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\begin{document}

\title{Analysis of circulating nutritional antigen-specific T-cells in celiac
disease and inflammatory bowel disease}



\author[1]{Rainer Glauben}%
\author[1]{Yasmina Rodriguez-Sillke}%
\author[1]{Michael Schumann}%
\author[1]{Donata Lissner}%
\author[1]{Federica Branchi}%
\author[2]{Ulrich Steinhoff}%
\author[1]{Britta Siegmund}%
\affil[1]{Charite Universitatsmedizin Berlin}%
\affil[2]{Philipps University Marburg Faculty of Medicine}%


\vspace{-1em}



  
  \date{June 15, 2024}


\begingroup
\let\center\flushleft
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\selectlanguage{english}
\begin{abstract}
Background: The present study aims to detect, quantify and analyze
circulating nutritional antigen-specific T-cells in patients with celiac
disease (CeD) as well as inflammatory bowel disease (IBD), thus
comparing the specific T-cell response following barrier disruption and
antigen translocation. Methods: The antigen-reactive T-cell enrichment
(ARTE) technique was applied allowing for a phenotypical and functional
flow cytometric analysis of rare nutritional antigen-specific T-cells,
including the CeD-causing gliadin (gluten), in the peripheral blood.
Results: Our study indicates that by applying the ARTE technique,
differences of gluten-specific T-cells as well as the differential
cytokine expression between the patient groups can be detected, even
without the burdening gluten re-exposure of the patients. CeD patients,
independent from the presence or absence of gluten exposure in their
current diet, featured an increase of the frequency of gliadin-specific
T-cells, which were characterized by a pro-inflammatory phenotype.
However, only for active CeD and a consecutive small intestinal barrier
breach, an increase of distinct nutritional T-cells could be detected.
Accordingly, frequency as well as pro-inflammatory phenotype of
nutritional antigen-specific T cells were highest in Crohn's disease
patients with small intestinal inflammation whereas no significant
increase was observed in ulcerative colitis. Conclusion: In summary, the
ARTE method allows not only for detection but also for functional
analysis of these rare cells even in healthy subjects. Applying this
method, we were able to demonstrate that for non-CeD-related nutritional
antigens, small intestinal barrier breach is mandatory for a peripheral
antigen-specific T-cell.%
\end{abstract}%



\sloppy


\textbf{Analysis of circulating nutritional antigen-specific T-cells in
celiac disease and inflammatory bowel disease}

Running title: Antigen-specific T-cells in IBD

Yasmina Rodr\selectlanguage{ngerman}íguez-Sillke\textsuperscript{1,2}, Michael
Schumann\textsuperscript{1}, Donata Lissner\textsuperscript{1}, Federica
Branchi\textsuperscript{1}, Ulrich Steinhoff\textsuperscript{3}, Britta
Siegmund\textsuperscript{1}*, Rainer Glauben\textsuperscript{1}*

\textsuperscript{1} Charité -- Universitätsmedizin Berlin, corporate
member of Freie Universität Berlin, Humboldt-Universität zu Berlin and
Berlin Institute of Health, Medizinische Klinik für Gastroenterologie,
Infektiologie und Rheumatologie, Berlin, Germany

\textsuperscript{2} University of Potsdam, Institute of Nutrition,
Nuthetal, Germany

\textsuperscript{3} Institute for Medical Microbiology and Hospital
Hygiene, Philipps University of Marburg, Germany.

* These authors contributed equally to this work.

\textbf{Corresponding author:}

Rainer Glauben, PhD

Charité - Universitätsmedizin Berlin, Campus Benjamin Franklin

Medizinische Klinik für Gastroenterologie, Infektiologie, Rheumatologie

Hindenburgdamm 30, 12200 Berlin, Germany

E-mail: rainer.glauben@charite.de

\textbf{Contributions} : YRS performed and analyzed the experiments, DL
and FB provided samples and patient information, YRS, MS, US, BS and RG
designed the experiments, interpreted the data and authored the
manuscript.

\textbf{Acknowledgment:} We thank Inka Freise for her technical
assistance. This work was funded by the Deutsche Forschungsgemeinschaft
SPP1656 (SPP1656); TRR241 (BS), DFG-SI749/10-1, and the Deutsche
Zöliakie-Gesellschaft e.V. (BS, RG and YRS).

\textbf{Conflict of Interests} : No conflicts of interest exist for any
of the coauthors.



\textbf{Abstract:}

\emph{Background:} The present study aims to detect, quantify and
analyze circulating nutritional antigen-specific T-cells in patients
with celiac disease (CeD) as well as inflammatory bowel disease (IBD),
thus comparing the specific T-cell response following barrier disruption
and antigen translocation.

\emph{Methods:} The antigen-reactive T-cell enrichment (ARTE) technique
was applied allowing for a phenotypical and functional flow cytometric
analysis of rare nutritional antigen-specific T-cells, including the
CeD-causing gliadin (gluten), in the peripheral blood.

\emph{Results:} Our study indicates that by applying the ARTE technique,
differences of gluten-specific T-cells as well as the differential
cytokine expression between the patient groups can be detected, even
without the burdening gluten re-exposure of the patients. CeD patients,
independent from the presence or absence of gluten exposure in their
current diet, featured an increase of the frequency of gliadin-specific
T-cells, which were characterized by a pro-inflammatory phenotype.
However, only for active CeD and a consecutive small intestinal barrier
breach, an increase of distinct nutritional T-cells could be detected.
Accordingly, frequency as well as pro-inflammatory phenotype of
nutritional antigen-specific T cells were highest in Crohn's disease
patients with small intestinal inflammation whereas no significant
increase was observed in ulcerative colitis.

\emph{Conclusion:} In summary, the ARTE method allows not only for
detection but also for functional analysis of these rare cells even in
healthy subjects. Applying this method, we were able to demonstrate that
for non-CeD-related nutritional antigens, small intestinal barrier
breach is mandatory for a peripheral antigen-specific T-cell.

\textbf{Keywords:}

antigen-specific T-cells / celiac disease / gluten / IBD / nutritional
antigens

\textbf{word count: 2648}

\textbf{Introduction}

Antigen-specific T-cells play a central role in the adaptive immune
system, promoting specific acute immune responses and the formation of
immunological memory. Analyzing not only frequency, but also phenotype
and function of these rare cells, represents a critical step to
understand the mechanisms of adaptive immunity in general, but also to
determine the specific immune status of the individual patient or to
diagnose infectious or auto-immune diseases. The high diversity of the
T-cell receptor, which allows for recognition of billions of different
antigens, leads to an extremely low frequency of T-cells, specific for a
single peptide-MHC ligand. This holds true even for pathogen-specific
memory compartments in the absence of acute infections, for which
specific T-cell frequencies in peripheral blood are typically far below
1\%, but all the more for the naive repertoire (\textless{}
0.0005\%)\textsuperscript{1,2}. Hence, the analysis of antigen-specific
T-cells demands methods which are highly specific, but in parallel allow
processing of large cell numbers to enable quantification of these rare
events. For the last decade, techniques such as antigen-specific
proliferation via \textsuperscript{3}H-thymidine
incorporation\textsuperscript{3} were applied, where antigen-specific
T-cells have been analyzed via bulk stimulation of peripheral blood
mononuclear cells (PBMC) with the respective antigen. However, in such
assays, it is not feasible to detect the phenotypic and functional
properties of the original reactive cells and therefore it is almost
impossible to determine the actual frequency and phenotype of these
cells in the starting cell sample or to exclude bystander effects.
ELISPOT\textsuperscript{4}, as an additional technical approach, reveals
information on a single cell level, but lacks the high throughput
capabilities to detect and quantify rare cells to an extent, where for
example food antigen-specific T-cells in healthy individuals can be
studied. Several studies aimed to characterize the systemic T-cell
response to decipher the role of circulating T-cells and their
functional impact \textsuperscript{5,6}. Until now, the specific
analysis of gluten-specific T-cells via flow cytometry depended on
tetramer analysis \textsuperscript{5}, which is limited to the knowledge
and availability of the antigen epitope \textsuperscript{7}, but also
the frequency of target cells, therefore suffering from a high
variability in cytokine analysis \textsuperscript{8}.

Among autoimmune diseases, celiac disease (CeD) represents a model
disease, since gluten has been identified as the disease-causing antigen
and elimination of gluten results in regeneration of the duodenal mucosa
and consecutive wellbeing of the patient \textsuperscript{9}. However,
the diagnosis in CeD patients who are already on a gluten-free diet
(GFD) remains challenging. Under a gluten-free diet (GFD),
tissue-transglutaminase (tTG) antibodies normalize and the small
intestinal villus atrophy regenerates. Until now, a burdening
re-challenge of the patients to gluten is mandatory for a valid
diagnosis. Yet, translocation of nutritional (and pathogenic) antigens
due to intestinal barrier breaches is described not exclusively for CeD,
but also for inflammatory bowel diseases (IBD). Although there are first
studies connecting GFD to improvement of patient
wellbeing\textsuperscript{10} and even microbiota
composition\textsuperscript{11} in IBD, until now, circulating
nutritional antigen-specific T-cells have not been analyzed in these
patients. Since the small intestine is the primary contact surface for
food antigens and hence for the immunological response, we analyzed the
specific nutritional T-cell response in the peripheral blood of patients
with small intestinal Crohn´s disease (CD), celiac disease as well as
ulcerative colitis (UC), respectively. To exclude the influence of a
non-intestinal inflammation, rheumatoid arthritis patients (RA) were
included as control.

We here applied the novel antigen-reactive T-cell enrichment
(ARTE)\textsuperscript{7} technology to determine the specific
nutritional effector T-cell response in the peripheral blood. The ARTE
technique is based on the stimulation of PBMC with a defined antigen and
the subsequent up-regulation of the activation marker
CD154\textsuperscript{+}, which is exclusively expressed on
antigen-specific CD4\textsuperscript{+} T-cells \textsuperscript{12}.
This method permits the detection of the entire antigen-specific
CD4\textsuperscript{+} T-cell response just by adding the antigen of
choice directly to PBMC without the need of in-vitro expanding the
reacting cells. The subsequent enrichment of
CD154\textsuperscript{+}cells enables further in-depth phenotyping of
this rare cell population. Thus, the ARTE technique allows a direct
\emph{ex vivo} cytometric - and hence functional - analyses of
gluten-specific, but also even rarer nutritional antigen-specific
T-cells.

\textbf{Methods}

PBMC from CeD, CD, UC and rheumatoid arthritis patients as well as
healthy controls (\textbf{Table 1} ) were cultured for 6 h in the
presence of defined antigens followed by magnetic enrichment of
activated CD154\textsuperscript{+} T-cells (as marker for
antigen-specific T-cells) \textsuperscript{7} (\textbf{Figure 1A, B} ).

\textbf{Blood donors and PBMC isolation}

Peripheral blood samples were obtained from healthy donors and patients
of the Charité - Universitätsmedizin Berlin, Medical Department,
Division of Gastroenterology, Infectiology and Rheumatology. All blood
donors gave informed consent and the study was approved by the ethical
committee of the Charité - Universitätsmedizin Berlin. PBMC were freshly
isolated from 20 mL blood by density gradient centrifugation (Biocoll;
Biochrom, Berlin, Germany). Heparinized whole blood was layered on the
Biocoll Separation Solution and centrifuged at 1200 g for 25 min at
21~°C. PBMC were collected from the interphase, washed and resuspended
in RPMI1640 (Gibco, Life Technologies, Darmstadt, Germany) supplemented
with 5\% human AB-serum (Sigma-Aldrich, St. Louis, MO, USA).

\textbf{Patients}

PBMC of CD patients with small intestinal manifestation and UC patients
with either active disease (defined by Harvey Bradshaw Index (HBI)) or
remission (defined by HBI; pMayo) \textsuperscript{13,14} were analyzed.
Additionally, CeD patients on a GFD for at least one year, newly
diagnosed active CeD patients still exposed to gluten (aCeD), or
GFD-refractory CeD patients (Refr) were included. Moreover, healthy
first-degree relatives (FDR) on a regular diet without symptoms were
included. The diagnosis of CeD was based on the presence of tTG
antibodies in the serum and characteristic histopathological features in
duodenal biopsies (Marsh score \textgreater{}1). Refractory celiac
disease diagnosis was based on the presence of a Marsh III enteropathy
and clinical malabsorption in spite of consumption of a gluten-free diet
for at least one year. Clonality analysis as done by PCR of the CDR3
region of the TCR was performed. Detection of a clonal T-cell population
and aberrant lymphocytes by immune phenotyping of duodenal tissue
allowed for diagnosis of Refr. type II. All other Refr. cases were
diagnosed as RCD type I\textsuperscript{15}. HLA-DQ status could not be
determined for IBD patients and controls. As additional non-intestinal
inflammatory control group PBMC from rheumatoid arthritis (RA) patients
were analyzed.

\textbf{Antigen-reactive T-cell enrichment}

Identification and enrichment of antigen-reactive T-cells was performed
by applying the recently described ARTE technique \textsuperscript{7}.
Briefly, 0.5 --1 x10\textsuperscript{7} PBMC were cultured in RPMI1640
supplemented with 5\% human AB-serum and stimulated for 6 h with 1 \selectlanguage{greek}µ\selectlanguage{english}g/mL
CD40 (Miltenyi Biotec, Bergisch Gladbach, Germany) in the presence or
absence of the pepsin-trypsin digested 33-mer gliadin peptide (200
\selectlanguage{greek}µ\selectlanguage{english}g/mL) (Sigma- Aldrich), OVA-peptide (Invitrogen) or soybean or peanut
extract (200 \selectlanguage{greek}µ\selectlanguage{english}g/mL) (Greer Laboratories). For the last 2 h, 1 \selectlanguage{greek}µ\selectlanguage{english}g/mL
brefeldin A (Sigma- Aldrich) was added. Cells were indirectly labeled
with anti-CD154-biotin antibody, followed by anti-biotin MicroBeads
(CD154 MicroBead-Kit, Miltenyi Biotec) and magnetically enriched using
MS columns (Miltenyi Biotec).

\textbf{Flow cytometric cell analysis}

Surface staining was performed on the MS column (first panel: Brilliant
violet 510 anti-human CD4; RPA-T4, Brilliant Violet 421 anti-human
CD197 (CCR7); G043H7, PE/Cy7 anti-human CD45RA; HI100, second panel:
Brilliant violet 510 anti-human CD4; PE/Cy7 anti-human CD29/\selectlanguage{ngerman}ß1; TS2/16,
PE anti-human ß7; FIB504, all from BioLegend (Koblenz, Germany), VioBlue
anti-human CD49d/\selectlanguage{greek}α\selectlanguage{english}4; MZ18-24A9 from Miltenyi Biotec. (Bergisch Gladbach,
Germany) and human FC block (CSL Behring, Marburg, Germany)). The
enriched cell fraction was fixed using eBioscience, FoxP3 staining
buffer, Thermo Fisher Scientific, Waltham, MA USA) and intracellular
staining was performed (APC anti-human IFN\selectlanguage{greek}γ; \selectlanguage{english}4S.B3, APC/Cy7 anti-human
IL-17A; BL168, PerCP/Cy5.5 anti-human TNF\selectlanguage{greek}α; \selectlanguage{english}MAb11, all from BioLegend
and FITC anti-human CD154 (5C8) from Miltenyi Biotec. Flow cytometry
analysis was performed on the FACS Canto II device (BD Bioscience,
Heidelberg, Germany). Data were analyzed with FlowJo analysis software
(Ashland, OR, USA).

\textbf{Statistics}

Statistical analysis was performed using Prism software (GraphPad
Software). Significance was determined using Mann-Whitney-U-Test as
indicated. *P\textgreater{}0.05, **P\textgreater{}0.01,
***P\textgreater{}0.001.

\textbf{Results}

\textbf{Circulating gliadin-specific T-cells are increased in active
disease with ileal inflammation}

ARTE technology was applied to all blood samples (\textbf{Figure~1A} )
for various nutritional antigens, including controls for
antigen-specific T-cell enrichment and T-cell activation. Moreover, we
could clearly demonstrate the necessity for T-cell enrichment to allow
for deeper cell analysis and therefore the advantage of this method over
direct staining protocols for rare antigen-specific cell populations
(\textbf{Figure~1B} ). With the overall frequency of
CD4\textsuperscript{+} T-cells remaining stable in the various disease
conditions (\textbf{Figure~1C} ), the frequency of gliadin-specific
CD154\textsuperscript{+} T-cells among CD4\textsuperscript{+} T-cells in
PBMC was expectedly highest in active CeD (aCeD), i.e. without GFD, as
well as in refractory CeD patients (Refr). aCeD are rare patients as we
did not actively initiate a gluten-re-challenge. Moreover the
frequencies were also significantly increased in CeD patients on a GFD
without clinical symptoms, when compared to healthy controls.
Remarkably, a similar frequency to active CeD patients was observed in
active CD patients with ileal inflammation (\textbf{Figure~2A} ).

The frequency was significantly lower in CD patients in remission, in UC
patients, independent of their inflammatory state and in healthy
controls. Interestingly, first-degree relatives (FDR) of CeD patients,
considered healthy by standard diagnostics, revealed a significant
increase in the frequency of gliadin-specific T-cells compared to
controls without familiar predisposition of CeD. Of notice, RA as
auto-inflammatory control without intestinal inflammation, did not
differ from healthy controls.

\textbf{Phenotyping circulating gliadin-specific T-cells}

Further phenotyping of gliadin--specific
CD4\textsuperscript{+}CD154\textsuperscript{+} T-cells in effector
memory (CD45RA\textsuperscript{-} CCR7\textsuperscript{-}), central
memory (CD45RA\textsuperscript{-}CCR7\textsuperscript{+}) or na\selectlanguage{ngerman}ïve
(CD45RA\textsuperscript{+}CCR7\textsuperscript{+}) cells revealed a
shift towards the memory types in the groups with active small
intestinal inflammation. Remarkably, effector memory T-cells outnumbered
naïve T-cells (ratio\textgreater{}1, \textbf{Figure~2B} ) only in aCeD,
Refr and CD patients. Moreover, gliadin-specific
CD4\textsuperscript{+}CD154\textsuperscript{+} T-cells, positive for the
small intestinal homing marker \selectlanguage{greek}α\selectlanguage{english}4\selectlanguage{greek}β\selectlanguage{english}1, but not for \selectlanguage{greek}α\selectlanguage{english}4\selectlanguage{greek}β\selectlanguage{english}7, a general gut
homing marker, were increased in aCeD patients (\textbf{Figure~2C, D} ),
further strengthening the connection of peripheral nutritional
antigen-specific T-cells to small intestinal inflammation.

\textbf{Pro-inflammatory cytokines of circulating gliadin-specific
T-cells}

The subsequent functional analysis of the antigen-specific T-cells after
gliadin stimulation (\textbf{Figure~2E, F; S.~Figure~1} ) revealed
highest production of the pro-inflammatory cytokines IFN\selectlanguage{greek}γ, \selectlanguage{english}IL-17A and
TNF\selectlanguage{greek}α \selectlanguage{english}in cells from aCeD, Refr, but also from CD patients with small
intestinal involvement. Remarkably, antigen-specific T-cells of
first-degree relatives of CeD patients (FDR) presented with higher
frequencies of gliadin-specific T-cells and an increased TNF\selectlanguage{greek}α
\selectlanguage{english}expression, and were thus comparable to aCeD patients. TNF\selectlanguage{greek}α-\selectlanguage{english}positive
CD154\textsuperscript{+} cells were most discriminative when comparing
active and inactive CeD to healthy controls.

\textbf{Further food antigen-specific T-cells are increased in active
disease with ileal inflammation}

To dissect a sole barrier defect, as it is present in small intestinal
CD, from the disease-driving gliadin-reactivity in CeD, we included
soybean protein, peanut protein and OVA-peptide in our analysis. In
fact, an increased frequency of antigen-specific
CD4\textsuperscript{+}T-cells was exclusively observed in the presence
of small intestinal inflammation, namely CD and aCeD. CD patients in
remission as well as UC patients independent of their inflammatory state
did not differ from healthy controls. Furthermore, CeD patients on GFD,
although being highly reactive to gliadin, showed no reaction to other
nutritional antigens (\textbf{Figure~3A, B} ).

\textbf{Discussion}

So far, the published data for ARTE have been focusing on bacteria- or
fungi-specific antigens as well as house dust mites\textsuperscript{16}.
However, this methods allows also to study even rarer nutritional
antigen-specific T-cells without in-vitro expanding of the reacting
cells and without re-challenging the patients. Therefore, we apply this
method for detection of the rare nutritional antigen-specific T-cells in
peripheral blood, in order to analyze antigen reactivity for different
clinical subgroups of CeD and IBD patients.

Recently, peripheral gluten-specific CD4\textsuperscript{+} T-cells were
analyzed applying HLA-DQ2:gluten tetramers, thus identifying an increase
of gluten-specific CD4\textsuperscript{+} T-cells in
aCeD\textsuperscript{5,6}. However, the here applied ARTE allows for a
deeper analysis of the respective specific CD4\textsuperscript{+}T-cells
to distinguish different disease states of CeD. The diagnosis of CeD in
patients who already follow a GFD is challenging, since tTG antibodies
under GFD normalize and histological markers, as the small intestinal
villous atrophy, regenerates. This clinical need is even growing, giving
the increasingly popular gluten-free life style in the western world
\textsuperscript{17,18}, or for first degree relatives, who frequently
initiate a GFD when a household member is diagnosed with CeD. For the
latter, the high risk of developing CeD has been proven in many studies
\textsuperscript{19,20} and surveillance for CeD is even recommended for
first-degree relatives of a diagnosed patient where carriage of a risk
gene has not been excluded \textsuperscript{21,22}. Work herein might be
the first step towards identifying such cases, without a conventional
burdening gluten re-challenge, since characteristic changes in cytokine
expression in gliadin-specific CD4\textsuperscript{+} T-cells in the
peripheral blood are present. For the rare subgroup of Refr patients,
especially for type~I, the specific immunological nature remains
unclear. Diagnosis is still based on histopathology alone, while recent
studies suggest a heterogeneous composition of different pathologies to
be merged under this term. In this respect, the ARTE technique for
gliadin-specific T-cells represents a unique research tool for future
studies that has the potential to contribute to a subclassification of
this disease group. Furthermore, our data reveal a specific
immunological phenotype of gliadin-specific CD4\textsuperscript{+}
T-cells from FDR regarding the hypersensitivity towards gluten, even if
diagnosed as healthy due to their tTG status (without GFD). By
demonstrating an active immune response against the pathogenic antigen,
identification and even phenotyping of gluten-reactive T-cells from
peripheral blood might represent an alternative, all the more in
pediatric cases, where first time diagnosis is common, while invasive
endoscopy is meant to be avoided. Thus, this novel approach could
fulfill the clinical need for a noninvasive marker of CeD activity as
clinical and research tool \textsuperscript{23}.

With regard to IBD, which shares the characteristics of barrier
disruption \textsuperscript{24} and subsequent intestinal inflammation
in the lamina propria, we detected increased levels of gliadin-specific
T-cells in the peripheral blood of active CD patients with concurrent
small intestinal inflammation, paralleled by the highest frequency of
antigen-specific T-cells expressing pro-inflammatory cytokines. This
distinct occurrence suggests the small intestinal barrier disruption as
major cause for the observed T-cell activation, since these cells
express small intestinal homing markers. The homing to the ileum (\selectlanguage{greek}α\selectlanguage{english}4\selectlanguage{greek}β\selectlanguage{english}1)
was described as essential pathway in CD \textsuperscript{25}. In line,
only in these three patient groups of active small intestinal
inflammation, the effector-memory T-cells outnumbered the na\selectlanguage{ngerman}ïve
phenotype among gliadin-specific T-cells in the peripheral blood.
Furthermore, peripheral T-cells from CD patients with small intestinal
inflammation proved to be responsive to other major nutritional
antigens\textsuperscript{26}, while neither active UC nor CD or UC in
remission showed any reaction. Again, only antigen-specific T-cells from
active CeD, but not GFD patients demonstrated similar properties,
corroborating on the one hand the leaky barrier of the affected small
intestine as the site of food antigen translocation and subsequent
T-cell activation. On the other hand, the significant effect of gliadin,
but no other food antigen, in the GFD group further confirmed the
singular antigen-driven nature of CeD. Nevertheless, based on surveys,
it has been suggested, that long-term GFD improves gastrointestinal
symptoms in active IBD patients \textsuperscript{10}. With the present
study, we are able to convey cellular and functional data by
demonstrating an enhanced gliadin-specific response of pro-inflammatory
cytokines towards gliadin for CD patients

Our data strongly suggest, that small intestinal inflammation is key for
the development of a nutritional antigen-specific T-cell response.
Therefore, ARTE allows to distinguish CD with small intestinal
inflammation from UC and CD in remission by a unique profile of
circulating antigen-specific T-cells, raising the question, if a
well-defined nutritional regimen (e.g. GFD) might have therapeutic
potential in the setting of IBD. Hence, based on the analysis of the
systemic immune response, an ``anti-inflammatory'' diet could be
developed and monitored. In addition, this technique allows detailed
analyses of gliadin-specific T-cells in such a high resolution that even
healthy first-degree relatives can be discriminated and might thus
provide a novel non-invasive diagnostic tool to identify symptom-free
CeD patients on a gluten-free diet.

\textbf{References}

1. Kwok WW, Tan V, Gillette L, et al. Frequency of epitope-specific
naive CD4(+) T cells correlates with immunodominance in the human memory
repertoire. \emph{J Immunol.} 2012;188(6):2537-2544.

2. Chu HH, Moon JJ, Takada K, et al. Positive selection optimizes the
number and function of MHCII-restricted CD4+ T cell clones in the naive
polyclonal repertoire. \emph{Proc Natl Acad Sci U S
A.}2009;106(27):11241-11245.

3. Gjertsen HA, Sollid LM, Ek J, Thorsby E, Lundin KE. T cells from the
peripheral blood of coeliac disease patients recognize gluten antigens
when presented by HLA-DR, -DQ, or -DP molecules. \emph{Scand J
Immunol.}1994;39(6):567-574.

4. Anderson RP, van Heel DA, Tye-Din JA, et al. T cells in peripheral
blood after gluten challenge in coeliac disease.
\emph{Gut.}2005;54(9):1217-1223.

5. Sarna VK, Lundin KEA, Morkrid L, Qiao SW, Sollid LM, Christophersen
A. HLA-DQ-Gluten Tetramer Blood Test Accurately Identifies Patients With
and Without Celiac Disease in Absence of Gluten
Consumption.\emph{Gastroenterology.} 2018;154(4):886-896 e886.

6. Ben-Horin S, Green PH, Bank I, Chess L, Goldstein I. Characterizing
the circulating, gliadin-specific CD4+ memory T cells in patients with
celiac disease: linkage between memory function, gut homing and Th1
polarization. \emph{J Leukoc Biol.} 2006;79(4):676-685.

7. Bacher P, Scheffold A. Flow-cytometric analysis of rare
antigen-specific T cells. \emph{Cytometry A.} 2013;83(8):692-701.

8. Pastore G, Carraro M, Pettini E, Nolfi E, Medaglini D, Ciabattini A.
Optimized Protocol for the Detection of Multifunctional Epitope-Specific
CD4(+) T Cells Combining MHC-II Tetramer and Intracellular Cytokine
Staining Technologies. \emph{Front Immunol.} 2019;10:2304.

9. Schuppan D, Junker Y, Barisani D. Celiac disease: from pathogenesis
to novel therapies. \emph{Gastroenterology.} 2009;137(6):1912-1933.

10. Herfarth HH, Martin CF, Sandler RS, Kappelman MD, Long MD.
Prevalence of a gluten-free diet and improvement of clinical symptoms in
patients with inflammatory bowel diseases. \emph{Inflamm Bowel
Dis.}2014;20(7):1194-1197.

11. Bonder MJ, Tigchelaar EF, Cai X, et al. The influence of a
short-term gluten-free diet on the human gut microbiome. \emph{Genome
Med.} 2016;8(1):45.

12. Frentsch M, Arbach O, Kirchhoff D, et al. Direct access to CD4+ T
cells specific for defined antigens according to CD154
expression.\emph{Nat Med.} 2005;11(10):1118-1124.

13. Harvey RF, Bradshaw JM. A simple index of Crohn's-disease
activity.\emph{Lancet.} 1980;1(8167):514.

14. Schroeder KW, Tremaine WJ, Ilstrup DM. Coated oral 5-aminosalicylic
acid therapy for mildly to moderately active ulcerative colitis. A
randomized study. \emph{N Engl J Med.} 1987;317(26):1625-1629.

15. Felber J, Aust D, Baas S, et al. {[}Results of a S2k-Consensus
Conference of the German Society of Gastroenterolgy, Digestive- and
Metabolic Diseases (DGVS) in conjunction with the German Coeliac Society
(DZG) regarding coeliac disease, wheat allergy and wheat
sensitivity{]}.\emph{Z Gastroenterol.} 2014;52(7):711-743.

16. Bacher P, Kniemeyer O, Schonbrunn A, et al. Antigen-specific
expansion of human regulatory T cells as a major tolerance mechanism
against mucosal fungi. \emph{Mucosal Immunol.} 2014;7(4):916-928.

17. Kim HS, Patel KG, Orosz E, et al. Time Trends in the Prevalence of
Celiac Disease and Gluten-Free Diet in the US Population: Results From
the National Health and Nutrition Examination Surveys
2009-2014.\emph{JAMA Intern Med.} 2016;176(11):1716-1717.

18. Hager AS, Taylor JP, Waters DM, Arendt EK. Gluten free beer - A
review. \emph{Trends Food Sci Tech.} 2014;36(1):44-54.

19. Acharya P, Kutum R, Pandey R, et al. First Degree Relatives of
Patients with Celiac Disease Harbour an Intestinal Transcriptomic
Signature that Might Protect them from Enterocyte Damage. \emph{Clin
Transl Gastroenterol.} 2018;9(10):195.

20. Singh P, Arora S, Lal S, Strand TA, Makharia GK. Risk of Celiac
Disease in the First- and Second-Degree Relatives of Patients With
Celiac Disease: A Systematic Review and Meta-Analysis. \emph{Am J
Gastroenterol.} 2015;110(11):1539-1548.

21. Hill ID, Dirks MH, Liptak GS, et al. Guideline for the diagnosis and
treatment of celiac disease in children: recommendations of the North
American Society for Pediatric Gastroenterology, Hepatology and
Nutrition. \emph{J Pediatr Gastroenterol Nutr.} 2005;40(1):1-19.

22. Husby S, Koletzko S, Korponay-Szabo IR, et al. European Society for
Pediatric Gastroenterology, Hepatology, and Nutrition guidelines for the
diagnosis of coeliac disease. \emph{J Pediatr Gastroenterol
Nutr.}2012;54(1):136-160.

23. Leffler DA, Schuppan D. Update on serologic testing in celiac
disease. \emph{Am J Gastroenterol.} 2010;105(12):2520-2524.

24. Martini E, Krug SM, Siegmund B, Neurath MF, Becker C. Mend Your
Fences: The Epithelial Barrier and its Relationship With Mucosal
Immunity in Inflammatory Bowel Disease. \emph{Cell Mol Gastroenterol
Hepatol.} 2017;4(1):33-46.

25. Zundler S, Fischer A, Schillinger D, et al. The alpha4beta1 Homing
Pathway Is Essential for Ileal Homing of Crohn's Disease Effector T
Cells In Vivo. \emph{Inflamm Bowel Dis.} 2017;23(3):379-391.

26. Tordesillas L, Berin MC, Sampson HA. Immunology of Food
Allergy.\emph{Immunity.} 2017;47(1):32-50.

\textbf{Table 1}\selectlanguage{english}
\begin{longtable}[]{@{}llllll@{}}
\toprule
\begin{minipage}[b]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[b]{0.14\columnwidth}\raggedright\strut
\textbf{Non-relative controls} (n=24)\strut
\end{minipage} & \begin{minipage}[b]{0.14\columnwidth}\raggedright\strut
\textbf{First-degree relatives} (n=6)\strut
\end{minipage} & \begin{minipage}[b]{0.14\columnwidth}\raggedright\strut
\textbf{Celiac disease on GFD} (n=24)\strut
\end{minipage} & \begin{minipage}[b]{0.14\columnwidth}\raggedright\strut
\textbf{Active celiac disease} (n=9)\strut
\end{minipage} & \begin{minipage}[b]{0.14\columnwidth}\raggedright\strut
\textbf{Refractory celiac disease*} (n=11)\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{Age} (mean \selectlanguage{ngerman}± SD)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
33.3 \selectlanguage{ngerman}± 9.4\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
34.5 \selectlanguage{ngerman}± 9.5\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
43.9 \selectlanguage{ngerman}± 16.8\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
47.3 \selectlanguage{ngerman}± 12.4\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
61.1 \selectlanguage{ngerman}± 11.6\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{Female} {[}\%{]}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
55\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
83\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
80\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
66\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
82\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{tTG} (mean \selectlanguage{ngerman}± SD) {[}U/mL{]} \textsuperscript{\#}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
1.6 \selectlanguage{ngerman}± 0.7\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
1.4 \selectlanguage{ngerman}± 0.4\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
6.3 \selectlanguage{ngerman}± 4.8\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
114.2 \selectlanguage{ngerman}± 70.9\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
21.0 \selectlanguage{ngerman}± 27.2\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
{[}CE{]}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
-\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{-}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{-}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
3428.1 \selectlanguage{ngerman}± 1313.7\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{-}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
\textbf{Marsh} \textbf{grade} - IIIa \textbf{at first diagnosis} - IIIb
- IIIc\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
\textbf{-}\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
\textbf{-}\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
10 9 4\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
3 3 2\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
6 2 2\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{RCD} type I /II {[}\%{]}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{-}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{-}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{-}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{-}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
63.6/36.4\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}\selectlanguage{english}
\begin{longtable}[]{@{}lllllll@{}}
\toprule
\begin{minipage}[b]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[b]{0.14\columnwidth}\raggedright\strut
\textbf{Non-relative controls} (n=24)\strut
\end{minipage} & \begin{minipage}[b]{0.14\columnwidth}\raggedright\strut
\textbf{Rheumatoid arthritis} (n=5)\strut
\end{minipage} & \begin{minipage}[b]{0.14\columnwidth}\raggedright\strut
\selectlanguage{ngerman}\textbf{Crohn´s disease} (n=19+13)\strut
\end{minipage} & \begin{minipage}[b]{0.14\columnwidth}\raggedright\strut
\selectlanguage{ngerman}\textbf{Crohn´s disease (remission}) (n=10+4)\strut
\end{minipage} & \begin{minipage}[b]{0.14\columnwidth}\raggedright\strut
\textbf{Ulcerative colitis} (n=12+7)\strut
\end{minipage} & \begin{minipage}[b]{0.14\columnwidth}\raggedright\strut
\textbf{Ulcerative colitis (remission)} (n=9+2)\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\textbf{Age} (mean \selectlanguage{ngerman}± SD)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
33.3 \selectlanguage{ngerman}± 9.4\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
49.4 \selectlanguage{ngerman}± 10.8\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
36.2 \selectlanguage{ngerman}± 9.3\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
41.4 \selectlanguage{ngerman}± 13.9\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
41.0 \selectlanguage{ngerman}± 14.9\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
42.0 \selectlanguage{ngerman}± 15.1\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\textbf{Female} {[}\%{]}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
55\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
67\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
50\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
57\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
37\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
64\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{Clinical score} \textbf{- HBI}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
-\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
-\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
5.1 \selectlanguage{ngerman}± 2.7\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
0.5 \selectlanguage{ngerman}± 1.2\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
-\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
-\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\textbf{- partial Mayo}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
-\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
-\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
-\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
-\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
3.9 \selectlanguage{ngerman}± 1.9\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
1.0 \selectlanguage{ngerman}± 1.0\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textbf{Montreal classification} - A1 \textless{}17 years - A2 17-40
years - A3 \textgreater{}40 years Crohn´s disease - L1 ileal - L3
ileocolonic - L4 upper GI Ulcerative colitis - E1 proctitis - E2 distal
UC - E3 extensive UC\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
-\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
-\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
0 23 9 11 12 6\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
0 7 7 4 8 2\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
0 7 12 0 8 10\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
0 6 5 0 8 3\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

HBI, Harvey-Bradshaw index



\textbf{Figure legends}

\textbf{Figure 1} . \emph{Enrichment of food antigen-specific
T-cells.}(\textbf{A-C} ) Peripheral blood mononuclear cells (PBMC) were
stimulated with various food antigens, magnetically enriched for CD154
and analyzed by flow cytometry. (\textbf{A} ) Methodology and
(\textbf{B} ) exemplary density plots of CD154\textsuperscript{+} T-cell
enrichment after stimulation with gliadin or control antigen are shown.
(\textbf{C} ) Frequencies of CD4\textsuperscript{+} T-cells in PBMC were
determined from healthy controls (non-relatives, NR), patients with
active Crohn\selectlanguage{ngerman}´s disease (CD) or ulcerative colitis (UC), or each of these
entities in remission (-R), celiac disease patients (CeD) ± gluten-free
diet (GFD, aCeD) or refractory (Refr) patients, first degree relatives
of CeD patients (FDR) and rheumatoid arthritis patients (RA). Data are
shown as median with 95\% CI.

\textbf{Figure 2} . \emph{Phenotyping gliadin-specific
T-cells.}(\textbf{A-F} ) Peripheral blood mononuclear cells (PBMC) were
stimulated with various food antigens, magnetically enriched for CD154
and analyzed by flow cytometry. (\textbf{A} ) Frequencies of
CD154\textsuperscript{+}cells among CD4\textsuperscript{+} T-cells in
PBMC from healthy controls (non-relatives, NR), patients with active
Crohn´s disease (CD) or ulcerative colitis (UC), or each of these
entities in remission (-R), celiac disease patients (CeD) ± gluten-free
diet (GFD, aCeD) or refractory (Refr) patients, first degree relatives
of CeD patients (FDR) and rheumatoid arthritis patients (RA) are shown.
(\textbf{B} ) Ratio of gliadin-specific effector memory
CD4\textsuperscript{+}CD154\textsuperscript{+} T-cells
(CD45RA\textsuperscript{-}CCR7\textsuperscript{-}) and naïve T-cells
(CD45RA\textsuperscript{+}CCR7\textsuperscript{+}) from controls and
disease groups are shown. (\textbf{C} ) Exemplary dot plots of \selectlanguage{greek}α\selectlanguage{english}4\selectlanguage{greek}β\selectlanguage{english}1
within CD4\textsuperscript{+} and
CD4\textsuperscript{+}CD154\textsuperscript{+} T-cells are shown.
(\textbf{D} ) Frequencies of CD4\textsuperscript{+} T cells and
CD4\textsuperscript{+} CD154\textsuperscript{+} T cells, positive for
integrins \selectlanguage{greek}α\selectlanguage{english}4\selectlanguage{greek}β\selectlanguage{english}1 and \selectlanguage{greek}α\selectlanguage{english}4\selectlanguage{greek}β\selectlanguage{english}7 are shown. (\textbf{E} ) Frequencies of
gliadin-specific IFN\selectlanguage{greek}γ\selectlanguage{english}\textsuperscript{+}, IL-17A\textsuperscript{+} and
TNF\selectlanguage{greek}α\selectlanguage{english}\textsuperscript{+} cells within CD154\textsuperscript{+} T-cells in
between the patient groups are shown. (\textbf{F} ) Exemplary dot plots
of IFN\selectlanguage{greek}γ\selectlanguage{english}\textsuperscript{+}, IL-17A\textsuperscript{+} and
TNF\selectlanguage{greek}α\selectlanguage{english}\textsuperscript{+}
CD4\textsuperscript{+}CD154\textsuperscript{+}gliadin-specific T-cells
are shown. Data are shown as median. Significance was determined using
Mann-Whitney-U-Test. *P\textgreater{}0.05, **P\textgreater{}0.01,
***P\textgreater{}0.001. Statistically significant differences were
calculated in comparison to healthy non-relatives, if not indicated
otherwise.

\textbf{Figure 3} . \emph{Frequencies of food antigen-specific
T-cells.}(\textbf{A-B} ) Peripheral blood mononuclear cells (PBMC) were
stimulated with various food antigens, magnetically enriched for CD154
and analyzed by flow cytometry. (\textbf{A} ) Exemplary dot plots of
CD154\textsuperscript{+} T-cell enrichment of indicated nutritional
antigens with absolute numbers and frequencies are shown. (\textbf{B} )
Frequencies of CD154\textsuperscript{+} cells among
CD4\textsuperscript{+} T-cells after stimulation with soybean, peanut
and OVA-peptide from healthy controls (non-relatives, NR), patients with
active Crohn\selectlanguage{ngerman}´s disease (CD) or ulcerative colitis (UC), or each of these
entities in remission (-R), celiac disease patients (CeD) ± gluten-free
diet (GFD, aCeD) or refractory (Refr) patients are shown. Data are shown
as median. Significance was determined using Mann-Whitney-U-Test.
*P\textgreater{}0.05, **P\textgreater{}0.01, ***P\textgreater{}0.001.
Statistically significant differences were calculated in comparison to
healthy non-relatives, if not indicated otherwise.

Figure 1\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

Figure 2:\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

Figure 3:\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image3/image3}

\end{center}
\end{figure}

\selectlanguage{english}
\FloatBarrier
\end{document}

