari
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Durham, NC, USA
| | - Charles P Schmitt
- Division of Translational Toxicology, National Institute of Environmental Health Sciences, Durham, NC, USA
| | - David C Fargo
- Office of the Director, National Institute of Environmental Health Sciences, Durham, NC, USA
| | | | | | | | | | - Janet E Hall
- Clinical Research Branch, National Institute of Environmental Health Sciences, Durham, NC, USA
| | - Alison A Motsinger-Reif
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Durham, NC, USA
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Sharif R, Ooi TC. Understanding exposomes and its relation with cancer risk in Malaysia based on epidemiological evidence: a narrative review. Genes Environ 2024; 46:5. [PMID: 38326915 PMCID: PMC10851543 DOI: 10.1186/s41021-024-00300-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 01/30/2024] [Indexed: 02/09/2024] Open
Abstract
The prevalence of cancer is increasing globally, and Malaysia is no exception. The exposome represents a paradigm shift in cancer research, emphasizing the importance of a holistic approach that considers the cumulative effect of diverse exposures encountered throughout life. The exposures include dietary factors, air and water pollutants, occupational hazards, lifestyle choices, infectious agents and social determinants of health. The exposome concept acknowledges that each individual's cancer risk is shaped by not only their genetic makeup but also their unique life experiences and environmental interactions. This comprehensive review was conducted by systematically searching scientific databases such as PubMed, Scopus and Google Scholar, by using the keywords "exposomes (environmental exposures AND/OR physical exposures AND/OR chemical exposures) AND cancer risk AND Malaysia", for relevant articles published between 2010 and 2023. Articles addressing the relationship between exposomes and cancer risk in the Malaysian population were critically evaluated and summarized. This review aims to provide an update on the epidemiological evidence linking exposomes with cancer risk in Malaysia. This review will provide an update for current findings and research in Malaysia related to identified exposomes-omics interaction and gap in research area related to the subject matter. Understanding the interplay between complex exposomes and carcinogenesis holds the potential to unveil novel preventive strategies that may be beneficial for public health.
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Affiliation(s)
- Razinah Sharif
- Centre of Healthy Ageing and Wellness, Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Bangi, Malaysia.
| | - Theng Choon Ooi
- Centre of Healthy Ageing and Wellness, Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Bangi, Malaysia
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Lee EY, Choi W, Burkholder AB, Perera L, Mack JA, Miller FW, Fessler MB, Cook DN, Karmaus PWF, Nakano H, Garantziotis S, Madenspacher JH, House JS, Akhtari FS, Schmitt CS, Fargo DC, Hall JE, Motsinger-Reif AA. Race/ethnicity-stratified fine-mapping of the MHC locus reveals genetic variants associated with late-onset asthma. Front Genet 2023; 14:1173676. [PMID: 37415598 PMCID: PMC10321602 DOI: 10.3389/fgene.2023.1173676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Accepted: 06/09/2023] [Indexed: 07/08/2023] Open
Abstract
Introduction: Asthma is a chronic disease of the airways that impairs normal breathing. The etiology of asthma is complex and involves multiple factors, including the environment and genetics, especially the distinct genetic architecture associated with ancestry. Compared to early-onset asthma, little is known about genetic predisposition to late-onset asthma. We investigated the race/ethnicity-specific relationship among genetic variants within the major histocompatibility complex (MHC) region and late-onset asthma in a North Carolina-based multiracial cohort of adults. Methods: We stratified all analyses by self-reported race (i.e., White and Black) and adjusted all regression models for age, sex, and ancestry. We conducted association tests within the MHC region and performed fine-mapping analyses conditioned on the race/ethnicity-specific lead variant using whole-genome sequencing (WGS) data. We applied computational methods to infer human leukocyte antigen (HLA) alleles and residues at amino acid positions. We replicated findings in the UK Biobank. Results: The lead signals, rs9265901 on the 5' end of HLA-B, rs55888430 on HLA-DOB, and rs117953947 on HCG17, were significantly associated with late-onset asthma in all, White, and Black participants, respectively (OR = 1.73, 95%CI: 1.31 to 2.14, p = 3.62 × 10-5; OR = 3.05, 95%CI: 1.86 to 4.98, p = 8.85 × 10-6; OR = 19.5, 95%CI: 4.37 to 87.2, p = 9.97 × 10-5, respectively). For the HLA analysis, HLA-B*40:02 and HLA-DRB1*04:05, HLA-B*40:02, HLA-C*04:01, and HLA-DRB1*04:05, and HLA-DRB1*03:01 and HLA-DQB1 were significantly associated with late-onset asthma in all, White, and Black participants. Conclusion: Multiple genetic variants within the MHC region were significantly associated with late-onset asthma, and the associations were significantly different by race/ethnicity group.
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Affiliation(s)
- Eunice Y. Lee
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Durham, NC, United States
| | - Wonson Choi
- Genomics and Bioinformatics Laboratory, Seoul National University, Seoul, Republic of Korea
| | - Adam B. Burkholder
- National Institute of Environmental Health Sciences, Durham, NC, United States
| | - Lalith Perera
- Genomic Integrity and Structural Biology Laboratory, National Institute of Environmental Health Sciences, Durham, NC, United States
| | - Jasmine A. Mack
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Durham, NC, United States
- Department of Obstetrics and Gynecology, University of Cambridge, Cambridge, United Kingdom
| | - Frederick W. Miller
- Environmental Autoimmunity Group, Clinical Research Branch, National Institute of Environmental Health Sciences, Durham, NC, United States
| | - Michael B. Fessler
- Immunity, Inflammation and Disease Laboratory, National Institute of Environmental Health Sciences, Durham, NC, United States
| | - Donald N. Cook
- Immunity, Inflammation and Disease Laboratory, National Institute of Environmental Health Sciences, Durham, NC, United States
- Immunogenetics Group, National Institute of Environmental Health Sciences, Durham, NC, United States
| | - Peer W. F. Karmaus
- Immunity, Inflammation and Disease Laboratory, National Institute of Environmental Health Sciences, Durham, NC, United States
| | - Hideki Nakano
- Immunity, Inflammation and Disease Laboratory, National Institute of Environmental Health Sciences, Durham, NC, United States
| | - Stavros Garantziotis
- Clinical Research Branch, National Institute of Environmental Health Sciences, Durham, NC, United States
| | - Jennifer H. Madenspacher
- Clinical Research Branch, National Institute of Environmental Health Sciences, Durham, NC, United States
| | - John S. House
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Durham, NC, United States
| | - Farida S. Akhtari
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Durham, NC, United States
- Clinical Research Branch, National Institute of Environmental Health Sciences, Durham, NC, United States
| | - Charles S. Schmitt
- Division of Translational Toxicology, National Institute of Environmental Health Sciences, Durham, NC, United States
| | - David C. Fargo
- National Institute of Environmental Health Sciences, Durham, NC, United States
| | - Janet E. Hall
- Clinical Research Branch, National Institute of Environmental Health Sciences, Durham, NC, United States
| | - Alison A. Motsinger-Reif
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Durham, NC, United States
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Akhtari FS, Lloyd D, Burkholder A, Tong X, House JS, Lee EY, Buse J, Schurman SH, Fargo DC, Schmitt CP, Hall J, Motsinger-Reif AA. Questionnaire-Based Polyexposure Assessment Outperforms Polygenic Scores for Classification of Type 2 Diabetes in a Multiancestry Cohort. Diabetes Care 2023; 46:929-937. [PMID: 36383734 PMCID: PMC10154656 DOI: 10.2337/dc22-0295] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Accepted: 10/23/2022] [Indexed: 11/17/2022]
Abstract
OBJECTIVE Environmental exposures may have greater predictive power for type 2 diabetes than polygenic scores (PGS). Studies examining environmental risk factors, however, have included only individuals with European ancestry, limiting the applicability of results. We conducted an exposome-wide association study in the multiancestry Personalized Environment and Genes Study to assess the effects of environmental factors on type 2 diabetes. RESEARCH DESIGN AND METHODS Using logistic regression for single-exposure analysis, we identified exposures associated with type 2 diabetes, adjusting for age, BMI, household income, and self-reported sex and race. To compare cumulative genetic and environmental effects, we computed an overall clinical score (OCS) as a weighted sum of BMI and prediabetes, hypertension, and high cholesterol status and a polyexposure score (PXS) as a weighted sum of 13 environmental variables. Using UK Biobank data, we developed a multiancestry PGS and calculated it for participants. RESULTS We found 76 significant associations with type 2 diabetes, including novel associations of asbestos and coal dust exposure. OCS, PXS, and PGS were significantly associated with type 2 diabetes. PXS had moderate power to determine associations, with larger effect size and greater power and reclassification improvement than PGS. For all scores, the results differed by race. CONCLUSIONS Our findings in a multiancestry cohort elucidate how type 2 diabetes odds can be attributed to clinical, genetic, and environmental factors and emphasize the need for exposome data in disease-risk association studies. Race-based differences in predictive scores highlight the need for genetic and exposome-wide studies in diverse populations.
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Affiliation(s)
- Farida S. Akhtari
- Biostatistics & Computational Biology Branch, National Institute of Environmental Health Sciences, Durham, NC
- Clinical Research Branch, National Institute of Environmental Health Sciences, Durham, NC
| | - Dillon Lloyd
- Biostatistics & Computational Biology Branch, National Institute of Environmental Health Sciences, Durham, NC
| | - Adam Burkholder
- Office of the Director, National Institute of Environmental Health Sciences, Durham, NC
| | - Xiaoran Tong
- Biostatistics & Computational Biology Branch, National Institute of Environmental Health Sciences, Durham, NC
| | - John S. House
- Biostatistics & Computational Biology Branch, National Institute of Environmental Health Sciences, Durham, NC
| | - Eunice Y. Lee
- Biostatistics & Computational Biology Branch, National Institute of Environmental Health Sciences, Durham, NC
| | - John Buse
- Department of Medicine, University of North Carolina, Chapel Hill, NC
| | - Shepherd H. Schurman
- Clinical Research Branch, National Institute of Environmental Health Sciences, Durham, NC
| | - David C. Fargo
- Office of the Director, National Institute of Environmental Health Sciences, Durham, NC
| | - Charles P. Schmitt
- Office of Data Science, National Institute of Environmental Health Science, Durham, NC
| | - Janet Hall
- Clinical Research Branch, National Institute of Environmental Health Sciences, Durham, NC
| | - Alison A. Motsinger-Reif
- Biostatistics & Computational Biology Branch, National Institute of Environmental Health Sciences, Durham, NC
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