Untargeted saliva metabolomics by liquid chromatography—Mass spectrometry reveals markers of COVID-19 severity

Abstract

Background The COVID-19 pandemic is likely to represent an ongoing global health issue given the potential for new variants, vaccine escape and the low likelihood of eliminating all reservoirs of the disease. Whilst diagnostic testing has progressed at a fast pace, the metabolic drivers of outcomes–and whether markers can be found in different biofluids–are not well understood. Recent research has shown that serum metabolomics has potential for prognosis of disease progression. In a hospital setting, collection of saliva samples is more convenient for both staff and patients, and therefore offers an alternative sampling matrix to serum. Methods Saliva samples were collected from hospitalised patients with clinical suspicion of COVID-19, alongside clinical metadata. COVID-19 diagnosis was confirmed using RT-PCR testing, and COVID-19 severity was classified using clinical descriptors (respiratory rate, peripheral oxygen saturation score and C-reactive protein levels). Metabolites were extracted and analysed using high resolution liquid chromatography-mass spectrometry, and the resulting peak area matrix was analysed using multivariate techniques. Results Positive percent agreement of 1.00 between a partial least squares–discriminant analysis metabolomics model employing a panel of 6 features (5 of which were amino acids, one that could be identified by formula only) and the clinical diagnosis of COVID-19 severity was achieved. The negative percent agreement with the clinical severity diagnosis was also 1.00, leading to an area under receiver operating characteristics curve of 1.00 for the panel of features identified. Conclusions In this exploratory work, we found that saliva metabolomics and in particular amino acids can be capable of separating high severity COVID-19 patients from low severity COVID-19 patients. This expands the atlas of COVID-19 metabolic dysregulation and could in future offer the basis of a quick and non-invasive means of sampling patients, intended to supplement existing clinical tests, with the goal of offering timely treatment to patients with potentially poor outcomes.

Integrated NMR and MS Analysis of the Plasma Metabolome Reveals Major Changes in One-Carbon, Lipid, and Amino Acid Metabolism in Severe and Fatal Cases of COVID-19

“…As observed in the plasma of infected subjects, lower contents of salivary amino acids are associated with SARS-CoV-2 infection [76]. Additionally, a decrease in plasma glutamine [77] and lower salivary levels of tyrosine and BCAA [78] seem to be associated with COVID-19 severity, which is consistent with our findings. Despite the fact that the literature shows an association between levels of circulating amino acids and COVID-19 severity, amino acid levels seem not to be good predictors of ICU admission or disease fatality [79].…”

Critical Factors in Sample Collection and Preparation for Clinical Metabolomics of Underexplored Biological Specimens

“…In general, the procedures involve protein precipitation with acetonitrile [ 189 , 190 , 191 , 192 , 193 , 194 , 195 ], methanol [ 196 , 197 , 198 ], or a combination of methanol/acetonitrile (1:1, v / v ) [ 199 , 200 , 201 ], methanol/water [ 202 , 203 , 204 , 205 , 206 ], and methanol/acetonitrile/water (2:2:1, v / v / v ) [ 207 ]. Other studies have used isopropanol [ 208 ] or acetone [ 209 ], which requires evaporation and resuspension in an appropriate solvent before chromatographic analysis. When GC–MS is used, the dried extracts are derivatized using oximation followed by a silylation step [ 209 , 210 , 211 , 212 , 213 , 214 , 215 , 216 ].…”

Metabolomics as a powerful tool for diagnostic, pronostic and drug intervention analysis in COVID-19

“…In terms of the nature of the specimen, serum and plasma followed by urine ( Kurano et al, 2022b ; Kida et al, 2022 ) are the most studied biofluids, while other samples also scrutinized include saliva ( Spick et al, 2022b ; Frampas et al, 2022 ; Saheb Sharif-Askari et al, 2022 ), faeces ( He et al, 2021 ; Lv et al, 2021 ; Ren et al, 2021 ), platelets ( Schuurman et al, 2022 ), exhaled breath ( Barberis et al, 2021a ; Grassin-Delyle et al, 2021 ; Bennet et al, 2022 ; Remy et al, 2022 ), sebum from skin ( Spick et al, 2021 ) and breastmilk ( Zhao et al, 2020 ). Due to the high volume of information ( Table 1 ), we here complement other recent reviews on COVID-19 metabolomics ( Hasan et al, 2021 ; Lin et al, 2021 ; Costanzo et al, 2022 ) by selecting a set of contributions to be discussed in the present review, based on our evaluation of novelty, impact and originality.…”