The utility of urinary biomarker panel in predicting renal pathology and treatment response in Chinese lupus nephritis patients

Investigating the value of urinary biomarkers in relation to lupus nephritis histopathology: present insights and future prospects

Lupus nephritis (LN), a leading cause of death in Systemic Lupus Erythematosus (SLE) patients, presents significant diagnostic and prognostic challenges. Although renal pathology offers critical insights regarding the diagnosis, classification, and therapy for LN, its clinical utility is constrained by the invasive nature and limited reproducibility of renal biopsies. Moreover, the continuous monitoring of renal pathological changes through repeated biopsies is impractical. Consequently, there is a growing interest in exploring urine as a non-invasive, easily accessible, and dynamic "liquid biopsy" alternative to guide clinical management. This paper examines novel urinary biomarkers from a renal pathology perspective, encompassing cellular components, cytokines, adhesion molecules, auto-antibodies, soluble leukocyte markers, light chain fragments, proteins, small-molecule peptides, metabolomics, urinary exosomes, and ribonucleic acids. We also discuss the application of combined models comprising multiple biomarkers in assessing lupus activity. These innovative biomarkers and models offer insights into LN disease activity, acute and chronic renal indices, fibrosis, thrombotic microangiopathy, podocyte injury, and other pathological changes, potentially improving the diagnosis, management, and prognosis of LN. These urinary biomarkers or combined models may serve as viable alternatives to traditional renal pathology, potentially revolutionizing the method for future LN diagnosis and observation.

Urinary biomarkers associated with podocyte injury in lupus nephritis

The most prevalent and devastating form of organ damage in systemic lupus erythematosus (SLE) is lupus nephritis (LN). LN is characterized by glomerular injury, inflammation, cell proliferation, and necrosis, leading to podocyte injury and tubular epithelial cell damage. Assays for urine biomarkers have demonstrated significant promise in the early detection of LN, evaluation of disease activity, and tracking of reaction to therapy. This is because they are non-invasive, allow for frequent monitoring and easy self-collection, transport and storage. Podocyte injury is believed to be a essential factor in LN. The extent and type of podocyte injury could be connected to the severity of proteinuria, making podocyte-derived cellular debris and injury-related urinary proteins potential markers for the diagnosis and monitoring of LN. This article focuses on studies examining urinary biomarkers associated with podocyte injury in LN, offering fresh perspectives on the application of biomarkers in the early detection and management of LN.

Development and application of an amplified luminescent proximity homogeneous assay-linked immunosorbent assay for the accurate quantification of kidney injury molecule-1

Background: Kidney injury molecule-1 (Kim-1), a specific marker of kidney injury, is usually not expressed in normal kidneys or at very low levels but is highly expressed in injured renal tubular epithelial cells until the damaged cells recover completely. Therefore, we aimed to develop an efficient and highly sensitive assay to accurately quantify Kim-1 levels in human serum and urine. Methods: In this study, a novel immunoassay was developed and named amplified luminescent proximity homogeneous assay-linked immunosorbent assay (AlphaLISA). Anti-Kim-1 antibodies can be directly coupled to carboxyl-modified donor and acceptor beads for the rapid detection of Kim-1 by double-antibody sandwich method. Serum and urine samples for Kim-1 measurements were obtained from 129 patients with nephropathy and 17 healthy individuals. Results: The linear range of Kim-1 detected by AlphaLISA was 3.83-5000 pg/mL, the coefficients of variation of intra-assay and inter-assay batches were 3.36%-4.71% and 5.61%-11.84%, respectively, and the recovery rate was 92.31%-99.58%. No cross reactions with neutrophil gelatinase-associated lipocalin, liver-type fatty acid binding protein, and matrix metalloproteinase-3 were observed. A good correlation (R 2 = 0.9086) was found between the findings of Kim-1-TRFIA and Kim-AlphaLISA for the same set of samples. In clinical trials, both serum and urine Kim-1 levels were significantly higher in patients with nephropathy than in healthy individuals, especially in patients with acute kidney injury. Furthermore, serum Kim-1 was superior to urinary Kim-1 in distinguishing between patients with nephropathy and healthy individuals. Conclusion: The developed Kim-1-AlphaLISA is highly efficient, precise, and sensitive, and it is suitable for the rapid detection of patients with acute kidney injury.

Lupus Nephritis Biomarkers: A Critical Review

Lupus nephritis (LN), a major complication in individuals diagnosed with systemic lupus erythematosus, substantially increases morbidity and mortality. Despite marked improvements in the survival of patients with severe LN over the past 50 years, complete clinical remission after immunosuppressive therapy is achieved in only half of the patients. Therefore, timely detection of LN is vital for initiating prompt therapeutic interventions and improving patient outcomes. Biomarkers have emerged as valuable tools for LN detection and monitoring; however, the complex role of these biomarkers in LN pathogenesis remains unclear. Renal biopsy remains the gold standard for the identification of the histological phenotypes of LN and guides disease management. However, the molecular pathophysiology of specific renal lesions remains poorly understood. In this review, we provide a critical, up-to-date overview of the latest developments in the field of LN biomarkers.

Urinary neutrophil gelatinase-associated lipocalin (uNGAL) and kidney injury molecule-1 (uKIM-1) as markers of active lupus nephritis

BACKGROUND AND OBJECTIVES

Despite much research about lupus nephritis, none of the urinary biomarkers has been proven to be truly reflecting lupus nephritis activity, response to treatment, or prognosis. We aimed to study urinary biomarkers in lupus nephritis and test their relation to kidney damage.

PATIENTS AND METHODS

Forty patients with systemic lupus erythematosus (SLE) were divided into two graoups: (1) lupus nephritis group with biopsy-proven proliferative lupus nephritis (classes III and IV) and who did not receive immunosuppressive drugs within the preceding 3 months except for glucocorticoids and (2) lupus non-nephritis group with SLE patients without any renal manifestation. We assessed disease activity by the SLE disease activity index. uNGAL, uKim-1, uNGAL to urinary creatinine excretion (mg/dl), and uKim-1 to urinary creatinine excretion were measured in random spot urine samples at the time of renal biopsy and 6 months after the induction therapy.

RESULTS

The LN group before treatment showed higher levels of uNGAL and uKIM-1 (P-value < 0.001). ROC analysis showed that uNGAL at level of > 59 has a 95 % sensitivity, a 100 % specificity, and an AUC = 0.996 in the ability to diagnose LN. While the uKIM-1 ROC showed that at level of > 1.6, it has an 85 % sensitivity, an 80 % specificity, and an AUC = 0.919. uNGAL and uKIM levels were significantly lower after treatment (P-value < 0.001). No significant correlations were found between urinary markers before and after treatment with other clinical, inflammatory, and serological markers of lupus nephritis.

CONCLUSION

uNGAL, uKIM, uNGAL/Creat ratio, and uKIM/Creat ratio can be used as a predictor and a marker of disease activity for lupus nephritis. Key Points • Renal biopsy is the current standard for diagnosis of lupus nephritis and none of the urinary biomarkers has been fully concluded to have a diagnostic power to reflect the activity or the response to treatment. • However, based on the finding of the current study, uNGAL, uKIM, uNGAL/Creat ratio, and uKIM/Creat ratio showed significant diagnostic performance and were powerful indices of renal involvement in systemic lupus patients and as markers of disease activity.

Biomarkers for systemic lupus erythematosus - a focus on organ damage

INTRODUCTION

Systemic lupus erythematosus (SLE) is complex autoimmune disease with heterogenous manifestations, unpredictable disease course and response to treatment. One of the critical needs in SLE management is the identification of reliable biomarkers that can aid in early diagnosis, accurate monitoring of disease activity, and assessment of treatment response.

AREAS COVERED

In the current review, we focus on the commonly affected organs (skin, kidney, and nervous system) in SLE to summarize the emerging biomarkers that show promise in disease diagnosis, monitoring and treatment response assessment. The subtitles within each organ domain were determined based on the most relevant and promising biomarkers for that specific organ damage.

EXPERT OPINION

Biomarkers have the potential to significantly benefit the management of SLE by aiding in diagnosis, disease activity monitoring, prognosis, and treatment response assessment. However, despite decades of research, none has been validated and implemented for routine clinical use. Novel biomarkers could lead to the development of precision medicine for SLE, guide personalized treatment, and improve patient outcomes. Challenges in biomarker research in SLE include defining clear and clinically relevant questions, accounting for the heterogeneity of SLE, and confirming initial findings in larger, multi-center, multi-ethnic, independent cohorts that reflect real-world clinical scenarios.

Measurement of Urinary Gc-Globulin by a Fluorescence ELISA Technique: Method Validation and Clinical Evaluation in Septic Patients-A Pilot Study

A major complication of sepsis is the development of acute kidney injury (AKI). In case of acute tubular damage, Gc-globulin, a known serum sepsis marker is increasingly filtrated into the urine therefore, urinary Gc-globulin (u-Gc) levels may predict septic AKI. We developed and validated a competitive fluorescence ELISA method for u-Gc measurement. Serum and urine samples from septic patients were collected in three consecutive days (T1, T2, T3) and data were compared to controls. Intra- and interassay imprecisions were CV < 14% and CV < 20%, respectively, with a recovery close to 100%. Controls and septic patients differed (p < 0.001) in their u-Gc/u-creatinine levels at admission (T1, median: 0.51 vs. 79.1 µg/mmol), T2 (median: 0.51 vs. 57.8 µg/mmol) and T3 (median: 0.51 vs. 55.6 µg/mmol). Septic patients with AKI expressed higher u-Gc/u-creatinine values than those without AKI at T1 (median: 23.6 vs. 136.5 µg/mmol, p < 0.01) and T3 (median: 34.4 vs. 75.8 µg/mmol, p < 0.05). AKI-2 stage patients exhibited more increased u-Gc/u-creatinine levels at T1 (median: 207.1 vs. 53.3 µg/mmol, p < 0.05) than AKI-1 stage individuals. Moderate correlations (p < 0.001) were observed between u-Gc/u-creatinine and se-urea, se-creatinine, se-hsCRP, WBC, u-total protein, u-albumin, u-orosomucoid/u-creatinine, and u-Cystatin C/u-creatinine levels. U-Gc testing may have a predictive value for AKI in septic patients.

Lupus Nephritis Risk Factors and Biomarkers: An Update

Lupus nephritis (LN) represents the most severe organ manifestation of systemic lupus erythematosus (SLE) in terms of morbidity and mortality. To reduce these risks, tremendous efforts have been made in the last decade to characterize the different steps of the disease and to develop biomarkers in order to better (i) unravel the pre-SLE stage (e.g., anti-nuclear antibodies and interferon signature); (ii) more timely initiation of therapy by improving early and accurate LN diagnosis (e.g., pathologic classification was revised); (iii) monitor disease activity and therapeutic response (e.g., recommendation to re-biopsy, new urinary biomarkers); (iv) prevent disease flares (e.g., serologic and urinary biomarkers); (v) mitigate the deterioration in the renal function; and (vi) reduce side effects with new therapeutic guidelines and novel therapies. However, progress is poor in terms of improvement with early death attributed to active SLE or infections, while later deaths are related to the chronicity of the disease and the use of toxic therapies. Consequently, an individualized treat-to-target strategy is mandatory, and for that, there is an unmet need to develop a set of accurate biomarkers to be used as the standard of care and adapted to each stage of the disease.

Incorporating knowledge of disease-defining hub genes and regulatory network into a machine learning-based model for predicting treatment response in lupus nephritis after the first renal flare

BACKGROUND

Identifying candidates responsive to treatment is important in lupus nephritis (LN) at the renal flare (RF) because an effective treatment can lower the risk of progression to end-stage kidney disease. However, machine learning (ML)-based models that address this issue are lacking.

METHODS

Transcriptomic profiles based on DNA microarray data were extracted from the GSE32591 and GSE112943 datasets. Comprehensive bioinformatics analyses were performed to identify disease-defining genes (DDGs). Peripheral blood samples (GSE81622, GSE99967, and GSE72326) were used to evaluate the effect of DDGs. Single-sample gene set enrichment analysis (ssGSEA) scores of the DDGs were calculated and correlated with specific immunology genes listed in the nCounter panel. GSE60681 and GSE69438 were used to examine the ability of the DDGs to discriminate LN from other renal diseases. K-means clustering was used to obtain the separate gene sets. The clustering results were extended to data derived using the nCounter technique. The least absolute shrinkage and selection operator (LASSO) algorithm was used to identify genes with high predictive value for treatment response after the first RF in each cluster. LASSO models with tenfold validation were built in GSE200306 and assessed by receiver operating characteristic (ROC) analysis with area under curve (AUC). The models were validated by using an independent dataset (GSE113342).

RESULTS

Forty-five hub genes specific to LN were identified. Eight optimal disease-defining clusters (DDCs) were identified in this study. Th1 and Th2 cell differentiation pathway was significantly enriched in DDC-6. LCK in DDC-6, whose expression positively correlated with various subsets of T cell infiltrations, was found to be differentially expressed between responders and non-responders and was ranked high in regulatory network analysis. Based on DDC-6, the prediction model had the best performance (AUC: 0.75; 95% confidence interval: 0.44-1 in the testing set) and high precision (0.83), recall (0.71), and F1 score (0.77) in the validation dataset.

CONCLUSIONS

Our study demonstrates that incorporating knowledge of biological phenotypes into the ML model is feasible for evaluating treatment response after the first RF in LN. This knowledge-based incorporation improves the model's transparency and performance. In addition, LCK may serve as a biomarker for T-cell infiltration and a therapeutic target in LN.

Clinical study on the use of advanced magnetic resonance imaging in lupus nephritis

OBJECTIVES

To investigate the correlation between the histopathology of the kidney and clinical indicators in patients with lupus nephritis (LN) using magnetic resonance imaging (MRI).

METHODS

A total 50 female participants were enrolled in the study. Thirty patients with LN were divided into types 2, 3, 4, and 5, according to their pathological features. The control group consisted of 20 healthy female volunteers. Serum creatinine, C3, C1q, and anti-ds-DNA were measured. Conventional MRI, DTI, DWI, and BOLD scanning was performed to obtain the FA, ADC, and R2* values for the kidney.

RESULTS

Compared with the control group, FA and the ADC were decreased in patients with LN, while the R2* value was increased (P < 0.05). The overall comparison of the SLEDAI (Activity index of systemic lupus erythematosus) score, total pathological score, AI, and serum creatinine C3 showed that these were significantly different between the two groups (P < 0.05). FA and the ADC were negatively correlated with urinary, blood ds-DNA, and serum creatinine and positively correlated with C1q (P < 0.05). The R2* value was positively correlated with urinary NGAL, blood ds-DNA, and serum creatinine (P < 0.05). FA and the ADC were negatively correlated with the SLEDAI score, total pathological score, AI, CI, nephridial tissue C3, and C1q. The R2* value was positively correlated with the SLEDAI score, total pathological score, AI, CI, nephridial tissue C3, and C1q (P < 0.05).

CONCLUSIONS

MRI examination in female patients with LN was correlated with pathologic test results, which may have clinical significance in determining the disease's severity, treatment, and outcome.

Research progress of risk factors and early diagnostic biomarkers of gout-induced renal injury

Gout renal injury has an insidious onset, no obvious symptoms, and laboratory abnormalities in the early stages of the disease. The injury is not easily detected, and in many cases, the patients have entered the renal failure stage at the time of diagnosis. Therefore, the detection of gout renal injury–related risk factors and early diagnostic biomarkers of gout renal injury is essential for the prevention and early diagnosis of the disease. This article reviews the research progress in risk factors and early diagnostic biomarkers of gout renal injury.

Identification and Validation of a Urinary Biomarker Panel to Accurately Diagnose and Predict Response to Therapy in Lupus Nephritis

Background

We have previously shown that 15 urinary biomarkers (of 129 tested by Luminex), discriminate between active Lupus Nephritis (ALN) and non-LN patients. The aim of this study was to evaluate the ability of these 15 previously-identified urinary biomarkers to predict treatment responses to conventional therapy, and for the most predictive of these biomarkers to validate their utility to identify ALN patients in an independent prospectively-acquired lupus cohort.

Methods

Our study had a 3-stage approach. In stage 1, we used Luminex to examine whether our previously identified urinary biomarkers at the time of the renal flare ( ± 3 months) or 12 ± 3 months after treatment of biopsy-proven ALN could predict treatment responses. In stage 2, a larger prospectively-acquired cross-sectional cohort was used to further validate the utility of the most predictive urinary biomarkers (identified in stage 1) to detect ALN patients. In this 2^nd stage, cut-offs with the best operating characteristics to detect ALN patients were produced for each biomarker and different combinations and/or numbers of elevated biomarkers needed to accurately identify ALN patients were analyzed. In stage 3, we aimed to further corroborate the sensitivity of the cut-offs created in stage 2 to detect ALN patients in a biopsy-proven ALN cohort who had a urine sample collection within 3 months of their biopsy.

Results

Twenty-one patients were included in stage 1. Twelve (57.1%), 4 (19.1%), and 5 (23.8%) patients had a complete (CR), partial (PR) and no (NR) remission at 24 ± 3 months, respectively. The percentage decrease following 12 ± 3 months of treatment for Adiponectin, MCP-1, sVCAM-1, PF4, IL-15 and vWF was significantly higher in patients with CR in comparison to those with PR/NR. In stage 2, a total of 247 SLE patients were included, of which 24 (9.7%) had ALN, 79 (31.9%) had LN in remission (RLN) and 144 (58.3%) were non-LN (NLN) patients. Based on the combinations of biomarkers with the best operating characteristics we propose “rule out” and “rule in” ALN criteria. In stage 3, 53 biopsy-proven ALN patients were included, 35 with proliferative LN and 18 with non-proliferative ALN, demonstrating that our “rule in ALN” criteria operate better in detecting active proliferative than non-proliferative classes.

Conclusions

Our results provide further evidence to support the role of Adiponectin, MCP-1, sVCAM-1 and PF4 in the detection of proliferative ALN cases. We further show the clinical utility of measuring multiple rather than a single biomarker and we propose novel “rule in” and “rule out” criteria for the detection of proliferative ALN with excellent operating characteristics.

Diagnostic, predictive and prognostic biomarkers in systemic lupus erythematosus: current insights

PURPOSE OF REVIEW

Biomarkers for diagnosis, monitoring and prognosis still constitute an unmet need for systemic lupus erythematosus (SLE). Focusing on recent findings, this review summarises the current landscape of biomarkers in lupus.

RECENT FINDINGS

Urine activated leukocyte cell adhesion molecule (ALCAM) exhibited good diagnostic ability in SLE and lupus nephritis (LN) whereas cerebrospinal fluid neutrophil gelatinase-associated lipocalin (NGAL) showed promise in neuropsychiatric SLE. Urine ALCAM, CD163 and vascular cell adhesion molecule 1 (VCAM-1) may be useful in surveillance of LN. Urine monocyte chemoattractant protein 1 was found to predict treatment response in SLE, and urine CD163 and NGAL treatment response in LN. Serum complement component 3 (C3) and urinary VCAM-1 have been reported to portend long-term renal prognosis in LN.

SUMMARY

NGAL holds promise as a versatile biomarker in SLE whereas urine ALCAM, CD163 and VCAM-1 displayed good performance as biomarkers in LN. The overall lack of concerted corroboration of leading candidates across multiple cohorts and diverse populations leaves the current biomarker landscape in SLE in an urgent need for further survey and systematic validation.

Emerging Molecular Markers Towards Potential Diagnostic Panels for Lupus

Systemic lupus erythematosus (SLE) is a multifactorial autoimmune disease which can affect various tissues and organs, posing significant challenges for clinical diagnosis and treatment. The etiology of SLE is highly complex with contributions from environmental factors, stochastic factors as well as genetic susceptibility. The current criteria for diagnosing SLE is based primarily on a combination of clinical presentations and traditional lab testing. However, these tests have suboptimal sensitivity and specificity. They are unable to indicate disease cause or guide physicians in decision-making for treatment. Therefore, there is an urgent need to develop a more accurate and robust tool for effective clinical management and drug development in lupus patients. It is fortunate that the emerging Omics have empowered scientists in the discovery and identification of potential novel biomarkers of SLE, especially the markers from blood, urine, cerebrospinal fluids (CSF), and other bodily fluids. However, many of these markers have not been carefully validated for clinical use. In addition, it is apparent that individual biomarkers lack sensitivity or specificity. This review summarizes the sensitivity, specificity and diagnostic value of emerging biomarkers from recent studies, and discusses the potential of these markers in the development of biomarker panel based diagnostics or disease monitoring system in SLE.

A review on the role of chemokines in the pathogenesis of systemic lupus erythematosus

Chemokines are a group of cytokines with low molecular weight that principally direct chemotaxis of target cells. They have prominent roles in the pathogenesis systemic lupus erythematosus (SLE) and related complications particularly lupus nephritis. These molecules not only induce autoimmune responses in the organs of patients, but also can amplify the induced inflammatory responses. Although chemokine family has at least 46 identified members, the role of a number of these molecules have been more clarified in SLE patients or animal models of this disorder. In the current paper, we review the role of CCL2, CCL3, CCL4, CCL11, CCL20, CXCL1, CXCL2, CXCL8, CXCL10, CXCL12 and CXCL13 in the pathogenesis of SLE.

Immune-Related Urine Biomarkers for the Diagnosis of Lupus Nephritis

The kidney is one of the main organs affected by the autoimmune disease systemic lupus erythematosus. Lupus nephritis (LN) concerns 30-60% of adult SLE patients and it is significantly associated with an increase in the morbidity and mortality. The definitive diagnosis of LN can only be achieved by histological analysis of renal biopsies, but the invasiveness of this technique is an obstacle for early diagnosis of renal involvement and a proper follow-up of LN patients under treatment. The use of urine for the discovery of non-invasive biomarkers for renal disease in SLE patients is an attractive alternative to repeated renal biopsies, as several studies have described surrogate urinary cells or analytes reflecting the inflammatory state of the kidney, and/or the severity of the disease. Herein, we review the main findings in the field of urine immune-related biomarkers for LN patients, and discuss their prognostic and diagnostic value. This manuscript is focused on the complement system, antibodies and autoantibodies, chemokines, cytokines, and leukocytes, as they are the main effectors of LN pathogenesis.