Communication

Using MicroRNA Arrays as a Tool to Evaluate COVID-19

Vaccine Efficacy
Yen-Pin Lin 1 , Yi-Shan Hsieh 2 , Mei-Hsiu Cheng 2 , Ching-Fen Shen 3 , Ching-Ju Shen 4, *
and Chao-Min Cheng 1, *

1 Institute of Biomedical Engineering, National Tsing Hua University, Hsinchu 300, Taiwan
2 Taiwan Business Development Department, Inti Taiwan, Inc., Hsinchu 302, Taiwan
3 Department of Pediatrics, National Cheng Kung University Hospital, College of Medicine, National Cheng
Kung University, Tainan 701, Taiwan
4 Department of Obstetrics and Gynecology, Kaohsiung Medical University Hospital, Kaohsiung Medical
University, Kaohsiung 807, Taiwan
* Correspondence: chenmed.tw@yahoo.com.tw (C.-J.S.); chaomin@mx.nthu.edu.tw (C.-M.C.)

Abstract: In order to solve COVID-19 pandemic, the entire world has invested considerable man-
power to develop various new vaccines to temporarily alleviate the disaster caused by the epidemic.
In addition to the development of vaccines, we need to also develop effective assessment methods to
confirm vaccines’ efficacy and maximize the benefits that vaccines can bring. In addition to common
evaluation methods, vaccine-specific and temporal expression of microRNAs have been shown to
be related to vaccine efficacy or vaccine-associated diseases. In this article, we have introduced a
microRNA-array-based approach, which could be potentially used for evaluating COVID-19 vaccine
efficacy, specifically for pregnant women. As the mRNA in mRNA vaccines is decomposed by host
cells within a few days, it is considered more suitable for pregnant women to utilize the method of
vaccination during pregnancy. Moreover, pregnant women belong to a high-risk group for COVID-19,
Citation: Lin, Y.-P.; Hsieh, Y.-S.; and there is currently no appropriate vaccine to newborns. Therefore, it’s important to find improved
Cheng, M.-H.; Shen, C.-F.; Shen, C.-J.; tools for evaluation of vaccine efficacy in response to the current situation caused by COVID-19.
Cheng, C.-M. Using MicroRNA
Arrays as a Tool to Evaluate Keywords: microRNA array; COVID-19; mRNA vaccine; pregnancy; immune response
COVID-19 Vaccine Efficacy. Vaccines
2022, 10, 1681. https://doi.org/
10.3390/vaccines10101681

Academic Editor: Francesco 1. Introduction

Paolo Bianchi COVID-19 is a global infectious disease caused by SARS-CoV-2 which starting from a
cluster of pneumonia cases in Wuhan, Hubei Province, China at the end of 2019 [1]; the
Received: 5 September 2022
Accepted: 7 October 2022
cause was identified as a SARS-CoV-2 and quickly spread to many surrounding countries
Published: 8 October 2022
in early 2020, evolving into a global pandemic. In order to improve this situation, the
world has invested considerable manpower and resources to develop various COVID-19
Publisher’s Note: MDPI stays neutral vaccines. Vaccines developed in response to the outbreak have had an effective and positive
with regard to jurisdictional claims in
impact; however, efficacy assessment methods should be used to confirm their efficacy and
published maps and institutional affil-
maximize vaccine benefits.
iations.
The mRNA vaccine does not contain any virus—it contains the genetic code (mRNA)
of the spike protein on the surface of the SARS-CoV-2 virus. This is a new technology [2]
to stimulate the body’s own immune response. These vaccines contain messages from
Copyright: © 2022 by the authors.
mRNA, usually constructed from foreign proteins produced by pathogens (such as viruses)
Licensee MDPI, Basel, Switzerland.
or cancer cells as blueprints [3]. These messages allow the body to produce this antigen
This article is an open access article on its own and the cells in our body then present the antigen on their surfaces, triggering
distributed under the terms and the desired specific immune response. Henceforth, if the body is exposed to a virus,
conditions of the Creative Commons the immune system already recognizes those specific antigens from the vaccine and can
Attribution (CC BY) license (https:// fight the infection quicker and in a targeted manner. As the mRNA in mRNA vaccines is
creativecommons.org/licenses/by/ decomposed by host cells within a few days, it is considered more suitable for pregnant
4.0/). women to use this vaccination method during pregnancy. In addition, pregnant women

Vaccines 2022, 10, 1681. https://doi.org/10.3390/vaccines10101681 https://www.mdpi.com/journal/vaccines

 can fight the infection quicker and in a targeted manner. As the mRNA in mRNA vaccines
is decomposed by host cells within a few days, it is considered more suitable for pregnant
Vaccines 2022, 10, 1681 women to use this vaccination method during pregnancy. In addition, pregnant women 2 of 8
and newborns are a high-risk group, meaning more effective vaccine assessment methods
are needed to ensure their health.
Vaccine-specific and temporal expression of microRNAs have been shown to be re-
and newborns are a high-risk group, meaning more effective vaccine assessment methods
lated to vaccine efficacy or vaccine-associated diseases. Atherton et al. (2019) found mi-
are needed to ensure their health.
croRNA patterns specific to vaccine types, and saw microRNAs as potential biomarkers
Vaccine-specific and temporal expression of microRNAs have been shown to be related
that could provide valuable insights for vaccine development [4]. Oshiumi H. (2021) sug-
to vaccine efficacy or vaccine-associated diseases. Atherton et al. (2019) found microRNA
gested thespecific
patterns importance of extracellular
to vaccine types, and vesicle microRNAs
saw microRNAs as tools tobiomarkers
as potential improve vaccine ef-
that could
ficacy and to act as biomarkers in predicting immune response and adverse
provide valuable insights for vaccine development [4]. Oshiumi H. (2021) suggested reactions after
vaccinations[5].
the importance Small regulatoryvesicle
of extracellular microRNAs also have
microRNAs fundamental
as tools to improveroles in regulating
vaccine efficacy
the
andexpression and functions
to act as biomarkers in of key immunological
predicting mediators
immune response andsuch as cytokines
adverse reactions[6–8].
after
These research[5].
vaccinations publications have found
Small regulatory microRNAs
microRNAs to be fundamental
also have involved in manyrolesimmune reg-
in regulating
ulatory pathways
the expression andfunctions
and have potential
of keyapplications in vaccine
immunological research.
mediators such as cytokines [6–8].
These research publications have found microRNAs to be involved in many immune
2.regulatory
Methods pathways and have potential applications in vaccine research.
Vaccination is the most commonly used method in the world today to prevent the
2. Methods
spread of bacteria and viruses. Vaccination against COVID-19 can not only prevent infec-
tion, but it can also
Vaccination protect
is the mostuscommonly
from serioususedillness
methodor death
in the from
worldCOVID-19. However,
today to prevent the
assessing
spread of vaccine
bacteria efficacy is anVaccination
and viruses. important step toward
against vaccine
COVID-19 canselection. Comparing
not only prevent and
infection,
evaluating the protect
but it can also effectiveness
us from of serious
each vaccine
illnesscan provide
or death frombetter vaccination
COVID-19. recommenda-
However, assessing
vaccine
tions andefficacy is an
facilitate important
significant step toward
follow-up vaccine selection. Comparing and evaluating
impacts.
the effectiveness of eachtwo
There are primarily vaccine
formscan of provide better vaccination
vaccine efficacy evaluation recommendations
methods: (1) humoral and
facilitate significant follow-up impacts.
immunity [9], referred to as “antibody production” [10] (Antibody production); and (2)
There
cellular are primarily
immunity, which twocan forms of vaccine
be roughly dividedefficacy
into Tevaluation methods:
cell response [11] and(1) humoral
Quanti-
immunity
FERON [9], referred
Array [12,13]. Into addition
as “antibody production”
to the [10] (Antibody
above methods, we hope thatproduction);
we can alsoandevalu-
(2) cel-
lular
ate immunity,
vaccine which
efficacy viacan be roughlyexpression
a microRNA divided into T cell response
profiling [11] and
array (Figure 1). QuantiFERON
We intend to
Array the
assess [12,13]. In of
effects addition
COVID-19 to thevaccination
above methods,
among wevaccinated
hope that we can also
pregnant evaluate
women andvaccine
non-
efficacy via a microRNA expression profiling array (Figure 1). We
vaccinated pregnant women by investigating real-time microRNA expression profiles intend to assess the effects
of COVID-19
with a MIRAscan vaccination among vaccinated
and NextAmp™ Analysispregnant
System. women and non-vaccinated pregnant
women by investigating real-time microRNA expression profiles with a MIRAscan and
NextAmp™ Analysis System.

Figure 1. Three methods to evaluate COVID-19 vaccines effectiveness.

Figure 1. Three methods to evaluate COVID-19 vaccines effectiveness.
The NextAmp™ Analysis System was developed as a molecular diagnostic device
designed to detect andAnalysis
The NextAmp™ analyze System
the genewas
expression of multiple
developed biomarkers
as a molecular based on
diagnostic poly-
device
merase chain
designed reaction
to detect andamplification
analyze the genetechnology. The of
expression core component
multiple of the system
biomarkers facilitat-
based on pol-
ing multi-gene
ymerase chain reaction is a 36 mm ×technology.
analysisamplification 36 mm × 1The mmcore
reaction chip called
component of theasystem facil-® ,
PanelChip
which multi-gene
itating consists of analysis
2500 nanowells,
is a 36 mm with
× 36each
mm nanowell representing
× 1 mm reaction one areal-time
chip called PCR
PanelChip ®,

reaction well [10]. MIRAscan is a microRNA PanelChip ® consisting of 83 different microR-

which consists of 2500 nanowells, with each nanowell representing one real-time PCR
NAs related to various diseases. MIRAscan microRNA analysis service is provided by Inti
Taiwan, Inc., whose vision is to help increase IVF success rates through more personalized
and accessible molecular testing solutions. These microRNA candidates were selected from
miDatabase™, a comprehensive microRNA database consisting of data from over 30,000
publications. After a sample was loaded into the MIRAscan microRNA PanelChip® , it was
 reaction well [10]. MIRAscan is a microRNA PanelChip® consisting of 83 different
microRNAs related to various diseases. MIRAscan microRNA analysis service is provided
by Inti Taiwan, Inc., whose vision is to help increase IVF success rates through more per-
Vaccines 2022, 10, 1681 sonalized and accessible molecular testing solutions. These microRNA candidates were 3 of 8
selected from miDatabase™, a comprehensive microRNA database consisting of data
from over 30,000 publications. After a sample was loaded into the MIRAscan microRNA
PanelChip
then loaded®, into
it was
Q then loaded
Station™ forinto
qPCRQ Station™ for qPCR
reaction and reaction
subsequent and subsequent
analysis, analy-
resulting in raw
sis, data
Cq resulting
values in depicting
raw Cq data values depicting
microRNA expressionmicroRNA
levels. expression levels.
The resulting microRNA expression profiles were normalized, and microRNAs microRNAs with-with-
out amplification
amplification signals
signalsacross
acrossall
allprofiles
profileswere
wereremoved.
removed. Based
Based on on
the the experimental
experimental de-
design,
sign, thethe number
number ofof differentiallyexpressed
differentially expressedmicroRNAs
microRNAsfor foreach
eachcomparison
comparisonwerewere iden-
iden-
tified (|ΔCq| ≥≥1).
tified (|∆Cq| 1).Once
Oncethe thedifferentially
differentiallyexpressed
expressedmicroRNAs
microRNAswere were found,
found, miRTarBase
miRTarBase
was
was used for microRNA target target interaction (MTI) analysis. miRTarBase
miRTarBase is is one
one of the largest
databases of experimentally validated microRNA-target interactions interactions (Figure
(Figure 2). WeWe fil-
fil-
tered out MTIs
MTIs withwithless
lessthan
than3 3reference
referencesupport
support and
and non-functional
non-functional MTIs.
MTIs. Gene
Gene set
set en-
enrichment analysis
richment analysis using
using clusterProfiler
clusterProfiler waswas
thenthen performed
performed onresulting
on the the resulting
gene gene list
list from
from MTI. Gene ontology, KEGG pathway and disease ontology were
MTI. Gene ontology, KEGG pathway and disease ontology were used for functional anal- used for functional
analysis
ysis due due to their
to their long-standing
long-standing curation.
curation. We We hopehope
the the resulting
resulting microRNA
microRNA data
data cancan be
be used for vaccine efficacy assessment and to provide a reference for subsequent
used for vaccine efficacy assessment and to provide a reference for subsequent vaccine vaccine
administration
administration planning.
planning.

Figure 2. microRNA candidate discovery services provided by Inti Taiwan Inc. with MIRAscan mi-
Figure 2. microRNA candidate discovery services provided by Inti Taiwan Inc. with MIRAscan
croRNA assay. MIRAscan is a microRNA PanelChip®®consisting of 83 different microRNAs related
microRNA assay. MIRAscan is a microRNA PanelChip consisting of 83 different microRNAs related
to various diseases. There are two spike-in controls for the MIRAscan microRNA assay: one is RT
to various
spike-in diseases.
control, theThere
otherare two spike-in
is qPCR spike-incontrols
control.for the MIRAscan
These microRNA
two controls are usedassay: one iscon-
to ensure RT
spike-in control, the other is qPCR spike-in control. These two controls are used to ensure
sistency and quality for the cDNA synthesis process and qPCR reaction process, respectively. consistency
and quality for the cDNA synthesis process and qPCR reaction process, respectively.
3. Results—Clinical Samples from Two Pregnant Women
3. Results—Clinical Samples from Two Pregnant Women
The entry of SARS-CoV-2 into human host cells is mediated by the SARS-CoV-2 spike
The entry of SARS-CoV-2 into human host cells is mediated by the SARS-CoV-2 spike
protein located on the surface of the virus [14]. An mRNA vaccine for COVID-19 provides
protein located on the surface of the virus [14]. An mRNA vaccine for COVID-19 provides
our bodies with the code to produce the non-infectious viral spike protein in order to di-
our bodies with the code to produce the non-infectious viral spike protein in order to
rect cells
direct cellstotohelp
helpstimulate
stimulateaanatural
naturalimmune
immuneresponse.
response. This
Thisresponse
response is is mainly
mainly achieved
achieved
through the production of T cells and neutralizing antibodies against
through the production of T cells and neutralizing antibodies against SARS-CoV-2, which SARS-CoV-2, which
circulate in the body and immediately bind to the virus and prevent it from entering cells,
circulate in the body and immediately bind to the virus and prevent it from entering cells,
thus protecting
thus protectingus usfrom
fromgetting
gettingsicksick easily.
easily. T cells
T cells helphelp
thethe immune
immune system
system fightfight intracel-
intracellular
lular infections
infections andalso
and can cankill
alsoinfected
kill infected cells directly.
cells directly. Thus,Thus, in contrast
in contrast to traditional
to traditional vac-
vaccines,
cines, mRNA vaccines do not contain any viral proteins themselves,
mRNA vaccines do not contain any viral proteins themselves, but only the information our but only the infor-
mation
own our
cells own
need tocells needthe
produce to produce the viral
viral signature thatsignature thatdesired
triggers the triggers the desired
immune immune
response [15].
response [15]. Each of the three COVID-19 vaccines described above
Each of the three COVID-19 vaccines described above induces an immune response against induces an immune
SARS-CoV-2, and after our first encounter with a particular bacterium or virus, in the
years or decades that follow, adaptation cells can remember them -this is what we call
immune memory [16], if you come into contact with a real virus or bacteria in the future,
the immune system will remember it, produce antibodies against it, and quickly activate
the right immune cells, thereby killing viruses or bacteria and protecting us from disease.
Vaccines 2022, 10, 1681 4 of 8

In this study, maternal blood samples from pregnant women were collected after the
doctor personally explained the research study content and obtained the patients agreement
for participating in the study. Patients then signed the consent form for specimen collection
that also included information such as vaccine type, dose, gestational weeks at the time
of administration, side effects, etc. for subsequent analysis. Maternal blood samples were
subsequently collected during delivery time. These samples were from the patients at Taiwan’s
Kaohsiung Medical University Chung-Ho Memorial Hospital (KMUHIRB-SV(II)-20210087).
The microRNAs detected in the plasma of pregnant women who had received three
doses of the Moderna vaccine (M1) and pregnant women who had not received any vaccine
(M2) were analyzed, and the ∆Cq (∆Cq(M1 vs. M2)) of each microRNA was calculated. To
identify differentially expressed microRNAs, the following selection criteria was applied:
|∆Cq| ≥ 1 (including ∆Cq ≥ 1 and ∆Cq ≤ −1). Comparative analysis showed that 7
microRNAs had |∆Cq| values greater than 1 between sample source types: hsa-miR-1972,
hsa-miR-191-5p, hsa-miR-423-5p (∆Cq (M1-M2) < −1); hsa-miR-16-5p, hsa-miR-486-5p,
hsa-miR-21-5p, hsa-miR-451a (∆Cq (M1-M2) > 1) (Table 1). When comparing ∆Cq (M1-M2)
values, those that were negative indicated that microRNAs were overexpressed in samples
from subjects that received three doses of COVID-19 vaccine (M1) compared to samples
from subjects that received no vaccine (M2).

Table 1. Clinical information and differential microRNA expression between two pregnant women
with different vaccination histories.

Clinical Data
3 doses (M1) No dose (M2)
Parity 2 3
Age (year) 36 40
BMI 21.797 28.377
Weeks of gestation at delivery 40 39
Kind of COVID-19 vaccine for first/
Moderna/Moderna/Moderna -/-/-
second/ third dose
Normalized Cq value
3 doses (M1) No dose (M2) ∆Cq (M1-M2)
hsa-miR-1972 7.8294 11.0089 −3.1795
hsa-miR-191-5p 9.2544 11.2722 −2.0178
hsa-miR-423-5p 10.7744 12.7122 −1.9378
hsa-miR-16-5p 8.3869 6.1593 2.2276
hsa-miR-486-5p 9.8724 7.5511 2.3213
hsa-miR-21-5p 9.1844 7.6378 1.5466
hsa-miR-451a 8.0427 5.0866 2.9561
MIRAscan was used to detect 83 microRNAs’ expression profiles in plasma samples collected from two pregnant
women. Additionally, selection criteria to identify differentially expressed microRNAs were as follows: |∆Cq| ≥ 1
(including ∆Cq ≥ 1 and ∆Cq ≤ −1); microRNAs highlighted in orange indicate overexpression of microRNAs in
the vaccinated, three-dose group (M1) while those highlighted in green represent overexpression of microRNAs
in the unvaccinated, no-dose group (M2).

Gene set enrichment analysis of pathway terms and gene ontology (GO) terms were
performed using the differentially expressed microRNAs as input. The background gene
set based on validated microRNA target interaction were from miRTarbase. A total of 3 of
the pathways identified in the top 10 biological processes Enrichment GO terms are closely
related to immune regulatory pathways after vaccination, including positive regulation
of protein modification process, positive regulation of tumor necrosis factor superfamily
cytokine production, and adaptive immune response (Table 2). The top 10 biological
process pathway Enrichment GO terms are organized in a network, where each pathway
is a node and edges represent gene overlap between pathways. Mutually overlapping
Vaccines 2022, 10, 1681 5 of 8

gene sets tend to cluster together, making it easy to quickly identify the major enriched
functional themes and interpret the enrichment results (Figure 3).

Table 2. Top 10 biological process Enrichment Gene Ontology (GO) terms.

ID Description GeneRatio BgRatio p Value (Adjust)

Vaccines 2022, 10, 1681
GO:0009628 response to abiotic stimulus 77/232 441/2689 1.06 × 10−7
GO:0031401 positive regulation of protein modification process 73/232 433/2689 1.28 × 10−6
GO:0060548 negative regulation of cell death 73/232 439/2689 1.67 × 10−6
Gene set enrichment analysis of pathway terms and gene ontology (GO)
GO:0060485 mesenchyme development 32/232 130/2689 9.37 × 10−6
performed using the differentially expressed microRNAs as input. The backg
GO:0043085 positive regulation of catalytic activity 76/232 494/2689 1.07 × 10−5
set based on validated microRNA target interaction were from miRTarbase.
GO:0050673 epithelial cell proliferation 40/232 205/2689 4.97 × 10 −5
of the pathways identified in the top 10 biological processes Enrichment GO
GO:0070848 response toclosely related to immune regulatory
growth factor 54/232 pathways
333/2689 after vaccination,
0.00014 including p
ulation
positive regulation of tumor necrosisoffactor
protein modification process, positive regulation of tumor necros
superfamily
GO:1903557 14/232 39/2689 0.00022
cytokineperfamily
production cytokine production, and adaptive immune response (Table 2). The
GO:0046649 logical
lymphocyte process pathway Enrichment
activation 44/232 GO 265/2689
terms are organized 0.00050in a network,
GO:0002250 pathway
adaptive immune response is a node and edges represent
24/232 gene overlap
115/2689 between
0.00109pathways. Mu
lapping
GeneRatio = Ratio of input gene setswere
genes that tend to cluster
annotated per term.together,
Input genesmaking it easy
are regulated by theto quickly identif
differentially
expressed microRNAs
enrichedanalyzed from the Cq
functional value data
themes andsets.interpret
BgRatio = ratio
theofenrichment
all genes that were annotated
results in
(Figure 3).
this term. The p-values were adjusted using the “BH” (Benjamini-Hochberg) method.

Figure 3. Enrichment map of the top 10 biological process (BP) Enrichment GO terms organizes them
Figure 3. Enrichment map of the top 10 biological process (BP) Enrichment G
into a network with edges connecting overlapping gene sets. The input genes used for enrichment
organizes them into a network with edges connecting overlapping gene sets.
analysis are regulated by the differentially expressed microRNAs identified between the plasma
samples of twogenes usedwomen,
pregnant for enrichment analysis
one who received aredoses
three regulated by thevaccine
of COVID-19 differentially
while the express
other receivedcroRNAs identified
no vaccinations. between
Pathways the plasma
highlighted samples
in red indicate close of two pregnant
relationships women, on
to immune
ceivedafter
regulatory pathways three doses of COVID-19 vaccine while the other received no vaccinati
vaccination.
ways highlighted in red indicate close relationships to immune regulatory pa
4. Discussion
after vaccination.
Most microRNAs regulate gene expression by inhibiting protein translation or by
degrading the mRNA transcript. A single microRNA may regulate the expression of
Table
multiple genes and 2.
itsTop 10 biological
encoded proteins.process Enrichment
microRNAs are not Gene Ontologyin(GO)
only involved terms.the
regulating
innate immune system, but also have been implicated in regulating adaptive immunity by
ID Description GeneRatio BgRatio

GO:0009628 response to abiotic stimulus 77/232 441/2689

GO:0031401 positive regulation of protein modification process 73/232 433/2689
Vaccines 2022, 10, 1681 6 of 8

controlling the development and activation of T and B cells [17]. During the past few years,
many microRNAs have been found to be important in the development, differentiation,
survival, and function of B and T lymphocytes, dendritic cells, macrophages, and other
immune cell types. After vaccination, innate sensors are triggered by the intrinsic adjuvant
activity of the vaccines, resulting in production of type I interferon and multiple pro-
inflammatory cytokines and chemokines. RNA sensors such as Toll-like receptor 7 (TLR7)
and MDA5 are triggered by the mRNA vaccines [18]. Researchers demonstrated that
IFN-g expressions in NK cells after 1st vaccine doses correlated with SARS-CoV-2 vaccine-
induced neutralizing antibody [19]. Analyzing the expression of immune related proteins
and cytokines has the potential to be a tool for assessing the relevance of vaccine-induced
immunity. Vaccine efficacy depends on immune responses, such as proinflammatory
cytokine production and lymphocyte activation. Proinflammatory cytokine production
are caused by immune responses to antigens, leading to production of antigen-specific
antibodies. The immune-regulatory microRNA levels in serum extracellular vesicles (EVs),
such as miR-148a levels were associated with specific antibody titers, and could be potential
biomarkers for vaccine efficacy [20].
Preliminary small-scale experiments were carried out on a new PCR array-based
platform for samples that were collected from vaccinated and unvaccinated pregnant
women. After analyzing the microRNA Cq values from each data set, seven microRNAs
with different expression between vaccinated and unvaccinated pregnant women sam-
ples were found. Among these seven microRNAs, hsa-miR-486-5p was also found to be
differentially expressed in plasma between pregnant women in their first trimester com-
pared to non-pregnant women [21]. MicroRNAs have been found to regulate different
mechanisms specific to pregnant women as substantial changes occur in the body to sup-
port the developing fetus [21]. Further experiments are still needed for the differential
expression of microRNAs of participants with physiological status in the future to find
out whether pregnant women have unique microRNA expression profiles due to specific
immune regulations.
According to the GO databases, among the identified genes regulated by differen-
tially expressed microRNAs, 14 genes (such as interleukin-6 (IL6), signal transducer and
activator of transcription 3 (STAT3), Toll-like receptor 3 (TLR3), etc.) were involved in the
positive regulation of the tumor necrosis factor superfamily cytokine production pathway,
while 24 genes participated in the adaptive immune response pathway (Table 3). Both
of these biological pathways are related to immune regulation. Through their effect on
the production of cytokines and proteins related to immune regulation, microRNAs may
further affect the production of antibodies. More experiments are still needed to confirm the
relationship between the differential expression of microRNAs, the production of cytokines
and proteins, and antibody response.
Vaccines 2022, 10, 1681 7 of 8

Table 3. Differentially expressed microRNAs and their target interaction genes participated in the
two pathways related to immune regulation in the top 10 enrichment Gene Ontology (GO) terms of
biological process.

* Differentially Expressed
ID Pathway Description ** Gene ID
microRNAs
hsa-miR-16-5p
positive regulation of tumor APP/CLU/HMGB1/IFNG/IL1A/ hsa-miR-21-5p
GO:1903557 necrosis factor superfamily IL6/IL12B/MIF/MYD88/PIK3R1/ hsa-miR-191-5p
cytokine production STAT3/TLR3/BCL10/RASGRP1 hsa-miR-451a
hsa-miR-486-5p
JAG1/BCL6/CLU/MTOR/MSH6/
HMGB1/ICAM1/IFNG/IL1B/IL6/ hsa-miR-16-5p
GO:0002250 adaptive immune response IL6R/IL12A/IL12B/SMAD7/MEF2C/ hsa-miR-21-5p
MSH2/MYD88/STAT3/TAP1/TSC1/ hsa-miR-451a
UNG/BCL10/DUSP10/ICOSLG
* The differentially expressed microRNAs selected were identified between the plasma samples of two preg-
nant women, one who received three doses of COVID-19 vaccine while the other received no vaccinations.
** Gene ID= gene-centered information at NCBI website. APP: amyloid beta precursor protein, CLU: clusterin,
HMGB1: high mobility group box 1, IFNG: interferon gamma, IL1A: interleukin 1 alpha, IL6: interleukin 6,
IL12B: interleukin 12B, MIF: macrophage migration inhibitory factor, MYD88: MYD88 innate immune signal
transduction adaptor, PIK3R1: phosphoinositide-3-kinase regulatory subunit 1, STAT3: signal transducer and
activator of transcription 3, TLR3: Toll-like receptor 3, BCL10: BCL10 immune signaling adaptor, RASGRP1: RAS
guanyl releasing protein 1, JAG1: jagged canonical Notch ligand 1, BCL6: BCL6 transcription repressor, MTOR:
mechanistic target of rapamycin kinase, MSH6: mutS homolog 6, ICAM1: intercellular adhesion molecule 1, IL1B:
interleukin 1 beta, IL6R: interleukin 6 receptor, IL12A: interleukin 12A, SMAD7: SMAD family member 7, MEF2C:
myocyte enhancer factor 2C, MSH2: mutS homolog 2, TAP1: transporter 1, ATP binding cassette subfamily B
member, TSC1: TSC complex subunit 1, UNG: uracil DNA glycosylase, DUSP10: dual specificity phosphatase 10,
ICOSLG: inducible T cell costimulator ligand.

5. Conclusions
The roles and regulatory mechanisms of these microRNAs in immune regulation
still require additional examination to confirm the relationship between microRNAs and
antibody responses among different physiological status and backgrounds. However,
through this preliminary study, the production of antibodies after vaccination can be linked
to the regulation of genes and microRNAs before the protein translation process. For
subsequent vaccine efficacy evaluation, microRNA expression may be used as a valuable
tool for real-time monitoring of antibody effects.

Author Contributions: Conceptualization, Y.-P.L., C.-M.C. and C.-J.S.; methodology, Y.-S.H., M.-H.C.,
C.-M.C. and C.-J.S.; software, Y.-P.L. and Y.-S.H.; validation, Y.-P.L., Y.-S.H. and M.-H.C.; formal
analysis, Y.-P.L., Y.-S.H., M.-H.C., C.-F.S., C.-M.C. and C.-J.S.; investigation, Y.-P.L. and Y.-S.H.;
resources, C.-M.C., C.-F.S. and C.-J.S.; data curation, Y.-P.L., Y.-S.H., M.-H.C., C.-M.C. and C.-J.S.;
writing—original draft preparation, Y.-P.L. and Y.-S.H.; writing—review and editing, C.-F.S., C.-
M.C. and C.-J.S.; visualization, Y.-P.L., Y.-S.H. and C.-M.C.; supervision, C.-M.C. and C.-J.S.; project
administration, C.-M.C. and C.-J.S.; funding acquisition, C.-F.S., C.-J.S. and C.-M.C. All authors have
read and agreed to the published version of the manuscript.
Funding: This research was funded by the Taiwan’s National Science and Technology Council (NSTC
111-2314-B-006-085 & NSTC 111-2628-E-007-005-MY2) and Taiwan’s Kaohsiung Medical University
Hospital (KMUH110-0M42).
Institutional Review Board Statement: The study was conducted according to the guidelines of the
Declaration of Helsinki, and approved by the Institutional Review Board of Kaohsiung Medical Uni-
versity Hospital (IRB No. KMUHIRB-SV(II)-20210087, an ethic review committee, on 7 August 2021).
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.
Data Availability Statement: Not applicable.
Conflicts of Interest: The authors declare no conflict of interest. The funders had no role in the
current study.
Vaccines 2022, 10, 1681 8 of 8

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