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Sdougkou K, Papazian S, Bonnefille B, Xie H, Edfors F, Fagerberg L, Uhlén M, Bergström G, Martin LJ, Martin JW. Longitudinal Exposomics in a Multiomic Wellness Cohort Reveals Distinctive and Dynamic Environmental Chemical Mixtures in Blood. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024. [PMID: 39236221 DOI: 10.1021/acs.est.4c05235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/07/2024]
Abstract
Chemical exposomes can now be comprehensively measured in human blood, but knowledge of their variability and longitudinal stability is required for robust application in cohort studies. Here, we applied high-resolution chemical exposomics to plasma of 46 adults, each sampled 6 times over 2 years in a multiomic cohort, resulting in 276 individual exposomes. In addition to quantitative analysis of 83 priority target analytes, we discovered and semiquantified substances that have rarely or never been reported in humans, including personal care products, pesticide transformation products, and polymer additives. Hierarchical cluster analysis for 519 confidently annotated substances revealed unique and distinctive coexposures, including clustered pesticides, poly(ethylene glycols), chlorinated phenols, or natural substances from tea and coffee; interactive heatmaps were publicly deposited to support open exploration of the complex (meta)data. Intraclass correlation coefficients (ICC) for all annotated substances demonstrated the relatively low stability of the exposome compared to that of proteome, microbiome, and endogenous small molecules. Implications are that the chemical exposome must be measured more frequently than other omics in longitudinal studies and four longitudinal exposure types are defined that can be considered in study design. In this small cohort, mixed-effect models nevertheless revealed significant associations between testosterone and perfluoroalkyl substances, demonstrating great potential for longitudinal exposomics in precision health research.
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Affiliation(s)
- Kalliroi Sdougkou
- Department of Environmental Science, Stockholm University, Stockholm 106 91, Sweden
| | - Stefano Papazian
- Department of Environmental Science, Stockholm University, Stockholm 106 91, Sweden
- National Facility for Exposomics, Metabolomics Platform, Science for Life Laboratory, Stockholm University, Solna 171 65, Sweden
| | - Bénilde Bonnefille
- Department of Environmental Science, Stockholm University, Stockholm 106 91, Sweden
- National Facility for Exposomics, Metabolomics Platform, Science for Life Laboratory, Stockholm University, Solna 171 65, Sweden
| | - Hongyu Xie
- Department of Environmental Science, Stockholm University, Stockholm 106 91, Sweden
| | - Fredrik Edfors
- Department of Protein Science, Science for Life Laboratory, KTH-Royal Institute of Technology, Stockholm 100 44, Sweden
| | - Linn Fagerberg
- Department of Protein Science, Science for Life Laboratory, KTH-Royal Institute of Technology, Stockholm 100 44, Sweden
| | - Mathias Uhlén
- Department of Protein Science, Science for Life Laboratory, KTH-Royal Institute of Technology, Stockholm 100 44, Sweden
| | - Göran Bergström
- Department of Molecular and Clinical Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg 40530, Sweden
- Department of Clinical Physiology, Sahlgrenska University Hospital, Region Västra Götaland, Gothenburg 413 45, Sweden
| | | | - Jonathan W Martin
- Department of Environmental Science, Stockholm University, Stockholm 106 91, Sweden
- National Facility for Exposomics, Metabolomics Platform, Science for Life Laboratory, Stockholm University, Solna 171 65, Sweden
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2
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Lai Y, Koelmel JP, Walker DI, Price EJ, Papazian S, Manz KE, Castilla-Fernández D, Bowden JA, Nikiforov V, David A, Bessonneau V, Amer B, Seethapathy S, Hu X, Lin EZ, Jbebli A, McNeil BR, Barupal D, Cerasa M, Xie H, Kalia V, Nandakumar R, Singh R, Tian Z, Gao P, Zhao Y, Froment J, Rostkowski P, Dubey S, Coufalíková K, Seličová H, Hecht H, Liu S, Udhani HH, Restituito S, Tchou-Wong KM, Lu K, Martin JW, Warth B, Godri Pollitt KJ, Klánová J, Fiehn O, Metz TO, Pennell KD, Jones DP, Miller GW. High-Resolution Mass Spectrometry for Human Exposomics: Expanding Chemical Space Coverage. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:12784-12822. [PMID: 38984754 PMCID: PMC11271014 DOI: 10.1021/acs.est.4c01156] [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: 02/01/2024] [Revised: 06/11/2024] [Accepted: 06/12/2024] [Indexed: 07/11/2024]
Abstract
In the modern "omics" era, measurement of the human exposome is a critical missing link between genetic drivers and disease outcomes. High-resolution mass spectrometry (HRMS), routinely used in proteomics and metabolomics, has emerged as a leading technology to broadly profile chemical exposure agents and related biomolecules for accurate mass measurement, high sensitivity, rapid data acquisition, and increased resolution of chemical space. Non-targeted approaches are increasingly accessible, supporting a shift from conventional hypothesis-driven, quantitation-centric targeted analyses toward data-driven, hypothesis-generating chemical exposome-wide profiling. However, HRMS-based exposomics encounters unique challenges. New analytical and computational infrastructures are needed to expand the analysis coverage through streamlined, scalable, and harmonized workflows and data pipelines that permit longitudinal chemical exposome tracking, retrospective validation, and multi-omics integration for meaningful health-oriented inferences. In this article, we survey the literature on state-of-the-art HRMS-based technologies, review current analytical workflows and informatic pipelines, and provide an up-to-date reference on exposomic approaches for chemists, toxicologists, epidemiologists, care providers, and stakeholders in health sciences and medicine. We propose efforts to benchmark fit-for-purpose platforms for expanding coverage of chemical space, including gas/liquid chromatography-HRMS (GC-HRMS and LC-HRMS), and discuss opportunities, challenges, and strategies to advance the burgeoning field of the exposome.
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Affiliation(s)
- Yunjia Lai
- Department
of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York 10032, United States
| | - Jeremy P. Koelmel
- Department
of Environmental Health Sciences, Yale School
of Public Health, New Haven, Connecticut 06520, United States
| | - Douglas I. Walker
- Gangarosa
Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia 30322, United States
| | - Elliott J. Price
- RECETOX,
Faculty of Science, Masaryk University, Kotlářská 2, 611 37 Brno, Czech Republic
| | - Stefano Papazian
- Department
of Environmental Science, Science for Life Laboratory, Stockholm University, SE-106 91 Stockholm, Sweden
- National
Facility for Exposomics, Metabolomics Platform, Science for Life Laboratory, Stockholm University, Solna 171 65, Sweden
| | - Katherine E. Manz
- Department
of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Delia Castilla-Fernández
- Department
of Food Chemistry and Toxicology, Faculty of Chemistry, University of Vienna, 1010 Vienna, Austria
| | - John A. Bowden
- Center for
Environmental and Human Toxicology, Department of Physiological Sciences,
College of Veterinary Medicine, University
of Florida, Gainesville, Florida 32611, United States
| | | | - Arthur David
- Univ Rennes,
Inserm, EHESP, Irset (Institut de recherche en santé, environnement
et travail) − UMR_S, 1085 Rennes, France
| | - Vincent Bessonneau
- Univ Rennes,
Inserm, EHESP, Irset (Institut de recherche en santé, environnement
et travail) − UMR_S, 1085 Rennes, France
| | - Bashar Amer
- Thermo
Fisher Scientific, San Jose, California 95134, United States
| | | | - Xin Hu
- Gangarosa
Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia 30322, United States
| | - Elizabeth Z. Lin
- Department
of Environmental Health Sciences, Yale School
of Public Health, New Haven, Connecticut 06520, United States
| | - Akrem Jbebli
- RECETOX,
Faculty of Science, Masaryk University, Kotlářská 2, 611 37 Brno, Czech Republic
| | - Brooklynn R. McNeil
- Biomarkers
Core Laboratory, Irving Institute for Clinical and Translational Research, Columbia University Irving Medical Center, New York, New York 10032, United States
| | - Dinesh Barupal
- Department
of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, New York 10029, United States
| | - Marina Cerasa
- Institute
of Atmospheric Pollution Research, Italian National Research Council, 00015 Monterotondo, Rome, Italy
| | - Hongyu Xie
- Department
of Environmental Science, Science for Life Laboratory, Stockholm University, SE-106 91 Stockholm, Sweden
| | - Vrinda Kalia
- Department
of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York 10032, United States
| | - Renu Nandakumar
- Biomarkers
Core Laboratory, Irving Institute for Clinical and Translational Research, Columbia University Irving Medical Center, New York, New York 10032, United States
| | - Randolph Singh
- Department
of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York 10032, United States
| | - Zhenyu Tian
- Department
of Chemistry and Chemical Biology, Northeastern
University, Boston, Massachusetts 02115, United States
| | - Peng Gao
- Department
of Environmental and Occupational Health, and Department of Civil
and Environmental Engineering, University
of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
- UPMC Hillman
Cancer Center, Pittsburgh, Pennsylvania 15232, United States
| | - Yujia Zhao
- Institute
for Risk Assessment Sciences, Utrecht University, Utrecht 3584CM, The Netherlands
| | | | | | - Saurabh Dubey
- Biomarkers
Core Laboratory, Irving Institute for Clinical and Translational Research, Columbia University Irving Medical Center, New York, New York 10032, United States
| | - Kateřina Coufalíková
- RECETOX,
Faculty of Science, Masaryk University, Kotlářská 2, 611 37 Brno, Czech Republic
| | - Hana Seličová
- RECETOX,
Faculty of Science, Masaryk University, Kotlářská 2, 611 37 Brno, Czech Republic
| | - Helge Hecht
- RECETOX,
Faculty of Science, Masaryk University, Kotlářská 2, 611 37 Brno, Czech Republic
| | - Sheng Liu
- Department
of Environmental Health Sciences, Yale School
of Public Health, New Haven, Connecticut 06520, United States
| | - Hanisha H. Udhani
- Biomarkers
Core Laboratory, Irving Institute for Clinical and Translational Research, Columbia University Irving Medical Center, New York, New York 10032, United States
| | - Sophie Restituito
- Department
of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York 10032, United States
| | - Kam-Meng Tchou-Wong
- Department
of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York 10032, United States
| | - Kun Lu
- Department
of Environmental Sciences and Engineering, Gillings School of Global
Public Health, The University of North Carolina
at Chapel Hill, Chapel Hill, North Carolina 27599, United States
| | - Jonathan W. Martin
- Department
of Environmental Science, Science for Life Laboratory, Stockholm University, SE-106 91 Stockholm, Sweden
- National
Facility for Exposomics, Metabolomics Platform, Science for Life Laboratory, Stockholm University, Solna 171 65, Sweden
| | - Benedikt Warth
- Department
of Food Chemistry and Toxicology, Faculty of Chemistry, University of Vienna, 1010 Vienna, Austria
| | - Krystal J. Godri Pollitt
- Department
of Environmental Health Sciences, Yale School
of Public Health, New Haven, Connecticut 06520, United States
| | - Jana Klánová
- RECETOX,
Faculty of Science, Masaryk University, Kotlářská 2, 611 37 Brno, Czech Republic
| | - Oliver Fiehn
- West Coast
Metabolomics Center, University of California−Davis, Davis, California 95616, United States
| | - Thomas O. Metz
- Biological
Sciences Division, Pacific Northwest National
Laboratory, Richland, Washington 99354, United States
| | - Kurt D. Pennell
- School
of Engineering, Brown University, Providence, Rhode Island 02912, United States
| | - Dean P. Jones
- Department
of Medicine, School of Medicine, Emory University, Atlanta, Georgia 30322, United States
| | - Gary W. Miller
- Department
of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York 10032, United States
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3
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Sun P, Guo X, Ding E, Li C, Ren H, Xu Y, Qian J, Deng F, Shi W, Dong H, Lin EZ, Guo P, Fang J, Zhang Q, Zhao W, Tong S, Lu X, Pollitt KJG, Shi X, Tang S. Association between Personal Abiotic Airborne Exposures and Body Composition Changes among Healthy Adults (60-69 Years Old): A Combined Exposome-Wide and Lipidome Mediation Approach from the China BAPE Study. ENVIRONMENTAL HEALTH PERSPECTIVES 2024; 132:77005. [PMID: 39028628 PMCID: PMC11259245 DOI: 10.1289/ehp13865] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 05/25/2024] [Accepted: 06/24/2024] [Indexed: 07/21/2024]
Abstract
BACKGROUND Evidence suggested that abiotic airborne exposures may be associated with changes in body composition. However, more evidence is needed to identify key pollutants linked to adverse health effects and their underlying biomolecular mechanisms, particularly in sensitive older adults. OBJECTIVES Our research aimed to systematically assess the relationship between abiotic airborne exposures and changes in body composition among healthy older adults, as well as the potential mediating mechanisms through the serum lipidome. METHODS From September 2018 to January 2019, we conducted a monthly survey among 76 healthy adults (60-69 years old) in the China Biomarkers of Air Pollutant Exposure (BAPE) study, measuring their personal exposures to 632 abiotic airborne pollutions using MicroPEM and the Fresh Air wristband, 18 body composition indicators from the InBody 770 device, and lipidomics from venous blood samples. We used an exposome-wide association study (ExWAS) and deletion/substitution/addition (DSA) model to unravel complex associations between exposure to contaminant mixtures and body composition, a Bayesian kernel machine regression (BKMR) model to assess the overall effect of key exposures on body composition, and mediation analysis to identify lipid intermediators. RESULTS The ExWAS and DSA model identified that 2,4,5-T methyl ester (2,4,5-TME), 9,10-Anthracenedione (ATQ), 4b,8-dimethyl-2-isopropylphenanthrene, and 4b,5,6,7,8,8a,9,10-octahydro-(DMIP) were associated with increased body fat mass (BFM), fat mass indicators (FMI), percent body fat (PBF), and visceral fat area (VFA) in healthy older adults [Bonferroni-Hochberg false discovery rate ( FD R BH ) < 0.05 ]. The BKMR model demonstrated a positive correlation between contaminants (anthracene, ATQ, copaene, di-epi-α -cedrene, and DMIP) with VFA. Mediation analysis revealed that phosphatidylcholine [PC, PC(16:1e/18:1), PC(16:2e/18:0)] and sphingolipid [SM, SM(d18:2/24:1)] mediated a significant portion, ranging from 12.27% to 26.03% (p-value < 0.05 ), of the observed increase in VFA. DISCUSSION Based on the evidence from multiple model results, ATQ and DMIP were statistically significantly associated with the increased VFA levels of healthy older adults, potentially regulated through lipid intermediators. These findings may have important implications for identifying potentially harmful environmental chemicals and developing targeted strategies for the control and prevention of chronic diseases in the future, particularly as the global population is rapidly aging. https://doi.org/10.1289/EHP13865.
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Affiliation(s)
- Peijie Sun
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- Department of Toxicology, School of Public Health, China Medical University, Shenyang, China
| | - Xiaojie Guo
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
| | - Enmin Ding
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Chenfeng Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- Department of Occupational Health and Environment Health, School of Public Health, Anhui Medical University, Hefei, Anhui, China
| | - Huimin Ren
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- Department of Toxicology, School of Public Health, China Medical University, Shenyang, China
| | - Yibo Xu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, China
| | - Jiankun Qian
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- Department of Toxicology, School of Public Health, China Medical University, Shenyang, China
| | - Fuchang Deng
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Wanying Shi
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Haoran Dong
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Elizabeth Z. Lin
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, Connecticut, USA
| | - Pengfei Guo
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, Connecticut, USA
| | - Jianlong Fang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Qian Zhang
- Chinese Center for Disease Control and Prevention, National Institute for Nutrition and Health, Beijing, China
| | - Wenhua Zhao
- Chinese Center for Disease Control and Prevention, National Institute for Nutrition and Health, Beijing, China
| | - Shilu Tong
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- School of Public Health and Social Work, Queensland University of Technology, Brisbane, Australia
| | - Xiaobo Lu
- Department of Toxicology, School of Public Health, China Medical University, Shenyang, China
| | - Krystal J. Godri Pollitt
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, Connecticut, USA
| | - Xiaoming Shi
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Song Tang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
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4
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Rutter LA, Cope H, MacKay MJ, Herranz R, Das S, Ponomarev SA, Costes SV, Paul AM, Barker R, Taylor DM, Bezdan D, Szewczyk NJ, Muratani M, Mason CE, Giacomello S. Astronaut omics and the impact of space on the human body at scale. Nat Commun 2024; 15:4952. [PMID: 38862505 PMCID: PMC11166943 DOI: 10.1038/s41467-024-47237-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2023] [Accepted: 03/22/2024] [Indexed: 06/13/2024] Open
Abstract
Future multi-year crewed planetary missions will motivate advances in aerospace nutrition and telehealth. On Earth, the Human Cell Atlas project aims to spatially map all cell types in the human body. Here, we propose that a parallel Human Cell Space Atlas could serve as an openly available, global resource for space life science research. As humanity becomes increasingly spacefaring, high-resolution omics on orbit could permit an advent of precision spaceflight healthcare. Alongside the scientific potential, we consider the complex ethical, cultural, and legal challenges intrinsic to the human space omics discipline, and how philosophical frameworks may benefit from international perspectives.
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Affiliation(s)
- Lindsay A Rutter
- Transborder Medical Research Center, University of Tsukuba, 305-8575, Tsukuba, Japan
- Department of Genome Biology, Institute of Medicine, University of Tsukuba, 305-8575, Tsukuba, Japan
- School of Chemistry, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Henry Cope
- School of Medicine, University of Nottingham, Derby, DE22 3DT, UK
| | - Matthew J MacKay
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, 10065, USA
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, 10021, USA
- The WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, New York, NY, 10065, USA
| | - Raúl Herranz
- Centro de Investigaciones Biológicas "Margarita Salas" (CSIC), Ramiro de Maeztu 9, Madrid, 28040, Spain
| | - Saswati Das
- Department of Biochemistry, Atal Bihari Vajpayee Institute of Medical Sciences & Dr. Ram Manohar Lohia Hospital, New Delhi, 110001, India
| | - Sergey A Ponomarev
- Department of Immunology and Microbiology, Institute for the Biomedical Problems, Russian Academy of Sciences, 123007, Moscow, Russia
| | - Sylvain V Costes
- Space Biosciences Division, NASA Ames Research Center, Moffett Field, CA, 94035, USA
| | - Amber M Paul
- Embry-Riddle Aeronautical University, Department of Human Factors and Behavioral Neurobiology, Daytona Beach, FL, 32114, USA
| | - Richard Barker
- Department of Botany, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Deanne M Taylor
- Department of Biomedical and Health Informatics, The Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Daniela Bezdan
- Institute of Medical Genetics and Applied Genomics, University of Tübingen, Tübingen, 72076, Germany
- NGS Competence Center Tübingen (NCCT), University of Tübingen, Tübingen, 72076, Germany
- yuri GmbH, Meckenbeuren, 88074, Germany
| | - Nathaniel J Szewczyk
- School of Medicine, University of Nottingham, Derby, DE22 3DT, UK
- Ohio Musculoskeletal and Neurological Institute (OMNI), Heritage College of Osteopathic Medicine, Ohio University, Athens, OH, 45701, USA
| | - Masafumi Muratani
- Transborder Medical Research Center, University of Tsukuba, 305-8575, Tsukuba, Japan
- Department of Genome Biology, Institute of Medicine, University of Tsukuba, 305-8575, Tsukuba, Japan
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, 10065, USA.
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, 10021, USA.
- The WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, New York, NY, 10065, USA.
- The Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, 10065, USA.
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5
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Garmendia J, Cebollero‐Rivas P. Environmental exposures, the oral-lung axis and respiratory health: The airway microbiome goes on stage for the personalized management of human lung function. Microb Biotechnol 2024; 17:e14506. [PMID: 38881505 PMCID: PMC11180993 DOI: 10.1111/1751-7915.14506] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2024] [Revised: 05/19/2024] [Accepted: 05/24/2024] [Indexed: 06/18/2024] Open
Abstract
The human respiratory system is constantly exposed to environmental stimuli, sometimes including toxicants, which can trigger dysregulated lung immune responses that lead to respiratory symptoms, impaired lung function and airway diseases. Evidence supports that the microbiome in the lungs has an indispensable role in respiratory health and disease, acting as a local gatekeeper that mediates the interaction between the environmental cues and respiratory health. Moreover, the microbiome in the lungs is intimately intertwined with the oral microbiome through the oral-lung axis. Here, we discuss the intricate three-way relationship between (i) cigarette smoking, which has strong effects on the microbial community structure of the lung; (ii) microbiome dysbiosis and disease in the oral cavity; and (iii) microbiome dysbiosis in the lung and its causal role in patients suffering chronic obstructive pulmonary disease (COPD), a leading cause of morbidity and mortality worldwide. We highlight exciting outcomes arising from recently established interactions in the airway between environmental exposures, microbiome, metabolites-functional attributes and the host, as well as how these associations have the potential to predict the respiratory health status of the host through an airway microbiome health index. For completion, we argue that incorporating (synthetic) microbial community ecology in our contemporary understanding of lung disease presents challenges and also rises novel opportunities to exploit the oral-lung axis and its microbiome towards innovative airway disease diagnostics, prognostics, patient stratification and microbiota-targeted clinical interventions in the context of current therapies.
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Affiliation(s)
- Junkal Garmendia
- Instituto de AgrobiotecnologíaConsejo Superior de Investigaciones Científicas (IdAB‐CSIC)‐Gobierno de NavarraMutilvaSpain
- Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES)MadridSpain
| | - Pilar Cebollero‐Rivas
- Servicio de NeumologíaHospital Universitario de NavarraNavarraSpain
- Universidad Pública de Navarra (UPNa)NavarraSpain
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6
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Boye C, Nirmalan S, Ranjbaran A, Luca F. Genotype × environment interactions in gene regulation and complex traits. Nat Genet 2024; 56:1057-1068. [PMID: 38858456 DOI: 10.1038/s41588-024-01776-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 04/25/2024] [Indexed: 06/12/2024]
Abstract
Genotype × environment interactions (GxE) have long been recognized as a key mechanism underlying human phenotypic variation. Technological developments over the past 15 years have dramatically expanded our appreciation of the role of GxE in both gene regulation and complex traits. The richness and complexity of these datasets also required parallel efforts to develop robust and sensitive statistical and computational approaches. Although our understanding of the genetic architecture of molecular and complex traits has been maturing, a large proportion of complex trait heritability remains unexplained. Furthermore, there are increasing efforts to characterize the effect of environmental exposure on human health. We therefore review GxE in human gene regulation and complex traits, advocating for a comprehensive approach that jointly considers genetic and environmental factors in human health and disease.
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Affiliation(s)
- Carly Boye
- Center for Molecular Medicine and Genetics, Wayne State University, Detroit, MI, US
| | - Shreya Nirmalan
- Center for Molecular Medicine and Genetics, Wayne State University, Detroit, MI, US
| | - Ali Ranjbaran
- Center for Molecular Medicine and Genetics, Wayne State University, Detroit, MI, US
| | - Francesca Luca
- Center for Molecular Medicine and Genetics, Wayne State University, Detroit, MI, US.
- Department of Obstetrics and Gynecology, Wayne State University, Detroit, MI, US.
- Department of Biology, University of Rome "Tor Vergata", Rome, Italy.
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7
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Zhou X, Shen X, Johnson JS, Spakowicz DJ, Agnello M, Zhou W, Avina M, Honkala A, Chleilat F, Chen SJ, Cha K, Leopold S, Zhu C, Chen L, Lyu L, Hornburg D, Wu S, Zhang X, Jiang C, Jiang L, Jiang L, Jian R, Brooks AW, Wang M, Contrepois K, Gao P, Rose SMSF, Tran TDB, Nguyen H, Celli A, Hong BY, Bautista EJ, Dorsett Y, Kavathas PB, Zhou Y, Sodergren E, Weinstock GM, Snyder MP. Longitudinal profiling of the microbiome at four body sites reveals core stability and individualized dynamics during health and disease. Cell Host Microbe 2024; 32:506-526.e9. [PMID: 38479397 PMCID: PMC11022754 DOI: 10.1016/j.chom.2024.02.012] [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: 12/05/2023] [Revised: 01/23/2024] [Accepted: 02/20/2024] [Indexed: 03/26/2024]
Abstract
To understand the dynamic interplay between the human microbiome and host during health and disease, we analyzed the microbial composition, temporal dynamics, and associations with host multi-omics, immune, and clinical markers of microbiomes from four body sites in 86 participants over 6 years. We found that microbiome stability and individuality are body-site specific and heavily influenced by the host. The stool and oral microbiome are more stable than the skin and nasal microbiomes, possibly due to their interaction with the host and environment. We identify individual-specific and commonly shared bacterial taxa, with individualized taxa showing greater stability. Interestingly, microbiome dynamics correlate across body sites, suggesting systemic dynamics influenced by host-microbial-environment interactions. Notably, insulin-resistant individuals show altered microbial stability and associations among microbiome, molecular markers, and clinical features, suggesting their disrupted interaction in metabolic disease. Our study offers comprehensive views of multi-site microbial dynamics and their relationship with host health and disease.
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Affiliation(s)
- Xin Zhou
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA; Stanford Center for Genomics and Personalized Medicine, Stanford, CA 94305, USA; Stanford Diabetes Research Center, Stanford, CA 94305, USA; The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA
| | - Xiaotao Shen
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA; Stanford Center for Genomics and Personalized Medicine, Stanford, CA 94305, USA
| | - Jethro S Johnson
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA; Oxford Centre for Microbiome Studies, Kennedy Institute of Rheumatology, University of Oxford, Roosevelt Drive, Headington, Oxford OX3 7FY, UK
| | - Daniel J Spakowicz
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA; Division of Medical Oncology, Ohio State University Wexner Medical Center, James Cancer Hospital and Solove Research Institute, Columbus, OH 43210, USA
| | | | - Wenyu Zhou
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA; Stanford Center for Genomics and Personalized Medicine, Stanford, CA 94305, USA
| | - Monica Avina
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Alexander Honkala
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA; Stanford Healthcare Innovation Labs, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR 97239, USA
| | - Faye Chleilat
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Shirley Jingyi Chen
- Stanford Healthcare Innovation Labs, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Kexin Cha
- Stanford Healthcare Innovation Labs, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Shana Leopold
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA; Department of Immunobiology, Yale University School of Medicine, New Haven, CT 06520, USA
| | - Chenchen Zhu
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Lei Chen
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA; Shanghai Institute of Immunology, Shanghai Jiao Tong University, Shanghai 200240, PRC
| | - Lin Lyu
- Shanghai Institute of Immunology, Shanghai Jiao Tong University, Shanghai 200240, PRC
| | - Daniel Hornburg
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Si Wu
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Xinyue Zhang
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Chao Jiang
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA; Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang 310058, PRC
| | - Liuyiqi Jiang
- Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang 310058, PRC
| | - Lihua Jiang
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Ruiqi Jian
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Andrew W Brooks
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Meng Wang
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Kévin Contrepois
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Peng Gao
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | | | | | - Hoan Nguyen
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA
| | - Alessandra Celli
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Bo-Young Hong
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA; Woody L Hunt School of Dental Medicine, Texas Tech University Health Science Center, El Paso, TX 79905, USA
| | - Eddy J Bautista
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA; Corporación Colombiana de Investigación Agropecuaria (Agrosavia), Headquarters-Mosquera, Cundinamarca 250047, Colombia
| | - Yair Dorsett
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA; Department of Medicine, University of Connecticut Health Center, Farmington, CT 06032, USA
| | - Paula B Kavathas
- Department of Immunobiology, Yale University School of Medicine, New Haven, CT 06520, USA; Department of Laboratory Medicine, Yale University School of Medicine, New Haven, CT 06520, USA
| | - Yanjiao Zhou
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA; Department of Medicine, University of Connecticut Health Center, Farmington, CT 06032, USA
| | - Erica Sodergren
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA
| | | | - Michael P Snyder
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA; Stanford Center for Genomics and Personalized Medicine, Stanford, CA 94305, USA; Stanford Diabetes Research Center, Stanford, CA 94305, USA; Stanford Healthcare Innovation Labs, Stanford University School of Medicine, Stanford, CA 94305, USA.
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8
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Hu W, Hsiao YC, Morrison-Welch N, Lamberti S, Liu CW, Lin W, Engel SM, Lu K, Zylka MJ. Co-detection of azoxystrobin and thiabendazole fungicides in mold and mildew resistant wallboards and in children. Heliyon 2024; 10:e27980. [PMID: 38509915 PMCID: PMC10951607 DOI: 10.1016/j.heliyon.2024.e27980] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2023] [Revised: 03/08/2024] [Accepted: 03/08/2024] [Indexed: 03/22/2024] Open
Abstract
The study measured the levels of azoxystrobin (AZ) and thiabendazole (TBZ) in wallboards and metabolite levels of these fungicides in children. The paper covering of wallboard samples contained a higher concentration of AZ and TBZ than the gypsum core, and similar amounts (w/w) of these two fungicides were present in the samples. These data suggest that commercial products containing a 1:1 (w/w) amount of AZ and TBZ, such as Sporgard® WB or Azo Tech™, were applied to the wallboard paper. This is the first detection of TBZ in mold-and-mildew resistant wallboards. The TBZ metabolite, 5OH-TBZ, was detected in 48% of urine samples collected from children aged 40-84 months, and was co-detected with AZ-acid, a common AZ metabolite, in 37.5% of the urine samples. The detection frequency of 5OH-TBZ was positively associated with the detection frequency of AZ-acid. These findings suggest that certain types of wallboards used in homes and commercial buildings may be a potential source of co-exposure to AZ and TBZ in humans.
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Affiliation(s)
- Wenxin Hu
- UNC Neuroscience Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
- Department of Cell Biology & Physiology, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Yun-Chung Hsiao
- Department of Environmental Sciences and Engineering, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Nikolas Morrison-Welch
- UNC Neuroscience Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
- Department of Cell Biology & Physiology, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Sophia Lamberti
- UNC Neuroscience Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
- Department of Cell Biology & Physiology, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Chih-Wei Liu
- Department of Environmental Sciences and Engineering, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Weili Lin
- Biomedical Research Imaging Center and Department of Radiology, The University of North Carolina at Chapel Hill, North Carolina, USA
| | - Stephanie M. Engel
- Department of Epidemiology, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Kun Lu
- Department of Environmental Sciences and Engineering, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Mark J. Zylka
- UNC Neuroscience Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
- Department of Cell Biology & Physiology, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
- Carolina Institute for Developmental Disabilities, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
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9
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Peng C, Chen Q, Tan S, Shen X, Jiang C. Generalized reporter score-based enrichment analysis for omics data. Brief Bioinform 2024; 25:bbae116. [PMID: 38546324 PMCID: PMC10976918 DOI: 10.1093/bib/bbae116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 01/25/2024] [Accepted: 03/01/2024] [Indexed: 06/15/2024] Open
Abstract
Enrichment analysis contextualizes biological features in pathways to facilitate a systematic understanding of high-dimensional data and is widely used in biomedical research. The emerging reporter score-based analysis (RSA) method shows more promising sensitivity, as it relies on P-values instead of raw values of features. However, RSA cannot be directly applied to multi-group and longitudinal experimental designs and is often misused due to the lack of a proper tool. Here, we propose the Generalized Reporter Score-based Analysis (GRSA) method for multi-group and longitudinal omics data. A comparison with other popular enrichment analysis methods demonstrated that GRSA had increased sensitivity across multiple benchmark datasets. We applied GRSA to microbiome, transcriptome and metabolome data and discovered new biological insights in omics studies. Finally, we demonstrated the application of GRSA beyond functional enrichment using a taxonomy database. We implemented GRSA in an R package, ReporterScore, integrating with a powerful visualization module and updatable pathway databases, which is available on the Comprehensive R Archive Network (https://cran.r-project.org/web/packages/ReporterScore). We believe that the ReporterScore package will be a valuable asset for broad biomedical research fields.
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Affiliation(s)
- Chen Peng
- MOE Key Laboratory of Biosystems Homeostasis & Protection, and Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang 310030, China
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Qiong Chen
- MOE Key Laboratory of Biosystems Homeostasis & Protection, and Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang 310030, China
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Shangjin Tan
- BGI Research, Wuhan, Hubei 430074, China
- BGI Research, Shenzhen, Guangdong 518083, China
| | - Xiaotao Shen
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Chao Jiang
- MOE Key Laboratory of Biosystems Homeostasis & Protection, and Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang 310030, China
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
- Center for Life Sciences, Shaoxing Institute, Zhejiang University, Shaoxing, Zhejiang 321000, China
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10
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Huang Z, Peng C, Rong Z, Jiang L, Li Y, Feng Y, Chen S, Xie C, Jiang C. Longitudinal Mapping of Personal Biotic and Abiotic Exposomes and Transcriptome in Underwater Confined Space Using Wearable Passive Samplers. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:5229-5243. [PMID: 38466915 DOI: 10.1021/acs.est.3c09379] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/13/2024]
Abstract
Silicone-based passive samplers, commonly paired with gas chromatography-mass spectrometry (GC-MS) analysis, are increasingly utilized for personal exposure assessments. However, its compatibility with the biotic exposome remains underexplored. In this study, we introduce the wearable silicone-based AirPie passive sampler, coupled with nontargeted liquid chromatography with high-resolution tandem mass spectrometry (LC-HRMS/MS), GC-HRMS, and metagenomic shotgun sequencing methods, offering a comprehensive view of personalized airborne biotic and abiotic exposomes. We applied the AirPie samplers to 19 participants in a unique deep underwater confined environment, annotating 4,390 chemical and 2,955 microbial exposures, integrated with corresponding transcriptomic data. We observed significant shifts in environmental exposure and gene expression upon entering this unique environment. We noted increased exposure to pollutants, such as benzenoids, polycyclic aromatic hydrocarbons (PAHs), opportunistic pathogens, and associated antibiotic-resistance genes (ARGs). Transcriptomic analyses revealed the activation of neurodegenerative disease-related pathways, mostly related to chemical exposure, and the repression of immune-related pathways, linked to both biological and chemical exposures. In summary, we provided a comprehensive, longitudinal exposome map of the unique environment and underscored the intricate linkages between external exposures and human health. We believe that the AirPie sampler and associated analytical methods will have broad applications in exposome and precision medicine.
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Affiliation(s)
- Zinuo Huang
- MOE Key Laboratory of Biosystems Homeostasis and Protection, and Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang 310058, China
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
- Center for Life Sciences, Shaoxing Institute, Zhejiang University, Shaoxing, Zhejiang 321000, China
| | - Chen Peng
- MOE Key Laboratory of Biosystems Homeostasis and Protection, and Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang 310058, China
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Zixin Rong
- MOE Key Laboratory of Biosystems Homeostasis and Protection, and Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Liuyiqi Jiang
- MOE Key Laboratory of Biosystems Homeostasis and Protection, and Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang 310058, China
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Yueer Li
- MOE Key Laboratory of Biosystems Homeostasis and Protection, and Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang 310058, China
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Yue Feng
- School of Exercise and Health, Shanghai University of Sport, Shanghai 200438, China
| | | | | | - Chao Jiang
- MOE Key Laboratory of Biosystems Homeostasis and Protection, and Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang 310058, China
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
- Center for Life Sciences, Shaoxing Institute, Zhejiang University, Shaoxing, Zhejiang 321000, China
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11
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YOU L, SUN G, YU D, LIU X, XU G. [New advances in exposomics-analysis methods and research paradigms based on chromatography-mass spectrometry]. Se Pu 2024; 42:109-119. [PMID: 38374591 PMCID: PMC10877474 DOI: 10.3724/sp.j.1123.2023.12001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Indexed: 02/21/2024] Open
Abstract
The occurrence and development of human diseases are influenced by both genetic and environmental factors. Research models that describe disease occurrence only from the perspective of genetics present certain limitations. In recent years, effects of environment factors on the occurrence and development of diseases have attracted extensive attentions. Exposomics focuses on the measurement of all exposure factors in an individual's life and how these factors are related to disease development. Exposomics provides new ideas to promote studies on the relationship between human health and environmental factors. Environmental exposures are characterized with different physical and chemical properties, as well as very low concentrations in vivo, which contribute great challenges in the comprehensive measurement of chemical residues in the human body. Chromatography-mass spectrometry-based technologies combine the high-efficiency separation ability of chromatography with the high resolution and sensitive detection characteristics of mass spectrometry; the combination of these techniques can achieve the high-coverage, high-throughput, and sensitive detection of environmental exposures, thus providing a powerful tool for measuring chemical exposures. Exposomics-analysis methods based on chromatography-mass spectrometry mainly include targeted quantitative analysis, suspect screening, and non-targeted screening. To explore the relationship between environmental exposure and the occurrence and development of diseases, researchers have developed research paradigms, including exposome wide association study, mixed-exposure study, exposomics and multi-omics (genome, transcriptome, proteome, metabolome)-association study, and so on. The emergence of these methods has brought about unprecedented developments in exposomics studies. In this manuscript, analytical methods based on chromatography-mass spectrometry, exposomics research paradigms, and their relevant prospects are reviewed.
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12
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Zhou X, Shen X, Johnson JS, Spakowicz DJ, Agnello M, Zhou W, Avina M, Honkala A, Chleilat F, Chen SJ, Cha K, Leopold S, Zhu C, Chen L, Lyu L, Hornburg D, Wu S, Zhang X, Jiang C, Jiang L, Jiang L, Jian R, Brooks AW, Wang M, Contrepois K, Gao P, Schüssler-Fiorenza Rose SM, Binh Tran TD, Nguyen H, Celli A, Hong BY, Bautista EJ, Dorsett Y, Kavathas P, Zhou Y, Sodergren E, Weinstock GM, Snyder MP. Longitudinal profiling of the microbiome at four body sites reveals core stability and individualized dynamics during health and disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.01.577565. [PMID: 38352363 PMCID: PMC10862915 DOI: 10.1101/2024.02.01.577565] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/26/2024]
Abstract
To understand dynamic interplay between the human microbiome and host during health and disease, we analyzed the microbial composition, temporal dynamics, and associations with host multi-omics, immune and clinical markers of microbiomes from four body sites in 86 participants over six years. We found that microbiome stability and individuality are body-site-specific and heavily influenced by the host. The stool and oral microbiome were more stable than the skin and nasal microbiomes, possibly due to their interaction with the host and environment. Also, we identified individual-specific and commonly shared bacterial taxa, with individualized taxa showing greater stability. Interestingly, microbiome dynamics correlated across body sites, suggesting systemic coordination influenced by host-microbial-environment interactions. Notably, insulin-resistant individuals showed altered microbial stability and associations between microbiome, molecular markers, and clinical features, suggesting their disrupted interaction in metabolic disease. Our study offers comprehensive views of multi-site microbial dynamics and their relationship with host health and disease. Study Highlights The stability of the human microbiome varies among individuals and body sites.Highly individualized microbial genera are more stable over time.At each of the four body sites, systematic interactions between the environment, the host and bacteria can be detected.Individuals with insulin resistance have lower microbiome stability, a more diversified skin microbiome, and significantly altered host-microbiome interactions.
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13
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Balcells C, Xu Y, Gil-Solsona R, Maitre L, Gago-Ferrero P, Keun HC. Blurred lines: Crossing the boundaries between the chemical exposome and the metabolome. Curr Opin Chem Biol 2024; 78:102407. [PMID: 38086287 DOI: 10.1016/j.cbpa.2023.102407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 10/22/2023] [Accepted: 11/09/2023] [Indexed: 02/09/2024]
Abstract
The aetiology of every human disease lies in a combination of genetic and environmental factors, each contributing in varying proportions. While genomics investigates the former, a comparable holistic paradigm was proposed for environmental exposures in 2005, marking the onset of exposome research. Since then, the exposome definition has broadened to include a wide array of physical, chemical, and psychosocial factors that interact with the human body and potentially alter the epigenome, the transcriptome, the proteome, and the metabolome. The chemical exposome, deeply intertwined with the metabolome, includes all small molecules originating from diet as well as pharmaceuticals, personal care and consumer products, or pollutants in air and water. The set of techniques to interrogate these exposures, primarily mass spectrometry and nuclear magnetic resonance spectroscopy, are also extensively used in metabolomics. Recent advances in untargeted metabolomics using high resolution mass spectrometry have paved the way for the development of methods able to provide in depth characterisation of both the internal chemical exposome and the endogenous metabolome simultaneously. Herein we review the available tools, databases, and workflows currently available for such work, and discuss how these can bridge the gap between the study of the metabolome and the exposome.
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Affiliation(s)
- Cristina Balcells
- Institute of Developmental and Reproductive Biology (IRDB), Division of Cancer, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, UK.
| | - Yitao Xu
- Institute of Developmental and Reproductive Biology (IRDB), Division of Cancer, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, UK
| | - Rubén Gil-Solsona
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona, Spain
| | - Léa Maitre
- ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Pablo Gago-Ferrero
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona, Spain
| | - Hector C Keun
- Institute of Developmental and Reproductive Biology (IRDB), Division of Cancer, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, UK.
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14
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Shen X, Kellogg R, Panyard DJ, Bararpour N, Castillo KE, Lee-McMullen B, Delfarah A, Ubellacker J, Ahadi S, Rosenberg-Hasson Y, Ganz A, Contrepois K, Michael B, Simms I, Wang C, Hornburg D, Snyder MP. Multi-omics microsampling for the profiling of lifestyle-associated changes in health. Nat Biomed Eng 2024; 8:11-29. [PMID: 36658343 PMCID: PMC10805653 DOI: 10.1038/s41551-022-00999-8] [Citation(s) in RCA: 27] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 12/14/2022] [Indexed: 01/21/2023]
Abstract
Current healthcare practices are reactive and use limited physiological and clinical information, often collected months or years apart. Moreover, the discovery and profiling of blood biomarkers in clinical and research settings are constrained by geographical barriers, the cost and inconvenience of in-clinic venepuncture, low sampling frequency and the low depth of molecular measurements. Here we describe a strategy for the frequent capture and analysis of thousands of metabolites, lipids, cytokines and proteins in 10 μl of blood alongside physiological information from wearable sensors. We show the advantages of such frequent and dense multi-omics microsampling in two applications: the assessment of the reactions to a complex mixture of dietary interventions, to discover individualized inflammatory and metabolic responses; and deep individualized profiling, to reveal large-scale molecular fluctuations as well as thousands of molecular relationships associated with intra-day physiological variations (in heart rate, for example) and with the levels of clinical biomarkers (specifically, glucose and cortisol) and of physical activity. Combining wearables and multi-omics microsampling for frequent and scalable omics may facilitate dynamic health profiling and biomarker discovery.
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Affiliation(s)
- Xiaotao Shen
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Center for Genomics and Personalized Medicine, Stanford, CA, USA
| | - Ryan Kellogg
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Center for Genomics and Personalized Medicine, Stanford, CA, USA
| | - Daniel J Panyard
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Center for Genomics and Personalized Medicine, Stanford, CA, USA
| | - Nasim Bararpour
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Center for Genomics and Personalized Medicine, Stanford, CA, USA
| | - Kevin Erazo Castillo
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Center for Genomics and Personalized Medicine, Stanford, CA, USA
| | - Brittany Lee-McMullen
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Center for Genomics and Personalized Medicine, Stanford, CA, USA
| | - Alireza Delfarah
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Center for Genomics and Personalized Medicine, Stanford, CA, USA
| | - Jessalyn Ubellacker
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Sara Ahadi
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Center for Genomics and Personalized Medicine, Stanford, CA, USA
| | - Yael Rosenberg-Hasson
- Human Immune Monitoring Center, Microbiology and Immunology, Stanford University Medical Center, Stanford, CA, USA
| | - Ariel Ganz
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Center for Genomics and Personalized Medicine, Stanford, CA, USA
| | - Kévin Contrepois
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Center for Genomics and Personalized Medicine, Stanford, CA, USA
| | - Basil Michael
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Center for Genomics and Personalized Medicine, Stanford, CA, USA
| | - Ian Simms
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Center for Genomics and Personalized Medicine, Stanford, CA, USA
| | - Chuchu Wang
- Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA
| | - Daniel Hornburg
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Center for Genomics and Personalized Medicine, Stanford, CA, USA
| | - Michael P Snyder
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
- Stanford Center for Genomics and Personalized Medicine, Stanford, CA, USA.
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15
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Zhang RM, Lian XL, Shi LW, Jiang L, Chen SS, Haung WQ, Wu JE, Wu FJ, Sun J, Liao XP, Chong YX, Liu YH, Jiang C. Dynamic human exposure to airborne bacteria-associated antibiotic resistomes revealed by longitudinal personal monitoring data. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 904:166799. [PMID: 37673270 DOI: 10.1016/j.scitotenv.2023.166799] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 08/26/2023] [Accepted: 09/01/2023] [Indexed: 09/08/2023]
Abstract
Airborne antibiotic-resistant bacteria (ARB) can critically impact human health. We performed resistome profiling of 283 personal airborne exposure samples from 15 participants spanning 890 days and 66 locations. We found a greater diversity and abundance of airborne bacteria community and antibiotic resistomes in spring than in winter, and temperature contributed largely to the difference. A total of 1123 bacterial genera were detected, with 16 genera dominating. Of which, 7/16 were annotated as major antibiotic resistance gene (ARG) hosts. The participants were exposed to a highly dynamic collection of ARGs, including 322 subtypes conferring resistance to 18 antibiotic classes dominated by multidrug, macrolide-lincosamide-streptogramin, β-lactam, and fosfomycin. Unlike the overall community-level bacteria exposure, an extremely high abundance of specific ARG subtypes, including lunA and qacG, were found in some samples. Staphylococcus was the predominant genus in the bacterial community, serving as a primary bacterial host for the ARGs. The annotation of ARG-carrying contigs indicated that humans and companion animals were major reservoirs for ARG-carrying Staphylococcus. This study contextualized airborne antibiotic resistomes in the precision medicine framework through longitudinal personal monitoring, which can have broad implications for human health.
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Affiliation(s)
- Rong-Min Zhang
- Guangdong Provincial Key Laboratory of Veterinary Pharmaceutics Development and Safety Evaluation, South China Agricultural University, China; Guangdong Laboratory for Lingnan Modern Agriculture, National Risk Assessment Laboratory for Antimicrobial Resistance of Animal Original Bacteria, College of Veterinary Medicine, South China Agricultural University, Guangzhou, China
| | - Xin-Lei Lian
- Guangdong Provincial Key Laboratory of Veterinary Pharmaceutics Development and Safety Evaluation, South China Agricultural University, China; Guangdong Laboratory for Lingnan Modern Agriculture, National Risk Assessment Laboratory for Antimicrobial Resistance of Animal Original Bacteria, College of Veterinary Medicine, South China Agricultural University, Guangzhou, China
| | - Li-Wei Shi
- Guangdong Provincial Key Laboratory of Veterinary Pharmaceutics Development and Safety Evaluation, South China Agricultural University, China; Guangdong Laboratory for Lingnan Modern Agriculture, National Risk Assessment Laboratory for Antimicrobial Resistance of Animal Original Bacteria, College of Veterinary Medicine, South China Agricultural University, Guangzhou, China
| | - Liuyiqi Jiang
- Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang, China
| | - Shan-Shan Chen
- Guangdong Provincial Key Laboratory of Veterinary Pharmaceutics Development and Safety Evaluation, South China Agricultural University, China; Guangdong Laboratory for Lingnan Modern Agriculture, National Risk Assessment Laboratory for Antimicrobial Resistance of Animal Original Bacteria, College of Veterinary Medicine, South China Agricultural University, Guangzhou, China
| | - Wen-Qing Haung
- Guangdong Provincial Key Laboratory of Veterinary Pharmaceutics Development and Safety Evaluation, South China Agricultural University, China; Guangdong Laboratory for Lingnan Modern Agriculture, National Risk Assessment Laboratory for Antimicrobial Resistance of Animal Original Bacteria, College of Veterinary Medicine, South China Agricultural University, Guangzhou, China
| | - Jia-En Wu
- Guangdong Provincial Key Laboratory of Veterinary Pharmaceutics Development and Safety Evaluation, South China Agricultural University, China; Guangdong Laboratory for Lingnan Modern Agriculture, National Risk Assessment Laboratory for Antimicrobial Resistance of Animal Original Bacteria, College of Veterinary Medicine, South China Agricultural University, Guangzhou, China
| | - Fei-Jing Wu
- School of Life Sciences, South China Normal University, Guangzhou 510642, China
| | - Jian Sun
- Guangdong Provincial Key Laboratory of Veterinary Pharmaceutics Development and Safety Evaluation, South China Agricultural University, China; Guangdong Laboratory for Lingnan Modern Agriculture, National Risk Assessment Laboratory for Antimicrobial Resistance of Animal Original Bacteria, College of Veterinary Medicine, South China Agricultural University, Guangzhou, China
| | - Xiao-Ping Liao
- Guangdong Provincial Key Laboratory of Veterinary Pharmaceutics Development and Safety Evaluation, South China Agricultural University, China; Guangdong Laboratory for Lingnan Modern Agriculture, National Risk Assessment Laboratory for Antimicrobial Resistance of Animal Original Bacteria, College of Veterinary Medicine, South China Agricultural University, Guangzhou, China
| | - Yun-Xiao Chong
- Guangdong Provincial Key Laboratory of Agricultural & Rural Pollution Abatement and Environmental Safety, College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China
| | - Ya-Hong Liu
- Guangdong Provincial Key Laboratory of Veterinary Pharmaceutics Development and Safety Evaluation, South China Agricultural University, China; Guangdong Laboratory for Lingnan Modern Agriculture, National Risk Assessment Laboratory for Antimicrobial Resistance of Animal Original Bacteria, College of Veterinary Medicine, South China Agricultural University, Guangzhou, China
| | - Chao Jiang
- Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang, China.
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16
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Gangneux JP, Rhodes JL, Papon N. Airway microbiome: environmental exposure-respiratory health nexus. Trends Mol Med 2023; 29:875-877. [PMID: 37690859 DOI: 10.1016/j.molmed.2023.08.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 08/27/2023] [Accepted: 08/28/2023] [Indexed: 09/12/2023]
Abstract
Toxicants such as smoke, biofuel, and pollutants constantly challenge our respiratory health, but little is known about the pathophysiological processes involved. In a new report, Lin et al. provide evidence that our bacterial and fungal lung populations orchestrate the interplay between environmental exposure and lung functions, thereby conditioning health outcomes.
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Affiliation(s)
- Jean-Pierre Gangneux
- Univ Rennes, CHU Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, F-35000 Rennes, France; Laboratory of Parasitology and Medical Mycology, European Confederation of Medical Mycology (ECMM) Excellence Center, Centre National de Référence Aspergilloses Chroniques, Rennes Teaching Hospital, F-35000 Rennes, France.
| | - Johanna L Rhodes
- MRC Centre for Global Infectious Disease Analysis, Imperial College School of Public Health, Imperial College London, South Kensington, London SW7 2BX, UK; Department of Medical Microbiology, Radboudumc, Nijmegen, The Netherlands.
| | - Nicolas Papon
- Univ Angers, Univ Brest, IRF, SFR ICAT, F-49000 Angers, France
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17
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Roos LG, Slavich GM. Wearable technologies for health research: Opportunities, limitations, and practical and conceptual considerations. Brain Behav Immun 2023; 113:444-452. [PMID: 37557962 PMCID: PMC11233111 DOI: 10.1016/j.bbi.2023.08.008] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 07/31/2023] [Accepted: 08/06/2023] [Indexed: 08/11/2023] Open
Abstract
One of the most notable limitations of laboratory-based health research is its inability to continuously monitor health-relevant physiological processes as individuals go about their daily lives. As a result, we have generated large amounts of data with unknown generalizability to real-world situations and also created a schism between where data are collected (i.e., in the lab) and where we need to intervene to prevent disease (i.e., in the field). Devices using noninvasive wearable technology are changing all of this, however, with their ability to provide high-frequency assessments of peoples' ever-changing physiological states in daily life in a manner that is relatively noninvasive, affordable, and scalable. Here, we discuss critical points that every researcher should keep in mind when using these wearables in research, spanning device and metric decisions, hardware and software selection, and data quality and sampling rate issues, using research on stress and health as an example throughout. We also address usability and participant acceptability issues, and how wearable "digital biomarker" and behavioral data can be integrated to enhance basic science and intervention studies. Finally, we summarize 10 key questions that should be addressed to make every wearable study as strong as possible. Collectively, keeping these points in mind can improve our ability to study the psychobiology of human health, and to intervene, precisely where it matters most: in peoples' daily lives.
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Affiliation(s)
- Lydia G Roos
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA.
| | - George M Slavich
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA
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18
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Gao P. Exploring Single-Cell Exposomics by Mass Spectrometry. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:12201-12209. [PMID: 37561608 PMCID: PMC10448745 DOI: 10.1021/acs.est.3c04524] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Indexed: 08/12/2023]
Abstract
Single-cell exposomics, a revolutionary approach that investigates cell-environment interactions at cellular and subcellular levels, stands distinct from conventional bulk exposomics. Leveraging advancements in mass spectrometry, it provides a detailed perspective on cellular dynamics, interactions, and responses to environmental stimuli and their impacts on human health. This work delves into this innovative realm, highlighting the nuanced interplay between environmental stressors and biological responses at cellular and subcellular levels. The application of spatial mass spectrometry in single-cell exposomics is discussed, revealing the intricate spatial organization and molecular composition within individual cells. Cell-type-specific exposomics, shedding light on distinct susceptibilities and adaptive strategies of various cell types to environmental exposures, is also examined. The Perspective further emphasizes the integration with molecular and cellular biology approaches to validate hypotheses derived from single-cell exposomics in a comprehensive biological context. Looking toward the future, we anticipate continued technological advancements and convergence with other -omics approaches and discuss implications for environmental health research, disease progression studies, and precision medicine. The final emphasis is on the need for robust computational tools and interdisciplinary collaboration to fully leverage the potential of single-cell exposomics, acknowledging the complexities inherent to this paradigm.
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Affiliation(s)
- Peng Gao
- Department
of Environmental and Occupational Health and Department of Civil and
Environmental Engineering, University of
Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
- UPMC
Hillman Cancer Center, Pittsburgh, Pennsylvania 15232, United States
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19
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Babu M, Snyder M. Multi-Omics Profiling for Health. Mol Cell Proteomics 2023; 22:100561. [PMID: 37119971 PMCID: PMC10220275 DOI: 10.1016/j.mcpro.2023.100561] [Citation(s) in RCA: 36] [Impact Index Per Article: 36.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 04/20/2023] [Accepted: 04/23/2023] [Indexed: 05/01/2023] Open
Abstract
The world has witnessed a steady rise in both non-infectious and infectious chronic diseases, prompting a cross-disciplinary approach to understand and treating disease. Current medical care focuses on treating people after they become patients rather than preventing illness, leading to high costs in treating chronic and late-stage diseases. Additionally, a "one-size-fits all" approach to health care does not take into account individual differences in genetics, environment, or lifestyle factors, decreasing the number of people benefiting from interventions. Rapid advances in omics technologies and progress in computational capabilities have led to the development of multi-omics deep phenotyping, which profiles the interaction of multiple levels of biology over time and empowers precision health approaches. This review highlights current and emerging multi-omics modalities for precision health and discusses applications in the following areas: genetic variation, cardio-metabolic diseases, cancer, infectious diseases, organ transplantation, pregnancy, and longevity/aging. We will briefly discuss the potential of multi-omics approaches in disentangling host-microbe and host-environmental interactions. We will touch on emerging areas of electronic health record and clinical imaging integration with muti-omics for precision health. Finally, we will briefly discuss the challenges in the clinical implementation of multi-omics and its future prospects.
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Affiliation(s)
- Mohan Babu
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
| | - Michael Snyder
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA.
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20
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Liang D, Li Z, Vlaanderen J, Tang Z, Jones DP, Vermeulen R, Sarnat JA. A State-of-the-Science Review on High-Resolution Metabolomics Application in Air Pollution Health Research: Current Progress, Analytical Challenges, and Recommendations for Future Direction. ENVIRONMENTAL HEALTH PERSPECTIVES 2023; 131:56002. [PMID: 37192319 PMCID: PMC10187974 DOI: 10.1289/ehp11851] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 03/22/2023] [Accepted: 03/30/2023] [Indexed: 05/18/2023]
Abstract
BACKGROUND Understanding the mechanistic basis of air pollution toxicity is dependent on accurately characterizing both exposure and biological responses. Untargeted metabolomics, an analysis of small-molecule metabolic phenotypes, may offer improved estimation of exposures and corresponding health responses to complex environmental mixtures such as air pollution. The field remains nascent, however, with questions concerning the coherence and generalizability of findings across studies, study designs and analytical platforms. OBJECTIVES We aimed to review the state of air pollution research from studies using untargeted high-resolution metabolomics (HRM), highlight the areas of concordance and dissimilarity in methodological approaches and reported findings, and discuss a path forward for future use of this analytical platform in air pollution research. METHODS We conducted a state-of-the-science review to a) summarize recent research of air pollution studies using untargeted metabolomics and b) identify gaps in the peer-reviewed literature and opportunities for addressing these gaps in future designs. We screened articles published within Pubmed and Web of Science between 1 January 2005 and 31 March 2022. Two reviewers independently screened 2,065 abstracts, with discrepancies resolved by a third reviewer. RESULTS We identified 47 articles that applied untargeted metabolomics on serum, plasma, whole blood, urine, saliva, or other biospecimens to investigate the impact of air pollution exposures on the human metabolome. Eight hundred sixteen unique features confirmed with level-1 or -2 evidence were reported to be associated with at least one or more air pollutants. Hypoxanthine, histidine, serine, aspartate, and glutamate were among the 35 metabolites consistently exhibiting associations with multiple air pollutants in at least 5 independent studies. Oxidative stress and inflammation-related pathways-including glycerophospholipid metabolism, pyrimidine metabolism, methionine and cysteine metabolism, tyrosine metabolism, and tryptophan metabolism-were the most commonly perturbed pathways reported in > 70 % of studies. More than 80% of the reported features were not chemically annotated, limiting the interpretability and generalizability of the findings. CONCLUSIONS Numerous investigations have demonstrated the feasibility of using untargeted metabolomics as a platform linking exposure to internal dose and biological response. Our review of the 47 existing untargeted HRM-air pollution studies points to an underlying coherence and consistency across a range of sample analytical quantitation methods, extraction algorithms, and statistical modeling approaches. Future directions should focus on validation of these findings via hypothesis-driven protocols and technical advances in metabolic annotation and quantification. https://doi.org/10.1289/EHP11851.
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Affiliation(s)
- Donghai Liang
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
| | - Zhenjiang Li
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
| | - Jelle Vlaanderen
- Department Population Health Sciences, Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands
| | - Ziyin Tang
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
| | - Dean P. Jones
- Department of Medicine, School of Medicine, Emory University, Atlanta, Georgia, USA
| | - Roel Vermeulen
- Department Population Health Sciences, Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands
| | - Jeremy A. Sarnat
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
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21
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Baccarelli A, Dolinoy DC, Walker CL. A precision environmental health approach to prevention of human disease. Nat Commun 2023; 14:2449. [PMID: 37117186 PMCID: PMC10147599 DOI: 10.1038/s41467-023-37626-2] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Accepted: 03/24/2023] [Indexed: 04/30/2023] Open
Abstract
Human health is determined by the interaction of our environment with the genome, epigenome, and microbiome, which shape the transcriptomic, proteomic, and metabolomic landscape of cells and tissues. Precision environmental health is an emerging field leveraging environmental and system-level ('omic) data to understand underlying environmental causes of disease, identify biomarkers of exposure and response, and develop new prevention and intervention strategies. In this article we provide real-life illustrations of the utility of precision environmental health approaches, identify current challenges in the field, and outline new opportunities to promote health through a precision environmental health framework.
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Affiliation(s)
- Andrea Baccarelli
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA.
| | - Dana C Dolinoy
- Department of Environmental Health Sciences, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Cheryl Lyn Walker
- Center for Precision Environmental Health, Baylor College of Medicine, Houston, TX, USA
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22
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Li K, Naviaux JC, Lingampelly SS, Wang L, Monk JM, Taylor CM, Ostle C, Batten S, Naviaux RK. Historical biomonitoring of pollution trends in the North Pacific using archived samples from the Continuous Plankton Recorder Survey. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 865:161222. [PMID: 36584956 DOI: 10.1016/j.scitotenv.2022.161222] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 12/13/2022] [Accepted: 12/23/2022] [Indexed: 06/17/2023]
Abstract
First started in 1931, the Continuous Plankton Recorder (CPR) Survey is the longest-running and most geographically extensive marine plankton sampling program in the world. This pilot study investigates the feasibility of biomonitoring the spatiotemporal trends of marine pollution using archived CPR samples from the North Pacific. We selected specimens collected from three different locations (British Columbia Shelf, Northern Gulf of Alaska, and Aleutian Shelf) in the North Pacific between 2002 and 2020. Comprehensive profiling of the plankton chemical exposome was conducted using liquid and gas chromatography coupled with tandem mass spectrometry (LC-MS/MS and GC-MS/MS). Our results show that phthalates, plasticizers, persistent organic pollutants (POPs), pesticides, pharmaceuticals, and personal care products were present in the plankton exposome, and that many of these pollutants have decreased in amount over the last two decades, which was most pronounced for tri-n-butyl phosphate. In addition, the plankton exposome differed significantly by regional human activities, with the most polluted samples coming from the nearshore area. Exposome-wide association analysis revealed that bioaccumulation of environmental pollutants was highly correlated with the biomass of different plankton taxa. Overall, this study demonstrates that exposomic analysis of archived samples from the CPR Survey is effective for long-term biomonitoring of the spatial and temporal trends of environmental pollutants in the marine environment.
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Affiliation(s)
- Kefeng Li
- The Mitochondrial and Metabolic Disease Center, University of California, San Diego School of Medicine, 214 Dickinson St., Bldg CTF, Rm C107, San Diego, CA 92103-8467, United States of America; Department of Medicine, University of California, San Diego School of Medicine, 214 Dickinson St., Bldg CTF, Rm C107, San Diego, CA 92103-8467, United States of America.
| | - Jane C Naviaux
- The Mitochondrial and Metabolic Disease Center, University of California, San Diego School of Medicine, 214 Dickinson St., Bldg CTF, Rm C107, San Diego, CA 92103-8467, United States of America; Department of Neurosciences, University of California, San Diego School of Medicine, 214 Dickinson St., Bldg CTF, Rm C107, San Diego, CA 92103-8467, United States of America
| | - Sai Sachin Lingampelly
- The Mitochondrial and Metabolic Disease Center, University of California, San Diego School of Medicine, 214 Dickinson St., Bldg CTF, Rm C107, San Diego, CA 92103-8467, United States of America; Department of Medicine, University of California, San Diego School of Medicine, 214 Dickinson St., Bldg CTF, Rm C107, San Diego, CA 92103-8467, United States of America
| | - Lin Wang
- The Mitochondrial and Metabolic Disease Center, University of California, San Diego School of Medicine, 214 Dickinson St., Bldg CTF, Rm C107, San Diego, CA 92103-8467, United States of America; Department of Medicine, University of California, San Diego School of Medicine, 214 Dickinson St., Bldg CTF, Rm C107, San Diego, CA 92103-8467, United States of America
| | - Jonathan M Monk
- The Mitochondrial and Metabolic Disease Center, University of California, San Diego School of Medicine, 214 Dickinson St., Bldg CTF, Rm C107, San Diego, CA 92103-8467, United States of America; Department of Medicine, University of California, San Diego School of Medicine, 214 Dickinson St., Bldg CTF, Rm C107, San Diego, CA 92103-8467, United States of America
| | - Claire M Taylor
- The Marine Biological Association, The Laboratory, Citadel Hill, Plymouth, Devon PL1 2PB, UK
| | - Clare Ostle
- The Marine Biological Association, The Laboratory, Citadel Hill, Plymouth, Devon PL1 2PB, UK
| | - Sonia Batten
- North Pacific Marine Science Organization (PICES), Sidney, BC V8L 4B2, Canada
| | - Robert K Naviaux
- The Mitochondrial and Metabolic Disease Center, University of California, San Diego School of Medicine, 214 Dickinson St., Bldg CTF, Rm C107, San Diego, CA 92103-8467, United States of America; Department of Medicine, University of California, San Diego School of Medicine, 214 Dickinson St., Bldg CTF, Rm C107, San Diego, CA 92103-8467, United States of America; Department of Pediatrics, University of California, San Diego School of Medicine, 214 Dickinson St., Bldg CTF, Rm C107, San Diego, CA 92103-8467, United States of America; Department of Pathology, University of California, San Diego School of Medicine, 214 Dickinson St., Bldg CTF, Rm C107, San Diego, CA 92103-8467, United States of America.
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23
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Grobe N, Scheiber J, Zhang H, Garbe C, Wang X. Omics and Artificial Intelligence in Kidney Diseases. ADVANCES IN KIDNEY DISEASE AND HEALTH 2023; 30:47-52. [PMID: 36723282 DOI: 10.1053/j.akdh.2022.11.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Revised: 10/28/2022] [Accepted: 11/16/2022] [Indexed: 01/20/2023]
Abstract
Omics applications in nephrology may have relevance in the future to improve clinical care of kidney disease patients. In a short term, patients will benefit from specific measurement and computational analyses around biomarkers identified at various omics-levels. In mid term and long term, these approaches will need to be integrated into a holistic representation of the kidney and all its influencing factors for individualized patient care. Research demonstrates robust data to justify the application of omics for better understanding, risk stratification, and individualized treatment of kidney disease patients. Despite these advances in the research setting, there is still a lack of evidence showing the combination of omics technologies with artificial intelligence and its application in clinical diagnostics and care of patients with kidney disease.
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Affiliation(s)
| | | | | | - Christian Garbe
- Frankfurter Innovationszentrum Biotechnologie, Frankfurt am Main, Germany
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24
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Wei X, Huang Z, Jiang L, Li Y, Zhang X, Leng Y, Jiang C. Charting the landscape of the environmental exposome. IMETA 2022; 1:e50. [PMID: 38867899 PMCID: PMC10989948 DOI: 10.1002/imt2.50] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 07/13/2022] [Accepted: 07/30/2022] [Indexed: 06/14/2024]
Abstract
The exposome depicts the total exposures in the lifetime of an organism. Human exposome comprises exposures from environmental and humanistic sources. Biological, chemical, and physical environmental exposures pose potential health threats, especially to susceptible populations. Although still in its nascent stage, we are beginning to recognize the vast and dynamic nature of the exposome. In this review, we systematically summarize the biological and chemical environmental exposomes in three broad environmental matrices-air, soil, and water; each contains several distinct subcategories, along with a brief introduction to the physical exposome. Disease-related environmental exposures are highlighted, and humans are also a major source of disease-related biological exposures. We further discuss the interactions between biological, chemical, and physical exposomes. Finally, we propose a list of outstanding challenges under the exposome research framework that need to be addressed to move the field forward. Taken together, we present a detailed landscape of environmental exposome to prime researchers to join this exciting new field.
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Affiliation(s)
- Xin Wei
- Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Sciences InstituteZhejiang UniversityHangzhouZhejiangChina
| | - Zinuo Huang
- Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Sciences InstituteZhejiang UniversityHangzhouZhejiangChina
| | - Liuyiqi Jiang
- Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Sciences InstituteZhejiang UniversityHangzhouZhejiangChina
| | - Yueer Li
- Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Sciences InstituteZhejiang UniversityHangzhouZhejiangChina
| | - Xinyue Zhang
- Department of GeneticsStanford UniversityStanfordCaliforniaUSA
| | - Yuxin Leng
- Department of Intensive Care UnitPeking University Third HospitalBeijingChina
| | - Chao Jiang
- Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Sciences InstituteZhejiang UniversityHangzhouZhejiangChina
- Zhejiang Provincial Key Laboratory of Pancreatic Disease, First Affiliated HospitalZhejiang University School of MedicineHangzhouZhejiangChina
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25
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Lippi L, de Sire A, Folli A, Turco A, Moalli S, Ammendolia A, Maconi A, Invernizzi M. Environmental Factors in the Rehabilitation Framework: Role of the One Health Approach to Improve the Complex Management of Disability. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:15186. [PMID: 36429901 PMCID: PMC9690359 DOI: 10.3390/ijerph192215186] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/23/2022] [Revised: 11/06/2022] [Accepted: 11/15/2022] [Indexed: 06/12/2023]
Abstract
Environment factors play a crucial implication in human health, with strong evidence suggesting that several biological, chemical, physical and social factors could be possible targets to implement effective strategies for human health promotion. On the other hand, a large gap of knowledge still exists about the implications of environmental factors in terms of functional impairment and disability, while the integration of an environmental-based approach in the therapeutic care of patients affected by disabilities remains still challenging. In this scenario, the One Health approach has been recently introduced in clinical care and aims to optimize health outcomes by recognizing the interconnection between people and the environment. Concurrently, the "Rehabilitation 2030 Initiative" proposed in 2017 by the WHO emphasized the need to integrate environmental-based strategies to promote rehabilitation across different health systems and different nations. However, no previous study underlined the potential implications of the One Health approach in the rehabilitation setting, nor the role of a comprehensive rehabilitation approach focused on environmental factors. Therefore, the aim of this narrative review was to present a comprehensive overview of the data currently available assessing the close relationship between rehabilitation and the environment to provide a different perspective on the comprehensive care of patients affected by disability.
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Affiliation(s)
- Lorenzo Lippi
- Physical and Rehabilitative Medicine, Department of Health Sciences, University of Eastern Piedmont “A. Avogadro”, 28100 Novara, Italy
- Dipartimento Attività Integrate Ricerca e Innovazione (DAIRI), Translational Medicine, Azienda Ospedaliera SS. Antonio e Biagio e Cesare Arrigo, 15121 Alessandria, Italy
| | - Alessandro de Sire
- Physical and Rehabilitative Medicine Unit, Department of Medical and Surgical Sciences, University of Catanzaro “Magna Graecia”, Viale Europa, 88100 Catanzaro, Italy
| | - Arianna Folli
- Physical and Rehabilitative Medicine, Department of Health Sciences, University of Eastern Piedmont “A. Avogadro”, 28100 Novara, Italy
| | - Alessio Turco
- Physical and Rehabilitative Medicine, Department of Health Sciences, University of Eastern Piedmont “A. Avogadro”, 28100 Novara, Italy
| | - Stefano Moalli
- Physical and Rehabilitative Medicine, Department of Health Sciences, University of Eastern Piedmont “A. Avogadro”, 28100 Novara, Italy
| | - Antonio Ammendolia
- Physical and Rehabilitative Medicine Unit, Department of Medical and Surgical Sciences, University of Catanzaro “Magna Graecia”, Viale Europa, 88100 Catanzaro, Italy
| | - Antonio Maconi
- SC Infrastruttura Ricerca Formazione Innovazione, Dipartimento Attività Integrate Ricerca Innovazione, Azienda Ospedaliera SS. Antonio e Biagio e Cesare Arrigo, 15121 Alessandria, Italy
| | - Marco Invernizzi
- Physical and Rehabilitative Medicine, Department of Health Sciences, University of Eastern Piedmont “A. Avogadro”, 28100 Novara, Italy
- Dipartimento Attività Integrate Ricerca e Innovazione (DAIRI), Translational Medicine, Azienda Ospedaliera SS. Antonio e Biagio e Cesare Arrigo, 15121 Alessandria, Italy
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Ding E, Wang Y, Liu J, Tang S, Shi X. A review on the application of the exposome paradigm to unveil the environmental determinants of age-related diseases. Hum Genomics 2022; 16:54. [DOI: 10.1186/s40246-022-00428-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Accepted: 10/29/2022] [Indexed: 11/11/2022] Open
Abstract
AbstractAge-related diseases account for almost half of all diseases among adults worldwide, and their incidence is substantially affected by the exposome, which is the sum of all exogenous and endogenous environmental exposures and the human body’s response to these exposures throughout the entire lifespan. Herein, we perform a comprehensive review of the epidemiological literature to determine the key elements of the exposome that affect the development of age-related diseases and the roles of aging hallmarks in this process. We find that most exposure assessments in previous aging studies have used a reductionist approach, whereby the effect of only a single environmental factor or a specific class of environmental factors on the development of age-related diseases has been examined. As such, there is a lack of a holistic and unbiased understanding of the effect of multiple environmental factors on the development of age-related diseases. To address this, we propose several research strategies based on an exposomic framework that could advance our understanding—in particular, from a mechanistic perspective—of how environmental factors affect the development of age-related diseases. We discuss the statistical methods and other methods that have been used in exposome-wide association studies, with a particular focus on multiomics technologies. We also address future challenges and opportunities in the realm of multidisciplinary approaches and genome–exposome epidemiology. Furthermore, we provide perspectives on precise public health services for vulnerable populations, public communications, the integration of risk exposure information, and the bench-to-bedside translation of research on age-related diseases.
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Zhou X, Wang B, Demkowicz PC, Johnson JS, Chen Y, Spakowicz DJ, Zhou Y, Dorsett Y, Chen L, Sodergren E, Kuchel GA, Weinstock GM. Exploratory studies of oral and fecal microbiome in healthy human aging. FRONTIERS IN AGING 2022; 3:1002405. [PMID: 36338834 PMCID: PMC9631447 DOI: 10.3389/fragi.2022.1002405] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 09/26/2022] [Indexed: 11/05/2022]
Abstract
Growing evidence has linked an altered host fecal microbiome composition with health status, common chronic diseases, and institutionalization in vulnerable older adults. However, fewer studies have described microbiome changes in healthy older adults without major confounding diseases or conditions, and the impact of aging on the microbiome across different body sites remains unknown. Using 16S ribosomal RNA gene sequencing, we reconstructed the composition of oral and fecal microbiomes in young (23-32; mean = 25 years old) and older (69-94; mean = 77 years old) healthy community-dwelling research subjects. In both body sites, we identified changes in minor bacterial operational taxonomic units (OTUs) between young and older subjects. However, the composition of the predominant bacterial species of the healthy older group in both microbiomes was not significantly different from that of the young cohort, which suggests that dominant bacterial species are relatively stable with healthy aging. In addition, the relative abundance of potentially pathogenic genera, such as Rothia and Mycoplasma, was enriched in the oral microbiome of the healthy older group relative to the young cohort. We also identified several OTUs with a prevalence above 40% and some were more common in young and others in healthy older adults. Differences with aging varied for oral and fecal samples, which suggests that members of the microbiome may be differentially affected by aging in a tissue-specific fashion. This is the first study to investigate both oral and fecal microbiomes in the context of human aging, and provides new insights into interactions between aging and the microbiome within two different clinically relevant sites.
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Affiliation(s)
- Xin Zhou
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, United States
- Department of Genetics and Genome Sciences, University of Connecticut Health Center, Farmington, CT, United States
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, United States
| | - Baohong Wang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University School of Medicine, Hangzhou City, China
| | - Patrick C. Demkowicz
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, United States
- Yale University School of Medicine, New Haven, CT, United States
| | - Jethro S. Johnson
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, United States
- Oxford Centre for Microbiome Studies, Kennedy Institute of Rheumatology, University of Oxford, Oxford, United Kingdom
| | - Yanfei Chen
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, United States
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University School of Medicine, Hangzhou City, China
| | - Daniel J. Spakowicz
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, United States
- The Ohio State University Comprehensive Cancer Center, Columbus, OH, United States
| | - Yanjiao Zhou
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, United States
- Department of Medicine, University of Connecticut Health Center, Farmington, CT, United States
| | - Yair Dorsett
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, United States
- Department of Medicine, University of Connecticut Health Center, Farmington, CT, United States
| | - Lei Chen
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, United States
- Shanghai Institute of Immunology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Erica Sodergren
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, United States
| | - George A. Kuchel
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, United States
- UConn Center on Aging, University of Connecticut Health Center, Farmington, CT, United States
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Shen X, Yan H, Wang C, Gao P, Johnson CH, Snyder MP. TidyMass an object-oriented reproducible analysis framework for LC-MS data. Nat Commun 2022; 13:4365. [PMID: 35902589 PMCID: PMC9334349 DOI: 10.1038/s41467-022-32155-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Accepted: 07/15/2022] [Indexed: 02/05/2023] Open
Abstract
Reproducibility, traceability, and transparency have been long-standing issues for metabolomics data analysis. Multiple tools have been developed, but limitations still exist. Here, we present the tidyMass project ( https://www.tidymass.org/ ), a comprehensive R-based computational framework that can achieve the traceable, shareable, and reproducible workflow needs of data processing and analysis for LC-MS-based untargeted metabolomics. TidyMass is an ecosystem of R packages that share an underlying design philosophy, grammar, and data structure, which provides a comprehensive, reproducible, and object-oriented computational framework. The modular architecture makes tidyMass a highly flexible and extensible tool, which other users can improve and integrate with other tools to customize their own pipeline.
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Affiliation(s)
- Xiaotao Shen
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Hong Yan
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA
| | - Chuchu Wang
- Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA
| | - Peng Gao
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Caroline H Johnson
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA.
| | - Michael P Snyder
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
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