Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 2 de 2
Filter
Add more filters










Language
Publication year range
1.
Preprint in English | bioRxiv | ID: ppbiorxiv-425478

ABSTRACT

COVID-19 is caused by the SARS-CoV-2 (SC2) virus and is more prevalent and severe in the elderly and patients with comorbid diseases (CM). Because chitinase 3-like-1 (CHI3L1) is induced during aging and CM, the relationships between CHI3L1 and SC2 were investigated. Here we demonstrate that CHI3L1 is a potent stimulator of the SC2 receptor ACE2 and viral spike protein priming proteases (SPP), that ACE2 and SPP are induced during aging and that anti-CHI3L1, kasugamycin and inhibitors of phosphorylation, abrogate these ACE2- and SPP-inductive events. Human studies also demonstrated that the levels of circulating CHI3L1 are increased in the elderly and patients with CM where they correlate with COVID-19 severity. These studies demonstrate that CHI3L1 is a potent stimulator of ACE2 and SPP; that this induction is a major mechanism contributing to the effects of aging during SC2 infection and that CHI3L1 coopts the CHI3L1 axis to augment SC2 infection. CHI3L1 plays a critical role in the pathogenesis of and is an attractive therapeutic target in COVID-19.

2.
Preprint in English | medRxiv | ID: ppmedrxiv-20235721

ABSTRACT

Although the range of immune responses to COVID-19 infection is variable, cytokine storm is observed in many affected individuals. To further understand the disease pathogenesis and, consequently, to develop an additional tool for clinicians to evaluate patients for presumptive intervention we sought to compare plasma cytokine levels between a range of donor and patient samples grouped by a COVID-19 Severity Score (CSS) based on need for hospitalization and oxygen requirement. Here we utilize a mutual information algorithm that classifies the information gain for CSS prediction provided by cytokine expression levels and clinical variables. Using this methodology, we found that a small number of clinical and cytokine expression variables are predictive of presenting COVID-19 disease severity, raising questions about the mechanism by which COVID-19 creates severe illness. The variables that were the most predictive of CSS included clinical variables such as age and abnormal chest x-ray as well as cytokines such as macrophage colony-stimulating factor (M-CSF), interferon-inducible protein 10 (IP-10) and Interleukin-1 Receptor Antagonist (IL-1RA). Our results suggest that SARS-CoV-2 infection causes a plethora of changes in cytokine profiles and that particularly in severely ill patients, these changes are consistent with the presence of Macrophage Activation Syndrome and could furthermore be used as a biomarker to predict disease severity.

SELECTION OF CITATIONS
SEARCH DETAIL
...