Research projects

Quantifying the impact of genetic variation on ageing-related diseases

Over the past decade, we have phenotyped several thousand mice of varying genetic backgrounds across their natural lifespans, observing the natural progression of age and the gradual accumulation of metabolic disorders. This population centred on a diverse collection of inbred BXD strains, was fed either low-fat and high-fat diets across their natural lifespans. Average lifespans were reduced by about 10% on high-fat feeding, whereas genetic factors have a tremendous effect size, with a more than 3-fold range in lifespan depending on genotype. Thus far, we have largely focused on liver disease, but since moving to the LCSB in May 2020, we have started extending our analytical approach to other tissues and their related diseases. We intend to continue large-scale sequencing and mass spectrometric approaches to quantifying the transcriptome, proteome, and metabolome in order to identify new causal genes underlying metabolic variation and to validate these candidate genes either in mice or, when suitable, in simpler model organisms such as C. elegans.

Modelling the fundamental relationships between DNA variants and their impact on mRNA and protein expression

The molecular networks underlying liver diseases, particularly non-alcoholic fatty liver disease, are strikingly variable across the BXD population as a function of age, diet, and genotype. We are currently analyzing the recently-generated multi-omics liver datasets for de novo hypothesis discovery on the aetiology of ageing and the development of associated metabolic diseases. Once the initial stage of the lab setup is finished (~summer 2020), we intend to process additional tissues collected from the same individuals at the same timepoints, which will provide us with the capacity for a reference database on ageing tissue samples taken from a large in vivo population—a resource which is not yet available in any mammalian population. Such large datasets provide us with the capacity to test for causality.