Health and Environment-wide Associations based on Large population Surveys (HEALS), Dr Isabella Annesi-Maesano: principal investigator
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HEALS represents a comprehensive applied methodology focusing on the different aspects of individual assessment of exposure to conventional and emerging environmental stressors and on the prediction of the associated health outcomes. For the first time, HEALS will try to reverse the paradigm of “nature versus nurture” and adopt one defined by complex and dynamic interactions between DNA sequence, epigenetic DNA modifications, gene expression and environmental factors that all combine to influence disease phenotypes. HEALS will start from analysis of data collected in on-going epidemiological EU studies involving mother/infant pairs, children, or adults including the elderly to evidence relevant environmental exposure/health outcome associations. These associations will aid in designing pilot surveys using an integrated approach, where the selection of biomarkers of exposure, effects and individual susceptibility results in integrated risk assessment. In the context of this new paradigm, a relevant contribution for a better understanding of the diseases comes also from twin studies.

In fact, HEALS proposes the functional integration of -omics derived data and biochemical biomonitoring to create the internal exposome at the individual level. These data will be exploited using advanced bioinformatics tools for both descriptive and predictive data mining. HEALS will propose a novel bioinformatics strategy focusing on biomarker fusion, and direct coupling of physiology-based biokinetic models to metabolic regulatory networks derived from -omics analyses. In this way, the internal dose of environmental stressors will be coupled to the alterations they bring about to gene expression, protein-protein interactions and metabolic regulation and plausible hypotheses on the respective pathways of toxicity can be established.

The HEALS consortium is dedicated to the rapid translation of scientific findings in the environment and health area into actual innovative tools that can enter the market in support of both job and wealth creation as well as cost-effective policy interventions that can mitigate the environmental burden of disease in Europe and worldwide.

concept heals 


Project overview


Assessing individual exposure to environmental stressors and predicting health outcomes implies that both environmental exposures and epi/genetic variations are reliably measured simultaneously. HEALS (Health and Environment-wide Associations based on Large population Surveys) brings together in an innovative approach a comprehensive array of novel technologies, data analysis and modeling tools that support efficiently exposome studies.

The general objective of HEALS is the refinement of an integrated methodology and the application of the corresponding analytical and computational tools for performing environment-wide association studies in support of EU-wide environment and health assessments. The exposome represents the totality of exposures from conception onwards, simultaneously identifying, characterizing and quantifying the exogenous and endogenous exposures and modifiable risk factors that predispose to and predict diseases throughout a person’s life span. The HEALS approach brings together and organizes environmental, socio-economic, exposure, biomarker and health effect data; in addition, it includes all the procedures and computational sequences necessary for applying advanced bioinformatics coupling thus effective data mining, biological and exposure modeling so as to ensure that environmental exposure-health associations are studied comprehensively.

The overall approach will be verified and refined in a series of population studies across Europe including twin cohorts, tackling different levels of environmental exposure, age windows of exposure, and socio-economic and genetic variability. The HEALS approach will be applied in a pilot environment and health examination survey of children including singletons and sets of twins and matched singletons (each twins pair having also a matched singleton) covering ten EU Member States and an African country (the EXHES Study). The lessons learned will be translated into scientific advice towards the development of protocols and guidelines for the setting up of a larger European environment and health examination survey.