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.

Background Complement activation may play a pathogenic role in patients with severe coronavirus disease 2019 (COVID-19) by contributing to tissue inflammation and microvascular thrombosis. Methods Serial samples were collected from patients receiving maintenance haemodialysis (HD). Thirty-nine patients had confirmed COVID-19 and 10 patients had no evidence of COVID-19. Plasma C5a and C3a levels were measured using enzyme-linked immunosorbent assay. Results We identified elevated levels of plasma C3a and C5a in HD patients with severe COVID-19 compared with controls. Serial sampling identified that C5a levels were elevated prior to clinical deterioration in patients who developed severe disease. C3a more closely mirrored both clinical and biochemical disease severity. Conclusions Our findings suggest that activation of complement plays a role in the pathogenesis of COVID-19, leading to endothelial injury and lung damage. C5a may be an earlier biomarker of disease severity than conventional parameters such as C-reactive protein and this warrants further investigation in dedicated biomarker studies. Our data support the testing of complement inhibition as a therapeutic strategy for patients with severe COVID-19.

Salt intake is an essential dietary requirement, but excessive consumption is implicated in hypertension and associated conditions. Little is known about the neural circuit mechanisms that control motivation to consume salt, although the midbrain dopamine system, which plays a key role in other reward-related behaviors, has been implicated. We, therefore, examined the effects on salt consumption of either optogenetic excitation or chemogenetic inhibition of ventral tegmental area (VTA) dopamine neurons in male mice. Strikingly, optogenetic excitation of dopamine neurons decreased salt intake in a rapid and reversible manner, despite a strong salt appetite. Importantly, optogenetic excitation was not aversive, did not induce hyperactivity, and did not alter salt concentration preferences in a need-free state. In addition, we found that chemogenetic inhibition of dopamine neurons had no effect on salt intake. Lastly, optogenetic excitation of dopamine neurons reduced consumption of sucrose following an overnight fast, suggesting a more general role of VTA dopamine neuron excitation in organizing motivated behaviors.

Changing dialysate acid concentrates, both labeled 1:44 dilution, led to the delivery of a higher dialysate sodium, resulting in weight gains, increased pre-dialysis blood pressure, but less symptomatic intradialytic hypotension. Following readjustment of volumetric dialysate mixing, excess weight gains and increased blood pressure resolved over 4 weeks, highlighting the importance of checking the delivered dialysate sodium following a change in dialysate acid concentrate.

Our single-centre experience suggests that a single dose of rituximab of 375 mg/m(2) is a reasonable and more cost-effective therapy for inducing remission in patients with AAV.

Introduction Sodium balance during hemodialysis is predominantly achieved by ultrafiltration. The additional effect of diffusional sodium losses and gains remains unclear. We recently changed our dialysate acid concentrate supplier, and although both concentrates were instructed to be diluted 1:44, we audited the practical effects of this change. Methods Review of electronic dialysis and laboratory records of patients attending a satellite dialysis center. Results 91 adult hemodialysis patients, mean age 61.4 ± 1.7 years, 65% male, 52% diabetic, median dialysate sodium machine setting at 137 mmol/l (137–138), following change in acid dialysate patients dialyzed against a mean measured dialysate sodium of 4.8 (95%cCL 3.6–6.1) mmol/l higher than setting. After six weeks, pre-dialysis weight increased from 75.5 ± 1.9 kg to 76.6 ± 1.9 kg, p<0.001, with increased mean weight loss on dialysis from 2.38 ± 0.1% to 3.28 ± 0.13%, p<0.001, and increase in pre-dialysis mean arterial blood pressure from 91.2 ± 1.5 mm Hg to 95.4 ± 1.5 mm Hg, p<0.001. Post-dialysis serum sodium increased from 0 (–3 to +3) mmol/l to +3 (1 to 5.5) mmol/l compared to pre-dialysis value, p<0.001. Monthly symptomatic episodes of intradialytic hypotension fell from 69 to 46. After correcting the dialysate sodium setting, blood pressure and weight gains resolved over 4 weeks. Conclusions Changing dialysate acid concentrates, both labeled 1:44 dilution, led to the delivery of a higher dialysate sodium, resulting in weight gains, increased pre-dialysis blood pressure, but less symptomatic intradialytic hypotension. Following readjustment of volumetric dialysate mixing, excess weight gains and increased blood pressure resolved over 4 weeks, highlighting the importance of checking the delivered dialysate sodium following a change in dialysate acid concentrate.

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.

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.