Ehsan Tamandeh, Kiran Kunwar, Jessica Bigge, Adrian Serohijos, Johannes Schumacher, Carlo Maj, Pouria Dasmeh
Together, these findings provide a systems-level framework linking molecular interaction architecture to the evolution of human polygenic traits. To support this effort, we also develop an online portal enabling researchers to generate and explore hypotheses by identifying genes that are both highly associated and highly connected across thousands of polygenic phenotypes.
BACKGROUND: Human polygenic phenotypes arise from the combined effects of many genes that interact within molecular networks. Yet, we know little about how the structure of these networks constrains or facilitates the evolution of complex traits. Here, we systematically examine the relationship between protein-protein interaction (PPI) network architecture and evolutionary signatures across 4,756 human polygenic phenotypes.
RESULTS: We show that genes associated with polygenic phenotypes exhibit significantly higher connectivity within the global PPI network compared to matched random gene sets. Highly connected genes are enriched for immune-related biological processes, whereas genes with fewer interactions are preferentially associated with neurogenesis-related functions. Importantly, among trait-associated genes, greater network connectivity is associated with weaker selective constraint, indicating that evolutionary pressure varies according to network embedding.
CONCLUSIONS: Together, these findings provide a systems-level framework linking molecular interaction architecture to the evolution of human polygenic traits. To support this effort, we also develop an online portal enabling researchers to generate and explore hypotheses by identifying genes that are both highly associated and highly connected across thousands of polygenic phenotypes.