Association between syndecan-4 and subclinical atherosclerosis in ankylosing spondylitis

Abstract

Background:

Despite advances in the diagnosis and treatment of ankylosing spondylitis (AS), the risk of cardiovascular complications in AS patients is still higher than in the general population. Macrophages are at the intersection of the basic pathogenetic processes of AS and atherosclerosis. Although syndecan-4 (SDC4) mediates a variety of biological processes, the role of SDC4 in macrophage-mediated atherogenesis in AS patients remains unclear. Herein, we aimed to investigate the role of SDC4 in subclinical atherosclerosis in AS patients.

Methods:

Subjects were selected from eligible AS patients and control subjects without a prior history of AS who were referred to the rheumatology outpatient clinics. All participants’ past medical records and clinical, and demographic characteristics were scanned. In addition, carotid intima-media thickness (CIMT) measurement and disease activity index measurement were applied to all patients.

Results:

According to our data, serum SDC4 level was significantly higher among AS patients compared with the control group (6.7 [1.5–35.0] ng/mL vs 5.1 [0.1–12.5] ng/mL, P < .001). The calculated CIMT was also significantly higher in AS patients than in the control group (0.6 [0.3–0.9] mm vs 0.4 (0.2–0.7), P < .001]. Additionally, serum C-reactive protein level and SDC4 level were independent predictors of AS and strongly associated with CIMT. Linear regression analysis showed that serum SDC4 level was the best predictor of CIMT (P = .004).

Conclusion:

Our data indicate that serum SDC4 levels provide comprehensive information about the clinical activity of the disease and subclinical atherosclerosis in AS patients.

1. Introduction

Ankylosing spondylitis (AS) is a chronic, progressive, and inflammatory disease of the axial skeleton and is associated with chronic inflammatory, axial back pain, oligoarthritis, and enthesitis.^[1,2] This disease not only manifests itself with joint problems but also with extraarticular problems such as uveitis, bone, kidney, and skin involvement, and intestinal, lung, and heart diseases.^[3] Previous reports have revealed that the prevalence of cardiac involvement in patients with AS is twice as high as in the general population.^[4] Since AS is a chronic, low-grade inflammatory course, subclinical atherosclerosis may develop in AS patients even in the absence of classical risk factors. Due to their pro- and antiinflammatory properties, macrophages are at the intersection of the basic pathogenetic processes of AS and atherosclerosis.^[5–7]

Syndecan-4 (SDC4) is a member of the syndecan family of major cell surface heparan sulfate proteoglycan receptors widely expressed in several tissues. This receptor has a protein core and is covalently bound by vertilinear polysaccharide chains. SDC4 mediates a variety of biological processes, including cell migration, proliferation, adhesion, endocytosis, tissue repair and regeneration, cell–matrix interactions, and matrix remodeling.^[8–11] Several studies have shown that stress factors, such as ischemia, hypoxia, and infection, can trigger the expression of SDC4 receptors.^[12,13] It is well known that macrophage-mediated vascular inflammatory responses play a crucial role in the formation of atherosclerosis.^[14–16] Yet, the role of SDC4 in macrophage-mediated atherogenesis in AS patients remains unclear. Therefore, this study investigated the role of SDC4 in subclinical atherosclerosis in AS patients.

2. Methods

2.1. Study population

In this study, subjects were selected from patients with AS who applied to the Necmettin Erbakan University Meram Medical Faculty Hospital Rheumatology outpatient clinics between January 2020 and December 2022. The control group was selected from people who applied to the cardiology outpatient clinic with nonspecific symptoms and did not have any additional diseases. The diagnosis of AS was made according to the Modified New York and American College of Rheumatology criteria.^[17] Patients with a prior history of coronary artery disease, severe valvular heart disease, congestive heart failure, atrial fibrillation, malignancy, renal failure, pregnancy, autoimmune diseases, and those under 18 years of age were excluded from the study. After applying exclusion criteria, eligible patients were included in the study as a study group. All participants’ past medical records and clinical and demographic characteristics were scanned and underwent comprehensive physical examination. In addition, carotid intima-media thickness (CIMT) measurement and disease activity index (Bath Ankylosing Spondylitis Disease Activity Index [BASDAI] measurement) were applied to all patients. BASDAI was calculated by rheumatology specialist physicians. Informed consent of all participants was taken, and approval was obtained from the local ethics committee of our hospital.

2.2. Data collection

The patient demographics, comorbidities, medications, and laboratory parameters were obtained from patient records and the hospital database. A comprehensive metabolic panel was performed to measure full blood count, liver and kidney functions, and lipid concentrations. Blood specimens were collected from the antecubital vein after 12-hour fasting before the data collection. All metabolic panel measurements were performed using an autoanalyzer (Roche Diagnostic Modular Systems, Tokyo, Japan). Syndecan-4 levels were analyzed by enzyme-linked immunosorbent assay (ELISA) using a commercial kit (IBL International, Hamburg, Germany) according to factory instructions. CIMT was measured using a Siemens Acuson S3000 ultrasound device using a 9L4 (4.0–9.0 MHz) linear transducer. The subjects’ carotid system was evaluated in B-mode, pulsed Doppler mode, and color mode, with the subject in the supine position, with their head slightly turned to the contralateral side of the carotid artery being examined. Carotid IMT is measured by calculating the space between the intimal-luminal and medial-adventitial interfaces of the carotid artery. In our study, the IMT average of both common carotid arteries was taken.

2.3. Statistical analysis

All statistical analyses were conducted using SPSS software version 24.0 for Windows (SPSS Inc., Chicago, IL, USA). Continuous data are presented as mean ± standard deviation (SD) if normally distributed, or as median (25th–75th percentiles), if not normally distributed. Continuous variables were compared using Student’s t test or the Mann–Whitney U test. Categorical variables are expressed as numbers and percentages and were analyzed using the χ² test or Fisher exact test. The effect of various variables on AS was calculated by univariate regression analysis. In these analyses, variants with unadjusted P < .1 were determined as confounding factors and were included in multivariate regression analyses to determine the independent predictors of AS. Spearman correlation analysis was used to identify factors associated with CIMT in the patient group. Linear regression analysis was performed to identify independent associates of CIMT in the patient group. A 2-tailed P < .05 was considered statistically significant during the study.

3. Results

Between January 2020 and December 2022, 48 AS patients (study group) who met the study criteria were included in the study. In the same period, 48 people were included in the study as age- and sex-matched control group. The baseline demographic, clinical, and laboratory characteristics of both groups are shown in Table 1. There was no statistically significant difference between the 2 groups in terms of clinical characteristics (P > .05). Regarding baseline laboratory values, both groups had similar laboratory properties (P > .05). Yet, serum C-reactive protein (CRP) levels were significantly higher among AS patients compared with the control group (5.2 [0.3–74.0] mg/L vs 1.4 [0.1–11.1] mg/L, P < .05). Serum SDC4 level was also significantly higher among AS patients compared with the control group (6.7 [1.5–35.0] ng/mL vs 5.1 [0.1–12.5] ng/mL, P < .001). With respect to carotid system ultrasound findings, the calculated CIMT was significantly higher in AS patients than in the control group (0.6 [0.3–0.9] mm vs 0.4 [0.2–0.7], P < .001).

Table 1.

Baseline parameters of the study population (n: 96).

Parameters	Patient group (n: 48)	Control group (n:48)	P
Age (y)	39 (20–66)	41 (22–65)	.592
Gender (males, n [%])	33 (68.8)	33 (68.8)	1.000
Heart rate (/min)	73.5 (50–100)	70.5 (55–102)	.369
WBC count (×106/µL)	7.6 (4.4–13.1)	8.1 (3.8–11.1)	.680
Hemoglobin (g/dL)	14.6 (10.2–17.3)	14.4 (10.5–18.7)	.378
Platelet count (×103/µL)	286 (143–508)	303 (151–523)	.942
Serum creatinine (mg/dL)	0.84 (0.45–1.25)	0.80 (0.56–1.10)	.766
Alanine aminotransferase (U/L)	17.6 (10.5–36.0)	17.4 (10.5–29.6)	.555
LDL (mg/dL)	96 (41–175)	104 (40–169)	.360
HDL (mg/dL)	44 (30–135)	50 (24–109)	.459
CRP (mg/L)	5.2 (0.3–74.0)	1.4 (0.1–11.1)	.007*
Syndecan (ng/ml)	6.7 (1.5–35.0)	5.1 (0.1–12.5)	<.001*
CIMT (mm)	0.06 (0.03–0.09)	0.04 (0.02–0.07)	<.001*

CIMT = carotid intima-media thickness, CRP = C-reactive protein, HDL = high density lipoprotein, LDL = low density lipoprotein, WBC = white blood cell.

^*Indicates statistically significant.

In addition, several variables were included in the univariate Cox regression analysis to demonstrate the relationship between baseline features and the presence of AS. After removing the variables that do not affect the presence of AS in univariate analysis, Cox multivariate regression analysis was performed, that identified serum CRP level and serum SDC4 level as the independent predictors of AS (Table 2). There was no relationship between BASDAI and SDC4. These 2 parameters, together with the calculated BASDAI scores were found to be independent associates of CIMT according to Spearman correlation analysis. According to linear regression analysis, serum SDC4 level was the best predictor of CIMT among the aforementioned parameters (P = .004; Table 3).

Table 2.

Univariate and multivariate binomial regression analyses demonstrating the relationship between baseline characteristics and presence of ankylosing spondylitis.

Parameters	Univariate analysis			Multivariate analysis
	OR	95% CI	P	OR	95% CI	P
CRP (mg/L)	1.116	1.029–1.210	.008*	1.106	1.012–1.208	.026*
Syndecan (ng/mL)	1.365	1.108–1.682	.003*	1.399	1.099–1.781	.006*

CRP = C-reactive protein.

^*Indicates statistically significant.

Table 3.

Correlation and linear regression analysis between CIMT and baseline characteristics in the ankylosing spondylitis patients.

Parameters	Spearman correlation analysis		Multivariate linear regression analysis
	r	P	B ± S.E.	95% CI	P
Age (y)	0.367	.010*	0.000 ± 0.000	0.000–0.001	.101
Heart rate (/min)	0.057	.699
WBC count (×106/µL)	0.125	.398
Hemoglobin (g/dL)	–0.100	.502
Platelet count (×103/µL)	0.176	.253
Serum creatinine (mg/dL)	–0.096	.516
Alanine aminotransferase (U/L)	0.023	.876
LDL (mg/dL)	–0.040	.815
HDL (mg/dL)	0.062	.744
CRP (mg/L)	0.320	.032*	0.000 ± 0.000	0.000–0.000	.500
Syndecan (ng/mL)	0.470	.001*	0.001 ± 0.000	0.000–0.001	.004*
BASDAI	0.354	.016*	0.001 ± 0.001	0.000–0.002	.206

BASDAI = Bath Ankylosing Spondylitis Disease Activity Index, CIMT = carotid intima-media thickness, CRP = C-reactive protein, HDL = high density lipoprotein, LDL = low density lipoprotein, WBC = white blood cell.

^*Indicates statistically significant.

4. Discussion

Despite advances in the diagnosis and treatment of AS, the risk of cardiovascular complications in AS patients is still higher than in the general population.^[18,19] As with other autoimmune rheumatic diseases, cardiovascular events in AS patients mostly result from the early development and rapid progression of atherosclerotic coronary lesions.^[20–23] Previous reports revealed that cardiovascular complications develop in AS patients with low or moderate cardiovascular risk, but with high clinical activity of the disease. Furthermore, a direct link has been demonstrated between the progression of subclinical carotid atherosclerosis and the clinical activity of autoimmune rheumatic diseases.^[24] Although many factors contribute to the development of cardiovascular complications in AS, it is still unknown which factors play an important role in the development of atherosclerosis in AS patients. However, recent studies have highlighted the potential role of macrophage dysfunction in the inflammatory mechanisms of various autoimmune rheumatic diseases and atherosclerosis. According to these studies, macrophage-mediated expression of proinflammatory molecules reduces new collagen synthesis and matrix metalloproteinases resulting in endothelial dysfunction, increased arterial stiffness and plaque remodeling, and ultimately vulnerable plaque rupture.^[25–27]

In our study, we investigated the relationship between subclinical atherosclerosis and disease activity using a novel biomarker known as SDC4. In terms of the detection of subclinical atherosclerosis, CIMT was used, whose reliability has been proven by many studies. According to our data, serum SDC4 level and calculated CIMT were significantly higher in AS patients compared with the control group (P < .001). The outcomes of our study comply with the result of a meta-analysis conducted by Yuan et al^[28] that revealed calculated CIMT was significantly higher in patients with AS compared with healthy controls (standardized mean differences = 0.725, 95% CI = 0.443–1.008, P < .001). It has been shown in large-scale studies that CIMT measurements are directly affected by glucose levels, TSH levels, smoking and alcohol consumption, and this issue should also be taken into consideration in the evaluation. Moreover, studies conducted by Gonzalez-Juanatey et al^[29] and Rueda-Gotor et al^[30] revealed a higher prevalence of carotid plaques in patients with AS compared with healthy controls. Although intima-media thickening was found to be strongly associated with increased arterial stiffness, endothelial dysfunction, and the atherosclerosis process in these studies, the exact mechanism was unclear. They postulated that genetic factors and persistent systemic inflammation work together in the process of atherosclerosis.^[29,30] Based on these data, we used SDC4, which is an important indicator of increased systemic inflammatory process.

SDC4, a heparan sulfate proteoglycan (HSPG), is widely expressed in endothelial and epithelial cells. It can cooperate with various receptors and play regulatory roles in different processes, including wound healing, inflammation, and atherosclerosis.^[31,32] SDC4 increases mineralization in vascular smooth muscle cells, which are important in atherosclerotic plaques.^[33] SDC1, in the same group as SDC4, an HSPG that uses different intracellular transduction mechanisms, was recently discovered to correlate with subclinical atherosclerosis in AS patients.^[33] In animal experiments, different results were found regarding the relationship between SDC4 and atherosclerosis. Hu et al^[34] found that blocking SDC4 degranulation slowed atherosclerosis in mice. Zimmer et al^[33] showed that inhibition of SDC4-mediated signaling pathways reduces vascular oxidative stress, improves endothelial function, and attenuates atherogenesis. Moreover, increased SDC4 expression in repaired areas of injured cardiac tissues has been interpreted as overexpression of SDC4 under ischemic conditions.^[35] Therefore, increased serum SDC4 levels are accepted as an indicator of the increase in the atherosclerotic process as well as the inflammatory process. In our study, we observed a positive correlation between serum SDC4 level and calculated CIMT in AS patients. This result indicates that SDC4 is likely to be a marker of subclinical atherosclerosis in AS patients and can be used as an accurate marker in determining the risk of cardiovascular complications. In addition, the results of our study can be interpreted in favor of a strong association between increased SDC4 expression and higher inflammatory activity, as well as an increased risk of cardiovascular complications.

5. Limitations

Our study has some limitations. First, it was a single-center study based on relatively small sample size. Second, serum SDC4 levels were calculated as a single measurement and not as repeated measurements, which may hinder the observation of long-term effects. Third, we did not compare the measurement of the SDC4 level with other well-known proinflammatory biomarkers for predicting subclinical atherosclerosis. Last but not least, the fact that our study sample consisted of patients who applied to our outpatient clinic limits the generalizability of the results.

6. Conclusion

Our data show that serum SDC4 levels provide comprehensive information about the clinical activity of the disease and subclinical atherosclerosis in AS patients. Due to the limited data on the effects of antirheumatic treatment options and the determination of cardiovascular risk factors associated with AS, it is very important to identify risky patients who require early diagnosis and close follow-up. In this context, SDC4 is likely to be a suitable biomarker for the early prediction of subclinical atherosclerosis in AS patients.

Author contributions

Conceptualization: Ahmet Lütfü Sertdemir, Yakup Alsancak.

Data curation: Ahmet Lütfü Sertdemir, İrem Oktay.

Formal analysis: Mustafa Duran.

Investigation: Mustafa Duran, Yakup Alsancak.

Methodology: Mustafa Çelik.

Project administration: Ahmet Taha Şahin.

Resources: Mustafa Çelik.

Software: Sefa Tatar.

Supervision: Ahmet Taha Şahin, Yakup Alsancak.

Validation: Sefa Tatar.

Visualization: İrem Oktay.

Writing—original draft: Ahmet Lütfü Sertdemir, Ahmet Taha Şahin.