Mass spectrometry-based identification of COVID-19 biomarkers

In a recent study published in the journal Metabolitesresearchers reported that metabolomics approaches based on mass spectrometry (MS) have high potential for biomarker discovery.

The coronavirus disease 2019 (COVID-19) pandemic has caused significant public health disruption. Conventional biomolecular testing has played a pivotal role in tracking severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). MS-based metabolomics represents the latest innovative technologies to identify circulating metabolites as COVID-19 biomarkers. In the current study, researchers examined the COVID-19-related metabolome for potential biomarkers.

Study: Diagnostic, prognostic and mechanistic biomarkers of COVID-19 identified by metabolomics by mass spectrometry. Image Credit: Intothelight Photography / Shutterstock

COVID-19 prognostic biomarkers

Metabolomics has been leveraged in the discovery of biomarkers to identify metabolites correlated with disease. Several studies have assessed the metabolome of COVID-19 by applying different criteria such as disease severity, outcome, risk factors for severe disease, treatments, and longitudinal analysis of infected people. These heterogeneous criteria can compromise comparisons between studies.

However, studies have adopted a robust clinical strategy to strengthen metabolomics analyses. Clinical standardization can be achieved with strict inclusion criteria and broad clinical characteristics. The severity of COVID-19 requires a more precise distinction between mild, moderate and severe illnesses. Moreover, it is essential to assess the reproducibility of the measurements and to evaluate them in validation cohorts to confirm the identification of the biomarkers.

In targeted and non-targeted metabolomics, chromatographic methods are coupled with mass spectrometers, with typical combinations including liquid chromatography (LC)-MS, gas chromatography (GC)-MS and ultra-performance LC-MS (UPLC-MS). Untargeted metabolomics has stimulated the discovery of potential biomarkers of COVID-19.

This approach facilitates the complete detection of metabolites requiring subsequent validation by a targeted method. Various mass analyzers have been used to identify metabolic biomarkers of COVID-19, such as phenols, mannose compounds, fructose, purine nucleosides, free fatty acids, and amino acids, among others. Machine learning algorithms have recently facilitated the detection of unique biomarkers.

Mechanistic, diagnostic and prognostic biomarkers of COVID-19 disease.

Diagnostic and prognostic features of the COVID-19 metabolome

A literature search was performed for studies applying MS-based metabolomics in COVID-19. Eligible studies recruited people infected with SARS-CoV-2 with a positive reverse transcription polymerase chain reaction (RT-PCR) test and controls without COVID-19. All publications were reviewed for metabolite biomarkers reflecting the severity of COVID-19. After selection and exclusions (due to irrelevant methodological approaches or inaccessible full texts), 20 articles were included.

A selected study reported that five plasma metabolites – aspartate, malate, guanosine monophosphate (GMP), D-xylulose-5-phosphate and carbamoyl phosphate, were down-regulated in severe cases of COVID -19. Additionally, he identified changes in amino acid metabolism in COVID-19 individuals affecting glutamine, arginine, branched chain amino acids and their derivatives.

These biological signatures were maintained in patients with mild/moderate and severe COVID-19. Additionally, glutamate remained dysregulated in longitudinal analyzes across waves of COVID-19. Some studies have also observed alterations in tryptophan metabolism; in addition, an association between immunosuppressive tryptophan metabolites (anthranilic acid and kynurenine) and COVID-19 severity has also been reported.

Such elevations have also been seen in long COVID or cancer patients. Additionally, many studies have focused on alterations in carbohydrate and energy metabolism, purine metabolism, tricarboxylic acid cycle, polyamines, and nicotinamide metabolites and identified significant changes in glycerophospholipids in patients with severe COVID-19.

For example, sphingosine-1-phosphate levels increase significantly during recovery, while higher levels of creatine and acetylated polyamine may indicate renal dysfunction in critical patients. Additionally, a meta-analysis of COVID-19 metabolomes identified cholesterol, tyrosine, bilirubin, L-phenylalanine, and D-mannose as key biomarkers, suggesting that disease severity was associated with changes in pathways involving the indicated metabolites.

Untargeted metabolomic analysis of blood/saliva samples revealed two molecules (L-proline betaine and 3-glycolithocholic acid sulfate) predicting severity. Another study showed that salivary concentrations of valine, proline, tyrosine, phenylalanine and leucine could differentiate between patients with mild and severe COVID-19.

Analysis of nasopharyngeal swabs from patients with mild COVID-19 identified methionine sulfoxide, carnosine and beta-hydroxybutyric acid, compared to those infected with other respiratory viruses. Additionally, one study found elevated levels of urea, lactate, and cyclohexane carboxylic acid, but reduced levels of D-cellobiose, 1-pentadecanol, propanoic acid, and monomethyl succinate in fecal samples. of patients with severe COVID-19 compared to those with mild disease. .

Increased L-cytosine levels correlate with SARS-CoV-2 infection and could be considered a relevant diagnostic biomarker, although the mechanistic basis remains unknown. Given the lack of large-scale validation, it remains unclear which sample type (plasma, saliva, urine, feces, etc.) would be optimal for COVID-19 detection.

Mechanistic biomarkers of COVID-19

COVID-19 amplifies glutamine breakdown and elevates glutamate levels. Curiously, one study found that comorbid glutamine deficiency predisposes individuals to severe COVID-19. Polyamines are essential for maintaining cellular homeostasis. Studies have found an overabundance of polyamines and L-ornithine in the sera of COVID-19 patients.

Additionally, 3-hydroxybutyric acid (3HB) was found to be elevated during COVID-19. 3HB has immunostimulatory properties and inhibits the inflammasome. In mouse models, 3HB increased the function of the 4-positive differentiation cluster (CD4⁺) T lymphocytes and decreased the mortality of infected mice. Therefore, it could serve as a COVID-19 attenuating metabolite.

Final remarks

Taken together, metabolomics has been continuously refined over the past decades to allow for greater coverage of the metabolome. The authors reported a catalog of COVID-19-relevant biomarkers. Nevertheless, standardization of the metabolomics workflow needs to be addressed. Future studies should determine which biomarkers, alone or in combination, best reflect COVID-19 infection and severity.