Bioinformatic analysis of microRNA and mRNA Regulation in peripheral blood mononuclear cells of patients with chronic obstructive pulmonary disease
Dang et al. Respiratory Research
Bioinformatic analysis of microRNA and mRNA Regulation in peripheral blood mononuclear cells of patients with chronic obstructive pulmonary disease
Xiaomin Dang 0
Xiaoyan Qu 1
Weijia Wang 1
Chongbing Liao 1
Ying Li 1
Xiaojin Zhang 1
Dan Xu 1
Carolyn J. Baglole
Dong Shang 0
Ying Chang 1
0 Department of Respiration, The First Affiliated Hospital, Xi'an Jiaotong University , Xi'an 710061, Shaanxi province , China
1 Center for Translational Medicine, The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology and Frontier Institute of Science and Technology, Xi'an Jiaotong University , Xi'an 710049, Shaanxi province , China
Background: Chronic obstructive pulmonary disease (COPD) is a progressive, irreversible chronic inflammatory disorder typified by increased recruitment of monocytes, lymphocytes and neutrophils. Because of this, as well as the convenience of peripheral blood nuclear cells (PBMCs) assessments, miRNA profiling of PBMCs has drawn increasing attention in recent years for various disease. Therefore, we analyzed miRNA and mRNA profiles to understand their regulatory network between COPD subjects versus smokers without airflow limitation. Methods: miRNA and mRNA profiling of PBMCs from pooled 17 smokers and 14 COPD subjects was detected by high-throughput microarray. The expression of dysregulated miRNAs were validated by q-PCR. The miRNA targets in dysregulated mRNAs were predicted and the pathway enrichment was analyzed. Results: miRNA microarray showed that 8 miRNAs were up-regulated and 3 miRNAs were down-regulated in COPD subjects compared with smokers; the upregulation of miR-24-3p, miR-93-5p, miR-320a and miR-320b and the downregulation of miR-1273 g-3p were then validated. Bioinformatic analysis of regulatory network between miRNA and mRNA showed that NOD and TLR were the most enriched pathways. miR-24-3p was predicted to regulate IL-18, IL-1β, TNF, CCL3 and CCL4 and miR-93-5p to regulate IκBα. Conclusions: The expression of miRNA and mRNA were dysregulated in PBMCs of COPD patients compared with smokers without airflow limitation. The regulation network between the dysregulated miRNA and mRNA may provide potential therapeutic targets for COPD.
miRNA; COPD; PBMC; Microarray; MicroRNA
Chronic obstructive pulmonary disease (COPD) is a
progressive, irreversible chronic inflammatory disorder.
Caused predominantly by cigarette smoking, COPD is
one of the leading causes of mortality globally .
Although cigarette smoking is the major cause of
COPD, there is currently no satisfactory therapy to
treat individuals once the disease is established.
Inflammation plays a pivotal role in the disease process, with
CD8+ T lymphocytes, neutrophils and macrophages
being the main type of immune cells of local
inflammatory milieu of COPD . Different immunoregulatory
properties of T cells and monocytes have been
demonstrated in COPD patients , and the inflammatory
response in the lungs of COPD patients is strongly linked
to tissue destruction and alveolar airspace enlargement
, in part due to the loss of lung structural cells due
to heightened apoptosis.
© The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
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microRNAs (miRNAs) are a growing family of small
non-coding RNAs (approximately 19 to 25 nucleotides
long) with a regulatory function on gene expression .
Through binding to the 3′ untranslated region (3′ UTR)
of target messenger RNAs, miRNAs can lead to direct
inhibition of protein translation or degradation of
messenger RNA . In addition, miRNAs can alter gene
expression by targeting transcription factors and DNA
methyltransferases. In this way, miRNAs work as
posttranscriptional regulators of gene expression and control
various cellular processes such as differentiation,
proliferation, and cell-cell interaction. The dysregulation of
miRNAs is linked to a wide spectrum of diseases,
including proliferative vascular disease, cardiac disorders, lung
diseases, kidney diseases, diabetes mellitus, fibrosis and
A few studies have been conducted to reveal the
dysregulation and role of miRNAs in COPD. Ezzie et al.
 compared the miRNA expression in lung tissue
derived from smokers with and without COPD and
identified 70 differentially expressed miRNAs. A report by
Pottelberge et al.  demonstrated that 34 miRNAs
were differentially expressed between never-smokers
and current smokers without airflow limitation, and 8
miRNAs were expressed at a significantly lower level in
current-smoking patients with COPD compared with
never-smokers without airflow limitation. Another
study showed that microRNA-34c is associated with
emphysema severity in COPD . Sato et al. 
observed reduced miR-146a expression in lung fibroblasts
of patients with COPD and showed that miR-146a
deficiency increased the expression of PGE2 through
depression of the miR-146a target COX-2. Finally, Lewis
et al.  found downregulated miR-1 expression in
quadriceps muscles and speculated that this is linked to
the muscle weakness observed in COPD.
On account of the convenience of peripheral blood
nuclear cells (PBMC) assessments, the miRNA profiling
of PBMC has drawn increasing attention in recent years
in various diseases such as cancer [14, 15], Alzheimer’s
Disease , diabetes  and autoimmune disease .
However, there is no report regarding miRNA
expression profiles of PBMC in COPD patients. Therefore, in
this study, we sought to determine if miRNAs were
differentially expressed in PBMCs of COPD patients and
if miRNA expression may be linked to dysregulated
mRNA expression relevant to the pathogenesis of
COPD. We analyzed miRNA and mRNA expression
profiles in PBMCs from COPD patients versus smokers
without airflow limitation. The mRNA targets of the
dysregulated miRNA were predicted and pathway
enrichment was analyzed. We identified a signature of
COPD-associated miRNA, such that miR-24-3p,
miR93-5p, miR-320a, miR-320b and miR-1273g-3p were
significantly dysregulated in COPD patients.
Bioinformatic analysis between miRNA and predicted mRNA
showed that NOD and TLR were the most enriched
pathways. In NOD pathway, miR-24-3p was predicted
to regulate IL18/IL1B/TNF, and miR-93-5p to regulate
NLRP3/IL6/NFKBIA. In TLR pathway, miR-24-3p was
predicted to regulate CCL3/CCL4/IL1B/TNF, and
miR93-5p to regulate IL6/CXCL10/NFKBIA.
Peripheral venous blood was taken in heparin-coated
tubes from 17 smokers without airflow limitation and 14
COPD subjects at Department of Respiration, The First
Affiliated Hospital, Xi’an Jiaotong University, Xi’an,
China. COPD subjects were eligible for this study if
they met the following criteria: age ≥ 50 and ≤76 years;
smoking history (≥20 pack-years); post-bronchodilator
FEV1 ≥ 25% of predicted value and post-bronchodilator
FEV1/forced vital capacity (FVC) ≤ 0.70; no history of
asthma, atopy (as assessed by an allergy skin prick test
during screening) or any other active lung disease.
Patients on home oxygen or with raised carbon dioxide
tension (>44 mmHg), α1-antitrypsin deficiency, recent
exacerbation (in the last 4 weeks), an uncontrolled
medical condition or hypersensitivity to inhaled
corticosteroids and bronchodilators were not eligible for the
study. All smokers without airflow limitation met the
following criteria: age ≥ 42 and ≤75 years, Post-BD FEV1%
predicted >80, no diagnostic cancer, diabetes,
cardiovascular disease and hypertension, no use of inhaled or oral
corticosteroids in the previous 6 months, no atopy, and no
respiratory tract infection 1 month prior to the study.
Patient characteristics are in Table 1. The
experimental procedures were performed with ethical approval
from the Research Ethics Boards of The First Affiliated
Hospital, Xi’an Jiaotong University (2015–015).
Table 1 Clinical characteristics of smokers without airflow
limitation and COPD patients
Post-BD FEV1% predicted
PBMC isolation and RNA extraction
PBMCs were isolated from venous blood by density
gradient centrifugation over Ficoll-Paque PLUS reagent
(GE Healthcare, Uppsala, Sweden) and suspended in
QIAzol Lysis Reagent (Qiagen, Dusseldorf, Germany).
Total RNA was extracted using miRNeasy Mini Kit
(Qiagen) according to the manufacturer’s procedure.
RNA integrity was determined by formaldehyde
denaturing gel electrophoresis.
miRNA and gene expression microarray
Equal amount of RNA sample from each smokers (N = 17)
and COPD patients (N = 14) was pooled respectively for
miRNA profiling assay using Affymetrix GeneChip
miRNA Array v.4.0 (Affymetrix, Santa Clara, CA, USA)
by Capitalbiotech company, Beijing, China. Briefly, after
labeled with Biotin, the total RNA was subsequently
hybridized overnight. The GeneChip® miRNA 4.0 arrays,
containing 30,424 total mature miRNA probe sets
including 2,588 mature human miRNAs and miRNAs of
202 other organisms, were washed and stained using
the Affymetrix GeneChip Hybridization Wash and
Stain Kit and were then scanned with the Affymetrix
GeneChip® Scanner 3000 (Affymetrix, Santa Clara, CA,
Messenger RNA microarray
Samples were prepared for mRNA microarray analysis
using Agilent Human Gene Expression Microarray
V4.0 (Santa Clara, California, USA). Hybridized slides
were then washed and scanned with Agilent Microarray
Scanner System (G2565CA).
The miRNA and mRNA array data were analyzed for
data summarization, normalization and quality control
using GeneSpring V11.5 software (Agilent). To select
differentially expressed genes, we used threshold values
of >2 fold change. The data were Log2 transformed and
median centred by genes using the Adjust Data function
of CLUSTER 3.0 software. Further analysis was
performed by hierarchical clustering with average linkages.
Finally, we performed tree visualization using Java
Treeview (Stanford University School of Medicine, Stanford,
Quantitative reverse transcription PCR validation
Independent assays were performed using quantitative
reverse transcription PCR (qRT-PCR) on all patient
samples for individual miRNA (miR-24-3p, miR-93-5p,
miR-320a, miR-320b, miR-191-5p, let-7b-5p,
miR-3423p, miR-92a-3p, miR-3613-3p, miR-1273 g-3p and
miR4668-5p) (Qiagen) and predicted target genes (IL18,
IL1B, TNF, CCL3, CCL4, NLRP3, IL6, NFKBIA and
CXCL10) (Bio-rad, Foster city, USA). In addition, the
expression of miR-24-3p, miR-93-5p, miR-320a,
miR320b and miR-1273 g-3p was detected on the isolated
different cell types including CD4+ T cells, CD8+ T
cells, CD20+ B cells and CD14+ monocytes from
PBMCs in some COPD patients by positive selection
(Anti-PE MicroBeads UltraPure, Miltenyi Biotec,
Teterow, Germany). Data were presented relative to U6
for miRNA and β-actin for target genes based on
calculations of 2(−σσCt). The primer sequences for target
genes were listed in Table 2. Statistical significance was
defined as p < 0.05 as measured by the t test using
GraphPad Prism 5 software (GraphPad, San Diego, CA,
Target prediction and network analysis
The target genes for miRNAs were predicted using
miRanda, MirTarget2, PicTar, PITA and TargetScan. The
regulation network diagram between miRNAs and
mRNAs was generated using Cytoscape. Based on the
data of mRNA array, the predicted target genes that
negatively regulated by the validated dysregulated
miRNAs were selected for the further pathway enrichment
analysis. The DAVID  online analysis tool was used
and the significant enrichment threshold was P value of
Modified Fisher exact less than 0.05 and enriched gene
count more than 2.
Table 2 The sequence of primers for real-time PCR
MicroRNAs are dysregulated in PBMCs of COPD patients
We investigated the miRNA profiling in pooled PBMCs
from 17 smokers without airflow limitation and 14
COPD patients (Fig. 1). Compared with smokers, there
were 103 up-regulated and 34 down-regulated miRNAs
in COPD patients. We selected the dysregulated
miRNAs with differences in the fluorescence intensity higher
than 1000 between the smokers and COPD patients. As
shown in Table 3, there were a total of 8 up-regulated
and 3 down-regulated miRNA; these were selected for
the further validation and analysis.
Validation of dysregulated miRNAs in PBMCs of COPD
Among the selected 11 dysregulated miRNAs in COPD
patients versus smokers, we validated the expression of
5 miRNAs (miR-24-3p, miR-93-5p, miR-320a, miR-320b
and miR-1273 g-3p) in smokers and COPD patients by
qRT-PCR, as shown in Fig. 2a. MiR-1273 g-3p was the
most highly expressed miRNA in PBMCs of smokers,
while miR-320a and miR-320b had the higher relative
abundance in PBMCs of COPD patients (Fig. 2b). The
correlation analysis between miRNA expression and
FEV1% predicted showed that significant negative
relevance appeared in the expression of miR-24-3p,
miR320a and miR-320b and positive relevance appeared in
miR-1273 g-3p (Fig. 2c). However, there is no difference
Table 3 Selected dysregulated miRNAs in COPD patients
compared with smokers without COPD
in miRNA sets between ex- and current smokers in the
smokers and COPD groups.
Verification of expression of dysregulated miRNAs in
different cell types of PBMCs
PBMCs consist mainly of T lymphocytes, B lymphocytes
and monocytes. We therefore analyzed the expression of
dysregulated miRNAs in the isolated different cell types
including CD4+ T cells, CD8+ T cells, CD20+ B cells and
CD14+ monocytes from PBMCs of smokers and COPD
patients. MiR-24-3p was consistently expressed higher in
monocytes. In smokers, miR-93-5p was mainly expressed
Fig. 1 Hierarchical clustering and scatter plot result of differentially expressed miRNAs in PBMCs from smokers and COPD patients. a Hierarchical
clustering image of miRNA expression of pooled RNA samples from PBMCs of COPD patients compared to smokers without airflow limitation.
b Scatter plot of miRNA expression of PBMCs of COPD patients compared to smokers without airflow limitation. Red and green colored dots
represent up- and down- regulated miRNAs in scatter plot, respectively
Fig. 2 (See legend on next page.)
(See figure on previous page.)
Fig. 2 Validation of differentially expressed miRNAs. a Expression of selected miRNAs in PBMCs of smokers and COPD patients. qRT-PCR was
performed on the same RNA samples (17smokers and 14 COPD patients) as microarray analysis. Data are presented as 2(−σσCt) relative to U6.
*P < 0.05, **P < 0.01 compared with smokers by Mann Whitney U test. b Relative abundance of differentially expressed miRNAs in PBMCs of
smokers and COPD patients. *P < 0.05, **P < 0.01 compared with smokers. c Correlation analysis between miRNA expression and FEV1% predicted
in monocytes, while it was equally expressed in CD4+
T cells, CD8+ T cells and monocytes in COPD patients.
CD8+ T cells mainly contribute to the increased expression
of miR-320a and miR-320b in COPD patients. In COPD
patients, more miR-1273 g-3p was expressed in monocytes,
suggesting that the expression was decreased in CD4+ T
cells, CD8+ T cells and CD20+ B cells in COPD (Fig. 3).
mRNAs are dysregulated in PBMCs of COPD patients
We performed a parallel mRNA microarray study to
compare the mRNA expression between the smokers
and COPD patients. The results revealed a total of 1508
genes that differed in expression between the two groups
(fold change >2; Fig. 4), where 164 mRNAs were
upregulated and 137 were down-regulated when filtered by
Fig. 3 Expression of miRNAs in the isolated different cell types of PBMCs from smokers (a) and COPD patients (b). The expression of miR-24-3p,
miR-93-5p, miR-320a, miR-320b and miR-1273g-3p was examined by qRT-PCR on CD4+ T lymphocytes, CD8+ T lymphocytes, CD20+ B lymphocytes
and CD14+ monocytes from smokers and COPD patients. Data are presented as 2(−σσCt) relative to β-actin
Fig. 4 Hierarchical clustering and scatter plot result of differentially expressed mRNAs in PBMCs from smokers and COPD patients. a Hierarchical
clustering image of mRNA expression of pooled RNA samples from PBMCs of COPD patients compared to smokers without airflow limitation.
b Scatter plot of mRNA expression of PBMCs of COPD patients compared to smokers without airflow limitation. Red and green colored dots
represent up- and down- regulated mRNAs in scatter plot, respectively
fluorescence intensity difference higher than 1000.
Table 4 shows the 20 genes with the largest fold changes
and their known biological functions.
Regulation network of dysregulated miRNAs and mRNAs
Based on the genes negatively correlated with miRNAs
from microarray, the predicted regulatory network
between the dysregulated miRNAs (that were validated)
and mRNAs in COPD patients was then analyzed (Fig. 5,
Table 5). The KEGG pathway enrichment analysis
indicated that the NOD − like receptor (NLR) and Toll − like
receptor (TLR) signaling pathway relevant to the
pathogenesis of COPD were significantly enriched (Fig. 6).
The involved genes include IL18/IL1B/TNF predicted to
be regulated by miR-24-3p, and NLRP3/IL6/NFKBIA by
miR-93-5p for NLR pathway. The genes CCL3/CCL4/
IL1B/TNF were predicted to be regulated by miR-24-3p,
and IL6/CXCL10/NFKBIA by miR-93-5p for TLR
pathway. The expression level of relevant predicted target
genes of individual subjects were further validated by
qRT-PCR. As shown in Fig. 7, the expression of IL18,
IL1B, TNF, NFKBIA, CCL3 and CCL4 was validated, but
not for NLRP3, IL6 and CXLC10.
MicroRNAs play important regulatory roles in cell
differentiation, cell cycle and apoptosis. Due to the role of
multiple gene regulation, miRNAs have received much
attention as biomarkers and target for novel
therapeutics. In COPD therefore, the role of miRNAs in disease
pathogenesis is an attractive area of research. For the
first time, we conducted a comprehensive analysis of
both miRNA and mRNA expression in PBMCs from
subjects with COPD and compared their expression
profiles to smokers without airflow limitation. We identified
137 differentially-expressed miRNAs in PBMCs from
COPD subjects compared with smokers without COPD.
Among the selected 11 miRNAs, the dysregulated
expression of 5 miRNAs including miR-24-3p, miR-93-5p,
miR-320a, miR-320b and miR-1273g-3p were validated
Of the miRNA investigated in this study, miR-24-3p is
of considerable interest. It has been reported that
miR24-3p was consistently upregulated during terminal
differentiation of hematopoietic cells into a variety of
lineages as well as during muscle and neuronal cell
differentiation [20, 21]. MiR-24-3p might also function
in cell proliferation [22, 23]. Upregulation of miR-24 is
associated with a decreased DNA damage response upon
etoposide treatment in highly differentiated CD8+ T cells
, and miR-24 is a negative regulator of classical
macrophage activation by LPS . In this study, we
found increased expression of miR-24-3p mainly in the
T lymphocytes and monocytes, which might in part
Table 4 Top 10 dysregulated mRNAs in COPD patients compared with smokers without COPD
Mucin 17, cell surface associated
Interleukin 1 receptor, type II
Early growth response 3
Solute carrier family 6
(neurotransmitter transporter, noradrenalin), member 2
Transmembrane protein 167A
FCH domain only 1
Interleukin 1, alpha
Interleukin 6 (interferon, beta 2)
Chemokine (C-X-C motif) ligand 10
Tumor necrosis factor
Chemokine (C-C motif) ligand 20
Chemokine (C-C motif) ligand 4
Chemokine (C-C motif) ligand 3-like 3
Chromosome 9 open reading frame 7
Interleukin 1 receptor antagonist
Ring finger protein 19B
contribute to the increased number of CD8+ T cells in
the lung  and to the impairment of host defenses in
the lower respiratory tract due to the smoke related
changes in the phenotype of alveolar macrophages of
COPD patients .
As for the rest of dysregulated miRNAs reported in
this study, we did not find the relevant evidences
involving the pathogenesis of COPD, which implies the
discrepancy of the miRNA profile between PBMCs and
lung tissues. These miRNAs were mainly found
dysregulated in cancers and other disorders like autoimmune
diseases. For example, miR-93-5p was identified as a
potential biomarker of various types of cancer such as
acute myeloid leukemia  and laryngeal squamous cell
carcinoma . This could be due to the link between
miR-93 and promotion of tumor growth, angiogenesis
and metastasis [30, 31]. miR-93 is up-regulated in
PBMCs from adult T-cell leukemia patients, and
suppresses the expression of a tumor suppressor protein,
tumor protein 53-induced nuclear protein 1 (TP53INP1)
. Four different transcripts have been reported in the
database for miR-320 (miR-320a, b, c, and d) . The
seed region considered crucial for target binding remains
Extracellular matrix constituent
Decoy receptor, inhibits the activity of IL-1
Positive regulation of endothelial cell proliferation
EGF family, promote the growth of normal epithelial cells
Potassium channel activity
Pro-inflammatory and anti-inflammatory role
Inflammation, cause apoptosis
Calcium channel activity
Inhibition of the activities of IL-1
Cytotoxic effects of natural killer (NK) cells
the same for miR-320a, b, c, and d. The plasma level of
miR-320a was found increased in patients with systemic
lupus erythematosus (SLE) , and miR-320-3p is
increased in the plasma of non-small cell lung cancer
(NSCLC) patients . The expression of miR-1273g-3p
was found remarkably changed in Human Umbilical
Vein Endothelial Cells (HUVECs) under acute glucose
fluctuations, which was demonstrated to contribute to
endothelial dysfunction and autophagy . MiR-1273
expression is also increased in the pancreas of mouse
model of pancreatic cancer .
By analyzing the regulation network between the
dysregulated miRNA and mRNA, we predicted the negative
regulatory role of miRNAs on a total of 36 over
expressed and 61 under expressed mRNAs. The KEGG
pathway enrichment analysis indicated that the NOD −
like receptor (NLR) signaling pathway and Toll − like
receptor (TLR) signaling pathway are the top 2 pathways
likely involved in the pathogenesis of COPD, with
mir24-3p and miR-93-5p being predicted to regulate the
relevant genes in both pathways. As down-stream factors
of the NLR and TLR pathway, the mRNA levels of
proinflammatory mediators including IL-18, IL-1β, CCL3,
Fig. 5 Regulation network between miRNAs and mRNAs. The negatively regulation of miRNA on dysregulated mRNAs was predicted and the
regulation network was drawn by using Cytoscape software. Red and green color represents up- and down-regulated genes, respectively
CCL4, and TNF were found down-regulated in PBMCs
of COPD patients in this study. To the best of our
knowledge, the down-regulation of these mRNAs in
PBMCs of COPD patients has not been previously
reported. In fact, a previous study performed on human
peripheral lung tissue obtained from non-smokers,
smokers and COPD patients revealed the similar trends
of expression level of pro-inflammatory mediators,
where the level of IL-8, IL-6, IL-1β and TNF-α showed
the decreased trend in COPD patients compared with
smokers . Instead, most previous studies showed
elevated expression levels of these mediators in serum or
lung . We suspect that certain changes in the
cytokine expression profile may happen when the peripheral
immune cells infiltrate the local inflammatory sites in
the lung. The reduced expression of TLR2 has been
found in the alveolar macrophages of smokers and
COPD patients, which was associated with the
impairment of host defenses in the lower respiratory tract .
Furthermore, decreased cytokine and chemokine mRNA
expression in bronchoalveolar lavage cells from
asymptomatic smokers has been reported .
In addition, NFKBIA predicted to be regulated by
miR-93-5p- was the other down-regulated gene involved
in enriched pathways. In unstimulated cells, NF-κB is
found in the cytoplasm in an inactive non-DNA binding
form, associated with its inhibitory protein κBα (IκBα,
coded by NFKBIA gene), IκBα degradation unmasks the
nuclear localization signal present in NF-κB, allowing it
to enter the nucleus, bind DNA, and initiate gene
transcription . In the present study, the down-regulation
of IκBα supposedly trigger the activation of NF-κB,
whose expression was also higher in PBMCs of COPD
patients. The coexistence of decreased level of IκBα and
pro-inflammatory mediators in COPD patients was also
reported on lung tissue . Besides trigging the
expression of pro-inflammatory mediators, NF-κB activation
may also be related with the disordered apoptosis of
Tcell hybridoma cell line . Thus, the decreased
expression of IκBα may contribute to the dysregulated
apoptosis of T cells in COPD .
Overall, through miRNAs and mRNAs expression
profiling in smokers and COPD patients, we identified the
dysregulated miRNAs and mRNAs in PBMCs from
COPD patients. We further analyzed the regulation
network between miRNA and mRNA, where NLR and TLR
was the most enriched pathways. Among them the
regulation of IL-18, IL-1β, TNF, CCL3 and CCL4 by
miR-24-3p, and IκBα by miR-93-5p may provide the
clue for potential investigations.
The expression of miRNA and mRNA were dysregulated
in PBMCs of COPD patients compared with smokers
without airflow limitation. The regulation network
between the dysregulated miRNA and mRNA may provide
potential therapeutic targets for COPD.
Table 5 The pathway enrichment of dysregulated mRNAs regulated by miRNAs
miRNA Pathway Genes
miR-24-3p Rheumatoid arthritis IL1A/CCL3/CCL3L3/IL18/IL1B/TNF
African trypanosomiasis HBA2/IL18/IL1B/TNF
Cytokine-cytokine receptor interaction IL1A/CCL3/CCL4/CCL3L3/IL18/IL1B/TNF
Toll-like receptor signaling pathway CCL3/CCL4/IL1B/TNF
Chagas disease (American trypanosomiasis) CCL3/CCL3L3/IL1B/TNF
Graft-versus-host disease IL1A/IL1B/TNF
Type I diabetes mellitus IL1A/IL1B/TNF
Cytosolic DNA-sensing pathway CCL4/IL18/IL1B
NOD-like receptor signaling pathway IL18/IL1B/TNF
miR-320a Natural killer cell mediated cytotoxicity ICAM1/KIR2DL2/TNF
African trypanosomiasis ICAM1/TNF
Graft-versus-host disease KIR2DL2/TNF
RIG-I-like receptor signaling pathway TANK/TNF
Antigen processing and presentation KIR2DL2/TNF
Rheumatoid arthritis ICAM1/TNF
Folate biosynthesis GCH1
Graft-versus-host disease GZMB/KIR2DL2/TNF
miR-320b Graft-versus-host disease GZMB/KIR2DL2/TNF
Natural killer cell mediated cytotoxicity GZMB/KIR2DL2/TNF
Allograft rejection GZMB/TNF
Type I diabetes mellitus GZMB/TNF
Antigen processing and presentation KIR2DL2/TNF
Hypertrophic cardiomyopathy (HCM) TNF/TPM1
Dilated cardiomyopathy TNF/TPM1
Folate biosynthesis GCH1
African trypanosomiasis TNF
miR-93-5p Malaria IL6/ICAM1/THBS1
Cytosolic DNA-sensing pathway IL6/CXCL10/NFKBIA
NOD-like receptor signaling pathway NLRP3/IL6/NFKBIA
RIG-I-like receptor signaling pathway CXCL10/NFKBIA/TANK
Rheumatoid arthritis IL6/ICAM1/IL1A
Toll-like receptor signaling pathway IL6/CXCL10/NFKBIA
African trypanosomiasis IL6/ICAM1
Prion diseases IL6/IL1A
Bladder cancer CDKN1A/THBS1
Fig. 6 Pathway enrichment of dysregulated mRNAs regulated by miRNAs. The pathways in dysregulated mRNAs predicted by miRNAs were
enriched by KEGG pathway enrichment analysis. “p adjust” represents the P value range. “Gene Ratio” represents the ratio of predicted target
gene number in total gene number of each relevant pathway
Fig. 7 Validation of predicted target genes of miRNAs. The expression of predicted target genes of miRNAs in PBMCs of smokers and COPD
patients was examined by qRT-PCR. Data are presented as 2(−σσCt) relative to β-actin. *P < 0.05, **P < 0.01, ***P < 0.001 compared with smokers by
Mann Whitney U test.
COPD: Chronic obstructive pulmonary disease; NLR: NOD − like receptor;
PBMC: Peripheral blood mononuclear cell; TLR: Toll − like receptor
The authors acknowledge Dr. Yong-Ping Shao and Dr. Wuyuan Lu for their
critical revise on manuscript and valuable suggestions on study.
This study was supported by National Natural Science Foundation of China
(31501044), Natural Science Basic Research Plan in Shaanxi Province of China
(2015JQ3066), Sci-tech Research and Development Project of Shaanxi
Province of China (2016KW-026), Fundamental Research Funds for the
Central Universities (xjj2014088), the Scientific Research Foundation for
the Returned Overseas Chinese Scholars, State Education Ministry and
the Richard and Edith Strauss Canada Foundation. This work was supported in
part by Project 985 of Xi’an Jiaotong University.
XD collected blood samples. XQ isolated PBMCs, performed qRT-PCR and cell
culture and analyzed the data. WW isolated part of PBMCs. CL helped
collecting blood samples. YL performed part of cell culture. DX coordinated
the collection of blood samples. CJB revised the manuscript. DS collected blood
samples. YC designed the study and drafted the manuscript. All authors read
and approved the final manuscript.
The authors declare that there have no competing interests.
Consent for publication
Ethics approval and consent to participate
The experimental procedures were performed with ethical approval from
the Research Ethics Boards of The First Affiliated Hospital, Xi’an Jiaotong
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