About the Systems Epidemiology laboratory
Cardiometabolic diseases — coronary heart disease, stroke and diabetes — are the leading cause of death and disability in Australia and worldwide. Cardiovascular health and diabetes are two of the nine National Health Priority Areas defined by Australian governments.
Key challenges to tackle these diseases include:
- Understanding of the complex molecular pathways in disease development.
- Clarifying the causal relationships of biomarkers.
- Determining opportunities for prevention.
Causality is fundamental for the efficacy of interventions; lifestyle and/or drug treatments directed at non-causal targets will not be effective.
While observational study designs are key to identifying associations between putative risk factors and disease, they cannot provide reliable evidence on causality owing to biases from confounding and reverse causality. The recent explosion and availability of genetic data via genome-wide analysis studies (GWASs) has provided means to assess causality via Mendelian randomisation making it a leading method in systems epidemiology.
Circulating biomarkers, including lipoprotein particles and the accompanying lipid molecules, represent key pathways for cardiometabolic diseases. Consequently metabolomics and lipidomics — via simultaneous analysis of large numbers of circulating biomarkers across multiple pathways — provide innovative opportunities to understand cardiometabolic processes in more detail. With appropriate study designs and large-scale data there are novel opportunities to find new causal molecular components that could provide new targets for interventions and disease prevention.
Our research on cardiometabolic health and diseases focuses on two broad areas: epidemiology, genetics and causal inference of large-scale blood-based metabolomics and development and systems epidemiology applications of new metabolomics methods and platforms. Our established and expanding collaborative network is comprehensive and aims for global population coverage and life-course understanding of systemic health and disease aetiologies. Various collaborations are resulting in an unprecedented amount of coherent quantitative molecular data on cardiometabolic health and diseases and will allow tackling key research questions and very large-scale analyses not otherwise feasible.
Finnish research team
This laboratory is associated with the Computational Medicine Research Team in Oulu, Finland.