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Grady SK, Dojcsak L, Harville EW, Wallace ME, Vilda D, Donneyong MM, Hood DB, Valdez RB, Ramesh A, Im W, Matthews-Juarez P, Juarez PD, Langston MA. Seminar: Scalable Preprocessing Tools for Exposomic Data Analysis. ENVIRONMENTAL HEALTH PERSPECTIVES 2023; 131:124201. [PMID: 38109119 PMCID: PMC10727037 DOI: 10.1289/ehp12901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 11/22/2023] [Accepted: 11/28/2023] [Indexed: 12/19/2023]
Abstract
BACKGROUND The exposome serves as a popular framework in which to study exposures from chemical and nonchemical stressors across the life course and the differing roles that these exposures can play in human health. As a result, data relevant to the exposome have been used as a resource in the quest to untangle complicated health trajectories and help connect the dots from exposures to adverse outcome pathways. OBJECTIVES The primary aim of this methods seminar is to clarify and review preprocessing techniques critical for accurate and effective external exposomic data analysis. Scalability is emphasized through an application of highly innovative combinatorial techniques coupled with more traditional statistical strategies. The Public Health Exposome is used as an archetypical model. The novelty and innovation of this seminar's focus stem from its methodical, comprehensive treatment of preprocessing and its demonstration of the positive effects preprocessing can have on downstream analytics. DISCUSSION State-of-the-art technologies are described for data harmonization and to mitigate noise, which can stymie downstream interpretation, and to select key exposomic features, without which analytics may lose focus. A main task is the reduction of multicollinearity, a particularly formidable problem that frequently arises from repeated measurements of similar events taken at various times and from multiple sources. Empirical results highlight the effectiveness of a carefully planned preprocessing workflow as demonstrated in the context of more highly concentrated variable lists, improved correlational distributions, and enhanced downstream analytics for latent relationship discovery. The nascent field of exposome science can be characterized by the need to analyze and interpret a complex confluence of highly inhomogeneous spatial and temporal data, which may present formidable challenges to even the most powerful analytical tools. A systematic approach to preprocessing can therefore provide an essential first step in the application of modern computer and data science methods. https://doi.org/10.1289/EHP12901.
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Affiliation(s)
- Stephen K. Grady
- Graduate School of Genome Science and Technology, University of Tennessee, Knoxville, Tennessee, USA
| | - Levente Dojcsak
- Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, Tennessee, USA
| | - Emily W. Harville
- Department Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana, USA
| | - Maeve E. Wallace
- Department of Social, Behavioral, and Population Sciences, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana, USA
| | - Dovile Vilda
- Department of Social, Behavioral, and Population Sciences, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana, USA
| | | | - Darryl B. Hood
- Division of Environmental Health Sciences, College of Public Health, Ohio State University, Columbus, Ohio, USA
| | - R. Burciaga Valdez
- Department of Economics, University of New Mexico, Albuquerque, New Mexico, USA
| | - Aramandla Ramesh
- Department of Biochemistry, Cancer Biology, Neuroscience & Pharmacology, Meharry Medical College, Nashville, Tennessee, USA
| | - Wansoo Im
- Department of Family and Community Medicine, Meharry Medical College, Nashville, Tennessee, USA
| | | | - Paul D. Juarez
- Department of Family and Community Medicine, Meharry Medical College, Nashville, Tennessee, USA
- Institute on Health Disparities, Equity, and the Exposome, Meharry Medical College, Nashville, Tennessee, USA
| | - Michael A. Langston
- Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, Tennessee, USA
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Stingone JA, Geller AM, Hood DB, Makris KC, Mouton CP, States JC, Sumner SJ, Wu KL, Rajasekar AK. Community-level exposomics: a population-centered approach to address public health concerns. EXPOSOME 2023; 3:osad009. [PMID: 38550543 PMCID: PMC10976977 DOI: 10.1093/exposome/osad009] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2024]
Abstract
Environmental factors affecting health and vulnerability far outweigh genetics in accounting for disparities in health status and longevity in US communities. The concept of the exposome, the totality of exposure from conception onwards, provides a paradigm for researchers to investigate the complex role of the environment on the health of individuals. We propose a complementary framework, community-level exposomics, for population-level exposome assessment. The goal is to bring the exposome paradigm to research and practice on the health of populations, defined by various axes including geographic, social, and occupational. This framework includes the integration of community-level measures of the built, natural and social environments, environmental pollution-derived from conventional and community science approaches, internal markers of exposure that can be measured at the population-level and early responses associated with health status that can be tracked using population-based monitoring. Primary challenges to the implementation of the proposed framework include needed advancements in population-level measurement, lack of existing models with the capability to produce interpretable and actionable evidence and the ethical considerations of labeling geographically-bound populations by exposomic profiles. To address these challenges, we propose a set of recommendations that begin with greater engagement with and empowerment of affected communities and targeted investment in community-based solutions. Applications to urban settings and disaster epidemiology are discussed as examples for implementation.
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Affiliation(s)
- Jeanette A. Stingone
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Andrew M. Geller
- Office of Research and Development, Environmental Protection Agency, RTP, NC, USA
| | - Darryl B. Hood
- Division of Environmental Health Sciences, The Ohio State University, Columbus, OH, USA
| | - Konstantinos C. Makris
- Cyprus International Institute for Environmental and Public Health, Cyprus University of Technology, Limassol, Cyprus
| | - Charles P. Mouton
- Department of Family Medicine, University of Texas Medical Branch Galveston, TX, USA
| | - J. Christopher States
- Center for Integrative Environmental Health Sciences, Department of Pharmacology and Toxicology University of Louisville School of Medicine, Louisville, KY, USA
| | - Susan J. Sumner
- Department of Nutrition, University of North Carolina, Chapel Hill, Chapel Hill, NC, USA
| | - K. Lily Wu
- California Environmental Protection Agency—Office of Environmental Health Hazard Assessment, Sacramento, CA, USA
| | - Arcot K Rajasekar
- School of Information and Library Science, University of North Carolina, Chapel Hill, Chapel Hill, NC, USA
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