Differential Peripheral Blood Glycoprotein Profiles in Symptomatic and Asymptomatic COVID-19

Abstract

Glycosylation is the most common form of post-translational modification of proteins, critically affecting their structure and function. Using liquid chromatography and mass spectrometry for high-resolution site-specific quantification of glycopeptides coupled with high-throughput artificial intelligence-powered data processing, we analyzed differential protein glycoisoform distributions of 597 abundant serum glycopeptides and nonglycosylated peptides in 50 individuals who had been seriously ill with COVID-19 and in 22 individuals who had recovered after an asymptomatic course of COVID-19. As additional comparison reference phenotypes, we included 12 individuals with a history of infection with a common cold coronavirus, 16 patients with bacterial sepsis, and 15 healthy subjects without history of coronavirus exposure. We found statistically significant differences, at FDR < 0.05, for normalized abundances of 374 of the 597 peptides and glycopeptides interrogated between symptomatic and asymptomatic COVID-19 patients. Similar statistically significant differences were seen when comparing symptomatic COVID-19 patients to healthy controls (350 differentially abundant peptides and glycopeptides) and common cold coronavirus seropositive subjects (353 differentially abundant peptides and glycopeptides). Among healthy controls and sepsis patients, 326 peptides and glycopeptides were found to be differentially abundant, of which 277 overlapped with biomarkers that showed differential expression between symptomatic COVID-19 cases and healthy controls. Among symptomatic COVID-19 cases and sepsis patients, 101 glycopeptide and peptide biomarkers were found to be statistically significantly abundant. Using both supervised and unsupervised machine learning techniques, we found specific glycoprotein profiles to be strongly predictive of symptomatic COVID-19 infection. LASSO-regularized multivariable logistic regression and K-means clustering yielded accuracies of 100% in an independent test set and of 96% overall, respectively. Our findings are consistent with the interpretation that a majority of glycoprotein modifications observed which are shared among symptomatic COVID-19 and sepsis patients likely represent a generic consequence of a severe systemic immune and inflammatory state. However, there are glycoisoform changes that are specific and particular to severe COVID-19 infection. These may be representative of either COVID-19-specific consequences or susceptibility to or predisposition for a severe course of the disease. Our findings support the potential value of glycoproteomic biomarkers in the biomedical understanding and, potentially, the clinical management of serious acute infectious conditions.

Plasma proteome analysis and validation of patients with community‐acquired pneumonia: A cohort study

“…Plasma samples were collected between 2017 and 2018, and the samples did not contain plasma from COVID-19 patients. KEGG analysis in our study revealed that many plasma proteins are involved in the pathway of complement and coagulation cascades (hsa04610) and ECM-receptor interaction (hsa04512), which is consistent with the reported plasma proteomic results for COVID-19 [20,35,36].…”

“…S100A9, and AACT( SERPINA3 ) levels were significantly elevated in more severe COVID‐19 patients, while fetuin‐A was significantly decreased [20, 35, 37, 38]. Our study showed that plasma levels of S100A9 and AACT increased and fetuin‐A decreased in patients with CAP.…”

Warning signs from the crypt: Aberrant protein glycosylation marks opportunities for early colorectal cancer detection.

“…It is not until recently that the enormously complex field of glycosylation can be studied, primarily because of the availability of the appropriate tools ( 95 ). Machine learning models (e.g., Support Vector Machines and Random Forest) can decipher the vast amount of complex data coming from, for instance, liquid chromatography-MS ( 96 – 98 ). Large-scale prospective clinical studies are currently underway to evaluate the clinical validity of glycosylation markers and determine their clinical utility and become an additional tool in the armamentarium for CRC screening.…”

Oxonium ion scanning mass spectrometry for large-scale plasma glycoproteomics

“…Glycoproteomics is considered an important reservoir for biomarker discovery. Protein glycosylation is abundant and diverse in plasma, and altered glycosylation has been observed in response to a variety of disease states, for example, prostate-specific antigen in prostate cancer and alpha-1-acid glycoprotein in sepsis 10 – 13 . Therefore, there is an increasing demand for approaches that allow the sensitive and quantitative profiling of blood plasma, where protein glycosylation plays a vital role in regulating the structure and function of both soluble and cell-surface proteins 14 .…”