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Integrating Multi-Omics with environmental data for precision health: A novel analytic framework and case study on prenatal mercury induced childhood fatty liver disease.
Goodrich, Jesse A; Wang, Hongxu; Jia, Qiran; Stratakis, Nikos; Zhao, Yinqi; Maitre, Léa; Bustamante, Mariona; Vafeiadi, Marina; Aung, Max; Andrusaityte, Sandra; Basagana, Xavier; Farzan, Shohreh F; Heude, Barbara; Keun, Hector; McConnell, Rob; Yang, Tiffany C; Siskos, Alexandros P; Urquiza, Jose; Valvi, Damaskini; Varo, Nerea; Småstuen Haug, Line; Oftedal, Bente M; Grazuleviciene, Regina; Philippat, Claire; Wright, John; Vrijheid, Martine; Chatzi, Leda; Conti, David V.
Afiliação
  • Goodrich JA; Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, United States. Electronic address: jagoodri@usc.edu.
  • Wang H; Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, United States.
  • Jia Q; Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, United States.
  • Stratakis N; Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Spain.
  • Zhao Y; Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, United States.
  • Maitre L; Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Spain.
  • Bustamante M; Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Spain.
  • Vafeiadi M; Department of Social Medicine Faculty of Medicine, University of Crete, Heraklion, Greece.
  • Aung M; Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, United States.
  • Andrusaityte S; Department of Environmental Sciences, Vytauto Didziojo Universitetas, Kaunas, Lithuania.
  • Basagana X; Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Spain.
  • Farzan SF; Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, United States.
  • Heude B; Université de Paris Cité, Institut National de la Santé et de la Recherche Médicale (INSERM), National Research Institute for Agriculture, Food and Environment, Centre of Research in Epidemiology and Statistics, Paris, France.
  • Keun H; Department of Surgery & Cancer and Department of Metabolism Digestion & Reproduction Imperial College London, London, United Kingdom.
  • McConnell R; Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, United States.
  • Yang TC; Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, United Kingdom.
  • Siskos AP; Department of Surgery & Cancer and Department of Metabolism Digestion & Reproduction Imperial College London, London, United Kingdom.
  • Urquiza J; Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Spain.
  • Valvi D; Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
  • Varo N; Laboratory of Biochemistry, University Clinic of Navarra, Pamplona, Spain.
  • Småstuen Haug L; Norwegian Institute of Public Health, Oslo, Norway.
  • Oftedal BM; Norwegian Institute of Public Health, Oslo, Norway.
  • Grazuleviciene R; Department of Environmental Sciences, Vytauto Didziojo Universitetas, Kaunas, Lithuania.
  • Philippat C; University Grenoble Alpes, Institut National de la Santé et de la Recherche Médicale (INSERM) U 1209, CNRS UMR 5309, Team of Environmental Epidemiology Applied to Development and Respiratory Health, Institute for Advanced Biosciences, 38000 Grenoble, France.
  • Wright J; Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, United Kingdom.
  • Vrijheid M; Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Spain.
  • Chatzi L; Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, United States.
  • Conti DV; Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, United States.
Environ Int ; 190: 108930, 2024 Aug.
Article em En | MEDLINE | ID: mdl-39128376
ABSTRACT

BACKGROUND:

Precision Health aims to revolutionize disease prevention by leveraging information across multiple omic datasets (multi-omics). However, existing methods generally do not consider personalized environmental risk factors (e.g., environmental pollutants).

OBJECTIVE:

To develop and apply a precision health framework which combines multiomic integration (including early, intermediate, and late integration, representing sequential stages at which omics layers are combined for modeling) with mediation approaches (including high-dimensional mediation to identify biomarkers, mediation with latent factors to identify pathways, and integrated/quasi-mediation to identify high-risk subpopulations) to identify novel biomarkers of prenatal mercury induced metabolic dysfunction-associated fatty liver disease (MAFLD), elucidate molecular pathways linking prenatal mercury with MAFLD in children, and identify high-risk children based on integrated exposure and multiomics data.

METHODS:

This prospective cohort study used data from 420 mother-child pairs from the Human Early Life Exposome (HELIX) project. Mercury concentrations were determined in maternal or cord blood from pregnancy. Cytokeratin 18 (CK-18; a MAFLD biomarker) and five omics layers (DNA Methylation, gene transcription, microRNA, proteins, and metabolites) were measured in blood in childhood (age 6-10 years).

RESULTS:

Each standard deviation increase in prenatal mercury was associated with a 0.11 [95% confidence interval 0.02-0.21] standard deviation increase in CK-18. High dimensional mediation analysis identified 10 biomarkers linking prenatal mercury and CK-18, including six CpG sites and four transcripts. Mediation with latent factors identified molecular pathways linking mercury and MAFLD, including altered cytokine signaling and hepatic stellate cell activation. Integrated/quasi-mediation identified high risk subgroups of children based on unique combinations of exposure levels, omics profiles (driven by epigenetic markers), and MAFLD.

CONCLUSIONS:

Prenatal mercury exposure is associated with elevated liver enzymes in childhood, likely through alterations in DNA methylation and gene expression. Our analytic framework can be applied across many different fields and serve as a resource to help guide future precision health investigations.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Efeitos Tardios da Exposição Pré-Natal / Mercúrio Limite: Adult / Child / Female / Humans / Male / Pregnancy Idioma: En Revista: Environ Int Ano de publicação: 2024 Tipo de documento: Article País de publicação: Holanda

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Efeitos Tardios da Exposição Pré-Natal / Mercúrio Limite: Adult / Child / Female / Humans / Male / Pregnancy Idioma: En Revista: Environ Int Ano de publicação: 2024 Tipo de documento: Article País de publicação: Holanda