The LongITools project is studying the interactions between environmental, lifestyle and biological factors to determine people’s risks of developing cardiometabolic non-communicable disease, such as obesity, type 2 diabetes, heart diseases and atherosclerosis.
Project objectives and outputs
Using a large resource of life-course data, LongITools aims to study how exposure to environmental (air pollution, noise and the built environment), lifestyle and biological factors collectively contribute to the risk of developing cardiovascular and metabolic diseases across the life-course. The project, part of the European Human Exposome Network, is taking an exposome or holistic-based approach to define the disease pathways and the points at which to best intervene during the life-course to reduce the risks. LongITools also aims to generate new monitoring and prediction methods and tools which can translate into innovative healthcare and policy options. The research will result in a number of key outputs:
The development of tools to collect and analyse research data
Metadata catalogue: an online, searchable tool enabling exposome researchers to access rich metadata about data sets for example, the type of data set (e.g., cohort), the population, number of participants, and harmonised data variables. Users are able to assess the suitability of the data sets to answer specific research questions.
Life-course causal models: novel statistical software to explore, understand and describe the associations/pathways between environmental, lifestyle and biological factors and risk of cardiovascular and metabolic disease.
Exposome data-analysis toolbox: an online toolbox that enables researchers to search for and use multiple exposome data analysis tools and visualisation methodologies via a single platform.
Policy and regulation database: details of the major policies, laws and regulations in the LongITools data set countries (Finland, France, Netherlands, Norway and the UK) which can affect the external exposome e.g., pension rules, state benefits, healthcare reforms.
Healthcare risk assessment app: personalised and precise monitoring system integrating exposome-based data from users, environmental sensors and wearables to estimate, using an artificial intelligence algorithm, an individual’s risk of developing cardiovascular and metabolic diseases.
Economic simulation model: a model for assessing, projecting and visualising the economic burden related to non-communicable diseases. Understanding the economic burden may help determine the amount of resources that may be saved due to early prevention/intervention.
Improving our knowledge and understanding
- Understanding the human exposome through longitudinal research;
- Identification of gaps in knowledge for future research.
Improving the health of EU citizens
Policy options: translation of the LongITools research, including economic modelling, to inform current policies and future policy development.
Our Partners and Advisory Board
The project is led by the University of Oulu in Finland and involves 18 partners, including 15 research institutions and 3 SMEs, across 8 European countries. The combined team has significant expertise in epidemiology, genetics, epigenetics, metabolomics, nutrition, lifestyle, mathematics, economics, policy making, artificial intelligence and sensor technology. The team is also supported by an External Advisory Board, providing independent scientific, policy and ethics advice to the consortium. The Board members include:
- Professor Alena Buyx, Technical University Munich, Germany;
- Dr Liisa Byberg, Uppsala University, Sweden;
- Dr Zoltan Kutalik, University of Lausanne, Switzerland;
- Dr Rupert Suckling, Director of Public Health, Doncaster Council, UK;
- Leena Vuotovesi, CEO, Oulu Business Center & Oulun Narikka Ltd, Finland.
Our Research Questions
LongITools is testing the following hypotheses:
- Environmental exposures are associated with cardiometabolic health and its trajectories from early-life until late adulthood.
- Environmental exposures may occur at a specific life stage or across multiple life stages.
- Environmental exposures may activate some biological pathways (mediation) such as inflammation, stress or hypoxia to modify individual’s cardiometabolic health.
- The activation of the underlying biological pathways may arise from molecular mechanisms i.e. multi-omics profile changes (DNA methylation, transcriptome, metabolome).
- Lifestyle and psychosocial factors, as well as genetic predisposition, modify the associations between environmental exposures and cardiometabolic health trajectories.