GMS6850 FOUNDATIONS OF BIOMEDICAL INFORMATICS

The Exposome: Concept, Utility, and Challenges

Hui Hu Ph.D.

Department of Epidemiology

College of Public Health and Health Professions & College of Medicine

October 1, 2020

The Genome

• Well-established tools to sequence the human genome and to examine individual susceptibility through genome-wide association studies (GWAS)
   
• Thousands of GWAS

A lack of comparable tools in relation to environmental exposure assessment

Traditional environmental health studies almost uniquely focused on single exposure-outcome relationships and no global view of how various types of coexisting exposures may jointly affect health

Concept

The Health and Environment-wide Associations based on Large population Surveys (HEALS)

Aims to develop an integrated methodology for compiling and organizing exposure data across multiple domains, and using these factors to predict health outcomes

Human Early-Life Exposome (HELIX) Project

Aim to implement tools and methods to characterize early-life exposure to a wide range of chemical and physical environmental factors and associate with data on major child health outcomes
-  early-life exposome approach

Source: Vrijheid et al. The human early-life exposome (HELIX): project rationale and design. Environmental health perspectives. 2014 Jun;122(6):535-44.

• There can be overlaps in the three domains
  “the difficulty in placing a particular exposure in one domain or another; for example, one can debate whether physical activity should be in the internal or specific external domains”
   
• The domains can also be considered as intertwined
  -  the internal may at least partially be a response to the external
   
• Measures in one domain or another may reflect to differing degrees one component of the exposome:
  -  the urban environment (general external)
  -  air pollution (specific external)
  -  inflammation (internal)

Source: Wild CP. The exposome: from concept to utility. International journal of epidemiology. 2012 Feb 1;41(1):24-32.

Two domains:

- The internal exposome

- The external exposome 

Approaches and Tools to Measure the Exposome

Source: Wild CP. The exposome: from concept to utility. International journal of epidemiology. 2012 Feb 1;41(1):24-32.

• Genome sequencing has been closely followed by analogous tools to characterize downstream biological event:
  -  RNA expression (transcriptomics)
  -  proteins (proteomics)
  -  metabolites (metabolomics)
  -  epigenomics
   
• Each of the omics provides information on thousands of individual component parts, and can be linked to disease outcomes in analogous fashion to GWAS
  
   
• Some of the limitations to use these approaches in the exposome framework:
  -  the 'top-down' approach lacks a crucial link between exposure to a given agent and the molecular profiles observed
  -  this is required to identify risk factors and to implement prevention strategies

Source: Wild CP. The exposome: from concept to utility. International journal of epidemiology. 2012 Feb 1;41(1):24-32.

Approaches and Tools to Measure the Exposome

Source: Wild CP. The exposome: from concept to utility. International journal of epidemiology. 2012 Feb 1;41(1):24-32.

Utility

Source: Zheng et al. Design and methodology challenges of environment-wide association studies: A systematic review. Environmental Research. 2020 Feb 19:109275.

Environment-Wide Association Studies (EWAS)

aka Exposome-Wide Association Studies (ExWAS)

Under review: Science of the Total Environment

Challenges

Source: Jiang et al. Dynamic human environmental exposome revealed by longitudinal personal monitoring. Cell. 2018 Sep 20;175(1):277-91.

Ontology

• Ontology: a formal, computational representation of a domain of knowledge based upon a controlled, standardized vocabulary for describing entities and the semantic relationships between them
   
• Several semantic standards developed for the internal exposome, e.g., Metabolomics Standards Initiative Ontology
   
• Few exists for the external exposome:
  -  Only 2 out of 882 ontologies found on
     BioPortal focused on the external exposome

Researchers may have many questions when conducting external exposome studies:

• What are the domains of the measures of interest?
• What are the spatial and temporal scales of the measures?
• How can we establish the susceptible spatial (e.g., buffer vs. administrative boundary) and temporal windows (e.g., short-term vs. long-term) to these external exposome measures?
• Are there similar measures (e.g., monitored vs. modelled PM2.5) from different sources?
• Which ones to use?
• Whether it make senses to combine these similar measures to a “better” (e.g., more reliable or representative) measure?
• How to interpret inconsistent results for similar measures from different sources; among many other practical considerations that are needed.

Statistical Methods for Exposome Studies (Inference)

• Numerous statistical methods for studies:
  EWAS, EWAS-MLR, ENET, sPLS, GUESS, DSA, Tree-based models, etc.
   
• Performances for internal exposome studies have been assessed.

Statistical Methods for Exposome Studies (Inference)

• No established methods for external exposome studies
   
• External exposome data are more heterogeneous internal exposome data:
  -  unique correlation structures:
      factors from the same data source are more likely to be highly correlated
  
  -  different spatiotemporal scales, leading to different aggregations and spatiotemporal linkages and subsequently different associations:
      e.g., the MAUP bias

Methods for Exposome Studies (Prediction)

• Existing machine/deep learning models can be implemented for internal exposome data
   
• More efforts needed for predictive models using external exposome data:
  -  Traditional machine learning models fail to preserve spatiotemporal structures in external exposome data
  -  No existing deep learning model architectures can be directly applied to external exposome data
   

Other Challenges

• Selection of confounders:
  -  all existing exposome studies used common sets of confounders for all exposures
   
• External validations:
  -  can be easily carried out by internal exposome studies
  -  much more complicated for external exposome studies:
      exposure-disease associations may vary by space when spatial stochastic
  process is in presence

Thank you!

huihu@ufl.edu

hui-hu.com

github.com/benhhu