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1.
Viruses ; 14(3)2022 03 07.
Article in English | MEDLINE | ID: covidwho-1732249

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.


Subject(s)
COVID-19 , Artificial Intelligence , COVID-19/diagnosis , Chromatography, Liquid/methods , Glycopeptides/analysis , Glycopeptides/chemistry , Glycopeptides/metabolism , Glycoproteins , Humans
2.
Nat Commun ; 12(1): 5417, 2021 09 14.
Article in English | MEDLINE | ID: covidwho-1410404

ABSTRACT

COVID-19 is associated with a wide range of clinical manifestations, including autoimmune features and autoantibody production. Here we develop three protein arrays to measure IgG autoantibodies associated with connective tissue diseases, anti-cytokine antibodies, and anti-viral antibody responses in serum from 147 hospitalized COVID-19 patients. Autoantibodies are identified in approximately 50% of patients but in less than 15% of healthy controls. When present, autoantibodies largely target autoantigens associated with rare disorders such as myositis, systemic sclerosis and overlap syndromes. A subset of autoantibodies targeting traditional autoantigens or cytokines develop de novo following SARS-CoV-2 infection. Autoantibodies track with longitudinal development of IgG antibodies recognizing SARS-CoV-2 structural proteins and a subset of non-structural proteins, but not proteins from influenza, seasonal coronaviruses or other pathogenic viruses. We conclude that SARS-CoV-2 causes development of new-onset IgG autoantibodies in a significant proportion of hospitalized COVID-19 patients and are positively correlated with immune responses to SARS-CoV-2 proteins.


Subject(s)
Autoantibodies/immunology , COVID-19/immunology , Immunoglobulin G/immunology , SARS-CoV-2/immunology , Aged , Antibodies, Antinuclear/blood , Antibodies, Antinuclear/immunology , Antibodies, Viral/blood , Antibodies, Viral/immunology , Autoantibodies/blood , Autoantigens/immunology , Connective Tissue Diseases/immunology , Cytokines/immunology , Female , Hospitalization , Humans , Immunoglobulin G/blood , Male , Middle Aged , SARS-CoV-2/pathogenicity , Viral Proteins/immunology
3.
Vaccine ; 39(39): 5688-5698, 2021 09 15.
Article in English | MEDLINE | ID: covidwho-1347852

ABSTRACT

The question associated with efficacy and longevity of SARS-CoV-2 protection post-vaccination is paramount. The cPass surrogate virus neutralization test (sVNT) has gained popularity globally as a dual application assay for: 1. Accurate SARS-CoV-2 population surveillance (seroprevalence) analysis and 2. Revealing the presence of antibodies that block and effectively neutralize the interaction between the SARS-CoV-2 receptor binding domain and the host cell ACE2 receptor in recovered or vaccinated individuals. This study describes an approach for accurate quantification of neutralizing antibodies using the cPass sVNT with an automated workflow on the Tecan EVO and Dynex Agility platforms that is applicable to other liquid handling systems. This methodology was used to assess the stability of SARS-CoV-2 neutralizing antibodies between freeze/thaw and refrigerated sample storage conditions. Furthermore, a subset of twenty-five samples from SARS-CoV-2 infected/recovered individuals revealed a 600-fold difference in the neutralizing antibody response where low titers were represented in about half of the samples. Finally, pre- and post-vaccination samples were tested for neutralizing antibodies using the qualitative and semi-quantitative cPass sVNT protocols revealing undetectable or relatively low levels after the first vaccine dose and a decline in levels longitudinally over the months following the second dose. This wide range in neutralizing (blocking) antibodies from both natural infection and vaccination supports a differential immune response that may be attributed to several physiological and genetic factors underlining the potential for measuring SARS-CoV-2 neutralizing antibody titer levels post-vaccination to help ensure robust and prolonged immunity.


Subject(s)
Antibodies, Neutralizing , COVID-19 , Antibodies, Viral , Humans , Immunity , Neutralization Tests , SARS-CoV-2 , Seroepidemiologic Studies , Vaccination
4.
Nat Immunol ; 22(1): 67-73, 2021 01.
Article in English | MEDLINE | ID: covidwho-1065904

ABSTRACT

Severe acute respiratory syndrome coronavirus 2 infections can cause coronavirus disease 2019 (COVID-19), which manifests with a range of severities from mild illness to life-threatening pneumonia and multi-organ failure. Severe COVID-19 is characterized by an inflammatory signature, including high levels of inflammatory cytokines, alveolar inflammatory infiltrates and vascular microthrombi. Here we show that patients with severe COVID-19 produced a unique serologic signature, including an increased likelihood of IgG1 with afucosylated Fc glycans. This Fc modification on severe acute respiratory syndrome coronavirus 2 IgGs enhanced interactions with the activating Fcγ receptor FcγRIIIa; when incorporated into immune complexes, Fc afucosylation enhanced production of inflammatory cytokines by monocytes, including interleukin-6 and tumor necrosis factor. These results show that disease severity in COVID-19 correlates with the presence of proinflammatory IgG Fc structures, including afucosylated IgG1.


Subject(s)
COVID-19/immunology , Cytokines/immunology , Immunoglobulin G/immunology , Receptors, IgG/immunology , SARS-CoV-2/immunology , Adolescent , Adult , Aged , COVID-19/metabolism , COVID-19/virology , Child , Cytokines/metabolism , Female , Glycosylation , Humans , Immunoglobulin G/metabolism , Interleukin-6 , Male , Middle Aged , Receptors, IgG/metabolism , SARS-CoV-2/metabolism , SARS-CoV-2/physiology , Severity of Illness Index , Tumor Necrosis Factor-alpha/immunology , Tumor Necrosis Factor-alpha/metabolism
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