In the modern World of today, the impetus of disease prevention and treatment focus on the main causes of mortality and morbidity, which is dominated by the non-communicable diseases (NCDs): cancers, cardiovascular, respiratory, and neurological diseases, mental health and increasingly, wellbeing and diabetes.
Inflammation and oxidative stress provoked by exposure to e.g. air-pollution are suggested to be a key element in the development of disease. Hence, identification of relevant biomarkers for inflammation, oxidative stress or immune dysregulation associated to pollutants like particulate matter (e.g. PM10 and PM2.5) or nitrogen oxides (NOx) is essential, when we investigate the mechanisms in disease development and for the surveillance of populations, and even more so for surveillance of susceptible groups with established NCDs.
Inflammation and oxidative stress provoked by exposure to e.g. air-pollution are suggested to be a key element in the development of disease. Hence, identification of relevant biomarkers for inflammation, oxidative stress or immune dysregulation associated to pollutants like particulate matter (e.g. PM10 and PM2.5) or nitrogen oxides (NOx) is essential, when we investigate the mechanisms in disease development and for the surveillance of populations, and even more so for surveillance of susceptible groups with established NCDs.
We have access to powerful tools and unique data sources to measure health effects of environmental exposures.
Our data include exposure data (noise, air and water quality), health register data, genetic data and biomarker assessments on samples from three cohorts: 110,000 healthy individuals from the Danish Blood Donor Study, minimum 2000 individuals exercising regularly from the Garmin-RUNSAFE cohort, and minimum 2000 Danish patients with implanted Cardioverter Defibrillators. We will also analyse inter-generational health effects, and include register data from the Danish Twin Registry with up to 86,000 twin pairs in our analyses.
The exposure data are modelled on individual level in the BERTHA work package on Environmental Exposures, monitored directly by Garmin smartwathces and the new personal sensors developed for and used in the BERTHA work package on Personalised Sensors. The health registry data, demographic and some genetic data are collected and linked by the BERTHA work package on Big data Collection and Linkage.
The techniques involved in the research of this work package will be determined by the availability of high resolution data over several decades, covering almost the entire area of the country. In the temporal domain, this means the Cardioverter Defibrillator data, the data from the new personal monitors and the Garmin smartwatches, the repeated blood samples of the blood donors, and the daily admission to hospitals or emergency rooms for acute diseases or exacerbation of existing diseases. In the spatial domain the health data from registries will be combined with the high resolution data on air pollution, noise and drinking water quality.
We will explore the association between environmental exposures, and biomarker and health outcomes and their interaction with the genomic variation, we find in the cohorts.
We will use omics techniques to explore pathways linked to a higher disease risk. After refinement and identification of biomarkers associated to environmental exposure, we will test the most promising biomarkers as predictors of disease risk on the individual level.
Work Package Leader: Professor Torben Sigsgaard
