Dataset Information

U-shaped association between abnormal serum uric acid levels and COVID-19 severity: Reports from the Japan COVID-19 Task Force.

ABSTRACT:

Objectives

This study aimed to identify the relationship between abnormal serum uric acid levels or a history of hyperuricemia and coronavirus disease 2019 (COVID-19) severity in the Japanese population.

Methods

We included 1,523 patients enrolled in the Japan COVID-19 Task Force cohort between February 2020 and May 2021. We compared the clinical characteristics, including comorbidities, laboratory findings, and outcomes, particularly invasive mechanical ventilation (IMV), among patients with and without abnormal uric acid levels or a history of hyperuricemia.

Results

Patients with high serum uric acid levels were older and had higher body weights and body mass index than those without. In addition, the multiple logistic regression analysis revealed a significant association between high serum uric acid levels or a history of hyperuricemia and an increased risk of IMV (odds ratio (OR)=1.77; p=0.03/OR=1.56; p=0.04). Moreover, patients with low uric acid levels on admission were also associated significantly with the requirement of IMV (OR=5.09; p<0.0001).

Conclusion

Abnormal serum uric acid levels or a history of hyperuricemia were significantly associated with COVID-19 severity in the Japanese cohort.

SUBMITTER: Fukushima T

PROVIDER: S-EPMC9262647 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Using RNA-seq and high-resolution mass spectrometry we performed a comprehensive systems analysis on 128 plasma and leukocyte samples from hospitalized patients with or without COVID-19 (n=102 and 26 respectively) and with differing degrees of disease severity. We generated abundance measurements for over 17,000 transcripts, proteins, metabolites, and lipids and compiled them with clinical data into a curated relational database. This resource offers the unique opportunity to perform systems analysis and cross-ome correlations to both molecules and patient outcomes. In total 219 molecular features were mapped with high significance to COVID-19 status and severity, including those involved in processes such as complement system activation, dysregulated lipid transport, and B cell activation. In one example, we detected a trio of covarying molecules – citrate, plasmenyl-phosphatidylcholines, and gelsolin (GSN) – that offer both pathophysiological insight and potential novel therapeutic targets. Further, our data revealed in some cases, and supported in others, that several biological processes were dysregulated in COVID-19 patients including vessel damage, platelet activation and degranulation, blood coagulation, and acute phase response. For example, we observed that the coagulation-related protein, cellular fibronectin (cFN), was highly increased within COVID-19 patients and provide new evidence that the upregulated proteoform stems from endothelial cells, consistent with endothelial injury as a major activator of the coagulation cascade. The abundance of prothrombin, which is cleaved to form thrombin during clotting, was significantly reduced and correlated with severity and might help to explain the hyper coagulative environment of SARS-CoV-2 infection. From transcriptomic analysis of leukocytes, we concluded that COVID-19 patients with acute respiratory distress syndrome (ARDS) demonstrated a phenotype that overlapped with, but was distinct from, that found in patients with non-COVID-19-ARDS. To aid in the global efforts toward elucidation of disease pathophysiology and therapeutic development, we created a web-based tool with interactive visualizations allowing for easy navigation of this systems-level compendium of biomolecule abundance in relation to COVID-19 status and severity. Finally, we leveraged these multi-omic data to predict COVID-19 patient outcomes with machine learning, which highlighted the predictive power of these expansive molecular measurements beyond the standardized clinical estimate of 10-year survival Charlson score.