Mass spectrometry-based identification of COVID-19 biomarkers

A recent study published in the journal metaboliteresearchers reported that mass spectrometry (MS)-based metabolomics approaches have high potential for biomarker discovery.

The 2019 coronavirus disease (COVID-19) pandemic has caused significant disruption to public health. Traditional biomolecular testing has been crucial in tracking severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). MS-based metabolomics is the latest innovative technique to identify circulating metabolites as his COVID-19 biomarkers. In the current study, researchers reviewed the COVID-19-related metabolome for potential biomarkers.

study: Diagnostic, prognostic and mechanistic biomarkers of COVID-19 identified by mass spectrometry metabolomicsImage credit: Intothelight Photography / Shutterstock

Prognostic COVID-19 biomarkers

Metabolomics is being harnessed to discover biomarkers that identify metabolites that correlate with disease. Multiple studies have assessed the COVID-19 metabolome by applying different criteria such as pathological severity, outcome, risk factors for severe disease, treatment, and longitudinal analysis of infected individuals. These heterogeneous criteria may jeopardize comparisons between studies.

However, studies have employed robust clinical strategies to enhance metabolomics analysis. Clinical standardization can be achieved through stringent selection criteria and a wide range of clinical characteristics. COVID-19 severity needs to distinguish between mild, moderate, and severe cases more precisely. Furthermore, it is imperative to evaluate the reproducibility of the measurements and evaluate them in a validation cohort to confirm the identification of the biomarkers.

In targeted and untargeted metabolomics, chromatographic methods are mass-scale, typically in combinations such as liquid chromatography (LC)-MS, gas chromatography (GC)-MS, and ultra-performance LC-MS (UPLC-MS). Connected to the analyzer. Untargeted metabolomics has boosted the discovery of potential COVID-19 biomarkers.

This approach facilitates comprehensive detection of metabolites that require subsequent validation by targeted methods. Various mass spectrometers have been used to identify COVID-19 metabolic biomarkers such as phenols, mannose compounds, fructose, purine nucleosides, free fatty acids and amino acids. Machine learning algorithms have recently facilitated the detection of unique biomarkers.

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

Diagnostic and prognostic features of the COVID-19 metabolome

A literature search was conducted for studies applying MS-based metabolomics to COVID-19. Eligible studies recruited SARS-CoV-2-infected individuals with a positive reverse transcription-polymerase chain reaction (RT-PCR) test and a COVID-19-free control group. All publications were screened for metabolite biomarkers that reflect COVID-19 severity. After screening and exclusion (because of irrelevant methodological approaches or inaccessible full text), 20 articles were included.

Five plasma metabolites (aspartate, malate, guanosine monophosphate (GMP), D-xylulose-5-phosphate, carbamoyl phosphate) were downregulated in severe COVID-19 in one selected study. Reported to be rated. In addition, she identified alterations in amino acid metabolism in her COVID-19 patients that affected glutamine, arginine, branched amino acids, and their derivatives.

These biological features were maintained in mild/moderate and severe COVID-19 patients. Moreover, glutamate remained dysregulated in longitudinal analyzes across COVID-19 waves. Alterations in tryptophan metabolism were also observed in some studies. In addition, an association between immunosuppressive tryptophan metabolites (anthranilic acid and kynurenine) and the severity of her COVID-19 has also been reported.

Such an increase was also observed in long-standing COVID or cancer patients. In addition, numerous studies have focused on alterations in carbohydrate and energy metabolism, purine metabolism, tricarboxylic acid cycle, polyamines, nicotinamide metabolites, and identified significant alterations in glycerophospholipids in his severe COVID-19 patients. doing.

For example, sphingosine-1-phosphate levels increase significantly during recovery, while high levels of creatine and acetylated polyamines may indicate impaired kidney function in critically ill patients. , a meta-analysis of the COVID-19 metabolome identified cholesterol, tyrosine, bilirubin, L-phenylalanine, and D-mannose as key biomarkers and associated alterations in pathways involving metabolites with disease severity. It was suggested that

Untargeted metabolomics analysis of blood/saliva samples revealed two molecules (L-proline betaine and glycolitocholic acid 3-sulfate) that were predictive of severity. Another study showed that salivary concentrations of valine, proline, tyrosine, phenylalanine, and leucine could distinguish between mild and severe her COVID-19 patients.

Analysis of nasopharyngeal swabs from patients with mild COVID-19 identified methionine sulfoxide, carnosine, and beta-hydroxybutyrate compared with patients infected with other respiratory viruses. In addition, studies have found elevated levels of urea, lactate, and cyclohexanecarboxylic acid in fecal specimens from severely ill COVID-19 patients compared to mildly ill patients, while D-cellobiose, 1-penta Decreased levels of decanol, propanoic acid, and monomethyl succinate were found. .

Elevated L-cytosine levels have been correlated with SARS-CoV-2 infection and may be considered a relevant diagnostic biomarker, although the underlying mechanism remains unclear. Due to the lack of large-scale validation, it remains difficult to identify the best specimen types (plasma, saliva, urine, feces, etc.) for the detection of COVID-19.

Mechanical COVID-19 biomarkers

COVID-19 amplifies glutamine breakdown and elevates glutamate levels. Interestingly, studies have revealed that glutamine deficiency associated with comorbidities predisposes individuals to severe her COVID-19. Polyamines are important for maintaining cellular homeostasis. A study revealed that a COVID-19 patient’s serum contained excess polyamines and her L-ornithine.

Additionally, 3-hydroxybutyrate (3HB) was found to be elevated during COVID-19. 3HB has immunostimulatory properties and inhibits the inflammasome. In mouse models, 3HB is differentiation cluster 4 positive (CD4⁺) reduced the mortality of T cells and infected mice. Therefore, it may act as a metabolite that attenuates COVID-19.

in conclusion

Taken together, metabolomics has been continually refined over the past decades to provide greater coverage of the metabolome. The authors reported a catalog of COVID-19-related biomarkers. Nevertheless, standardization of metabolomics workflows needs to be addressed. Future studies should determine the biomarkers that best reflect the infection and the severity of his COVID-19, either alone or in combination.