Natalizumab for COVID-19

Abstract Objectives Coronavirus disease 2019 (COVID-19) and SSc share multiple similarities in their clinical manifestations, alterations in immune response and therapeutic options. These resemblances have also been identified in other immune-mediated inflammatory diseases where a common genetic component has been found. Thus, we decided to evaluate for the first time this shared genetic architecture with SSc. Methods For this study, we retrieved genomic data from two European-ancestry cohorts: 2 597 856 individuals from The COVID-19 Host Genetics Initiative consortium, and 26 679 individuals from the largest genomic scan in SSc. We performed a cross-trait meta-analyses including >9.3 million single nucleotide polymorphisms. Finally, we conducted functional annotation to prioritize potential causal genes and performed drug repurposing analysis. Results Our results revealed a total of 19 non-HLA pleiotropic loci, including 2 novel associations for both conditions (BMP1 and PPARG) and 12 emerging as new shared loci. Functional annotation of these regions underscored their potential regulatory role and identified potential causal genes, many of which are implicated in fibrotic and inflammatory pathways. Remarkably, we observed an antagonistic pleiotropy model of the IFN signalling between COVID-19 and SSc, including the well-known TYK2 P1104A missense variant, showing a protective effect for SSc while being a risk factor for COVID-19, along with two additional novel pleiotropic associations (IRF8 and SENP7). Finally, our findings provide new therapeutic options that could potentially benefit both conditions. Conclusion Our study confirms the genetic resemblance between susceptibility to and severity of COVID-19 and SSc, revealing a novel common genetic contribution affecting fibrotic and immune pathways.

AbstractHuman organoids recapitulate the cell type diversity and function of their primary organs holding tremendous potentials for basic and translational research. Advances in single‐cell RNA sequencing (scRNA‐seq) technology and genome‐wide association study (GWAS) have accelerated the biological and therapeutic interpretation of trait‐relevant cell types or states. Here, we constructed a computational framework to integrate atlas‐level organoid scRNA‐seq data, GWAS summary statistics, expression quantitative trait loci, and gene–drug interaction data for distinguishing critical cell populations and drug targets relevant to coronavirus disease 2019 (COVID‐19) severity. We found that 39 cell types across eight kinds of organoids were significantly associated with COVID‐19 outcomes. Notably, subset of lung mesenchymal stem cells increased proximity with fibroblasts predisposed to repair COVID‐19‐damaged lung tissue. Brain endothelial cell subset exhibited significant associations with severe COVID‐19, and this cell subset showed a notable increase in cell‐to‐cell interactions with other brain cell types, including microglia. We repurposed 33 druggable genes, including IFNAR2, TYK2, and VIPR2, and their interacting drugs for COVID‐19 in a cell‐type‐specific manner. Overall, our results showcase that host genetic determinants have cellular‐specific contribution to COVID‐19 severity, and identification of cell type‐specific drug targets may facilitate to develop effective therapeutics for treating severe COVID‐19 and its complications.