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\begin{document}

\title{Tropical urban environments reveal a strong association of CD45RB lo
TH2A subset to allergic rhinitis}



\author[1]{Anand Kumar Andiappan}%
\author[1]{Wendy W.L. Lee}%
\author[1]{Kia Joo PUAN}%
\author[1]{Bernett Lee}%
\author[1]{Celine Chua}%
\author[1]{Ser Mei Koh}%
\author[1]{Nurhashikin YUSOF}%
\author[1]{Kim Peng Tan}%
\author[1]{Boris San Luis}%
\author[1]{Jocelyn Ong}%
\author[2]{Simon Merid}%
\author[1]{Rachel Ang}%
\author[1]{Xue Ying Chan}%
\author[1]{Low Jing}%
\author[1]{Eliza Terenzani}%
\author[1]{Josephine Lum}%
\author[1]{Shihui Foo}%
\author[1]{Francesca Zolezzi}%
\author[3]{Annabelle Tay Sok Yan}%
\author[2]{Erik Melén}%
\author[4]{Soh Jian Yi}%
\author[1]{Olaf Rotzschke}%
\affil[1]{Singapore Immunology Network}%
\affil[2]{Karolinska Institutet}%
\affil[3]{National University of Singapore Department of Otolaryngology}%
\affil[4]{National University of Singapore Department of Paediatrics}%


\vspace{-1em}



  
  \date{May 17, 2024}


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\selectlanguage{english}
\begin{abstract}
\textbf{Background}: Allergic rhinitis (AR) is strongly associated with
a type 2 response, characterized by the cytokines IL-5, IL-4 and IL-13.
Several studies have implicated ILC2 and TH2A (CD161+ TH2) but it is not
yet entirely clear which subsets are driving the common allergic
reactions underlying AR. The objective of this study aims to identify
critical pathogenic cell populations associated with AR and to determine
their phenotype and functional contribution to disease progression.
\textbf{Methods}: We identified integral allergic-specific cell types by
transcriptomic sequencing. Whole blood, PBMCs and plasma from a
cross-sectional cohort of 216 individuals were analysed by 9-colour flow
cytometry and ultra-sensitive cytokine bead arrays using unsupervised
clustering algorithms. Clinically active AR cases were further analysed
by functional mass cytometry to define phenotype and cytokine secretion
(IL-2, IL-3, IL-4, IL-5, IL-9, IL13, IL-17A and IL-22) as well as the
expression of the hematopoietic prostaglandin D synthetase (HPGDS).
\textbf{Results}: The unbiased analysis revealed that atopy and AR
manifestation corelated only with eosinophils, plasma IL-5 and CD161+
TH2 cells. In-depth characterization further revealed that the CD45RB
\textsuperscript{lo} CD161+ TH2 subset were most closely associated with
severity. This subset is able to concomitantly secrete multiple
cytokines including IL-5, IL-13 and IL-4 and has been previously
reported to be associated with other eosinophilic allergies.
\textbf{Conclusion}: CD45RB \textsuperscript{lo} CD161+ TH2 have key
roles in driving the allergic response in AR. Neutralizing the CD45RB
\textsuperscript{lo} CD161+ TH2 subset should disrupt the allergic
response pathway, thus providing a target for lasting therapeutic
interventions.%
\end{abstract}%



\sloppy


\textbf{INTRODUCTION}

Allergic airway diseases such as allergic rhinitis (AR) and asthma are a
group of chronic immunopathological conditions affecting more than 20\%
of the world's population. As the most common clinical presentation of
allergy, AR affects up to 400 million individuals worldwide and afflicts
substantial health and economic morbidity. In many regions, AR and other
allergic diseases are still increasing. {[}1{]}

The immunopathogenesis of eosinophilic AR and asthma is typically
associated with a type 2 response, involving cytokines such as
interleukin-5 (IL-5), IL-4 and IL-13. Importantly, IL-5 plays a key role
in promoting the differentiation and survival of eosinophils. The main
producers of IL-5 are type 2 helper T (TH2) cells and mast cells. In
RAG-/- mice lacking both T and B lymphocytes, IL-5 is released by tissue
resident Innate Lymphoid Cells type 2 cells (ILC2), which is associated
with eosinophilia in the pancreas, lung, and the spleen after IL-2
treatment. {[}2{]} In patients with eosinophilic gastrointestinal
disease (EGID), IL-5 is preferentially produced by a subset of TH2 cells
which expresses CRTH2, CD161 and hematopoietic prostaglandin synthase
(HPGDS). As TH2 cell counts positively correlated with blood
eosinophilia, they are also termed pathogenic effector (peTH2) cells.
{[}3{]} HPGDS catalyses the synthesis of prostaglandin D2 (PGD2), a
powerful lipid mediator for allergic inflammation. PGD2 exerts its
effect by promoting the recruitment of CRTH2 expressing cells to induce
airway hyperreactivity.{[}4-6{]} Given that CRTH2 is found on most of
the cell types involved in the eosinophilic response pathway including
eosinophils, basophils, ILC2, type 2 CD8+ T cells (TC2), macrophages and
non-classical monocytes {[}2, 3, 7-9{]} , we sought to determine the
contribution of each cell type in mediating pathogenesis of AR.

In a prior study, we established a sensitisation rate of approximately
80\% of the local population in Singapore to house dust mite (HDM)
allergens. {[}10{]} This results in an incidence rate of about 40\% for
AR. In order to identify the key driver behind airway allergies, we
analysed the CRTH2+ subset in the PBMCs of our Singapore Systems
Immunology Cohort (SSIC) longitudinal cohort. {[}10, 11{]}

Here, we employed unsupervised PhenoGraph clustering to analyse whole
blood and PBMCs from the SSIC cohort. Flow cytometry and ultra-sensitive
cytokine arrays revealed positive associations between circulating
eosinophil numbers and plasma IL-5, confirming the eosinophilic nature
of AR. Furthermore, supervised cluster analysis of PBMCs revealed strong
correlation between CD161+ TH2 and self-reported symptoms of AR as well
as between eosinophil numbers and IgE titres. Notably, IL-5 was found to
be exclusively produced by CD45RB low expressing
(CD45RB\textsuperscript{lo}) CD161+ TH2 subset, suggesting the role of
this population in driving eosinophilia in AR. Finally, in-depth
analysis in an active disease cohort by functional mass cytometry
further established that a specific subset of
CD45RB\textsuperscript{lo}HPGDS+ CD161+ TH2 is directly associated with
AR. {[}12, 13{]} In particular, this subset co-expressed CD27, KLRG1,
CD38, ICOS, C45RO and TSLP-R. Upon stimulation, a complex set of
cytokines comprising IL-5, IL-13, IL-4, IL-2, IL-3 and IL-9 is
concomitantly released from our identified disease-driving subset,
contributing towards inflammation in AR.

\textbf{METHODS}

\textbf{Ethics Statement}

This study was performed in accordance with the declaration of Helsinki
and approved by the Institutional Review Board at the National
University of Singapore (IRB numbers: NUS 10-445) and the SingHealth
Centralised Institutional Review Board (CIRB Ref: 2017/2806). Written
informed consent was obtained from donors prior to sample collection.

\textbf{Cohort Information}

Singapore adult cohort

This study was carried using fresh blood samples from volunteer donors
as well as frozen samples of PBMCs and blood plasma collected from the
Singapore Systems Immunology Cohort (SSIC). {[}10, 11{]} Blood was also
collected in Tempus[?] Blood RNA tubes (Life Technologies, Carlsbad,
Calif) for RNA isolation. The cross-sectional cohort database was
generated based on the recruitment of Singaporeans Chinese (n=216) from
National University of Singapore as previously reported. {[}10, 11{]}
Volunteers were classified as individuals with and without allergic
rhinitis using demographics and medical history information collected
from a survey questionnaire based on the Allergic Rhinitis Impact on
Asthma (ARIA) {[}14, 15{]} and International Study of Asthma and
Allergies in Childhood (ISAAC) guidelines. {[}16{]} Atopy status of
donors were determined using a skin prick test (SPT) as previously
described. {[}10{]}~ A positive SPT response is determined by wheal
diameter of 3 mm or greater, when compared to positive (histamine) and
negative (saline) controls.

Singapore children cohort

The active disease cohort is comprised of mixed-ethnicity Singaporean
subjects below the age of 21 years old. Similarly, clinical phenotypic
information and demographic parameters were obtained from volunteers
using a standardised survey questionnaire based on ARIA and ISSAC
guidelines. All volunteers underwent a SPT using common HDM
allergens\emph{Dermatophagoides pteronyssinus} (DP) and \emph{Blomia
tropicalis}(BT) to ascertain atopy status. Fresh whole blood samples
were collected from the volunteers into Tempus[?] Blood RNA tubes (Life
Technologies, Carlsbad, Calif) for RNA isolation.

Swedish cohort

BAMSE is a population-based Swedish cohort which recruited 4089 newborn
children between 1994-1996. The participants have been followed
repeatedly with questionnaires on lifestyle, exposures and symptoms of
allergic disease, and have attended regular clinical follow-ups. At the
16-year follow-up, gene expression levels were measured (256 individuals
of mean age 16.7 years) with the Affymetrix Human Transcriptome Array
2.0 (HTA).{[}17{]} Whole blood was collected from study subjects in
PAXgene tubes, and RNA was extracted batch-wise (QIAGEN, Courtaboeuf,
France). RNA yield and quality were assessed. RNA of highest quality was
selected for amplification, labelling, and hybridization on HTA with WT
PLUS kit (Affymetrix Inc). Gene expression levels were normalized with
the Robust Multi-array Average (RMA) algorithm and transcript clusters
were annotated as previously described.{[}17{]}

\textbf{Nucleic Acid Extraction and RNA Sequencing}

Total RNA from whole blood was extracted using the MagMAX for Stabilized
Blood Tubes RNA Isolation Kit (ThermoFisher), after which globin mRNA
depletion was performed using Ambion GLOBINclear (ThermoFisher).
Transcript abundance was measured using the Illumina Human HT-12-v4
Expression Bead Chip after preparing fluorescent-labelled PCR products
according to the Illumina Human Whole-Genome Gene Expression DASL Assay
Guide. Only Illumina probes free of any single nucleotide polymorphisms
(SNPs) were used to determine the expression level of the genes to avoid
allele-specific artifacts.

\textbf{RNA Sequencing Data Analysis}

STAR aligner was used (splice junction annotations based on GENCODE
version 27; www.gencodegenes.org) to map paired-end raw reads to human
genome build GRCh38. Based on GENCODE v27, mapped reads and gene
annotations were enumerated using featureCounts. edgeR bioconductor
package was used to compute log2 transformed counts per million mapped
reads (log2CPM) and log2 transformed reads per kilobase per million
mapped reads (log2RPKM). Removal of genes with the log2CPM
inter-quartile range (IQR) of which across all samples was less than 0.5
preceded analysis of differentially expressed genes. Pairwise
comparisons of differentially expressed genes between AR and non-AR was
performed using edgeR. P-values were corrected for multiple testing
using the Benjamini-Hochberg procedure (Benjamini, 2010) and false
discovery rate (FDR). Corrected p-values were presented with a
significance threshold of 0.05. Differentially expressed gene analysis
was carried out using edgeR with the eosinophil percentage as a
covariate. Default parameters were applied to run all software listed
above.

\textbf{Immunophenotyping by flow cytometry}

Fresh whole blood samples from SSIC cohort were lysed using RBC lysis
buffer (containing 155 mM NH\textsubscript{4}Cl, 10 mM
KHCO\textsubscript{3} and 0.1mM EDTA). Cells were washed using PBS and
stained using Anti-IgE (MB10-5C4, Miltenyi Biotec), FcERIA (AER-37,
eBioscience), CCR3 (5E8, Biolegend), CD203c (97A6, Beckman Coulter),
CD123 (6H6, eBioscience), CD14 (61D3, eBioscience), CD16 (3G8,
Biolegend), HLA-DR (L243, BD Biosciences), CD1c (L161, BD Biosciences).
The cells were acquired on LSRFortessa\textsuperscript{TM} cell analyzer
(BD) and analysed using FlowJo v10 (BD)\textbf{.} Flow cytometry data on
PBMCs were generated newly for this study by using frozen PBMC samples
of the SSIC cohort. Cells were thawed using pre-warmed RPMI medium (Life
Technologies). Dead cells were discriminated by staining PBMCs with
LIVE/DEAD Fixable Blue Dead cell stain kit (Life Technologies).~ The
cells were then washed using MACS buffer (0.5\% BSA, 2 mM EDTA in PBS)
and stained using the following antibodies:~ Anti-CD49d (clone 9F10,
Biolegend), Anti-CD45RB (clone MEM-55, Immunotools), Anti-CD3 (clone
UCHT1, BD Biosciences), Anti-CD45RO (clone UCHL1, Biolegend), Anti-CD161
(clone HP-3G10, Biolegend), Anti-CRTH2 (clone BM16, BD Bioscience),
Anti-CD4 (clone RPA-T4, BD Biosciences), Anti-CD27 (clone O323,
Biolegend) and Anti-CD38 (clone HB7, BD Biosciences; O323). The cells
were acquired on LSR II 5 lasers flow cytometer (BD) and analysis was
performed using FlowJo v10 (BD) and unsupervised cluster analysis tools
(see below).

\textbf{Plasma cytokine quantification}

The plasma levels of IL-5, IL-13, IL-6, IL-17A and TNF[?] were quantified
using Quanterix Single Molecule-Arrays (SiMoA) analyser using the
Simoa[?] IL-5 Advantage Kit, Simoa[?] IL-13 Advantage Kit and Simoa[?]
Cytokine 3-Plex B Advantage Kit respectively following the
manufacturer's protocol.

\textbf{Detection of cytokine secretion by flow cytometry}

Frozen cells were~thawed using RPMI 1640 Medium (Gibco), supplemented
with 10\% FBS~(BioWhittaker)~and~washed with homemade 1X MACS buffer (1X
PBS + 0.5\% BSA + 2mM EDTA). Cells were then pre-stained for 15
minutes~at~37\textsuperscript{o}C with~5\%
CO\textsubscript{2}~using~the~following antibodies: anti-CD294 (clone
BM16,~BD Pharmingen)~and~anti-CD45RB~(clone MEM-55,~ImmunoTools). Cells
were washed with~1X MACS buffer~and~then stimulated for 4 hours
at~37\textsuperscript{o}C with 5\%
CO\textsubscript{2}~with~20ng/ml~Phorbol myristate acetate (PMA)
(Sigma-Aldrich),~1\selectlanguage{greek}µ\selectlanguage{english}M~Ionomycin calcium
salt~(Sigma-Aldrich)~and~GolgiPlug~(BD Biosciences).

After 4 hours of stimulation, cells were washed with 1X PBS (Gibco)
and~stained with LIVE/DEAD Fixable Aqua Dead Cell Stain Kit (Invitrogen)
for 10 minutes~at room temperature.~Cells were then washed~with 1X MACS
buffer~and stained~for 15 minutes at 4\textsuperscript{o}C~using the
following antibodies:~anti-CD161~(clone HP-3G10,~eBioscience).
Intracellular staining was performed using the BD~Cytofix/Cytoperm~Kit
(BD Biosciences) according to the manufacturer's instructions.
Cells~were fixed with Fixation/Permeabilization solution (BD
Biosciences) for 20 minutes at~4\textsuperscript{o}C. Cells were washed
and kept in 1X MACS buffer overnight~at 4\textsuperscript{o}C. On the
next day, cells were permeabilized with~1X~Perm/Wash buffer for 15
minutes~at~4\textsuperscript{o}C and stained~with the following
antibodies:~ anti-CD3 (clone UCHT1,~BD Pharmingen),~anti-CD4 (clone
RPA-T4,~BD Pharmingen) and anti-IL-5 (clone TRFK5,~BioLegend).~After 30
minutes, cells were washed with 1X~Perm/Wash~buffer and resuspended in
1X MACS buffer. Samples were acquired~using~BD LSR~II flow cytometer and
analysed using FlowJo v10 (BD).

\textbf{Functional analysis of stimulated PBMC by mass cytometry}

All antibodies used in the study were labelled in house with metal tags.
Purified antibodies for mass cytometry were obtained in
carrier/protein-free buffer and coupled to lanthanide metals using the
MaxPar DN3 antibody conjugation kit (Fluidigm Inc.) according to the
manufacturer's recommendations. Upon conjugation, the yield of recovered
antibody was determined by measurement of absorbance at 280~nm on a
nanodrop before dilution of the antibodies in Candor PBS Antibody
Stabilization solution (Candor Bioscience, Germany) for long-term
storage at 4\selectlanguage{ngerman}°C. Antibodies used are listed in~\textbf{Supplementary
Table 1} . In order to capture the phenotype of resting cells, most of
the surface markers were stained prior to the stimulation. Frozen PBMCs
were~thawed using RPMI 1640 Medium (Gibco), supplemented with 10\%
FBS~(BioWhittaker)~and~washed with homemade 1X MACS buffer. Cells were
resuspended in pre-stimulation antibody cocktail and incubated for 30
minutes on ice. Cells were washed with CyFACS buffer (PBS with 4\% FBS,
0.05\% sodium azide) and transferred to a 6-well plate for stimulation.
The cells were stimulated using the PMA/Ionomycin cocktail described
earlier and incubated for 4 hours in a 37°C incubator. The cells were
then transferred into a 96-well U bottom plate and washed with PBS,
followed by post-stimulation surface antibody cocktail and incubation of
30 minutes at 37°C. Subsequently, cells were washed with CyFACS buffer
and resuspended with the post-stimulation antibody cocktail and
incubated for 30 minutes on ice. Cells were washed twice with CyFACS
buffer and then treated with Cisplatin for 5 minutes on ice. Following
double washes with CyFACS buffer and fixation overnight using 2\% PFA,
cells were permeabilized and stained with intracellular antibody
cocktail for 30 minutes on ice. Washes were then carried out with
permeabilization buffer followed by barcoding. Lastly, cells were
stained with DNA intercalator (Cell-ID Intercalator-Ir, Fluidigm) in PBS
for 20~mins at room temperature. After washing twice with CyFACS buffer,
cells were washed with MiliQ water and filtered through a cell strainer
snap cap tube in preparation of CyTOF acquisition. Cells were then
diluted to 0.5 × 10\textsuperscript{6}~cells/mL in MiliQ water
containing 2\% EQ\selectlanguage{english} Four Element Calibration Beads (Fluidigm). Cells were
acquired using Helios mass cytometer at a rate of 280-350 cells/s on
CyTOF software version 7.0.5189 and analysed using FlowJo v10 (BD).

\textbf{Statistical Analysis}

Flow cytometry, mass cytometry and plasma cytokine data analysis were
done using non-parametric methods in R and GraphPad Prism (Dotmatics).
Correlation of two continuous variables was performed using Spearman
Rank correlation while comparison of continuous variables against binary
categorical variables was done using Mann-Whitney U tests. PhenoGraph
and UMAP analysis were done in R using the
Cytofkit2\textsuperscript{14}{[}18{]}. P values less than 0.05 were
deemed to be statistically significant.

PhenoGraph and cluster analysis was performed using Cytofkit2 {[}18{]}
followed by statistical analysis using Graphpad Prism (Dotmatics).

\textbf{RESULTS}

\textbf{Transcriptomics highlight eosinophils and TH2 as disease-driving
cells in AR}

We assessed whole blood gene expression comparing AR and non-AR
individuals from our previously described SSIC cohort using whole
transcriptomic sequencing (\textbf{Supplementary Table 2A} ). A total of
1160 unique probes associated to 1095 unique genes were differentially
expressed at a nominal significance level of 0.05. A total of 23 probes
representing 20 unique gene transcripts were robust after stringent
correction for multiple testing at a false discovery rate (FDR) p-value
of 0.05, with all transcripts upregulated in AR (\textbf{Table 1A} ).
Given that atopy is well known to be associated with eosinophil levels,
sensitivity analysis with adjustment for eosinophil counts was
performed, with all identified differentially expressed genes (DEGs)
remaining significant post adjustment. To account for ethnicity and
environmental influences on atopic gene expression, we validated our
findings in BAMSE population-based cohort comprising of Swedish
adolescents (\textbf{Table 1B} ). Out of 20 DEGs identified in the SSIC
cohort, 11 DEGs were replicated and reached significance in BAMSE,
confirming the transferability of our findings irrespective of ethnicity
and environmental differences (\textbf{Table 1B} ).

For top DEGs that reached nominal significance in the SSIC cohort, we
interrogated for biological function and performed Ingenuity Pathway
Analysis (IPA). In the disease and disorders category, hypersensitivity
and inflammatory responses were significantly associated with nominal
AR-related DEGs (\textbf{Table 2A} ). Top pathways enriched for
hypersensitivity and inflammatory responses included cell-to-cell
signalling and haematological system and cell-mediated immune response
(\textbf{Table 2B, C} ). Importantly, we observed strong functional
enrichment for eosinophils, along with basophils and mast cells, in
hypersensitivity responses associated with AR (\textbf{Table 2B} ).
Similarly, functional activation of TH2 and myeloid cells were
highlighted to drive inflammatory responses in AR (\textbf{Table 2C)} .
Consistent with current understanding, transcriptomic findings emphasise
eosinophils and TH2 cells as key drivers of AR.

\textbf{Blood eosinophilia and eosinophilic inflammation correlates
strongly with AR}

In order to identify the cellular drivers of airway inflammation in AR,
we took a deeper look into the SSIC cohort. {[}10, 11{]} Using flow
cytometry data from whole blood analysis, we performed unsupervised
PhenoGraph clustering of whole blood subsets and correlated them with
atopy status (\textbf{Figure 1A-C} and \textbf{Supplementary Table 3} ).
Of all cell subsets, eosinophils were identified as the only leukocyte
cluster directly associated with atopy (\textbf{Figure 1B} and
\textbf{C} ). Atopic individuals were demonstrated to have higher
frequencies of eosinophils than individuals without atopy
(\textbf{Supplementary Figure 1A} ). Following this, we did a
correlation analysis of the symptoms of AR with eosinophil counts. While
atopy status was defined objectively by SPT, assessment of AR
manifestation and symptoms for SSIC cohort was based on a survey
questionnaire. {[}11{]} Despite the subjective nature of these
self-reported parameters, we observed strong associations between
eosinophils and AR, where AR cases registered significantly higher
eosinophil frequencies than non-AR controls (\textbf{Figure} \textbf{1D}
). The same trend was observed for total IgE levels (\textbf{Figure 1E}
).

\textbf{CD161+ TH2 plays a role in driving eosinophilic inflammation in
AR}

In order to identify other atopy and AR-related subsets within lymphoid
and myeloid populations, a flow cytometry panel was specifically
designed for the detection of allergy-related PBMC subsets. {[}13{]} In
contrast to whole blood analysis, PBMC clusters demonstrated
non-significant associations with atopy and AR (\textbf{Supplementary
Figure 2} ). Given that TH2 was earlier identified as a disease-driving
subset by transcriptomic sequencing, we gated for chemoattractant
receptor homologue on TH2 (CRTH2+) positive cells to further enrich for
key PBMC subsets with roles in disease progression of AR. CRTH2 is
expressed by a small fraction (approximately 1.6\%) of the PBMC
population (\textbf{Figure 2A} ) and is typically expressed on
TH2-associated immune cells such as TH2 and ILC2. {[}19{]} In line with
transcriptomic analysis, \emph{PTGDR2} (gene encoding CRTH2) was also
differentially expressed between non-AR and AR individuals
(\textbf{Table 1} ).

UMAP analysis segregated the entire CRTH2+ population into five distinct
clusters representing basophils, TH2, ILC2, TC2 and non-classical
monocytes (\textbf{Figure 2B} ). PhenoGraph clustering subdivided these
five main clusters into 28 distinct subpopulations
(K1-K28;\textbf{Supplementary Figure 3} ). While all CRTH2+ subsets are
reportedly involved in allergy and allergic diseases, cluster `K9' is
highlighted here as the sole subset directly associated with atopy
(\textbf{Figure 2C} ). Cluster `K9' (CD161+ TH2) is a TH2A-like subset
{[}13{]} located within the TH2 cluster (\textbf{Figure 2D} and
\textbf{Supplementary Figure 3} ). Next, we interrogated CD161+ TH2 for
associations with AR. Similar to eosinophils, frequency of CD161+ TH2 is
significantly associated with both atopy and AR (\textbf{Supplementary
Figure 1B} and \textbf{Figure 2E} ). Furthermore, we observed a positive
correlation between the frequencies of CD161+ TH2 and eosinophils
(\textbf{Figure 2F} ). Likewise, frequency of CD161+ TH2 is also
positively correlated to titres of total IgE (\textbf{Figure 2G} ).
Taken together, CD161+ TH2 cells may represent a key cellular subset
driving atopy and airway inflammation in AR.

\textbf{CD45RB\textsuperscript{lo} CD161+ TH2 promotes IL-5 production
and disease progression}

As cellular phenotype is crucial to functional characteristics, we
further refined the phenotype of the CD161+ TH2 subset driving AR. Of
particular interest is the activation status of this cellular subset.
Interestingly, surface expression of marker CD45RB was significantly
downregulated on CD161+ TH2 cells of AR individuals compared to non-AR
individuals, indicative of memory and differentiation characteristics
(\textbf{Figure 3A} ).

To assess the inflammatory profile of AR, we quantified IL-5, IL-13,
IL-17A, IL-6 and TNF\selectlanguage{greek}α \selectlanguage{english}plasma levels by ultra-sensitive SiMoA array. AR
cases had significantly elevated plasma IL-5 levels as compared to
non-AR cases, which confirmed Type 2 inflammation in AR (\textbf{Figure
3B} and \textbf{Supplementary Figure 4} ). As the key survival factor of
eosinophils, IL-5 plays a pivotal role in eosinophilic allergic
diseases. {[}20-23{]} Given that TH2A and pe-TH2 populations were
previously reported to be major producers of IL-5, {[}13, 24{]} we
probed for IL-5 secretion in AR-relevant CD161+ TH2 subset.
Interestingly, high circulatory plasma IL-5 levels were only observed in
individuals with low CD45RB (CD45RB\textsuperscript{lo}) expression on
CD161+ TH2 cells (\textbf{Figure 3C} ), suggesting that
CD45RB\textsuperscript{lo} CD161+ TH2 could be responsible for IL-5
secretion. To clarify the cell subsets responsible for IL-5 secretion,
PBMCs were stimulated with PMA and Ionomycin, and respective cytokine
secretion was analysed using flow cytometry. As stimulation results in
an upregulation of CD45RB, PBMCs were pre-stained with surface markers
(including CD45RB) prior to activation so that steady state phenotype
could be preserved. IL-5 expression was then quantified by intracellular
staining following stimulation. While we note a small population of IL-5
secreting conventional CD161- TH2 (cTH2), IL-5 secretion was
significantly elevated in CD161+ TH2 cells (\textbf{Figure 3D} and
\textbf{E} ). Strikingly, IL-5 secretion was exclusively found within
the CD45RB\textsuperscript{lo} subset in both cTH2 and CD161+ TH2
(\textbf{Figure 3E} ). These findings confirm
CD45RB\textsuperscript{lo}CD161+ TH2 as the main producers of IL-5.

Importantly, the proportion of IL-5 producing
CD45RB\textsuperscript{lo}CD161+ TH2 cells was significantly elevated in
AR as compared to non-AR (\textbf{Figure 3F} ). In contrast, there was
no significant difference in the proportion of IL-5 producing
CD45RB\textsuperscript{lo} cTH2 between the non-AR and AR individuals.
Taken together, these results suggest a role for IL-5 producing
CD45RB\textsuperscript{lo} CD161+ TH2 cells in the pathogenesis of AR.

\textbf{CD45RB\textsuperscript{lo} CD161+TH2 is the central pathogenic
cell type in active disease}

As allergic manifestation in the aforementioned SSIC cohort were based
on self-reported historical symptoms and is susceptible to recall bias,
we therefore validated our findings in a second paediatric cohort with
clinically diagnosed active AR manifestations (\textbf{Supplementary
Table 2B} ). As expected, there are significantly higher levels of
eosinophils and CD161+ TH2 observed in AR cases, thus confirming
eosinophilic inflammation in active AR (\textbf{Figure 4A, B} ). In
order to obtain a wide comprehensive phenotypic outlook of the
disease-driving CD161+ TH2 subset, an extended 40plex mass cytometry
allergy panel was designed to include antibodies specific for
inflammatory cytokines and activation markers such as IL-2, IL-3, IL-4,
IL-5, IL-9, IL-13, IL-17A, IL-22, IFN-\selectlanguage{greek}γ, \selectlanguage{english}TNF-\selectlanguage{greek}α \selectlanguage{english}and HPGDS {[}12{]}
(\textbf{Supplementary Table 1} ). As the stimulation required to induce
cytokine production triggers major shifts in the expression of surface
markers, most of the lineage and surface markers (including CD45RB) were
stained prior to stimulation, which enabled depiction of the
actual\emph{ex vivo} cellular phenotype.

Mass cytometry of PBMCs with the expanded 40-marker panel revealed all
key populations as defined previously with the narrower FACS panel but
at much higher granularity. Consistent with observations in the SSIC
cohort (\textbf{Figure 3F} ), a significantly higher proportion of IL-5
producing CD45RB\textsuperscript{lo} CD161+ TH2 was found in individuals
with active AR compared to non-AR controls (\textbf{Figure 4C} ). This
trend was not observed in CD161- cTH2.

To confirm our earlier observations in the SSIC cohort, we gated for
CRTH2+ CD161+ cells and performed supervised phonograph clustering. A
total of 9 sub-populations were segregated from the CD161+ TH2 subset
(\textbf{Figure 4D} and \textbf{E} ). Of all sub-populations, Cluster 3
was found to be significantly increased in individuals with active AR
(\textbf{Figure} \textbf{4F, G} and \textbf{Supplementary Table 5} ).

In line with expectations, `Cluster 3' is indeed an IL-5 secreting
CD45RB\textsuperscript{lo} population (\textbf{Figure 5A} ). Moreover,
this cluster appeared to be a highly differentiated population of mature
CD161+ TH2 cells with an activated phenotype characterized by low
expression of CD27, CD45RB, KLRG1 and high expression of CD45RO, HPGDS,
ICOS, and CD38. The cytokine profile suggests that in addition to IL-5
production, this population also secretes a multitude of cytokines that
includes IL-2, IL-3, IL-4, IL-9 and IL-13. Taking a deeper look, we
further confirmed that cytokine secretion is highly correlative
(\textbf{Figure 5B} ). Thus, the severity of eosinophilic airway
allergies such as AR seems to be driven by an activated terminally
differentiated CD161+ TH2 subset that is able to concomitantly secrete a
complex set of inflammatory cytokines.

\textbf{DISCUSSION}

There has been growing evidence of heterogeneity within the human TH2
subsets discovered over the years. {[}12, 13, 25{]} Prussian and
colleagues first reported high levels of IL-5+ producing TH2 subset in
patients with allergic eosinophilic gastroenteritis. {[}12{]} This
population was named 'peTH2' and was defined by their expression of
HPGDS and CD161. {[}12{]} In parallel, the importance of IL-5 producing
TH2 subset was further confirmed in mouse models of allergic airway
inflammation and atopic dermatitis. {[}26, 27{]} Wambre et al defined a
subpopulation of human allergen-specific TH2 subset which they coined as
TH2A. {[}13{]} TH2A was identified as a memory subset that is
over-represented in allergic individuals and secretes IL-5, IL-4 and
IL-13 in response to stimulation. {[}13{]} As different cell markers
were used across different groups to identify the subsets, this raises
the question whether the identified TH2 populations pertinent for
allergic diseases across these studies were homogenous.

In this study, we used unsupervised clustering tools (UMAP and
PhenoGraph) on CRTH2+ PBMCs and identified a TH2A-like subset that
correlated directly to the markers of atopy. A common feature between
the different TH2 subsets reported in literature was the production of
IL-5. {[}13, 19, 27{]} Similarly, we were also able to detect IL-5 in
our identified CD161+ TH2 subset. Strikingly, IL-5 production was only
limited to the CD45RB\textsuperscript{lo} T cell population. As
CD45RB\textsuperscript{lo} T cells are typically terminally
differentiated memory cells, this suggests a need for repetitive antigen
stimulation before CD161+ TH2 subsets are capable of IL-5 secretion.
This is supported the studies by Upadhyaya et al. and Islam et al, who
found that the ability of TH2 cells to secrete IL-5 requires multiple
rounds of \emph{in vitro} stimulation. {[}25, 27{]} Similar requirements
for repeated allergen exposure is needed to polarize IL-5 producing TH2
cells.

Intriguingly, CD45RB\textsuperscript{lo}CD161+ TH2 population was found
to be directly correlated to AR in both cohorts with active and
self-reported AR. Not only does this show the persistence of the
CD45RB\textsuperscript{lo}CD161+ TH2 population, it also implies the
pertinence of this population in the pathogenesis of AR and possibly
other allergic diseases. Both SSIC and active AR cohorts described in
this study were collected in Singapore, whereby majority of the
individuals are sensitized against HDM. {[}10{]} HDM is a perennial
allergen in tropical nations such as Singapore, thus T cells in atopic
individuals undergo constant stimulation. {[}11{]} This could explain
the strong association observed between CD45RB expression on CD161+ TH2
cells and atopy markers despite the fact that not all subjects
demonstrated active AR symptoms during the collection of SSIC cohort.

A high dimensional 40-marker panel was used to further characterize the
CD161+ TH2 population. As mentioned previously, pre-staining of cell
surface markers was performed prior to stimulation in order to preserve
the steady state cell identities. We identified a specific subset within
the CD161+ TH2 population that associated strongly with AR. Other than
exhibiting a terminally differentiated phenotype (defined by low
expression of CD27 and CD45RB with concomitant high expression of CD45RO
and ICOS) with intracellular expression of HPGDS, this subset was also
able to secrete multiple cytokines upon stimulation. Amongst several
others, this included allergy related cytokines such as IL-5, IL-4 and
IL-13. Taken together, our current study unifies the markers previously
reported for allergic-specific TH2 subsets and provides clarity for the
pathogenic TH2 subset previously reported in different allergic
diseases. The persistence of CD45RB\textsuperscript{lo} CD161+ TH2 may
allow for public health surveillance of allergic individuals. Moreover,
these cells may also be leveraged as a biomarker for the effectiveness
of immunotherapy as well as a potential disease target in the treatment
of AR and allergic diseases.

\textbf{Acknowledgements}

We would like to thank volunteers and patients for their participation
in this study. We would also like to express our thanks to the
immunogenomics, CyTOF and flow cytometry platforms at Singapore
Immunology Network.

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\textbf{Table 1. Differential gene expression (DEGs) comparison between
non-AR and AR from whole blood samples in (A) SSIC and (B) BAMSE
cohorts}\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
\textbf{A) Differentially Expressed Genes (DEGs) for AR from SSIC} &
\textbf{A) Differentially Expressed Genes (DEGs) for AR from SSIC} &
\textbf{A) Differentially Expressed Genes (DEGs) for AR from SSIC} &
\textbf{A) Differentially Expressed Genes (DEGs) for AR from SSIC} &
\textbf{A) Differentially Expressed Genes (DEGs) for AR from
SSIC}\tabularnewline
\textbf{Gene} & \textbf{logFC} & \textbf{Avg\_Expr} & \textbf{P-value} &
\textbf{P.eosadj}\tabularnewline
\emph{IL5RA} & 0.475 & 13.46 & 4.01E-07 & 4.04E-05\tabularnewline
\emph{PYROXD2} & 0.202 & 12.48 & 2.72E-06 & 7.11E-05\tabularnewline
\emph{SIGLEC8} & 0.575 & 11.92 & 2.22E-07 & 2.25E-04\tabularnewline
\emph{THBS4} & 0.390 & 8.93 & 2.43E-05 & 2.64E-04\tabularnewline
\emph{ALOX15} & 0.526 & 8.95 & 4.59E-07 & 3.49E-04\tabularnewline
& 0.411 & 12.53 & 9.78E-06 & 8.25E-04\tabularnewline
\emph{OLIG2} & 0.614 & 9.61 & 1.16E-06 & 5.45E-04\tabularnewline
\emph{ADGRE4P} & 0.411 & 11.97 & 1.16E-05 & 5.75E-04\tabularnewline
\emph{CLC} & 0.189 & 14.8 & 1.29E-05 & 1.06E-03\tabularnewline
\emph{LINC00323} & 0.422 & 7.68 & 1.98E-06 & 1.23E-03\tabularnewline
\emph{CCL23} & 0.678 & 9.95 & 1.30E-05 & 2.24E-03\tabularnewline
& 0.604 & 11.95 & 7.57E-06 & 1.33E-02\tabularnewline
\emph{HES1} & 0.356 & 10.84 & 2.95E-06 & 2.42E-03\tabularnewline
\emph{SMPD3} & 0.356 & 9.89 & 1.74E-06 & 4.53E-03\tabularnewline
\emph{HRASLS5} & 0.367 & 8.07 & 9.05E-06 & 5.51E-03\tabularnewline
\emph{PRSS33} & 0.595 & 10.22 & 2.59E-05 & 1.05E-02\tabularnewline
\emph{SLC29A1} & 0.411 & 12.47 & 3.63E-05 & 1.19E-02\tabularnewline
& 0.275 & 13.29 & 3.30E-05 & 3.32E-02\tabularnewline
\emph{TFF3} & 0.614 & 10.03 & 8.55E-06 & 1.68E-02\tabularnewline
\emph{PTGDR2} & 0.401 & 11.96 & 3.57E-05 & 1.78E-02\tabularnewline
\emph{IL17RB} & 0.345 & 8.92 & 3.49E-05 & 1.90E-02\tabularnewline
\emph{P2RY2} & 0.310 & 9.24 & 1.47E-05 & 2.58E-02\tabularnewline
\emph{RASL11B} & -0.286 & 8.39 & 8.70E-06 & 2.88E-02\tabularnewline
\textbf{B) DEGs for AR replicated in BAMSE} & \textbf{B) DEGs for AR
replicated in BAMSE} & \textbf{B) DEGs for AR replicated in BAMSE} &
\textbf{B) DEGs for AR replicated in BAMSE} & \textbf{B) DEGs for AR
replicated in BAMSE}\tabularnewline
\textbf{Gene} & \textbf{logFC} & \textbf{AveExpr} & \textbf{P-value} &
\textbf{P.eosadj}\tabularnewline
\emph{SLC29A1} & 0.125 & 5.496 & 6.23E-06 & 9.97E-05\tabularnewline
\emph{IL5RA} & 0.366 & 5.142 & 6.26E-05 & 4.27E-04\tabularnewline
\emph{ALOX15} & 0.313 & 5.401 & 8.64E-05 & 4.27E-04\tabularnewline
\emph{SMPD3} & 0.137 & 5.424 & 1.07E-04 & 4.27E-04\tabularnewline
\emph{CLC} & 0.415 & 5.688 & 2.13E-04 & 6.82E-04\tabularnewline
\emph{HRASLS5} & 0.109 & 4.045 & 1.16E-03 & 2.70E-03\tabularnewline
\emph{SIGLEC8} & 0.148 & 4.851 & 1.18E-03 & 2.70E-03\tabularnewline
\emph{OLIG2} & 0.085 & 4.792 & 1.87E-03 & 3.74E-03\tabularnewline
\emph{P2RY2} & 0.09 & 5.772 & 4.72E-03 & 8.39E-03\tabularnewline
\emph{PRSS33} & 0.069 & 5.589 & 8.99E-03 & 1.44E-02\tabularnewline
\emph{HES1} & 0.058 & 3.107 & 1.46E-02 & 2.12E-02\tabularnewline
\bottomrule
\end{longtable}

\textbf{logFC} - logarithm base 2 of fold change effect size for AR
phenotype; \textbf{Avg\_Expr} - mean expression across all
samples;\textbf{P-value} -- False discovery rate (FDR) corrected p-value
of gene expression to AR; \textbf{P.eosadj -} P-value for AR after
correcting for eosinophil percentages. In the case of \emph{ALOX15} ,
\emph{CCL23}and \emph{SLC29A1} , there were dual probes present that
tagged to the same gene where expression values of both probes achieved
FDR-significance.

\textbf{Table 2: Ingenuity Pathway Analysis for nominally significant
AR-related DEGs from the SSIC cohort.}\selectlanguage{english}
\begin{longtable}[]{@{}lll@{}}
\toprule
\textbf{(A) Enrichment for AR candidates for diseases and disorders} &
\textbf{(A) Enrichment for AR candidates for diseases and disorders} &
\textbf{(A) Enrichment for AR candidates for diseases and
disorders}\tabularnewline
\textbf{Diseases and Disorders} & \textbf{P-value} & \textbf{Number of
genes}\tabularnewline
Hypersensitivity response & 1.98E-05 -- 4.08E-02 & 5\tabularnewline
Inflammatory response & 1.98E-05 -- 4.99E-02 & 10\tabularnewline
Haematological disease & 2.27E-04 -- 4.26E-02 & 4\tabularnewline
Immunological disease & 2.27E-04 -- 1.69E-02 & 5\tabularnewline
Cancer & 1.17E-03 -- 4.32E-02 & 34\tabularnewline
\bottomrule
\end{longtable}

\textbf{(B) Significant terms enriched in the hypersensitivity response}\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
\textbf{Categories} & \textbf{Function} & \textbf{P-value} &
\textbf{Gene Symbol}\tabularnewline
Cell-to-Cell Signalling & Activation of eosinophils & 1.98E-05 & IL1RL1,
IL5RA, PTGDR2\tabularnewline
Haematological system & Quantity of eosinophils & 6.25E-05 & IL1RL1,
IL5RA, PTGDR2, SIGLEC8\tabularnewline
Cellular movement & Infiltration by eosinophils & 2.68E-04 & IL1RL1,
PTGDR2, SIGLEC8\tabularnewline
Cell-to-Cell Signalling & Response of eosinophils & 3.60E-04 & IL1RL1,
IL5RA\tabularnewline
Cellular function and movement & Function of eosinophils & 3.72E-03 &
IL1RL1, SIGLEC8\tabularnewline
Cellular function \& haematological system & Infiltration by basophils &
3.78E-03 & IL1RL1, PTGDR2\tabularnewline
Hypersensitivity Response & Tolerization of mast cells & 3.78E-03 &
PTGDR2\tabularnewline
Cell-to-Cell Signalling & Inflammation of eosinophils & 1.13E-02 &
IL1RL1\tabularnewline
\bottomrule
\end{longtable}\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\textbf{(C) Significant terms enriched in the inflammatory
response}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\textbf{(C) Significant terms enriched in the inflammatory
response}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\textbf{(C) Significant terms enriched in the inflammatory
response}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\textbf{(C) Significant terms enriched in the inflammatory
response}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\textbf{Categories}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\textbf{Function}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\textbf{P-value}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\textbf{Gene Symbol}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Cell-to-Cell Signalling\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Activation of Th2 cells\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
3.60E-04\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
IL1RL1, PTGDR2\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Cell-mediated immune response\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Chemotaxis of T lymphocytes\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
1.48E-02\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
CCL23, PTGDR2\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
Cellular movement\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
Leukocyte migration\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
1.93E-02\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
ALOX15, CCL23, IL1RL1, THBS4, SIGLEC8, PTGDR2\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Cell-to-Cell Signalling\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Activation of myeloid cells\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
9.52E-04\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
IL1RL1, IL34, IL5RA, PTGDR2, SIGLEC8\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

A total of 1160 unique probes with nominal P-value \textless{}0.05
associated with 1095 unique genes were evaluated with IPA analysis.
P-value for each category is reported. (A) Diseases and disorders
enriched in DEG candidates from Table 1A. Top pathways enriched in the
(B) hypersensitivity and (C) inflammatory response from the enrichment
candidates in (A).

\emph{Figure Legends}

\textbf{Figure 1. Eosinophilic allergic rhinitis (AR) in SSIC cohort is
associated with high levels of HDM-specific IgE} Whole blood leukocytes
from SSIC cohort were stained and analysed with flow
cytometry.\textbf{(A)} Representative scatterplot showing lymphocytes
(green), monocytes (red) and granulocytes (blue) subsets in whole blood
(n=216) and these subsets are analysed using unsupervised phenograph
clustering and umap dimensionality reduction. \textbf{(B)} Umap clusters
were annotated based on their lineage markers and \textbf{(C)}
associated with atopy phenotype. P-value of the respective cluster was
presented as blue/red shading based on statistical analysis. Red denotes
direct correlation while blue denotes negative correlation. Scatter
plots comparing \textbf{(D)} percentage of eosinophils in total
leukocytes and\textbf{(E)} total plasma immunoglobulin E (IgE) between
non-AR and AR individuals. Spearman correlation was performed in
\textbf{Figure 1C}while pairwise two-tailed Mann-Whitney \emph{U} test
was performed in\textbf{Figure 1D-H} . A p-value of less than 0.05 is
considered statistically significant. (\emph{**p\textless{}0.01,
***p\textless{}0.001} )

\textbf{Figure 2. CD161+ CD4+ TH2 cells are associated with AR.} PBMCs
of SSIC individuals were stained and analysed using flow
cytometry.\textbf{(A)} CRTH2+ subsets from PBMCs (n=216) were gated and
used for analysis by phenograph clustering and umap dimensionality
reduction.\textbf{(B)} Umap clusters were annotated based on lineage
markers and associated with \textbf{(C)} atopy phenotype. Statistical
analysis was performed using Wilcoxon rank sum test. Umap clusters were
shaded red according to statistical significance. \textbf{(D)}
Representative scatterplot showing CD4 and CD161 expression on cluster
K9 (derived from umap cluster in (C)) overlaid on total CRTH2+ PBMCs.
Number in the plot refers to the representative percentage of cluster K9
of all CRTH2+ PBMCs. \textbf{(E)} Scatter plot comparing the numbers of
peripheral CD161+ TH2 cells between non-AR and AR individuals.
Two-tailed Mann-Whitney \emph{U} test was performed. Association of
peripheral CD161+ TH2 numbers with \textbf{(F)} whole blood eosinophil
numbers and\textbf{(G)} total plasma IgE. Non-atopic individuals were
shaded in grey while atopic individuals were shaded in black.
Statistical analysis was performed using Spearman correlation. P-value
of less than 0.05 is considered statistically significant.
(\emph{**p\textless{}0.01, ***p\textless{}0.001} )

\textbf{Figure 3. CD45RB\textsuperscript{lo}CD161+ TH2 subset produces
high level of IL-5 and are associated with AR.} PBMCs of SSIC
individuals were stained and analysed using flow cytometry.
\textbf{(A)}Scatterplots of CD45RB log mean fluorescence intensity (MFI)
on CD161+ TH2 comparing between non-AR and AR individuals.
\textbf{(B)}Scatterplot comparing plasma IL-5 level between non-AR and
AR in SSIC individuals. Two-tailed Mann-Whitney \emph{U} test was
performed.\textbf{(C)} Scatterplot showing association of plasma IL-5
levels against CD45RB MFI on CD161+ TH2. PBMCs were pre-stained with
CD45RB and stimulated using PMA/ionomycin. Intracellular staining was
performed to determine IL-5 production using flow cytometry.
\textbf{(D)} Paired analysis of IL-5 MFI on CD161- or CD161+ TH2 cells
from non-AR or AR individuals. Wilcoxon paired analysis was performed.
\textbf{(E)}Representative scatterplots showing expression of IL-5 and
CD45RB in CD161- TH2 (cTH2) and CD161+ TH2 subsets. Numbers in quadrant
represents percentage of cells in each quadrant of the plot.
\textbf{(F)}Scatterplot showing association of
CD45RB\textsuperscript{lo}IL-5+ cTH2 or CD161+ TH2 in non-AR or AR
individuals. Statistical analysis was performed using one-way ANOVA
followed by Tukey post test. P-values less than 0.05 are considered
statistically significant. (\emph{**p\textless{}0.01,
***p\textless{}0.001} )

\textbf{Figure 4. CD45RB\textsuperscript{lo}CD161+ TH2 subset is
associated with active AR manifestation.} Whole blood leukocytes from
the pediatric cohort were stained and analysed with flow cytometry.
Scatterplots comparing the percentage of \textbf{(A)} eosinophils
and\textbf{(B)} CD161+ TH2 between non-AR and AR individuals.
Statistical analysis was performed using two-tailed Mann-Whitney
\emph{U} test. PBMCs were pre-stained with cell surface markers and
stimulated using PMA/ionomycin. Intracellular staining was performed to
determine cytokine production using CyTOF. \textbf{(C)} Scatterplot
showing association of CD45RB\textsuperscript{lo}IL-5+ cTH2 or CD161+
TH2 in non-AR or AR individuals. \textbf{(D)} Representative scatterplot
showing gating of CD161+ TH2 from total CD4+ T cells to be used for umap
cluster analysis in \textbf{(E)} . CD161+ TH2 cells were gated,
downsampled to 200 cells per sample and analysed using unsupervised
phenograph clustering with 38 markers. \textbf{(E)} Umap dimensionality
reduction was performed and cells were segregated into different
clusters. Numbers in the plot represent cluster numbers.
\textbf{(F)}Scatterplot comparing percentage of cluster 3 (derived
from\textbf{(E)} ) between non-AR and AR individuals. Statistical
analysis was performed using two-tailed Mann-Whitney \emph{U} test.
P-value of less than 0.05 is considered statistically significant.
(\emph{*p\textless{}0.05} ) \textbf{(G)} Umap scatterplot showing the
distribution of cluster 3 (in red) in concatenated non-AR (n=6) and AR
(n=14) samples respectively.

\textbf{Figure 5. AR-associated CD45RB\textsuperscript{lo}CD161+ TH2
subset secreting diverse range allergy-related cytokines (A)} Heatmap
showing marker and cytokine expression on the different clusters derived
from Figure 4E . \textbf{(B)} Scatterplots showing expression of
hematopoietic prostaglandin D synthase (HPGDS), CD45RB, IL-5, IL-4 and
IL-13 on cluster 3 overlaid on total CD161+ TH2.

\emph{Supplementary figure and tables legends}

\textbf{Supplementary Figure 1. Scatterplots comparing percentage (A)
eosinophils and CD161+ TH2 on Non-atopic and atopic individuals in SSIC
cohort}

\textbf{Supplementary Figure 2. Umap clustering of PBMCs from SSIC
cohort and the association to atopy.} Representative scatterplot showing
representative PBMCs population. PBMCs from SSIC cohort (n=216) were
analysed using unsupervised phenograph clustering and umap
dimensionality reduction. Umap clusters were annotated based on their
lineage markers and associated with atopy phenotype.

\textbf{Supplementary Figure 3. Heatmap showing phenograph cluster K1-28
and their associated markers}

\textbf{Supplementary Figure 4. Quantification of plasma (A) IL-13, (B)
IL-17A, (C) IL-6 and (D) TNF? in SSIC cohort individuals}

\textbf{Supplementary Table 1. List of CyTOF antibodies used for surface
and intracellular staining}

\textbf{Supplementary Table 2. Demographic table of SSIC and Pediatric
cohort}

\textbf{Supplementary Table 3. Association of umap clusters from SSIC
CRTH2+ PBMCs to atopy}

\textbf{Supplementary Table 4. Association of surface markers on CD161+
TH2 to AR}

\textbf{Supplementary Table 5. Association of umap cluster from
pediatric cohort CD161+ TH2 to AR}\selectlanguage{english}
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