Prediction of Disease Risk in Personalised Medicine

We have developed novel methodology was developed to improve disease prediction from genetic data by using information across multiple phenotypes. There is widespread evidence of genetic correlations among a large number of phenotypes and we developed an approach to use this information by combining summary statistics from many different traits. We have demonstrated that the improvements in prediction through this approach are similar to those gained by combining full sets of genotype-phenotype information on all individuals. As combining individual-level genotype-phenotype data from multiple disease consortia is impossible under current data sharing restrictions, we expect this summary statistic approach to be widely used in future. We are now developing Bayesian methods to further improve prediction accuracy and are developing frameworks to apply these approaches in a clinical setting utilising other forms of information within an individual’s health record.

The Genetics of Human Ageing

This project uses the UKBiobank data, a genotype-phenotype study of 500,000 individuals, multivariate mixed effects models, and novel association mapping techniques. The project will empirically test theory for the genetic basis of ageing, in an experimental design that is unbiased of confounders such as common/shared environment. We are identifying trait-associated loci, testing for age-specific effects, and then replicating our results across other studies. We will test whether age-specific genetic effects involve rare or common loci, whether they cluster into specific genomic annotations, whether the same pathways have the same direction of effects across traits throughout life, and whether the regions identified overlap with those that influence gene expression and gene methylation.

​Genotype-covariate interactions

Whole genome interaction effects have been little studied for human complex traits. We are interested in developing methods to test for interactive effects such as whether the environment modifies genetic predisposition to common disease. This work so far has focussed on body mass index, but more methodological improvement is required as well as application to many more phenotypes.

​Population Genetic Differentiation

We have developed population genetic models to examine the role that selection has played in creating population genetic differences in human complex traits. We are currently working to combine these methods with hundreds of ancient DNA samples across Europe. As part of this proposal, a collaboration with Dr. Ray Tobler and Prof. Alan Cooper at the University of Adelaide who has pioneered the study of ancient human DNA (aDNA). We aim to exploit a unique opportunity to investigate the selective context under which human traits evolved. In particular, we propose an experimental design that utilises the Online Ancient Genome Repository (OAGR) database – the world’s first repository for all available specimen and sequence metadata from ancient humans to generate the first detailed spatio-temporal portrait of human adaptation over periods covering the major socio-cultural transitions in human history. Through merging the fields of aDNA, quantitative genetics, population genetics and evolutionary genomics, we hope this project will reveal the environmental drivers that shaped modern human diversity and pathology. As part of this project, we hope to develop further methodology to investigate changes in genetic covariance among phenotypes across human evolutionary history.

Assortative mating and mate choice​

​Assortative mating occurs when individuals exhibit a preference for pairing with those who are either similar or dissimilar to themselves. In human populations, assortment is almost universally in the same direction, with observed similarities between spouses for quantitative phenotypes, common disease, behaviour, social factors, and personality. Assortative mating can arise from phenotypic assortment based on mate choice, partner interaction and convergence in phenotype over time, or because individuals pair on social or environmental background, referred to as social homogamy. Distinguishing among these mechanisms is a long-standing question. In previous work, we have developed a new design and analytical approach, to show that assortative mating for many human phenotypes occurs through phenotypic assortment based on mate choice across human populations.