Poster AA13 - Uncovering cell-type-specific immunomodulatory variants and associated molecular phenotypes in infectious disease using structurally-resolved protein networks

Introduction: Past work has demonstrated the importance of incorporating structural information in the integration of Mendelian mutations with protein networks, to elucidate molecular phenotypes of genetic disease. However, genomic variation in infectious disease is far more nuanced, as specific pathogens cause these disorders and genetic variants are immunomodulatory. Here, we present a novel pipeline that integrates a structurally-resolved reference human protein interactome with signaling cascades inferred from expression and chromatin accessibility to uncover cell-type-specific immunomodulatory molecular phenotypes in infectious disease. We used Covid-19 as an exemplar, but the framework is broadly applicable. We combined genotype data for COVID-19 disease occurrence and severity with a structurally-resolved human protein interactome to identify coding mutations at and away from the interfaces of specific protein-protein interactions. We compared cell-type-specific functional impacts of these variants to non-coding regulatory variants that attain/do not attain genome-wide significance. The functional impact of these classes of mutations on different specific cell types was inferred via network propagation of the effects of these mutations on cell-intrinsic and cell-extrinsic signaling networks inferred from scRNA-seq and scATAC-seq data. We recapitulated well-known roles of classical and non-classical monocytes in Covid-19 pathogenesis. However, surprisingly, we found that most of the signal was driven by only a handful of prioritized coding variants at interaction interfaces. These were functionally as important as genome-wide-significant regulatory variants, and both sets were far more important than other variants. We also converged on and validated a novel common variant on OAS1 that modulates disease risk via altering interferon signaling.

Materials and

Methods: While Mendelian disorders are typically monogenic and often attributable to a handful of high penetrance mutations, the role of genomic variation in infectious disease is far more nuanced, as specific pathogens cause these disorders and the genetic variants are immunomodulatory. Here, we present a novel pipeline that integrates a structurally resolved reference human protein interactome with signaling cascades inferred from expression and chromatin accessibility data to uncover cell-type-specific immunomodulatory molecular phenotypes in infectious disease. We used Covid-19 as an exemplar given the availability of deep genotype data from the Covid-HGI, and corresponding cellular and molecular data. However, the framework is broadly applicable across infectious disease contexts. We combined genotype data for COVID-19 disease occurrence and severity with a structurally resolved reference human protein interactome network to identify coding mutations at and away from the interfaces of specific protein-protein interactions. We then compared the cell-type-specific functional impact of these variants to non-coding regulatory variants that attain/do not attain genome-wide significance. The functional impact of these classes of mutations on different specific cell types was inferred via network propagation of the effects of these mutations on cell-intrinsic and cell-extrinsic signaling networks inferred from scRNA-seq and scATAC-seq data. Mutation effects within cell types were also ensembled to evaluate the relative importance of different cell types in Covid-19 pathogenesis. Key hits from our pipeline were validated using edgotyping assays.

Results, Conclusions, and Discussions: We recapitulated the well-known roles of classical and non-classical monocytes in Covid-19 pathogenesis. However, surprisingly, we found that a large component of the signal was driven by only a handful of prioritized coding variants at specific protein interaction interfaces. These were functionally as important as genome-wide-significant regulatory variants, and both sets were far more important than all other classes of variants. The same results were observed both in terms of overall odds ratios of disease vs healthy and more granular trait-relevance scores. We also recapitulated the same trend using scRNA-seq and scATAC-seq data from both the peripheral compartment (PBMCs) and bronchoalveolar lavage samples. Intriguingly, the handful of coding interface variants (~50) captured the same signal as thousands of genome-wide significant variants. The interface variants also captured dysregulated crosstalk between myeloid cells and T cells; this was missed by the genome-wide significant variants.
Of particular interest, was a common coding variant, that is not genome-wide significant, with a minor allele frequency of 40%, at the interface of the OAS1-PRMT6 interaction. While the OAS1 locus has recently been reported to have critical immunomodulatory roles in Covid-19 via altered gene regulation and/or splicing, the variant we uncovered is novel and immunomodulatory via the modulation of the TBK1-IRF3 axis and downstream interferon signaling. Our hit was validated using downstream validation experiments that confirmed disruption of the corresponding interaction by this coding variant. Thus, our framework demonstrates the importance of examining coding interface variants that are not genome-wide significant. We also converged on a novel molecular phenotype that explains a key component of the variance in the host immune response to Covid-19.

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