Dataset Information

Altered somatic hypermutation patterns in COVID-19 patients classifies disease severity.

ABSTRACT:

Introduction

The success of the human body in fighting SARS-CoV2 infection relies on lymphocytes and their antigen receptors. Identifying and characterizing clinically relevant receptors is of utmost importance.

Methods

We report here the application of a machine learning approach, utilizing B cell receptor repertoire sequencing data from severely and mildly infected individuals with SARS-CoV2 compared with uninfected controls.

Results

In contrast to previous studies, our approach successfully stratifies non-infected from infected individuals, as well as disease level of severity. The features that drive this classification are based on somatic hypermutation patterns, and point to alterations in the somatic hypermutation process in COVID-19 patients.

Discussion

These features may be used to build and adapt therapeutic strategies to COVID-19, in particular to quantitatively assess potential diagnostic and therapeutic antibodies. These results constitute a proof of concept for future epidemiological challenges.

SUBMITTER: Safra M

PROVIDER: S-EPMC10154551 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Publications

Altered somatic hypermutation patterns in COVID-19 patients classifies disease severity.

Safra Modi M Tamari Zvi Z Polak Pazit P Shiber Shachaf S Matan Moshe M Karameh Hani H Helviz Yigal Y Levy-Barda Adva A Yahalom Vered V Peretz Avi A Ben-Chetrit Eli E Brenner Baruch B Tuller Tamir T Gal-Tanamy Meital M Yaari Gur G

Frontiers in immunology 20230419

<h4>Introduction</h4>The success of the human body in fighting SARS-CoV2 infection relies on lymphocytes and their antigen receptors. Identifying and characterizing clinically relevant receptors is of utmost importance.<h4>Methods</h4>We report here the application of a machine learning approach, utilizing B cell receptor repertoire sequencing data from severely and mildly infected individuals with SARS-CoV2 compared with uninfected controls.<h4>Results</h4>In contrast to previous studies, our a ...[more]

PMID: 37153628

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Project description:The severity of COVID-19 is linked to an imbalanced immune response. The dysregulated metabolism of small molecules and bioactive lipids has also been associated with disease severity. To promote understanding of the disease biochemistry and provide targets for intervention, we applied a range of LC-MS platforms to analyze over 100 plasma samples from patients with varying COVID-19 severity and with detailed clinical information on inflammatory responses (>30 immune markers). This is the third publication in a series, and it reports the results of comprehensive lipidome profiling using targeted LC-MS/MS. We identified 1076 lipid features across 25 subclasses, including glycerophospholipids, sterols, glycerolipids, and sphingolipids, among which 531 lipid features were dramatically changed in the plasma of intensive care unit (ICU) patients compared to patients in the ward. Patients in the ICU showed 1.3-57-fold increases in ceramides, (lyso-)glycerophospholipids, diglycerides, triglycerides, and plasmagen phosphoethanolamines, and 1.3-2-fold lower levels of a cyclic lysophosphatidic acid, sphingosine-1-phosphates, sphingomyelins, arachidonic acid-containing phospholipids, lactosylceramide, and cholesterol esters compared to patients in the ward. Specifically, phosphatidylinositols (PIs) showed strong fatty acid saturation-dependent behavior, with saturated fatty acid (SFA)- and monosaturated fatty acid (MUFA)-derived PI decreasing and polystaturated (PUFA)-derived PI increasing. We also found ~4000 significant Spearman correlations between lipids and multiple clinical markers of immune response with |R| ≥ 0.35 and FDR corrected Q < 0.05. Except for lysophosphatidic acid, lysophospholipids were positively associated with the CD4 fraction of T cells, and the cytokines IL-8 and IL-18. In contrast, sphingosine-1-phosphates were negatively correlated with innate immune markers such as CRP and IL-6. Further indications of metabolic changes in moderate COVID-19 disease were demonstrated in recovering ward patients compared to those at the start of hospitalization, where 99 lipid species were altered (6 increased by 30-62%; 93 decreased by 1.3-2.8-fold). Overall, these findings support and expand on early reports that dysregulated lipid metabolism is involved in COVID-19.

Dataset Information

Altered somatic hypermutation patterns in COVID-19 patients classifies disease severity.

Introduction

Methods

Results

Discussion

Publications

Altered somatic hypermutation patterns in COVID-19 patients classifies disease severity.

Similar Datasets

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