ABSTRACT
Severe lung damage in COVID-19 involves complex interactions between diverse populations of immune and stromal cells. In this study, we used a spatial transcriptomics approach to delineate the cells, pathways and genes present across the spectrum of histopathological damage in COVID-19 lung tissue. We applied correlation network-based approaches to deconvolve gene expression data from areas of interest within well preserved post-mortem lung samples from three patients. Despite substantial inter-patient heterogeneity we discovered evidence for a common immune cell signaling circuit in areas of severe tissue that involves crosstalk between cytotoxic lymphocytes and pro-inflammatory macrophages. Expression of IFNG by cytotoxic lymphocytes was associated with induction of chemokines including CXCL9, CXCL10 and CXCL11 which are known to promote the recruitment of CXCR3+ immune cells. The tumour necrosis factor (TNF) superfamily members BAFF (TNFSF13B) and TRAIL (TNFSF10) were found to be consistently upregulated in the areas with severe tissue damage. We used published spatial and single cell SARS-CoV-2 datasets to confirm our findings in the lung tissue from additional cohorts of COVID-19 patients. The resulting model of severe COVID-19 immune-mediated tissue pathology may inform future therapeutic strategies. One Sentence SummarySpatial analysis identifies IFN{gamma} response signatures as focal to severe alveolar damage in COVID-19 pneumonitis.
ABSTRACT
Treatment of severe COVID-19 is currently limited by clinical heterogeneity and incomplete understanding of potentially druggable immune mediators of disease. To advance this, we present a comprehensive multi-omic blood atlas in patients with varying COVID-19 severity and compare with influenza, sepsis and healthy volunteers. We identify immune signatures and correlates of host response. Hallmarks of disease severity revealed cells, their inflammatory mediators and networks as potential therapeutic targets, including progenitor cells and specific myeloid and lymphocyte subsets, features of the immune repertoire, acute phase response, metabolism and coagulation. Persisting immune activation involving AP-1/p38MAPK was a specific feature of COVID-19. The plasma proteome enabled sub-phenotyping into patient clusters, predictive of severity and outcome. Tensor and matrix decomposition of the overall dataset revealed feature groupings linked with disease severity and specificity. Our systems-based integrative approach and blood atlas will inform future drug development, clinical trial design and personalised medicine approaches for COVID-19.
