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No patient is the same; lessons learned from antibody repertoire profiling in hospitalized severe COVID-19 patients (preprint)
medrxiv; 2022.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2022.12.23.22283896
ABSTRACT
Here, by using mass spectrometry-based methods IgG1 and IgA1 clonal repertoires were monitored quantitatively and longitudinally in more than 50 individual serum samples obtained from 17 COVID-19 patients admitted to intensive care units because of acute respiratory distress syndrome. These serological clonal profiles were used to examine how each patient reacted to a severe SARS-CoV-2 infection. All 17 donors revealed unique polyclonal repertoires and changes after infection. Substantial changes over time in the IgG1 and/or IgA1 clonal repertoires were observed in individual patients, with several new clones appearing following the infection, in a few cases leading to a few very high abundant IgG1 and/or IgA1 clones dominating the repertoire. Several of these clones were de novo sequenced through combinations of top-down, middle-down and bottom-up proteomics approaches. This revealed several sequence features in line with sequences deposited in the SARS-CoV-specific database of antibodies. In other patients, the serological Ig profiles revealed the treatment with tocilizumab, as after treatment, this IgG1-mAb dominated the serological IgG1 repertoire. Tocilizumab clearance could be monitored and a half-life of approximately 6 days was established in these patients. Overall, our longitudinal monitoring of IgG1 and IgA1 repertoires of individual donors reveals that antibody responses are highly personalized traits of each patient, affected by the disease and the chosen clinical treatment. The impact of these observations argues for a more personalized and longitudinal approach in patients diagnostics, both in serum proteomics as well as in monitoring immune responses.
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Full text: Available Collection: Preprints Database: medRxiv Main subject: Respiratory Distress Syndrome / COVID-19 Language: English Year: 2022 Document Type: Preprint

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Full text: Available Collection: Preprints Database: medRxiv Main subject: Respiratory Distress Syndrome / COVID-19 Language: English Year: 2022 Document Type: Preprint