Pathogens impose selection pressures on human genomes. Depending on local environments, over time this pressure may lead to population-specific genetic variation that differentially affects infectious disease susceptibility. Randolph et al. sought to characterize the genetic determinants of differences in immune responses to viral infection between individuals of European and African ancestries.

Previous work investigating the effects of genetic ancestry on the response to viral infection focused on isolated cell types and was thus unable to discern interactions between different immune cells or distinguish between cell-type-specific and general effects. The authors infected peripheral blood mononuclear cells (PBMCs), obtained from 90 men of European or African ancestries, with influenza A virus (IAV) or mock treatment and obtained single-cell RNA sequencing (scRNA-seq) profiles after 6 h. Whole-genome sequencing was performed to estimate the proportion of African and European ancestries for each individual.

Differential gene expression analysis of the major PBMC cell types allowed the dissection of cell-type-specific versus shared responses and confirmed previous findings that monocytes exhibit the strongest response to IAV infection. While some responses correlated across cell types, opposing responses were also observed, for example, between monocytes and natural killer cells, despite these cell types sharing several differentially expressed genes.

Next, the team identified 1,949 genes whose expression levels correlated with the proportion of estimated ancestry. These population differentially expressed genes were highly cell type-specific and were enriched for transcriptional and translational functions. Gene-set enrichment analysis revealed differences in type I and II interferon pathways associated with genetic ancestry, with further experiments indicating that genetic ancestry may predict the magnitude of response to IAV infection. Indeed, increased degrees of European ancestries were associated with higher type I interferon activity during the early response to infection, which was able to predict a reduction in viral titres occurring at later stages. Mapping expression quantitative trait loci (eQTLs) in the IAV-infected and control samples revealed that cis eQTLs explain >50% of population differences in response to viral infection.

cis eQTLs explain >50% of population differences in response to viral infection

Finally, ancestry-related differentially expressed genes were enriched for genes associated with COVID-19 disease severity. While it remains to be seen whether this translates to differences in COVID-19 outcomes, it will be important to ensure that host genetic variation in the immune response does not exacerbate existing health disparities driven by external circumstances.