Multi-modal generative modeling for joint analysis of single-cell T cell receptor and gene expression data.

Recent advances in single-cell immune profiling have enabled the simultaneous measurement of transcriptome and T cell receptor (TCR) sequences, offering great potential for studying immune responses at the cellular level. However, integrating these diverse modalities across datasets is challenging due to their unique data characteristics and technical variations. Here, to address this, we develop the multimodal generative model mvTCR to fuse modality-specific information across transcriptome and TCR into a shared representation. Our analysis demonstrates the added value of multimodal over unimodal approaches to capture antigen specificity. Notably, we use mvTCR to distinguish T cell subpopulations binding to SARS-CoV-2 antigens from bystander cells. Furthermore, when combined with reference mapping approaches, mvTCR can map newly generated datasets to extensive T cell references, facilitating knowledge transfer. In summary, we envision mvTCR to enable a scalable analysis of multimodal immune profiling data and advance our understanding of immune responses.

Targeting of the CD80/86 proinflammatory axis as a therapeutic strategy to prevent severe COVID-19.

An excessive immune response known as cytokine storm is the hallmark of severe COVID-19. The cause of this cytokine rampage is yet not known. Based on recent epidemiological evidence, we hypothesized that CD80/86 signaling is essential for this hyperinflammation, and that blocking this proinflammatory axis could be an effective therapeutic approach to protect against severe COVID-19. Here we provide exploratory evidence that abatacept, a drug that blocks CD80/86 co-stimulation, produces changes at the systemic level that are highly antagonistic of the proinflammatory processes elicited by COVID-19. Using RNA-seq from blood samples from a longitudinal cohort of n = 38 rheumatic patients treated with abatacept, we determined the immunological processes that are significantly regulated by this treatment. We then analyzed available blood RNA-seq from two COVID19 patient cohorts, a very early cohort from the epicenter of the pandemic in China (n = 3 COVID-19 cases and n = 3 controls), and a recent and larger cohort from the USA (n = 49 severe and n = 51 mild COVD-19 patients). We found a highly significant antagonism between SARS-CoV-2 infection and COVID-19 severity with the systemic response to abatacept. Analysis of previous single-cell RNA-seq data from bronchoalveolar lavage fluid from mild and severe COVID-19 patients and controls, reinforce the implication of the CD80/86 proinflammatory axis. Our functional results further support abatacept as a candidate therapeutic approach to prevent severe COVID-19.