Matthew's Group

Introduction - what do we do?

We develop novel statistical methodology and apply this to large human phenotype-genotype datasets (‘big data’) to address long-standing questions in population, quantitative, and medical genetics. Our approaches have improved accuracy for the prediction of disease risk in personalized medicine, quantified the contribution of genotype-environment interaction effects to obesity risk, and provided frameworks to examine the underlying genetic basis of phenotypic differences among groups of people as well as phenotypic similarities within families. Current work focuses on improved testing for sex-, age-, or environment-specific genetic effects, quantifying maternal genetic and social genetic effects, and investigating the role of genetic interactions between microbial and host genotype in shaping phenotype in the human population.


Complex Trait Genetics Group

Department of Computational Biology

Quartier Sorge, Bâtiment Génopode

Univerisité de Lausanne

1015 Lausanne

el+41 21 692 39 16

Research Highlights

Matt established the Complex Trait Genetics Group in March this year. We published the first large-scale genotype-covariate interaction study of obesity in Nature Genetics, finding that genetic effects for body mass index change through life, but that genotype-environment interactions likely contribute little to differences among people in weight gain. We have also shown how prediction of person's risk of disease can be improved by using information from correlated disorders (to appear in Nature Communications). In 2017, Matt co-authored an additional ten papers on a wide range of research topics including assortative mating in humans (in Nature Human Behaviour), better identification of disease interventions (Nature Communications), assessing differences in genetic effects for education and fertility across countries (Nature Human Behaviour), quantifying natural selection in current human populations (PNAS), estimating the effects of inbreeding (PNAS), determining how responses to climate change depends upon previous experience (Nature Ecology and Evolution), and improving our understanding of the genetic basis of psychiatric (Psycological Medicine) and neurological disorders (Molecular Genetics & Genomic Medicine). Post-doc Daniel Trejo Baños joined in October and post-doc Athanasios Kousathanas will join in January, and we look forward in 2018 to developing models to improve prediction of disease risk from clinical and genetic risk factors, and to better characterising genetic effects for a range of common complex disorders.

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