Circulating Dickkopf1 Parallels Metabolic Adaptations and Predicts Disease Trajectories in Patients With COVID-19

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.

Bone Metastases: From Mechanisms to Treatment

OBJECTIVES

Bone metastases are of high clinical relevance because they are a frequent complication of most types of common cancers, such as breast and prostate. The metastatic process is complex, requiring the completion of several different steps to allow successful dissemination and homing. In addition, preparation of the metastatic niche changes the constant cycle of bone matrix formation and degradation, leading to the clinical phenotypes of lytic and sclerotic lesions. We review our current knowledge on this topic and briefly explain the current treatment landscape of bone metastasis.

DATA SOURCES

These include PubMed, international guidelines, and clinician experience.

CONCLUSION

Bone metastases remain a clinical challenge that negatively impacts patients prognosis and quality of life. A comprehensive understanding of the complex molecular mechanisms that results in bone metastasis is the basis for successful treatment of affected patients. The disruption of bone matrix metabolism is already recognized as the prerequisite for metastasis formation, but many open questions remain that need to be addressed in future research to establish individually tailored treatment approaches.

IMPLICATIONS FOR NURSING PRACTICE

Patient-centered therapy of bone metastases requires suitable pharmacological options, and importantly a holistic approach in care delivery across the multidisciplinary team. Nurses provide the cornerstone of the multidisciplinary team and provide the closest and the most frequent contact to the patient and their families to provide timely intervention. Nurses require a basic understanding of the complex physiology of metastasis to inform practice.