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. Author manuscript; available in PMC: 2024 Jul 1.
Published in final edited form as: J Allergy Clin Immunol. 2023 Mar 30;152(1):155–166.e9. doi: 10.1016/j.jaci.2023.03.020

Distinct trajectories distinguish Antigen-specific T cells in peanut-allergic individuals undergoing oral immunotherapy

Justine Calise 1, Hannah DeBerg 2, Nahir Garabatos 1, Sugandhika Khosa 1, Veronique Bajzik 1, Lorena Botero Calderon 1, Kelly Aldridge 1, Mario Rosasco 2, Brian C Ferslew 3, Tong Zhu 3, Ronald Smulders 3, Lisa M Wheatley 6, Tanya M Laidlaw 7,8, Tielin Qin 7, Gurunadh R Chichili 3, Daniel C Adelman 4, Mary Farrington 5, David Robinson 5, David Jeong 5, Stacie M Jones 9, Srinath Sanda 10, David Larson 7, William W Kwok 1, Carolyn Baloh 7,8, Gerald T Nepom 7, Erik Wambre 1
PMCID: PMC10330178  NIHMSID: NIHMS1896602  PMID: 37003475

Abstract

Background:

Despite similar clinical symptoms, peanut allergic (PA) individuals may respond very differently to the same therapeutic interventions.

Objective:

This study aimed to determine whether inherent qualities of pTeff cell responses at baseline may influence response to PnOIT.

Methods:

We first performed ex vivo T cell profiling on peanut-reactive CD154+ CD137+ T (pTeff) cells from 90 challenged-confirmed peanut allergic (PA) individuals. We developed a gating strategy for unbiased assessment of the phenotypic distribution of rare pTeff cells across different memory CD4+ T cell subsets to define the patient’s immunotype. In longitudinal samples of 29 peanut allergic participants enrolled in the IMPACT trial of peanut oral immunotherapy (PnOIT), we determined whether patient immunotype at baseline may influence response to PnOIT.

Results:

Our data emphasize the heterogeneity of pTeff cell responses in PA participants with two mutually exclusive phenotypic entities (CCR6-CRTH2+ and CCR6+CRTH2-). Our findings lead us to propose that peanut allergy can be classified broadly into at least 2 discrete subtypes, termed “immunotypes”, with distinct immunological and clinical characteristics based on proportion of TH2A pTeff cells. PnOIT induced elimination of TH2A pTeff cells in the context of the IMPACT clinical trial. Only PA patient with low level of TH2A pTeff cells at baseline had a long-lasting benefit of remission following PnOIT discontinuation.

Conclusion:

Dividing PA patients according to their individual peanut specific T cell profile may facilitate patient stratification in the clinic by identifying which immunotypes might be most responsive to different therapies.

Keywords: CD4+ T cells, oral immunotherapy, Immunotype, peanut allergy, TH2A cells, IMPACT trial

Graphical Abstract

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Capsule Summary:

Peanut allergic T cells display distinct immunotypes with differential response to immunotherapy.

INTRODUCTION

Peanut allergy is one of the most common food allergies worldwide, accounting for a majority of the food-induced fatal anaphylactic reactions [1]. While many food allergies are outgrown, most children who are peanut allergic (PA) retain their allergy into adulthood. Moreover, not only do peanut-induced allergic reactions vary in severity and symptoms, but therapeutic responses to oral immunotherapy also vary among individuals. It is likely that differing clinical phenotypes of peanut allergy are caused by differing molecular and cellular phenotypes, but the mechanisms underlying these phenotypes of peanut allergy and responses to treatment are still unknown.

It is now well established that allergen specific CD4+ T cells in allergic individuals play a key role in the induction of the immune cascade that leads to food allergy [2, 3]. While an aberrant T helper 2 (TH2) response is a characteristic feature of food allergy, it is less certain whether food allergy can be driven by non-TH2 cell subsets of allergen-specific cells [4].Previous studies tracking peanut specific CD4+ T cells in PA individuals receiving PnOIT showed that T cell phenotypes are heterogeneous and change throughout therapy [5, 6]. A greater understanding of the heterogeneity of peanut-reactive effector T cell (pTeff) responses in PA individuals will provide important insights about the mechanisms of clinical and immunologic responses associated with peanut allergy.

In this study, we utilized a classification of peanut-specific CD4 T cells into discrete subtypes, termed “immunotypes”, with distinct immunological and clinical characteristics based on the proportion of TH2A pTeff cells (readily identified by cell surface expression of CRTH2 and associated markers). In PA participants enrolled in the IMPACT trial of PnOIT, conducted by the Immune Tolerance Network, we assessed the prevalence of these cells at baseline and during response to PnOIT. IMPACT was a randomized, double-blind placebo-controlled study of PnOIT in young children aged 12 to 48 months conducted in 5 US academic centers [7]. Participants were randomized to daily PnOIT or placebo for 134 weeks followed by a period of peanut avoidance for 26 weeks. PnOIT resulted in desensitization of a majority (71%) of participants; however, remission after PnOIT discontinuation was only achieved in 21% of PnOIT recipients. We found that longitudinal profiling of circulating peanut-specific T cells by flow cytometry and RNA sequencing (RNA-seq) suggests that the baseline properties of PA individuals and their trajectory during PnOIT differed according to the cellular phenotype. These immunotypes likely result from different immunologic mechanisms and therefore may require different immunotherapeutic approaches.

METHODS

Study design

The main objective of this study was to characterize heterogeneity of peanut-specific T cells in challenged-confirmed peanut allergic individuals and to determine whether inherent composition of pTeff cell responses at start of therapy is linked to PnOIT-related outcomes. Every patient that participated in the mechanistic study arm was included. We first used CD154/CD137 upregulation assay and RNA-Seq analysis to profile ex vivo pTeff cell responses in challenged-confirmed PA individuals. From this, we defined a T cell immunotype for each PA individual by considering the prevalence of pTeff cell responses within seven major memory CD4 T cell populations. Our finding leads us to propose that peanut allergy can be classified broadly into at least 2 discrete subtypes, termed “immunotypes”, with distinct immunological and clinical characteristics based on proportion of TH2A pTeff cells (readily identified by cell surface expression of CRTH2 and associated markers). In PA participants enrolled in the IMPACT trial of PnOIT conducted by the Immune Tolerance Network, we next determined whether inherent qualities of pTeff cell responses at baseline may influence response to POIT. We also performed longitudinal small bulk RNA-seq analysis on total pTeff cells to examine gene transcript alteration during PnOIT.

Peanut allergic study participants

Challenged-confirmed PA participants aged 6 to 35 years old were all screened for participation in peanut immunotherapy trials (NCT02635776, NCT02851277, NCT03755713) and some were recruited at the Allergy Clinic at Virginia Mason Franciscan Health Medical Center. All individuals were recruited with informed consent, and the study was approved by the Institutional Review Board of Benaroya Research Institute (IRB07109–605). The participants all had a history of peanut-induced reactions, a clinical reaction at or below ingestion of 300 mg peanut protein during the screening DBPCFC, a positive skin prick test, and positive peanut-specific IgE ≥0.35 kU/liter (ImmunoCAP test; Thermo Fisher). Blood samples were taken before any treatment for peanut allergy. Every patient that participated in the mechanistic study arm was included. A table summarizing demographics and baseline clinical reactivity between trials is shown in Supplemental Table 1.

IMPACT trial design and participants

IMPACT (#NCT01867671) [7] was a randomized, double-blind, placebo-controlled, multi-center study comparing PnOIT to placebo in the induction of desensitization and remission in peanutallergic children aged 12-<48 months. Eligible participants were randomly assigned to receive either target maintenance dose of 2000mg peanut protein or placebo for 134 weeks followed by peanut avoidance for 26 weeks. Desensitization was defined as the ability to tolerate 5000mg of peanut protein with no more than mild symptoms during DBPCFC at week 134. Remission was defined as retaining the ability to tolerate 5000mg of peanut protein with no more than mild symptoms during DBPCFC at week 160. During this trial, coded samples from 29 participants were provided to the operator at baseline, during the build-up phase (Week 12), at the target maintenance phase (week 30), at the end of the maintenance phase (week 134) and after 26 weeks of treatment discontinuation during the avoidance period (week 160). These participants represented all subjects with longitudinal collection of sufficient PBMC for analysis. Within this cohort, 5 did not achieve successful desensitization to peanut (not desensitized/no remission group), 8 participants were desensitized but did not achieve remission (desensitized/no remission group), 8 participants were successfully desensitized and achieved remission (desensitized/remission group) and 8 participants received placebo (oat flour). A table summarizing demographics and baseline clinical reactivity of IMPACT mechanistic study participants is shown in Supplemental Table 2.

Ex vivo peanut reactive T cell assay

PBMCs were isolated from patient blood samples by density gradient centrifugation (Ficoll-Paque Plus; GE Healthcare). Assays for the detection of peanut reactive CD4+ T cells (pTeff) were performed as described [8]. In brief, frozen PBMCs resuspended in T cell medium at a concentration of 10*106/ml were stimulated for 16 hours with a pooled library of 20-mer overlapping peptides spanning the entire Ara h 1, Ara h 2, Ara h 3, Ara h 6, and Ara h 8 peanutallergic components in the presence of functional grade αCD40 at a concentration of 1μg/ml cells (clone HB-14, Miltenyi Biotec). Cells were then harvested, and a fraction of the cells was saved for frequency estimation based on a previously published method [9]. The rest of cultured cells were stained with PE-CF594-conjugated anti−CD154 and PE-Cy7-conjugated anti-CD137 (clone 4B4–1) mAbs and magnetically enriched by anti-PE MicroBeads and MS column according to the manufacturer’s instructions (Miltenyi Biotec). Magnetically enriched cells were stained for 10 minutes at room temperature with antibodies directed against surface molecule (Supplemental Table 3) before analysis. A combination of the vital dye Via-Probe (BD Pharmingen) as a viability marker, CD19, CD56 and CD14 was used to exclude dead cells, B cells, NK cells and monocytes from the analysis, respectively. Peanut-reactive T cells were identified by co-expression of CD154 and CD137 within non-naive CD4+ T cell populations. pTreg cells were defined by expression of CD137 within the CD154-CD127-CD25+ Treg cells. The FACS LSR Fortessa and FACS Aria Fusion (BD Biosciences) were used for multi-parameter analysis and sorting, respectively. Sorted cells were quickly spun down, flash frozen on dry ice and stored at −80C until RNAseq analysis. Data were analyzed with FlowJo software (FlowJo LLC, BD Biosciences), GraphPad Prism and with R.

Intracellular cytokine analysis

For ICS combined with the CD154 activation assay, BD GolgiStop™ was added to the PBMCs during the last three hours of ex vivo culture according to the manufacturer’s instructions. Enriched pTeff cells were then surface stained, fixed and permeabilized for 30 minutes at room temperature using the Foxp3 Transcription Factor Staining Buffer Set (eBioscience, San Diego) according to the manufacturer’s instructions. Cells were then stained for 20 minutes at room temperature with antibodies directed against IL-5, IL-4, IFN-g, IL-13 and IL-17A (Supplementary Table 1). Cells were then washed once prior to data acquisition.

Allergen-elicited T helper response analysis (AETHER)

AETHER (Allergen-Elicited T Helper Responses) is a flow cytometry-based analysis method that we developed to cluster allergen-reactive T helper subsets with no overlap. To this end, total CD4+ memory T cells from individuals were clustered based on a Boolean gating strategy into seven T-Helper subsets based on the expression pattern of these chemokine receptors [2, 10–14]. These clusters were labelled as TH2A (CRTH2+CXCR5-), TFH (CRTH2-CXCR5+), TH1 (CRTH2-CXCR5-CXCR3+CCR6-), TH1/TH17 (CRTH2-CXCR5-CXCR3+ CCR6+), TH17 (CRTH2-CXCR5-CXCR3-CCR6+), TH2conv (CRTH2-CXCR5-CXCR3-CCR6-CCR4+) and a cluster that did not express any of these chemokine receptors, referred to as TH0. Subsequently, prevalence of peanut-reactive T cells (CD154+) was determined for each cluster in each subject. For characterization of the peanut-reactive T cell immunotype, we restricted analysis to samples that contained 50 or more CD154+ cell events. Clusters were considered dominant if they contained more than 20% of the total CD154+ T cells, as this cutoff required more than 10 pTeff cells to be present.

RNAseq library preparation and analysis

A total of 25 sorted cells (minimum 20) were sorted directly into reaction buffer from the SMART-Seq v4 Ultra Low Input RNA Kit for Sequencing (Takara), and reverse transcription was performed followed by PCR amplification to generate full length amplified cDNA. Sequencing libraries were constructed using the NexteraXT DNA sample preparation kit with unique dual indexes (Illumina) to generate Illumina-compatible barcoded libraries. Libraries were pooled and quantified using a Qubit® Fluorometer (Life Technologies). Sequencing of pooled libraries was carried out on a NextSeq 2000 sequencer (Illumina) with paired-end 53-base reads, using NextSeq P2 sequencing kits (Illumina) with a target depth of 5 million reads per sample. Base calls were processed to FASTQs on BaseSpace (Illumina), and a base call quality-trimming step was applied to remove low-confidence base calls from the ends of reads. The FASTQs were aligned to the University of California Santa Cruz (UCSC) Human genome assembly version 19, using STAR v.2.4.2a and gene counts were generated using htseq-count. QC and metrics analysis was performed using the Picard family of tools (v1.134). In total, 182 samples were sequenced. 178 (98%) of samples passed the quality criteria. To detect differentially expressed genes between sorted cell subsets, the RNA-seq analysis functionality of the linear models for microarray data (Limma) R package was used [15]. Expression counts were normalized using the TMM algorithm [16]. A false discovery rate adjustment was applied to correct for multiple testing.

TCR clonality analysis

To reconstruct full-length nucleotide sequences encoding TCR chains from bulk RNAseq libraries, we applied a three-step bioinformatic pipeline. First, all reads were processed using Trimmomatic [17] to remove adapter sequences and to require a minimum average Phred quality score of 20 across each 4-base window. Next, contigs were assembled from the short-read data using the Trinity assembler [18]. Default Trinity parameters were used except for `‐‐group_pairs_distance=2000, ‐‐path_reinforcement_distance=40, ‐‐inchworm_min_kmer_cov=3`. Contigs generated by Trinity were then processed using MiXCR [19] to identify sequences encoding TCR chains. The alignment stage of MiXCR was run with the option `-OvParameters.geneFeatureToAlign=VTranscript`, and the assembly stage of MiXCR was run with the option `-OassemblingFeatures=VDJRegion`.

Statistical analysis

Statistical analysis was performed using GraphPad Prism software or in R. The following statistical tests were used where appropriate: Mann Whitney tests with the Holm-Sidak method as needed for a multiple testing correction or Kruskal Wallis tests with the Dunn test as needed for a multiple testing correction. Longitudinal cytometry data was modeled using generalized least squares with the R package nlme [20]. Percent of antigen-reactive cells or log-transformed frequencies were modeled as a function of visit and result group with interaction effects. A firstorder autoregressive covariance structure of order 1 was used to model within patient error. The multcomp r package was used for comparisons between result groups with a false discovery rate multiple testing adjustment [21].

RESULTS

Peanut-reactive CCR6+ T cells display distinct effector and homing properties from TH2A cells

Expression of cell surface markers (CD154 and CD137) reflects recent engagement of the T cell receptor (TCR) by cognate major histocompatibility complex (MHC)-peptide complexes [22, 23]. We used a selective ex-vivo CD154/CD137 upregulation assay to characterize peanut-reactive CD4+ T cell responses in baseline PBMC samples from challenge-confirmed PA individuals that participated in clinical trials. This flow-based assay demonstrates high sensitivity for detection of peanut-reactive CD4+ T cells (CD154+CD137+) (Figure 1A). To examine heterogeneity of peanut-reactive CD4+ T cells, we assessed the expression of canonical T helper cell-associated surface markers such as CXCR3, CCR6, CXCR5, CCR4, and CRTH2. We observed a low proportion of pTeff cells expressing the TH1-associated marker CXCR3 or the TFH-associated marker CXCR5 but a high proportion of CCR4-expressing pTeff cells (Figure 1B). We noticed that PA individuals have variable proportions of pTeff cells expressing the TH2A-related marker, CRTH2, and the TH17-related marker, CCR6, as some were CRTH2-immunodominant and others CCR6-immunodominant (Figure 1B & C). Interestingly, CRTH2 and CCR6 expression within pTeff cells was mutually exclusive, suggesting distinct effector and homing potential of these cells in PA individuals (Figure 1D). To further assess phenotypic differences between CCR6+ and CRTH2+ pTeffs cells in PA individuals, we next examined expression of additional cell surface markers selected to elucidate the maturation (CD27, CD161), exhaustion (PD-1) and homing (CLA, iB7) properties of pTeff cells. We also included cell surface markers for epithelial cytokine receptors ST2 and IL-17RB, recently reported to be selectively up-regulated on activated TH2A cells [24]. Consistent with previous reports, CRTH2+ pTeff cells fell into the CD161+CD27- subset and expressed ST2 and IL-17RB, allowing us to consider them as TH2A cells [2, 24] (Figure 1E & Supplementary Figure 1A-C). We also observed significantly higher expression of PD1 within CRTH2+ pTeffs cells, which is a characteristic marker of T cell exhaustion and poor survival rate following repeated antigenic stimulation. CCR6+ pTeff cells contrasted phenotypically with CRTH2+ pTeff cells, with higher expression of CD27 and lower expression of CD161, ST2 and IL-17RB. Assessment of homing potential also revealed that CCR6+ pTeffs cells expressed higher levels of the skin-homing receptor (CLA) than did CRTH2+ pTeff cells. However, no statistical difference was observed between these two pTeff cell subsets regarding the expression of the gut-homing receptor integrin β7. Ex vivo intracellular cytokine staining further indicated differential effector cell function between CRTH2+ and CCR6+ pTeff cells (Figure 1F & Supplementary Figure 1D). For instance, CRTH2+ pTeff cells were capable of immediately producing cardinal TH2 cytokines (i.e., IL4, IL-5 and IL-13) after short peanut peptide stimulation. In contrast, we observed a lack of immediate effector cell functions in CCR6+ pTeff cells, likely reflecting the difference in maturation stage.

Figure 1. CCR6+ pTeff cells contrasted phenotypically with CRTH2+ pTeff cells.

Figure 1.

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A. Representative flow cytometric plots showing ex vivo detection of peanut-reactive T cells in PA individual using CD154/CD137 up-regulation assay. Plots are gated on CD4+CD45RA-Dump- T cells in PE-enriched PBMCs. B. Expression of canonical T helper cell-associated surface markers within peanut-reactive T cells in PA individuals. C. Correlation between percentage of CRTH2+ and CCR6+ peanut-reactive T cells in PA individuals. D. Representative flow cytometric plots showing CRTH2 and CCR6 expression within peanut-reactive T cells in PA individuals. E and F. Surface marker (E) and cytokine (F) profiling between CRTH2+ (red) and CCR6+ (green) peanutreactive T cells in PA individuals. B, C, E and F. Each dot represents distinct individuals. Differences between groups were analyzed by using the two-sided Mann-Whitney test with a Holm-Sidak adjustment for multiple comparisons. * p < 0.05, ** p < 0.01, *** p <0.001, **** p <0.0001

Markers of TH2A inflammation are absent in a specific subset of peanut allergic individuals

Seven major memory CD4+ T cell populations were classified by flow cytometry using differential expression of CRTH2, CXCR5, CXCR3, CCR6, and CCR4 cell surface markers to define TH2A (CRTH2+CXCR5-), TFH (CRTH2-CXCR5+), TH1 (CRTH2-CXCR5-CXCR3+CCR6-), TH1/TH17 (CRTH2-CXCR5-CXCR3+CCR6+), TH17 (CRTH2-CXCR5-CXCR3-CCR6+), TH2 conventional (TH2conv; CRTH2-CXCR5-CXCR3-CCR6-CCR4+) and a cluster that did not express any of these chemokine receptors, referred to as TH0. Next, CD154 expression in response to stimulation with peanut antigen was determined within this CD4+ T cell landscape, as shown in Supplementary Figure 2. The prevalence of each pTeff cell subset observed in a PA individual was then considered as a T cell immunotype of that response. We found heterogeneity of pTeff cells within PA individuals and common phenotypes across individuals (Figure 2A). Three common clusters (i.e., TH2conv, TH2A and TH17-like) contained the largest representation of pTeff cells in PA individuals. When the TH2A cluster accounted for less than 20% of the total pTeff cells, these PA individuals were classified as “TH2A-low” immunotype, versus a “TH2A-high immunotype” when the TH2A cluster accounted for more than 20% of the total pTeff cells (Supplementary Figure 3A&B). Importantly, ex vivo pTeff cell profiles were stable over time in the absence of therapy, as was the number of dominant pTeff clusters present in an individual (Supplementary Figure 3C). The proportion of TH17-like pTeff cells was significantly higher in the TH2A-low group (Figure 2B); however, no significant differences in TH1, TFH, TH0, or TH2conv-like pTeff cell subsets were observed between the two PA immunotypes. PA individuals with a TH2A-high immunotype had significantly higher frequencies of circulating pTeff cells than TH2A-low PA individuals (Figure 2C). Clinical features differed between the two PA immunotypes within our cohort of PA individuals. Consistent with a positive correlation between CRTH2+ pTeff cells and psIgE level [25], TH2A-high PA individuals were associated with significantly higher serum peanut-specific (ps) IgE (p<0.0001) (Figure 2D). Interestingly, we also observed a significantly higher level of serum psIgG4 (<0.01) in TH2A-high PA individuals suggesting a potential functional connection in B-cell derived shifts from IgE to IgG4 (Figure 2E). Age was also statistically different between the two PA immunotypes in this cohort of PA patients aged 6 to 35 years old (Figure 2F). However, skin prick test (SPT) wheals to peanut were not different between groups (Figure 2G).

Figure 2. Peanut allergy can be divided into at least two distinct immunotypes defined by degree of TH2A inflammation.

Figure 2.

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A. Heatmap of phenotypic distribution of peanut-reactive T cells across seven major memory T cell population are indicated across the top in N=90 PA individuals indicated by row. Clusters containing more than 20% peanut-reactive T cells for a PA individual are indicated in black. B. Prevalence of each pTeff cell subset between TH2A-High (red dots) and TH2A-low (blue dots) PA individuals. C. Frequencies of global circulating peanut-reactive T cells between TH2A-High (red dots) and TH2A-low (blue dots) PA individuals. D-G. Serum peanutspecific IgE level (D), serum peanut-specific IgG4 level (E), Age (F) and Skin prick test to peanut (G) between TH2A-low and TH2A-high PA individuals. E. The dashed line indicates the lower limit of detection. B-G. Each dot represents distinct individuals. Differences between groups in B-G were analyzed by using a two-sided Mann-Whitney test. A false discovery rate multiple testing correction was applied in B. * p < 0.05, ** p < 0.01, *** p <0.001, **** p <0.0001

TH2A high and low immunotypes are associated with distinct gene expression signatures

To comprehensively characterize the molecular properties of CRTH2+ pTeff and CCR6+ pTeff cells and determine their potential roles relative to immunotype, we sorted these cell subsets and performed RNA-seq analysis. Double negative (DN) CRTH2-CCR6- pTeff cells were also sorted for this analysis. As expected, CRTH2+ pTeff cells expressed gene transcripts linked to TH2/TH2A effector functions including (i) epithelium-derived cytokines receptors (IL1RL1, IL17RB), (ii) TH2 cytokines (IL-5, IL-9, IL-13, IL-31), (iii) transcription factors (GATA-3, PPARg) and (iv) lipid synthesis (HPGDS, ALOX5AP) (Figure 3A-B). Gene transcripts associated with antigen-driven T cell anergy and exhaustion such as EGR2 and TIGIT were also significantly upregulated in CRTH2+ pTeff cells. In contrast, CCR6+ pTeff cells expressed higher levels of genes linked to TH17 function, such as IL-17A, IL-17F, IL23R, CCL20, IL1R1 when compared with CRTH2+ pTeff cells, potentially implicating this pathway in this immunotype. CCR6+ pTeff cells also contrasted transcriptionally with CRTH2+ pTeff cells with higher levels of CCR7, CD27 and Foxp3, potentially conferring a survival benefit and regulatory function during chronic antigen exposure. The DN pTeff cell subset represents an “in between” cell type when compared to the CRTH2+ and CCR6+ pTeff cells (Figure 3C and D). Consistent with our surface marker profiling, none of our sorted pTeff cell subset showed significantly increased expression of TFH-like gene modules. Sequencing of T cell receptors in each cohort revealed only limited clonal overlap between CCR6+ pTeff cells and CRTH2+ pTeff cells, compatible with different ancestries and epitope specificity for the subsets. We also found that the vast majority of TCRα and β chains were private (not shared between individuals) with limited convergence onto common TCR motifs (Figure 3E).

Figure 3. Dichotomous pattern of CRTH2+ and CCR6+ pTeff cells in PA individuals.

Figure 3.

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A. Volcano plots show differentially expressed genes contrasting CCR6+ (green), CRTH2+ (red), and DN (yellow) peanut-reactive T cell subsets. Genes with a false discovery rate less than 0.05 and a fold-change of at least 2 between conditions are considered differentially expressed. The 20 genes with the smallest FDR values are indicated by name. (B) Heatmap showing gene expression of pathway-associated genes between the sorted pTeff cell subset. Data are shown in z score– scaled values. (C-D) Expression levels of transcripts associated with (C) TH2/TH2A and (D) TH1/TH17 signaling in CCR6+ (green), CRTH2+ (red), and DN (yellow) peanut-reactive T cell subsets. (E) Each segment of the Circos plot represents a TCR junction found in CCR6+ (green), CRTH2+ (red), or DN (yellow) peanut-reactive T cell subsets. Outer ring denotes donors. Arcs connect junctions shared between samples. (C-D) Each dot represents distinct individuals. False discovery rate adjusted p-values from differential expression linear models are reported. * p < 0.05, ** p < 0.01, *** p <0.001

Immunotype trajectories associated with peanut OIT

Longitudinal collections of peripheral T cells from 29 participants were obtained from the IMPACT PnOIT trial to assess immunotype properties during immunotherapy. A schematic of the IMPACT trial participant samples included for T cell analyses is shown in Supplementary Figure 4A and B. IMPACT study participants were all reactive to <500 mg of peanut protein during DBPCFC at study entry. PnOIT-treated participants were classified in 3 groups according to the ability to consume 5000mg during DBPCFC at the end of treatment (week 134) and 26 weeks after treatment discontinuation (week 160) (Supplementary Figure 4C). The 29 subjects studied represented all subjects with longitudinal collection of sufficient PBMC for analysis, and characteristics of the subset used for T cell analysis were consistent with data from the entire IMPACT study cohorts [7] (Supplementary Figure 4D-F). As expected for a TH2A-associated marker, we found a positive correlation between baseline CRTH2+ pTeff cell frequencies and baseline serum psIgE level (Figure 4A). However, no correlation was observed between CRTH2+ pTeff cell frequencies and baseline psIgG4 in this cohort of toddler PA individuals (Figure 4B). During PnOIT, a marked decrease in global pTeff cell frequency was observed compared to baseline as PA individuals progressed through active therapy (Figure 4C). This downward trajectory reached its nadir at the end of PnOIT (week 134) and was lower in the desensitized groups compared to the not desensitized/no remission group. Interestingly, pTeff cell frequency tended to rebound 6 months after treatment discontinuation (week 160) in all PnOIT treated groups. Conversely, the frequency of pTeff cells increased over time in the IMPACT placebo participants. No significant variation was observed in pTreg cell frequency during the course of PnOIT (Figure 4D). Consistent with the use of CRTH2+ and CCR6+ markers to identify distinct pTeff cell subsets described in Figures 1–3, these same markers represented distinct populations in the IMPACT study participants, and notably differed in frequency during the course of PnOIT clinical trial. As shown in Figure 4E, CRTH2+ pTeff cells decreased in all OIT participants, but not in the placebo subjects during immunotherapy, with a partial rebound towards baseline levels after week 134, when therapy was discontinued. In contrast, CCR6+ pTeff cells did not show this decrease, and instead showed a reciprocal relative increase. Noteworthy, we also observed a progressive and significant increase in the proportion of CD27+ pTeff cells and decrease in the proportion of TIGIT+ pTeff cells in active PnOIT groups compared to placebo (Figure 4F). These changes during desensitization occurred in all OIT groups and did not significantly differ with respect to the durability of clinical outcome. PA immunotype assessment at baseline, although limited by the small number of subjects analyzed, also suggested that participants who achieved desensitization and remission following PnOIT mainly displayed a TH2A-low immunotype while most participants in the desensitized/no remission group had greater than 20% CRTH2+ pTeff cells at baseline, allowing us to consider them primarily as TH2A-high PA individuals. (Figure 4G&H and Supplementary Figure 5). In the IMPACT PnOIT trial, likelihood of successful desensitization and tolerance were correlated with younger ages [7]. Same trend was observed in our cohort of IMPACT study participant (Figure 5A); however, age was not a determinant of immunotype in these subjects (Figure 5B). We also observed that PA Immunotype in the placebo group of this cohort of toddler individuals was stable during the period of the trial (Figure 5C and D). However, cross-sectional analysis of all tested PA individuals in this study suggests that PA immunotype may vary by age in absence of therapy providing different window of opportunity for intervention (Figure 5E-F).

Figure 4. Trajectories of peanut-specific T cells in peanut-allergic individuals undergoing oral immunotherapy.

Figure 4.

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(A-B). Correlation between frequency of CRTH2+ pTeff cells and serum peanut-specific IgE level (A) or serum peanut-specific IgG4 level (B) in IMPACT mechanistic study participants at baseline. Each dot represents distinct individuals. (C-D). Dynamic of peanutreactive T effector cell (C) and peanut-reactive T regulatory cell (D) responses between cohorts during the IMPACT trial. (E) Percent changes from baseline of CRTH2 and CCR6 expression within pTeff cells during PnOIT. (F) Percent changes from baseline of CD27 and TIGIT expression within pTeff cells during PnOIT. (G-H) Percentages (G) and frequencies (H) of CRTH2-expressing peanut reactive T cells between cohorts are indicated for each time point of the IMPACT trial. ND/NR = not desensitized/no remission, D/NR = desensitized/no remission, D/R = desensitized/remission. Differences between active group and placebo in the indicated time point were analyzed by using generalized least squares modeling followed by a false discovery rate adjustment for multiple testing. * p < 0.05, ** p < 0.01, *** p

Figure 5. Cross-sectional analysis of how peanut reactive T cell profile vary by age.

Figure 5.

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(A). Relationship between Age and likelihood of successful desensitization and remission during IMPACT trial mechanistic study. (B) Relationship between Peanut allergic immunotype and age of participants from IMPACT trial mechanistic study. (C and D) River plots depicting percentage of peanut-reactive cells across the seven major memory CD4 T cell populations for PA toddler individuals at four different time point in a TH2A-low (C) and a TH2A-high (D) PA individual in absence of therapy (Placebo group of IMPACT study). The widths of the color “rivers” in the plots reflect percentages for each pTeff cell subset. Data are representative of at least three donors. (E and F) Correlation between Age of PA individuals and percentage of CRTH2+ pTeff cells (E) or CCR6+ pTeff cells (F). (A-B and E-F) Each dot represents distinct PA individuals.

Characteristic gene transcript alterations during PnOIT reflect each immunotype profile

To better examine impact of PnOIT on pTeff cells, we performed longitudinal RNA-seq analysis on antigen-specific pTeff cells from IMPACT study participants. First, we performed pairwise analyses to identify differentially expressed genes between active and placebo relative to baseline during the course of PnOIT (Figure 6A). Consistent with our flow cytometry-based T cell profiling, only genes associated with TH2 and TH2A effector function, such as IL-4, IL-9, IL-13, IL-31, IL1RL1 and IL17RB, were significantly decreased over time compared to baseline as individuals progressed on active therapy. We also observed an increase in expression of genes associated with TH1 and TH17 effector function, such as IFNg, T-bet, IL-17A and IL-17F. This trend was not observed in the placebo group. These transcriptional profiles support the notion that the CRTH2+ and CCR6+ flow cytometry-defined pTeff cell clusters are distinct immunotypes, as described above. We next examined differentially expressed genes from baseline in relation to clinical outcome at the end of treatment phase (week 134) and after 26 weeks of PnOIT avoidance (week 160) (Figure 6B&C). Decreases in TH2/TH2A gene expression levels were observed in all active groups at week 134 compared to baseline. However, only the desensitized/no remission group reached statistical significance likely due to the combination of TH2A high PA immunotype at baseline and a substantial decrease in CRTH2+ pTeff cells with treatment. Similarly, as the D/R group in our study had a baseline Immunotype that was more TH2A-low like than that of the other groups, the depletion of TH2A cells was smaller in magnitude and therefore did not rise to the level of statistical significance. We also observed increased gene expression of TNFSF10 in all active PnOIT groups, which has been recently demonstrated to negatively correlate with peanut-specific IgE production [6] and to play a role in dampening Th2 responses to allergen [26]. Following PnOIT discontinuation, a low TH2/TH2A signature and low IL-10 gene expression were observed in each active group compared to placebo irrespective of clinical outcome. However, the decrease in the TH2A gene signature IL1RL1 (ST2/IL33 receptor) only reached significance at week 160 in the desensitized/remission group relative to baseline. Interestingly, we observed a trend of higher expression of genes associated with TH1 (IFNg; T-bet) and regulatory (FOXP3) function within the two desensitized groups compared to the no desensitized/no remission and placebo groups. We also investigated clonality of psTCRs in IMPACT study participants over time to determine if T cell repertoire evolved during PnOIT. Although our profiling was shallow (N=25 cells per sample), we were able to recover the same TCRs repeatedly across time points for most participants, suggesting persistence of some clones. We observed mostly private TCR α and β chains, consistent with donor specific dominant TCR profiles (Supplementary Figure 6).

Figure 6. A critical low level of TH2A cells is required to elicit clinical remission during PnOIT.

Figure 6.

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(A). Heatmap showing longitudinal change from baseline in median expression of selected gene between placebo (green) and active group (red) during IMPACT trial. (B-C) Heatmap showing change from baseline at week 134 (B) and week 160 (C) in median expression of selected gene between each cohort of IMPACT trial. (A-C) Data are shown in z score–scaled values. * FDR < 0.05, ** FDR < 0.01, *** FDR <0.001, **** FDR < 0.0001

DISCUSSION

PnOIT can be an effective disease-modifying treatment to induce desensitization in PA individuals. In this study, we used an antigen-driven CD154/CD137 upregulation assay and RNA-Seq analysis to profile pTeff cell responses which defined a T cell immunotype for each PA individual based on the prevalence of pTeff cell characteristics in memory CD4+ T cell populations. Our data emphasize a dichotomy in the pTeff cell responses in PA individuals, with two mutually exclusive cellular and molecular signatures associated with food allergy. The first signature includes genes enriched in pathogenic type 2 inflammatory response (GATA-3, IL1RL1, IL-5, IL-9, IL17RB). Consistent with previous reports, this gene signature characterized a TH2A cell subset within pTeff cells that co-express CRTH2, ST2, IL25R and CD161 but lack expression of CD27. This contrasts with an alternative cellular signature among CCR6+ CRTH2- pTeff cells with skin-homing properties (CLA surface expression) and high gene expression of RORγt, IL-7A, IL-17F, IL-22, IL-23R and CCL20. Notably, in the absence of intervention, these circulating pTeff cell profiles were stable over time, establishing an individual-specific pattern that highlights the potential impact of a personalized approach to food allergy care. This finding leads us to propose that peanut allergy can be classified broadly into at least 2 discrete subtypes, termed “immunotypes”, based upon the predominance of TH2A pTeff cells in peripheral blood, readily identified by cell surface expression of CRTH2 and associated markers. PA individuals with a “TH2A-high” immunotype are characterized by high frequency of circulating pTeff cells and high level of serum psIgE and psIgG4 whereas the “TH2A low” immunotype is characterized by a dominant CCR6+ pTeff cell responses that shares some characteristics with TH1 and TH17-like lineages. PnOIT in the context of the IMPACT clinical trial selectively decreased the frequency of CRTH2+ pTeff cells, thereby reshaping initial TH2A-high immunotypes toward a TH2A-low immunotype. Effective PnOIT was associated with immunotherapy-induced decreased frequency of circulating pTeff cells without induction of pTreg cells, supporting the concept that a critical low level of TH2A cells is required to elicit clinical remission and that the development of effective strategies targeting TH2A cells may improve outcomes of peanut immunotherapy.

Food allergy has been conventionally thought to be driven by an aberrant TH2 immune response to food antigens that initiate and maintain key pathophysiological features of the disease. Our observation that a subset of patients manifests clinical features of peanut allergy despite a relative absence of peanut specific TH2 cells, with a dominance of an alternative CCR6+ pTeff immunotype, offers a new perspective. The exact role for T cells in food allergy is yet to be fully understood but alternate immunotypes could be involved in different stages of disease or could represent distinct pathogenesis. There is precedent for associating a CCR6+, IL-17-like phenotype with allergy, particularly in disease initiation. For instance, abrogation of IL-17 or IL-22 function impairs both epicutaneous [27] and airway [28] allergic sensitization in mouse models [29, 30]. Similarly, in human tissues, IL-17A and IL-22 levels correlate with asthma severity and seem to directly influence the nature of the cellular recruitment at the site of inflammation [29]. Sensitization through the skin is likely the first in a cascade of events that ultimately leads to food allergy. CCR6+ pTeff cells may also contribute to exacerbation of allergic inflammation following food antigen exposure into lesional skin. For instance, blockade of IL-17A activity by administering anti-IL17A monoclonal antibodies to OVA alum sensitized and challenge mice remarkably reduces oral allergen induced TH2 cytokine production, OVA-specific IgE in serum and TH2-mediated eosinophilic inflammation [31–34]. IL-17A is also able to induce IL-19 expression in airway epithelia synergistically with IL-4 and IL-13, enhancing a possible Th2 response [35].

Several findings in the current study suggest a possible pathogenic contribution of the CRTH2-negative peanut-specific T cell subset; in particular, we observed higher expression of the skinhoming marker CLA in CCR6+ pTeff cells compared to CRTH2+ pTeff cells, reminiscent of the strong association between skin sensitization, skin barrier dysfunction, and peanut allergy. Our transcript analysis in CCR6+ pTeff cells also revealed high expression of guanylate binding protein 5 (GBP5). GBP5 serves as a unique rheostat for NLRP3 inflammasome activation which proteolytically activates IL-1β and IL-18 [36]. These pro-inflammatory cytokines further induce effector cells, such as neutrophils and macrophages, to instigate inflammatory responses in damaged tissue. Recently, human and mouse experimental evidence has demonstrated that the NLRP3 inflammasome, IL-1β, and IL-18 are critically involved in the development of allergic diseases [37, 38].

Compared to CRTH2+ pTeff, we found that CCR6+ pTeff cells have a significantly higher expression of CD27 but lower expression of PD-1, which suggests the possibility that high allergen dose and persistent TCR stimulation during PnOIT may promote different “selection” or “T cell fate” between CRTH2+ and CCR6+ pTeff cell subsets. Thus, in addition to the effect of PnOIT lowering the frequency of TH2A cells, antigen-based therapies could shift immunotype fate determination, such that skewing of pTeff cells away from the TH2A cell responses might represent a key event in the development of long-lasting peripheral tolerance to allergen. Drivers may include (i) selective T cell exhaustion/deletion in pathogenic TH2 cells during PnOIT allowing other T cell responses to emerge, (ii) auto-regulatory feedback loop to prevent excessive TH2A cell responses, (iii) induction of regulatory B cells or tolerogenic dendritic cells. Addressing these possibilities in future studies may provide a better understanding of the clinically evident need to sustain allergen immunotherapy over several years in order to facilitate a durable outcome. A limitation of the current study relates to the small number of participants within the different cohorts of the IMPACT mechanistic study arm (due to limited access to longitudinal samples with sufficient PBMC for analysis). Consequently, we were unlikely to detect statistically significant differences in these samples. However, we showed strong correlation between TH2A pTeff cells and psIgE level. As likelihood of sustained unresponsiveness in the entire IMPACT trial dataset was correlated with low baseline psIgE, it can be speculated that TH2A pTeff level at baseline will also be associated with response to immunotherapy. Whether our findings in IMPACT trial generalize to older PnOIT participants will also need to be investigated as phenotype of pTeff cells may change with age. Future studies in larger multi-institutional cohorts should address these limitations, along with greater application of T cell immunotype profiling, both before and during the early stages of immunotherapy. In addition, it will be important to confirm our findings in other allergy settings, such as house dust mite and pollen allergies.In summary, our data emphasize the heterogeneity of pTeff cell responses in PA participants with two mutually exclusive phenotypic entities (CCR6-CRTH2+ and CCR6+CRTH2-) associated with food allergy. Dividing PA patients according to their individual peanut specific T cell profile or ‘immunotype’ may facilitate patient stratification in the clinic by identifying which immunotypes might be most responsive to different therapies. Further definition of these immunotypes offers the potential for targeted food allergy management, with therapeutic and prognostic implications.

Supplementary Material

1

Key messages.

  • Peanut allergy can be classified into at least 2 discrete immunotypes, based upon the predominance of peanut-specific TH2A cells

  • Peanut-reactive CCR6+ T cells display distinct effector and homing properties from TH2A cells

  • Low level of peanut-specific TH2A cells at baseline is required to elicit clinical remission following PnOIT discontinuation

Acknowledgments:

We gratefully acknowledge the patients who participated in the IMPACT clinical trial, and the following investigators who contributed to that effort: Edwin H. Kim, MD2, Kari C. Nadeau, MD, PhD3, Anna Nowak-Wegrzyn, MD4,6, Robert A. Wood, MD5, Hugh A. Sampson, MD4, Amy M. Scurlock, MD1, Sharon Chinthrajah, MD3, Julie Wang, MD4, Robert D. Pesek, MD1, Sayantani B. Sindher, MD3, Mike Kulis, PhD2, Jacqueline Johnson, DrPH7, Katharine Spain, MS7, Denise C. Babineau, PhD7, Hyunsook Chin, MPH7, Joy Laurienzo-Panza, RN8, Rachel Yan, MS9 , David Larson, PhD10, Tielin Qin, PhD10, Don Whitehouse, MS9, Michelle L. Sever, PhD7, Srinath Sanda, MD9, Marshall Plaut, MD8, Lisa M. Wheatley, MD, MPH8, and A. Wesley Burks, MD2, as well as additional members of the Immune Tolerance Network. We also gratefully acknowledge all peanut allergic participants. We acknowledge the M. J. Murdock Charitable Trust for awarding BRI Equipment & Technology Grants. We would like to thank Gina Marchesini11, Kavitha Gilroy11, Sylvia Posso11, Sabrina Skiba11, and Thien-Son Nguyen11 for their assistance in collecting sample during this study. We acknowledge members of the BRI flow cytometry core facility and genomics core for their technical assistance: Adam Wojno11, Tuan Nguyen11, Vivian Gersuk11, Quynh-Anh Nguyen11, Jessica Garber11, Kimberly O’Brien11, and Brandon Larson11. We thank C. Cousens-Jacobs11 for the excellent secretarial assistance. We gratefully acknowledge Alex Hu11 for bioinformatic assistance.

1Department of Pediatrics, University of Arkansas for Medical Sciences and Arkansas Children’s Hospital, Little Rock, AR, USA; 2Departments of Medicine and Pediatrics, University of North Carolina, Chapel Hill, NC, USA; 3Department of Pediatrics and Sean N. Parker Center for Allergy and Asthma Research, Stanford University, Palo Alto, CA, USA; 4Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY, USA; 5Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD, USA; 6Department of Pediatrics, New York University Langone Health, New York, NY, USA; 7Rho Federal Systems Division, Durham, NC, USA; 8National Institute of Allergy and Infectious Diseases, National Institutes of Health (NIAID, NIH), Bethesda, MD, USA; The Immune Tolerance Network, 9San Francisco, CA, USA and 10Bethesda, MD, USA; 11Benaroya Research Institute at Virginia Mason, Seattle, WA.

Funding:

Research reported in this publication was performed as a project of the Immune Tolerance Network and supported by:

The National Institute of Allergy and Infectious Diseases of the National Institutes of Health under Award Number UM1AI109565 and U19 AI135817 to E. Wambre and W.W. Kwok.

The Seattle Food Allergy Consortium (SeaFAC) and the Food Allergy Research and Education (FARE) contributed supplemental support to the Wambre Laboratory.

Astellas Pharma provided support to the Benaroya Research Institute for experiments on samples from Astellas’s clinical trial.

The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Disclosure:

EW receives grant support from NIAID, NCI, Food Allergy Research and Education (FARE), Immune Tolerance Network (ITN), research sponsorship from Regeneron Pharmaceuticals, Astellas Pharma, COUR Pharma and Aimmune Therapeutics.

JC, GN declare no competing interests.

BF, TZ, RS, GC are full-time employees of Astellas and hold stock or stock options.

DCA is a former employee of Aimmune Therapeutics and currently chairs the company’s scientific advisory board.

The rest of the authors declare that they have no relevant conflicts of interest.

Abbreviations:

CCR6

C-C motif chemokine receptor 6

CRTH2

chemoattractant receptorhomologous molecule expressed on Th2 cells

DBPCFC

double-blinded placebo-controlled peanut challenge

DN

Double negative

FOXP3

forkhead box P3

IL

interleukin

ND

Nondesensitized

NR

No Remission

PA

Peanut Allergic

PnOIT

peanut oral immunotherapy

pTeff

peanut-reactive T cell

ps

peanut-specific

R

Remission

Th

T helper

TH2A

pro-allergic TH2 cells

TH2conv

TH2 conventional

Footnotes

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Data and materials availability:

Datasets utilized in this study are available without restriction on the Immune Tolerance Network data-sharing portal, www.ITNTrialShare.org.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

1
NIHMS1896602-supplement-1.pdf (13.4MB, pdf)

Data Availability Statement

Datasets utilized in this study are available without restriction on the Immune Tolerance Network data-sharing portal, www.ITNTrialShare.org.

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