EXPOsOMICS

EXPOsOMICS will predict individual disease risk related to the environment, by characterizing the external and internal exposome for common exposures (air and drinking water contaminants) during critical periods of life, including in utero.

Using ‘omic’ techniques the collected exposure data can be linked to biochemical and molecular changes in our body. The results will help to improve our understanding on how these pollutants influence the risk of developing chronic diseases. 

The exposome concept refers to the totality of environmental exposures from conception onwards, and is a novel approach to studying the role of the environment in human disease.

For more information please visit the  EXPOsOMICS website.

Kings College London leads on air pollution monitoring and modeling in WP3 as well as leads WP6 and conduct analysis of protein adducts (adductomics).

The aim of the air pollution component in the project is to construct the short term and long term air pollution exposure estimates for adults and children via both personal and ambient measurements and modelling using novel and existing technologies.

Epidemiological studies traditionally assessed air pollution exposure based on data collected by outdoor monitoring stations at fixed locations. This exposure estimation method however does not take into account the micro-environmental conditions (e.g. indoor-outdoor exposure) and personal activity patters (i.e. traveling from-to work). 

One of the advances of this project is to develop personal exposure models by using a mobile personal exposure monitoring (PEM) system. 

Name	Expertise	Role in the project
Professor Frank Kelly	Respiratory toxicology and physiology	WP3 participant Joint lead at Personal monitoring in short term studies task   Lead Development of LUR models for OP measurements task
Professor David Phillips	Human biomonitoring and carcinogen activation	Lead of WP6
TBA	Modeller	Model development for PM oxidative potential
Layla Aithadj	Toxicologist	PM filter oxidative potential analysis
George Preston	Adductomics analysis	Adductomics analysis