Serum uric acid as a predictor for nephritis in Egyptian patients with systemic lupus erythematosus

Objective Lupus nephritis (LN) is closely associated with hyperuricemia, and uric acid is considered a risk factor for renal involvement in systemic lupus erythematosus (SLE). This study aimed to examine the association between serum uric acid (SUA) level and LN development and progression in SLE patients with normal renal function. Methods A total of 60 SLE patients with normal renal function from Ain Shams University Hospital were selected and assigned to group 1 (30 patients with LN) and group 2 (30 patients without LN). All patients were subjected to history taking, clinical examination, disease activity assessment based on SLE disease activity index (SLEDAI) and renal SLEDAI (SLEDAI-R) scores, and laboratory investigations, including as SUA, complete blood count, blood urea nitrogen (BUN), serum creatinine, creatinine clearance, urine analysis, protein/creatinine ratio, 24-h urinary protein excretion, Antinuclear antibodies (ANA), anti-dsDNA antibody, and serum complement (C3, C4). Results Disease duration, SLEDAI score, and SUA level were higher in group 1 than in group 2 (p < 0.001). SUA level was positively correlated with SLEDAI and SLEDAI-R scores, proteinuria, urinary casts, renal biopsy class, disease activity and chronicity indices, BUN level, and serum creatinine level but was negatively correlated with creatinine clearance (p < 0.05). SUA was a predictor of LN development in SLE patients (sensitivity, 83.3%; specificity, 70%). Conclusion SUA is associated with the development of lupus nephritis in patients with normal kidney function also SUA in-dependently correlated with disease activity and chronicity in LN.

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Serum GlycA level is a candidate biomarker for disease activity in systemic lupus erythematosus and for proliferative status of lupus nephritis, independent of renal function impairment.

10.1101/493809 ◽

2018 ◽

Author(s):

Tim Dierckx ◽

Sylvie Goletti ◽

Laurent Chiche ◽

Laurent Daniel ◽

Bernard Lauwerys ◽

...

Keyword(s):

Systemic Lupus Erythematosus ◽

Logistic Regression ◽

Renal Function ◽

Lupus Nephritis ◽

Serum Albumin ◽

Disease Activity ◽

Lupus Erythematosus ◽

Regression Models ◽

Systemic Lupus ◽

Logistic Regression Models

Objective: Glycoprotein acetylation (GlycA) is a novel biomarker for chronic inflammation, associated to cardiovascular risk. Serum GlycA levels are increased in several inflammatory diseases, including systemic lupus erythematosus (SLE). We investigated the relevance of serum GlycA measurement in SLE and lupus nephritis (LN). Methods: GlycA was measured by NMR in 194 serum samples from patients and controls. Comparisons were performed between groups. Clinical and biological parameters were tested for correlation with GlycA levels. The predictive value of GlycA to differentiate proliferative from non-proliferative LN was determined using logistic regression models. Results: GlycA was correlated to C-reactive protein (CRP), neutrophil count, proteinuria and the SLE disease activity index (SLEDAI), and inversely with serum albumin. GlycA was higher in active (n=105) than in quiescent (n=39) SLE patients, in healthy controls (n=29), and in patients with non-lupus nephritis (n=21), despite a more altered renal function in the latter. In patients with biopsy-proven active LN, GlycA was higher in proliferative (n=32) than non-proliferative (n=11) LN, independent of renal function and proteinuria level. Logistic regression models showed that, in univariate models, GlycA outperforms traditional biomarkers. A bivariate model using GlycA and BMI better predicted the proliferative status of LN than a model comprising CRP, renal function (eGFR), serum albumin, proteinuria, C3 consumption and the presence of anti-dsDNA antibodies. Conclusion: Serum GlycA is elevated in SLE, and correlates with disease activity and LN. Serum GlycA, which summarizes different inflammatory processes, could be a valuable biomarker to discriminate proliferative from non-proliferative LN and should be tested in large, prospective cohorts.

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Cytokine clusters as potential diagnostic markers of disease activity and renal involvement in systemic lupus erythematosus

Journal of International Medical Research ◽

10.1177/0300060520926882 ◽

2020 ◽

Vol 48 (6) ◽

pp. 030006052092688

Author(s):

Joonhong Park ◽

Woori Jang ◽

Hye Sun Park ◽

Ki Hyun Park ◽

Seung-Ki Kwok ◽

...

Keyword(s):

Systemic Lupus Erythematosus ◽

Cluster Analysis ◽

Disease Activity ◽

Lupus Erythematosus ◽

Renal Involvement ◽

Principal Component ◽

Systemic Lupus ◽

Group 2 ◽

And Cluster Analysis ◽

Group 1

Objective To describe interactions among cytokines and to identify subgroups of systemic lupus erythematosus (SLE) patients based on cytokine levels using principal component analysis and cluster analysis. Methods Levels of 12 cytokines were measured using sensitive multiplex bead assays and associations with SLE features including disease activity and renal involvement were assessed. Results In a group of 203 SLE patients, strong correlations were observed between interleukin (IL)6 and interferon (IFN)γ levels (r = 0.624), IL17 and IFNγ levels (r = 0.768), and macrophage inflammatory protein (MIP)1α and MIP1β levels (r = 0.675). Cluster analysis revealed two distinct patient groups characterized by high levels of IL8, MIP1α, and MIP1β (group 1) or of IL2, IL6, IL10, IL12, IFNγ, and tumor necrosis factor α (group 2). Active disease was more common in group 1 (49/88, 55.7%) than in group 2 (40/115, 34.8%). More patients in group 2 had renal involvement (42/115, 36.5%) than in group 1 (22/88, 25%). Conclusions Assessment of cytokine profiles can identify distinct SLE patient subgroups and aid in understanding clinical heterogeneity and immunological phenotypes.

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POS0174 IMMUNOPHENOTYPE OF SJÖGREN´S SYNDROME AND SYSTEMIC LUPUS ERYTHEMATOSUS PATIENTS IDENTIFIED TWO ENDOTYPES WITH POTENTIAL THERAPEUTIC IMPLICATIONS

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2021-eular.2434 ◽

2021 ◽

Vol 80 (Suppl 1) ◽

pp. 300.1-300

Author(s):

L. Martin-Gutierrez ◽

J. Peng ◽

G. Robinson ◽

M. Naja ◽

H. Peckham ◽

...

Keyword(s):

Machine Learning ◽

Systemic Lupus Erythematosus ◽

Disease Activity ◽

Lupus Erythematosus ◽

Immune Cell ◽

T Cell Subsets ◽

Systemic Lupus ◽

Immune Cell Subsets ◽

Group 2 ◽

Group 1

Background:Primary Sjögren’s syndrome (pSS) and systemic lupus erythematosus (SLE) are chronic autoimmune rheumatic diseases (ARDs) that share a strong female gender bias, as well as genetic, clinical and serological characteristics.Although significant progress has been made in improving treatment and patient related outcomes in pSS and SLE, there is a need for improved early diagnosis, adequate therapy monitoring, treatment of refractory manifestations and strategies to address co-morbidities.However, the results of many clinical trials are disappointing, and nobiologic treatments are licensedin pSS, while few are available for SLE patients with refractory disease.Objectives:Identifying shared immunological features between patients with pSS and SLE that could lead to better treatment selection using a stratification approach.Methods:Immune-phenotyping of 29 immune-cell subsets in peripheral blood from patients with pSS (n=45), SLE (n=29) and secondary SS associated with SLE (SLE/SS) (n=14) with low disease activity or in clinical remission, and sex-matched healthy controls (n=31), was performed using flow cytometry. Data were analysed using logistic regression and multiple t-tests andsupervised machine learning (balanced random forest-BRF, sparse partial least squares discriminant analysis-sPLS-DA). Patients were stratified by k-means clustering. Clinical trajectories were analysed over 5 year follow-up.Results:Comparing the immune profile of pSS and SLE patients using a variety of statistical and machine learning (ML) approaches, identified very few statistically significant differences between the two cohorts despite patients having a different clinical presentation and diagnosis. Thus, we hypothesised that immune-based subtypes could be shared between pSS, SLE and SLE/SS patients. Unsupervised k-means clustering was applied to the immunological features of the combined patient cohorts and two distinct patient endotypes, were identified: Group-1 (n=49; pSS=24, SLE=19, SLE/SS=6) and Group-2 (n=39; pSS=21, SLE=10, SLE/SS=8). Significant differences in immune-cell phenotypes across B-cell and T-cell subsets were identified by logistic regression, BRF (AUC=0.9942, assessed by 10-fold cross-validation) and sPLS-DA analysis. Comparison of the multiple analysis approaches identified eight common immune-cell subsets, including total and memory CD4+ and CD8+ T-cell subsets but no B-cell subsets. Using this common immune-signature the stratification between the groups was maintained and slightly improved (AUC=0.9979 and accuracy 96.16%). Interestingly, patients in Group-2 had elevated disease activity measures at baseline and over a 5-year trajectory compared to Group-1. Finally, correlation analysis identifed correlations between disease activity markers and the top ranked immune features from the ML models.Conclusion:The identified immune-cell signatures could reflect the underlying disease pathogenesis that spans diagnositc criteria and could be used to select patients for targeted therapeutic approaches.Acknowledgements:LM-G is supported by a project grant from The Dunhill Medical Trust (RPGF1902\117); JP is supported by Versus Arthritis (21226). GAR is supported by Lupus UK, The Rosetrees Trust (M409) and Versus Arthritis (21593). MN is supported by NIHR UCLH Biomedical Research Centre (BRC525/III/CC/191350). HP has a Versus Arthritis PhD studentship (22203). This work was performed within the Centre for Adolescent Rheumatology Versus Arthritis at UCL UCLH and GOSH supported by grants from Versus Arthritis (21593 and 20164), GOSCC, and the NIHR-Biomedical Research Centres at both GOSH and UCLH.We would like to thank Mr Jamie Evans for expert support with flow cytometry analysis and Ms Eve McLoughlin for support with patient recruitment.Disclosure of Interests:None declared

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AB0051 SERUM AMYLOID A AND PENTRAXIN 3: INNATE IMMUNE RESPONSE AND DISEASE ACTIVITY IN SYSTEMIC LUPUS ERYTHEMATOSUS

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2020-eular.1933 ◽

2020 ◽

Vol 79 (Suppl 1) ◽

pp. 1328.1-1328

Author(s):

R. Assandri ◽

G. Martellosio ◽

A. Montanelli

Keyword(s):

Disease Activity ◽

Lupus Erythematosus ◽

Serum Amyloid A ◽

Serum Levels ◽

Innate Immune ◽

Pentraxin 3 ◽

Systemic Lupus ◽

Amyloid A ◽

Group 2 ◽

Group 1

Background:Systemic Lupus Erythematosus (SLE) is an autoimmune disease that involves several molecular patterns with a wide spectrum of clinical manifestations and symptoms. Inflammation and related pathway play a role in SLE pathogenesis. The pentraxin superfamily including long and short pentraxin, C Reactive Protein CRP, Serum amyloid A (SAA), Pentraxin 3 (PTX3) are key components of innate immune system and induce a variety of inflammation associated pathway. However Literature provides several evidences that CRP serum levels not correlated with clinical and immunological manifestations. This situation affected clinical practice and the patient follow up. PTX3 have been identified as a component of inflammatory status in several autoimmune conditions. SAA is an acute phase protein secreted in large quantity during inflammation.Objectives:We want to evaluated SAA, PTX3 and CRP concentrations, their correlation between SLE Disease Activity Index (SLEDAI), that including complement fractions C3, C4.Methods:We enrolled fifty patients that fulfilled the SLE American College of Rheumatology criteria and fifty healthy subjects. The SLE disease activity was classified with the SLEDAI (0 to 12). Patients were divided into two groups according to SLEDAI score: inactive group (Group 1, 25 patients, 50%: SLEDAI < 4) and active group (Group 2, 25 patients, 50%: SLEDAI 5 to 12). PTX3 concentration was measured by a sandwich ELISA kit (Hycult) with 2.8 ng/mL cut-off point. SAA concentration was detected by nephelometry performed on a BN ProSpec System (Siemens, Germany), with assay kit based on polyclonal antibodies (Siemens Healthcare Diagnostics Products, Germany, 6.5 mg/L cut-off point). High sensitive CRP concentrations were determined using the ci8200 platform (Abbott Laboratories Chicago, Illinois).Results:Plasma PTX3 and serum SAA levels was significantly higher in SLE patients than in the healthy subjects (PTX311.5 ± 7.3 ng/mL vs 2.3 ± 1.1; p < 0.001; SAA: 87 ±77 mg/L vs 2.6±2.5; p < 0.001). These differences were not evident in CRP levels (8.5 ± 7.8 mg/L vs 6.2± 2.5). Considering two groups, there were statistical differences in PTX3 level (Group 2: 14.9 ± 12 ng/mL vs Group 1: 2.16 ±0.5 ng/mL, p<0,05) and SAA concentration (Group 2: 114 ± 89 ng/mL vs Group 1: 3.6 ±1.7 ng/mL, p<0,05) but not in CRP concentration (Group 2: 11.5 ± 8.4 mg/L vs Group 1: 9.5 ±3.5). There was a significantly negative correlation between C3, C4 fractions, PTX3 and SSA levels (respectively r = −0.74, p=<0.05, and r = −0.79, p<0.05). No statistical correlation were appeared between C3, C4 fractions and CRP serum levels (r= −0,12., p= 0.82, and r= −0.18, p= 0,21). We noted a positive significant correlation between SLEDAI, PTX3 and SAA concentration (r = 0.79, p < 0.05, 0.83, p < 0.05, respectively) an increase in PTX3 and SAA levels followed the lupus flare and symptoms. No significant correlation appeared between SLEDAI and CRP (r= 0.15, p=0.89)Conclusion:PTX3 and SAA concentration was significantly higher in SLE patients than the healthy control subjects and their levels reflected disease activity. We showed a direct correlation between PTX3 and SAA. In SLE patients PTX3 and SAA concentrations were correlated with SLEDAI. We suggest an integrate viewpoint in witch SAA and PTX3 may play a role as a biomarker of disease activity, with synergic work during SLE events. Evidences suggested that PTX3 and SAA could trigger the same molecular pathway, by TLR4, via NF-kB.References:[1]Assandri R, Monari M Montanelli A. Pentraxin 3 in Systemic Lupus Erithematosus: Questions to be Resolved, Translational Biomedicine (2015)Disclosure of Interests:None declared

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Clinical and immunological characteristics of 150 systemic lupus erythematosus patients in Jamaica: a comparative analysis

Lupus ◽

10.1177/0961203317707828 ◽

2017 ◽

Vol 26 (13) ◽

pp. 1448-1456 ◽

Cited By ~ 4

Author(s):

K C Maloney ◽

T S Ferguson ◽

H D Stewart ◽

A A Myers ◽

K De Ceulaer

Keyword(s):

Systemic Lupus Erythematosus ◽

Lupus Nephritis ◽

Disease Activity ◽

Renal Biopsy ◽

Diagnostic Criteria ◽

Lupus Erythematosus ◽

Antinuclear Antibodies ◽

Damage Index ◽

Systemic Lupus ◽

Dsdna Antibodies

Background Epidemiological studies in systemic lupus erythematosus have been reported in the literature in many countries and ethnic groups. Although systemic lupus erythematosus in Jamaica has been described in the past, there has not been a detailed evaluation of systemic lupus erythematosus patients in urban Jamaica, a largely Afro-Caribbean population. The goal of this study was to describe the clinical features, particularly disease activity, damage index and immunological features, of 150 systemic lupus erythematosus subjects. Methods 150 adult patients (≥18 years) followed in rheumatology clinic at a tertiary rheumatology hospital centre (one of two of the major public referral centres in Jamaica) and the private rheumatology offices in urban Jamaica who fulfilled Systemic Lupus International Collaborating Clinics (SLICC) criteria were included. Data were collected by detailed clinical interview and examination and laboratory investigations. Hence demographics, SLICC criteria, immunological profile, systemic lupus erythematosus disease activity index 2000 (SLEDAI-2K) and SLICC/American College of Rheumatology (ACR) damage index (SDI) were documented. Results Of the 150 patients, 145 (96.7%) were female and five (3.3%) were male. The mean age at systemic lupus erythematosus onset was 33.2 ± 10.9. Mean disease duration was 11.3 ± 8.6 years. The most prevalent clinical SLICC criteria were musculoskeletal, with 141 (94%) of subjects experiencing arthralgia/arthritis, followed by mucocutaneous manifestations of alopecia 103 (68.7%) and malar rash 46 (30.7%), discoid rash 45 (30%) and photosensitivity 40 (26.7%). Lupus nephritis (biopsy proven) occurred in 42 (28%) subjects and 25 (16.7%) met SLICC diagnostic criteria with only positive antinuclear antibodies/dsDNA antibodies and lupus nephritis on renal biopsy. The most common laboratory SLICC criteria were positive antinuclear antibodies 136 (90.7%) followed by anti-dsDNA antibodies 95 (63.3%) and low complement (C3) levels 38 (25.3%). Twenty-seven (18%) met SLICC diagnostic criteria with only positive antinuclear antibodies/anti-dsDNA antibodies and lupus nephritis on renal biopsy. Mean SLEDAI score was 6.9 ± 5.1 with a range of 0–32. Organ damage occurred in 129 (86%) patients; mean SDI was 2.4 ± 1.8, with a range of 0–9. Conclusion These results are similar to the clinical manifestations reported in other Afro-Caribbean populations; however, distinct differences exist with respect to organ involvement and damage, particularly with respect to renal involvement, which appears to be reduced in our participants.

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The association between serum prolactin levels and interleukin-6 and systemic lupus erythematosus activity

Reumatismo ◽

10.4081/reumatismo.2018.1075 ◽

2018 ◽

Vol 70 (4) ◽

pp. 241-250 ◽

Cited By ~ 4

Author(s):

W.A. Wan Asyraf ◽

M.S. Mohd Shahrir ◽

W. Asrul ◽

A.W. Norasyikin ◽

O. Hanita ◽

...

Keyword(s):

Systemic Lupus Erythematosus ◽

Lupus Nephritis ◽

Disease Activity ◽

Lupus Erythematosus ◽

Prolactin Level ◽

Serum Prolactin ◽

Systemic Lupus ◽

Serum Prolactin Level ◽

Active Lupus Nephritis ◽

Active Lupus

Based on the recent evidence of association between hyperprolactinemia and systemic lupus erythematosus disease activity (SLEDAI), a study was conducted to analyze the association of hyperprolactinemia with lupus nephritis disease activity. In this cross-sectional study, the analysis was conducted on SLE patients who visited the University Kebangsaan Malaysia Medical Centre (UKMMC) Nephrology Clinic from August 2015 till February 2016. The disease activity was measured using the SLEDAI score, with more than 4 indicating active lupus nephritis. Basal resting prolactin level was analyzed in 43 patients with lupus nephritis, in 27.9% of them had raised serum prolactin. The median of serum prolactin level at 0 minutes was 19.91 ng/mL (IQR: 15.95-22.65 ng/ mL) for active lupus nephritis, which was significantly higher compared to the median of serum prolactin level of 14.34 ng/mL (IQR: 11.09-18.70 ng/mL) for patients in remission (p=0.014). The serum prolactin level positively correlated with SLEDAI (rhos: 0.449, p=0.003) and the UPCI level in lupus nephritis patients (rhos: 0.241, p=0.032). The results were reproduced when the serum prolactin was repeated after 30 minutes. However, the serum prolactin levels at 0 minutes were higher than those taken after 30 minutes (p=0.001). An assessment of serum IL-6 levels found that the active lupus nephritis patients had a higher median level of 65.91 pg/ mL (IQR: 21.96-146.14 pg/mL) compared to the in-remission level of 15.84 pg/mL (IQR: 8.38-92.84 pg/mL), (p=0.039). Further correlation analysis revealed that there was no statistical correlation between the interleukin (IL)-6 levels with serum prolactin, SLEDAI and other lupus nephritis parameters. An ROC curve analysis of serum prolactin at 0 minutes and serum prolactin after 30 minutes and IL-6 levels for prediction of SLE disease activity provided the cutoff value of serum prolactin at 0 minutes, which was 14.63 ng/mL with a sensitivity of 91.7% and specificity of 58.1% and AUC of 0.74 (p=0.015). This study concurred with the previous findings that stated that hyperprolactinemia is prevalent in SLE patients and correlated with clinical disease activity and UPCI level. The baseline of the fasting serum prolactin level was found to be a sensitive biomarker for the evaluation of lupus nephritis disease activity.

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