The genetics of human trait variation – from atoms to the organism

The number of genetic studies of human traits and diseases has grown over the past years with many thousands of traits analysed by genome-wide association studies or clinical studies. However, connecting trait associated genetic variation to mechanisms through individual proteins and cellular mechanisms remains a challenge. Our group is interested in building computational models that aim to address this challenge. As an example, we have been developing methods to facilitate the interpretation of protein missense variants. To illustrate this, I will present work on the application of AlphaFold2 in predicting the impact of mutations on protein stability, protein-protein and protein-ligand interactions. In parallel, we have been using interaction protein network-based methods to expand and prioritize trait associated genes for over 6000 traits influenced by common and rare mutations, showing how this recovers known disease genes and drug targets. However, the current human protein interaction networks don’t reflect tissue or cell type specificity. To study tissue specificity we are using datasets of protein abundance measurements to predict in which tissues protein interactions are more likely to occur. We can show that protein co-variation is a strong predictor of protein interactions and can be used to build tissue specific interaction networks. These tissue specific networks can be used to link trait/disease associated genes to specific tissues and can serve as a resource for studying tissue specific differences in cell biology and disease. Our goal is to work towards an integrative modelling of human genetic variation that can inform on the impact on protein function, cell biology and the physiology of the organism.