Network expansion of genetic associations defines a pleiotropy map of human cell biology
This work by the Beltrao group recently published in Nature Genetics, describes a network based method to predict novel trait and disease associated genes for more than 1000 human traits. It established relations across the different traits to better understand their biology and explore therapeutic opportunities.
Proteins work together as part of larger molecular machines to perform most of processes that underlie life. Proteins that interact in this way tend to have similar functions and when perturbed often give rise to the same diseases. In the last decades the number of genetic variants and genes linked with human disease has grown dramatically due to the increase in number of Genome Wide Association Studies (GWAS) performed. Studying these GWAS linked genes through protein interaction networks can help better identify the biological processes underlying human traits and diseases.
Barrio-Hernandez and colleagues, used a protein interaction network to predict novel trait associated genes from genome-wide association studies of 1,002 human traits, showing how this can recover known disease genes and drug targets. The analysis can identify groups of traits and diseases that are likely to share a common genetic basis, leading to the identification of cellular processes linked to multiple traits. This work generated a map indicating which molecular machines and cellular processes may influence different human traits and diseases. As there are several approve drugs that can target specific biological processes, this newly generated map can generate candidate ideas for the repurposing of existing drugs to novel disease indications.
Link to to the paper in "external pageNature Genetics".