Validation of multi-step disease trajectories and identification of underlying genetics risks
Principal Investigator: Professor Soren Brunak
Approved Research ID: 31823
Approval date: June 25th 2018
The aim of the project is to validate general disease co-occurrences and trajectories that we have identified in the complete Danish population through systematic studies. Further, we wish to perform a phenome-wide association study (PheWAS) of our validated disease co-occurrences and trajectories to examine if there is any association to molecular phenotypes. We will look broadly at all diseases, both self-reported and from hospital admission data. Replication of our findings and association to molecular phenotypes are of general interest and important to the understanding of multi-morbidity disease progression, differences between men and women, and ultimately the interaction between disease mechanisms. This project focuses on differences in health, diseases and complications derived from associations in big data. Findings from this study are in the general interest of the public as they can prove prognostic in clinical settings or help explain disease etiology, and thus shape future healthcare. We will explore disease co-occurrences in a systematic manner to identify associations and multi-step trajectories of disease progression in the context of multi-morbidities. The multi-step trajectories will be compared with our findings in the Danish population, and we will explore if underlying changes in the genome are associated with any of the multi-step trajectories. We wish to include the full cohort in our study. To mitigate common confounding factors, such as age, sex and social status, we require a large amount of controls. Disease trajectories require in general large data sets (the Danish set comprise 7 million patients) as we need to test for directional significance in the progression.