Summary

Humans display substantial interindividual clinical variability after SARS-CoV-2 infection1,2,3, the genetic and immunological basis of which has begun to be deciphered4. However, the extent and drivers of population differences in immune responses to SARS-CoV-2 remain unclear. Here we report single-cell RNA-sequencing data for peripheral blood mononuclear cells—from 222 healthy donors of diverse ancestries—that were stimulated with SARS-CoV-2 or influenza A virus. We show that SARS-CoV-2 induces weaker, but more heterogeneous, interferon-stimulated gene activity compared with influenza A virus, and a unique pro-inflammatory signature in myeloid cells. Transcriptional responses to viruses display marked population differences, primarily driven by changes in cell abundance including increased lymphoid differentiation associated with latent cytomegalovirus infection. Expression quantitative trait loci and mediation analyses reveal a broad effect of cell composition on population disparities in immune responses, with genetic variants exerting a strong effect on specific loci. Furthermore, we show that natural selection has increased population differences in immune responses, particularly for variants associated with SARS-CoV-2 response in East Asians, and document the cellular and molecular mechanisms by which Neanderthal introgression has altered immune functions, such as the response of myeloid cells to viruses. Finally, colocalization and transcriptome-wide association analyses reveal an overlap between the genetic basis of immune responses to SARS-CoV-2 and COVID-19 severity, providing insights into the factors contributing to current disparities in COVID-19 risk.

Overall design

Transcriptional profiles at the single cell level (scRNA-seq) of human PBMCs stimulated for 6h with Influenza A and SARS-CoV-2 viruses in 222 healthy, SARS-CoV-2-naïve individuals of African, European, and East Asian ancestries. For 8 individuals, data is also available at T0 and 24h post stimulation (experimental run 1). For 16 samples (run 16), extracellular protein markers were labelled with the CITE-seq technology in addition to scRNA-seq.

Contributors

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Contact

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