Human disease arises from genetically-encoded or acquired perturbations in protein expression or activity. These initiate the transition from wellbeing to illness through effects on physiology, metabolism and organ and systems function. Therefore, understanding disease mechanism centres on the identification of the relevant protein-disease relationships and the downstream phenotypic consequences. Knowledge of these is a pre-requisite for drug development (since almost all drug targets are proteins), and also for precision medicine since the prevailing mechanisms in an individual, by definition, deviate from average effects in populations. New opportunities for deeper understanding of human disease mechanisms and individual differences in susceptibility come from the falling cost, accuracy and scalability of genomic (and now proteomic and metabolomic) technologies; safe, high-resolution, imaging modalities such as magnetic resonance imaging; as well as the availability for research, of millions of routine clinical measurements and health outcomes in NHS electronic health records. With these tools, connectivity between the genome, environment and phenome (in individuals and in populations) becomes possible with unprecedented scale and detail.

Our work centres of discovering genotype-phenotype relationships through multi -omics and disease outcome data from population and patient cohorts. We use statistical genetics, bioinformatics and computational biology methods, to organise, make sense of and apply the data to support precision medicine. A particular focus is on accurate drug target identification and validation through human genomics.

The group serves as the co-ordinating centre for the University College London-Edinburgh-Bristol Consortium of cohort studies.