Copies of Donor Killer Immunoglobulin-like Receptor Genes and Motifs Titrate Natural Killer (NK) Cells' Functional Response to Epstein - Barr Virus Infections and Influence the Risk of Developing Post-Transplant Lymphoproliferative Disease (PTLD) after Allogeneic Hematopoietic Cell Transplantation
Notice bibliographique
Résumé
Abstract BACKGROUND: Recipientsof allogeneic HCT remain vulnerable to a heightened risk of reactivation of otherwise latent viral infections owing to a compromised immune system early after transplantation. Uncontrolled reactivation of Epstein-Barr virus (EBV) leading to post-transplant lymphoproliferative disorder (PTLD) is one of such major complications after T-cell depleted HCT. Recovering within weeks after transplantation and being first in line of defense against viral infections, natural killer (NK) cells are deemed important in the immunopathogenesis of EBV complications. Their role however remains elusive. NK cell responses are regulated by a series of activating and inhibitory cell surface receptors, central to which are the Killer Immunoglobulin-like Receptors (KIR). Through these receptors NK cells discriminate healthy cells from 'altered' self-cells by scaling the perturbations in HLA expression after viral transformation of the target cell. Here, we set out to determine whether and how KIR gene and motifs' content of HCT donors and/or recipients influences the development of PTLD after allo-HCT. STUDY DESIGN: Hypothesizing that diverse NK cell receptor repertoires can titrate NK cell functional responses to EBV infections/reactivation and can potentially modify the risk of developing PTLD, we determined the KIR gene repertoires of 356 HLA-matched donor-recipient pairs of first allo-HCT and 50 healthy donors through Next Generation Sequencing of the KIR locus on the Illumina MiSeq platform. Based on the presence/absence and number of copies of individual genes, the KIR genotypes were determined and classified into four common centromeric (cA01, cB01, cB02 and cB03) and two telomeric (tA01 and tB01) motifs along with their variants. PBMNCs from KIR typed healthy volunteers were stimulated with EBV-transformed target cells to enumerate NK cell response to EBV (degranulation and/or IFNγ production) as a function of KIR gene content and motifs' distribution using a multicolor flow cytometry-based assay. Effect of KIR gene profile on development of PTLD was analyzed using binomial competing risks regression statistics. Distribution of NK cell functional response across various KIR characterized groups was analyzed using Mann-Whitney U statistics. RESULTS: Donor telomeric A motifs (tA01, KIR3DL1+ve KIR2DS4+ve; KIR3DS1/2DS1+/-ve), strongly protected against PTLD (p=0.0001, SHR=0.17; Figure 1). An increased protection against PTLD with increasing number of tA01 was noted with at least one copy required for a significant protective effect (Figure 1B). Copy number analysis of tA01 gene contents yielded similar associations. Further, the number of EBV induced functional NK cell subsets were significantly higher in individuals with than without KIR genotypes containing tA01 motifs (Figure 2 A-C) and was found to be increasing with an increasing number of tA01 copies (Figure 2 A'-C'). There was no influence of recipients' KIR repertoire on the risk of developing PTLD CONCLUSIONS: NK cell responsiveness, a function of KIR gene repertoire has a profound effect on the development of PTLD. Appropriately characterized KIR gene profile based identification of HCT recipients at high risk of developing PTLD will enable closer monitoring of EBV DNAemia and facilitate prompt therapy. Figure 1. Donor KIR telomeric A motif (tA01) protects against the risk of developing PTLD (A). Presence of at least one copy of donor KIR tA01 motif confers significant protection from PTLD (B) Figure 1. Donor KIR telomeric A motif (tA01) protects against the risk of developing PTLD (A). Presence of at least one copy of donor KIR tA01 motif confers significant protection from PTLD (B) Figure 2. KIR telomeric A motifs (tA01) titrate NK cells' functional response to Epstein-Barr virus infected cells (A-C), with and increasing %functional NK cells and subsets (measures as expressing CD107a, IFN-γ, or both) are observed with increasing tA01 motifs' copies (A'-C') Figure 2. KIR telomeric A motifs (tA01) titrate NK cells' functional response to Epstein-Barr virus infected cells (A-C), with and increasing %functional NK cells and subsets (measures as expressing CD107a, IFN-γ, or both) are observed with increasing tA01 motifs' copies (A'-C') Disclosures No relevant conflicts of interest to declare.
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 | 0,000 |
| 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) | 0,002 | 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 ».