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1.
Preprint en Inglés | medRxiv | ID: ppmedrxiv-22279558

RESUMEN

BackgroundT cells are important in preventing severe disease from SARS-CoV-2, but scalable and field-adaptable alternatives to expert T cell assays are needed. The interferon-gamma release assay QuantiFERON platform was developed to detect T cell responses to SARS-CoV-2 from whole blood with relatively basic equipment and flexibility of processing timelines. Methods48 participants with different infection and vaccination backgrounds were recruited. Whole blood samples were analysed using the QuantiFERON SARS-CoV-2 assay in parallel with the well-established Protective Immunity from T Cells in Healthcare workers (PITCH) ELISpot, which can evaluate spike-specific T cell responses. AimsThe primary aims of this cross-sectional observational cohort study were to establish if the QuantiFERON SARS-Co-V-2 assay could discern differences between specified groups and to assess the sensitivity of the assay compared to the PITCH ELISpot. FindingsThe QuantiFERON SARS-CoV-2 distinguished acutely infected individuals (12-21 days post positive PCR) from naive individuals (p< 0.0001) with 100% sensitivity and specificity for SARS-CoV-2 T cells, whilst the PITCH ELISpot had reduced sensitivity (62.5%) for the acute infection group. Sensitivity with QuantiFERON for previous infection was 12.5% (172-444 days post positive test) and was inferior to the PITCH ELISpot (75%). Although the QuantiFERON assay could discern differences between unvaccinated and vaccinated individuals (55-166 days since second vaccination), the latter also had reduced sensitivity (55.5%) compared to the PITCH ELISpot (66.6%). ConclusionThe QuantiFERON SARS-CoV-2 assay showed potential as a T cell evaluation tool soon after SARS-CoV-2 infection but has lower sensitivity for use in reliable evaluation of vaccination or more distant infection. Graphical abstractWith the exception of acute infection group, the PITCH ELISpot S1+S2 had greater sensitivity for SARS-CoV-2 specific T cell responses compared with the QuantiFERON SARS-CoV-2 assay tube Ag3. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=64 SRC="FIGDIR/small/22279558v1_ufig1.gif" ALT="Figure 1"> View larger version (13K): org.highwire.dtl.DTLVardef@1913a88org.highwire.dtl.DTLVardef@199b88corg.highwire.dtl.DTLVardef@12309cborg.highwire.dtl.DTLVardef@15807a0_HPS_FORMAT_FIGEXP M_FIG C_FIG

2.
Preprint en Inglés | medRxiv | ID: ppmedrxiv-22275865

RESUMEN

Both infection and vaccination, alone or in combination, generate antibody and T cell responses against SARSCoV2. However, the maintenance of such responses, and hence protection from disease, requires careful characterisation. In a large prospective study of UK healthcare workers (Protective immunity from T cells in Healthcare workers (PITCH), within the larger SARSCoV2 immunity and reinfection evaluation (SIREN) study) we previously observed that prior infection impacted strongly on subsequent cellular and humoral immunity induced after long and short dosing intervals of BNT162b2 (Pfizer/BioNTech) vaccination. Here, we report longer follow up of 684 HCWs in this cohort over 6-9 months following two doses of BNT162b2 or AZD1222 (Oxford/AstraZeneca) vaccination and up to 6 months following a subsequent mRNA booster vaccination. We make three observations: Firstly, the dynamics of humoral and cellular responses differ; binding and neutralising antibodies declined whereas T and memory B cell responses were maintained after the second vaccine dose. Secondly, vaccine boosting restored IgG levels, broadened neutralising activity against variants of concern including omicron BA.1, BA.2 and BA.5, and boosted T cell responses above the 6 month level post dose 2. Thirdly, prior infection maintained its impact driving larger as well as broader T cell responses compared with never-infected people, a feature maintained until 6 months after the third dose. In conclusion, broadly cross-reactive T cell responses are well maintained over time, especially in those with combined vaccine and infection-induced immunity (hybrid immunity), and may contribute to continued protection against severe disease.

3.
Preprint en Inglés | medRxiv | ID: ppmedrxiv-22270447

RESUMEN

BackgroundT cell responses to SARS-CoV-2 following infection and vaccination are less characterised than antibody responses, due to a more complex experimental pathway. MethodsWe measured T cell responses in 108 healthcare workers (HCWs) in an observational cohort study, using the commercialised Oxford Immunotec T-SPOT Discovery SARS-CoV-2 assay (OI T-SPOT) and the PITCH ELISpot protocol established for academic research settings. ResultsBoth assays detected T cell responses to SARS-CoV-2 spike, membrane and nucleocapsid proteins. Responses were significantly lower when reported by OI T-SPOT than by PITCH ELISpot. Four weeks after two doses of either Pfizer/BioNTech BNT162b or ChAdOx1 nCoV-19 AZD1222 vaccine, the responder rate was 63% for OI T-SPOT Panels1+2 (peptides representing SARS-CoV-2 spike protein excluding regions present in seasonal coronaviruses), 69% for OI T-SPOT Panel 14 (peptides representing the entire SARS-CoV-2 spike), and 94% for the PITCH ELISpot assay. The two OI T-SPOT panels correlated strongly with each other showing that either readout quantifies spike-specific T cell responses, although the correlation between the OI T-SPOT panels and the PITCH ELISpot was moderate. ConclusionThe standardisation, relative scalability and longer interval between blood acquisition and processing are advantages of the commercial OI T-SPOT assay. However, the OI T-SPOT assay measures T cell responses at a significantly lower magnitude compared to the PITCH ELISpot assay, detecting T cell responses in a lower proportion of vaccinees. This has implications for the reporting of low-level T cell responses that may be observed in patient populations and for the assessment of T cell durability after vaccination.

4.
- The COvid-19 Multi-omics Blood ATlas (COMBAT) Consortium; David J Ahern; Zhichao Ai; Mark Ainsworth; Chris Allan; Alice Allcock; Azim Ansari; Carolina V Arancibia-Carcamo; Dominik Aschenbrenner; Moustafa Attar; J. Kenneth Baillie; Eleanor Barnes; Rachael Bashford-Rogers; Archana Bashyal; Sally Beer; Georgina Berridge; Amy Beveridge; Sagida Bibi; Tihana Bicanic; Luke Blackwell; Paul Bowness; Andrew Brent; Andrew Brown; John Broxholme; David Buck; Katie L Burnham; Helen Byrne; Susana Camara; Ivan Candido Ferreira; Philip Charles; Wentao Chen; Yi-Ling Chen; Amanda Chong; Elizabeth Clutterbuck; Mark Coles; Christopher P Conlon; Richard Cornall; Adam P Cribbs; Fabiola Curion; Emma E Davenport; Neil Davidson; Simon Davis; Calliope Dendrou; Julie Dequaire; Lea Dib; James Docker; Christina Dold; Tao Dong; Damien Downes; Alexander Drakesmith; Susanna J Dunachie; David A Duncan; Chris Eijsbouts; Robert Esnouf; Alexis Espinosa; Rachel Etherington; Benjamin Fairfax; Rory Fairhead; Hai Fang; Shayan Fassih; Sally Felle; Maria Fernandez Mendoza; Ricardo Ferreira; Roman Fischer; Thomas Foord; Aden Forrow; John Frater; Anastasia Fries; Veronica Gallardo Sanchez; Lucy Garner; Clementine Geeves; Dominique Georgiou; Leila Godfrey; Tanya Golubchik; Maria Gomez Vazquez; Angie Green; Hong Harper; Heather A Harrington; Raphael Heilig; Svenja Hester; Jennifer Hill; Charles Hinds; Clare Hird; Ling-Pei Ho; Renee Hoekzema; Benjamin Hollis; Jim Hughes; Paula Hutton; Matthew Jackson; Ashwin Jainarayanan; Anna James-Bott; Kathrin Jansen; Katie Jeffery; Elizabeth Jones; Luke Jostins; Georgina Kerr; David Kim; Paul Klenerman; Julian C Knight; Vinod Kumar; Piyush Kumar Sharma; Prathiba Kurupati; Andrew Kwok; Angela Lee; Aline Linder; Teresa Lockett; Lorne Lonie; Maria Lopopolo; Martyna Lukoseviciute; Jian Luo; Spyridoula Marinou; Brian Marsden; Jose Martinez; Philippa Matthews; Michalina Mazurczyk; Simon McGowan; Stuart McKechnie; Adam Mead; Alexander J Mentzer; Yuxin Mi; Claudia Monaco; Ruddy Montadon; Giorgio Napolitani; Isar Nassiri; Alex Novak; Darragh O'Brien; Daniel O'Connor; Denise O'Donnell; Graham Ogg; Lauren Overend; Inhye Park; Ian Pavord; Yanchun Peng; Frank Penkava; Mariana Pereira Pinho; Elena Perez; Andrew J Pollard; Fiona Powrie; Bethan Psaila; T. Phuong Quan; Emmanouela Repapi; Santiago Revale; Laura Silva-Reyes; Jean-Baptiste Richard; Charlotte Rich-Griffin; Thomas Ritter; Christine S Rollier; Matthew Rowland; Fabian Ruehle; Mariolina Salio; Stephen N Sansom; Alberto Santos Delgado; Tatjana Sauka-Spengler; Ron Schwessinger; Giuseppe Scozzafava; Gavin Screaton; Anna Seigal; Malcolm G Semple; Martin Sergeant; Christina Simoglou Karali; David Sims; Donal Skelly; Hubert Slawinski; Alberto Sobrinodiaz; Nikolaos Sousos; Lizzie Stafford; Lisa Stockdale; Marie Strickland; Otto Sumray; Bo Sun; Chelsea Taylor; Stephen Taylor; Adan Taylor; Supat Thongjuea; Hannah Thraves; John A Todd; Adriana Tomic; Orion Tong; Amy Trebes; Dominik Trzupek; Felicia A Tucci; Lance Turtle; Irina Udalova; Holm Uhlig; Erinke van Grinsven; Iolanda Vendrell; Marije Verheul; Alexandru Voda; Guanlin Wang; Lihui Wang; Dapeng Wang; Peter Watkinson; Robert Watson; Michael Weinberger; Justin Whalley; Lorna Witty; Katherine Wray; Luzheng Xue; Hing Yuen Yeung; Zixi Yin; Rebecca K Young; Jonathan Youngs; Ping Zhang; Yasemin-Xiomara Zurke.
Preprint en Inglés | medRxiv | ID: ppmedrxiv-21256877

RESUMEN

Treatment of severe COVID-19 is currently limited by clinical heterogeneity and incomplete understanding of potentially druggable immune mediators of disease. To advance this, we present a comprehensive multi-omic blood atlas in patients with varying COVID-19 severity and compare with influenza, sepsis and healthy volunteers. We identify immune signatures and correlates of host response. Hallmarks of disease severity revealed cells, their inflammatory mediators and networks as potential therapeutic targets, including progenitor cells and specific myeloid and lymphocyte subsets, features of the immune repertoire, acute phase response, metabolism and coagulation. Persisting immune activation involving AP-1/p38MAPK was a specific feature of COVID-19. The plasma proteome enabled sub-phenotyping into patient clusters, predictive of severity and outcome. Tensor and matrix decomposition of the overall dataset revealed feature groupings linked with disease severity and specificity. Our systems-based integrative approach and blood atlas will inform future drug development, clinical trial design and personalised medicine approaches for COVID-19.

5.
Preprint en Inglés | medRxiv | ID: ppmedrxiv-20202929

RESUMEN

A major issue in identification of protective T cell responses against SARS-CoV-2 lies in distinguishing people infected with SARS-CoV-2 from those with cross-reactive immunity generated by exposure to other coronaviruses. We characterised SARS-CoV-2 T cell immune responses in 168 PCR-confirmed SARS-CoV-2 infected subjects and 118 seronegative subjects without known SARS-CoV-2 exposure using a range of T cell assays that differentially capture immune cell function. Strong ex vivo ELISpot and proliferation responses to multiple antigens (including M, NP and ORF3) were found in those who had been infected by SARS-CoV-2 but were rare in pre-pandemic and unexposed seronegative subjects. However, seronegative doctors with high occupational exposure and recent COVID-19 compatible illness showed patterns of T cell responses characteristic of infection, indicating that these readouts are highly sensitive. By contrast, over 90% of convalescent or unexposed people showed proliferation and cellular lactate responses to spike subunits S1/S2, indicating pre-existing cross-reactive T cell populations. The detection of T cell responses to SARS-CoV-2 is therefore critically dependent on the choice of assay and antigen. Memory responses to specific non-spike proteins provides a method to distinguish recent infection from pre-existing immunity in exposed populations.

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