Clinicopathological correlation of patients with lupus nephritis: Data from a tertiary center in Saudi Arabia.

Systemic lupus erythematosus mainly affects young women, and approximately half of systemic lupus erythematosus patients develop lupus nephritis (LN). However, data on the types and remission rates of LN in Saudi Arabia are limited. Therefore, we aimed to highlight the LN remission rates in our population. A retrospective record review was conducted between January 2007 and December 2020 in a tertiary center in the western region of Saudi Arabia to determine the remission rates among patients with biopsy-proven LN who met the EULAR\ACR 2019 classification criteria. We identified 59 patients with biopsy-proven LN, mostly in young women. The common histopathological pattern was Class IV LN in 26 patients (44%). Three induction protocols were identified, along with systemic steroids: the high-dose cyclophosphamide protocol in 21 patients (35.6%), low-dose protocol in 4 patients (6.8%), and mycophenolate mofetil (MMF) in 41 patients (69.5%). Partial response, defined as the reduction of the 24-hour proteinuria by 25% at 3 months and 50% at 6 months, was achieved in 18 patients (33.3%) at 3 months and decreased to 13 patients (24.1%) at 6 months. Complete clinical response, defined as 24-hour urinary protein between 500 and 700 mg at 12 months, was achieved in 44 patients (81.5%). Complete remission was higher among patients with Class IV LN (64.4%). The achievement of partial clinical response at 3 months was significantly lower among patients with hypertension (P = .041). This study presented the LN remission rates in a single center in Saudi Arabia. Similar to previous studies, Class IV LN were the most common histopathological finding in this study. Complete remission at 12 months was achieved in 44 (81%) patients. Delayed remission is associated with hypertension at the time of LN diagnosis.

Polygenic Risk Score Predicts Earlier-Onset Adult Systemic Lupus Erythematosus and First-Year Renal Diseases in a Taiwanese Cohort.

OBJECTIVES: This study aimed to develop a predictive model using polygenic risk score (PRS) to forecast renal outcomes for adult systemic lupus erythematosus (SLE) in a Taiwanese population. METHODS: Patients with SLE (n=2782) and matched non-SLE controls (n=11 128) were genotyped using Genome-Wide TWB 2.0 single-nucleotide polymorphism (SNP) array. PRS models (C+T, LDpred2, Lassosum, PRSice-2, PRS-continuous shrinkage (CS)) were constructed for predicting SLE susceptibility. Logistic regression was assessed for C+T-based PRS association with renal involvement in patients with SLE. RESULTS: In the training set, C+T-based SLE-PRS, only incorporating 27 SNPs, outperformed other models with area under the curve (AUC) values of 0.629, surpassing Lassosum (AUC=0.621), PRSice-2 (AUC=0.615), LDpred2 (AUC=0.609) and PRS-CS (AUC=0.602). Additionally, C+T-based SLE-PRS demonstrated consistent predictive capacity in the testing set (AUC=0.620). Individuals in the highest quartile exhibited earlier SLE onset (39.06 vs 44.22 years, p<0.01), higher Systemic Lupus Erythematosus Disease Activity Index scores (3.00 vs 2.37, p=0.04), elevated risks of renal involvement within the first year of SLE diagnosis, including WHO class III-IV lupus nephritis (OR 2.36, 95% CI 1.47 to 3.80, p<0.01), estimated glomerular filtration rate <60 mL/min/1.73m2 (OR 1.49, 95% CI 1.18 to 1.89, p<0.01) and urine protein-to-creatinine ratio >150 mg/day (OR 2.07, 95% CI 1.49 to 2.89, p<0.01), along with increased seropositivity risks, compared with those in the lowest quartile. Furthermore, among patients with SLE with onset before 50 years, the highest PRS quartile was significantly associated with more serious renal diseases within the first year of SLE diagnosis. CONCLUSIONS: PRS of SLE is associated with earlier onset, renal involvement within the first year of SLE diagnosis and seropositivity in Taiwanese patients. Integrating PRS with clinical decision-making may enhance lupus nephritis screening and early treatment to improve renal outcomes in patients with SLE.

Machine learning-based identification of novel hub genes associated with oxidative stress in lupus nephritis: implications for diagnosis and therapeutic targets.

BACKGROUND: Lupus nephritis (LN) is a complication of SLE characterised by immune dysfunction and oxidative stress (OS). Limited options exist for LN. We aimed to identify LN-related OS, highlighting the need for non-invasive diagnostic and therapeutic approaches. METHODS: LN-differentially expressed genes (DEGs) were extracted from Gene Expression Omnibus datasets (GSE32591, GSE112943 and GSE104948) and Molecular Signatures Database for OS-associated DEGs (OSEGs). Functional enrichment analysis was performed for OSEGs related to LN. Weighted gene co-expression network analysis identified hub genes related to OS-LN. These hub OSEGs were refined as biomarker candidates via least absolute shrinkage and selection operator. The predictive value was validated using receiver operating characteristic (ROC) curves and nomogram for LN prognosis. We evaluated LN immune cell infiltration using single-sample gene set enrichment analysis and CIBERSORT. Additionally, gene set enrichment analysis explored the functional enrichment of hub OSEGs in LN. RESULTS: The study identified four hub genes, namely STAT1, PRODH, TXN2 and SETX, associated with OS related to LN. These genes were validated for their diagnostic potential, and their involvement in LN pathogenesis was elucidated through ROC and nomogram. Additionally, alterations in immune cell composition in LN correlated with hub OSEG expression were observed. Immunohistochemical analysis reveals that the hub gene is most correlated with activated B cells and CD8 T cells. Finally, we uncovered that the enriched pathways of OSEGs were mainly involved in the PI3K-Akt pathway and the Janus kinase-signal transducer and activator of transcription pathway. CONCLUSION: These findings contribute to advancing our understanding of the complex interplay between OS, immune dysregulation and molecular pathways in LN, laying a foundation for the identification of potential diagnostic biomarkers and therapeutic targets.

Comparison of late-onset and non-late-onset systemic lupus erythematosus individuals in a real-world electronic health record cohort.

Objective: Late-onset systemic lupus erythematosus (LO-SLE) is defined as SLE diagnosed at age 50 years or later. Current studies on LO-SLE are small and have conflicting results.Methods: Using a large, electronic health record (EHR)-based cohort of SLE individuals, we compared demographics, disease characteristics, SLE-specific antibodies, and medication prescribing practices in LO (n = 123) vs. NLO-SLE (n = 402) individuals.Results: The median age (interquartile range) at SLE diagnosis was 60 (56-67) years for LO-SLE and 28 (20-38) years for NLO-SLE. Both groups were predominantly female (85% vs. 91%, p = 0.10). LO-SLE individuals were more likely to be White than NLO-SLE individuals (74% vs. 60%, p = 0.005) and less likely to have positive dsDNA (39% vs. 58%, p = 0.001) and RNP (17% vs. 32%, p = 0.02) with no differences in Smith, SSA, and SSB. Autoantibody positivity declined with increasing age at SLE diagnosis. LO-SLE individuals were less likely to develop SLE nephritis (9% vs. 29%, p < 0.001) and less likely to be prescribed multiple classes of SLE medications including antimalarials (90% vs. 95%, p = 0.04), azathioprine (17% vs. 31%, p = 0.002), mycophenolate mofetil (12% vs. 38%, p < 0.001), and belimumab (2% vs. 8%, p = 0.02).Conclusion: LO-SLE individuals may be less likely to fit an expected course for SLE with less frequent positive autoantibodies at diagnosis and lower rates of nephritis, even after adjusting for race. Understanding how age impacts SLE disease presentation could help reduce diagnostic delays in SLE.

Evaluating inter-rater reliability in the context of "Sysmex UN2000 detection of protein/creatinine ratio and of renal tubular epithelial cells can be used for screening lupus nephritis": a statistical examination.

BACKGROUND: The evaluation of inter-rater reliability (IRR) is integral to research designs involving the assessment of observational ratings by two raters. However, existing literature is often heterogeneous in reporting statistical procedures and the evaluation of IRR, although such information can impact subsequent hypothesis testing analyses. METHODS: This paper evaluates a recent publication by Chen et al., featured in BMC Nephrology, aiming to introduce an alternative statistical approach to assessing IRR and discuss its statistical properties. The study underscores the crucial need for selecting appropriate Kappa statistics, emphasizing the accurate computation, interpretation, and reporting of commonly used IRR statistics between two raters. RESULTS: The Cohen's Kappa statistic is typically used for two raters dealing with two categories or for unordered categorical variables having three or more categories. On the other hand, when assessing the concordance between two raters for ordered categorical variables with three or more categories, the commonly employed measure is the weighted Kappa. CONCLUSION: Chen and colleagues might have underestimated the agreement between AU5800 and UN2000. Although the statistical approach adopted in Chen et al.'s research did not alter their findings, it is important to underscore the importance of researchers being discerning in their choice of statistical techniques to address their specific research inquiries.

Advancing Point-of-Care Diagnosis: Digitalizing Combinatorial Biomarker Signals for Lupus Nephritis.

To improve the efficiency and patient coverage of the current healthcare system, user-friendly novel homecare devices are urgently needed. In this work, we developed a smartphone-based analyzing and reporting system (SBARS) for biomarker detection in lupus nephritis (LN). This system offers a cost-effective alternative to traditional, expensive large equipment in signal detection and quantification. This innovative approach involves using a portable and affordable microscopic reader to capture biomarker signals. Through smartphone-based image processing techniques, the intensity of each biomarker signal is analyzed. This system exhibited comparable performance to a commercial Genepix scanner in the detection of two potential novel biomarkers of LN, VISG4 and TNFRSF1b. Importantly, this smartphone-based analyzing and reporting system allows for discriminating LN patients with active renal disease from healthy controls with the area-under-the-curve (AUC) value = 0.9 for TNFRSF1b and 1.0 for VSIG4, respectively, indicating high predictive accuracy.

Deep learning model to predict lupus nephritis renal flare based on dynamic multivariable time-series data.

OBJECTIVES: To develop an interpretable deep learning model of lupus nephritis (LN) relapse prediction based on dynamic multivariable time-series data. DESIGN: A single-centre, retrospective cohort study in China. SETTING: A Chinese central tertiary hospital. PARTICIPANTS: The cohort study consisted of 1694 LN patients who had been registered in the Nanjing Glomerulonephritis Registry at the National Clinical Research Center of Kidney Diseases, Jinling Hospital from January 1985 to December 2010. METHODS: We developed a deep learning algorithm to predict LN relapse that consists of 59 features, including demographic, clinical, immunological, pathological and therapeutic characteristics that were collected for baseline analysis. A total of 32 227 data points were collected by the sliding window method and randomly divided into training (80%), validation (10%) and testing sets (10%). We developed a deep learning algorithm-based interpretable multivariable long short-term memory model for LN relapse risk prediction considering censored time-series data based on a cohort of 1694 LN patients. A mixture attention mechanism was deployed to capture variable interactions at different time points for estimating the temporal importance of the variables. Model performance was assessed according to C-index (concordance index). RESULTS: The median follow-up time since remission was 4.1 (IQR, 1.7-6.7) years. The interpretable deep learning model based on dynamic multivariable time-series data achieved the best performance, with a C-index of 0.897, among models using only variables at the point of remission or time-variant variables. The importance of urinary protein, serum albumin and serum C3 showed time dependency in the model, that is, their contributions to the risk prediction increased over time. CONCLUSIONS: Deep learning algorithms can effectively learn through time-series data to develop a predictive model for LN relapse. The model provides accurate predictions of LN relapse for different renal disease stages, which could be used in clinical practice to guide physicians on the management of LN patients.

Natural language processing to identify lupus nephritis phenotype in electronic health records.

BACKGROUND: Systemic lupus erythematosus (SLE) is a rare autoimmune disorder characterized by an unpredictable course of flares and remission with diverse manifestations. Lupus nephritis, one of the major disease manifestations of SLE for organ damage and mortality, is a key component of lupus classification criteria. Accurately identifying lupus nephritis in electronic health records (EHRs) would therefore benefit large cohort observational studies and clinical trials where characterization of the patient population is critical for recruitment, study design, and analysis. Lupus nephritis can be recognized through procedure codes and structured data, such as laboratory tests. However, other critical information documenting lupus nephritis, such as histologic reports from kidney biopsies and prior medical history narratives, require sophisticated text processing to mine information from pathology reports and clinical notes. In this study, we developed algorithms to identify lupus nephritis with and without natural language processing (NLP) using EHR data from the Northwestern Medicine Enterprise Data Warehouse (NMEDW). METHODS: We developed five algorithms: a rule-based algorithm using only structured data (baseline algorithm) and four algorithms using different NLP models. The first NLP model applied simple regular expression for keywords search combined with structured data. The other three NLP models were based on regularized logistic regression and used different sets of features including positive mention of concept unique identifiers (CUIs), number of appearances of CUIs, and a mixture of three components (i.e. a curated list of CUIs, regular expression concepts, structured data) respectively. The baseline algorithm and the best performing NLP algorithm were externally validated on a dataset from Vanderbilt University Medical Center (VUMC). RESULTS: Our best performing NLP model incorporated features from both structured data, regular expression concepts, and mapped concept unique identifiers (CUIs) and showed improved F measure in both the NMEDW (0.41 vs 0.79) and VUMC (0.52 vs 0.93) datasets compared to the baseline lupus nephritis algorithm. CONCLUSION: Our NLP MetaMap mixed model improved the F-measure greatly compared to the structured data only algorithm in both internal and external validation datasets. The NLP algorithms can serve as powerful tools to accurately identify lupus nephritis phenotype in EHR for clinical research and better targeted therapies.

Clinical significance of miR-200a in systemic lupus erythematosus and renal damage in children.

The purpose was to analyze the clinical significance of miR-200a in children with initially diagnosed SLE and renal damage. Children with initially diagnosed SLE (n=100) and healthy children (n=50) undergoing physical examinations during the same period were recruited. Disease activity of SLE children was determined based on SLEDAI (systemic lupus erythematosus disease activity index), and they were divided to SLEDAI≤9 group and SLEDAI>9 group, respectively. Moreover, SLE children were divided to LN group and non-LN group based on the occurrence of lupus nephritis. Differential level of miR-200a between groups was detected by qRT-PCR. Spearman correlation test was conducted to analyze the influence of miR-200a on SLEDAI and other laboratory indexes of SLE children. Its diagnostic potential in SLE and LN was assessed through depicting ROC curves. MiR-200a level was remarkably lower in SLE children than that of healthy children. Lower level of miR-200a was detected in SLE children with high SLEDAI or accompanied LN. MiR-200a level was negatively correlated to SLEDAI (r=-0.425), ESR (r=-0.284), CRP (r=-0.338), BUN (r=-0.263) and Scr (r=-0.345), while it was positively correlated to C3 (r=0.631), C4 (r=0.524) and ALB (r=0.394) in SLE children. The AUC of miR-200a in diagnosing SLE was 0.8379 (cut-off value=2.225, sensitivity=70%, specificity=70%). Besides, the AUC of miR-200a in diagnosing LN was 0.7619 (cut-off value=2.005, sensitivity=80%, specificity=76%). MiR-200a level has a certain correlation to the disease activity of children with initially diagnosed SLE, which can be utilized as an adjuvant indicator in evaluating SLE severity. Meanwhile, miR-200a has predictive value for SLE-induced renal damage.

Population-wide long-term study of incidence, renal failure, and mortality rates for lupus nephritis.

OBJECTIVE: Given limited regional data, we investigate the state-wide epidemiology, renal and patient outcomes for lupus nephritis (LN) in Western Australia (WA). METHODS: Patients hospitalized with incident SLE (≥2 diagnostic codes in the state-wide WA Health Hospital Morbidity Data Collection) in the period 1985-2015 were included (n = 1480). LN was defined by the presence of glomerulonephritis and/or raised serum creatinine. Trends over three study decades for annual incidence rate (AIR)/100.000 population, mortality (MR), and end-stage renal disease (ESRD) rates/100 person years were analyzed by least square regression and compared with a matched control group (n = 12 840). RESULTS: Clinical evidence of LN developed in 366 SLE patients (25.9%) after a median disease duration of 10 months (IQR 0-101) with renal biopsy performed in 308 (84.2%). The AIR for LN (0.63/100.000) did not change significantly over time (R2 = .11, p = .85), while point prevalence reached 11.9/100.000 in 2015. ESRD developed in 14.1% (n = 54) of LN patients vs. 0.2% in non-LN SLE patients and 0.05% in controls (all p ≤ 0.01). ESRD rates increased over time in LN patients (0.4 to 0.7, R2 = .52, p = .26). The odds ratio for death was 8.81 (CI 3.78-22.9) for LN and 6.62 (CI 2.76-17.9) for non-LN SLE patients compared to controls and MR for LN patients increased over time (1.3 to 2.2, R2 = .84, p = .26). CONCLUSIONS: The incidence rate of LN in WA remained unchanged over 30 years. A lack of improvement in renal failure and mortality rates illustrates the pressing need for better long-term treatment options and/or strategies in LN.

Evaluation of Type 2 SLE symptoms in patients with a range of lupus nephritis activity.

BACKGROUND: Type 2 systemic lupus erythematosus (SLE) symptoms, including fatigue, fibromyalgia, and brain fog, contribute to poor health-related quality of life (HRQoL) in patients with lupus. To test the hypothesis that Type 1 (classical inflammatory lupus) activity is associated with Type 2 SLE activity, we characterized the features of Type 2 SLE in patients with a range of lupus nephritis (LN) activity. METHODS: This was a cross-sectional study of SLE patients [American College of Rheumatology (ACR) 1997 or Systemic Lupus International Collaborating Clinics (SLICC) 2012 classification criteria] from June 2018 to March 2020. Patients completed the Systemic Lupus Activity Questionnaire (SLAQ) and the Polysymptomatic Distress Scale. Patients were divided into groups based on their renal status. Active nephritis was defined using the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) lupus nephritis parameter. Differences across groups were analyzed by Fisher's exact test and ANOVA. RESULTS: In this cohort of 244 patients (93% female, mean age 43 years, 58% Black), 10% had active nephritis, 35% had historical nephritis, and 55% never had nephritis (non-nephritis). Active nephritis and non-nephritis patients had a similar burden of Type 2 SLE symptoms, despite a difference in Type 1 SLE activity. Patients with active nephritis had higher Type 2 PGA (Physician Global Assessment) scores and reported more Type 2 SLE symptoms than inactive nephritis patients. Patients with inactive nephritis had the lowest Type 2 SLE activity. CONCLUSIONS: While Type 2 SLE symptoms are common in SLE, our findings suggest that patients with active nephritis experience significant Type 2 SLE symptoms that may be ameliorated as nephritis improves. We also observed that non-nephritis patients had a similar burden of Type 2 SLE symptoms as patients with active nephritis, despite having on average lower Type 1 SLE activity. Therefore, the etiology of Type 2 SLE symptoms is likely multifactorial and may be driven by inflammatory and non-inflammatory biopsychosocial factors. Key Points • Patients with active nephritis experienced significant Type 2 symptoms that may be ameliorated as nephritis improves. • Non-nephritis patients had a similar burden of Type 2 SLE symptoms as patients with active nephritis, despite having on average lower Type 1 SLE activity. • Because etiology of Type 2 SLE symptoms is likely multifactorial and may be driven by inflammatory and non-inflammatory biopsychosocial factors.

Prediction of treatment response in lupus nephritis using density of tubulointerstitial macrophage infiltration.

Background: Lupus nephritis (LN) is a common disease with diverse clinical and pathological manifestations. A major challenge in the management of LN is the inability to predict its treatment response at an early stage. The objective of this study was to determine whether the density of tubulointerstitial macrophage infiltration can be used to predict treatment response in LN and whether its addition to clinicopathological data at the time of biopsy would improve risk prediction. Methods: In this retrospective cohort study, 430 patients with LN in our hospital from January 2010 to December 2017 were included. We used immunohistochemistry to show macrophage and lymphocyte infiltration in their biopsy specimens, followed by quantification of the infiltration density. The outcome was the treatment response, defined as complete or partial remission at 12 months of immunosuppression. Results: The infiltration of CD68+ macrophages in the interstitium increased in patients with LN. High levels of CD68+ macrophage infiltration in the interstitium were associated with a low probability of treatment response in the adjusted analysis, and verse vice. The density of CD68+ macrophage infiltration in the interstitium alone predicted the response to immunosuppression (area under the curve [AUC], 0.70; 95% CI, 0.63 to 0.76). The addition of CD68+cells/interstitial field to the pathological and clinical data at biopsy in the prediction model resulted in an increased AUC of 0.78 (95% CI, 0.73 to 0.84). Conclusion: The density of tubulointerstitial macrophage infiltration is an independent predictor for treatment response in LN. Adding tubulointerstitial macrophage infiltration density to clinicopathological data at the time of biopsy significantly improves risk prediction of treatment response in LN patients.

Expression profile of long-noncoding RNAs MIR31HG, NKILA, and PACER in systemic lupus erythematosus patients.

OBJECTIVES: Growing evidence suggests that systemic lupus erythematosus (SLE), an organ-damaging systemic autoimmune illness, may be influenced by long-noncoding RNAs (lncRNAs). This study aimed to assess the relative expression of lncRNAs (MIR31HG, NKILA, and PACER) in patients with SLE to evaluate their role in the disease. DESIGN AND METHODS: This study involved 70 patients with SLE and 70 apparently healthy control subjects. The expression levels of lnc-MIR31HG, NKILA, and PACER were quantified using real-time PCR. RESULTS: Lnc-MIR31HG, NKILA, and PACER were significantly upregulated in SLE cases compared to controls (P < 0.001). ROC curve analysis revealed a 91.43 % sensitivity of PACER for the diagnosis of SLE at a cutoff point of > 1.46, followed by NKILA with 90 % sensitivity at a cutoff point of > 1.16, and MIR31HG with 85.71 % sensitivity at a cutoff point of > 1.43. MIR31HG had the highest sensitivity for the diagnosis of lupus nephritis (86.67 %) at a cutoff point of > 7.19, then NKILA with 80 % sensitivity at a cutoff point of > 8.12, and finally PACER expression with 73.33 % sensitivity at a cutoff point of > 18.19. Moreover, MIR31HG and NKILA revealed a significant correlation with albumin/creatinine ratio, estimated glomerular filtration rate, and the SLEDAI score. Regression analysis revealed the potential roles of MIR31HG, NKILA, and PACER expression as predictors for SLE. CONCLUSION: An upregulated lncRNA panel (MIR31HG, NKILA, and PACER) could play a role in the pathogenesis and, hence, the predispositiontoSLE. MIR31HG and NKILA can serve as prognostic markers significantly linked with disease activity.

New guidelines and therapeutic updates for the management of lupus nephritis.

PURPOSE OF REVIEW: Systemic lupus erythematosus (SLE) can be a devastating condition, striking young patients often in their prime reproductive years. Lupus nephritis is a common and serious complication occurring in roughly 50% of SLE cases, indicating a high likelihood of disease progression, morbidity, and mortality. As the early trials of steroid therapy, and later cyclophosphamide (CYC), therapeutic changes had been stagnant. Then came the introduction of mycophenolate mofetil (MMF) in the 2000s. After the Aspreva Lupus Management Study, there had been a dearth of trials showing positive therapy results. Since 2020, new studies have emerged for lupus nephritis involving the use of anti-BLYS agents, novel calcineurin inhibitors, CD20 blockade, and antiinterferon agents. Nephrology and rheumatology society guidelines in the United States and across the world are still catching up. RECENT FINDINGS: Although therapeutic guidelines are being developed, updates that have come through have focused on improved diagnostic and monitoring guidelines. One theme is the recommendation of increasingly tight proteinuria control and firmer guidelines for the rapid induction of remission. The reality of multitarget therapy and the expectation of rapid induction for a more complete remission are being widely recognized. SUMMARY: The need for more complete and more rapid induction and control of lupus nephritis is undisputed according to the evidence and guidelines, and the medications to achieve this are growing at a rate not seen over the prior two decades. What remains is a stepwise approach to recognize how to best optimize therapy. Based on available evidence, an algorithm for induction and maintenance treatment of lupus nephritis used by the University of California Irvine Lupus Nephritis clinic, is recommended.

Potential involvement of circulating exosomal miRNA-146a in disease activity and TRAF6 gene expression in juvenile proliferative lupus nephritis.

BACKGROUND: Juvenile SLE (JSLE) is a complex autoimmune disorder that predominantly affects children and adolescents with several unique challenges, and microRNA-146a (miRNA-146a) might be an interesting anti-inflammatory molecule. Because exosomes in the blood might protect miRNAs, the association between circulating exosomal miRNA-146a and lupus proinflammatory genes, such as IRAK1 and TRAF6, was studied in peripheral blood mononuclear cells from people with JSLE. METHODS: Blood samples from 12 patients were collected every 3 months until 1 year with the recorded disease activity, and quantitative real-time PCR was used to determine the circulating exosomal miRNA-146a and the gene expression (IRAK1 and TRAF6). RESULTS: The mean age was 12.60±0.43 years at diagnosis and all patients had a complete response at 12 months. According to the nanoparticle tracking analysis, the abundance of exosomes was significantly lower at 3, 6 and 12 months compared with 0 months, while the level of circulating exosomal miRNA-146a was significantly higher at 12 months than at diagnosis (p<0.001). There was a negative correlation between the level of circulating exosomal miRNA-146a expression and the level of TRAF6 mRNA (r=-0.30, p=0.049). Moreover, there were correlations between circulating exosomal miRNA-146a and disease severity such as SLE Disease Activity Index 2000 score, anti-double-stranded DNA antibody and proteinuria (urine protein-creatinine ratio), respectively. Therefore, increasing the level of circulating exosomal miRNA-146a, which might control TRAF6 mRNA expression, could have an effect on the production of inflammatory cytokines. CONCLUSION: This suggests that miRNA-146a might serve as a non-invasive biomarker to evaluate the response to treatment in patients with juvenile lupus nephritis.

Tacrolimus-Associated Posterior Reversible Encephalopathy Syndrome in Renal Transplant Recipient in Early Posttransplant Period: Case Report.

Posterior reversible encephalopathy syndrome is an emergency medical condition with varied causes presenting as reversible subcortical vasogenic brain edema caused by endothelial injury, resulting from changes in blood pressure or direct effects of cytokines on endothelium. Posterior reversible encephalopathy syndrome is manifested by neurologic symptoms. Common causes include hypertensive emergency, renal disease, preeclampsia, eclampsia, and immunosuppressive drugs. In this case report, a 17-year-old female patient on hemodialysis as a result of lupus nephritis who had previously undergone deceased donor organ transplant and was on triple immunosuppression presented with neurological symptoms of posterior reversible encephalopathy syndrome in the early posttransplant period. She was normotensive, and tacrolimus level was in desired level. She improved after cessation of tacrolimus from immunosuppression with complete resolution of radiological lesions. Posterior reversible encephalopathy syndrome can occur in solid-organ transplant recipients who are on tacrolimus as a part of immunosuppression.

Proximity extension assay proteomics and renal single cell transcriptomics uncover novel urinary biomarkers for active lupus nephritis.

OBJECTIVE: To identify urinary biomarkers that can distinguish active renal involvement in Lupus Nephritis (LN), a severe manifestation of systemic lupus erythematosus (SLE). METHODS: Urine from 117 subjects, comprised of inactive SLE, active non-renal lupus, active LN, and healthy controls, were subjected to Proximity Extension Assay (PEA) based comprehensive proteomics followed by ELISA validation in an independent, ethnically diverse cohort. Proteomic data is also cross-referenced to renal transcriptomic data to elucidate cellular origins of biomarkers. RESULTS: Systems biology analyses revealed progressive activation of cytokine signaling, chemokine activity and coagulation pathways, with worsening renal disease. In addition to validating 30 previously reported biomarkers, this study uncovers several novel candidates. Following ELISA validation in an independent cohort of different ethnicity, the six most discriminatory biomarkers for active LN were urinary ICAM-2, FABP4, FASLG, IGFBP-2, SELE and TNFSF13B/BAFF, with ROC AUC ≥80%, with most correlating strongly with clinical disease activity. Transcriptomic analyses of LN kidneys mapped the likely origin of these proteins to intra-renal myeloid cells (CXCL16, IL-1RT2, TNFSF13B/BAFF), T/NK cells (FASLG), leukocytes (ICAM2) and endothelial cells (SELE). CONCLUSION: In addition to confirming the diagnostic potential of urine ALCAM, CD163, MCP1, SELL, ICAM1, VCAM1, NGAL and TWEAK for active LN, this study adds urine ICAM-2, FABP4, FASLG, IGFBP-2, SELE, and TNFSF13B/BAFF as additional markers that warrant systematic validation in larger cross-sectional and longitudinal cohorts.

Complement C4d as a biomarker for systemic lupus erythematosus and lupus nephritis.

Background: Increasing studies in the last decade have led to the widespread understanding that C4d, a split product of complement component 4 (C4), is a potential biomarker for systemic lupus erythematosus (SLE) and lupus nephritis (LN).Purpose: The aim of this review is to summarize the highlights of studies investigating the use of C4d as a biomarker for diagnosing and monitoring SLE and LN patients.Data collection: we searched PubMed/Medline and Wanfang databases using the terms "C4d and systemic lupus erythematosus", "C4d and lupus nephritis", and "Complement C4d".Results: The deposition of C4d on circulating blood cells has been shown in several clinical studies to be a potential diagnostic marker that can be used to monitor patients with SLE. In addition, C4d deposits on circulating blood cells may be a helpful diagnostic marker for LN, one of the most severe complications of SLE. Meanwhile, studies utilizing renal biopsy specimens have indicated that C4d deposition in the renal peritubular capillaries of LN patients may predict more severe LN or a worse patient prognosis. Generally, a high plasma C4d level and a high plasma C4d/C4 ratio may also be promising indicators that can be used to monitor patients with SLE and LN.Conclusions: C4d detection may be a novel strategy for further clinical prediction and therapy.

Rationale and design of the Japanese Biomarkers in Nephrotic Syndrome (J-MARINE) study.

INTRODUCTION: Disease subtyping and monitoring are essential for the management of nephrotic syndrome (NS). Although various biomarkers for NS have been reported, their clinical efficacy has not been comprehensively validated in adult Japanese patients. METHODS: The Japanese Biomarkers in Nephrotic Syndrome (J-MARINE) study is a nationwide, multicenter, and prospective cohort study in Japan, enrolling adult (≥18 years) patients with minimal change disease (MCD), focal segmental glomerulosclerosis (FSGS), membranous nephropathy (MN), membranoproliferative glomerulonephritis (MPGN), C3 glomerulopathy (C3G), and lupus nephritis (LN). Baseline clinical information and plasma and urine samples will be collected at the time of immunosuppressive therapy initiation or biopsy. Follow-up data and plasma and urine samples will be collected longitudinally based on the designated protocols. Candidate biomarkers will be measured: CD80, cytotoxic T-lymphocyte antigen 4, and soluble urokinase plasminogen activator receptor for MCD and FSGS; anti-phospholipase A2 receptor and thrombospondin type-1 domain-containing protein 7A antibodies for MN; fragment Ba, C3a, factor I, and properdin for MPGN/C3G; and CD11b, CD16b, and CD163 for LN. Outcomes include complete and partial remission, relapse of proteinuria, a 30% reduction in estimated glomerular filtration rate (eGFR), eGFR decline, and initiation of renal replacement therapy. The diagnostic accuracy and predictive ability for clinical outcomes will be assessed for each biomarker. RESULTS: From April 2019 to April 2023, 365 patients were enrolled: 145, 21, 138, 10, and 51 cases of MCD, FSGS, MN, MPGN/C3G, and LN, respectively. CONCLUSION: This study will provide valuable insights into biomarkers for NS and serve as a biorepository for future studies.