
==== Front
Lupus Sci Med
Lupus Sci Med
lupusscimed
lupus
Lupus Science & Medicine
2053-8790
BMJ Publishing Group BMA House, Tavistock Square, London, WC1H 9JR

39242108
10.1136/lupus-2024-001190
lupus-2024-001190
Original Research
Childhood Lupus
2259
1506
Learning from serum markers reflecting endothelial activation: longitudinal data in childhood-onset systemic lupus erythematosus
http://orcid.org/0000-0001-9737-3142
Bergkamp Sandy C 1s.c.bergkamp@amsterdamumc.nl

Bergkamp Nick D 2n.d.bergkamp@vu.nl

http://orcid.org/0000-0003-3961-1274
Wahadat Mohamed Javad 34m.wahadat@erasmusmc.nl

Gruppen Mariken P 1m.p.gruppen@amsterdamumc.nl

Nassar-Sheikh Rashid Amara 15a.nassar@amsterdamumc.nl

Tas Sander W 6s.w.tas@amsterdamumc.nl

Smit Martine J 2mj.smit@vu.nl

http://orcid.org/0000-0003-0245-5386
Versnel Marjan A 4m.versnel@erasmusmc.nl

van den Berg J Merlijn 1j.m.vandenberg@amsterdamumc.nl

http://orcid.org/0000-0002-1964-352X
Kamphuis Sylvia 3s.kamphuis@erasmusmc.nl

http://orcid.org/0000-0001-9416-6631
Schonenberg-Meinema Dieneke 1d.schonenberg@amsterdamumc.nl

1 Department of Paediatric Immunology, Rheumatology and Infectious Diseases, Emma Children’s Hospital, Amsterdam University Medical Centres (AUMC), University of Amsterdam, Amsterdam, The Netherlands
2 Amsterdam Institute for Molecular and Life Sciences (AIMMS), Division of Medicinal Chemistry, Faculty of Science, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
3 Department of Paediatric Rheumatology, Sophia Children’s Hospital, Erasmus University Medical Centre, Rotterdam, The Netherlands
4 Department of Immunology, Erasmus Medical Centre, Rotterdam, The Netherlands
5 Department of Paediatrics, Zaans Medisch Centrum, Zaandam, The Netherlands
6 Amsterdam Rheumatology and Immunology Centre, Department of Rheumatology and Clinical Immunology, and Laboratory for Experimental Immunology, Amsterdam University Medical Centres (AUMC), University of Amsterdam, Amsterdam, The Netherlands
Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

Additional supplemental material is published online only. To view, please visit the journal online (https://doi.org/10.1136/lupus-2024-001190).

None declared.

Sandy CBergkamp; s.c.bergkamp@amsterdamumc.nl
2024
05 9 2024
11 2 e00119022 3 2024
04 8 2024
Copyright © Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.
2024
https://creativecommons.org/licenses/by-nc/4.0/ This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

Abstract

Objectives

In childhood-onset SLE (cSLE), patients have an increased risk of premature atherosclerosis. The pathophysiological mechanisms for this premature atherosclerosis are not yet completely understood, but besides traditional risk factors, the endothelium plays a major role. The first aim of this study was to measure levels of SLE-associated markers involved in endothelial cell (EC) function and lipids in a cSLE cohort longitudinally in comparison with healthy controls (HC). Next aim was to correlate these levels with Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) and nailfold capillaroscopic patterns.

Methods

Blood serum samples, videocapillaroscopy images and patient characteristics were collected in a multicentre longitudinal cSLE cohort and from age and sex comparable HC. Disease activity was evaluated by SLEDAI. A total of 15 EC markers and six lipids were measured in two longitudinal cSLE samples (minimum interval of 6 months) and in HC. Nailfold videocapillaroscopy images were scored according to the guidelines from the EULAR Study Group on Microcirculation in Rheumatic Diseases.

Results

In total, 47 patients with cSLE and 42 HCs were analysed. Median age at diagnosis was 15 years (IQR 12–16 years). Median time between t=1 and t=2 was 14.5 months (IQR 9–24 months). Median SLEDAI was 12 (IQR 6–18) at t=1 and 2 (IQR 1–4) at t=2. Serum levels of angiopoietin-2, CCL2, CXCL10, GAS6, pentraxin-3, thrombomodulin, VCAM-1 and vWF-A2 were elevated in cSLE compared with HC at t=1. While many elevated EC markers at t=1 normalised over time after treatment, several markers remained significantly increased compared with HC (angiopoietin-2, CCL2, CXCL10, GAS6, thrombomodulin and VCAM-1).

Conclusion

In serum from patients with cSLE different markers of endothelial activation were dysregulated. While most markers normalised during treatment, others remained elevated in a subset of patients, even during low disease activity. These results suggest a role for the dysregulated endothelium in early and later phases of cSLE, possibly also during lower disease activity.

Trial registration number

NL60885.018.17.

Autoimmune Diseases
Cardiovascular Diseases
Lupus Erythematosus, Systemic
Lipids
http://dx.doi.org/10.13039/501100009622 Stichting Zeldzame Ziekten Fonds
==== Body
pmcWHAT IS ALREADY KNOWN ON THIS TOPIC

WHAT THIS STUDY ADDS

Our study shows that numerous serum markers associated with endothelial cell (EC) function in SLE are upregulated in patients with cSLE compared with healthy controls, particularly in those with untreated disease. We also show that certain EC markers (angiopoietin-2, CCL2, CXCL10, GAS6, thrombomodulin and VCAM-1) could stay persistently upregulated in patients with cSLE, even in states of low disease activity. This suggests that in a subset of patients with cSLE, the endothelium seems to remain in a state of chronic activation irrespective of disease activity.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

We urge for more investigations on the relation between EC dysregulation and increased risk for premature atherosclerosis and cardiovascular disease in SLE. We emphasise that patients with cSLE should be studied as a subgroup because of longer disease duration while being adults.

Introduction

Patients suffering from autoimmune diseases have an increased risk of developing atherosclerosis, the most important cause of cardiovascular disease (CVD).1 Compared with other autoimmune diseases, patients with SLE have an even higher risk for premature atherosclerosis and the majority of SLE-associated deaths have been attributed to CVD.2 3

Childhood-onset SLE (cSLE) represents 10–20% of all SLE cases and is more severe than adult-onset SLE (aSLE), as it is characterised by a more severe disease course and earlier damage accrual.47 cSLE is a life-threatening disease, which results in a 20-fold higher mortality rate in children when compared with healthy peers.8 Furthermore, SLE-associated premature atherosclerosis and CVD manifest at a much younger age in cSLE compared with aSLE.4 Cardiovascular and cerebrovascular complications have been reported in 5–10% of young adults with cSLE and the majority of these occur between the ages of 20 and 40.4

To date, the complex pathophysiological mechanisms underlying premature atherosclerosis in SLE are not completely understood.9 Although traditional risk factors (eg, hypertension, obesity and dyslipidaemia) contribute to atherosclerosis and CVD in patients with SLE, non-traditional SLE-specific risk factors (such as corticosteroid use) seem to be just as important.911 A growing body of evidence indicates an important role of endothelial dysfunction in the development of accelerated atherosclerosis in cSLE.1217 Different mechanisms play a role, including inflammation triggered by aggregation and oxidation of low-density lipoprotein (LDL), inducing the expression of cell adhesion molecules (CAMs),18 activation of endothelial cells (ECs) and higher leucocyte-EC interactions.19 Apparently, these events constitute the initial stage of endothelial dysfunction and atherogenesis in SLE.20 21 Furthermore, activation of ECs triggers proinflammatory cytokines, for example, CCL2, which play a direct role in accelerated atherosclerosis in SLE.22 Neutrophil extracellular traps are a key factor in atherosclerosis in SLE by augmenting EC death and endothelial-to-mesenchymal transition.23 24 Lastly, in SLE, endothelial progenitor cells (EPC), which play a crucial role in endothelial repair and vascular homeostasis control, are reduced in number and the function of EPCs is often impaired.25 Thus, the endothelium in SLE suffers from inflammation, defective repair and prothrombogenic factors.25

To decrease the risk of CVD in cSLE, early-stage detection of atherosclerosis and vascular damage is critical.26 Until now, screening protocols for detecting biomarkers that predict those atherosclerotic risks are not routinely implemented in clinical care of patients with SLE (in a possible preventive preatherosclerotic phase). Currently, only investigations are available that detect an atherosclerotic plaque when it is already macroscopically visible with functional microcirculation assessment, such as carotid intima-media thickness test.15 Nailfold videocapillaroscopy (NVC) is also a tool to visualise the microvascular pathology. We have shown that the majority of patients with cSLE show an abnormal capillary pattern in nailfolds and that a capillary scleroderma pattern in SLE seems associated with damage.27 28 The predominant finding of nailfold microangiopathy in cSLE anatomically looks like capillary leakage and revascularisation and might be due to endothelial dysregulation in SLE which could lead to this microangiopathy.27 Following our systematic review and meta-analysis,29 we hypothesised that the endothelium in SLE remains dysregulated even in states of low disease activity. If endothelial dysregulation proceeds atherosclerosis, measuring SLE-related markers involved in the EC function in cSLE would give us more insight into the preatherosclerotic phase.

In this study, we measured SLE-related EC markers and serum lipids in cSLE and in healthy controls (HC). We assessed a potential correlation between these EC markers and serum lipids with disease activity and with the nailfold capillary pattern. Moreover, we analysed these EC markers and serum lipids longitudinally.

Methods

Study design and patient selection

Between April 2016 and January 2022, patients with cSLE who visited the (out)patient clinics of the Amsterdam UMC and Erasmus MC (Rotterdam) were recruited for a longitudinal prospective cSLE cohort. Inclusion criteria for patients were all patients (new or already diagnosed) with (1) SLE diagnosis according to the 2012 Systemic Lupus International Collaborating Clinics classification criteria and (2) disease diagnosis before the age of 18 years. At diagnosis and during follow-up at study visits every 6–12 months, demographics, autoimmune serology, time of disease onset, disease activity and type of organ involvement were noted. In the majority of the patients, NVC was performed at diagnosis and annually thereafter if possible. Exclusion followed when it was not possible to collect images with good enough quality for analysis (due to thickness of nailfold skin) or when a patient was too sick to undergo capillaroscopy examination. Disease activity was defined by the Systemic Lupus Erythematosus Disease Activity Index 2000 (SLEDAI-2K)30; serum samples were collected at study visits and immediately stored at −80°C until analysis.

For this study, selection of data was performed retrospectively on patients from this longitudinal cohort study with preferably two available longitudinal serum samples (minimum interval of 6 months), one with active disease (SLEDAI>4) at t=1 (preferably treatment naïve, at diagnosis) and one, later in time, during low disease activity (SLEDAI≤4) at t=2. To include all available treatment-naïve patients, some of these did not have a sample with low disease activity. Thus, if patients had less than two samples in total, two samples with less than 6 months of interval or two samples with both SLEDAI<4 or both >4, SLEDAI≤4 at t=1, these samples were included for cross-sectional analyses but excluded for the longitudinal analyses.

One-time blood samples from age and sex comparable HCs were obtained from children who were investigated by MRI for joint complaints, and in whom an inflammatory disease had been excluded (JIA-MRI study, NL52625.018.15; approved by the Medical Ethical Committee (MEC) Amsterdam, MEC 2015-046).

Measurement of serum marker levels and lipids

Based on our previous systematic literature review on (dysregulated) SLE-associated markers involved in EC function,29 we selected the following panel of 15 markers (panel 1). Serum levels of CXCL12 (SDF-1), TWEAK and vascular endothelial growth factor (VEGF) were measured using a commercially available ELISA kit (R&D Systems) according to the manufacturer’s instructions. Serum levels of CXCL10 (IP-10), ADAMTS13, angiopoietin-2, pentraxin-3, E-selectin, thrombomodulin, P-selectin, CCL2 (MCP-1), VCAM-1, ICAM-1, vWF-A2 and GAS6 were determined using a tailor-made magnetic bead Luminex Multiplex Assay Kit (R&D Systems), according to manufacturer’s procedures, and measured using a Bioplex 200 system (Bio-Rad). Samples were thawed only once for measurements of marker levels. Technical duplicates of samples were run simultaneously on the same plate, resulting in no need for an extra freeze-thaw cycle.

For those samples with sufficient material left after serum marker-level determinations, lipids were determined (panel 2). Of note, these measurements were assessed in blood that was taken from patients in a non-fasted state. Total cholesterol, high-density lipoprotein-cholesterol (HDL-C), triglyceride (TG) levels, ApoA1 and ApoB were determined by our ISO-certified central laboratory facility. LDL-cholesterol (LDL-C) was calculated by the Friedewald formula. ApoB/ApoA1 was calculated as a ratio. These samples were thawed twice before measurements.

Nailfold capillaroscopy technique and image analysis

NVC was performed with a ×200 magnification lens from Optilia. In total, eight fingers per patient (excluding the thumbs) were examined. Per finger, four images were stored. Images were collected and evaluated by two investigators (DS-M and SCB with, respectively, 8 and 5 years of experience in performing an analysis of NVC). According to the ‘EULAR Study Group on Microcirculation in Rheumatic Diseases standardised capillaroscopy evaluation chart’, the three different capillary patterns were described. When capillary abnormalities were absent by NVC analysis the capillary pattern was defined as ‘normal’. Microangiopathy was defined as an abnormal capillary pattern (with abnormal capillary morphology and/or capillary haemorrhages), but without criteria for a scleroderma pattern. A capillary scleroderma pattern was defined as extremely lowered density (≤3 capillaries/mm) with abnormal shapes and/or the presence of giant capillaries.31 The majority of patients underwent NVC at least once during follow-up. For analysis, the most abnormal capillary pattern ever during follow-up was used.

Statistical methods

Descriptive statistics were used to analyse demographics of patients with cSLE and HC. Spearman’s rank correlation coefficients were calculated to quantify the relationship between SLEDAI and EC marker levels and lipids. R values between 0.3 and 0.5 were classified as weak relations, between 0.5 and 0.7 as moderate relations and r values >0.7 as strong relations.32 Mann-Whitney U tests were used to compare differences between two different groups (for differences between HC and SLE, and differences in HC vs active disease and low disease activity). Wilcoxon signed-rank tests (for paired samples over time) were performed to compare levels of EC markers in cSLE at t=1 and t=2 and lipids at t=1 and t=2. To investigate the potential link between levels of EC markers with capillary patterns, Spearman’s correlation analysis was performed. A p value <0.05 was considered statistically significant. Statistical analysis was performed using IBM SPSS statistics software V.28 and GraphPad Prism V.9 (GraphPad Software). Since this is an exploratory study, we did not perform multiple testing correction.

Results

Demographic profile of study subjects

47 patients with cSLE (of which 30 were treatment naïve) and 42 HCs had available samples for inclusion in cross-sectional analyses. Median age at diagnosis in cSLE was 15 years (IQR 12–16 years). At t=1, median SLEDAI was 13 (IQR 9–20) for treatment-naïve patients and median SLEDAI was 8 (IQR 2.5–13.5) for non-naïve patients. Median disease duration at t=1 was 0 month (IQR 0–18 months) for treatment-naïv†e patients and 42 months (IQR 13.6–62.5) for non-naïve patients (n=17). All demographic and clinical characteristics of patients with SLE and (age and sex comparable) HC are depicted in table 1.

Table 1 Demographics and clinical characteristics of patients with cSLE and HC

	Patientsn=47	HCn=42	P value*	
Female, n (%)	40 (85.1)	36 (85.7)	0.935	
Treatment naïve, n (%)	30 (63.8)	 	 	
Race/ethnicity, n (%)	 	 	<0.001	
 Caucasian	20 (42.6)	37 (88)		
 African/Afro-Caribbean	17 (36.2)	2 (4.8)	 	
 North-African/Middle-Eastern	4 (8.5)	2 (4.8)		
 Mixed/other	4 (8.5)	1 (2.5)		
 Asian	2 (4.3)	0 (0)	 	
Age at diagnosis, median (IQR)	15 (12–16)	15 (12–16)†	0.276	
BMI at t=1, median (IQR)	19.8(17.3–22.9)	 	 	
SLEDAI at diagnosis, median (IQR)	14 (10–18.5)	 	 	
Paired samples (n=31 patients with cSLE)				
 SLEDAI at t=1 (IQR)	12 (6–18)			
 SLEDAI at t=2 (IQR)	2 (1–4)			
 Age at sample t=1, years (IQR)	16 (14–17)			
 Age at sample t=2, years (IQR)	17 (16–18)			
 Disease duration at t=1, months (IQR)	0 (0–18)			
 Disease duration at t=2, months (IQR)	16.5 (10–53)			
Capillaroscopy pattern (n=32 patients with cSLE)	 	 	 	
 Normal, n (%)	4 (12.5)	 	 	
 Microangiopathy, n (%)	22 (68.8)	 	 	
 Scleroderma pattern, n (%)	6 (18.8)	 	 	
ANA at diagnosis, n (%)	44 (93.6)	 	 	
Anti-ds-DNA, n (%)	36 (76.6)	 	 	
Anti-RNP, n (%)	22 (46.8)	 	 	
Anti-Sm, n (%)	17 (36.2)	 	 	
Cutaneous involvement, n (%)	35 (74.5)	 	 	
Nephritis, n (%)	22 (46.8)	 	 	
Neuropsychiatric involvement, n (%)	7 (14.9)	 	 	
Arthritis, n (%)	34 (72.3)	 	 	
* Mann -Whitney U test between HC and all patients with cSLE (n=47).

† Age at date of MRI/blood sampling.

Anti-ds-DNAanti-double stranded DNAAnti-RNPantinuclear ribonucleoproteinAnti-Smanti-SmithBMIbody mass indexcSLEchildhood-onset SLEHChealthy controlSLEDAISystemic Lupus Erythematosus Disease Activity Index

31/47 patients could be included in the longitudinal analyses with active disease at t=1 and low disease activity at t=2. In n=11 patients we did not have second samples (yet). Five excluded patients had low disease activity (SLEDAI≤4) at t=1 and active disease at t=2 (median SLEDAI 8 (range 6–33)). Five patients had minimal active disease (SLEDAI=4) at t=1 and SLEDAI <4 at t=2, these patients were included for longitudinal analyses.

Serum EC marker levels in patients with cSLE versus HC at t=1

Serum levels of angiopoietin-2, CCL2, CXCL10, GAS6, pentraxin-3, thrombomodulin, VCAM-1 and vWF-A2 were significantly higher in all patients with cSLE (n=36/47 with active disease) compared with HC (n=42). Serum levels of ADAMTS13, CXCL12, E-selectin, ICAM-1, P-selectin, TWEAK and VEGF did not differ between the groups (figure 1 and online supplemental table S1). When evaluating these EC markers in only treatment-naïve patients with cSLE (n=30) and compared with HC, similar findings were obtained (online supplemental figure S1).

Figure 1 Serum EC marker levels in childhood-onset SLE (cSLE) at t=1 compared with HC. Serum concentration (pg/mL) of each EC marker for all patients with cSLE at t=1 (n=47) compared with HC (n=42). The horizontal line depicts the median serum concentration (pg/mL) of each EC marker for HC and all patients with cSLE. **P<0.01, ***p<0.001, ****p<0.0001, as calculated by Mann-Whitney U test. ADAMTS13, a disintegrin-like and metalloprotease with thrombospondin type 1 motif; CCL2, chemokine (C-C motif) ligand 2; CXCL10, C-X-C motif chemokine ligand 10; CXCL12, C-X-C motif chemokine ligand 12; EC, endothelial cell; Gas6, growth arrest-specific gene 6; HC, healthy control; ICAM-1, intercellular adhesion molecule 1; ns, non-significant; TWEAK, tumour necrosis factor (TNF)-like weak inducer of apoptosis, VCAM-1, vascular cell adhesion molecule 1; VEGF, vascular endothelial growth factor; vWF, von Willebrand factor.

EC markers in patients with cSLE in different disease activity states versus HC at t=1

At t=1, serum levels of CXCL10 (p=0.01), thrombomodulin (p=0.03) and VCAM-1 (p=0.01) were higher in patients with active disease (n=36/47) as compared with those with low disease activity (n=11/47) (figure 2) in cross-sectional analysis. Angiopoietin-2, CCL2, CXCL10, GAS6, pentraxin-3, thrombomodulin, VCAM-1 and vWF-A2 differed between patients with active disease and HC. Additionally, from all EC markers only angiopoietin-2 was higher when comparing low disease activity with HC.

Figure 2 Comparing serum EC marker levels from HC with patients with childhood-onset SLE (cSLE) at t=1 in low disease activity (SLEDAI≤4 in n=11) and in active disease (SLEDAI>4 in n=36). The horizontal line depicts the median serum concentration (pg/mL) of each EC marker. *P<0.05, **p<0.01, ***p<0.001, ****p<0.0001, as calculated by Mann-Whitney U test. AD, active disease; ADAMTS13, a disintegrin-like and metalloprotease with thrombospondin type 1 motif; CCL2, chemokine (C-C motif) ligand 2; CXCL10, C-X-C motif chemokine ligand 10; CXCL12, C-X-C motif chemokine ligand 12; EC, endothelial cell; Gas6, growth arrest-specific gene 6; HC, healthy control; ICAM-1, intercellular adhesion molecule 1; LDA, low disease activity; ns, non-significant; SLEDAI, Systemic Lupus Erythematosus Disease Activity Index; TWEAK, tumour necrosis factor (TNF)-like weak inducer of apoptosis; VCAM-1, vascular cell adhesion molecule 1; VEGF, vascular endothelial growth factor; vWF, von Willebrand factor.

Correlations of EC marker serum levels with SLEDAI at t=1

Angiopoietin-2, CCL2 and VCAM-1 levels did not correlate with SLEDAI at t=1 (table 2) despite higher median serum concentrations in cSLE versus HC (figure 1). A moderate relation for thrombomodulin (r=0.414, p=0.004) with SLEDAI at t=1 was identified (table 2). A weak correlation for GAS6 (r=324, p=0.003) and weak correlations for P-selectin (r=0.348, p=0.02), pentraxin-3 (r=0.290, p=0.01), CXCL10 (r=0.394, p=0.007), VCAM-1 (r=0.317, p=0.03) and CCL2 (r=0.293, p=0.04) with SLEDAI were found.

Table 2 Spearman’s R correlations (r) between EC marker levels and SLEDAI at t=1

	Spearman’s R	P value	
ADAMTS13	−0.048	0.75	
Angiopoietin-2	0.175	0.24	
CCL2	0.293	0.04	
CXCL10	0.394	0.007	
CXCL12	0.008	0.96	
E-selectin	−0.213	0.15	
GAS6	0.324	0.03	
ICAM-1	0.074	0.62	
Pentraxin-3	0.290	0.04	
P-selectin	0.348	0.02	
Thrombomodulin	0.414	0.004	
VCAM-1	0.317	0.03	
TWEAK	−0.001	0.99	
VEGF	−0.011	0.94	
vWF-A2	0.264	0.08	
Bold values represent statistic significant Spearman’s R values.

ADAMTS13a disintegrin-like and metalloprotease with thrombospondin type 1 motifCCL2chemokine (C-C motif) ligand 2CXCL10C-X-C motif chemokine ligand 10CXCL12C-X-C motif chemokine ligand 12ECendothelial cellGAS6growth arrest-specific gene 6ICAM-1intercellular adhesion molecule 1SLEDAISystemic Lupus Erythematosus Disease Activity IndexTWEAKtumour necrosis factor (TNF)-like weak inducer of apoptosisVCAM-1vascular cell adhesion molecule 1VEGFvascular endothelial growth factorvWFvon Willebrand factor

Correlations between different EC markers

Correlations between all measured EC markers at t=1 are depicted in online supplemental table S2. Strong correlations at t=1 were found for thrombomodulin and GAS6 (r=0.712, p<0.001) and for CXCL12 and TWEAK (r=0.823, p<0.001). These markers are involved in different endothelial functions: EC activation, disturbed angiogenesis and vasculogenesis, as well as in coagulopathy.33 There were moderate correlations for angiopoietin-2 and pentraxin-3 (r=0.512, p<0.001), pentraxin-3 and thrombomodulin (r=0.562, p<0.001), CCL2 and CXCL10 (r=0.574, p<0.001), CXCL12 and VEGF (r=0.592, p<0.001), vWF-A2 and GAS6 (r=0.667, p<0.001) and VEGF and TWEAK (r=0.680, p<0.001).

At t=2, correlations between angiopoietin-2 with thrombomodulin/GAS6 changed from weak to moderate. A moderate correlation was observed for VCAM-1 and E-selectin (r=0.507, p=0.002) (online supplemental table S3).

Longitudinal analyses of EC markers in cSLE

Only patients with paired samples that had active disease at t=1 and low disease activity at t=2 (n=31/47) were included for longitudinal analyses. Median time between the blood samples at t=1 and t=2 was 14.5 months (IQR 9–24 months). The median SLEDAI at t=1 was 12 (IQR 6–18) and median SLEDAI at t=2 was 2 (IQR 1–4) (p=0.0004) (figure 3). Serum levels of CXCL10, angiopoietin-2, pentraxin-3, E-selectin, CCL2, VCAM-1 and vWF-A2 decreased over time (p=0.005, p=0.005, p=0.03, p=0.03, p=0.02, p=0.0004 and p=0.0007, respectively), while serum levels of TWEAK increased (p=0.04). At t=2, many elevated EC markers after treatment were not different from those in HC. However, several markers remained significantly increased compared with HC: angiopoietin-2, CCL2, CXCL10, GAS6, thrombomodulin and VCAM-1 (table 3). The outliers in the TWEAK, VEGF and CXCL12 levels at t=2 did not correlate with SLEDAI.

Table 3 Mean serum EC levels for HC versus cSLE (all, LDA or AD) at t=2

	HCn=42	cSLE, t=2		
All patients (n=36)	P value	LDA (n=31)	P value	AD (n=5)	P value	
ADAMTS13	1 344 200 (1 167 727–1 618 825)	1 399 650 (1 169 950–1 696 350)	ns	1 496 900 (1 385 600–1 733 950)	0.011	1 367 650 (1 128 725–1 677 775)	ns	
Angiopoietin-2	2429 (2068–2857)	3715 (2950–4967)	0.003	3683 (3219–4293)	ns	3845 (2774–5037)	<0.001	
CCL2	356 (288–455)	638 (282–1233)	0.001	410 (217–666)	ns	769 (311–1501)	ns	
CXCL10	23 (20–28)	125 (54–303)	<0.001	58 (32–110)	0.017	163 (68–375)	0.014	
CXCL12	94 (35–294)	70 (33–309)	ns	51 (36–368)	ns	67 (38–295)	ns	
E-selectin	29 170 (18 164–42 955)	36 353 (24 220–47 929)	ns	46 222 (23 220–63 471)	ns	36 353 (24 631–39 901)	ns	
GAS6	11 657 (10 124–15 096)	15 957 (13 093–19 422)	0.002	7530 (5541–14 019)	<0.001	15 453 (8524–20 266)	0.010	
ICAM-1	191 812 (156 443–238 270)	226 510 (1 693 340–301 594)	ns	206 851 (152 322–226 511)	ns	246 580 (170 911–307 649)	ns	
Pentraxin-3	2389 (1983–2883)	3165 (2202–4100)	ns	2277 (1809–4333)	ns	3210 (2422–4031)	ns	
P-selectin	40 308 (35 492–51 894)	41 217 (32 057–48 543)	ns	36 145 (25 351–43 991)	ns	42 166 (32 188–49 752)	ns	
Thrombomodulin	5275 (4517–6135)	6399 (5049–9070)	0.028	5564 (4912–6399)	ns	6556 (5103–10 058)	<0.001	
VCAM-1	1 006 903 (701 340–1 155 362)	2 421 200 (1 579 300–3 924 350)	0.001	1 689 750 (1 365 500–2 437 350)	ns	2 599 925 (1 608 063–4 613 425)	ns	
TWEAK	307 (165–574)	258 (177–380)	ns	258 (214–347)	ns	245 (170–533)	ns	
VEGF	35 (8–95)	40 (14–75)	ns	34 (13–64)	ns	40 (13–83)	ns	
vWF-A2	7102 (4576–10 147)	10 790 (7276–13 918)	ns	6388 (4316–9463)	0.035	9873 (4721–14 162)	ns	
Median serum levels (pg/mL) (IQR). Mann -Whitney U test for cSLE versus HC.

P values are given for Mann-Whitney U test between HC and all patients, HC and LDA patients, and HC and AD patients.

Bold values represent significant differences in mean serum EC levels for HC versus cSLE.

ADactive diseaseADAMTS13a disintegrin-like and metalloprotease with thrombospondin type 1 motifCCL2chemokine (C-C motif) ligand 2cSLEchildhood-onset SLECXCL10C-X-C motif chemokine ligand 10CXCL12C-X-C motif chemokine ligand 12ECendothelial cellGAS6growth arrest-specific gene 6HChealthy controlICAM-1intercellular adhesion molecule 1LDAlow disease activitynsnon-significantTWEAKtumour necrosis factor (TNF)-like weak inducer of apoptosisVCAM-1vascular cell adhesion molecule 1VEGFvascular endothelial growth factorvWFvon Willebrand factor

Figure 3 Changes over time in serum EC marker levels and SLEDAI in longitudinal childhood-onset SLE (cSLE) cohort. Serum marker concentrations (pg/mL) and SLEDAI for t=1 (active disease) and t=2 samples (low disease activity) of patients with cSLE (n=31). Orange line indicates the median serum marker concentration for each EC marker in our HC cohort. *P<0.05, **p<0.01, ***p<0.001, ****p<0.0001, as calculated by Wilcoxon signed-rank test. ADAMTS13, a disintegrin-like and metalloprotease with thrombospondin type 1 motif; CCL2, chemokine (C-C motif) ligand 2; CXCL10, C-X-C motif chemokine ligand 10; CXCL12, C-X-C motif chemokine ligand 12; EC, endothelial cell; Gas6, growth arrest-specific gene 6; HC, healthy control; ICAM-1, intercellular adhesion molecule 1; ns, non-significant; SLEDAI, Systemic Lupus Erythematosus Disease Activity Index; TWEAK, tumour necrosis factor (TNF)-like weak inducer of apoptosis; VCAM-1, vascular cell adhesion molecule 1; VEGF, vascular endothelial growth factor; vWF, von Willebrand factor.

Correlation of EC marker serum levels with nailfold capillary pattern

In 32/47 patients with cSLE, nailfold capillaroscopy data were available. No significant correlations by Spearman’s rank test were found between type of capillary pattern and EC marker levels at t=1 (n=32 cSLE), but a weak positive correlation was found between levels of angiopoietin-2 with a scleroderma capillary pattern at t=2 (n=6 cSLE) (R2=0.167, F(2, 25)=2514, p=0.039) (data not shown).

Lipids in cSLE and HC

Lipids could be measured in a subset of patients with cSLE (n=33/47) and in all HCs (n=42). Although median levels of TG, ApoB and ApoB/ApoA1 ratios were increased in patients with cSLE at t=1 (n=28/33 with active disease) compared with HC, values were still within the physiological ranges for these lipids (online supplemental table S4). Median levels of ApoA1 and HDL were markedly decreased in cSLE, which persisted at t=2 (n=20/22 with low disease activity), but these values were also still within normal physiological range. Weak correlations were observed between TG (r=0.452, p=0.008), ApoB/ApoA1 (r=0.405, p=0.020), ApoB (r=0.483, p=0.004) and SLEDAI.

When analysing correlations between lipids and EC markers, moderate correlations were found between HDL and VCAM-1, TG and thrombomodulin, ApoA1 and VCAM-1, ApoB and thrombomodulin and between ApoB/ApoA1 and pentraxin-3 (table 4). After treatment at t=2, differences in lipids between patients with cSLE and HC disappeared over time.

Table 4 Correlations between EC markers and lipids at t=1

	Total cholesterol (mmol/L)	HDL(mmol/L)	LDL (mmol/L)	Triglycerides (mmol/L)	ApoA1 (mg/dL)	ApoB (mg/dL)	ApoB/ApoA1 ratio (mg/dL)	
CXCL10		r=−0.518		r=0.474	r=−0.410		r=0.306	
ADAMTS13				r=0.262				
Angiopoietin-2		r=−0.567		r=0.381	r=−0.512		r=0.363	
Pentraxin-3		r=−0.455		r=0.288	r=−0.472	r=0.314	r=0.523	
E-selectin					r=−0.331			
Thrombomodulin				r=0.437			r=0.332	
P-selectin	r=0.317					r=0.347	r=0.243	
CCL2				r=0.341			r=0.345	
VCAM-1		r=−0.607		r=0.404	r=−0.596		r=0.351	
ICAM-1								
vWF-A2				r=0.301		r=0.301	r=0.371	
GAS6		r=−0.411			r=−0.392		r=0.352	
CXCL12								
TWEAK								
VEGF								
Spearman’s rank correlation reported for correlations between 15 EC markers and lipids. Only significant correlations are shown.

Light grey: weak correlations (r=0.3–0.5). Darker grey: moderate correlations (r=0.5–0.7).

ADAMTS13a disintegrin-like and metalloprotease with thrombospondin type 1 motifApoA1apolipoprotein AIApoBapolipoprotein BCCL2chemokine (C-C motif) ligand 2CXCL10C-X-C motif chemokine ligand 10CXCL12C-X-C motif chemokine ligand 12ECendothelial cellGAS6growth arrest-specific gene 6HDLhigh-density lipoproteinICAM-1intercellular adhesion molecule 1LDLlow-density lipoproteinTWEAKtumour necrosis factor (TNF)-like weak inducer of apoptosisVCAM-1vascular cell adhesion molecule 1VEGFvascular endothelial growth factorvWFvon Willebrand factor

Longitudinal measurements of lipids (with high disease activity at t=1 and low disease activity at t=2) were only possible in a subgroup of patients with cSLE (n=20/33). ApoB (p=0.0032) and ApoB/ApoA1 ratio (p=0.0014) and TG (p=0.0042) decreased over time, while HDL levels (p=0.03) increased. Total cholesterol, LDL and ApoA1 levels did not differ over time (p=0.21, p=0.19 and p=0.085, respectively) (figure 4).

Figure 4 Longitudinal measurements of lipids (mg/dL or mM) at t=1 (active disease) and t=2 (low disease activity) in childhood-onset SLE (cSLE; n=20). On the x-axis, blue dots represent t=1, red dots t=2. Serum levels of lipids are displayed on the y-axis. Orange line indicates median concentrations for lipids in our HC cohort. *P<0.05, **p<0.01, as calculated by Wilcoxon signed-rank test. ApoA1, apolipoprotein AI; ApoB, apolipoprotein B; HC, healthy control; HDL, high-density lipoprotein; LDL, low-density lipoproteinns; ns, non-significant.

Discussion

Our study shows that many of the assessed SLE-associated markers involved in EC function were upregulated in patients with cSLE compared with HC, especially in treatment-naïve and active disease. Angiopoietin-2, CCL2 and VCAM-1 were upregulated in patients with cSLE compared with HC but interestingly also in some patients with lower disease activity (at t=1). Despite low median disease activity, angiopoietin-2, CCL2, CXCL10, GAS6, thrombomodulin and VCAM-1 remained significantly upregulated in patients with cSLE compared with HC (at t=2). This implies that the endothelium in (a subset of) patients with cSLE remains in a chronically active state, regardless of disease activity. The aforementioned markers are involved in a broad spectrum of biological functions of EC, including vascular inflammation, EC activation and a proangiogenic state. HDL, TG, ApoA1 and ApoB/ApoA1 were dysregulated in patients with cSLE compared with HC (at t=1), but still within the physiological range. In longitudinal analyses, differences in lipids between patients with cSLE and HC disappeared over time, which is probably related to lower disease activity (and treatment).

Thrombomodulin is found on the surface of vascular EC and acts as a receptor for thrombin.34 Studies indicate that serum thrombomodulin is released when ECs are damaged.35 36 Dysfunction in either the amount or quality of thrombomodulin may contribute to thrombogenesis, which commonly occurs in patients with SLE.37 Importantly, thrombomodulin is being considered as a marker for EC damage and has been linked to active vasculitis in SLE.35 In line with our results, Lee et al demonstrated upregulated levels of thrombomodulin in cSLE compared with HC as well as a significant relation between thrombomodulin and SLEDAI.38 This correlation between thrombomodulin and SLEDAI was also seen in an aSLE cohort.39

VCAM-1 is a cell surface adhesion molecule, overexpressed on EC that plays a role in the immune response. In activated EC, VCAM-1 contributes to the adhesion and migration of immune cells from the blood to sites of inflammation. We found VCAM-1 to be upregulated in cSLE but we did not find a correlation between VCAM-1 levels and disease activity. In line with our findings, a study in aSLE reported upregulated serum levels of VCAM-1 but they found a weak correlation for VCAM-1 with disease activity.35

CCL2 (also known as MCP-1) is a chemokine that is produced by various cell types, for example, macrophages, fibroblasts and ECs, in response to inflammation. When there is vascular injury or inflammation, such as in atherosclerosis or other inflammatory conditions as, for example, SLE, ECs lining the blood vessels can produce CCL2. The locally produced CCL2 acts as a signalling molecule. It binds to its receptor (CCR2) on the surface of monocytes. This binding triggers a series of events that result in the monocytes leaving the bloodstream, adhering to the endothelium and migrating through the blood vessel wall into the subendothelial space.40 A study with adult patients with SLE41 demonstrated an upregulation of CCL2 serum levels in SLE compared with HC, without correlation with disease activity, which is in accordance with our results. These findings suggest a dysregulated endothelium irrespective of SLE disease activity.

CXCL10 is released by a diverse range of cells, including leucocytes, activated neutrophils and ECs. CXCL10 attracts activated Th1 lymphocytes, monocytes and natural killer cells to the area of inflammation.42 It has been shown that CXCL10 is increased in patients with aSLE compared with HC.43 In that study, CXCL10 correlated strongly with disease activity. In our study, CXCL10 was also upregulated in cSLE compared with HC and there was a weak correlation with SLEDAI (r=0.39, p=0.008).

The majority of the assessed lipids differed significantly in patients with cSLE compared with HC in our study, despite means of values falling within the normal physiological range. As shown previously in the APPLE (Atherosclerosis Prevention in Pediatric Lupus Erythematosus) study,44 mean levels of HDL, LDL and TG were also in the normal or borderline ranges in that cSLE cohort. Another cross-sectional study showed a significant difference in ApoB and TG levels between cSLE and HC.45 There was no significant difference in levels of total cholesterol, LDL-C, HDL-C and ApoA1 levels. ApoB/Apo1 ratios were not reported. Interestingly, based on multiserum metabolomics analysis, it has been suggested that high ApoB/ApoA1 ratio could function as a potential biomarker of an increased cardiometabolic risk.46 It has been reported that the ApoB/ApoA1 ratio can assist in classifying patients who require increased disease monitoring, lipid modification or lifestyle changes.46 In our study, ApoB/ApoA1 ratio was elevated in patients with cSLE (with normal body mass index (BMI) ranges) with active disease compared with HC. However, after treatment, this difference disappeared in low disease activity states. Similarly, most of the differences in lipids between patients with cSLE and HC disappeared. This implies that there was a trend towards dysregulated lipids during active disease with positive effect of anti-inflammatory treatment in these patients. However, due to limited sample volumes we were only able to measure lipids longitudinally in 22/47 patients with cSLE. Interestingly, in a subset analysis within the previously mentioned APPLE study, 36% of patients with cSLE experienced ongoing atherosclerosis, which was not predictable by metabolic biomarkers. This suggests the presence of non-lipid drivers for atherosclerosis, emphasising the importance of considering such factors in the management of these patients.47

Recently, we proposed that an abnormal nailfold capillary pattern reflects early vasculopathy in patients with cSLE, since we observed that more than 50% of patients with a capillary scleroderma pattern already had SLE-related disease damage within 5 years after diagnosis.28 In the current study, 68.8% of patients with cSLE had a capillary microangiopathy pattern and 18.8% showed a capillary scleroderma pattern at diagnosis. In an exploratory manner, we have analysed possible relationships between EC marker levels and abnormal nailfold capillaroscopic patterns. Angiopoietin-2 showed a weak correlation with a scleroderma pattern. Angiopoeitin-2 was also elevated irrespective of disease activity in our patients with cSLE. This EC marker is involved in the ‘disturbed angiogenesis’ of EC function.33 These results are in line with a previous study, in which higher levels of angiopoietin-2 in SLE compared with HC were found. Moreover, there was no correlation between angiopoietin-2 levels and SLEDAI.48 In the aforementioned study by Lee et al,38 angiopoietin-2 was also upregulated in patients with cSLE compared with HC, but did not correlate with SLE disease activity, similar to our current findings. We hypothesise that high angiopoietin-2 levels might reflect the vasculopathy and disturbed angiogenesis that is observed by nailfold capillaroscopy (abnormal nailfold capillaries with capillary giants, haemorrhages and abnormal capillary morphology). To our knowledge, there is only one study that studied the potential correlation between EC markers and NVC patterns.49 Angiopoietin-2 levels were not measured in this study, but a correlation between VEGF and microvascular abnormalities in nailfold capillaroscopy was reported. In our study, we did not observe a correlation between VEGF levels and an abnormal capillary pattern. Another study also stated that angiopoietin-2 may be used as a potential biomarker in SLE, since this marker seemed to have potential to differentiate patients with SLE from those with rheumatoid arthritis, osteoarthritis, gout, Sjögren’s syndrome and ankylosing spondylitis.48 It is important to mention that in our study not all samples were taken simultaneously with capillaroscopy examination. Although we have shown earlier that most capillary patterns do not change over time,28 this is a limitation. Future studies will have to show whether angiopoietin-2, in combination with NVC, might be used as a biomarker for (ongoing) vascular inflammation.

This is the first longitudinal study in cSLE assessing SLE-associated markers involved in EC function in combination with longitudinal measurements of lipids. The number of studies on EC markers in patients with cSLE is very limited. The uniqueness of our cohort also lies in the fact that more than half of the patients (30/47, 63.8%) were treatment naïve at the moment of first blood sample. These treatment-naïve samples reflect an endothelial state that is solely attributable to the disease itself, with no influence from medication.

Nonetheless, there are also several limitations. First, we were not able to perform longitudinal analyses in all patients, if patients did not yet achieve inactive disease. Additionally, we were not able to perform lipid measurements in all patients due to a lack of material in a substantial part of our patients. Therefore, it was only possible to measure the lipids longitudinally in 50% of the cSLE cohort which might have biased our results with less statistical significance. Other limitations are the lack of nailfold capillaroscopy data in a considerable number of patients with cSLE (n=15) and the limited follow-up period (mean 31 months, median 16.5 months) after diagnosis. Therefore, we were not able to determine any effects caused by medication and/or disease duration over time on the measured EC markers and lipids. Moreover, it is of note that HCs were not matched with patients with cSLE. Therefore, ethnic backgrounds of the HC group differed substantially from the cSLE group, with a majority of Caucasian subjects in the HC group (88% compared with 42% in cSLE patient group) which might have an effect on biology and their cardiovascular risks. In addition, BMIs of the HCs were not obtained.

It is important to decrease the overall incidence of CVD-related morbidity and mortality in SLE by using appropriate prevention and treatment strategies. To date, established screening protocols for detecting or monitoring CVD in cSLE do not exist. However, for patients with cSLE who have become adults, such protocols would be valuable, as we know they suffer from higher disease activity, longer disease duration and premature atherosclerosis at a relatively young age, compared with aSLE. There is a pressing and unmet need to develop improved methods to stratify patients with cSLE who are at risk for CVD in order to start preventive treatment. Future studies should therefore further elucidate the changes in EC markers in combination with lipids over time. We urge for more thorough investigations on the relation between the EC dysregulation in SLE and increased risk of premature atherosclerosis and CVD, with an emphasis on the differences in cSLE and adult-onset patients.

Conclusion

In cSLE, markers of endothelial activation were dysregulated. Some of those EC markers remained dysgregulated in a subset of patients with cSLE despite low disease activity. This study could aid in unravelling a part of the pathophysiology of endothelial dysregulation in patients with cSLE. These results suggest a role for the dysregulated endothelium in early and later phases of cSLE and if so, this could have implications for future screening protocols for vascular health in cSLE.

supplementary material

10.1136/lupus-2024-001190 online supplemental file 1

Acknowledgements

We thank the included patients with cSLE and healthy controls for taking part in this study. We thank Professor TW Kuijpers for his critical reading and valuable input and feedback on the manuscript.

Data availability statement

Data are available upon reasonable request.

Funding: This work was made possible by the support of the Stichting Zeldzame Ziektenfonds.

Provenance and peer review: Not commissioned; externally peer reviewed.

Patient consent for publication: Not applicable.

Ethics approval: This study involves human participants and was approved by the Medical Ethical Committee (MEC) at the Amsterdam University Medical Centres (MEC 2017-172; Dutch trial register registration number: NL60885.018.17) and the Erasmus Medical Centre Rotterdam (MEC 2019-0412). Written informed consent was given by the patients and/or parents (from patients with cSLE and HC). The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013).

Presented at: A part of this work was previously presented as a poster presentation at the Paediatric Rheumatology European Society Congress, which was held from 28 September to 1 October 2023.
==== Refs
References

1 Chen H-J Tas SW de Winther MPJ Type-I interferons in atherosclerosis J Exp Med 2020 217 e20190459 10.1084/jem.20190459 31821440
2 Restivo V Candiloro S Daidone M et al Systematic review and meta-analysis of cardiovascular risk in rheumatological disease: Symptomatic and non-symptomatic events in rheumatoid arthritis and systemic lupus erythematosus Autoimmun Rev 2022 21 102925 10.1016/j.autrev.2021.102925 34454117
3 McMahon M Seto R Skaggs BJ Cardiovascular disease in systemic lupus erythematosus Rheumatol Immunol Res 2021 2 157 72 10.2478/rir-2021-0022 35880242
4 Groot N Shaikhani D Teng YKO et al Long-Term Clinical Outcomes in a Cohort of Adults With Childhood-Onset Systemic Lupus Erythematosus Arthritis Rheumatol 2019 71 290 301 10.1002/art.40697 30152151
5 Hersh AO von Scheven E Yazdany J et al Differences in long-term disease activity and treatment of adult patients with childhood- and adult-onset systemic lupus erythematosus Arthritis Rheum 2009 61 13 20 10.1002/art.24091 19116979
6 Levy DM Kamphuis S Systemic lupus erythematosus in children and adolescents Pediatr Clin North Am 2012 59 345 64 10.1016/j.pcl.2012.03.007 22560574
7 Mina R Brunner HI Update on differences between childhood-onset and adult-onset systemic lupus erythematosus Arthritis Res Ther 2013 15 218 10.1186/ar4256 23998441
8 Kamphuis S Silverman ED Prevalence and burden of pediatric-onset systemic lupus erythematosus Nat Rev Rheumatol 2010 6 538 46 10.1038/nrrheum.2010.121 20683438
9 Westerweel PE Luyten RKMAC Koomans HA et al Premature atherosclerotic cardiovascular disease in systemic lupus erythematosus Arthritis Rheum 2007 56 1384 96 10.1002/art.22568 17469095
10 Esdaile JM Abrahamowicz M Grodzicky T et al Traditional Framingham risk factors fail to fully account for accelerated atherosclerosis in systemic lupus erythematosus Arthritis Rheum 2001 44 2331 7 10.1002/1529-0131(200110)44:10<2331::aid-art395>3.0.co;2-i 11665973
11 Roman MJ Shanker B-A Davis A et al Prevalence and correlates of accelerated atherosclerosis in systemic lupus erythematosus N Engl J Med 2003 349 2399 406 10.1056/NEJMoa035471 14681505
12 Atehortúa L Rojas M Vásquez GM et al Endothelial Alterations in Systemic Lupus Erythematosus and Rheumatoid Arthritis: Potential Effect of Monocyte Interaction Mediators Inflamm 2017 2017 9680729 10.1155/2017/9680729 28546658
13 Conrad N Verbeke G Molenberghs G et al Autoimmune diseases and cardiovascular risk: a population-based study on 19 autoimmune diseases and 12 cardiovascular diseases in 22 million individuals in the UK Lancet 2022 400 733 43 10.1016/S0140-6736(22)01349-6 36041475
14 Mendoza-Pinto C Rojas-Villarraga A Molano-González N et al Endothelial dysfunction and arterial stiffness in patients with systemic lupus erythematosus: A systematic review and meta-analysis Atherosclerosis 2020 297 55 63 10.1016/j.atherosclerosis.2020.01.028 32078830
15 Moschetti L Piantoni S Vizzardi E et al Endothelial Dysfunction in Systemic Lupus Erythematosus and Systemic Sclerosis: A Common Trigger for Different Microvascular Diseases Front Med (Lausanne) 2022 9 849086 10.3389/fmed.2022.849086 35462989
16 Wigren M Nilsson J Kaplan MJ Pathogenic immunity in systemic lupus erythematosus and atherosclerosis: common mechanisms and possible targets for intervention J Intern Med 2015 278 494 506 10.1111/joim.12357 25720452
17 Ding X Xiang W He X IFN-I Mediates Dysfunction of Endothelial Progenitor Cells in Atherosclerosis of Systemic Lupus Erythematosus Front Immunol 2020 11 581385 10.3389/fimmu.2020.581385 33262760
18 Marui N Offermann MK Swerlick R et al Vascular cell adhesion molecule-1 (VCAM-1) gene transcription and expression are regulated through an antioxidant-sensitive mechanism in human vascular endothelial cells J Clin Invest 1993 92 1866 74 10.1172/JCI116778 7691889
19 Springer TA Traffic signals for lymphocyte recirculation and leukocyte emigration: the multistep paradigm Cell 1994 76 301 14 10.1016/0092-8674(94)90337-9 7507411
20 Park JK Kim J-Y Moon JY et al Altered lipoproteins in patients with systemic lupus erythematosus are associated with augmented oxidative stress: a potential role in atherosclerosis Arthritis Res Ther 2016 18 306 10.1186/s13075-016-1204-x 28038677
21 Yang X Li Y Li Y et al Oxidative Stress-Mediated Atherosclerosis: Mechanisms and Therapies Front Physiol 2017 8 600 10.3389/fphys.2017.00600 28878685
22 Teixeira V Tam LS Novel Insights in Systemic Lupus Erythematosus and Atherosclerosis Front Med (Lausanne) 2017 4 262 10.3389/fmed.2017.00262 29435447
23 Moore S Juo HH Nielsen CT et al Role of Neutrophil Extracellular Traps Regarding Patients at Risk of Increased Disease Activity and Cardiovascular Comorbidity in Systemic Lupus Erythematosus J Rheumatol 2020 47 1652 60 10.3899/jrheum.190875 31839592
24 Carmona-Rivera C Zhao W Yalavarthi S et al Neutrophil extracellular traps induce endothelial dysfunction in systemic lupus erythematosus through the activation of matrix metalloproteinase-2 Ann Rheum Dis 2015 74 1417 24 10.1136/annrheumdis-2013-204837 24570026
25 Haque S Alexander MY Bruce IN Endothelial progenitor cells: a new player in lupus? Arthritis Res Ther 2012 14 203 10.1186/ar3700 22356717
26 Drosos GC Vedder D Houben E et al EULAR recommendations for cardiovascular risk management in rheumatic and musculoskeletal diseases, including systemic lupus erythematosus and antiphospholipid syndrome Ann Rheum Dis 2022 81 768 79 10.1136/annrheumdis-2021-221733 35110331
27 Schonenberg-Meinema D Bergkamp SC Nassar-Sheikh Rashid A et al Nailfold capillary abnormalities in childhood-onset systemic lupus erythematosus: a cross-sectional study compared with healthy controls Lupus (Los Angel) 2021 30 818 27 10.1177/0961203321998750
28 Schonenberg-Meinema D Bergkamp SC Nassar-Sheikh Rashid A et al Nailfold capillary scleroderma pattern may be associated with disease damage in childhood-onset systemic lupus erythematosus: important lessons from longitudinal follow-up Lupus Sci Med 2022 9 e000572 10.1136/lupus-2021-000572 35140136
29 Bergkamp SC Wahadat MJ Salah A et al Dysregulated endothelial cell markers in systemic lupus erythematosus: a systematic review and meta-analysis J Inflamm (Lond) 2023 20 18 10.1186/s12950-023-00342-1 37194071
30 Gladman DD Ibañez D Urowitz MB Systemic lupus erythematosus disease activity index 2000 J Rheumatol 2002 29 288 91 11838846
31 Smith V Vanhaecke A Herrick AL et al Fast track algorithm: How to differentiate a “scleroderma pattern” from a “non-scleroderma pattern.” Autoimmun Rev 2019 18 102394 10.1016/j.autrev.2019.102394 31520797
32 Mukaka MM Statistics corner: A guide to appropriate use of correlation coefficient in medical research Malawi Med J 2012 24 69 71 23638278
33 Mostmans Y Cutolo M Giddelo C et al The role of endothelial cells in the vasculopathy of systemic sclerosis: A systematic review Autoimmun Rev 2017 16 774 86 10.1016/j.autrev.2017.05.024 28572048
34 Martin FA Murphy RP Cummins PM Thrombomodulin and the vascular endothelium: insights into functional, regulatory, and therapeutic aspects Am J Physiol Heart Circ Physiol 2013 304 H1585 97 10.1152/ajpheart.00096.2013 23604713
35 Boehme MW Raeth U Galle PR et al Serum thrombomodulin-a reliable marker of disease activity in systemic lupus erythematosus (SLE): advantage over established serological parameters to indicate disease activity Clin Exp Immunol 2000 119 189 95 10.1046/j.1365-2249.2000.01107.x 10606982
36 Watanabe-Kusunoki K Nakazawa D Ishizu A et al Thrombomodulin as a Physiological Modulator of Intravascular Injury Front Immunol 2020 11 575890 10.3389/fimmu.2020.575890 33042158
37 Kiraz S Ertenli I Benekli M et al Clinical significance of hemostatic markers and thrombomodulin in systemic lupus erythematosus: evidence for a prothrombotic state Lupus (Los Angel) 1999 8 737 41 10.1191/096120399678840918
38 Lee WF Wu CY Yang HY et al Biomarkers associating endothelial Dysregulation in pediatric-onset systemic lupus erythematous Pediatr Rheumatol Online J 2019 17 69 10.1186/s12969-019-0369-7 31651352
39 Mahmood A Farhad G Mehrzad H et al Assessment of Serum Thrombomodulin in Patients with Systemic Lupus Erythematosus in Rheumatology Research Center Acta Med Iran 1970 47
40 Singh S Anshita D Ravichandiran V MCP-1: Function, regulation, and involvement in disease Int Immunopharmacol 2021 101 107598 10.1016/j.intimp.2021.107598 34233864
41 Cieślik P Hrycek A Pentraxin 3 as a biomarker of local inflammatory response to vascular injury in systemic lupus erythematosus Autoimmunity 2015 48 242 50 10.3109/08916934.2014.983264 25401491
42 Liu M Guo S Stiles JK The emerging role of CXCL10 in cancer (Review) Oncol Lett 2011 2 583 9 10.3892/ol.2011.300 22848232
43 Narumi S Takeuchi T Kobayashi Y et al Serum levels of ifn-inducible PROTEIN-10 relating to the activity of systemic lupus erythematosus Cytokine 2000 12 1561 5 10.1006/cyto.2000.0757 11023674
44 Ardoin SP Schanberg LE Sandborg C et al Laboratory markers of cardiovascular risk in pediatric SLE: the APPLE baseline cohort Lupus (Los Angel) 2010 19 1315 25 10.1177/0961203310373937
45 Boros CA Bradley TJ Cheung MMH et al Early determinants of atherosclerosis in paediatric systemic lupus erythematosus Clin Exp Rheumatol 2011 29 575 81 21640055
46 Robinson GA Waddington KE Coelewij L et al Increased apolipoprotein-B:A1 ratio predicts cardiometabolic risk in patients with juvenile onset SLE EBioMedicine 2021 65 103243 10.1016/j.ebiom.2021.103243 33640328
47 Peng J Dönnes P Ardoin SP et al Atherosclerosis Progression in the APPLE Trial Can Be Predicted in Young People With Juvenile-Onset Systemic Lupus Erythematosus Using a Novel Lipid Metabolomic Signature Arthritis Rheumatol 2024 76 455 68 10.1002/art.42722 37786302
48 Wang J-M Xu W-D Yuan Z-C et al Serum levels and gene polymorphisms of angiopoietin 2 in systemic lupus erythematosus patients Sci Rep 2021 11 10 10.1038/s41598-020-79544-z 33420149
49 Ciołkiewicz M Kuryliszyn-Moskal A Klimiuk PA Analysis of correlations between selected endothelial cell activation markers, disease activity, and nailfold capillaroscopy microvascular changes in systemic lupus erythematosus patients Clin Rheumatol 2010 29 175 80 10.1007/s10067-009-1308-7 19907914
