Third and fourth vaccine doses broaden and prolong immunity to SARS-CoV-2 in immunocompromised adult patients
Notice bibliographique
Résumé
Abstract Background Previous studies have reported impaired humoral responses after SARS-CoV-2 mRNA vaccination in immunocompromised patients with immune-mediated inflammatory diseases (IMID), particularly those treated with anti-tumor necrosis factor (TNF) biologics. We previously reported that IMID patients exhibited greater waning of antibody and T cell responses compared to healthy controls after dose 2. Fewer data are available on the effects of third and fourth doses. Methods This observational cohort study collected plasma and peripheral blood mononuclear cells from healthy controls and untreated or treated IMID patients, pre-vaccination and after one to four doses of SARS-CoV-2 mRNA vaccine (BNT162b2 or mRNA-1273). SARS-CoV-2- specific antibody levels, neutralization, and T cell cytokine responses were measured against Wildtype (WT) and BA.1 and BA.5 variants of concern (VOCs). Results Third vaccine doses substantially restored and prolonged antibody and T cell responses in IMID patients and broadened responses against VOCs. Fourth dose effects were subtle but also prolonged antibody responses. However, IMID patients treated with anti-TNF, especially inflammatory bowel disease (IBD) patients, exhibited lower antibody responses even after the fourth dose. Although T cell IFNγ responses were maximal after one dose, IL-2 and IL-4 production increased with successive doses, and early production of these cytokines was predictive of neutralization responses at 3-4 months post-vaccination. Conclusion Our study demonstrates that third and fourth doses of the SARS-CoV-2 vaccine sustain and broaden immune responses to SARS-CoV-2, supporting the recommendation for three- and four-dose vaccination regimens in IMID patients. Funding COVID-19 Immunity Task Force and Speck family donation Conflict-of-Interest Statements Anne-Claude Gingras has received research funds from a research contract with Providence Therapeutics Holdings, Inc., for other projects, participated in the COVID-19 Immunity Task Force (CITF) Immune Science and Testing working party, chaired the CIHR Institute of Genetics Advisory Board, and chairs the SAB of the National Research Council of Canada Human Health Therapeutics Board. Vinod Chandran has received research grants from AbbVie, Amgen, and Eli Lilly and has received honoraria for advisory board member roles from AbbVie, Amgen, BMS, Eli Lilly, Janssen, Novartis, Pfizer, and UCB. His spouse is an employee of AstraZeneca. Vincent Piguet has no personal financial ties with any pharmaceutical company. He has received honoraria for speaker and/or advisory board member roles from AbbVie, Celgene, Janssen, Kyowa Kirin Co. Ltd, LEO Pharma, Novartis, Pfizer, Sanofi, UCB, and Union Therapeutics. In his role as Department Division Director of Dermatology at the University of Toronto, Dr. Piguet has received departmental support in the form of unrestricted educational grants from AbbVie, Bausch Health, Celgene, Janssen, LEO Pharma, Lilly, L’Oréal, NAOS, Novartis, Pfizer, Sandoz and Sanofi in the past 36 months. Vincent Piguet has received research grants from Sanofi, Abbvie and Novartis. Mark Silverberg has received research support, consulting fees and speaker honoraria from AbbVie, Janssen, Takeda, Pfizer, Gilead, and Amgen. All other authors have no conflicts to declare. Graphical Abstract
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».