Dataset Information

Asymptomatic Carotid Atherosclerosis Cardiovascular Risk Factors and Common Hypertriglyceridemia Genetic Variants in Patients with Systemic Erythematosus Lupus.

ABSTRACT: SLE is associated with increased cardiovascular risk. The objective of this study was to determine the prevalence of asymptomatic carotid atherosclerosis to analyze its relationship with dyslipidemia and related genetic factors in a population of patients with SLE. Seventy-one SLE female patients were recruited. Carotid ultrasound, laboratory profiles, and genetic analysis of the ZPR1, APOA5, and GCKR genes were performed. SLE patients were divided into two groups according to the presence or absence of carotid plaques. Patients with carotid plaque had higher plasma TG (1.5 vs. 0.9 mmol/L, p = 0.001), Non-HDL-C (3.5 vs. 3.1 mmol/L, p = 0.025), and apoB concentrations (1.0 vs. 0.9 g/L, p = 0.010) and a higher prevalence of hypertension (80 vs. 37.5%, p = 0.003) than patients without carotid plaque. The GCKR C-allele was present in 83.3% and 16.7% (p = 0.047) of patients with and without carotid plaque, respectively. The GCKR CC genotype (OR = 0.026; 95% CI: 0.001 to 0.473, p = 0.014), an increase of 1 mmol/L in TG concentrations (OR = 12.550; 95% CI: 1.703 to 92.475, p = 0.013) and to be hypertensive (OR = 9.691; 95% CI: 1.703 to 84.874, p = 0.040) were independently associated with carotid atherosclerosis. In summary, plasma TG concentrations, CGKR CC homozygosity, and hypertension are independent predictors of carotid atherosclerosis in women with SLE.

SUBMITTER: Fanlo-Maresma M

PROVIDER: S-EPMC8160900 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:ObjectiveThe progress of accelerated atherosclerosis in systemic lupus erythematosus (SLE) is incompletely understood. Circulating osteopontin (OPN) is increased in autoimmune conditions, e.g. SLE, and its serum concentration was recently reported to associate with subclinical atherosclerosis in SLE, as measured by carotid intima-media thickness. The aim of this study was to investigate whether OPN may be used as a surrogate biomarker of subclinical atherosclerosis in SLE patients with different disease phenotypes.MethodsWe recruited 60 well-characterised SLE cases and 60 age- and sex-matched healthy controls. The SLE cases were divided into three different disease phenotypes: SLE with antiphospholipid syndrome (APS), lupus nephritis, and isolated skin and joint involvement. Plasma OPN was detected by ELISA (Quantikine®, R&D Systems). Common carotid arteries intima media thickness was compared between the studied groups in relation to OPN levels and risk factors for vascular changes. Intima media thickness of common carotid arteries was measured by using a sensitive ultrasound technique (LOGIQ™ E9 ultrasound, GE Healthcare).ResultsOPN levels were significantly higher among the entire SLE group (n = 60) compared to the healthy controls (P = 0.03). SLE cases with concomitant APS (n = 20) showed higher OPN levels than the controls (P = 0.004), whereas none of the other two subgroups differed significantly from the healthy controls. OPN and intima media thickness were correlated to several traditional risk factors of atherosclerosis, as well as to SLE-related factors. Yet, no significant correlation was observed between OPN levels and ultrasound findings of the common carotid arteries.ConclusionsIn line with previous studies, we observed increased OPN levels among SLE patients as compared to matched controls. However, the OPN concentrations did not correlate with intima media thickness of the common carotid arteries. Based on our findings, the use of OPN as a surrogate biomarker of subclinical atherosclerosis in SLE subjects, regardless of clinical phenotypes, cannot be recommended.

Project description:Background and aims: Patients with systemic lupus erythematosus (SLE) have a significantly higher incidence of atherosclerosis than the general population. Studies on atherosclerosis prediction models specific for SLE patients are very limited. This study aimed to build a risk prediction model for atherosclerosis in SLE. Methods: RNA sequencing was performed on 67 SLE patients. Subsequently, differential expression analysis was carried out on 19 pairs of age-matched SLE patients with (AT group) or without (Non-AT group) atherosclerosis using peripheral venous blood. We used logistic least absolute shrinkage and selection operator regression to select variables among differentially expressed (DE) genes and clinical features and utilized backward stepwise logistic regression to build an atherosclerosis risk prediction model with all 67 patients. The performance of the prediction model was evaluated by area under the curve (AUC), calibration curve, and decision curve analyses. Results: The 67 patients had a median age of 42.7 (Q1-Q3: 36.6-51.2) years, and 20 (29.9%) had atherosclerosis. A total of 106 DE genes were identified between the age-matched AT and Non-AT groups. Pathway analyses revealed that the AT group had upregulated atherosclerosis signaling, oxidative phosphorylation, and interleukin (IL)-17-related pathways but downregulated T cell and B cell receptor signaling. Keratin 10, age, and hyperlipidemia were selected as variables for the risk prediction model. The AUC and Hosmer-Lemeshow test p-value of the model were 0.922 and 0.666, respectively, suggesting a relatively high discrimination and calibration performance. The prediction model had a higher net benefit in the decision curve analysis than that when predicting with age or hyperlipidemia only. Conclusions: We built an atherosclerotic risk prediction model with one gene and two clinical factors. This model may greatly assist clinicians to identify SLE patients with atherosclerosis, especially asymptomatic atherosclerosis.

Dataset Information

Asymptomatic Carotid Atherosclerosis Cardiovascular Risk Factors and Common Hypertriglyceridemia Genetic Variants in Patients with Systemic Erythematosus Lupus.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets