Serum Metabolomic Signatures Can Predict Subclinical Atherosclerosis in Patients With Systemic Lupus Erythematosus.
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ABSTRACT:
SUBMITTER: Coelewij L
PROVIDER: S-EPMC7610443 | biostudies-literature | 2021 Apr
REPOSITORIES: biostudies-literature
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Serum Metabolomic Signatures Can Predict Subclinical Atherosclerosis in Patients With Systemic Lupus Erythematosus.
Coelewij Leda L Waddington Kirsty E KE Robinson George A GA Chocano Elvira E McDonnell Thomas T Farinha Filipa F Peng Junjie J Dönnes Pierre P Smith Edward E Croca Sara S Bakshi Jyoti J Griffin Maura M Nicolaides Andrew A Rahman Anisur A Jury Elizabeth C EC Pineda-Torra Ines I
Arteriosclerosis, thrombosis, and vascular biology 20210204 4
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Project description:AimTo determine periodontitis prevalence in patients with systemic lupus erythematosus (SLE) and to assess whether periodontitis in SLE patients is associated with a greater subclinical atherosclerosis.MethodsAn observational case-control study was conducted in SLE (cases) and patients without any rheumatic diseases (controls), matched for sex. Sociodemographic and cardiometabolic variables were gathered, and SLE activity was assessed through several indexes. Periodontal examination registered probing pocket depth, clinical attachment level, bleeding on probing, plaque index, and tooth loss. Subclinical atherosclerosis was assessed by measuring the carotid-femoral pulse wave velocity (PWV) by Doppler velocimetry, homocysteine levels, C-reactive protein (CRP), and erythrocyte sedimentation rate (ESR). Bivariate analyses and logistic regression were used to assess the association of any of the studied variables with SLE.ResultsSeventy-one cases and 72 controls were included in the study. Thirty-nine SLE patients (54.9%) were diagnosed with periodontitis, compared with 16 controls (22.2%). High levels of PWV (≥7.7 m/s, 75th percentile) were shown by 44.3% of the cases vs. 22.4% of the controls (p = .011). Among SLE patients, those with periodontitis showed higher PWV values (8.1 ± 1.52 vs. 7.16 ± 1.11 m/s, p = .006) and higher homeostasis model assessment index (indicative of insulin resistance) (1.7 ± 0.73 vs. 2.92 ± 3.05, p = .028) compared to those with periodontal health. Logistic regression showed that waist circumference (OR 1.06, 95% CI 1.01-1.12, p = .015); ESR (OR 1.09, 95% CI 1.03-1.16, p = .003); and bleeding on probing (OR 1.1, 95% CI 1.01-1.19, p = .018) were associated with the risk of SLE.ConclusionSystemic lupus erythematosus patients showed a higher periodontitis percentage than controls. Higher PWV values were found in SLE patients with periodontitis, indicating a higher prevalence of subclinical atherosclerosis. Patients with higher gingival bleeding showed a higher risk of SLE.
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Project description:BackgroundLupus nephritis (LN) occurs in 50% of patients with systemic lupus erythematosus (SLE), causing considerable morbidity and even mortality. Previous studies had shown the potential of metabolic profiling in the diagnosis of SLE or LN. However, few metabonomics studies have attempted to distinguish SLE from LN based on metabolic changes. The current study was designed to find new candidate serum signatures that could differentiate LN from SLE patients using a non-targeted metabonomics method based on ultra high performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS).MethodMetabolic profiling of sera obtained from 21 healthy controls, 52 SLE patients and 43 LN patients. We used SPSS 25.0 for statistical analysis. Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) and metabolic pathway analysis were used to analyze the metabolic data.ResultsUpon comparison of SLE and LN groups, 28 differential metabolites were detected, the majority of which were lipids and amino acids. Glycerolphospholipid metabolism, pentose and glucuronate interconversions and porphyrin and chlorophyll metabolism were obviously enriched in LN patients versus those with SLE. Among the 28 characteristic metabolites, five key serum metabolites including SM d34:2, DG (18:3(9Z,12Z,15Z)/20:5(5Z,8Z,11Z,14Z,17Z)/0:0), nervonic acid, Cer-NS d27:4, and PC (18:3(6Z,9Z,12Z)/18:3(6Z,9Z,12Z) performed higher diagnostic performance in discriminating LN from SLE (all AUC > 0.75). Moreover, combined analysis of neuritic acid, C1q, and CysC (AUC = 0.916) produced the best combined diagnosis.ConclusionThis study identified five serum metabolites that are potential indicators for the differential diagnosis of SLE and LN. Glycerolphospholipid metabolism may play an important role in the development of SLE to LN. The metabolites we screened can provide more references for the diagnosis of LN and more support for the pathophysiological study of SLE progressed to LN.
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Project description:Systemic lupus erythematosus (SLE) is a chronic, autoimmune disease affecting multiple heterogeneous organs and systems. SLE is associated with increased risk of atherosclerosis and increased cardiovascular complications. In this study, we specifically aimed to identify patients with SLE who are genetically at risk for developing atherosclerosis. Sureprint G3 Human Gene Expression 8x60K Microarray kit (Agilent technologies, Santa Clara, CA, USA) was used in our study. Genes showing differences in expression between the groups were identified by using GeneSpring GX 10.0 program. A total of 155 genes showing expression level difference were detected between SLE patients and healthy controls. In molecular network analysis.
2020-07-22 | GSE154851 | GEO
Project description:Metabolic fingerprints in serum characterize diverse diseases for diagnostics and biomarker discovery. The identification of systemic lupus erythematosus (SLE) by serum metabolic fingerprints (SMFs) will facilitate precision medicine in SLE in an early and designed manner. Here, a discovery cohort of 731 individuals including 357 SLE patients and 374 healthy controls (HCs), and a validation cohort of 184 individuals (SLE/HC, 91/93) are constructed. Each SMF is directly recorded by nano-assisted laser desorption/ionization mass spectrometry (LDI MS) within 1 minute using 1 µL of native serum, which contains 908 mass to charge features. Sparse learning of SMFs achieves the SLE identification with sensitivity/specificity and area-under-the-curve (AUC) up to 86.0%/92.0% and 0.950 for the discovery cohort. For the independent validation cohort, it exhibits no performance loss by affording the sensitivity/specificity and AUC of 89.0%/100.0% and 0.992. Notably, a metabolic biomarker panel is screened out from the SMFs, demonstrating the unique metabolic pattern of SLE patients different from both HCs and rheumatoid arthritis patients. In conclusion, SMFs characterize SLE by revealing its unique metabolic pattern. Different regulation of small molecule metabolites contributes to the precise diagnosis of autoimmune disease and further exploration of the pathogenic mechanisms.
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Project description:ObjectivesIn this study, we aimed to identify patients with systemic lupus erythematosus (SLE) who are genetically at risk for developing atherosclerosis.Patients and methodsBetween November 2014 and May 2016, a total of 38 patients with SLE (36 females, 2 males; mean age: 37.6 years; range, 18 to 71 years) and 32 healthy females (mean age: 31.5 years; range, 19 to 54 years) were included in the study. Carotid intima-media thickness (CIMT) was measured using high-resolution B-mode ultrasonography. SurePrint G3 Human Gene Expression 8x60K Microarray kit was used in our study. Genes showing differences in expression between the groups were identified by using GeneSpring GX 10.0 program. Pathway analyses of gene expressions were performed using Ingenuity Pathways Analysis (IPA). Gene ontology analyses were performed using the Protein Analysis Through Evolutionary Relationships (PANTHER).ResultsClinical findings of SLE patients were mainly photosensitivity (71.1%), arthritis (63.2%), lupus nephritis (55.3%), thrombocytopenia (26.3%), and autoimmune hemolytic anemia (21.1%). A total of 155 genes showing expression level difference were detected between SLE patients and healthy controls. In molecular network analysis, 28.2% of all genes were found to be directly or indirectly associated with atherosclerosis and cardiovascular disease.ConclusionIn SLE patients, many genes are expressed differently from healthy individuals. Expression of these genes is important in the pathogenesis of SLE. Genes identified differently in gene expression analysis can help us to identify SLE patients at risk for atherosclerosis in the Turkish population.
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Project description:Systemic lupus erythematosus (SLE) is a chronic autoimmune disease that affects females more than males, with African Americans developing more severe manifestation of the disease. SLE patients are at increased risk for cardiovascular disease (CVD), and SLE women 35-44 years old have 50 fold the incidence rate of CVD. Because SLE patients do not follow the typical age and gender pattern for CVD, but instead an accelerated disease course, the traditional biomarkers of elevated LDL and total cholesterol levels do not accurately assess their CVD risk. Recently, we have reported that African American SLE patients had higher ceramide, hexosylceramide, sphingosine and dihydrosphingosine 1-phosphate levels compared to their healthy controls, and those with atherosclerosis had higher sphingomyelin and sphingoid bases levels than those without (PLoS One. 2019; e0224496). In the current study, we sought to identify sphingolipid species that correlate with and pose the potential to predict atherosclerosis severity in African American SLE patients. Plasma samples from a group of African American predominantly female SLE patients with well-defined carotid atherosclerotic plaque burden were analyzed for sphingolipidomics using targeted mass spectroscopy. The data demonstrated that at baseline, plaque area and C3 values correlated inversely with most lactoceramide species. After one-year follow-up visit, values of the change of plaque area correlated positively with the lactoceramide species. There was no correlation between LDL-C concentrations and lactoceramide species. Taken together, lactocylcermide levels may have a 'predictive' value and sphingolipidomics have an added benefit to currently available tools in early diagnosis and prognosis of African American SLE patients with CVD.
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