Keywords
psoriatic arthritis - aterosclerosis - carotid intima–media thickness - cell adhesion molecules - pentraxin 3
Schlüsselwörter
psoriasis-arthritis - arteriosklerose - karotis-intima-media-dicke - zelladhäsionsmoleküle - pentraxin 3published online 2022
Introduction
Psoriatic arthritis (PsA) is an inflammatory disease characterized not only by joint
and skin involvement, but also by an higher prevalence of cardiovascular (CV) risk
factors and a greater risk of subsequent cardiovascular disease (CVD) compared to
the general population [1]. CVD is responsible
for 20–56% of all deaths in these patients [2]. Conventional CV risk factors such as
obesity, hypertension (HT), impaired fasting glucose, and hyperlipidemia have been
shown to be more common in patients with PsA [3]. However, the increase in CV morbidity and mortality cannot be fully
explained by traditional risk factors. Chronic inflammation is also an important
factor accelerating atherosclerosis in PsA patients with no known risk of CVD [4]. Due to increased CV morbidity and
mortality, all rheumatologists should be aware of the need for accurate CV risk
estimation and CVD detection, even in subclinical stages of atherosclerosis.
Carotid ultrasound is a non-invasive, well-validated and reproducible imaging
modality that determines subclinical vascular disease and ultimately CVD risk. An
increased carotid intima-media thickness (CIMT) as an early predictor of
atherosclerosis have been demonstrated previously in PsA patients with no known risk
of CVD [4]. In addition, it has been suggested
that many biomarkers of the ongoing low-grade systemic inflammation during the
development of atherosclerosis may be useful in determining CV risk in these
patients [3].
Inflammation is an important component of the atherosclerotic process and is
characterized by leukocyte infiltration of the vascular endothelial wall. Binding of
neutrophils to the endothelium leads to endothelial damage. Cell adhesion molecules
(CAMs) are structural cell components that are presented on the cell surface with
certain stimuli and play a role in the leukocyte-endothelial cell interaction in
inflammation. There are four main groups of adhesion molecules: the integrin family,
the immunoglobulin superfamily, selectins, and cadherins [5]. E-selectin plays a key role in leukocyte
tethering and rolling on the endothelium. The members of the immunoglobulin
superfamily including intercellular adhesion molecule 1 (ICAM-1) and vascular
adhesion molecule 1 (VCAM-1) are responsible for endothelial adhesion and
penetration of leukocytes. Proinflammatory cytokines and C-Reactive Protein (CRP)
produced during acute and chronic inflammation promote endothelial expression of
ICAM-1 and VCAM-1 [6]. The expression of
VCAM-1, ICAM-1, and E-selectin are found to be related to the severity and prognosis
of atherosclerosis in patients with known coronary artery disease [7].
Pentraxin 3 (PTX-3), from the same family as CRP (pentraxins), is another biomarker
of CVD. PTX-3 has been shown to regulate the inflammatory response in
atherosclerosis [8]. Data from animal models
indicate that the inflammatory reaction of the vascular wall and macrophage
accumulation in the plaque may be related to PTX-3 [9]. An association between elevated PTX-3 levels and increased CVD risk
and mortality has been reported in the healthy population [10]. Cell adhesion molecules are believed to
mediate the vascular effects of PTX-3 [11].
Angiogenesis and endothelial dysfunction are the major inflammatory pathways
associated with atherosclerosis. Many biomarkers (PTX-3, E-selectin, angiopoietin,
endothelial cell specific molecule 1, asymmetrical dimethylarginine, von Willebrand
factor) can be used to evaluate endothelial dysfunction which is the earlier phase
of vascular diseases [12]. An upregulation of
CAMs is associated with increasing in angiogenesis. The expression of angiogenic
factors (vascular endothelial growth factor (VEGF), fibroblast growth factor (FGF),
platelet-derived growth factor (PDGF) angiopoietins, and soluble CAMs) and
anti-angiogenic factors (angiostatin, endostatin, PTX-3) is regulated by
proinflammatory cytokines in rheumatic diseases, there by promoting angiogenesis in
atherosclerotic plaques [13].
Angiogenesis is also an essential stage in the pathogenesis of PsA. In a clinical
study comparing the joint microenvironments of patients with PsA and those with
rheumatoid arthritis (RA), pro-angiogenic factors including VCAM-1, ICAM-1,
E-Selectin were found to be significantly more expressed in the PsA synovial
fibroblast culture (PsA SFC) than in the RA SFC [14]. Since neo-angiogenesis plays an important role in the progression of
both atherosclerotic plaque and synovial inflammation, CAMs and PTX-3 may predict
CVD in patients with PsA. The performance of PTX-3 and CAMs as candidate biomarkers
of atherosclerosis has not previously been studied together in patients with PsA.
The aim of this study was to determine the relationship between serum VCAM-1,
ICAM-1, E-selectin, PTX-3 levels and CIMT in PsA patients without CV
comorbidity.
Materials and Methods
Subjects
This cross-sectional study included 43 PsA patients who applied to the Manisa
Celal Bayar University Hafsa Sultan Hospital rheumatology outpatient clinic
between February 2019 and May 2020, and 37 healthy controls (HCs). The patients
were classified as PsA according to the CASPAR (Classification criteria for
Psoriatic Arthritis) criteria [15].
Patients with a history of CVD (myocardial infarction, coronary artery bypass
graft surgery, coronary artery stenting), peripheral artery disease, and
cerebrovascular disease were not included in the study. Patients diagnosed with
diabetes mellitus (DM), HT, chronic kidney disease (CKD), and chronic liver
disease were also excluded. Among the PsA patients who applied to the
rheumatology outpatient clinic at that time, those who met the study criteria
and age-matched healthy individuals selected from our clinical staff were
included in the study. The study protocol was approved by Manisa Celal Bayar
University ethics committee (dated 29.08.2018, decision number 20.478.486).
Informed consent forms were obtained from all participants before the study.
In the PsA group, disease activity was assessed using the DAS28-CRP (Disease
Activity Score) [16] and BASDAI (Bath
Ankylosing Spondylitis Disease Activity Index) [17]. The functional status of patients was evaluated using the HAQ
(Health Assessment Questionnaire) [18],
BASFI (Bath Ankylosing Spondylitis Functional Index) [19], and BASMI (Bath Ankylosing Spondylitis
Metrology Index) [20]. In addition,
psoriasis (PsO) severity was evaluated using the PASI scoring system (Psoriasis
Area and Severity Index) [21]. The
relatively new criterion DAPSA (Disease Activity index for PSoriatic Arthritis)
[22] and CPDAI (Composite Disease
Activity Index) [23] were calculated in
all patients. The quality of life was with the ASQoL (Ankylosing Spondylitis
Quality of Life) [24] and DLQI
(Dermatology Life Quality Index) [25].
Procedures and Measurements
Anthropometric measurements were performed on an empty stomach with the patients
in standing position, lightly clothed and without shoes. Body weight was
measured with an electronic scale sensitive to 0.1 kg and height was
measured with a stadiometer sensitive to 0.1 cm. Waist circumference was
measured with an inelastic measuring tape midway between the lowest rib and the
iliac crest. Body mass index (BMI) was calculated by dividing body weight (kg)
by height squared (m2).
Blood samples were collected from both patients and HCs after 12 hours of
fasting for routine biochemical tests including complete blood count,
erythrocyte sedimentation rate (ESR), CRP, lipid profile consisting of
triglycerides, total cholesterol, high-density lipoprotein (HDL), and
low-density lipoprotein (LDL) levels, fasting blood glucose, and kidney and
liver function tests. Serum was separated from the venous blood samples and
stored at − 80°C until analysis. CAMs and PTX-3 analyses
of all samples were performed at the same time. Serum VCAM-1, ICAM-1,
E-selectin, and PTX-3 concentrations were measured using enzyme-linked
immunoassays (ELISA) (BioTek Instruments Inc. Highland Park, Winooski, VT, USA).
Kit sensitivities were 22 pg/mL for the PTX-3 ELISA kit
(BioVendor, Czech Republic) and 0.6 ng/mL,
2.2 ng/mL, and 0.3 ng/mL for the ELISA kits of
VCAM-1, ICAM-1, and E-Selectin (Thermofisher Scientific, Czech Republic),
respectively.
Carotid artery doppler ultrasound examinations were conducted by a single
experienced radiologist blinded to the participants’ clinical
characteristics. The right and left carotid arteries were visualized while the
patients were in the supine position and the neck was extended. Measurements
were obtained with a Toshiba Aplio 500 ultrasound device using a superficial
linear 12 MHz probe. The CIMT was measured as the distance between the
two echogenic lines belonging to the intima-lumen interface and the
media-adventitia interface. For each participant, 3 measurements were taken from
the distal common carotid artery (the arterial segment 1 cm proximal to
the carotid bulb), bulb, and proximal internal carotid artery (the arterial
segment 1 cm distal to the carotid bifurcation) on each side and the
mean of these 6 measurements was calculated as the CIMT. Plaque was defined as a
localized thickening>1.2 mm [26]. Patients with maximum IMT>0.9 mm and/or
the presence of plaque were classified as subclinical atherosclerosis [27].
Statistical Analysis
The data were recorded and analyzed using IBM SPSS Statistics version 24.0 (IBM
Corp, Armonk, NY, USA). In the statistical analysis of continuous data,
normality of distribution was assessed using Kolmogorov-Smirnov test. Depending
on the results of the normality test, numerical data were compared between
independent groups using independent samples T-test or Mann-Whitney U test and
categorical variables were compared using Pearson’s chi-square or
Fischer’s exact test. A two-tailed p value less than 0.05 was accepted
as significant for all tests. Relationships between variables were examined
using Spearman correlation analysis (r value).
Multiple regression analysis was used to determine the most important predictors
of CIMT. Automatic stepwise regression analyses were employed with the CIMT in
all subjects and CIMT in patients with PsA as dependent variables and CAMs,
PTX-3, age, BMI, CRP, smoking, ESR, and serum glucose, HDL-cholesterol, and
triglyceride levels as explanatory variables. All regression analyses were
checked for multicollinearity.
Results
The study included 43 PsA patients without CV comorbidity and 37 HCs. Most PsA
patients were women (62.8%), with a mean age of 42.49±11.70 years,
and a mean disease duration of 9.37±7.96 years. Age, gender distribution,
body mass index, and smoking rates were similar between the groups. The comparison
of demographic, clinical, and laboratory data between the groups and disease
activity, functional, and quality of life parameters in the patient group are
summarized in [Table 1]. Waist circumference
was significantly increased in PsA patients compared to HCs.
Table 1 Demographic, clinical, and laboratory features of
healthy controls and patients with psoriatic arthritis.
|
Variables
|
Psoriatic arthritis
|
Healthy controls
|
p
|
|
(n=43)
|
(n=37)
|
|
Age (year)
|
42.49±11.70
|
42.16±11.38
|
0.900
|
|
Sex (M/F) (%)
|
16/27 (37/63)
|
9/28 (24/76)
|
0.215
|
|
Smoking (%)
|
39.50
|
36.10
|
0.755
|
|
BMI (kg/m²)
|
29.29±5.11
|
27.84±3.25
|
0.141
|
|
Waist circumference (cm)
|
95.73±13.96
|
89.95±11.48
|
0.048
|
|
Disease duration (year)
|
9.37±7.96
|
_
|
_
|
|
BASDAI
|
4.12±2.68
|
_
|
_
|
|
BASFI
|
2.08±2.23
|
_
|
_
|
|
BASMI
|
3.16±0.94
|
_
|
_
|
|
HAQ
|
0.48±0.21
|
_
|
_
|
|
DAS28CRP
|
3.34±1.35
|
_
|
_
|
|
PASI
|
2.35±2.26
|
_
|
_
|
|
CPDAI
|
1.71±0.81
|
_
|
_
|
|
DAPSA
|
23.8±8.76
|
|
|
|
DLQI
|
4.33±3.13
|
_
|
_
|
|
ASQoAL
|
6.23±5.35
|
_
|
_
|
|
ESR (mm/h)
|
23.93±17.19
|
18.53±9.29
|
0.112
|
|
CRP (mg/L)
|
8.36±11.58
|
2.95±3.04
|
0.001
|
|
Fibrinogen (mg/dL)
|
385.50±115.48
|
306.32±69.28
|
0.007
|
|
Total cholesterol (mg/dL)
|
201.23±45.21
|
205.17±37.07
|
0.701
|
|
HDL cholesterol (mg/dL)
|
52.50±11.60
|
58.86±11.67
|
0.028
|
|
LDL cholesterol (mg/dL)
|
123.33±38.00
|
124.24±30.86
|
0.915
|
|
TG (mg/dL)
|
135.20±87.09
|
119.24±54.45
|
0.440
|
|
ICAM-1 (ng/mL)
|
425.32±89.17
|
379.19±111.15
|
0.048
|
|
VCAM-1 (ng/mL)
|
827.60±229.06
|
621.12±121.75
|
<0.001
|
|
E-selectin (ng/mL)
|
62.74±28.59
|
61.46±15.43
|
0.397
|
|
PTX-3 (ng/mL)
|
3.49±0.77
|
2.22±0.66
|
<0.001
|
|
CIMT (mm)
|
0.63±0.18
|
0.49±0.10
|
<0.001
|
M male, F female, BMI body mass index, BASDAI
Bath Ankylosing Spondylitis Disease Activity Index, BASFI Bath
Ankylosing Spondylitis Functional Index, BASMI Bath Ankylosing
Spondylitis Metrology Index, HAQ Health Assessment Questionnaire,
DAS28 Disease Activity Score of 28 joints, PASI Psoriasis
Area and Severity Index, CPDAI Composite Disease Activity Index,
DAPSA Disease Activity index for Psoriatic Arthritis, DLQI
Dermatology Life Quality Index, ASQoAL Ankylosing Spondylitis Quality
of Life, ESR erythrocyte sedimentation rate, CRP C-reactive
protein, HDL high-density lipoprotein, LDL low-density
lipoprotein, TG triglycerides, ICAM-1 intercellular cell
adhesion molecule-1, VCAM-1 vascular cell adhesion molecule-1,
PTX-3 pentraxin-3, CIMT carotid intima-media thickness;
Note: Data are presented as mean±SD.
In the PsA group, serum levels of PTX-3, ICAM-1, and VCAM-1 were significantly higher
than HCs (p<0.05 for all values) ([Table
1]). Carotid ultrasound evaluation revealed carotid plaque in one of the
PsA patients and subclinical atherosclerosis in a total of 3 (7%) patients
(two patients had CIMT>0.9 mm). There was no plaque or subclinical
atherosclerosis in the HCs group. CIMT was significantly higher in PsA patients
compared with HCs (0.63±0.18 vs. 0.49±0.10 mm,
p<0.01).
In subgroup analyses, there was no difference between smokers (38%) and
non-smokers in terms of CAMs, PTX-3, or CIMT values (p>0.05 for all
values). The PsA group included 14 patients with predominantly axial involvement, 12
patients with predominantly peripheral involvement, and 17 patients with both
peripheral and axial involvement. Serum CAMs and PTX-3 levels and CIMT were similar
in these clinical subgroups (p>0.05 for all values).
In the PsA group, 10 patients (23.8%) were receiving corticosteroids (CS), 14
patients (33.3%) were receiving nonsteroidal anti-inflammatory drugs
(NSAIDs), and 39 patients (90.7%) were receiving disease-modifying
antirheumatic drugs (DMARDs) [methotrexate, leflunomide, anti-TNF agents,
interleukin-17 (IL-17) inhibitors] . Serum CAMs and PTX-3 levels and CIMT values
showed no significant difference in patients using CS or biologic agents compared to
non-users (p>0.05 for all).
Correlation analysis in the PsA patient group showed that CIMT was positively
correlated with age, disease duration, ICAM-1, VCAM-1, and PTX-3, and negatively
correlated with GFR and albumin ([Table 2],
[Fig. 1]). Age was positively correlated
with ICAM-1 (r=0.452, p=0.002), VCAM-1
(r=0.393, p=0.009), and PTX-3 (r=0.491,
p=0.001). In the patient group, PTX-3 was positively correlated
with ICAM-1 (r=0.391, p=0.010) and VCAM-1
(r=0.401, p=0.008). Disease activity (assessed by
BASDAI, DAS28-CRP, DAPSA and CPDAI) and functional capacity (assessed by BASFI,
BASMI, HAQ) showed no significant correlation with CAMs, PTX-3, or CIMT
(p>0.05 for all values).
Fig. 1 Correlation between CIMT and (a) ICAM-1, (b) VCAM-1, (c)
E-Selectin, and (d) PTX-3 in PsA patients. CIMT carotid intima-media
thickness, ICAM-1 intercellular cell adhesion molecule-1,
VCAM-1 vascular cell adhesion molecule-1, PTX-3 pentraxin
3, PsA psoriatic arthritis.
Table 2 Correlation of CIMT with demographic and clinical
disease variables in psoriatic arthritis patients.
|
Variables
|
r
|
p
|
|
Age (year)
|
0.582
|
<0.001
|
|
Disease duration (year)
|
0.416
|
0.005
|
|
BMI (kg/m²)
|
0.073
|
0.643
|
|
Waist circumference (cm)
|
0.115
|
0.309
|
|
ESR (mm/h)
|
0.031
|
0.844
|
|
CRP (mg/L)
|
0.108
|
0.490
|
|
GFR ml/min/1.73 m²
|
-0.524
|
<0.001
|
|
Glucose (mg/dL)
|
0.274
|
0.076
|
|
Albumin (g/dL)
|
− 0.370
|
0.019
|
|
HDL cholesterol (mg/dL)
|
− 0.040
|
0.804
|
|
LDL cholesterol (mg/dL)
|
0.110
|
0.501
|
|
TG (mg/dL)
|
0.027
|
0.867
|
|
ICAM-1 (ng/mL)
|
0.433
|
0.004
|
|
VCAM-1 (ng/mL)
|
0.491
|
0.001
|
|
E-selectin (ng/mL)
|
− 0.113
|
0.471
|
|
PTX-3 (ng/mL)
|
0.690
|
<0.001
|
BMI body mass index, ESR erythrocyte sedimentation rate,
CRP C-reactive protein, GFR glomerular filtration rate,
HDL high-density lipoprotein, LDL low-density lipoprotein,
TG triglycerides, ICAM-1 intercellular cell adhesion
molecule-1, VCAM-1 vascular cell adhesion molecule-1, PTX-3
pentraxin-3
Best predictors of carotid intima-media thickness
To examine which markers best predicted CIMT, we performed automatic stepwise
regression analyses with CIMT as the dependent variable and selected laboratory
and demographic data as explanatory variables both for all subjects and for
patients with PsA ([Table 3]). Regression
model 1 (all subjects) showed that 34.5% of the variance in CIMT is
explained by age. Introducing the other biomarkers in the automatic analysis
shows a better solution with all subjects (57.3% of the variance
explained) using age, PTX-3, and VCAM-1. In patients with PsA, regression model
2 shows that 52.1% of the variance in CIMT is explained by age and
PTX-3. BMI, CRP, smoking, ESR, and serum ICAM-1, E-selectin, glucose,
HDL-cholesterol, and triglyceride levels were not significant in this
regression.
Table 3 Results of automatic stepwise multiple regression
analysis with carotid intima-media thickness (CIMT) in all subjects
and CIMT in patients with psoriatic arthritis (PsA) as dependent
variables.
|
Dependent variables
|
Explanatory
variables
|
β
|
t
|
p
|
F model
|
df
|
p
|
R² (%)
|
|
CIMT in all subjects
|
|
#1
|
Age
|
0.596
|
5.980
|
<0.001
|
30.759
|
1/65
|
<0.001
|
34.5
|
|
#2
|
Age
|
0.486
|
5.455
|
<0.001
|
30.372
|
2/64
|
<0.001
|
51.0
|
|
PTX-3
|
0.427
|
4.788
|
<0.001
|
|
|
|
|
|
#3
|
Age
|
0.421
|
4.911
|
<0.001
|
30.521
|
3/63
|
<0.001
|
57.3
|
|
PTX-3
|
0.310
|
3.409
|
0.001
|
|
|
|
|
|
VCAM-1
|
0.299
|
3.227
|
0.002
|
|
|
|
|
|
CIMT in patients with PsA
|
|
#1
|
Age
|
0.673
|
5.457
|
<0.001
|
29.779
|
1/36
|
<0.001
|
43.8
|
|
#2
|
Age
|
0.527
|
4.182
|
<0.001
|
21.107
|
2/35
|
<0.001
|
52.1
|
|
PTX-3
|
0.340
|
2.694
|
0.011
|
|
|
|
|
CIMT carotid intima-media thickness, PsA psoriatic
arthritis, PTX-3 pentraxin-3, VCAM-1 vascular cell
adhesion molecule-1
Discussion
The main finding of the present study is that PsA is characterized by higher plasma
levels of VCAM-1, ICAM-1, PTX-3, and increased CIMT as compared with HCs. There were
significant positive correlations between CIMT and plasma levels of VCAM-1, ICAM-1,
and PTX-3. In addition, in regression analyses, age and PTX-3 were found to be the
best predictors of CIMT in patients with PsA.
The development of atherosclerosis is known to be associated with classical CV risk
factors such as advanced age, increased BMI, elevated serum triglycerides,
LDL-cholesterol, and total cholesterol levels [28]. PsA patients have a higher risk of developing CV risk factors, and a
higher risk of presenting a CVD, compared to the general population. However, as in
our study, the effect of systemic inflammation on the endothelium and its
contribution to the atherosclerotic process can be better understood in patients
without conventional CV risk factors and CV comorbidity. The mean CIMT value of the
43 PsA patients in our study (0.63 mm) was similar to that reported in
previous studies and significantly higher than in the HCs group
(p<0.001) [29]
[30]
[31].
Although we found that this young patient population (mean age, 42 years) with no
atherosclerotic disease burden had an increased waist circumference and low
HDL-cholesterol levels compared to the HCs group, these findings were not correlated
with CIMT.
Identification of biomarkers that can be used in determining subclinical
atherosclerosis even years before clinical CVD is of great importance for predicting
the CV morbidity and mortality risk. Homocysteine, CRP, IL-6, ICAM-1, fibrinogen,
and uric acid were the markers shown to be associated with early atherosclerosis in
PsA patients [4]
[31]. In contrast to most studies, we did not
find a correlation between CIMT and the commonly used acute phase reactants (CRP and
ESR). This may be because most patients had normal or slightly elevated CRP and ESR
values (8.36±11.58 mg/L and
23.93±17.19 mm/h, respectively). In addition, these
parameters are acute phase markers and may not reflect a chronic inflammatory
burden. Shen and colleagues reported no association with CIMT and PsO severity, PsA
severity, or PsA treatment (NSAIDs, systemic steroids, and synthetic or biologic
DMARDs) in line with our study [32]. Of the
CAMs that mediate inflammation in both synovitis and atherosclerosis in PsA, ICAM-1
was shown to be associated with subclinical atherosclerosis [4]
[31],
whereas no such relationship has been previously reported for VCAM-1. However, in a
recent study on patients undergoing coronary angiography, it was suggested that
VCAM-1 may predict CVD risk due to its association with the prevalence of coronary
lesions [33]. Dessein et al. [34] also reported that serum VCAM-1 levels were
associated with CIMT and plaque formation in patients with RA. In our study, both
ICAM-1 and VCAM-1 were positively correlated with CIMT.
The expression of PTX-3, another biomarker of CVD, was found to be increased in PsO
patients compared to HCs and was associated with increased insulin resistance [35]
[36].
Firstly, Sunar et al. reported that elevated PTX-3 was associated with increased
CIMT in their study of 38 PsA patients [37].
Consistent with their results, we demonstrated a significant positive correlation
between PTX-3 level and CIMT. Because we excluded patients with CV comorbidity, the
relationship between PTX-3 and CIMT in our study is most likely a result of chronic
inflammatory mechanisms associated with PsA. In addition, we showed for the first
time that the most important predictors of CIMT in patients with PsA were age and
PTX-3 level. Of the other variables included in the regression model, we found no
significant correlation between CIMT and BMI, CRP, smoking, ESR, or serum ICAM-1,
E-selectin, glucose, HDL-cholesterol, or triglyceride levels. In conclusion, PTX-3
seems to be an important biomarker for increased CIMT predicting the development of
atherosclerosis in PsA patients, independent of classical risk factors such as
obesity, hyperlipidemia, impaired fasting glucose, and smoking.
An increase in CIMT was also detected in vasculitides such as giant cell arteritis
(GCA) [38]. Systemic inflammatory response
markers including IL-6, IL-1, IL-17, IL-23, VEGF, von Willebrand factor, ICAM-1, and
PTX-3 are responsible from chronic inflammation and an increase in CIMT in patients
with GCA [39]. Theoretically, secukinumab
(IL-17 inhibitor), which have been shown to be effective in the treatment of GCA
[40] and PsA [41] are likely to prevent the increase in CIMT
and thus subclinical atherosclerosis in PsA patients. Further studies are needed in
this regard.
The strengths of our study are the relatively large number of patients, the
simultaneous assessment of ICAM-1, VCAM-1, E-selectin, and PTX-3 in the serum of PsA
patients, and the careful exclusion of diseases that could interfere with the
results. A potential limitation of the current study was including patients with
other traditional cardiovascular risk factors such as smoking and obesity. However,
we observed no significant relationship between CIMT and variables associated with
these factors in our correlation and regression analyses. Another limitation of our
study was that all patients were using CS, conventional and/or biologic
DMARDs. Blood levels of biomarkers and even CIMT may be affected by the medications
used and the duration of use. It is well known that the use of NSAIDs and CS are
associated with increased cardiac risk in the general population and in rheumatic
patients. On the other hand, there has been increasing evidence in recent years that
treatment with biological DMARDs is associated with a reduced risk of developing CVD
in patients with PsO and PsA. However, our results indicated that CIMT and levels of
CAMs and PTX-3 were not associated with the use of CS or biologic agents.
This is the first study analyzing the relationship between the CAM profile together
with PTX-3 and CIMT, in PsA patients. Our results demonstrated that PsA is
characterized by increased CIMT and high levels of VCAM-1, ICAM-1, and PTX-3.
Although there was a correlation between adhesion molecules and CIMT in this study,
we found PTX-3 to be the best predictive biomarker of vascular structural damage in
patients with PsA. Therapeutic strategies targeting PTX-3 and cell adhesion
molecules, which are overexpressed during inflammation, may be effective in managing
the disease and atherosclerosis caused by chronic inflammation. However, more
studies are needed to verify the causality among these factors, as well as their
associations with different aspects of disease activity and atherosclerosis.
This study was supported by the Manisa Celal Bayar University Scientific Research
Projects Coordination Unit. Project Number: 2018–220”
Main Points
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Age and PTX-3 were found to be the best predictors of CIMT in patients with
PsA.
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PsA is characterized by higher plasma levels of VCAM-1, ICAM-1, PTX-3, and
increased CIMT as compared with HCs.
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There were significant positive correlations between CIMT and plasma levels
of VCAM-1, ICAM-1, and PTX-3.
