Abstract

Genetic studies of schizophrenia (SCZ) increasingly reveal a complex polygenic risk architecture reflecting the aggregate impact of hundreds of risk variants, the majority of which are predicted to have individually small effects. Towards resolving how these variants interact to contribute to SCZ risk, we previously described a gene expression effect based on the combined CRISPRa/RNAi perturbation of four SCZ risk genes (“eGenes”, whose expression is regulated by common variants) that was not predicted by their individual perturbations and that was most non-additive (“synergistic”) among genes associated with synaptic function and SCZ risk. Now, across fifteen SCZ eGenes, we demonstrate that synergy is greatest within groups of functionally similar eGenes. At the transcriptomic level, individual eGene perturbations reveal common downstream effects (“convergence”), while combinatorial eGene perturbations result in changes that are smaller than predicted by summing individual eGene effects (“saturation”). These convergent and synergistic genes overlap, suggesting that functional redundancy of eGenes may be a major mechanism underlying non-additivity. At the cellular level, combinatorial eGene perturbations yield phenotypes opposite to the effects predicted from single gene perturbations. By unravelling the interactions between complex risk variants, it may be possible to improve the clinical utility of polygenic risk scores by identifying novel targets for therapeutic intervention.