Uncovering cell-type-specific immunomodulatory variants and molecular phenotypes in COVID-19 using structurally resolved protein networks.

Abstract

Immunomodulatory variants that lead to the loss or gain of specific protein interactions often manifest only as organismal phenotypes in infectious disease. Here, we propose a network-based approach to integrate genetic variation with a structurally resolved human protein interactome network to prioritize immunomodulatory variants in COVID-19. We find that, in addition to variants that pass genome-wide significance thresholds, variants at the interface of specific protein-protein interactions, even though they do not meet genome-wide thresholds, are equally immunomodulatory. The integration of these variants with single-cell epigenomic and transcriptomic data prioritizes myeloid and T cell subsets as the most affected by these variants across both the peripheral blood and the lung compartments. Of particular interest is a common coding variant that disrupts the OAS1-PRMT6 interaction and affects downstream interferon signaling. Critically, our framework is generalizable across infectious disease contexts and can be used to implicate immunomodulatory variants that do not meet genome-wide significance thresholds.