Oral Immunotherapy of Peanut Allergy: A Critical Role for Gut‐Associated Immunity
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".