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Heparan sulfate (HS) polysaccharides are ubiquitous in animal tissues as components of proteoglycans, and they participate in many important biological processes. HS carbohydrate chains are complex and can contain rare structural components such as N-unsubstituted glucosamine (GlcN). Commercially available HS preparations have been invaluable in many types of research activities. In the course of preparing microarrays to include probes derived from HS oligosaccharides, we found an unusually high content of GlcN residue in a recently purchased batch of porcine intestinal mucosal HS. Composition and sequence analysis by mass spectrometry of the oligosaccharides obtained after heparin lyase III digestion of the polysaccharide indicated two and three GlcN in the tetrasaccharide and hexasaccharide fractions, respectively. (1)H NMR of the intact polysaccharide showed that this unusual batch differed strikingly from other HS preparations obtained from bovine kidney and porcine intestine. The very high content of GlcN (30%) and low content of GlcNAc (4.2%) determined by disaccharide composition analysis indicated that N-deacetylation and/or N-desulfation may have taken place. HS is widely used by the scientific community to investigate HS structures and activities. Great care has to be taken in drawing conclusions from investigations of structural features of HS and specificities of HS interaction with proteins when commercial HS is used without further analysis. Pending the availability of a validated commercial HS reference preparation, our data may be useful to members of the scientific community who have used the present preparation in their studies.

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.

Funder: The Sidharth Burman endowment, 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.

Dengue disease is a mosquito-borne condition that has become a major public health concern. Dengue severity can be classified into mild Dengue fever (DF) and severe Dengue or Dengue hemorrhagic fever (DHF). Genetic polymorphisms and variations in the host immune response are believed to contribute to different degrees to the disease progression. In this study, factors that have an influence on Dengue infection were identified. Genetic variants in the complement system, of which the degree of activation increases with Dengue severity, were identified. There was no association between the disease and complement genetic variants (complement factor H [CFH] rs3753394, CFH rs1061170, CFH rs800292, complement factor B (FB) rs12614/rs641153 and complement C3 rs2230199) in Thai cohorts. By contrast, with multiplex bead immunoassay, numerous biological markers measured in the plasma of Dengue patients were shown to increase the risk of Dengue severity. Up-regulation of plasma matrix metalloproteinase 3 (MMP-3) was shown to be associated with the risk of developing DHF even though recombinant MMP-3 (rMMP-3) did not affect endothelial permeability in vitro. Finally, an early predictive model to predict DHF was examined by using binary logistic regression. Low platelet cell count and high plasma levels of Monocyte chemotactic protein 2 (MCP2) were identified as early indicators. Sensitivity, specificity, and accuracy of the test were 73.17%, 83.13% and 82%, respectively. These data might be useful in the development of therapeutic agents and predictive markers for Dengue infection. Open Access