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\begin{document}

\title{CircRNA expression profile and circRNA-miRNA-mRNA crosstalk in allergic
rhinitis}



\author[1]{Chang-Yu Qiu}%
\author[1]{Qing Yang}%
\author[2]{Mei-Ping Lu}%
\author[1]{Min Yin}%
\author[1]{Wan-Yun Xu}%
\author[1]{Xin-Jie Zhu}%
\author[1]{Xin-Yan Cui}%
\author[1]{Lei Cheng}%
\affil[1]{The First Affiliated Hospital, Nanjing Medical University}%
\affil[2]{The First Affiliated Hospital of Nanjing Medical University}%


\vspace{-1em}



  
  \date{May 22, 2024}


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\textbf{CircRNA expression profile and circRNA-miRNA-mRNA crosstalk in
allergic rhinitis}

To the Editor,

Allergic rhinitis (AR) is a chronic multi-factorial inflammatory
disease, with a prevalence on the rise in China\textsuperscript{1}.
CircRNAs, a newly discovered family of endogenous non-coding RNAs,
function in various biological processes\textsuperscript{2}. For
instance, circRNAs are involved in neuronal activities, tumor
development, and innate immune responses, inflammatory
diseases\textsuperscript{3-4}. However, the roles of circRNAs in AR
remain unclear. In this study, using high-throughput sequencing (HTS),
we explored the circRNA, miRNA, and mRNA expression profiles in nasal
mucosa from AR patients, and constructed a differentially expressed (DE)
circRNA-DEmiRNA-DEmRNA network to illustrate the molecular mechanism in
AR.

This study was approved by the Ethics Committee of the First Affiliated
Hospital of Nanjing Medical University and each patient provided written
informed consent. Patients and methods are detailed as online data.

\textbf{RESULTS}

\textbf{CircRNA expression profile in nasal mucosa}

Three pairs of nasal mucosa tissue of middle turbinate were randomly
selected from ten patients with perennial AR and ten healthy controls
for HTS analysis. The clinical characteristics of the patients are shown
in Table S1. All normalized sample datasets displayed similar circRNA
distribution intensities (Fig. S1A). A total of 30,936 circRNAs were
identified, including 12,376 known and 18,560 novel ones (Fig. S1B).
CircRNA transcripts were widely distributed on all chromosomes
(Fig.S1C). Spliced reads per million (RPM) revealed that almost all
circRNA transcripts were expressed at low levels (Fig.S1D)

Among these circRNA, 1,119 were antisense and 29,335 were sense,
including 28,694 exonic, 641 intronic, and 1,119 intergenic circRNAs. In
particular, 93\% of the circRNAs were sense exons (Fig. S2A) and most
circRNA transcripts carried 1--7 exons (Fig.S2B), with a length of
200--400bpor \textgreater{}2000bp (Fig.S2C). Hierarchical clustering
revealed the DEcircRNAs between samples (Fig. S2D) and HTS analysis
identified 264 DEcircRNAs (120 upregulated and 144 downregulated). The
top 300 relevant circRNA-miRNA pairs were screened and their network
constructed with Cytoscape software (Fig.S3).

\textbf{MiRNA and mRNA expression profiles in nasal mucosa}

Of the 1,784 miRNAs, 13 were upregulated and 15 downregulated. Of the
2,030 mRNAs,93 were upregulated and 79 downregulated. Hierarchical
clustering revealed that these DEmiRNAs (Fig. S4A) and DEmRNAs (Fig.
S4B) were distinct between samples.

\textbf{DEcircRNA-DEmiRNA, DEmiRNA-DEmRNA, and DEcircRNA-DEmRNA
interactions}

Using miRanda software, 911 DEmiRNA-DEcircRNA pairs and 379
DEmiRNA-DEmRNA pairs were detected. Next, we calculated their Pearson
correlation coefficients (PCCs), with \emph{p} -value \textless{}0.05
and an absolute PCC of [?]0.7. We screened out 941 DEmiRNA-DEcircRNA and
865 DEmiRNA-DEmRNA pairs with negative correlation, and 116
DEmiRNA-DEcircRNA and 379 DEmiRNA-DEmRNA pairs were screened by miRanda
and correlation analyses. Then a DEcircRNA-DEmRNA network was made based
on 11 circRNAs and 29 mRNAs that were positively correlated (Fig. S5).

\textbf{DEcircRNA-DEmiRNA-DEmRNA network and functional annotation}

Next, we identified17 miRNAs interacting with both circRNAs and mRNAs,
and used them to construct a DEcircRNA-DEmiRNA-DEmRNA network (Table S2)
containing 64 interaction pairs (Fig.1).

According to GO and KEGG analyses, the genes in the network were
enriched in 159 terms, including 172 biological processes, 47 cell
components, and 46 molecular functional components. The GO terms mainly
involved the Wnt signaling pathway, lung epithelial cell development,
and TNF biosynthesis(biological processes), endoplasmic reticulum lumen,
flotillin complex, and intercellular canaliculus (cell components),
fibronect in binding, collagen binding, and calcium:sodium antiporter
activity (molecular functions; Fig.2A). In addition, these genes were
enriched in the inflammatory response and various signaling pathways
(such as cell surface receptor signaling pathways), indicating that
circRNAs may participate in multiple pathways related to AR. KEGG
analysis revealed 24 significantly involved pathways, mainly about
adhesion, ECM receptor interaction, protein degradation and absorption,
and PI3K-Akt signaling (Fig. 2B). However, other pathways, such as the
Toll-like receptor signaling pathway, suggested that circRNAs may act as
competing endogenous RNAs (ceRNAs) in AR to regulate mRNAs by
competitively binding to miRNAs.

\textbf{Sanger sequencing verification and RT-PCR quantification of
circRNAs}

Of the 11 circRNAs in the network (Table S2), two were known
(hsa\_circ\_0008668 and hsa\_circ\_0029853) and nine were novel. Then,
hsa\_circ\_0008668, hsa\_circ\_0029853, circTRIQK (a sense-overlapping
circRNA), and circRNA\_01002 (an intergenic circRNA) were subjected to
RT-PCR amplification and Sanger sequencing to confirm their
back-splicing sites (Fig.S6A-D). The RT-PCR dissolution curve had a
single peak, suggesting that the primers had good repeatability and
yielded a single type of product. In addition, RT-PCR revealed that
hsa\_circ\_0008668 (Fig. S6E) and circTRIQK (Fig. S6G) were upregulated
in AR, whereas hsa\_circ\_0029853 (Fig. S6F) and circRNA\_01002 were
downregulated (Fig.S6H). These findings were consistent with the HTS
data.

\textbf{DISCUSSION}

CircRNAs have been shown to regulate mRNAs by sponging
miRNA\textsuperscript{5}. Fang \emph{et al} . reported that circANKRD36
expression positively correlated with the level of IL-6 and might be
involved in type 2 diabetes mellitus and inflammation-related
pathways\textsuperscript{6}. Similarly, Ddx17 was found to exert
protective effects by inhibiting miR-17-5p expression in ovalbumin
-induced AR mice\textsuperscript{7}. To the best of our knowledge, this
is the first study to investigate circRNA expression profiles and
functions in AR.

We predicted DEmiRNAs and DEcircRNAs using miRanda and screened out 116
pairs with negative relationships, including 17 miRNAs (like
hsa-miR-98-5p and hsa-miR-455-5p). Similarly, we identified 379
DEmiRNA-DEmRNA pairs and many DEgenes (such as DOCK8 and MUC19) that
were significantly associated with allergic
inflammation\textsuperscript{8}. Finally, we constructed a novel
DEcircRNA-DEmiRNA-DEmRNA network consisting of 64 ceRNA pairs. In this
network, 11 circRNAs bound to 17 miRNAs, such as hsa-miR-98-5p, to
regulate the expression of 29 genes. Previous studies have found that AR
is regulatedby many signaling pathways, including PI3K-Akt and TLR
signaling pathways\textsuperscript{9}. Consistent with these findings,
we found that the 29 AR-related genes also were involved these signaling
pathways, suggestive of the key roles of these genes in AR development.

In summary, crosstalk between circRNAs, miRNAs, and mRNAs is essential
for AR development and the crosstalk network identified in this study
provides new directions for targeted treatments against AR.

\textbf{KEYWORDS}

Allergic rhinitis; Circular RNA; MicroRNA; mRNA; Nasal mucosa

\textbf{CONFLICT OF INTEREST}

The authors declare that they have no conflicts of interests.

\textbf{AUTHOR CONRTIBUTIONs}

Chang-Yu Qiu performed data analysis and wrote the draft manuscript.
Qing Yang performed RT-PCR. Mei-Ping Lu, Min Yin, Wan-Yun Xu, Xin-Jie
Zhu, and Xin-Yan Cui collected samples and performed specimen quality
screening. Lei Cheng designed the study and finalized the manuscript.
All authors approved the final version of the manuscript.

\textbf{FUNDING INFORMATION}

This study was supported by a grant (No.81970862) from the National
Natural Science Foundation of China.

Chang-Yu Qiu\textsuperscript{1}, Qing Yang\textsuperscript{1}, Mei-Ping
Lu\textsuperscript{1}, Min Yin\textsuperscript{1,2}, Wan-Yun
Xu\textsuperscript{1}, Xin-Jie Zhu\textsuperscript{1}, Xin-Yan
Cui\textsuperscript{1}, Lei Cheng\textsuperscript{1,2*}

\textsuperscript{1}Department of Otorhinolaryngology \& Clinical Allergy
Center, The First Affiliated Hospital, Nanjing Medical University,
Nanjing, China

\textsuperscript{2}International Centre for Allergy Research, Nanjing
Medical University, Nanjing, China

\textbf{Correspondence}

Lei Cheng, MD, PhD, Department of Otorhinolaryngology \& Clinical
Allergy Center, The First Affiliated Hospital, Nanjing Medical
University, 300 Guangzhou Road, Nanjing 210029, China.

E-mail:chenglei@jsph.org.cn



\textbf{Figure legends}

\textbf{Figure 1. DEcircRNA-DEmiRNA-DEmRNA crosstalk network.} The
network includes 17 miRNAs (red nodes), 11 circRNAs (green nodes), and
29 mRNAs (yellow nodes). CircRNAs and miRNAs were annotated using
circBase and miRbase, respectively. Novel circRNAs and miRNAs were
described in terms of their genome location. circRNA, circular RNA;
miRNA, microRNA; DE, differentially expressed.

\textbf{Figure 2. Bioinformatics analysis of the
DEcircRNA-DEmiRNA-DEmRNA network. (A)} GO terms pertaining to biological
processes, cell components, and molecular functions,
respectively.\textbf{(B)} KEGG analysis of the transcripts involved in
different biological pathways. Bar plot depicting the enrichment score
of significantly enriched pathways. circRNA, circular RNA; miRNA,
microRNA; DE, differentially expressed; GO, gene ontology; KEGG, Kyoto
encyclopedia of genes and genomes.



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