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1.
JCI Insight ; 7(10)2022 05 23.
Article in English | MEDLINE | ID: covidwho-1794308

ABSTRACT

BACKGROUNDMeasuring the immune response to SARS-CoV-2 enables assessment of past infection and protective immunity. SARS-CoV-2 infection induces humoral and T cell responses, but these responses vary with disease severity and individual characteristics.METHODSA T cell receptor (TCR) immunosequencing assay was conducted using small-volume blood samples from 302 individuals recovered from COVID-19. Correlations between the magnitude of the T cell response and neutralizing antibody (nAb) titers or indicators of disease severity were evaluated. Sensitivity of T cell testing was assessed and compared with serologic testing.RESULTSSARS-CoV-2-specific T cell responses were significantly correlated with nAb titers and clinical indicators of disease severity, including hospitalization, fever, and difficulty breathing. Despite modest declines in depth and breadth of T cell responses during convalescence, high sensitivity was observed until at least 6 months after infection, with overall sensitivity ~5% greater than serology tests for identifying prior SARS-CoV-2 infection. Improved performance of T cell testing was most apparent in recovered, nonhospitalized individuals sampled > 150 days after initial illness, suggesting greater sensitivity than serology at later time points and in individuals with less severe disease. T cell testing identified SARS-CoV-2 infection in 68% (55 of 81) of samples with undetectable nAb titers (<1:40) and in 37% (13 of 35) of samples classified as negative by 3 antibody assays.CONCLUSIONThese results support TCR-based testing as a scalable, reliable measure of past SARS-CoV-2 infection with clinical value beyond serology.TRIAL REGISTRATIONSpecimens were accrued under trial NCT04338360 accessible at clinicaltrials.gov.FUNDINGThis work was funded by Adaptive Biotechnologies, Frederick National Laboratory for Cancer Research, NIAID, Fred Hutchinson Joel Meyers Endowment, Fast Grants, and American Society for Transplantation and Cell Therapy.


Subject(s)
COVID-19 , Antibodies, Neutralizing , Antibodies, Viral , Humans , Receptors, Antigen, T-Cell/genetics , SARS-CoV-2 , Severity of Illness Index , United States
2.
Cell ; 185(5): 881-895.e20, 2022 03 03.
Article in English | MEDLINE | ID: covidwho-1649960

ABSTRACT

Post-acute sequelae of COVID-19 (PASC) represent an emerging global crisis. However, quantifiable risk factors for PASC and their biological associations are poorly resolved. We executed a deep multi-omic, longitudinal investigation of 309 COVID-19 patients from initial diagnosis to convalescence (2-3 months later), integrated with clinical data and patient-reported symptoms. We resolved four PASC-anticipating risk factors at the time of initial COVID-19 diagnosis: type 2 diabetes, SARS-CoV-2 RNAemia, Epstein-Barr virus viremia, and specific auto-antibodies. In patients with gastrointestinal PASC, SARS-CoV-2-specific and CMV-specific CD8+ T cells exhibited unique dynamics during recovery from COVID-19. Analysis of symptom-associated immunological signatures revealed coordinated immunity polarization into four endotypes, exhibiting divergent acute severity and PASC. We find that immunological associations between PASC factors diminish over time, leading to distinct convalescent immune states. Detectability of most PASC factors at COVID-19 diagnosis emphasizes the importance of early disease measurements for understanding emergent chronic conditions and suggests PASC treatment strategies.


Subject(s)
COVID-19/complications , COVID-19/diagnosis , Convalescence , Adaptive Immunity/genetics , Adolescent , Adult , Aged , Aged, 80 and over , Autoantibodies/blood , Biomarkers/metabolism , Blood Proteins/metabolism , CD8-Positive T-Lymphocytes/immunology , CD8-Positive T-Lymphocytes/metabolism , COVID-19/immunology , COVID-19/pathology , COVID-19/virology , Disease Progression , Female , Humans , Immunity, Innate/genetics , Longitudinal Studies , Male , Middle Aged , Risk Factors , SARS-CoV-2/isolation & purification , Transcriptome , Young Adult
3.
Open forum infectious diseases ; 8(Suppl 1):S77-S77, 2021.
Article in English | EuropePMC | ID: covidwho-1602523

ABSTRACT

Background T cells are central to the early identification and clearance of viral infections and support antibody generation by B cells, making them desirable for assessing the immune response to SARS-CoV-2 infection and vaccines. We combined 2 high-throughput immune profiling methods to create a quantitative picture of the SARS-CoV-2 T-cell response that is highly sensitive, durable, diagnostic, and discriminatory between natural infection and vaccination. Methods We deeply characterized 116 convalescent COVID-19 subjects by experimentally mapping CD8 and CD4 T-cell responses via antigen stimulation to 545 Human Leukocyte Antigen (HLA) class I and 284 class II viral peptides. We also performed T-cell receptor (TCR) repertoire sequencing on 1815 samples from 1521 PCR-confirmed SARS-CoV-2 cases and 3500 controls to identify shared public TCRs from SARS-CoV-2-associated CD8 and CD4 T cells. Combining these approaches with additional samples from vaccinated individuals, we characterized the response to natural infection as well as vaccination by separating responses to spike protein from other viral targets. Results We find that T-cell responses are often driven by a few immunodominant, HLA-restricted epitopes. As expected, the SARS-CoV-2 T-cell response peaks about 1-2 weeks after infection and is detectable at least several months after recovery. Applying these data, we trained a classifier to diagnose past SARS-CoV-2 infection based solely on TCR sequencing from blood samples and observed, at 99.8% specificity, high sensitivity soon after diagnosis (Day 3–7 = 85.1%;Day 8–14 = 94.8%) that persists after recovery (Day 29+/convalescent = 95.4%). Finally, by evaluating TCRs binding epitopes targeting all non-spike SARS-CoV-2 proteins, we were able to separate natural infection from vaccination with > 99% specificity. Conclusion TCR repertoire sequencing from whole blood reliably measures the adaptive immune response to SARS-CoV-2 soon after viral antigenic exposure (before antibodies are typically detectable) as well as at later time points, and distinguishes post-infection vs. vaccine immune responses with high specificity. This approach to characterizing the cellular immune response has applications in clinical diagnostics as well as vaccine development and monitoring. Disclosures Thomas M. Snyder, PhD, Adaptive Biotechnologies (Employee, Shareholder) Rachel M. Gittelman, PhD, Adaptive Biotechnologies (Employee, Shareholder) Mark Klinger, PhD, Adaptive Biotechnologies (Employee, Shareholder) Damon H. May, PhD, Adaptive Biotechnologies (Employee, Shareholder) Edward J. Osborne, PhD, Adaptive Biotechnologies (Employee, Shareholder) Ruth Taniguchi, PhD, Adaptive Biotechnologies (Employee, Shareholder) H. Jabran Zahid, PhD, Microsoft Research (Employee, Shareholder) Rebecca Elyanow, PhD, Adaptive Biotechnologies (Employee, Shareholder) Sudeb C. Dalai, MD, PhD, Adaptive Biotechnologies (Employee, Shareholder) Ian M. Kaplan, PhD, Adaptive Biotechnologies (Employee, Shareholder) Jennifer N. Dines, MD, Adaptive Biotechnologies (Employee, Shareholder) Matthew T. Noakes, PhD, Adaptive Biotechnologies (Employee, Shareholder) Ravi Pandya, PhD, Microsoft Research (Employee, Shareholder) Lance Baldo, MD, Adaptive Biotechnologies (Employee, Shareholder, Leadership Interest) James R. Heath, PhD, Merck (Research Grant or Support, Funding (from BARDA) for the ISB INCOV project, but had no role in planning the research or in writing the paper.) Joaquin Martinez-Lopez, MD, PhD, Adaptive Biotechnologies (Consultant) Jonathan M. Carlson, PhD, Microsoft Research (Employee, Shareholder) Harlan S. Robins, PhD, Adaptive Biotechnologies (Board Member, Employee, Shareholder)

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