全身染毒暴露系统，全身染毒系统

Identification of molecular biomarkers associated with neutrophilic asthma (NA) phenotype may inform the discovery
of novel pathobiological mechanisms and the development of diagnostic markers. Three mRNA transcriptome datasets
extracted from induced sputum of asthma patients with various inflammatory types were used to screen for macrophage-
related molecular mechanisms and targets in NA. Furthermore, the predicted targets were also validated on an independent
dataset (N = 3) and animal model (N = 5). A significant increase in total cells, neutrophils and macrophages was observed
in bronchoalveolar lavage (BAL) fluid of NA mice induced by ovalbumin/freund’s adjuvant, complete (OVA/CFA). And
we also found elevated levels of neutrophil and macrophage infiltration in NA subtype in external datasets. NA mice had
increased secretion of IgE, IL-1β, TNF-α and IL-6 in serum and BAL fluid. MPO, an enzyme present in neutrophils, was also
highly expressed in NA mice. Then, weighted gene co-expression network analysis (WGCNA) identified 684 targets with
the strongest correlation with NA, and we obtained 609 macrophage-related specific differentially expressed genes (DEGs)
in NA by integrating macrophage-related genes. The top 10 genes with high degree values were obtained and their mRNA
levels and diagnostic performance were then determined by RT-qPCR and receiver operator characteristic (ROC) analysis.
Statistically significant correlations were found between macrophages and all key targets, with the strongest correlation
between ITGAM and macrophages in NA. Double-Immunofluorescence staining further confirmed the co-localization of
ITGAM and F4/80 in NA. ITGAM was identified as a critical target to distinguish NA from healthy/non-NA individuals,
which may provide a novel avenue to further uncover the mechanisms and therapy of NA.
Keywords Neutrophilic Asthma · Transcriptome · Macrophages · WGCNA · ITGAM
Qian Yan, Zixing Liu and Yujing Chen have contributed equally to
this work.
* Yong Jiang
jiangyongszzxy@163.com
* Shaofeng Zhan
zsfstone@163.com
* Xiufang Huang
huangxiufang@gzzyydx17.wecom.work
1
The First Affiliated Hospital of Guangzhou University
of Chinese Medicine, Guangzhou, China
2
Guangzhou University of Chinese Medicine, Guangzhou,
China
3
Shenzhen Hospital of Integrated Traditional Chinese
and Western Medicine, Shenzhen, China
4
Lingnan Medical Research Center of Guangzhou, University
of Chinese Medicine, Guangzhou, China
5
Guangdong Provincial Clinical Research Academy
of Chinese Medicine, Guangzhou, China
6
Haikou hospital of Chinese traditional medicine, Haikou,
China
7
Lingnan Medical Research Center of Guangzhou,
University of Chinese Medicine, the First Affiliated Hospital
of Guangzhou University of Chinese Medicine, 12 Airport
Road, Guangzhou 510405, People’s Republic of China
Apoptosis
1 3
Abbreviations
EA
Eosinophilic asthma
NA
Neutrophilic asthma
MA
Mixed-granulocytic asthma
PGA
Pauci-granulocytic asthma
NNA
Non-neutrophilic asthma
S100A9
S100calcium-binding protein A9
BAL
Bronchoalveolar lavage
MPO
Myeloperoxidase
ROC
Receiver operator characteristic
FC
Fold change
GO
Gene ontology
KEGG
Kyoto Encyclopedia of Genes and Genomes
WGCNA Weighted gene co-expression network analysis
PPI
Protein-protein interaction
AUCs
Areas under the curves
OVA
Ovalbumin
CFA
Freund’s adjuvant, complete
HE
Hematoxylin and eosin
PAS
Periodic acid-Schiff
PCA
Principal component analysis
BP
Biological processes
DEGs
Differentially expressed genes
GS
Gene Significance
MM
Module membership
SA
Severe asthma
Introduction
The symptoms of asthma include hyperreactivity of the air-
ways, reversible limitations of airflow, mucus overproduc-
tion and remodeling of the airway wall [1]. Over 300 million
people worldwide suffer from this condition, with significant
economic and health implications [2, 3]. It is necessary to
determine the asthma phenotype as it varies in phenotype
and response to treatment. Based on sputum inflamma-
tory cells counts, asthma patients can be categorized into
various inflammatory phenotypes, including eosinophilic
asthma (EA), neutrophilic asthma (NA, neutrophils ≥ 61%
and eosinophils < 3%), mixed-granulocytic asthma (MA) or
pauci-granulocytic asthma (PGA) [4]. Patients with NA are
commonly prone to developing steroid resistance and pro-
gressing to severe or refractory asthma [5]. Nonetheless, the
complete cellular and molecular mechanisms responsible for
NA remain to be comprehensively elucidated and suitable
biomarkers for NA phenotype classification and prediction
are still lacking.
In addition to eosinophils and neutrophils, there are other
cell types, such as macrophages, monocytes and epithelial
cells, all with their own characteristics [6]. Macrophages
play an important multifunctional role as innate immune
cells in the airways and their dysregulation is associated with
the development of asthma [7]. In addition to promoting
airway inflammation, macrophage polarization also con-
tributes to airway repair and remodeling processes [8]. The
cytokines IL-8 and IL-17 secreted by Th17 cells and TNF-α
primarily produced by macrophages, have been identified as
the primary inflammatory mediators involved in the devel-
opment of neutrophilic inflammation [9–11]. Fricker et al.
confirm that specific transcriptomic changes exhibited by
macrophages in sputum may be closely related to the neu-
trophil inflammatory response in NA by bulk RNA-Seq and
bioinformatic analyses [12]. A recent study utilizing gene
set variation analysis (GSVA) and whole sputum microar-
ray analysis find that changes in macrophage gene expres-
sion profiles may contribute to alterations in the sputum
transcriptomes of NA patients [13]. It has been found that
S100 calcium-binding protein A9 (S100A9) is significantly
increased in serum and bronchoalveolar lavage (BAL) fluid
samples of NA mice and that S100A9 activates M0 mac-
rophages to enhance the expression of CD68 and iNOS,
which can be reversed by the anti-S100A9 antibody [14].
The above studies suggest that macrophages may be an
important biomarker in the pathogenesis of NA. Neverthe-
less, more research is required to establish the pathogenesis
of lung macrophages in NA.
Despite the pathogenesis of NA is not fully compre-
hended, the accumulating relevant transcriptomic and bio-
informatic analyses provide a basis for assessing pathogen-
esis and immune targets. For example, Hern-Tze Tian Tan
et al. confirm the upregulation of NLRP3, IL-1β, caspase-1
and IL-1 pathway members in NA by whole-genome tran-
scriptome profiling of mouse model lungs [15]. Fricker et al.
confirm that phlegm macrophages may be closely related to
neutrophilic inflammatory responses in NA by bulk RNA-
seq and bioinformatic analyses [12]. However, no effective
biomarkers have been identified to evaluate the prognosis of
NA and to guide the subsequent therapeutic regimen of NA.
In this study, an NA mouse model was established to
observe high infiltration of neutrophils and macrophages
in BAL fluid. Meanwhile, induced sputum mRNA expres-
sion profiles were analyzed in asthma patients with different
inflammatory phenotypes and controls to identify potential
biomarkers, immune-related signal pathways and mecha-
nisms related to macrophages. The diagnostic performance
of potential gene signatures was verified by RT-qPCR on NA
mice and receiver operator characteristic (ROC) analysis on
independent validation datasets. The findings of this study
established a bioinformatics framework for unraveling the
molecular mechanisms and creating effective gene signa-
tures for the diagnosis and treatment of NA. The flow chart
was displayed in Fig