Type I interferons affect the metabolic fitness of CD8+ T cells from patients with systemic lupus erythematosus.

The majority of patients with systemic lupus erythematosus (SLE) have high expression of type I IFN-stimulated genes. Mitochondrial abnormalities have also been reported, but the contribution of type I IFN exposure to these changes is unknown. Here, we show downregulation of mitochondria-derived genes and mitochondria-associated metabolic pathways in IFN-High patients from transcriptomic analysis of CD4+ and CD8+ T cells. CD8+ T cells from these patients have enlarged mitochondria and lower spare respiratory capacity associated with increased cell death upon rechallenge with TCR stimulation. These mitochondrial abnormalities can be phenocopied by exposing CD8+ T cells from healthy volunteers to type I IFN and TCR stimulation. Mechanistically these 'SLE-like' conditions increase CD8+ T cell NAD+ consumption resulting in impaired mitochondrial respiration and reduced cell viability, both of which can be rectified by NAD+ supplementation. Our data suggest that type I IFN exposure contributes to SLE pathogenesis by promoting CD8+ T cell death via metabolic rewiring.

Longitudinal proteomic profiling of dialysis patients with COVID-19 reveals markers of severity and predictors of death.

End-stage kidney disease (ESKD) patients are at high risk of severe COVID-19. We measured 436 circulating proteins in serial blood samples from hospitalised and non-hospitalised ESKD patients with COVID-19 (n = 256 samples from 55 patients). Comparison to 51 non-infected patients revealed 221 differentially expressed proteins, with consistent results in a separate subcohort of 46 COVID-19 patients. Two hundred and three proteins were associated with clinical severity, including IL6, markers of monocyte recruitment (e.g. CCL2, CCL7), neutrophil activation (e.g. proteinase-3), and epithelial injury (e.g. KRT19). Machine-learning identified predictors of severity including IL18BP, CTSD, GDF15, and KRT19. Survival analysis with joint models revealed 69 predictors of death. Longitudinal modelling with linear mixed models uncovered 32 proteins displaying different temporal profiles in severe versus non-severe disease, including integrins and adhesion molecules. These data implicate epithelial damage, innate immune activation, and leucocyte-endothelial interactions in the pathology of severe COVID-19 and provide a resource for identifying drug targets.

COVID-19 varies from a mild illness in some people to fatal disease in others. Patients with severe disease tend to be older and have underlying medical problems. People with kidney failure have a particularly high risk of developing severe or fatal COVID-19. Patients with severe COVID-19 have high levels of inflammation, causing damage to tissues around the body. Many drugs that target inflammation have already been developed for other diseases. Therefore, to repurpose existing drugs or design new treatments, it is important to determine which proteins drive inflammation in COVID-19. Here, Gisby, Clarke, Medjeral-Thomas et al. measured 436 proteins in the blood of patients with kidney failure and compared the levels between patients who had COVID-19 to those who did not. This revealed that patients with COVID-19 had increased levels of hundreds of proteins involved in inflammation and tissue injury. Using a combination of statistical and machine learning analyses, Gisby et al. probed the data for proteins that might predict a more severe disease progression. In total, over 200 proteins were linked to disease severity, and 69 with increased risk of death. Tracking how levels of blood proteins changed over time revealed further differences between mild and severe disease. Comparing this data with a similar study of COVID-19 in people without kidney failure showed many similarities. This suggests that the findings may apply to COVID-19 patients more generally. Identifying the proteins that are a cause of severe COVID-19 ­ rather than just correlated with it ­ is an important next step that could help to select new drugs for severe COVID-19.

Induced pluripotent stem cell line MUSIi006-A derived from hair follicle keratinocytes as a non-invasive somatic cell source.

In this study, we used hair follicle keratinocytes for reprogramming. Collection of plucked hairs offers advantages over other somatic cells because no medical professional or operation room is required. Keratinocytes were isolated from plucked hairs of a 21-year-old healthy woman and characterized for the expression of cytokeratin 14 (CK14). Reprogramming of keratinocytes was performed using Sendai virus. Further characterization of the keratinocyte-derived iPSC line (designated as MUSIi006-A) confirmed that the cell line was pluripotent, free from Sendai viral genome and transgenes, and retained normal karyotype. Our method represents an easy, non-invasive and efficient approach for iPSC generation from hair samples.