Validity of miR-146a an d TLR4 gene expression in predicting [601100]

Validity of miR-146a an d TLR4 gene expression in predicting
rheumatoid arthritis disease activity
Rabab Fawzy Salim1,Tohamy G. Hassan2, Basant M. Elnady3
1Department of Medical Biochemistry, Faculty of Medicine, Benha University, Benha
– Egypt.
2 Department of Orthopedic Surgery, Faculty of Medicine, Al-Azhar University,
Cairo – Egypt.
3Department of Rheumatology and Rehabilitation, Faculty of Medicine, Benha
University, Benha – Egypt.
ABSTRACT
Disease Activity Score 28 (DAS28 ) is the most widely used method for rheumatoid
arthritis(RA) disease activity evaluation. However, it may not reflect disease activity accurately being a subjective tool dependent on patient's self-health assessment and evaluation of swollen and tender joint counts. Therefore, finding a suitable blood
genetic marker for accurate monitoring of RA disease activity became essential. So
the aim of this study was to assess miR-146a and TLR4 expression in PBMCs of RA
patients and to study their value as potential molecular biomarkers for RA disease
activity in comparison to DAS28 score. This study was conducted on 51 RA patients and 15 age and sex matched healthy subjects as control group. The relative gene expression levels of miR-146a and TLR4 were determined by reverse transcriptase quantitative real time polymerase chain re action. There were highly statistically
significant differences between patients and healthy controls as regards miR-146a
(p < 0.001) and TLR4 (p < 0.004) expression. In addition, highly statistically
significant differences (p < 0.001)were observed between different patients’ subgroups as regards miR-146a and TLR4 expression. Moreover, miR-146a and
TLR4 expression levels showed significant positive correlations(p < 0.001)with those
of morning stiffness durations, tender joints counts, swollen joints counts, visual
analogue scale values, erythrocyte sedimentation rates, CRP, Anti-CCP antibody and
DAS28.MiR-146aillustrated the best perform ance characteristics particularly in
differentiating between high and moderate disease activity grades, showing highest
sensitivity and specificity (100%) (AUC: 1.0 at a cut off value of ⩾0.17).Furthermore,
there was a statistically significant increase (p < 0.001) in the expression levels of miR-146a and TLR4 in PBMCs of RA patients with ankles and/or feet joints involvement, as compared with those without involvement. Conclusion: MiR-146a
and TLR4 were overexpressed in PBMCs of RA patients and were correlated with
disease activity. However, miR-146a can be a promising biomarker for accurate monitoring of disease activity.
Keywords: MiR-146a, TLR4 , DAS28 , RA, reverse transcriptase quantitative real
time PCR.

INTRODUCTION
Rheumatoid arthritis (RA) is an autoimmune systemic disorderwhich is
characterized by chronic inflammation of sy novial tissue, causing irreversible damage
of joints (Pauley et al., 2009) .
Developing a reliable method for assessme nt of RA progression, and administered
therapy effectiveness, is time-consuming. Suggested methods often yield debatable
results (van Riel, 1992) . Although, there is no real “gold standard” available to judge
RA disease activity (Farnsen et al., 2003) , the most commonly used method for
evaluation of RA activity is the Disease Activity Score DAS28 because ofthe relative
ease of its acquisition and calculation. Th e formulas of DAS28 calculation incorporate
the number of swollen and tender joints, self-health assessment by using the visual-
analog scale (VAS), and erythrocyte sediment ation rate (ESR) or C-reactive protein
(CRP) (Barczyńska et al., 2015) .
The DAS28 may not provide accurate reflection of disease activity because
ofmultiple limitations. One of these limitations is the great weight of the count of
swollen joints in the score, as this parameter may not be precisely determined by
physical examination provided by a health-care provider. Furthermore, the DAS28
may remain increasedbecause of irreversible damage of joints, which remain tender in
spite of subsidence of the inflammatory process (Barczyńska et al., 2015) . In
addition, ankles and feet joints are not included in the DAS28, which may result in
misclassification regarding low diseas e activity or remission. Furthermore
concomitant fibromyalgia may lead to high DAS28, because of positive association of
tender points with the VAS global and tende r joint (TJ) scores. This too might result
in misclassification (Jacobs et al., 2014) .
Another limitation is the ESR use in the DAS28, since the ESR parameter is age
and gender dependent (it rises with age and is elevated in females) and is also
dependent on blood cell count (it rises with anemia).This may result in inaccurate
reflection of disease activity (Jurado, 2001) . CRP can be used in the DAS28 instead
of ESR. It is less influenced by other conditions than ESR. However, CRP possess the same drawback as ESR, i.e. changes in its lower range affect DAS28 most (Jacobs et
al., 2014) .
Based on the issues described above, applying the treat-to-target principle in a RA
patient needsaccurate and valid measurement of the activity of the disease, which has
not been achieved completely with DAS28. This has prompted us to search for blood
genetic markers for accurate monitoring of RA disease activity and to assist clinical decision-making.
Toll-like receptors (TLRs), a family of conserved pattern recognition receptors,
play crucial roles in the innate and adaptive immune systems, and are principally
expressed on cells, such as dendritic cells and macrophages.These cells act as primary
sensors that recognizeexoge nous and endogenous stimuli (Kawai and Akira,

2007). Over the past decade, TLRs have been proposed to drive inflammation in
RA(Fui and Kim, 2012) . Among the family of TLRs, TLR4 can recognize
lipopolysaccharide (LPS) which is an integral component of Gram-negative bacteria
outer membranes (Akira and Takeda, 2004). Upon ligand binding, TLR4-
mediatedsignals are stimulated by toll-interleukin-1 receptor domain-containing adaptor inducing IFN- γ (TRIF) and myeloid differentiation factor 88
(MyD88) (Takeda et al., 2003 and Lu et al., 2008) These interactions induce a
cascade of intra-cellular signaling incl uding TNF receptor-a ssociated factor 6
(TRAF6) and IL-1 receptor-associated kinase 1( IRAK1) that results in nuclear factor
kappa B (NF- κB) activation. NF- κB activation induces the transcription of pro-
inflammatory cytokines and interferons (IFNs) which initiate an inflammatory
response (Saba et al., 2014) .
MicroRNAs (miRNAs) are non-coding small RNAs that, by base pairing to
messenger RNA (mRNA) mediate mRNA cleavage, translational repression or mRNA destabilization (Filková et al., 2012) . This mode of posttranscriptional
regulation of gene expression has been recent ly found to play a role in modulating the
TLR response in a broad range of human immune cells, including monocytes,
macrophages, and T cells (O’Neill et al., 2011). Certain miRNAs were found to be
key regulators of development of immune cell and innate/adaptive immune responses
(Pauley et al., 2009) . Of these miRNAs, miR-146a, a member of the miR-146
miRNA family, emerged as a negative master regulator of TLR activation (Taganov
et al., 2006). MiR-146a was revealedto be a key regulator of the TLR4-MyD88
pathway by directly targeting IRAK1 and TRAF6 mRNAs ( Boldin et al.,
2006andZhao et al., 2011) and hence, it can dampen down and switch off the
inflammatory response to prevent over stimulation of the signal (Quinn and O’Neill,
2011) suggesting its role as a “brake on immunity” (Boldin et al., 2006 and Zhao et
al., 2011).
The aim of this study was to assess miR-146a and TLR4 expression in PBMCs of
RA patients and to study their value as pot ential molecular biomarkers for RA disease
activity in comparison to DAS28 score, considered to be the most widely used method for evaluation of RA activity.
PATIENTS AND METHODS
Study participants
Fifty-one RA patients who fulfilled the American College of Rheumatology
guidelines were enrolled in this study. Th e patients were selected during regular
follow up at the outpatients' clinic of the Rheumatology and Orthopedic Surgery Departments, Benha University Hospitals and Al-zhraa University Hospitals.Patients with any other autoimmune disorders or chronic diseases were excluded from this study.Fifteen age and sex matched apparently healthy volunteers were also recruited as a control group.
All patients were subjected to full history taking, thorough clinical examination
and assessment of disease activity by dis ease activity score of joint count (DAS -28)
(Prevo et al.,1995) . Disease duration, morning stiffness duration, self-assessment of

health measured by VAS, presence of rh eumatoid factor (RF), anti-CCP (cyclic
citrullinated peptide) and hemoglobin concentrationswere recorded. All patients were
also subjected to radiological assessment through Plain x rays of both hands and
wrists. Posterioanterior and lateral views were performed and graded according to
Larsen et al. (1977) . In addition, assessment of the status of ankle and feet joints
together with presence or absence of concomitant fibromyalgia was carried out.The patients group was further subdivided accor ding to DAS28 score into: low disease
activity (DAS28 ≤3.2), moderate disease activity (3.2<DAS28 ≤5.1), and high disease
activity (DAS28>5.1) (van Gestel et al., 1998) . All participants gave their written
consent after being informed about the purpose of the study, which was previously
approved by the Ethics Committee of Benha Faculty of medicine.
Blood sampling and processing
Blood samples (5  ml per subject) were collected by peripheral venipuncturein
EDTA-treated tubes . Peripheral blood mononuclear cells (PBMCs) were separated by
Ficoll density-gradient centrifugation method (Amos and Pool, 1976) using
FicollHistopaque
®-1077 (Sigma-Aldrich, U.S.A.).PBMCs werestored at -80 °C until
later assessment of miR-146a and TLR4 gene expression.
Total RNA extraction
Total RNA including miRNAs was extracted using miRNeasy mini kit
(Qiagen,Germany) in accordance with the manufacturer's protocol. Quantity and
quality of the extracted RNA were assessed by Nanodrop 2000 (Thermofisher
scientific, USA) .
cDNA synthesis
Extracted RNA (100 ng) was reverse transcribed using RevertAid First Strand
cDNA Synthesis Kit (Thermo Fisher Scientific, USA), in accordance with the
manufacturer's instructions.Random pr imers were used for TLR4 and GAPDH
reverse transcription, whereas s pecific reverse transcriptio n (RT) primers were used
for miR-146a and the housekeeping snRNA U6 . Stem loop primer for miR-146a was as
follows: hsa-miRNA-146a stem loop primer: GTCGTATCCAGTGCGTGTCGTGGAGTCGGCAATTGCACTGGATACGACaaccca, whereas U6 RT primer was: CGCTTCACGAATTTGCGTGTCAT (Xie et al.,
2013) . Reverse transcription was carried out on T100 thermal cycler, Bio-Rad,
Singapore.
Quantitative real-time PCR:

Real-time PCR was performed using QuantiTect® SYBR® Green PCR (Qiagen,
Germany)on Rotor-Gene Q (Qiagen, Germany). The sequences of the primers used
were: hsa-miRNA-146a forward: GGGTGAGAACTGAATTCCA; hsa-miRNA-146a
reverse: CAGTGCGTGTCGTGGAGT; U6-forward:
GCTTCGGCAGCACATATACTAAAAT and U6-reverse:
CGCTTCACGAATTTGCGTGTCAT (Xie et al., 2013) ; TLR4 forward:
CTTATAAGTGTCTGAACTCCC; TLR4 reverse: TAC

CAGCACGACTGCTCAG (Szebeni et al.,2007) ; GAPDH
forward:TGCACCACCAACTGCTTAGCand GAPDH
reverse:GGCATGGACTGTGGTCATGAG (Cicinnati et al., 2008) .Each reaction
contained 10 μl of 2 × QuantiTect® SYBR® Green PCR, 0.7 μl of 10 μM of each
primer, 1 μl of the cDNA, to a total volume of 20 μl. The optimized thermal profile
included an initial denaturation at 95 °C for 10 min, 45 cycles of denaturation at 95 °C for 30 s, annealing for 30 s at 63°C for miR-146a,66°C for U6,61°C for TLR4 and 70°C for GAPDHand extension at 72 °C for 30 s.Subsequently, at the end of the PCR
cycles, specificities of the amplified products were assessed by melting curve
analysis. Relative expression of miR-146a and TLR4 mRNA in each sample were
finally detected after normalization to snRNA U6 and GAPDHexpression respectively
and calculated as 2
^-ΔCt(Lin et al., 2003), ΔCt was calculated by subtracting the Ct of
the housekeeping gene from that of the target gene. Lower ΔCt values and higher 2^-
ΔCt indicated higher expression level of the target gene.
Statistical Analysis
The collected data were computed and statistically analyzed using Statistical
Package for the Social Science (SPSS) ve rsion 23 software. Qu antitative variables
were expressed as mean ± SD or mean±SE. Parametric data were compared using student t- test. Non parametric data were compared by Mann-Whitney U-test. Kruskal-Wallis test was used for compar ison between three groups of not normally
distributed variables. Qualitative variables were expressed as number and percentage
and were compared by Fisher's exact test. Spearmen correlations were applied for
correlating different variables.
ROC curve was used to predict the best cutoff values of 2^-
ΔCt of the expressed miR-146a and TLR4 with the optimum sensitivity, specificity, positive
predictive value (PPV) and nega tive predictive value (NPV) for prediction of RA disease
activity. In all tests, p value less than 0.05 was considered significant.

RESULTS
The RA patients and controls were matched for age (p>0.05) and sex (p>0.05). The
age ranged from 30 to 58 years with mean±SD of 41.61±6.45 years in the RA patients and from 30 to 58 years with mean±SD of 42.8±7.56 in the control group. The RA
patients group comprised 42(82.4%) females and 9(17.6%) males whereas the control
group comprised 12(80.0%) females and 3(20.0%) males. The clinical and laboratory
characteristics of the RA patients are shown in Table 1.
MiR-146a expression levels were statistically significantly higher (p<0.001) in the
RA patients (0.96±0.21) than in the control group (0.03±0.01)as shown in Figure1. In addition, TLR4 expression levels were statistically significantly higher (p<0.004) in
the RA patients(2.26±0.39) than in the control group (0.58±0.17) as shown in Figure 2.
Kruskal-Wallis test was used to compare between the patients’ subgroups (divided
according to DAS28) regarding miR-146a and TLR4 expression levels. Highly
statistically significant differences (p < 0.001)were observed between different

patients’ subgroups beinghighest in RA patie nts with the most severe disease activity
as shown in Table 2.
In addition, there were highly statistical ly significant differences as regards both
miR-146a and TLR4 expression levels among the different grades of the Larsen
score (p< 0.001). MiR-146a expression levels were highest in RA patients at grade
1and lowest at grade 5whereas TLR4 expression levels were highest in RA patients
with radiological damage at grade 5 and lowest at grade 1 as shown in Table 2.
MiR-146aand TLR4 expression levels showed significant positive
correlations(p < 0.001)with those of morning stiffness durations, tender joints counts
(TJC), swollen joints counts (SJC), VAS values, ESR, CRP, Anti-CCP antibody and
DAS28. Although TLR4 expression levels showed significant positive
correlation(p<0.05)with RFtitres, there was no significant positive correlation(p>0.05)
between miR-146a and RFtitres. Both miR-146a and TLR4 expression levels
showed no statistically signifi cant correlation (p>0.05)with any of the age, disease
durations and hemoglobin concentrations. However, there was statistically significant
positive correlation (p < 0.001)between miR-146aand TLR4 expression levels.
ROC curve was plotted to compare the performance of miR-146aand TLR4
expression in differentiating betw een different grades of DAS28 score . The best cut
off values for 2^- ΔCt of the expressed miR-146aand TLR4 with the highest,
sensitivity, specificity, PPV and NPV were determined and analyzed as shown in Table 3.
MiR-146a illustrated the best performance characteristics particularly in
differentiating between high and moderate disease activity grades showing highest
sensitivity and specificity (100%)(AUC: 1.0 at a cut off value of ⩾0.17). On the other
hand, TLR4 performance characteristicswas incomparable with that of MiR-146a. It
illustrated lower specificities in all gradesand it couldn't differentiate between low and
moderate disease activity grades being having the same cut off value of ⩾0.09.
Changes in TLR4 and miR-146a according to the presence or absence of ankles &/or feet joints involvement, irreversibly damaged joints and concomitant fibromyalgia are represented in Table 4.
Table (1):Clinical and laboratory characteristics of the RA patients
Parameter Mean ±SE
Disease duration (years) 3.29±0.36
Morning stiffness (minutes) 79.8±7.03
Number of tender joints 7.65±0.54
Number of swollen joints 6.04±0.33
VAS 5.06±0.34
DAS 28 5.19±1.41
Hemoglobin concentration (g/dL) 10.59 ±0.12
ESR (mm/h) 57.29 ±2.24
RF (U/ml) 76.0±8.14
CRP (mg/dl) 14.82 ±2.29
Anti CCP (U/ml) 42.54 ±19.15

Parameter Number (%)
DAS 28
Low activity 9 (17.6)
Moderate activity 10 (19.6)
High activity 32 (62.7)
Larsen score
Grade 1 12 (23.5)
Grade 2 12 (23.5)
Grade 3
Grade 4 15 (29.4)
1 (2.0)
Grade 5 11 (21.6)
Involvement ofankles or feet joints 29 (56.9)
Presence of irreversibly damaged joints 11 (21.6)
concomitant fibromyalgia 13 (25.5)

Figure (1): MiR-146a gene expression levels in the different studied groups

Figure (2): TLR4 gene expression levels in the different studied groups

Table (2): Changes in miR-146a andTLR4according to sex,DAS28 and Larsen scores
Parameter
miR-146a TLR4
Mean ±SE P value Mean ±SE P value
Sex
Male
Female
1.36±2.27
0.87±1.23 0.71
3.12±3.94
2.07±2.49
0.77
DAS 28
Low activity
Moderate activity
High activity
0.22±0.06
0.19±0.06 0.001*
0.40±0.13
0.60±0.26 0.001*

1.42±0.30 3.30±0.54
Larsen score
Grade 1
Grade 2
Grade 3
Grade 4
Grade 5
2.03±0.51
1.28±0.56
0.48±0.09
0.25±-
0.11±0.03 0.001* 0.23±0.06
1.16±0.35
3.19±0.95
3.64±-
4.68±0.84

0.001*
*P<0.05 is significant

Table (3): Performance characteristics of miR-146a and TLR4 expression (2^- ∆Ct) in
differentiating between different grades of DAS28
Parameter Cut off
point AUC Sensitivity Specificity PPV NPV Accuracy
P value
miR146a expression level
At low grade of DAS28 ≥0.05 0.97 100 86.7 81.8 100 91.7 0.001*
At moderate grade of DAS28 ≥0.11 0.90 100 60.0 62.5 100 76.0 0.008*
At high grade of DAS28 ≥0.17 1.0 100 100 100 100 100 0.001*
TLR4 expression level
At low grade of DAS28 ≥0.09 0.56 100 46.7 52.9 100 66.7 0.049*
At moderate grade of DAS28 ≥0.09 0.64 100 46.7 55.6 100 68.0 0.037*
At high grade of DAS28 ≥0.45 0.84 100 66.7 86.5 100 89.4 0.001*
*P<0.05 is significant
Table (4): Changes in miR-146a and TLR4according to the presence or absence of
ankles &/or feet joints involvement, i rreversibly damaged joints and concomitant
fibromyalgia
*P<0.05 is significant
DISCUSSION
Changes in miR-146a expression have been reported in different human diseases,
such as autoimmune andinflammatory diseases, sepsis, viral infections, cancer, and multiorgan failure (Li et al., 2010) .
Regarding miR-146a expression levels, the results of the present study showed a
statistically significant increase in the expr ession levels of miR-146a in PBMCs of
RA patients, as compared with healthy controls. Several previous studies confirmed Parameter  
 miR‐146a TLR4 
Mean ±SE  P value  Mean ±SE  P value 
Ankles &/or feet joints Involvement  
 Present  
 Absent   
1.52±0.32 
0.18±0.03  0.001**  
3.68±0.55 
0.38±0.05  0.001** 
irreversibly  damaged  joints  
 Present  
 Absent  
0.62±0.05 
1.05±0.26  0.15  
2.38±0.49  
1.82±0.35 0.11 
Concomitant  fibromyalgia   
 Present  
 Absent 1.134±0.26  
0.41±0.06 0.495  
2.73±0.50  
0.89±0.18 0.294

upregulation of miR-146a in PBMCs of RA patients (Pauley et al., 2008, Niimoto et
al., 2010 and Murata et al., 2010) . Furthermore, the results of the current study were
in concordance with Nakasa et al.(2008) and Stancyk et al.(2008) who stated that
miR-146a was highly expressed in RA synovial tissue and fibroblasts and its
expression mimics that of PBMCs.
The principal advantage of detecting miR-146a in circulating PBMCs of RA
patients opened the field for its utilization as a biomarkerfor monitoring the course of the disease and treatment efficacy without needing surgical intervention to get joint tissues toanalyze miRNA.
Upregulation of miR-146a in RA patients could be explained by the fact that
transcription of miRNA 146a is induced through the NF- κB-dependent pathway in
response to various pro-inflammatory immune mediators, such as LPS, IL-1 β, TNF α
and LMP1, which are increased in RA patients (Taganov et al., 2006) .
Regarding miR-146a expression levels in other autoimmune diseases, increased
expression of miR-146a in skin lesions and peripheral blood of psoriasis patients was
previously reported (Sonkoly et al., 2007 and Azab et al., 2017) .Upregulation of
miR-146a in psoriasis patients limits its use as a specific diagnostic marker for RA.
On the contrary, Tang et al.(2009) showed a 3-fold down regulation of miR-146a in
SLE patients. Also Balasubramanyam et al. (2011) reported that miR-146a
expression levels decreased significantly in PBMCs of Type 2 diabetic patients.
The controversial observations on miR-146a expression levels in different
autoimmune diseases could be attributed to different pathogenic pathways in which
miR-146a is involved in different diseases.
The result of the present study showed that miR-146a expression was positively
correlated with the morning stiffness dura tions, VAS score, ESR, CRP, TJC, SJC,
anti-CCP and DAS28. Moreover, highly statistically significant differences
(p < 0.001)were observed between different patients’ subgroups as regards miR-146a
expression, beinghighest in RA patients with the most severe disease activity and
lowest in those with low-grade disease activity.These findings could suggest the
usefulness of miR-146a as a prognostic biomarker for RA.
A previous study was in consistent with our results and reported that high miR-
146a expression levels correlated with activ e disease, whereas low expression levels
correlated with inactive disease (Pauley et al., 2008) . In addition, Abou-Zeid et al.
(2011) reported that miR-146a expression levels positively correlated with the
indicators of the disease activity and hence, it could be used as a prognostic biomarker
for RA. Furthermore, similar results were reported by Elsayed et al.(2016) .
In contrast to our results, a previous study reported that plasma level of miR-146a
expression inversely correlated with clin ical indices, such as TJC and DAS 28
score (Murata et al., 2010) .Different types of samples obtained and different stages
during the course of the disease at which the samples have been taken could explain
the discrepancy between their results and ours.
In the current study, miR-146a expression levels showed highly statistically
significant differences among the different grades of Larsen score, being highest in
grade 1 with low radiological damage and lowest in grade 5 withirreversible joint

damage. Our findings were in concordance with Niimoto et al.(2010) who stated that
the expression of miR-146a was high in PBMC s of patients with low score of Larsen
grade and patients with a high score of Lars en grade showed a low expression level of
miR-146a.
This could be attributed to the fact that down-regulation of IRAK1 and NF- κB by
increased expression of miR-146a may lead toosteoclastogenesisrepression which in
turn contribute to a decrease in joint destruct ion. It is worth to be mentioned that both
IRAK1 and NF- κB are essential molecules in octeoclastogenesis through the
activation of osteoclast precursor cells (Saba et al., 2014). Rather, it's here to notice
that the therapeutic application of miR-146a in RA stems from this finding.
Our study showed that TLR4 expression was significantly elevated in PBMCs of
RA patients, as compared with healthy controls. Consistent with our data, several
previous studies confirmed increased expr ession of TLR4 in RA peripheral blood
monocytes as well as in RA synovial tissue and synovial fluid macrophages
(Iwahashi et al., 2004, Radstake et al., 2004, Huang et al., 2007 and Sørensen et
al., 2008) . In addition, Kim et al. (2007) reported increased TLR4 in synovial
fibroblasts of RA patients compared to those from patients with osteoarthritis. These
findings could support the role of TLR4 in RA pathogenesis.
This study revealed that TLR4 expression levels in PBMCs of RA patients showed
significant positive correlations with the morning stiffness durations, VAS score, ESR, CRP, TJC, SJC, anti-CCP antibody and RF titers. Furthermore,our study
showed that there was highly statistically significant differences in the peripheral
blood TLR4 expressions according to DAS28 being highest in patients had the most
severe disease activity and lowest in those with low disease activity.
These results could be explained by Termeer et al. (2002) who stated that TLR4 is
a transmembrane receptor that, when triggered by endogenous and/or exogenous
ligands, initiates activation of NF-kB, whichin turn leads to production of numerous
pro-inflammatory cytokines and chemokines and so this contributes significantly to
disease activity during disease progression.
In the present study, there was highly statistically significant differences in TLR4
expression levels according to radiological grades of RA patients being highest in
patients who had grade5 and lowest in those who had grade 1. These results were
confirmed by (Roodsaz et al., 2008) who conducted their study on experimental
streptococcal cell wall modeland proved that TLR4 was important in the destructive
phase, and it contributed to matrix metall oproteinase-mediated cartilage damage and
osteoclast formation.Normally, activation of a counter mechanism occurs after every pro-inflammatory response to restore the immunologic balance.However,such a mechanism appears to be insufficient in RA, leading to a vicious circle of activation
andcell influx, ending in total joint destruction (Roelofs etal.,2005) .
Our results revealed thatTLR4expression levels positively correlated with that
ofmiR-146a.However,there is a negative feedback loop regulation,involving TLR4
and miR-146a, through which miR-146a down-regulates TLR4 signaling pathways by targeting IRAK1 and TRAF6 mRNAs in an attempt to tone down the immune

response and so miRNA are considered as ‘fine-tuners’ of the immune response (Saba
et al., 2014).
In the current study, the accuracy of miR-146a was superior to that of TLR4 in
differentiating between di fferent grades of DAS28 scoreand showed highest
sensitivity and specificity (100%) (AUC: 1.0 at a cut off value of ⩾0.17)in
differentiating between high and moderate grades, as shown by ROC curve,
suggesting its value as a potential biomarker for RA disease activity. Interestingly, to
our knowledge, there was no previous comparative study of miR-146a and TLR4 regarding their performance in predicting RA disease activity had been done.
As stated before, DAS28didn't take into ac countthe status of ankles and feet joints,
irreversibly damaged joints and concomitant fibromyalgia. However, the results of the present study showed a statistically signifi cant increase in the expression level of
miR-146a and TLR4 in PBMCs of RA patients with ankles and/or feet joints
involvement, as compared with those without involvement. In addition, there were no
significant differences between RA patients with irreversible damaged joints and
those without regarding miR-146a and TLR4 expression levels. Furthermore, no
statistically significant differences were observed between RA patients with
concomitant fibromyalgia and those without as regards miR-146a expression levels.
The levels of TLR4 in patients with concomitant fibromyalgia were higher than those
without but did not reach statistical significa nce.In fibromyalgia, LPS and the released
inflammatory mediators activate TLR4 causing its upregulation leading to microglial
and astrocytes activation which in turn promotes excitatory glutaminergic
neurotransmission causingcentral sensitization to pain (Littlejohn, 2015) .
Based on our findings, it is now clear that miR-146a, and to lesser extentTLR4, can
avoid DAS28 limitations and hence, can re place it in clinical practice.However,
Validation in larger study groups before clinical application is recommended.
CONCLUSION
Both miR-146a and TLR4 were upregulated in PBMCs of RA patients and were
correlated with clinical and laboratory indices as well as DAS28 and Larsen score.
However, miR-146a exhibited better performance in predicting RA disease activity, a finding that nominated miR-146a to be a promising biomarker for assessment of RA
disease activity thus avoiding subjectiv ity ofDAS28 and its other limitations.
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