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Enregistrement W4412839068 · doi:10.1111/all.16657

Oral Immunotherapy of Peanut Allergy: A Critical Role for Gut‐Associated Immunity

2025· editorial· en· W4412839068 sur OpenAlexaff
Annette Kuehn, Thomas Eiwegger

Notice bibliographique

RevueAllergy · 2025
Typeeditorial
Langueen
DomaineMedicine
ThématiqueFood Allergy and Anaphylaxis Research
Établissements canadiensUniversity of Toronto
Organismes subventionnairesAustrian Science FundFonds National de la Recherche Luxembourg
Mots-clésOral immunotherapyPeanut allergyImmunologyAllergyMedicineImmunotherapyImmunityFood allergyOral toleranceImmune system

Résumé

récupéré en direct d'OpenAlex

IgE-mediated food allergy is an important burden affecting up to 2%–3% of the global pediatric population [1]. Oral immunotherapy (OIT) has emerged as an important treatment option in managing food-allergic conditions [2]. OIT is very efficient regarding desensitization, but tolerance induction (i.e., the maintenance of complete desensitization in the absence of food ingestion) is observed in ~10%–20% of patients undergoing peanut OIT [3]. To completely overcome or establish full control over such a well-established response as IgE-mediated food allergy with anaphylaxis is a challenging task, and understanding the immune alterations underlying OIT is a prerequisite. To date, a consistent reduction in type 2 immunity, particularly in Th2 cell frequency and levels of allergen-specific type 2-associated cytokines, has been observed across multiple studies and correlated with treatment response [1, 4]. Cell subsets like Th2A cells, which are terminally differentiated CD4+ T cells expressing CRTH2, CD49d, and CD161, were reduced in frequency following OIT treatment. More recently, cell populations including Th17 cells, CD8+ T cells, unconventional T cell subsets, and NK cells were linked to OIT-induced immune alterations. These changes complement insights on neutralizing antibodies (increased blood IgG4, mucosal IgA) and reduced basophil activation capacity. In this issue of Allergy, Arnau-Soler et al. [5] report a combined transcriptome and methylome approach of ex vivo short-term allergen-stimulated peripheral blood mononuclear cells (PBMCs) to describe blood immune responses during peanut OIT from a randomized, double-blind, placebo-controlled peanut OIT trial with 27 children in the active and 22 children in the placebo arm. The authors discriminate responders passing the oral food challenge (OFC) with 4500 mg peanut protein (15–20 peanuts) and incomplete responders tolerating ≤ 1000 mg peanut protein. Humoral immune responses were consistent with previous studies [1, 2, 4], with low baseline levels of specific IgE and increased specific IgG4 post-treatment as positive predictors of a complete response. Unlike many others, cytokine production was assessed at 48 h, before allergen-specific T cell clones' expansion, thus reflecting a more ex vivo representation of the paramount of PBMC-related allergen-specific cytokine response. A reduction of Th2 cytokine secretion was reported in line with previous reports. Unlike other studies focusing on allergen-specific T cells using CD154-based approaches, they addressed the transcriptome and methylome profiling of whole PBMC bulks, yielding more granular high-level insights into the functional biology of peanut OIT. This poses risks and chances in re-visiting more general questions with new state-of-the-art transcriptomic methods by using “older” methods of allergen-specific stimulation, which are less rigid than those performed more recently in this context (Table 1A). In the present study, mRNA sequencing and DNA methylation profiling of whole PBMC were performed, and deconvolution approaches were applied to single out cell-type-specific changes. Outcomes indicated toward crucial immune processes happening in the gut: Frequencies of CD4+ T cells with signatures pointing to the small intestine, gut-resident innate lymphoid cells type 3 (ILC3s), and other gut-homing lymphoid cells (CD8αα subsets of CD8+ T cells, γδ T cells) were primarily altered. In addition, OIT-associated DNA methylation changes pointed to human disease associations involving gut inflammation, such as ulcerative colitis and inflammatory bowel disease. The role of gut-associated immune responses is largely underexplored in clinical food allergy, mainly because food allergy is more commonly explored in children, and the clinical indications to conduct biopsies are limited [18]. All the more important are findings on surrogate markers in blood (Figure 1). Using deep immune phenotyping of PBMC from peanut-allergic patients, gastrointestinal symptoms were associated with gut-migratory immune signatures—marked by Th2, memory regulatory T cells (Tregs) and CD8+ T cell responses—via chemotactic navigation and CD196/CCR6 upregulation, further emphasizing the importance of gut tissue inflammation [15]. It has been more recently acknowledged that the breakdown of oral tolerance is broader than hitherto appreciated, involving local gut immune responses, gut barrier integrity, and gut microbiota (Table 1B). This compartmental importance may also happen at the level of IgE responses. IgE+CD138+ plasma cells in gut biopsies from peanut-allergic patients were found to be distinct from IgE+CD138− plasma cells, suggesting native reservoirs of long-lived plasma cells in the lamina propria of the gut, rather than migrating IgE+ plasma cells from distant sites [14]. Local gut IgE production, probably in connection with increased mucosal permeability, tallies with reports of IgE in stool and intestinal secretions. Such fecal IgE was positively associated with abdominal pain scores in peanut allergy, outperforming peanut-sIgE in serum [16]. Good evidence of a link between local IgE production and symptoms also exists for allergic rhinitis. An additional aspect may relate to anti-microbiota Th2 responses occurring in food-allergic patients, as evidenced by fecal bacteria opsonized with IgE [13]. Nascent gut Treg cells usually help direct IgA responses to gut luminal antigens, including bacteria and foods, in part regulated by a MyD88-dependent signaling pathway. In food allergy and gut dysbiosis, a disruption of the MyD88-ROR-γt regulatory axis involves decreased IgA and increased IgE responses to gut microbiota. Such food antigen-specific immune response via receptor-associated orphan γt+ (RORγt+) Treg, a specialized subset of CD4+Foxp3+ cells in the gut, is tightly controlled by goblet-cell-derived resistin-like molecule (RELMβ) as a critical regulator of oral tolerance [17]. Indeed, RELMβ was highly increased in sera from patients with food allergy, confirming heightened pathogenic immune responses to foods. Recently, changes in gene expression profiles of peripheral γδ T cells and GI-resident γδ T cells revealed specific signaling pathway changes during peanut OIT [12]. Notably, the lamina propria harbors a significant number of Tregs (including RORγt+ Treg) and γδ T cells. These new, encouraging treatment targets and predictive biomarkers warrant closer monitoring of gut-associated outcome parameters in peanut OIT. The data from Arnau-Soler et al. [5] is highly relevant in pointing toward changes of gut-associated immunity in successful peanut OIT. A limitation is that those findings are confirmed at the protein and single-cell level. In the future, it will be required to combine different OMIC approaches exploring both innate and adaptive targets, considering gut immune homeostasis when investigating immunological changes during OIT (Figure 1). For the purpose of open access, the authors have applied a Creative Commons Attribution 4.0 International (CC BY 4.0) license to any Author Accepted Manuscript version arising from this submission. The authors declare no conflicts of interest. Data sharing is not applicable to this article as no new data were created or analyzed in this study.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,006
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Intégrité de la recherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,121
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,006
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0020,002
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,017
Tête enseignante GPT0,344
Écart entre enseignants0,327 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2025
Routes d'admission1
Résumé présentoui

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