JultikaUniversity of Oulu repository

Environmental factors, including air and noise pollution, and the built environment, are typically associated with cardiovascular and metabolic non-communicable diseases (NCDs), e.g. obesity, type 2 diabetes, heart diseases and atherosclerosis. The extent to which these exposures may cause their attributed health effects (via molecular mediation) directly or indirectly as a result of associations to an individual’s psychosocial context is largely unknown. NCDs arise from a lifelong process influencing anthropometric, glycaemic, cardiac and lipid-related health trajectories. Risks may start as early as during the fetal period and are modified during sensitive periods in childhood, adolescence and adulthood. Despite this, research has not focused enough on the life-course characterisation of the exposome and the application of this to health and disease. In 5 years, LONGITOOLS, a partnership of 15 academic groups and 3 small companies will harness a catalogue of birth cohorts, longitudinal data, registers and biobanks. We will characterise coincident longitudinal trajectories of exposure and cardiometabolic health combining the study of longitudinal effects and internal responses. The latter will include measures of DNA methylation, RNA expression and read outs of metabolic pathways. LONGITOOLS will implement this longitudinal approach in 11 work packages designed to generate a catalogue of FAIR data and a novel analytical toolbox. Evidence-based life-course causal models will estimate how clinical and policy interventions may sustainably affect the health and economic burden of NCDs. A key objective will be to generate evidence-based predictions which can ultimately translate into innovative healthcare applications (apps) and policy options. LONGITOOLS will also allow researchers and policy makers to generate new knowledge - identifying the likely causal (direct and indirect) mechanisms through which exposures to man-made environmental factors affect the risk of NCDs. LONGITOOLS is one of the nine projects composing the European Human Exposome Network.