Introduction

Psoriatic arthritis (PsA) is an inflammatory arthritis that can lead to significant joint damage and disability. A recent meta-analysis of observational studies reported a 43% increased risk of cardiovascular disease (CVD) and 55% increased risk of incident cardiovascular events in patients with PsA compared to the general population. In addition, an increased morbidity risk for myocardial infarction, stroke and heart failure of 68, 22 and 31%, respectively, in patients with PsA was reported in that meta-analysis [1]. When compared with patients with rheumatoid artrhritis and non- PsA spondyloarthritis, cardiovascular and metabolic comorbidities, such as hypertension, hyperglycemia, obesity, hyperlipidemia and the metabolic syndrome, were significantly higher in PsA patients [2,3,4]. Vascular comorbidities is higher in patients with PsA compared with psoriatic patients without arthritis [4,5,6,7]. This difference is independent of traditional cardiovascular risk factors and correlates with disease duration of PsA, severity of skin disease and erythrocyte sedimentation rate (ESR) [8].

Assessing clinical endpoints, such as myocardial infarction or stroke, in prospective cohort studies requires following large patients cohorts for extended periods of time. Due to this limitation, surrogate endpoints such as imaging modalities of atherosclerosis or serum biomarkers vascular and metabolic function are commonly investigated to reveal the link between PsA and CVD [9]. Among the imaging modalities, ultrasonographic assessment of carotid intima-media thickness (CIMT) is a non- invasive and reproducible imaging modality for subclinical atherosclerosis and has been widely accepted as one of the strongest predictors of major cardiovascular events [10,11,12].

For an absolute CIMT difference of 0.1 mm, the future risk of myocardial infarction increases by 10–15%, and the stroke risk increases by 13–18% [13]. Increased CIMT were reported in PsA patients without clinically evident cardiovascular disease or any traditional atherosclerosis risk factors [14].

Carbamylation is a post-translational modification in which cyanate binds to primary amino or thiol groups. Inflammation, renal insufficiency and smoking can stimulate the degree of carbamylation. Several proteins, particularly long lived proteins, can undergo carbamylation in different pathophysiological conditions [15, 16]. Antibodies against carbamylated proteins have been detected in PsA patients and are correlated with disease activity [17]. Ca-LDL can exhibits a variety of biological effects relevants to atherosclerosis, such as induction of injury to endothelial cells, cell adhesion molecule expression, attraction of monocytes, endothelial and vascular smooth muscle cells proliferation [18,19,20,21,22]. Atherogenic effect of ca-LDL has been widely studied in chronic kidney disease [20].

Atherogenic indices such as atherogenic index of plasma (AIP), atherogenic coefficient (AC), Castelli’s risk indices I and II (CRI I and II) are the novel indexes used for identifying cardiovascular disease. In this study we aimed to investigate the link between ca-LDL, AIP, AC, CRI and subclinic atherosclerosis in patients with PsA.

Materials and methods

Thirty-nine patients with PsA who fulfilled the Classification criteria for psoriatic arthritis and 19 age and sex matched healty controls were included in this cross sectional study [23]. Those with history of smoking, diabetes mellitus (glycated hemoglobina1c ≥ 6.5), hypertension, coronary artery disease, heart failure, symptomatic carotid artery disease, peripheral artery disease, aortic aneurysm, a history of cerebrovascular disease, pregnacy, malignancy, active infection, acute or chronic renal failure, nonalcoholic fatty liver disease, chronic liver disease, chronic obstructive pulmonary disease, obstructive sleep apnea, thyroid dysfunction and concomitant rheumatic disease were excluded from this study. Patients who were receiving systemic steroids were also excluded.

The study protocol was approved by the Local Research Ethics Committee. A written informed consent form was signed by the all participants. Demographic and clinical data were recorded. After a 12 h fasting period, venous blood samples was collected from all the subjects in the morning. The following parameters were analysed: ESR, c-reactive protein (CRP), fasting blood glucose (FBG), insulin, total cholesterol (TC), high density lipoprotein cholesterol (HDL-C) and low- density lipoprotein cholesterol (LDL-C), triglyceride (TG), serum amyloid A protein (SAP) and Ca-LDL levels. Ca-LDL level was measured with Human carbamylated LDL (cLDL) ELISA Kit (Sunred Bio, Shanghai, China). The Atherogenic Index of Plasma (AIP) was calculated by using base 10 logarithm of ratio TG to HDL-c [24]. Atherogenic Coefficient (AC) was calculated as total cholesterol - HDL cholesterol / HDL cholesterol (TC- HDL-c)/HDL-c [25]. Castelli risk index 1 and Castelli risk index 2 were calculated as TC/HDL-c and LDL/HDL-c, respectively. The homeostasis model assessment (HOMA) index was used to estimate insulin resistance and calculated as fasting serum insulin (in microunits per milliliter) × fasting serum glucose (in millimolar)/22.5 [26]. An index > 2.5 reflects the clinical state of insulin resistance.

CIMT was measured by an experienced physician, who was blinded to the clinical characteristics of the partipicant. To avoid interobserver variability all measurements were performed by the same examiner. All subjects were examined using a high resolution Doppler ultrasound with a 7.5 MHz scanning frequency in B mode. Mean CIMT was calculated by taking the average of the three measurements taken from both carotid arteries [27].

All data were analyzed using the Statistical Package for Social Sciences (SPSS Inc., Chicago, IL, USA) 16.0 program for Windows. The variables were investigated using visual and analytical methods to determine whether they were normally distributed. Normally distributed continuous values were expressed as mean ± standard deviation (SD) and categorical variables as number and percentage. Non-normally distributed parameters were reported as median values with inter-quartile range (IQR) (25th and 75th percentiles). Student’s t-test was used for comparison of normally distributed data, and the Mann-Whitney U test was used for comparison of non-normally distributed data. The chi squared test was used for categorical variables. Spearman’s correlation coefficient were used in the PsA group, to evaluate the linear relationship between CIMT and other variables. A value of p < 0.05 was considered statistically significant.

Results

The mean age was 49.50 ± 11.86 years and 64.1% were females in PsA group. Patients were on the following medications: methotrexate or leflunomide in 14 (35.9%) patients, combined DMARDs in 7 (17.9%) patients, anti-tumor necrosis factor alpha in 7 (17.9%) patients, anti-TNF with methotrexate in 9 (23.1%) patients, cyclosporine A in 1 (2.6%) patient, non-steroidal anti-inflammatory drugs in 1(2.6%) patient. Clinical characteristics and laboratory results of participants were summarized in Table 1. Mean CIMT levels in the PsA group were higher than the healthy volunteers (p = 0.003). Difference in ca-LDL levels was not statistically significant between groups. In PsA group, although CIMT was positively correlated with HOMA-IR, TG/HDL and AIP, there was no correlation between ca-LDL, AC, CRI-1, CRI-2 and CIMT (Table 2). In addition, CIMT was not correlated with ESR, CRP and SAP (p: 0.481, r: 0.118; p: 0.463, r: 0.123; p: 0.062 r: 0.306 respectively). Ca-LDL was positively correlated with only serum amyloid A protein level (r = 0.744, p < 0.001).

Table 1 Clinical characteristics and laboratory results of patients and healthy volunteers
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Table 2 Univariate correlation of mean CIMT with selected variables in patients with PsA
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Insulin resistance as reflected by the HOMA-IR was significantly increased in the PsA patients compared with the controls (Table 1). PsA patients with IR tended to have higher ca-LDL levels than patients without IR, but this difference lacked statistical significance (33.65 ± 26.94, 28.63 ± 28.06, respectively, p = 0.237).

Discussion

To our knowledge, this is the first study evaluated the level of caLDL in patients with PsA. Ca-LDL levels were not significantly different between groups. In PsA patients, although ca-LDL level was not correlated with CIMT, it was positively correlated with SAP level. SAP, which secreted mainly by the liver under the transcriptional control of IL-1 and IL-6, is a major acute-phase protein present in serum. SAP levels increases up to 1000 fold following an inflammatory stimulation [28]. It is likely to be more than a biomarker of cardiovascular disease and is a participant in the early atherogenic process [29]. It is well recognized that SAP plays an important role in lipid metabolism, but how SAP impacts lipid metabolism remains incompletely understood [30]. During the acute-phase response, SAP causes HDL remodeling and reducing the cholesterol efflux capacity and antiinflammatory ability of the HDL [29, 30].

Proinflammatory cytokines alter the function of the adipose tissue, the skeletal muscle, the liver and the vascular endothelium, to generate a spectrum of proatherogenic changes that includes insulin resistance, dyslipidemia, prothrombotic effects, prooxidative stress, and endothelial dysfunction [31, 32]. Adipokines such as resistin, visfatin and leptin act as insulin antagonists and are elevated in patients with PsA [33,34,35]. Insulin resistance increases the risk for coronary artery disease even in the absence of hyperglycemia [36]. The HOMA-IR reflects dysregulation of fasting glucose and insulin [37]. Also, the TG/HDL-C reflects the dyslipidemia seen in insulin resistance [38]. Our study showed that PsA patients were more insulin resistant than healthy subjects. In addition, HOMA-IR and TG/HDL were positively correlated with CIMT.

AIP, reflect the true relationship between protective and atherogenic lipoprotein and is associated with the size of pre and anti-atherogenic lipoprotein particle [39]. In this study, AIP was positively correlated with CIMT in patients with PsA. Similarly, Sunitha et al. reported that AIP was significantly increased in patients with psoriasis than healthy controls and positively correlated with psoriasis area severity index [40]. Also, it has recently been reported that the AIP may be a good biomarker for the early detection of subclinical atherosclerosis in patient with various rheumatologic diseases, such as ankylosing spondylitis, rheumatoid arthritis, Behçet’s disease, systemic lupus erythematosus, and familial Mediterranean fever [41,42,43,44,45].

AC is ratio relying on the significance of HDL-C in predicting the risk of cardiovascular disease [25]. CRI-1 anda CRI-2 are another parameters which are significant vascular risk indicators and their predictive value is greater than isolated parameters [46]. In this study, CIMT was not correlated with AC and CRI.

The relationship between inflammatory biomarkers levels and atherosclerosis has been merely speculative in patients with PsA. In our study, we did not find any correlation between CIMT and ESR, CRP, SAA. Similarly to our study, Gonzalez-Juanatey et al. demonstrated there was no significant correlation between ESR, CRP and CIMT [14]. Garg et al. observed no correlation between ESR, CRP, IL-1 and CIMT although CIMT was positively correlation with IL-6 [47].

Small sample size, lack of the information on skin involvement severity in PsA patients were major limitation of our study. Another limitation of our study is cross-sectional comparative design. Our results do not provide adequate results to explore potential causality and not reflect changes in these variables with disease duration, disease activity and therapy response.

Conclusions

As a conclusion, our findings contribute to the body of evidence showing increased premature atherosclerosis in PsA patients without clinically evident cardiovascular disease or any traditional atherosclerosis risk factors. TG/HDL ratio and AIP may be useful to screening premature atherosclerosis. Prospectively, long-term follow up further studies are needed to determine changes in these variables over time. Understanding the relationship between atherogenic indices and disease activity in PsA may help screen and risk stratify PsA patients in terms of CVD risk.