Method developments for the genetic analysis of complex traits
Approved Research ID: 59366
Approval date: January 12th 2021
This research project aims at developing innovative statistical methods to study the genomic architecture of complex traits. Complex traits are diseases common in the population, such as diabetes or cancers, but also how a person will respond to a medical treatment. They are complex because they are related to the individuals' genetic factors (each genetic factor is a small sequence of DNA on the individual's chromosome), their environmental factors (the environment they live in, e.g. smoking habits, diet !) and the interactions between these factors. Finding the genetic bases for complex traits is difficult because the effect of the genetic factors may be masked by these interactions.
Most studies only consider the genetic factors one by one and explore very simple scenarios. Going beyond these simple scenarios will require novel methods at the interface between statistics and bioinformatics.
We propose to exploit the biological knowledge present in molecular networks such as on protein-protein interaction networks and metabolic pathways. We are currently developing tools to explore such complex (multi-layer) networks, which could be one way to improve methods to find genetic factors involved in complex traits. In this project, we plan to apply our network exploration methodologies to the UK Biobank genotype and phenotype data to discover novel associations and improve our understanding of the role played by genetic variability in human health and disease.
The project duration will be 36 months.