Accelerated atherosclerosis is an established complication of systemic autoimmune diseases, particularly SLE. Young female patients with SLE are more likely to develop myocardial infarction than matched healthy controls, and CVD is nowadays one of the most common causes of death (27%) in lupus patients. While traditional CV risk factors cannot explain such increased CV morbidity associated with SLE, common disease factors shared between SLE, atherosclerosis and treatment exposure may be of outmost importance in this process. Our group made 3 findings of particular interest that could link SLE pathogenesis and atherosclerosis-associated immune dysregulation: 1/ the investigators identified specific immunometabolites (circulating nucleotide-derived metabolites adenine and N4-acetylcytidine), which are increased in the circulation of SLE patients. These immunometabolites trigger a constitutive inflammasome activation resulting in aberrant IL1-β production. Given that IL1-β inhibition was reported to significantly reduce CV events without altering lipid levels, the investigators propose that these immunometabolites may represent novel candidate biomarkers of CV risk stratification in SLE. 2/ the investigators identified OX40L as an important costimulatory molecule implicated in follicular helper T cell (Tfh) activation in SLE. Interestingly, OX40L polymorphism has been associated to both SLE and atherosclerosis, and Tfh have been recently shown to accelerate atherosclerosis progression. 3/ Immune complexes-activated platelets sustain aberrant immune response in SLE and block immunosuppressive functions of regulatory T cells (Tregs) in a P-selectin/PSGL1 dependent manner. Selectins and Tregs cell dysfunction are well accepted players in atherosclerosis pathogenesis. Thus there are multiple pathways that are shared between SLE and atherosclerosis and that may results in an increased risk of CV-associated morbidity in SLE patients. Exploring these interconnected pathways in SLE patients together with traditional and other well-established disease-related factors, might lead to a better stratification of CV risk in SLE. The aim of this study is to investigate the accuracy, predictive value and utility of immunological disease-related biomarkers in stratifying CV risk in patients with SLE.
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
OTHER
Masking
NONE
Enrollment
500
35 ml whole blood for Peripheral blood mononuclear cell (PBMC), serum and plasma
assessment of atherosclerotic plaques and measurement of carotid intima-media thickness (cIMT)
Food and exercise questionnaires validated by the American heart Association
CHU de Bordeaux - service de médecine interne
Bordeaux, France
CHU de Brest - service de rhumatologie
Brest, France
CHRU de Lille - service de Médecine Interne
Lille, France
AP-HP - Hôpital Cochin - service de Médecine Interne
Paris, France
CHU de Strasbourg - service d'Immunologie Clinique
Strasbourg, France
Universität Freiburg
Freiburg im Breisgau, Germany
Proportion of patients who show atherosclerotic plaque progression defined by the absence of carotid plaque in patients at baseline and its subsequent development at follow-up evaluated by semi-automated 3D vascular ultrasound
Time frame: At baseline (Day 0) and 18 months from baseline
Proportion of patients who show carotid Intima Media Thickness (cIMT) progression measured in the common carotid artery, at the bulb and the origin of the internal carotid artery
defined as an increase of 0.1mm or more evaluated by vascular ultrasound.
Time frame: At baseline (Day 0) and 18 months from baseline
Proportion of patients with atherosclerotic plaques
Time frame: At baseline (Day 0) and 18 months from baseline
Proportion of patients with hypertension
Time frame: At baseline (Day 0) and 18 months from baseline
Proportion of patients with Body Mass Index around 30 or more
Time frame: At baseline (Day 0) and 18 months from baseline
Proportion of patients who are smokers or past-smokers
Time frame: At baseline (Day 0) and 18 months from baseline
Proportion of patients who present a history of ischemic heart disease
Time frame: At baseline (Day 0) and 18 months from baseline
Proportion of patients who present a history of cerebral vascular accident
Time frame: At baseline (Day 0) and 18 months from baseline
Proportion of patients who present a history of peripheral artery disease
Time frame: At baseline (Day 0) and 18 months from baseline
Change in waist size in centimeters
Time frame: At baseline (Day 0) and 18 months from baseline
Change in blood glucose levels in milligram per deciliter
Time frame: At baseline (Day 0) and 18 months from baseline
Change in total cholesterol levels
Time frame: At baseline (Day 0) and 18 months from baseline
Change in HDL cholesterol levels
Time frame: At baseline (Day 0) and 18 months from baseline
Change in LDL cholesterol levels
Time frame: At baseline (Day 0) and 18 months from baseline
Change in triglycerides levels
Time frame: At baseline (Day 0) and 18 months from baseline
Change in Very Low Density Lipoprotein (VLDL) levels
Time frame: At baseline (Day 0) and 18 months from baseline
Change in C-Reactive protein levels
Time frame: At baseline (Day 0) and 18 months from baseline
Change in insulin levels
Time frame: At baseline (Day 0) and 18 months from baseline
Change in lupus disease activity according to Systemic Lupus Erythematosus Disease Activity Index (SLEDAI)
score (Min value: 0 - Max value: 105), with higher values mean higher disease activity.
Time frame: At baseline (Day 0) and 18 months from baseline
Change in lupus disease activity according to Systemic Lupus International Collaborating Clinics /American College of Rheumatology (SLICC/ACR) damage index
(Min value: 0 - Max value: 47), with higher values mean more important damages.
Time frame: At baseline (Day 0) and 18 months from baseline
Change in glucocorticoids intake
Time frame: At baseline (Day 0) and 18 months from baseline
Change in platelets-derived biomarkers (P-selectin, sCD154) in micrograms per milliliter, evaluated by Western Blot analysis.
Time frame: At baseline (Day 0) and 18 months from baseline
Change in neutrophils-derived biomarkers Proteins S100A8, A9, A8/9, and A12, IL-6 in micrograms per milliliter, evaluated by Western Blot analysis.
Time frame: At baseline (Day 0) and 18 months from baseline
Change in interleukin-6 levels
Time frame: At baseline (Day 0) and 18 months from baseline
Change in interleukin-12 levels
Time frame: At baseline (Day 0) and 18 months from baseline
Change in T-Follicular Helpers lymphocytes
Time frame: At baseline (Day 0) and 18 months from baseline
Change in myeloperoxidase-conjugated DNA levels in fluorescence intensity evaluated by fluorometric assay.
Time frame: At baseline (Day 0) and 18 months from baseline
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.