The cGAS-STING pathway drives type I IFN immunopathology in COVID-19.

COVID-19, which is caused by infection with SARS-CoV-2, is characterized by lung pathology and extrapulmonary complications <sup>1,2</sup> . Type I interferons (IFNs) have an essential role in the pathogenesis of COVID-19 (refs <sup>3-5</sup> ). Although rapid induction of type I IFNs limits virus propagation, a sustained increase in the levels of type I IFNs in the late phase of the infection is associated with aberrant inflammation and poor clinical outcome <sup>5-17</sup> . Here we show that the cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) pathway, which controls immunity to cytosolic DNA, is a critical driver of aberrant type I IFN responses in COVID-19 (ref. <sup>18</sup> ). Profiling COVID-19 skin manifestations, we uncover a STING-dependent type I IFN signature that is primarily mediated by macrophages adjacent to areas of endothelial cell damage. Moreover, cGAS-STING activity was detected in lung samples from patients with COVID-19 with prominent tissue destruction, and was associated with type I IFN responses. A lung-on-chip model revealed that, in addition to macrophages, infection with SARS-CoV-2 activates cGAS-STING signalling in endothelial cells through mitochondrial DNA release, which leads to cell death and type I IFN production. In mice, pharmacological inhibition of STING reduces severe lung inflammation induced by SARS-CoV-2 and improves disease outcome. Collectively, our study establishes a mechanistic basis of pathological type I IFN responses in COVID-19 and reveals a principle for the development of host-directed therapeutics

Differentiation of IL-26+ TH17 intermediates into IL-17A producers via epithelial crosstalk in psoriasis.

Interleukin (IL)-26 is a T <sub>H</sub> 17 cytokine with known antimicrobial and pro-inflammatory functions. However, the precise role of IL-26 in the context of pathogenic T <sub>H</sub> 17 responses is unknown. Here we identify a population of blood T <sub>H</sub> 17 intermediates that produce high levels of IL-26 and differentiate into IL-17A-producing T <sub>H</sub> 17 cells upon TGF-β1 exposure. By combining single cell RNA sequencing, TCR sequencing and spatial transcriptomics we show that this process occurs in psoriatic skin. In fact, IL-26+ T <sub>H</sub> 17 intermediates infiltrating psoriatic skin induce TGF-β1 expression in basal keratinocytes and thereby promote their own differentiation into IL-17A-producing cells. Thus, our study identifies IL-26-producing cells as an early differentiation stage of T <sub>H</sub> 17 cells that infiltrates psoriatic skin and controls its own maturation into IL17A-producing T <sub>H</sub> 17 cells, via epithelial crosstalk involving paracrine production of TGF-β1

Cross-comparison of inflammatory skin disease transcriptomics identifies PTEN as a pathogenic disease classifier in cutaneous lupus erythematosus.

Tissue transcriptomics is used to uncover molecular dysregulations underlying diseases. However, the majority of transcriptomics studies focus on single diseases with limited relevance for understanding the molecular relationship between diseases or for identifying disease-specific markers. Here, we used a normalization approach to compare gene expression across nine inflammatory skin diseases. The normalized datasets were found to retain differential expression signals that allowed unsupervised disease clustering and identification of disease-specific gene signatures. Using the NS-Forest algorithm, we identified a minimal set of biomarkers and validated their use as diagnostic disease classifier. Among them, PTEN was identified as being a specific marker for cutaneous lupus erythematosus (CLE) and found to be strongly expressed by lesional keratinocytes in association with pathogenic type I interferons (IFNs). In fact, PTEN facilitated expression of IFN-β and IFN-κ in keratinocytes by promoting activation and nuclear translocation of IRF3. Thus, cross-comparison of tissue transcriptomics is a valid strategy to establish a molecular disease classification and identify pathogenic disease biomarkers