SUMMARY While many genetic variants have been associated with risk for human diseases, how these variants affect gene expression in various cell types remains largely unknown. To address this gap, the DICE (Database of Immune Cell Expression, Expression quantitative trait loci (eQTLs) and Epigenomics) project was established. Considering all human immune cell types and conditions studied, we identified cis-eQTLs for a total of 12,254 unique genes, which represent 61% of all protein-coding genes expressed in these cell types. Strikingly, a large fraction (41%) of these genes showed a strong cis-association with genotype only in a single cell type. We also found that biological sex is associated with major differences in immune cell gene expression in a highly cell-specific manner. These datasets will help reveal the effects of disease risk-associated genetic polymorphisms on specific immune cell types, providing mechanistic insights into how they might influence pathogenesis (http://dice-database.org).

The contribution of CD4 + T cells to protective or pathogenic immune responses to SARS-CoV-2 infection remains unknown. Here, we present single-cell transcriptomic analysis of >100,000 viral antigen-reactive CD4 + T cells from 40 COVID-19 patients. In hospitalized patients compared to non-hospitalized patients, we found increased proportions of cytotoxic follicular helper (T FH ) cells and cytotoxic T helper cells (CD4-CTLs) responding to SARS-CoV-2, and reduced proportion of SARS-CoV-2-reactive regulatory T cells (T REG ). Importantly, in hospitalized COVID-19 patients, a strong cytotoxic T FH response was observed early in the illness which correlated negatively with antibody levels to SARS-CoV-2 spike protein. Polyfunctional T helper (T H )1 and T H 17 cell subsets were underrepresented in the repertoire of SARS-CoV-2-reactive CD4 + T cells compared to influenza-reactive CD4 + T cells. Together, our analyses provide insights into the gene expression patterns of SARS-CoV-2-reactive CD4 + T cells in distinct disease severities.