# Alterations in the serum metabolome in patients with the COVID-19 Omicron variant and in recovered cases

## TL;DR

This study identifies specific changes in blood metabolites in patients with the Omicron variant of COVID-19 and shows that these changes are not fully reversed after recovery.

## Contribution

The first large-scale characterization of serum metabolites in Omicron cases and recovered patients, with a validated noninvasive diagnostic model.

## Key findings

- Six serum metabolites were significantly altered in Omicron cases compared to healthy controls.
- A noninvasive diagnostic model using these metabolites showed high accuracy in identifying Omicron cases.
- Changes in the oropharyngeal microbiome and serum metabolome correlated with clinical indicators in Omicron cases.

## Abstract

Corona Virus Disease (COVID-19) has become a global public health crisis, and the Omicron variant has rapidly taken over as soon as it was detected Serum circulating metabolites can provide extensive insights into the pathogenesis and diagnosis of many diseases. We included 336 omicron variant cases (OC), 216 recovered cases (RC), and 380 healthy controls (HC) for untargeted metabolomics analysis and analyzed their serum metabolic profiles by liquid chromatography-tandem mass spectrometry. Principal component analysis, orthogonal partial least squares discriminant analysis, t-test analysis and false discovery rate were used to characterize the serum metabolites of OC and RC. In addition, a noninvasive diagnostic model for OC was developed using Receiver operating characteristic analysis. Finally, a correlation analysis was performed using data from our published articles. The results showed that compared with HC, five metabolites, including DL-stachydrine, D-(+)-pipecolinic acid, furazolidone, L-arginine and 5α-dihydrotestosterone glucuronide were significantly elevated and one metabolite, prenylcysteine, was significantly decreased in the serum of OC, and that the increase in L-arginine and the decrease in prenylcysteine led to impaired urea cycling and a high risk of developing atherosclerosis, respectively. These metabolites were not fully restored to healthy human levels in recovered cases. In addition, we constructed a noninvasive diagnostic model for distinguishing Omicron variant patients from healthy individuals based on the six differential metabolites, and achieved high diagnostic efficacy in both the discovery and validation cohorts. Finally, the results of the correlation analysis showed a strong correlation between the alterations in the oropharyngeal microbiome and serum metabolome and the clinical indicators in the omicron variant cases. This study was the first to characterize serum metabolites in OC and RC based on a large clinical cohort, and successfully constructed and validated a noninvasive diagnostic model for Omicron variant patients.