New methods to assess the role of coding and non-coding genetic variation in human complex diseases
Approved Research ID: 80963
Approval date: February 22nd 2022
Aims and scientific rationale
For many common diseases, such as Alzheimer´s, type 2 diabetes mellitus, or breast cancer, the precise molecular mechanisms that underpin who is at increased risk for developing the disease are poorly understood. Despite substantial progress in recent years, our ability to predict disease, and to influence underlying causes, is still limited. Another common feature of such diseases is that each on is likely to represent a spectrum of diseases that is lumped into a single category due to our incomplete understanding.
This study will develop methods to tackle this problem using both genetic data (such as whole genome sequencing), as well as non-genetic data available in UK Biobank. It will discover new genetic makers, and develop methods to predict different subtypes of common diseases that are likely to benefit from different types of therapies or prevention strategies.
Public health impact
This research application has the potential to unveil novel approaches to predict disease more accurately, and to uncover molecular mechanisms underlying the pathophysiology of complex diseases that could aid drug discovery. It will reveal unrecognised forms of complex diseases that open new avenues for targeted therapeutic strategies.