Circulating DKK-1 levels predict disease outcomes and mirror metabolic adaptations in patients with Covid-19
Individuals with low serum levels of DKK-1 (Dickkopf-1) are twice as likely to die from Covid-19 than those with high levels according to new research published by Nikolai Jaschke and colleagues in the Journal of Clinical Endocrinology & Metabolism.
The researchers found that circulating DKK1 levels vary in humans and change as a function of time during SARS-CoV-2 infection. The infection promotes metabolic adaptations that resembles fasting, which are mirrored by circulating DKK1 levels. DKK-1 levels predict disease outcomes in Covid-19 individuals.
The results of the study suggest a potential use of measuring circulating DKK1 as an indicator of disease severity in COVID-19 patients.
Context and aims: Coronavirus disease 19 (COVID-19) trajectories show high interindividual variability, ranging from asymptomatic manifestations to fatal outcomes, the latter of which may be fueled by immunometabolic maladaptation of the host. Reliable identification of patients who are at risk of severe disease remains challenging. We hypothesized that serum concentrations of Dickkopf1 (DKK1) indicate disease outcomes in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected individuals.
Methods: We recruited hospitalized patients with PCR-confirmed SARS-CoV-2 infection and included 80 individuals for whom blood samples from 2 independent time points were available. DKK1 serum concentrations were measured by ELISA in paired samples. Clinical data were extracted from patient charts and correlated with DKK1 levels. Publicly available datasets were screened for changes in cellular DKK1 expression on SARS-CoV-2 infection. Plasma metabolites were profiled by nuclear magnetic resonance spectroscopy in an unbiased fashion and correlated with DKK1 data. Kaplan-Meier and Cox regression analysis were used to investigate the prognostic value of DKK1 levels in the context of COVID-19.
Results: We report that serum levels of DKK1 predict disease outcomes in patients with COVID-19. Circulating DKK1 concentrations are characterized by high interindividual variability and change as a function of time during SARS-CoV-2 infection, which is linked to platelet counts. We further find that the metabolic signature associated with SARS-CoV-2 infection resembles fasting metabolism and is mirrored by circulating DKK1 abundance. Patients with low DKK1 levels are twice as likely to die from COVID-19 than those with high levels, and DKK1 predicts mortality independent of markers of inflammation, renal function, and platelet numbers.
Conclusion: Our study suggests a potential clinical use of circulating DKK1 as a predictor of disease outcomes in patients with COVID-19. These results require validation in additional cohorts.
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