No abstract

Summary Iron is an essential metal that fine-tunes the innate immune response by regulating macrophage function, but an integrative view of transcriptional and metabolic responses to iron perturbation in macrophages is lacking. Here, we induced acute iron chelation in primary human macrophages and measured their transcriptional and metabolic responses. Acute iron deprivation causes an anti-proliferative Warburg transcriptome, characterized by an ATF4-dependent signature. Iron-deprived human macrophages show an inhibition of oxidative phosphorylation and a concomitant increase in glycolysis, a large increase in glucose-derived citrate pools associated with lipid droplet accumulation, and modest levels of itaconate production. LPS polarization increases the itaconate:succinate ratio and decreases pro-inflammatory cytokine production. In rats, acute iron deprivation reduces the severity of macrophage-dependent crescentic glomerulonephritis by limiting glomerular cell proliferation and inducing lipid accumulation in the renal cortex. These results suggest that acute iron deprivation has in vivo protective effects mediated by an anti-inflammatory immunometabolic switch in macrophages.

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. 203 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.

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.

In response to environmental stimuli, macrophages change their nutrient consumption and undergo an early metabolic adaptation that progressively shapes their polarization state. During the transient, early phase of pro-inflammatory macrophage activation, an increase in tricarboxylic acid (TCA) cycle activity has been reported but the relative contribution of branched chain amino acid (BCAA) leucine remain to be determined. Here we show that glucose but not glutamine is a major contributor of the increase in TCA cycle metabolites during early macrophage activation in humans. We then show that, although BCAA uptake is not altered, their transamination by BCAT1 is increased following 8h lipopolysaccharide (LPS) stimulation. Of note, leucine is not metabolized to integrate the TCA cycle in neither basal nor stimulated human macrophages. Surprisingly, the pharmacological inhibition of BCAT1 reduced glucose-derived itaconate, α-ketoglutarate, and 2-hydroxyglutarate levels, without affecting succinate and citrate levels, indicating a partial inhibition of TCA cycle. This indirect effect is associated with NRF2 activation and anti-oxidant responses. These results suggest a moonlighting role of BCAT1 through redox-mediated control of mitochondrial function during early macrophage activation.

No abstract

Patients with end-stage kidney disease (ESKD) are at high risk of severe COVID-19. Here, we perform longitudinal blood sampling of ESKD haemodialysis patients with COVID-19, collecting samples pre-infection, serially during infection, and after clinical recovery. Using plasma proteomics, and RNA-sequencing and flow cytometry of immune cells, we identify transcriptomic and proteomic signatures of COVID-19 severity, and find distinct temporal molecular profiles in patients with severe disease. Supervised learning reveals that the plasma proteome is a superior indicator of clinical severity than the PBMC transcriptome. We show that a decreasing trajectory of plasma LRRC15, a proposed co-receptor for SARS-CoV-2, is associated with a more severe clinical course. We observe that two months after the acute infection, patients still display dysregulated gene expression related to vascular, platelet and coagulation pathways, including PF4 (platelet factor 4), which may explain the prolonged thrombotic risk following COVID-19.

End-stage kidney disease (ESKD) patients are at high risk of severe COVID-19. We performed dense serial blood sampling in hospitalised and non-hospitalised ESKD patients with COVID-19 (n=256 samples from 55 patients) and used Olink immunoassays to measure 436 circulating proteins. Comparison to 51 non-infected ESKD patients revealed 221 proteins differentially expressed in COVID-19, of which 69.7% replicated in an independent cohort of 46 COVID-19 patients. 203 proteins were associated with clinical severity scores, including IL6, markers of monocyte recruitment (e.g. CCL2, CCL7), neutrophil activation (e.g proteinase-3) and epithelial injury (e.g. KRT19). Random Forests machine learning identified predictors of current or future severity such as KRT19, PARP1, PADI2, CCL7, and IL1RL1 (ST2). Survival analysis with joint models revealed 69 predictors of death including IL22RA1, CCL28, and the neutrophil-derived chemotaxin AZU1 (Azurocidin). Finally, longitudinal modelling with linear mixed models uncovered 32 proteins that display different temporal profiles in severe versus non-severe disease, including integrins and adhesion molecules. Our findings point to aberrant innate immune activation and leucocyte-endothelial interactions as central to the pathology of severe COVID-19. The data from this unique cohort of high-risk individuals provide a valuable resource for identifying drug targets in COVID-19.