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1.
Nat Commun ; 13(1): 1220, 2022 03 09.
Article in English | MEDLINE | ID: covidwho-1735246

ABSTRACT

COVID-19 shares the feature of autoantibody production with systemic autoimmune diseases. In order to understand the role of these immune globulins in the pathogenesis of the disease, it is important to explore the autoantibody spectra. Here we show, by a cross-sectional study of 246 individuals, that autoantibodies targeting G protein-coupled receptors (GPCR) and RAS-related molecules associate with the clinical severity of COVID-19. Patients with moderate and severe disease are characterized by higher autoantibody levels than healthy controls and those with mild COVID-19 disease. Among the anti-GPCR autoantibodies, machine learning classification identifies the chemokine receptor CXCR3 and the RAS-related molecule AGTR1 as targets for antibodies with the strongest association to disease severity. Besides antibody levels, autoantibody network signatures are also changing in patients with intermediate or high disease severity. Although our current and previous studies identify anti-GPCR antibodies as natural components of human biology, their production is deregulated in COVID-19 and their level and pattern alterations might predict COVID-19 disease severity.


Subject(s)
Autoantibodies/immunology , COVID-19/immunology , Receptors, G-Protein-Coupled/immunology , Renin-Angiotensin System/immunology , Autoantibodies/blood , Autoimmunity , Biomarkers/blood , COVID-19/blood , COVID-19/classification , Cross-Sectional Studies , Female , Humans , Machine Learning , Male , Multivariate Analysis , Receptor, Angiotensin, Type 1/immunology , Receptors, CXCR3/immunology , SARS-CoV-2 , Severity of Illness Index
2.
RMD Open ; 7(3)2021 12.
Article in English | MEDLINE | ID: covidwho-1561469

ABSTRACT

BACKGROUND: The persistence of the SARS-CoV2 pandemic, partly due to the appearance of highly infectious variants, has made booster vaccinations necessary for vulnerable groups. Questions remain as to which cohorts require SARS-CoV2 boosters. However, there is a critical lack of data on the dynamics of vaccine responses in patients with chronic inflammatory diseases (CID) undergoing immunosuppressive/disease modifying anti-rheumatic (DMARD) treatment. Here, we present the first data regarding the decline of the vaccine-induced humoral immune responses in patients with CID. METHODS: 23 patients with CID were monitored clinically and for anti-spike IgG and IgA levels, neutralization efficacy and antigen-specific CD4+ T cell responses over the first 6 months after SARS-CoV2 vaccination. 24 healthy individuals were included as controls. RESULTS: While anti-spike IgG-levels declined in CID patients and healthy controls, patients receiving anti-TNF treatment showed significantly greater declines at 6 months post second vaccination in IgG and especially neutralizing antibodies. IgA levels were generally lower in CID patients, particularly during anti-TNF therapy. No differences in SARS-CoV2 spike-specific CD4+ T-cell frequencies were detected. CONCLUSION: Although the long-term efficacy of SARS-CoV2 vaccination in CID patients undergoing disease-modifying therapy is still not known, the pronounced declines in humoral responses towards SARS-CoV2 6 months after mRNA vaccination in the context of TNF blockade should be considered when formulating booster regimens. These patients should be considered for early booster vaccinations.


Subject(s)
COVID-19 Vaccines/immunology , COVID-19 , Immunity, Humoral , Tumor Necrosis Factor Inhibitors/adverse effects , Antibodies, Viral/blood , Antirheumatic Agents/adverse effects , COVID-19/immunology , COVID-19/prevention & control , Humans , Immunosuppressive Agents/adverse effects
4.
Nature ; 594(7862): 265-270, 2021 06.
Article in English | MEDLINE | ID: covidwho-1246377

ABSTRACT

Fast and reliable detection of patients with severe and heterogeneous illnesses is a major goal of precision medicine1,2. Patients with leukaemia can be identified using machine learning on the basis of their blood transcriptomes3. However, there is an increasing divide between what is technically possible and what is allowed, because of privacy legislation4,5. Here, to facilitate the integration of any medical data from any data owner worldwide without violating privacy laws, we introduce Swarm Learning-a decentralized machine-learning approach that unites edge computing, blockchain-based peer-to-peer networking and coordination while maintaining confidentiality without the need for a central coordinator, thereby going beyond federated learning. To illustrate the feasibility of using Swarm Learning to develop disease classifiers using distributed data, we chose four use cases of heterogeneous diseases (COVID-19, tuberculosis, leukaemia and lung pathologies). With more than 16,400 blood transcriptomes derived from 127 clinical studies with non-uniform distributions of cases and controls and substantial study biases, as well as more than 95,000 chest X-ray images, we show that Swarm Learning classifiers outperform those developed at individual sites. In addition, Swarm Learning completely fulfils local confidentiality regulations by design. We believe that this approach will notably accelerate the introduction of precision medicine.


Subject(s)
Blockchain , Clinical Decision-Making/methods , Confidentiality , Datasets as Topic , Machine Learning , Precision Medicine/methods , COVID-19/diagnosis , COVID-19/epidemiology , Disease Outbreaks , Female , Humans , Leukemia/diagnosis , Leukemia/pathology , Leukocytes/pathology , Lung Diseases/diagnosis , Machine Learning/trends , Male , Software , Tuberculosis/diagnosis
5.
Ann Rheum Dis ; 80(10): 1306-1311, 2021 10.
Article in English | MEDLINE | ID: covidwho-1150213

ABSTRACT

INTRODUCTION: In light of the SARS-CoV-2 pandemic, protecting vulnerable groups has become a high priority. Persons at risk of severe disease, for example, those receiving immunosuppressive therapies for chronic inflammatory cdiseases (CIDs), are prioritised for vaccination. However, data concerning generation of protective antibody titres in immunosuppressed patients are scarce. Additionally, mRNA vaccines represent a new vaccine technology leading to increased insecurity especially in patients with CID. OBJECTIVE: Here we present for the first time, data on the efficacy and safety of anti-SARS-CoV-2 mRNA vaccines in a cohort of immunosuppressed patients as compared with healthy controls. METHODS: 42 healthy controls and 26 patients with CID were included in this study (mean age 37.5 vs 50.5 years). Immunisations were performed according to national guidelines with mRNA vaccines. Antibody titres were assessed by ELISA before initial vaccination and 7 days after secondary vaccination. Disease activity and side effects were assessed prior to and 7 days after both vaccinations. RESULTS: Anti-SARS-CoV-2 antibodies as well as neutralising activity could be detected in all study participants. IgG titres were significantly lower in patients as compared with controls (2053 binding antibody units (BAU)/mL ±1218 vs 2685±1102). Side effects were comparable in both groups. No severe adverse effects were observed, and no patients experienced a disease flare. CONCLUSION: We show that SARS-CoV-2 mRNA vaccines lead to development of antibodies in immunosuppressed patients without considerable side effects or induction of disease flares. Despite the small size of this cohort, we were able to demonstrate the efficiency and safety of mRNA vaccines in our cohort.


Subject(s)
COVID-19 Vaccines/immunology , COVID-19/prevention & control , Immunocompromised Host/immunology , Immunogenicity, Vaccine/immunology , Inflammation/drug therapy , Adult , Aged , Aged, 80 and over , Antibodies, Neutralizing/immunology , Antibodies, Viral/immunology , Cohort Studies , Female , Humans , Immunosuppressive Agents/therapeutic use , Inflammation/immunology , Male , Middle Aged , Rheumatic Diseases/drug therapy , Rheumatic Diseases/immunology , SARS-CoV-2 , Vaccines, Synthetic/immunology
6.
Immunity ; 53(6): 1258-1271.e5, 2020 12 15.
Article in English | MEDLINE | ID: covidwho-988080

ABSTRACT

CD4+ T cells reactive against SARS-CoV-2 can be found in unexposed individuals, and these are suggested to arise in response to common cold coronavirus (CCCoV) infection. Here, we utilized SARS-CoV-2-reactive CD4+ T cell enrichment to examine the antigen avidity and clonality of these cells, as well as the relative contribution of CCCoV cross-reactivity. SARS-CoV-2-reactive CD4+ memory T cells were present in virtually all unexposed individuals examined, displaying low functional avidity and multiple, highly variable cross-reactivities that were not restricted to CCCoVs. SARS-CoV-2-reactive CD4+ T cells from COVID-19 patients lacked cross-reactivity to CCCoVs, irrespective of strong memory T cell responses against CCCoV in all donors analyzed. In severe but not mild COVID-19, SARS-CoV-2-specific T cells displayed low functional avidity and clonality, despite increased frequencies. Our findings identify low-avidity CD4+ T cell responses as a hallmark of severe COVID-19 and argue against a protective role for CCCoV-reactive T cells in SARS-CoV-2 infection.


Subject(s)
CD4-Positive T-Lymphocytes/immunology , COVID-19/immunology , Receptors, Antigen, T-Cell/metabolism , Rhinovirus/immunology , SARS-CoV-2/immunology , Antigens, Viral/immunology , Cells, Cultured , Cross Reactions , Disease Progression , Environmental Exposure , Humans , Immunologic Memory , Lymphocyte Activation , Protein Binding , Severity of Illness Index , T-Cell Antigen Receptor Specificity
7.
Immunity ; 53(6): 1296-1314.e9, 2020 12 15.
Article in English | MEDLINE | ID: covidwho-965599

ABSTRACT

Temporal resolution of cellular features associated with a severe COVID-19 disease trajectory is needed for understanding skewed immune responses and defining predictors of outcome. Here, we performed a longitudinal multi-omics study using a two-center cohort of 14 patients. We analyzed the bulk transcriptome, bulk DNA methylome, and single-cell transcriptome (>358,000 cells, including BCR profiles) of peripheral blood samples harvested from up to 5 time points. Validation was performed in two independent cohorts of COVID-19 patients. Severe COVID-19 was characterized by an increase of proliferating, metabolically hyperactive plasmablasts. Coinciding with critical illness, we also identified an expansion of interferon-activated circulating megakaryocytes and increased erythropoiesis with features of hypoxic signaling. Megakaryocyte- and erythroid-cell-derived co-expression modules were predictive of fatal disease outcome. The study demonstrates broad cellular effects of SARS-CoV-2 infection beyond adaptive immune cells and provides an entry point toward developing biomarkers and targeted treatments of patients with COVID-19.


Subject(s)
COVID-19/metabolism , Erythroid Cells/pathology , Megakaryocytes/physiology , Plasma Cells/physiology , SARS-CoV-2/physiology , Adult , Aged , Aged, 80 and over , Biomarkers , Blood Circulation , COVID-19/immunology , Cells, Cultured , Cohort Studies , Disease Progression , Female , Gene Expression Profiling , Humans , Male , Middle Aged , Proteomics , Sequence Analysis, RNA , Severity of Illness Index , Single-Cell Analysis
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