Approved Research

Assessing covariate-mediated polygenetic risk scores for mortality

Lay summary

Technological advances have made genetic data easier to obtain at large scale, holding the promise of an individualised approach to genetic-informed health care. That said, the same genetics that informs treatment may also be predictive of risk, which can be notably used to predict life expectancy more accurately. Here we use large scale genetic data to model mortality risk and assess its contribution relative to more conventional mortality factors such as health and family history.

The public health impact of the proposed research is multitudinous. The most notable impact of whole DNA incorporation into models for mortality prediction will allow us to find out whether using entire DNA sequencing is too course for increasing accuracy of life expectancy predictions or whether it can in fact add to current models at play in the health sector. In this sense, DNA can potentially allow individuals to better evaluate their mortality and thereby optimise their own health outcomes through lifestyle choices based on better informed decision making processes.  Additionally, the research would allow health professionals to give more tailored advice to their patients, thus allowing such individuals to take ownership of their health with greater confidence and potentially making choices that are more effective in prolonging their wellbeing.

As a preliminary study to future models and investigations, we anticipate a 12-month project duration.