Researchers Develop Novel Framework Leveraging Multi-Omics Data to Advance Environmental Precision Health

Over the last 20 years, vast advancements in the field of biotechnology have led to the development of a research approach called multi-omics, which looks at multiple layers of biological information—like gene expression, proteins, and metabolites—all at once to get a complete picture of how the body functions. These advancements have resulted in the emerging field of precision environmental health which aims to integrate environmental and biological factors to identify, understand, and address the impact of the environment on human health.

Now, in one of the first studies of its kind, a group of researchers from the Keck School of Medicine of USC have developed a novel precision health framework that leverages multi-omics to understand environment-related diseases. The findings were published in the journal Environment International.

“To showcase how our proposed methods can be used towards precision health investigations, we carried out a study examining how mercury exposure in utero might impact the risk of developing liver injury in childhood,” explains Jesse Goodrich, PhD, assistant professor of population and public health sciences. “Previous research has shown that prenatal mercury exposure increases the risk of liver injury, but the biological mechanisms and pathways have not been well understood.”

Exposure to mercury, a neurotoxin, can lead to increased oxidative stress and alter gene regulations, which can in turn increase the risk of various diseases. One such illness is metabolic dysfunction-associated fatty liver disease (MAFLD). Goodrich and his colleagues developed three data analysis approaches that integrated multi-omics to uncover insights on prenatal mercury induced childhood fatty liver disease, a common liver condition in children that can cause severe health issues.

The framework in action

The first method for analyzing this type of data identifies multi-omics biomarkers of environment-associated diseases years after the environmental exposure. “This approach identifies signatures in the blood, in this case MAFLD, that signal whether or not you are at risk for certain diseases based on your previous environmental exposures,” explains Goodrich.

The second method aims to identify altered biological pathways that inform environment-associated diseases. “Here, we are identifying biological mechanisms of how environmental factors actually cause disease,” he says.

The third method identifies groups of individuals at the highest risk of disease based on different patterns of what they have been exposed to. “This method is closely related to precision medicine, which uses genetics to predict disease outcome, but in precision environmental health, we are combining biological and environmental factors,” he shares.

Goodrich’s study found that prenatal mercury exposure was associated with epigenetic changes which affect how genes work, and those alterations were linked to higher risk of liver injury in childhood. “We found that higher prenatal mercury levels were linked to increased risk of liver injury children. Using our first method, researchers can now predict whether someone was exposed to mercury and has a risk of developing liver injury,” he shares.

“Next, we observed that when we put all the different signatures together, children who had higher exposure to mercury in utero, had changes in their inflammation signal, leading to higher inflammation and oxidative stress which were suggestive of higher risk of liver injury. Third, we used the information on blood mercury levels to predict who was at risk of developing severe health outcomes such as liver injury later on in life based on their molecular markers, exposure levels, and MAFLD risk,” he says.

Advancing precision environmental health

The research team’s aim was to develop a resource to address key aspects of precision environmental health. This publication was the first attempt to develop a conceptual framework to combine multi-omics data integration with methods for understanding how environmental exposures impact intermediate biological factors to cause adverse health outcomes. “This study comes at a time when the National Institute of Environmental Health Sciences (NIEHS) is promoting these advanced technologies around multi-omics data to better understand how environmental factors impact disease,” he says.

Goodrich shares that the development of these methods broadens the horizons of the field of precision environmental health, allowing researchers to examine both the environment and biological processes together. These techniques will help future scientists to better understand why certain people develop diseases while others do not. This knowledge will inform the development of tools and interventions that could potentially prevent diseases before they develop.

This publication was selected by the NIEHS as an extramural Paper of the Month of October. “This recognition is a testament that the National Institutes of Health is invested in this type of research and helping to promote it. It highlights the importance these methods hold in identifying biologically significant insights that are fundamental to progressing precision environmental health,” he shares.

About this research

 In addition to Goodrich, the study’s other authors are  Hongxu Wang, Qiran Jia, Yinqi Zhao,  Max Aung ,  Shohreh F Farzan, Rob McConnell, Leda Chatzi  and David V Conti from Keck School of Medicine of USC; Nikos Stratakis, Léa Maitre, Mariona Bustamante, Xavier Basagana , Jose Urquiza and Martine Vrijheid from Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Spain; Marina Vafeiadi  from Department of Social Medicine Faculty of Medicine, University of Crete, Heraklion, Greece; Sandra Andrušaitytė  and Regina Gražulevičienė  from Department of Environmental Sciences, Vytauto Didžiojo Universitetas, Kaunas, Lithuania; Barbara Heude from 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; Hector Keun and Alexandros P Siskos from the Department of Surgery & Cancer and Department of Metabolism Digestion & Reproduction Imperial College London, London, United Kingdom; Tiffany C Yang and John Wright  from Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, United Kingdom; Damaskini Valvi  from Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Nerea Varo from Laboratory of Biochemistry, University Clinic of Navarra, Pamplona, Spain; Line Småstuen Haug and  Bente M Oftedal  from Norwegian Institute of Public Health, Oslo, Norway; and Claire Philippat  from 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.

This work was primarily funded by the National Institute of Environmental Health Sciences [K01ES036193]. Additional funding came from the National Institutes of Health, including the National Institute of Environmental Health Sciences [P30ES007048, R21ES029681], the National Human Genome Research Institute [U01HG013288], the National Cancer Institute [P01CA196569; P30CA014089, U19CA214253, U01CA164973], the National Institute of Arthritis and Musculoskeletal and Skin Diseases [R21AR084040], the European Community’s Seventh Framework Programme [FP7/2007–2013] under grant agreement no. 308333 [the HELIX project], and by the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 874583 [ATHLETE].