Serum and Urinary Galectin-3 as a Non-Invasive Marker of Renal Fibrosis in Patients with Lupus Nephritis: A Cross-Sectional Controlled Study

Serum and Urinary Galectin-3 as a Non-Invasive Marker of Renal Fibrosis in Patients with Lupus Nephritis: A Cross-Sectional Controlled Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Serum and Urinary Galectin-3 as a Non-Invasive Marker of Renal Fibrosis in Patients with Lupus Nephritis: A Cross-Sectional Controlled Study Ahmed Mohamed Fahmy, rasha youssef hagag, Amira Mahmoud Radwan, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8444239/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Kidney fibrosis (KF) is a key determinant of adverse outcomes in lupus nephritis (LN). Although kidney biopsy remains the diagnostic gold standard, its invasiveness limits its routine use, necessitating the development of reliable non-invasive biomarkers. Galectin-3 (Gal-3), a β-galactoside-binding lectin involved in fibrogenesis, has been proposed as a candidate marker; however, its clinical value in LN remains uncertain. Objectives Our aim was to evaluate serum/urinary Gal-3 as non-invasive biomarkers of kidney fibrosis in LN and compare their diagnostic performance with non-nephritic systemic lupus erythematosus (SLE) and healthy controls. Methods This cross-sectional case-control study enrolled 150 participants (50 LN, 50 non-LN SLE, 50 controls). LN patients were stratified by interstitial fibrosis and tubular atrophy (IFTA) score. Subsequently, we measured serum/urinary Gal-3, renal function indices, C3, C4, anti-dsDNA, BMI, and urinary protein-to-creatinine ratio (UPCR). Disease activity was assessed using the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI). Results Unlike the other groups, serum/urinary Gal-3 levels were significantly higher in the LN group (p < 0.001). Both correlated strongly with IFTA score (ρ = 0.76–0.81, p < 0.001) and moderately with SLEDAI. Urinary Gal-3 showed superior diagnostic accuracy for moderate–severe fibrosis (AUC = 0.87, 95% CI 0.77–0.98) than serum (AUC = 0.74). Both remained independent predictors of fibrosis severity after adjustment. Conclusions Serum/urinary Gal-3 are reliable, non-invasive biomarkers of kidney fibrosis in LN, with urinary Gal-3 demonstrating the highest diagnostic performance. Galectin-3 lupus nephritis renal fibrosis biomarker non-invasive IFTA Figures Figure 1 Figure 2 Introduction Chronic kidney injury and progressive fibrosis are central pathological processes driving the decline in renal function across numerous glomerular diseases, including lupus nephritis (LN), a leading complication of systemic lupus erythematosus (SLE) that is substantially implicated in long-term morbidity and mortality. Despite advances in immunosuppressive therapy, LN is still a leading driver of end-stage renal disease (ESRD). The severity of interstitial fibrosis and tubular atrophy (IFTA), together with glomerular and vascular lesions, serves as a key histologic predictor of prognosis and renal survival in patients with LN. Currently, renal biopsy represents the gold standard for assessing these parameters, including chronicity indices and structural damage. However, biopsy is invasive, carries procedural risks, and cannot be performed repeatedly, limiting its utility for disease monitoring and longitudinal assessment ( 1 ). This limitation highlights the urgent need for non-invasive biomarkers that can accurately reflect ongoing renal structural deterioration, particularly fibrosis, to facilitate early detection, risk stratification, and enhanced management of LN. Galectin-3 (Gal-3), a β-galactoside-binding lectin, has become a promising candidate biomarker. It plays multifaceted roles in cell proliferation, differentiation, immune activation, and extracellular matrix remodeling, and contributes to the fibrogenic cascade within renal tissue ( 2 – 3 ). Experimental and clinical data suggest that elevated Gal-3 expression contributes to fibroblast activation, inflammation, and tissue remodeling, ultimately leading to renal scarring and functional decline. A biopsy-based human study demonstrated that chronic kidney disease (CKD) patients exhibited significantly higher plasma Gal-3 levels than non-CKD controls, which displays an inverse correlation with eGFR and positive correlation with histologic fibrosis indices: Interstitial fibrosis, tubular atrophy, and vascular intimal fibrosis ( 3 ). Moreover, individuals in the highest urinary Gal-3 tertile exhibited the most pronounced renal impairment, greatest proteinuria, and highest risk of progression or ESRD, supporting the concept that urinary Gal-3 may be a robust non-invasive marker of renal damage ( 4 ). Because fibrosis and tubular atrophy are irreversible features strongly linked to poor long-term outcomes, early detection of fibrotic remodeling is clinically critical in LN ( 5 ). Serum Gal-3 levels have been found to be significantly elevated in LN in contrast to both healthy controls and SLE patients without nephritis, correlating with renal dysfunction and histologic indices of chronic damage such as IFTA ( 4 ). Immunohistochemical studies further revealed that renal tissues from LN patients display increased glomerular and tubular Gal-3 expression, correlating positively with disease activity and chronicity ( 6 ). Collectively, Gal-3 may be a mechanistic link between autoimmune-mediated injury and fibrotic transformation in LN. Despite encouraging evidence, critical knowledge gaps remain. Few studies have simultaneously assessed both serum/urinary Gal-3 levels in LN, and no standardized threshold values currently exist to quantify fibrosis severity in this population. Moreover, earlier investigations in broader CKD cohorts (not specific to LN) have yielded inconsistent results regarding Gal-3's predictive capacity for renal and cardiovascular outcomes. Given the unique immunopathology of LN, characterized by immune complex deposition and concurrent glomerular and tubulointerstitial injury, it is essential to validate Gal-3 as a disease-specific, non-invasive biomarker within biopsy-proven LN populations ( 7 ). Therefore, the present cross-sectional controlled study aims to determine whether patients with biopsy-confirmed LN exhibit significantly higher serum/urinary Gal-3 levels than matched controls (healthy individuals and SLE without nephritis) and to evaluate their correlations with key clinical indicators of renal dysfunction (eGFR, proteinuria) and histologic measures of fibrosis (IFTA, chronicity index). Our central hypothesis is that elevated serum and/or urinary Gal-3 reflects renal fibrotic burden in LN and may represent a non-invasive surrogate marker for chronic histologic injury, thereby reducing dependence on repeat biopsies and enhancing risk stratification and long-term monitoring of LN patients. Patients and Methods Study Design and Participants This cross-sectional observational study was conducted between July 2025 and November 2025 and included 150 participants, recruited from the Rheumatology and Nephrology Outpatient Clinics and Inpatient Departments, and were divided equally (n = 50/group) into three age- and sex-matched groups. Group 1 included patients with biopsy-indicated LN, Group 2 included patients with SLE without nephritis, and Group 3 comprised healthy control individuals. Inclusion criteria comprised participants aged 18 years or older who met the SLE classification criteria established by the European League Against Rheumatism/American College of Rheumatology ( 9 ). Among these, patients with nephritis underwent kidney biopsy following the KDIGO guidelines, which recommend biopsy in the presence of albuminuria and/or reduced eGFR ( 10 ). Exclusion criteria included a history of sepsis, active cancer, diabetes, uncontrolled hypertension, chronic liver disease, known cardiovascular disease, or other autoimmune conditions. The study was authorized by the Research Ethics Committee of the Faculty of Medicine, Tanta University, Egypt (36264PR1300/7/25) and followed the Declaration of Helsinki, with all participants signing informed consent. Clinical Assessment All participants underwent a thorough clinical evaluation, including disease duration, presenting manifestations, treatment history, and prior renal biopsy findings, when available. Disease activity was evaluated using the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) and categorized as follows: no activity (SLEDAI = 0), mild ( 1 – 5 ), moderate ( 6 – 10 ), high ( 11 – 19 ), or very high (≥ 20) ( 8 ). Demographic and clinical data were also recorded. Laboratory Investigations Venous blood and midstream urine samples were collected from all participants under sterile conditions. Laboratory investigations included complete blood count (CBC), blood urea, serum creatinine, serum albumin, antinuclear antibodies (ANA), anti-dsDNA, complement components (C3 and C4), urinary protein-to-creatinine ratio (UPCR), and serum/urinary Gal-3 levels. CBC was performed using EDTA anticoagulated samples analyzed with an ERMA automated cell counter (Japan). Serum urea, creatinine, and albumin were measured using the INDIKO Plus automated chemistry analyzer (Finland). Complement C3, C4, and urinary protein concentrations were determined using a Cobas c311 automated analyzer (HITACHI, Germany). ANA and anti-dsDNA antibodies were quantified by ELISA using ORGENTEC Diagnostika kits (catalog numbers ORG600 and ORG604, Germany). Serum/urinary Gal-3 concentrations were measured using the AssayMax Human Gal-3 ELISA Kit (Cat. No. EG3311-1; AssayMax, USA). All ELISA assays were performed in duplicate per the protocols, and optical density was measured at 450 nm using a calibrated microplate reader. Histopathological Evaluation The histological categorization of renal biopsy data has been verified against the International Society of Nephrology/Renal Pathology Society (ISN/RPS) standard for individuals diagnosed with LN. To measure renal fibrosis (RF) extent, the IFTA score and chronicity index were documented. These measures were used as benchmarks for establishing a correlation between the severity of histology and the levels of Gal-3 in blood and urine. Results Baseline Characteristics The LN group had significantly higher urea, creatinine, and UPCR, and lower eGFR than non-LN SLE and controls ( p < 0.001). Serum/urinary Gal-3 were markedly increased in LN (31.93 ± 12.22 and 19.55 ± 7.89 ng/mL) relative to non-LN SLE (15.78 ± 2.46 and 7.42 ± 1.96 ng/mL) and controls (9.86 ± 2.15 and 5.22 ± 1.65 ng/mL, Table 1 ). Table 1 Baseline Characteristics of the Participants Variable LN Non-LN SLE Healthy Control Age (years) 32.94 ± 8.00 32.88 ± 7.52 32.14 ± 7.99 BMI (kg/m²) 25.27 ± 2.79 24.27 ± 3.22 22.86 ± 2.77 Serum Creatinine (mg/dL) 1.85 ± 0.62 0.91 ± 0.18 0.81 ± 0.11 eGFR (mL/min) 48.06 ± 18.46 94.80 ± 20.02 107.00 ± 16.46 Serum Gal-3 (ng/ml) 31.93 ± 12.22 15.78 ± 2.46 9.86 ± 2.15 Urinary Gal-3 (ng/ml) 19.55 ± 7.89 7.42 ± 1.96 5.22 ± 1.65 C3 (mg/dL) 63.87 ± 14.11 80.51 ± 9.58 93.04 ± 10.11 C4 (mg/dL) 9.73 ± 3.55 18.59 ± 3.97 24.60 ± 5.23 Anti-dsDNA (IU/ml) 101.75 ± 29.47 50.04 ± 29.53 SLEDAI Score 12.70 ± 3.89 4.06 ± 1.93 Association of Gal-3 with Fibrosis Severity Patients with moderate-to-severe fibrosis (IFTA ≥ 10%) exhibited significantly higher serum/urinary Gal-3 levels compared to those with mild fibrosis (p = 0.025 and p < 0.001, respectively, Table 2 ). Table 2 Comparison of Serum/urinary Gal-3 Levels According to Fibrosis Severity Biomarker Mild Fibrosis (IFTA < 10%) Mod-Severe Fibrosis (IFTA ≥ 10%) U-Statistic P-value Serum Gal-3 (ng/ml) 21.98 ± 3.14 34.17 ± 12.41 92.5 0.025* Urinary Gal-3 (ng/ml) 11.67 ± 2.36 21.28 ± 7.62 46.0 < 0.001*** Correlation with Renal Function and Disease Activity Spearman's correlation analysis showcased strong positive correlations between serum/urinary Gal-3 and IFTA scores, and moderate-to-strong correlations with serum creatinine and eGFR (p < 0.001 for all, Table 3 ). There was a moderate positive correlation between serum/urinary Gal-3 and SLEDAI scores (Table 4 ). Table 3 Correlation Between Serum/urinary Gal-3 and Clinical-Histopathological Parameters in LN patients (N = 49) Serum Gal-3 Urinary Gal-3 IFTA Score Spearman rho 0.7635 P < 0.001*** Spearman rho 0.8074 P < 0.001*** eGFR (ml/min) Spearman rho − 0.6013 P < 0.001*** Spearman rho − 0.6459 P < 0.001*** Creatinine (mg/dl) Spearman rho 0.6570 P < 0.001*** Spearman rho 0.7651 P < 0.001*** UPCR (mg/g) Spearman rho − 0.0454 P = 0.757 Spearman rho − 0.0009 P = 0.995 Table 4 Correlation Between Gal-3 (Serum & Urine) and SLEDAI Score, N = 99) Variable Spearman rho P-value Correlation Type Serum Gal-3 vs SLEDAI 0.6775 < 0.001*** Moderate Positive Urinary Gal-3 vs SLEDAI 0.6697 < 0.001*** Moderate Positive Variation of Gal-3 Across LN Classes Serum/urinary Gal-3 levels increased progressively across histopathological LN classes (p < 0.05). Class III (focal proliferative, 5–10% involvement; n = 9) exhibited the lowest concentrations (serum: 21.98 ± 3.14 ng/mL; urine: 11.67 ± 2.36 ng/mL). Higher levels were observed in Class IV (diffuse proliferative, 10–30%; n = 29) (serum: 29.62 ± 12.07 ng/mL; urine: 18.66 ± 7.40 ng/mL), peaking in Class IV + V (mixed proliferative/membranous, 30–40%; n = 9) (serum: 44.65 ± 3.72 ng/mL; urine: 27.89 ± 3.47 ng/mL) and Class VI (sclerosing, > 40%; n = 3) (serum: 45.20 ± 3.44 ng/mL; urine: 26.87 ± 2.10 ng/mL). This progressive elevation correlated significantly with histopathological severity (Table 5 ). Table 5 Serum/urinary Gal-3 Levels by LN Class (ISN/RPS) LN Class ISN/RPS Category Num Serum Gal- 3 Urinary Gal-3 Class III Focal proliferative (5–10%) 9 21.98 ± 3.14 11.67 ± 2.36 Class IV Diffuse proliferative (10–30%) 29 29.62 ± 12.07 18.66 ± 7.40 Class IV + V Mixed proliferative + membranous (30–40%) 9 44.65 ± 3.72 27.89 ± 3.47 Class VI Sclerosing (> 40%) 3 45.20 ± 3.44 26.87 ± 2.10 Spearman's correlation confirmed a strong positive association between urinary Gal-3 levels and LN class (ρ = 0.647, p < 0.00001). Serum Gal-3 levels differed significantly across LN classes by the Kruskal-Wallis test (p = 0.0007), consistent with the stepwise increase in severity. There was a strong correlation between serum/urinary Gal-3 (p < 0.001, Table 6 ). Table 6 Correlation Analysis of Galectin-3 Levels with Lupus Nephritis Class and Between Compartments Correlation Pair Spearman ρ p-value Interpretation Urinary Gal-3 vs LN Class 0.6470 < 0.00001 Strong positive correlation with disease severity Serum Gal-3 vs LN Class - 0.0007 Significant difference across classes (Kruskal-Wallis) Serum vs Urinary Gal-3 - < 0.001 Strong intercorrelation validates both biomarkers Diagnostic Performance of Gal-3 The ROC curve analysis demonstrated superior diagnostic performance of urinary Gal-3 compared with serum Gal-3 in detecting RF. Urinary Gal-3 achieved an AUC value of 0.872, with specificity of 88.9% and a Youden Index of 0.589 at an optimal cutoff value of 14.81 ng/mL. In contrast, serum Gal-3 showed a moderate diagnostic ability with an AUC of 0.743, specificity of 66.7%, and a Youden Index of 0.367 at an optimal cutoff of 22.5 ng/mL (Table 7 , Fig. 1 – 2 ). Table 7 ROC Analysis of Serum/urinary Gal-3 for RF Biomarker AUC 95% CI Optimal Cutoff Sensitivity Specificity Youden Index Serum Gal-3 (ng/ml) 0.7431 0.584–0.902 22.5 0.700 0.667 0.367 Urinary Gal-3 (ng/ml) 0.8722 0.768–0.977 14.81 0.700 0.889 0.589 Interpretation: AUC 0.8722 = GOOD discriminatory ability (0.8–0.9 range); AUC 0.7431 = FAIR discriminatory ability (0.7–0.8 range) Regression Analysis Multivariable regression analyses demonstrated that both serum/urinary Gal-3 were significant and independent fibrosis severity predictors in LN. Urinary Gal-3 exhibited a stronger association (β = 0.817, p < 0.001) compared with serum (β = 0.549, p < 0.001). eGFR was the only other significant independent variable, showing a negative association with fibrosis severity, consistent with the decline in renal function accompanying disease progression. Other clinical parameters, including SLEDAI, UPCR, and age, did not reach significance in either model (Tables 8 – 9 ) . Table 8 Multivariable Regression Analysis of Serum Gal-3 as a Predictor of Fibrosis Severity in LN Variable Coefficient (β) 95% CI t-statistic P-value Intercept 10.04 -7.36 to 27.44 1.13 0.264 Serum Gal-3 (ng/ml) 0.549 0.33 to 0.77 4.96 < 0.001*** SLEDAI 0.127 -0.41 to 0.66 0.47 0.644 UPCR (mg/g) 0.0003 -0.002 to 0.002 0.25 0.801 Age (years) -0.041 -0.30 to 0.21 -0.32 0.753 eGFR (ml/min) -0.226 -0.37 to -0.08 -3.09 0.004*** Table 9 Multivariable Regression Analysis of urinary Gal-3 as a Predictor of Fibrosis Severity in LN Variable Coefficient (β) 95% CI t-statistic P-value Intercept 9.06 -9.81 to 27.92 0.94 0.352 Urinary Gal-3 (ng/ml) 0.817 0.45 to 1.18 4.40 < 0.001*** SLEDAI 0.119 -0.44 to 0.68 0.42 0.677 UPCR (mg/g) 0.0004 -0.002 to 0.002 0.32 0.749 Age (years) 0.031 -0.24 to 0.30 0.23 0.820 eGFR (ml/min) -0.223 -0.38 to -0.07 -2.81 0.007*** Discussion The last common pathway of CKD progression across etiologies, including LN, is kidney fibrosis, characterized by IFTA. Although invasive kidney biopsy is still the gold standard for fibrosis evaluation, its inherent risks and limited reproducibility necessitate the development of reliable non-invasive biomarkers. Among these, Gal-3 has recently gained attention for its role in tissue fibrosis and inflammation, suggesting its potential as a non-invasive indicator of LN activity and chronicity. Our study's renal profile revealed that LN patients displayed significantly higher blood urea, UPCR, and serum creatinine levels than lupus patients without nephritis, with a corresponding reduction in eGFR. These findings align with El-Shehaby et al. ( 11 ), who also observed significant differences in these renal indices between LN and non-LN SLE patients. Similarly, Ding et al. ( 12 ) reported significantly lower eGFR in active LN, unlike inactive LN, in agreement with our data. Compared to controls, SLE groups exhibited significantly reduced levels of complement components C3 and C4, with more pronounced reductions among LN patients. This pattern reflects complement consumption due to immune complex deposition and renal inflammation. Sharifipour et al. ( 13 ) reported similar findings, while Farid et al. ( 14 ) and Rubinstein et al. ( 15 ) found no significant variation in C3 levels between LN and non-LN SLE, possibly reflecting differences in disease stage or patient demographics. Herein, serum/urinary Gal-3 levels were significantly higher in LN patients than in non-LN SLE and controls. eGFR was notably lower in the LN group, aligning with Faustini et al. ( 16 ), who demonstrated that urinary Gal-3 was higher in LN, distinguishing LN from active SLE without nephritis. Levels decreased after treatment, related to the activity index, and were independent of proteinuria. Similarly, serum Gal-3 was higher in LN than in non-renal SLE, correlated with renal biopsy activity and chronicity indices, and helped confirm LN presence ( 17 ). Furthermore, urinary Gal-3 was significantly higher in active LN, unlike inactive LN, with ROC curve analysis showing good discriminatory ability for differentiating active LN from inactive LN and healthy controls, and was positively correlated with SLEDAI ( 12 ). Skoot et al. ( 18 ) similarly observed that serum Gal-3 levels were considerably higher in LN patients than in SLE without LN and controls. Urinary Gal-3 was likewise elevated in LN, unlike non-LN SLE and controls. Collectively, serum/urinary Gal-3 reliably reflects renal involvement and fibrotic burden in LN. Gal-3 proved to be a dependable quantitative biomarker of both pathological fibrosis and deteriorating kidney function, showing moderate-to-strong correlations with serum creatinine and eGFR, as well as significant positive correlations with histologic fibrosis (IFTA scores). This is consistent with Ou et al. ( 4 ), who found a negative correlation between urinary Gal-3 and eGFR and positive correlations with plasma Gal-3, serum creatinine, and UPCR. Urinary Gal-3 levels also increased progressively with CKD stage, with marked elevations in stage 5 disease, and were associated with interstitial fibrosis, tubular atrophy, and interstitial inflammation. Chen et al. ( 20 ) reported similar associations in diabetic kidney disease, showing that macrophage-derived Gal-3 promotes renal damage via TGFβ1 signaling. Further, Ou et al. ( 3 ) demonstrated that plasma Gal-3 was higher in CKD compared to non-CKD, inversely correlated with eGFR, and was significantly related to tubular atrophy, interstitial fibrosis, and vascular intimal fibrosis. Similarly, Rao et al. ( 21 ) linked urinary Gal-3 with RF in heart failure patients, and Drechsler et al. ( 22 ) found that elevated Gal-3 in the blood correlated with adverse renal outcomes and fibrosis progression. Interstitial fibrosis and irreversible kidney injury in LN arise from fibroblast activation, epithelial–mesenchymal transition, and extracellular matrix deposition, all of which are facilitated by Gal-3 ( 23 ). Elevated serum Gal-3 positively correlated with serum creatinine, activity and chronicity indices, and IFTA degree, suggesting that rising Gal-3 reflects worsening renal function ( 1 ). In our cohort, both serum/urinary Gal-3 levels rose progressively across LN classes, consistent with Wu et al. ( 1 ), who noted that serum Gal-3 increased with renal impairment and correlated with pathological activity and chronicity indices across LN classes. Faustini et al. ( 16 ) also observed that urinary Gal-3 was higher in proliferative and membranous LN than mesangial forms and declined after treatment, implying its function as a biomarker of LN activity and class severity. The significant correlations between Gal-3 and histologic fibrosis emphasize its applicability as a non-invasive biomarker for assessing RF in LN. Urinary Gal-3, in particular, demonstrated superior diagnostic accuracy for moderate-to-severe fibrosis compared to serum levels. These findings support its integration into LN monitoring protocols as a complementary tool to eGFR and proteinuria, possibly reducing reliance on repeat biopsies. Moreover, given Gal-3's active role in fibrogenic signaling pathways, therapeutic targeting of Gal-3 may represent a novel antifibrotic approach in LN management. This study is limited to its relatively small sample size, which may limit generalizability. The cross-sectional design precludes assessment of temporal variations in Gal-3 with treatment or disease activity changes. Although the correlations observed were robust, residual confounding from systemic inflammation or other comorbidities cannot be ruled out. Nevertheless, the inclusion of both serum and urine Gal-3 measurements, along with histopathological validation, provides methodological strength and internal consistency. Future research should employ longitudinal studies to determine whether serial Gal-3 measurements predict LN activity, response to therapy, or renal outcomes. Exploring Gal-3 alongside other emerging biomarkers such as NGAL, MCP-1, and TGF-β may enhance diagnostic accuracy and improve mechanistic understanding. Furthermore, interventional studies targeting Gal-3 inhibition could clarify its causal role in RF. Large-scale, multiethnic cohorts are also warranted to establish standardized reference ranges and validate Gal-3's clinical utility across diverse LN populations. This study has some limitations. The single-center, cross-sectional design and the relatively small sample size may limit generalizability and preclude causal inferences. In addition, the limited number of patients in advanced lupus nephritis classes, particularly class VI, may have reduced the power of subgroup analyses. Nevertheless, the inclusion of biopsy-proven lupus nephritis cases and the combined assessment of serum and urinary Gal-3 with histopathological validation strengthen the robustness of our findings. Conclusion Serum/urinary Gal-3 levels were significantly higher in LN patients than in non-LN SLE and controls. Both related moderately to disease activity and strongly to the IFTA score. Urinary Gal-3 demonstrated superior diagnostic accuracy for moderate-to-severe fibrosis. After adjustment for covariates, both markers independently predicted fibrosis severity. These findings highlights serum/urinary Gal-3 appears to to be promising, non-invasive biomarkers for assessing RF in LN, with urinary Gal-3 offering the greatest diagnostic potential for long-term monitoring and risk assessment. Abbreviations LN Lupus Nephritis KF Kidney Fibrosis Gal-3 Galectin-3 SLE Systemic Lupus Erythematosus IFTA Interstitial Fibrosis and Tubular Atrophy SLEDAI Systemic Lupus Erythematosus Disease Activity Index UPCR Urinary Protein-to-Creatinine Ratio BMI Body Mass Index eGFR Estimated Glomerular Filtration Rate AUC Area Under the Curve ROC Receiver Operating Characteristic CKD Chronic Kidney Disease NGAL Neutrophil Gelatinase-Associated Lipocalin MCP-1 Monocyte Chemoattractant Protein-1 and TGF-β Transforming Growth Factor-beta. Declarations Ethics approval and consent to participate The study was authorized by the Research Ethics Committee of the Faculty of Medicine, Tanta University, Egypt (36264PR1300/7/25) and followed the Declaration of Helsinki, with all participants signing informed consent. Consent for publication: Not applicable Availability of data and materials: The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Competing interests: The authors declare that they have no competing interests Funding: None Authors' contributions: A.M.F .: Study Conception and Design, Clinical Data Collection, and Writing-Original Draft. R.Y.H .: Data Interpretation and Literature Review. A.M.E .: Writing – Review & Editing. A.M.R .: Clinical Data Collection and Data Interpretation. A.E .: Statistical Analysis and Data Collection. All authors read and approved the final manuscript. 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Fahmy","email":"data:image/png;base64,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","orcid":"","institution":"Tanta University","correspondingAuthor":true,"prefix":"","firstName":"Ahmed","middleName":"Mohamed","lastName":"Fahmy","suffix":""},{"id":577932771,"identity":"1659280f-e6ea-402b-b247-a6f8b9f1d02a","order_by":1,"name":"rasha youssef hagag","email":"","orcid":"","institution":"Tanta 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08:28:02","extension":"png","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":37083,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8444239/v1/e9d1fdc5e73d3da1ae1e3a24.png"},{"id":100865835,"identity":"7c70292e-8631-42b0-aa44-ba88d4ebf41f","added_by":"auto","created_at":"2026-01-22 08:27:42","extension":"png","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":34516,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8444239/v1/fe43268f63f8a9b2825cc0eb.png"},{"id":100865939,"identity":"4aabe413-ee14-4be8-88f6-e47f17393957","added_by":"auto","created_at":"2026-01-22 08:27:53","extension":"xml","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":92434,"visible":true,"origin":"","legend":"","description":"","filename":"240b75efb4574f7da17197f7e69ad5a81structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8444239/v1/10429923510b132fa25ab06d.xml"},{"id":101203188,"identity":"8f167176-0073-44e1-9b26-6ac016ee124e","added_by":"auto","created_at":"2026-01-27 09:39:01","extension":"html","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":102281,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8444239/v1/7c538d0680826f4a5d5be6c5.html"},{"id":100865909,"identity":"4eab97e8-a2ff-45b6-918d-be4f1c6c08a1","added_by":"auto","created_at":"2026-01-22 08:27:50","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":103965,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eROC Analysis of Urinary Gal-3 for kidney fibrosis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUrinary Gal-3 showed good discriminative ability for detecting moderate-to-severe RF (IFTA ≥10%), with an AUC of 0.872, indicating a high true-positive rate across a wide range of false-positive rates.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8444239/v1/ca99fb2171e93ff54ad68479.png"},{"id":100865812,"identity":"a73b12d1-29ff-41ad-9914-17b1b01ed929","added_by":"auto","created_at":"2026-01-22 08:27:36","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":99613,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eROC Analysis of serum Gal-3 for kidney fibrosis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSerum Gal-3 demonstrated fair ability to identify patients with moderate-to-severe RF (IFTA ≥10%), with an AUC of 0.743, indicating moderate discriminative performance compared with the reference line of no discrimination.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8444239/v1/fe7f5cad503d0aa3939c4462.png"},{"id":103562061,"identity":"f0737695-fa6b-45b4-8277-a8403267e254","added_by":"auto","created_at":"2026-02-27 06:10:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1381850,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8444239/v1/690d2869-5a10-4131-98d3-0cfe000d0d0b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eSerum and Urinary Galectin-3 as a Non-Invasive Marker of Renal Fibrosis in Patients with Lupus Nephritis: A Cross-Sectional Controlled Study\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eChronic kidney injury and progressive fibrosis are central pathological processes driving the decline in renal function across numerous glomerular diseases, including lupus nephritis (LN), a leading complication of systemic lupus erythematosus (SLE) that is substantially implicated in long-term morbidity and mortality. Despite advances in immunosuppressive therapy, LN is still a leading driver of end-stage renal disease (ESRD). The severity of interstitial fibrosis and tubular atrophy (IFTA), together with glomerular and vascular lesions, serves as a key histologic predictor of prognosis and renal survival in patients with LN. Currently, renal biopsy represents the gold standard for assessing these parameters, including chronicity indices and structural damage. However, biopsy is invasive, carries procedural risks, and cannot be performed repeatedly, limiting its utility for disease monitoring and longitudinal assessment (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). This limitation highlights the urgent need for non-invasive biomarkers that can accurately reflect ongoing renal structural deterioration, particularly fibrosis, to facilitate early detection, risk stratification, and enhanced management of LN.\u003c/p\u003e \u003cp\u003eGalectin-3 (Gal-3), a β-galactoside-binding lectin, has become a promising candidate biomarker. It plays multifaceted roles in cell proliferation, differentiation, immune activation, and extracellular matrix remodeling, and contributes to the fibrogenic cascade within renal tissue (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Experimental and clinical data suggest that elevated Gal-3 expression contributes to fibroblast activation, inflammation, and tissue remodeling, ultimately leading to renal scarring and functional decline. A biopsy-based human study demonstrated that chronic kidney disease (CKD) patients exhibited significantly higher plasma Gal-3 levels than non-CKD controls, which displays an inverse correlation with eGFR and positive correlation with histologic fibrosis indices: Interstitial fibrosis, tubular atrophy, and vascular intimal fibrosis (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Moreover, individuals in the highest urinary Gal-3 tertile exhibited the most pronounced renal impairment, greatest proteinuria, and highest risk of progression or ESRD, supporting the concept that urinary Gal-3 may be a robust non-invasive marker of renal damage (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBecause fibrosis and tubular atrophy are irreversible features strongly linked to poor long-term outcomes, early detection of fibrotic remodeling is clinically critical in LN (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Serum Gal-3 levels have been found to be significantly elevated in LN in contrast to both healthy controls and SLE patients without nephritis, correlating with renal dysfunction and histologic indices of chronic damage such as IFTA (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Immunohistochemical studies further revealed that renal tissues from LN patients display increased glomerular and tubular Gal-3 expression, correlating positively with disease activity and chronicity (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Collectively, Gal-3 may be a mechanistic link between autoimmune-mediated injury and fibrotic transformation in LN.\u003c/p\u003e \u003cp\u003eDespite encouraging evidence, critical knowledge gaps remain. Few studies have simultaneously assessed both serum/urinary Gal-3 levels in LN, and no standardized threshold values currently exist to quantify fibrosis severity in this population. Moreover, earlier investigations in broader CKD cohorts (not specific to LN) have yielded inconsistent results regarding Gal-3's predictive capacity for renal and cardiovascular outcomes. Given the unique immunopathology of LN, characterized by immune complex deposition and concurrent glomerular and tubulointerstitial injury, it is essential to validate Gal-3 as a disease-specific, non-invasive biomarker within biopsy-proven LN populations (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTherefore, the present cross-sectional controlled study aims to determine whether patients with biopsy-confirmed LN exhibit significantly higher serum/urinary Gal-3 levels than matched controls (healthy individuals and SLE without nephritis) and to evaluate their correlations with key clinical indicators of renal dysfunction (eGFR, proteinuria) and histologic measures of fibrosis (IFTA, chronicity index).\u003c/p\u003e \u003cp\u003eOur central hypothesis is that elevated serum and/or urinary Gal-3 reflects renal fibrotic burden in LN and may represent a non-invasive surrogate marker for chronic histologic injury, thereby reducing dependence on repeat biopsies and enhancing risk stratification and long-term monitoring of LN patients.\u003c/p\u003e"},{"header":"Patients and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Participants\u003c/h2\u003e \u003cp\u003e This cross-sectional observational study was conducted between July 2025 and November 2025 and included 150 participants, recruited from the Rheumatology and Nephrology Outpatient Clinics and Inpatient Departments, and were divided equally (n\u0026thinsp;=\u0026thinsp;50/group) into three age- and sex-matched groups. Group 1 included patients with biopsy-indicated LN, Group 2 included patients with SLE without nephritis, and Group 3 comprised healthy control individuals.\u003c/p\u003e \u003cp\u003eInclusion criteria comprised participants aged 18 years or older who met the SLE classification criteria established by the European League Against Rheumatism/American College of Rheumatology (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Among these, patients with nephritis underwent kidney biopsy following the KDIGO guidelines, which recommend biopsy in the presence of albuminuria and/or reduced eGFR (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Exclusion criteria included a history of sepsis, active cancer, diabetes, uncontrolled hypertension, chronic liver disease, known cardiovascular disease, or other autoimmune conditions.\u003c/p\u003e \u003cp\u003e The study was authorized by the Research Ethics Committee of the Faculty of Medicine, Tanta University, Egypt (36264PR1300/7/25) and followed the Declaration of Helsinki, with all participants signing informed consent.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eClinical Assessment\u003c/h3\u003e\n\u003cp\u003eAll participants underwent a thorough clinical evaluation, including disease duration, presenting manifestations, treatment history, and prior renal biopsy findings, when available. Disease activity was evaluated using the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) and categorized as follows: no activity (SLEDAI\u0026thinsp;=\u0026thinsp;0), mild (\u003cspan additionalcitationids=\"CR2 CR3 CR4\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e), moderate (\u003cspan additionalcitationids=\"CR7 CR8 CR9\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e), high (\u003cspan additionalcitationids=\"CR12 CR13 CR14 CR15 CR16 CR17 CR18\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e), or very high (\u0026ge;\u0026thinsp;20) (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Demographic and clinical data were also recorded.\u003c/p\u003e\n\u003ch3\u003eLaboratory Investigations\u003c/h3\u003e\n\u003cp\u003eVenous blood and midstream urine samples were collected from all participants under sterile conditions. Laboratory investigations included complete blood count (CBC), blood urea, serum creatinine, serum albumin, antinuclear antibodies (ANA), anti-dsDNA, complement components (C3 and C4), urinary protein-to-creatinine ratio (UPCR), and serum/urinary Gal-3 levels.\u003c/p\u003e \u003cp\u003eCBC was performed using EDTA anticoagulated samples analyzed with an ERMA automated cell counter (Japan). Serum urea, creatinine, and albumin were measured using the INDIKO Plus automated chemistry analyzer (Finland). Complement C3, C4, and urinary protein concentrations were determined using a Cobas c311 automated analyzer (HITACHI, Germany). ANA and anti-dsDNA antibodies were quantified by ELISA using ORGENTEC Diagnostika kits (catalog numbers ORG600 and ORG604, Germany). Serum/urinary Gal-3 concentrations were measured using the AssayMax Human Gal-3 ELISA Kit (Cat. No. EG3311-1; AssayMax, USA). All ELISA assays were performed in duplicate per the protocols, and optical density was measured at 450 nm using a calibrated microplate reader.\u003c/p\u003e\n\u003ch3\u003eHistopathological Evaluation\u003c/h3\u003e\n\u003cp\u003eThe histological categorization of renal biopsy data has been verified against the International Society of Nephrology/Renal Pathology Society (ISN/RPS) standard for individuals diagnosed with LN. To measure renal fibrosis (RF) extent, the IFTA score and chronicity index were documented. These measures were used as benchmarks for establishing a correlation between the severity of histology and the levels of Gal-3 in blood and urine.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eBaseline Characteristics\u003c/h2\u003e \u003cp\u003eThe LN group had significantly higher urea, creatinine, and UPCR, and lower eGFR than non-LN SLE and controls (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Serum/urinary Gal-3 were markedly increased in LN (31.93\u0026thinsp;\u0026plusmn;\u0026thinsp;12.22 and 19.55\u0026thinsp;\u0026plusmn;\u0026thinsp;7.89 ng/mL) relative to non-LN SLE (15.78\u0026thinsp;\u0026plusmn;\u0026thinsp;2.46 and 7.42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.96 ng/mL) and controls (9.86\u0026thinsp;\u0026plusmn;\u0026thinsp;2.15 and 5.22\u0026thinsp;\u0026plusmn;\u0026thinsp;1.65 ng/mL, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline Characteristics of the Participants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-LN SLE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHealthy Control\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e32.94\u0026thinsp;\u0026plusmn;\u0026thinsp;8.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e32.88\u0026thinsp;\u0026plusmn;\u0026thinsp;7.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e32.14\u0026thinsp;\u0026plusmn;\u0026thinsp;7.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI (kg/m\u0026sup2;)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e25.27\u0026thinsp;\u0026plusmn;\u0026thinsp;2.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e24.27\u0026thinsp;\u0026plusmn;\u0026thinsp;3.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e22.86\u0026thinsp;\u0026plusmn;\u0026thinsp;2.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSerum Creatinine (mg/dL)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e1.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eeGFR (mL/min)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e48.06\u0026thinsp;\u0026plusmn;\u0026thinsp;18.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e94.80\u0026thinsp;\u0026plusmn;\u0026thinsp;20.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e107.00\u0026thinsp;\u0026plusmn;\u0026thinsp;16.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSerum Gal-3 (ng/ml)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e31.93\u0026thinsp;\u0026plusmn;\u0026thinsp;12.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e15.78\u0026thinsp;\u0026plusmn;\u0026thinsp;2.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e9.86\u0026thinsp;\u0026plusmn;\u0026thinsp;2.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUrinary Gal-3 (ng/ml)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e19.55\u0026thinsp;\u0026plusmn;\u0026thinsp;7.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e7.42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e5.22\u0026thinsp;\u0026plusmn;\u0026thinsp;1.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eC3 (mg/dL)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e63.87\u0026thinsp;\u0026plusmn;\u0026thinsp;14.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e80.51\u0026thinsp;\u0026plusmn;\u0026thinsp;9.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e93.04\u0026thinsp;\u0026plusmn;\u0026thinsp;10.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eC4 (mg/dL)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e9.73\u0026thinsp;\u0026plusmn;\u0026thinsp;3.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e18.59\u0026thinsp;\u0026plusmn;\u0026thinsp;3.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e24.60\u0026thinsp;\u0026plusmn;\u0026thinsp;5.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAnti-dsDNA (IU/ml)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e101.75\u0026thinsp;\u0026plusmn;\u0026thinsp;29.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e50.04\u0026thinsp;\u0026plusmn;\u0026thinsp;29.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSLEDAI Score\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e12.70\u0026thinsp;\u0026plusmn;\u0026thinsp;3.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e4.06\u0026thinsp;\u0026plusmn;\u0026thinsp;1.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAssociation of Gal-3 with Fibrosis Severity\u003c/h3\u003e\n\u003cp\u003ePatients with moderate-to-severe fibrosis (IFTA\u0026thinsp;\u0026ge;\u0026thinsp;10%) exhibited significantly higher serum/urinary Gal-3 levels compared to those with mild fibrosis (p\u0026thinsp;=\u0026thinsp;0.025 and p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, respectively, Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of Serum/urinary Gal-3 Levels According to Fibrosis Severity\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBiomarker\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild Fibrosis (IFTA\u0026thinsp;\u0026lt;\u0026thinsp;10%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMod-Severe Fibrosis\u003c/p\u003e \u003cp\u003e(IFTA\u0026thinsp;\u0026ge;\u0026thinsp;10%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eU-Statistic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSerum Gal-3\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(ng/ml)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e21.98\u0026thinsp;\u0026plusmn;\u0026thinsp;3.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e34.17\u0026thinsp;\u0026plusmn;\u0026thinsp;12.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e92.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.025*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUrinary Gal-3\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(ng/ml)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e11.67\u0026thinsp;\u0026plusmn;\u0026thinsp;2.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e21.28\u0026thinsp;\u0026plusmn;\u0026thinsp;7.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eCorrelation with Renal Function and Disease Activity\u003c/h3\u003e\n\u003cp\u003eSpearman's correlation analysis showcased strong positive correlations between serum/urinary Gal-3 and IFTA scores, and moderate-to-strong correlations with serum creatinine and eGFR (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 for all, Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). There was a moderate positive correlation between serum/urinary Gal-3 and SLEDAI scores (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation Between Serum/urinary Gal-3 and Clinical-Histopathological Parameters in LN patients (N\u0026thinsp;=\u0026thinsp;49)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSerum Gal-3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUrinary Gal-3\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIFTA Score\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpearman rho 0.7635 \u003c/p\u003e \u003cp\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpearman rho 0.8074\u003c/p\u003e \u003cp\u003e P\u0026thinsp;\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eeGFR (ml/min)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpearman rho \u0026minus;\u0026thinsp;0.6013 \u003c/p\u003e \u003cp\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpearman rho \u0026minus;\u0026thinsp;0.6459 \u003c/p\u003e \u003cp\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCreatinine (mg/dl)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpearman rho 0.6570 \u003c/p\u003e \u003cp\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpearman rho 0.7651 \u003c/p\u003e \u003cp\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUPCR (mg/g)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpearman rho \u0026minus;\u0026thinsp;0.0454\u003c/p\u003e \u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.757\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpearman rho \u0026minus;\u0026thinsp;0.0009\u003c/p\u003e \u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.995\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation Between Gal-3 (Serum \u0026amp; Urine) and SLEDAI Score, N\u0026thinsp;=\u0026thinsp;99)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpearman rho\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCorrelation Type\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSerum Gal-3 vs SLEDAI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.6775\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate Positive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUrinary Gal-3 vs SLEDAI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.6697\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate Positive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eVariation of Gal-3 Across LN Classes\u003c/h2\u003e \u003cp\u003eSerum/urinary Gal-3 levels increased progressively across histopathological LN classes (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Class III (focal proliferative, 5\u0026ndash;10% involvement; n\u0026thinsp;=\u0026thinsp;9) exhibited the lowest concentrations (serum: 21.98\u0026thinsp;\u0026plusmn;\u0026thinsp;3.14 ng/mL; urine: 11.67\u0026thinsp;\u0026plusmn;\u0026thinsp;2.36 ng/mL). Higher levels were observed in Class IV (diffuse proliferative, 10\u0026ndash;30%; n\u0026thinsp;=\u0026thinsp;29) (serum: 29.62\u0026thinsp;\u0026plusmn;\u0026thinsp;12.07 ng/mL; urine: 18.66\u0026thinsp;\u0026plusmn;\u0026thinsp;7.40 ng/mL), peaking in Class IV\u0026thinsp;+\u0026thinsp;V (mixed proliferative/membranous, 30\u0026ndash;40%; n\u0026thinsp;=\u0026thinsp;9) (serum: 44.65\u0026thinsp;\u0026plusmn;\u0026thinsp;3.72 ng/mL; urine: 27.89\u0026thinsp;\u0026plusmn;\u0026thinsp;3.47 ng/mL) and Class VI (sclerosing, \u0026gt;\u0026thinsp;40%; n\u0026thinsp;=\u0026thinsp;3) (serum: 45.20\u0026thinsp;\u0026plusmn;\u0026thinsp;3.44 ng/mL; urine: 26.87\u0026thinsp;\u0026plusmn;\u0026thinsp;2.10 ng/mL). This progressive elevation correlated significantly with histopathological severity (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSerum/urinary Gal-3 Levels by LN Class (ISN/RPS)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLN Class\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eISN/RPS Category\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNum\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSerum Gal- 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUrinary Gal-3\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClass III\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFocal proliferative (5\u0026ndash;10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e21.98\u0026thinsp;\u0026plusmn;\u0026thinsp;3.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e11.67\u0026thinsp;\u0026plusmn;\u0026thinsp;2.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClass IV\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDiffuse proliferative (10\u0026ndash;30%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e29.62\u0026thinsp;\u0026plusmn;\u0026thinsp;12.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e18.66\u0026thinsp;\u0026plusmn;\u0026thinsp;7.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClass IV\u0026thinsp;+\u0026thinsp;V\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMixed proliferative\u0026thinsp;+\u0026thinsp;membranous (30\u0026ndash;40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e44.65\u0026thinsp;\u0026plusmn;\u0026thinsp;3.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e27.89\u0026thinsp;\u0026plusmn;\u0026thinsp;3.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClass VI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSclerosing (\u0026gt;\u0026thinsp;40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e45.20\u0026thinsp;\u0026plusmn;\u0026thinsp;3.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e26.87\u0026thinsp;\u0026plusmn;\u0026thinsp;2.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSpearman's correlation confirmed a strong positive association between urinary Gal-3 levels and LN class (ρ\u0026thinsp;=\u0026thinsp;0.647, p\u0026thinsp;\u0026lt;\u0026thinsp;0.00001). Serum Gal-3 levels differed significantly across LN classes by the Kruskal-Wallis test (p\u0026thinsp;=\u0026thinsp;0.0007), consistent with the stepwise increase in severity. There was a strong correlation between serum/urinary Gal-3 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation Analysis of Galectin-3 Levels with Lupus Nephritis Class and Between Compartments\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCorrelation Pair\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpearman ρ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInterpretation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUrinary Gal-3 vs LN Class\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.6470\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.00001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStrong positive correlation with disease severity\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSerum Gal-3 vs LN Class\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSignificant difference across classes (Kruskal-Wallis)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSerum vs Urinary Gal-3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStrong intercorrelation validates both biomarkers\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eDiagnostic Performance of Gal-3\u003c/h2\u003e \u003cp\u003eThe ROC curve analysis demonstrated superior diagnostic performance of urinary Gal-3 compared with serum Gal-3 in detecting RF. Urinary Gal-3 achieved an AUC value of 0.872, with specificity of 88.9% and a Youden Index of 0.589 at an optimal cutoff value of 14.81 ng/mL. In contrast, serum Gal-3 showed a moderate diagnostic ability with an AUC of 0.743, specificity of 66.7%, and a Youden Index of 0.367 at an optimal cutoff of 22.5 ng/mL (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eROC Analysis of Serum/urinary Gal-3 for RF\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBiomarker\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAUC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOptimal Cutoff\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSpecificity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYouden Index\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSerum Gal-3\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(ng/ml)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.7431\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.584\u0026ndash;0.902\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.700\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.367\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUrinary Gal-3\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(ng/ml)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.8722\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.768\u0026ndash;0.977\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.700\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.889\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.589\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cem\u003eInterpretation: AUC 0.8722\u0026thinsp;=\u0026thinsp;GOOD discriminatory ability (0.8\u0026ndash;0.9 range); AUC 0.7431\u0026thinsp;=\u0026thinsp;FAIR discriminatory ability (0.7\u0026ndash;0.8 range)\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eRegression Analysis\u003c/h2\u003e \u003cp\u003eMultivariable regression analyses demonstrated that both serum/urinary Gal-3 were significant and independent fibrosis severity predictors in LN. Urinary Gal-3 exhibited a stronger association (β\u0026thinsp;=\u0026thinsp;0.817, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared with serum (β\u0026thinsp;=\u0026thinsp;0.549, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). eGFR was the only other significant independent variable, showing a negative association with fibrosis severity, consistent with the decline in renal function accompanying disease progression. Other clinical parameters, including SLEDAI, UPCR, and age, did not reach significance in either model (Tables\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariable Regression Analysis of Serum Gal-3 as a Predictor of Fibrosis Severity in LN\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCoefficient (β)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003et-statistic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIntercept\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-7.36 to 27.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.264\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSerum Gal-3\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(ng/ml)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.549\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.33 to 0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSLEDAI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.41 to 0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.644\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUPCR (mg/g)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.002 to 0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.801\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.30 to 0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.753\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eeGFR (ml/min)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.226\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.37 to -0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-3.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.004***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariable Regression Analysis of urinary Gal-3 as a Predictor of Fibrosis Severity in LN\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCoefficient (β)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003et-statistic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIntercept\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-9.81 to 27.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.352\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUrinary Gal-3\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(ng/ml)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.817\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.45 to 1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSLEDAI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.44 to 0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.677\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUPCR (mg/g)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.002 to 0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.749\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.24 to 0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.820\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eeGFR (ml/min)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.223\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.38 to -0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-2.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.007***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe last common pathway of CKD progression across etiologies, including LN, is kidney fibrosis, characterized by IFTA. Although invasive kidney biopsy is still the gold standard for fibrosis evaluation, its inherent risks and limited reproducibility necessitate the development of reliable non-invasive biomarkers. Among these, Gal-3 has recently gained attention for its role in tissue fibrosis and inflammation, suggesting its potential as a non-invasive indicator of LN activity and chronicity.\u003c/p\u003e \u003cp\u003eOur study's renal profile revealed that LN patients displayed significantly higher blood urea, UPCR, and serum creatinine levels than lupus patients without nephritis, with a corresponding reduction in eGFR. These findings align with El-Shehaby et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e), who also observed significant differences in these renal indices between LN and non-LN SLE patients. Similarly, Ding et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e) reported significantly lower eGFR in active LN, unlike inactive LN, in agreement with our data.\u003c/p\u003e \u003cp\u003eCompared to controls, SLE groups exhibited significantly reduced levels of complement components C3 and C4, with more pronounced reductions among LN patients. This pattern reflects complement consumption due to immune complex deposition and renal inflammation. Sharifipour et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) reported similar findings, while Farid et al. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e) and Rubinstein et al. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) found no significant variation in C3 levels between LN and non-LN SLE, possibly reflecting differences in disease stage or patient demographics.\u003c/p\u003e \u003cp\u003eHerein, serum/urinary Gal-3 levels were significantly higher in LN patients than in non-LN SLE and controls. eGFR was notably lower in the LN group, aligning with Faustini et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e), who demonstrated that urinary Gal-3 was higher in LN, distinguishing LN from active SLE without nephritis. Levels decreased after treatment, related to the activity index, and were independent of proteinuria. Similarly, serum Gal-3 was higher in LN than in non-renal SLE, correlated with renal biopsy activity and chronicity indices, and helped confirm LN presence (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Furthermore, urinary Gal-3 was significantly higher in active LN, unlike inactive LN, with ROC curve analysis showing good discriminatory ability for differentiating active LN from inactive LN and healthy controls, and was positively correlated with SLEDAI (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSkoot et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e) similarly observed that serum Gal-3 levels were considerably higher in LN patients than in SLE without LN and controls. Urinary Gal-3 was likewise elevated in LN, unlike non-LN SLE and controls. Collectively, serum/urinary Gal-3 reliably reflects renal involvement and fibrotic burden in LN.\u003c/p\u003e \u003cp\u003eGal-3 proved to be a dependable quantitative biomarker of both pathological fibrosis and deteriorating kidney function, showing moderate-to-strong correlations with serum creatinine and eGFR, as well as significant positive correlations with histologic fibrosis (IFTA scores). This is consistent with Ou et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e), who found a negative correlation between urinary Gal-3 and eGFR and positive correlations with plasma Gal-3, serum creatinine, and UPCR. Urinary Gal-3 levels also increased progressively with CKD stage, with marked elevations in stage 5 disease, and were associated with interstitial fibrosis, tubular atrophy, and interstitial inflammation.\u003c/p\u003e \u003cp\u003eChen et al. (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e) reported similar associations in diabetic kidney disease, showing that macrophage-derived Gal-3 promotes renal damage via TGFβ1 signaling. Further, Ou et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) demonstrated that plasma Gal-3 was higher in CKD compared to non-CKD, inversely correlated with eGFR, and was significantly related to tubular atrophy, interstitial fibrosis, and vascular intimal fibrosis. Similarly, Rao et al. (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e) linked urinary Gal-3 with RF in heart failure patients, and Drechsler et al. (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e) found that elevated Gal-3 in the blood correlated with adverse renal outcomes and fibrosis progression.\u003c/p\u003e \u003cp\u003eInterstitial fibrosis and irreversible kidney injury in LN arise from fibroblast activation, epithelial\u0026ndash;mesenchymal transition, and extracellular matrix deposition, all of which are facilitated by Gal-3 (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Elevated serum Gal-3 positively correlated with serum creatinine, activity and chronicity indices, and IFTA degree, suggesting that rising Gal-3 reflects worsening renal function (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). In our cohort, both serum/urinary Gal-3 levels rose progressively across LN classes, consistent with Wu et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e), who noted that serum Gal-3 increased with renal impairment and correlated with pathological activity and chronicity indices across LN classes. Faustini et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e) also observed that urinary Gal-3 was higher in proliferative and membranous LN than mesangial forms and declined after treatment, implying its function as a biomarker of LN activity and class severity.\u003c/p\u003e \u003cp\u003eThe significant correlations between Gal-3 and histologic fibrosis emphasize its applicability as a non-invasive biomarker for assessing RF in LN. Urinary Gal-3, in particular, demonstrated superior diagnostic accuracy for moderate-to-severe fibrosis compared to serum levels. These findings support its integration into LN monitoring protocols as a complementary tool to eGFR and proteinuria, possibly reducing reliance on repeat biopsies. Moreover, given Gal-3's active role in fibrogenic signaling pathways, therapeutic targeting of Gal-3 may represent a novel antifibrotic approach in LN management.\u003c/p\u003e \u003cp\u003eThis study is limited to its relatively small sample size, which may limit generalizability. The cross-sectional design precludes assessment of temporal variations in Gal-3 with treatment or disease activity changes. Although the correlations observed were robust, residual confounding from systemic inflammation or other comorbidities cannot be ruled out. Nevertheless, the inclusion of both serum and urine Gal-3 measurements, along with histopathological validation, provides methodological strength and internal consistency.\u003c/p\u003e \u003cp\u003eFuture research should employ longitudinal studies to determine whether serial Gal-3 measurements predict LN activity, response to therapy, or renal outcomes. Exploring Gal-3 alongside other emerging biomarkers such as NGAL, MCP-1, and TGF-β may enhance diagnostic accuracy and improve mechanistic understanding. Furthermore, interventional studies targeting Gal-3 inhibition could clarify its causal role in RF. Large-scale, multiethnic cohorts are also warranted to establish standardized reference ranges and validate Gal-3's clinical utility across diverse LN populations.\u003c/p\u003e \u003cp\u003eThis study has some limitations. The single-center, cross-sectional design and the relatively small sample size may limit generalizability and preclude causal inferences. In addition, the limited number of patients in advanced lupus nephritis classes, particularly class VI, may have reduced the power of subgroup analyses. Nevertheless, the inclusion of biopsy-proven lupus nephritis cases and the combined assessment of serum and urinary Gal-3 with histopathological validation strengthen the robustness of our findings.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eSerum/urinary Gal-3 levels were significantly higher in LN patients than in non-LN SLE and controls. Both related moderately to disease activity and strongly to the IFTA score. Urinary Gal-3 demonstrated superior diagnostic accuracy for moderate-to-severe fibrosis. After adjustment for covariates, both markers independently predicted fibrosis severity. These findings highlights serum/urinary Gal-3 appears to to be promising, non-invasive biomarkers for assessing RF in LN, with urinary Gal-3 offering the greatest diagnostic potential for long-term monitoring and risk assessment.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eLN\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLupus Nephritis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eKF\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eKidney Fibrosis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eGal-3\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGalectin-3\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eSLE\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSystemic Lupus Erythematosus\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eIFTA\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInterstitial Fibrosis and Tubular Atrophy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eSLEDAI\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSystemic Lupus Erythematosus Disease Activity Index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eUPCR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eUrinary Protein-to-Creatinine Ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eBMI\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBody Mass Index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eeGFR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEstimated Glomerular Filtration Rate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eAUC\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eArea Under the Curve\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eROC\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eReceiver Operating Characteristic\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eCKD\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eChronic Kidney Disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eNGAL\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNeutrophil Gelatinase-Associated Lipocalin\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eMCP-1\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMonocyte Chemoattractant Protein-1\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eand \u003cb\u003eTGF-β\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTransforming Growth Factor-beta.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was authorized by the Research Ethics Committee of the Faculty of Medicine, Tanta University, Egypt (36264PR1300/7/25) and followed the Declaration of Helsinki, with all participants signing informed consent.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u0026nbsp;\u003c/strong\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eNone\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions: A.M.F\u003c/strong\u003e.: Study Conception and Design, Clinical Data Collection, and Writing-Original Draft. \u003cstrong\u003eR.Y.H\u003c/strong\u003e.: Data Interpretation and Literature Review. \u003cstrong\u003eA.M.E\u003c/strong\u003e.: Writing – Review \u0026amp; Editing. \u003cstrong\u003eA.M.R\u003c/strong\u003e.: Clinical Data Collection and Data Interpretation. \u003cstrong\u003eA.E\u003c/strong\u003e.: Statistical Analysis and Data Collection. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eWu J, Yu X, Liu X, Chen J, Zhou X, Zhao X. Serum galectin-3 can help distinguish lupus nephritis from systemic lupus erythematosus and is also correlated with the degree of renal damage in lupus nephritis. Medicine (Baltimore). 2024;103(51): e40987.\u003c/li\u003e\n \u003cli\u003eChen SC, Kuo PL. The role of galectin-3 in the kidneys. Int J Mol Sci. 2016;17(4):565.\u003c/li\u003e\n \u003cli\u003eOu SM, Tsai MT, Chen HY, Li FA, Tseng WC, Lee KH. Identification of galectin-3 as potential biomarkers for renal fibrosis by RNA-sequencing and clinicopathologic findings of kidney biopsy. Front Med. 2021; 8:748225.\u003c/li\u003e\n \u003cli\u003eOu SM, Tsai MT, Chen HY, Li FA, Lee KH, Tseng WC. Urinary galectin-3 as a novel biomarker for the prediction of renal fibrosis and kidney disease progression. Biomedicines. 2022;10(3):585.\u003c/li\u003e\n \u003cli\u003eSyn G, Lee YQ, Lim ZY, Chan GC. Galectin-3: action and clinical utility in chronic kidney disease. Int Urol Nephrol. 2024;56(11):3535\u0026ndash;3543.\u003c/li\u003e\n \u003cli\u003eKang EH, Moon KC, Lee EY, et al. Renal expression of galectin-3 in systemic lupus erythematosus patients with nephritis. Lupus. 2009;18(1):22\u0026ndash;28.\u003c/li\u003e\n \u003cli\u003eBellos I, Marinaki S, Lagiou P, Benetou V. Galectin-3 in chronic kidney disease. Clin Chim Acta. 2024; 559:119727.\u003c/li\u003e\n \u003cli\u003eMosca M, Merrill JT, Bombardieri S. Assessment of disease activity in systemic lupus erythematosus. In: Tsokos GC, Gordon C, Smolen JS, editors. Systemic Lupus Erythematosus. Philadelphia: Mosby; 2007. p. 19\u0026ndash;23.\u003c/li\u003e\n \u003cli\u003eAringer M. EULAR/ACR classification criteria for SLE. Semin Arthritis Rheum. 2019;49(3 Suppl): S14\u0026ndash;S17.\u003c/li\u003e\n \u003cli\u003eRovin BH, Ayoub IM, Chan TM. KDIGO 2024 clinical practice guideline for the management of lupus nephritis. Kidney Int. 2024;105(1 Suppl): S1\u0026ndash;S69.\u003c/li\u003e\n \u003cli\u003eEl-Shehaby A, Darweesh H, El-Khatib M, et al. Correlations of urinary biomarkers TWEAK, OPG, MCP-1, and IL-8 with lupus nephritis. J Clin Immunol. 2011;31(5):848\u0026ndash;856.\u003c/li\u003e\n \u003cli\u003eDing H, Shen Y, Lin C. Urinary galectin-3 binding protein (G3BP) as a biomarker for disease activity and renal pathology characteristics in lupus nephritis. Arthritis Res Ther. 2022; 24:77.\u003c/li\u003e\n \u003cli\u003eSharifipour F, Zeraati A, Sahebari M, Hatef M, Naghibi M, Rezaieyazdi Z. Association of urinary lipocalin-2 with lupus nephritis. Iran J Basic Med Sci. 2013;16(9):1011\u0026ndash;1015.\u003c/li\u003e\n \u003cli\u003eFarid EM, Hassan AB, Abalkhail AA, et al. Immunological aspects of biopsy-proven lupus nephritis in Bahraini patients with SLE. Saudi J Kidney Dis Transpl. 2013;24(6):1271\u0026ndash;1279.\u003c/li\u003e\n \u003cli\u003eRubinstein T, Pitashny M, Levine B, et al. Urinary NGAL as a novel biomarker for disease activity in lupus nephritis. Rheumatology. 2010;49(5):960\u0026ndash;971.\u003c/li\u003e\n \u003cli\u003eFaustini F, Idborg H, Fuzzi E, Lood C, Gunnarsson I, Svenungsson E. Urine galectin-3 binding protein reflects nephritis activity in SLE. Lupus. 2023;32(2):252\u0026ndash;262.\u003c/li\u003e\n \u003cli\u003eWu J, Wang P, Liu Z. Serum galectin-3 can help distinguish lupus nephritis from SLE and correlates with renal damage severity. Eur J Clin Invest. 2025;55(1): e14294.\u003c/li\u003e\n \u003cli\u003eSkoot A, Ghazy MA, Nosair N. Serum and urinary galectin-3 binding protein (G3BP) as novel biomarkers in lupus nephritis. Egypt J Intern Med. 2025; 37:144.\u003c/li\u003e\n \u003cli\u003eSaccon F, Gatto M, Ghirardello A, Iaccarino L, Punzi L, Doria A. Role of galectin-3 in autoimmune and non-autoimmune nephropathies. Autoimmun Rev. 2017;16(1):34\u0026ndash;47.\u003c/li\u003e\n \u003cli\u003eChen Y, Jiang Q, Xing X,et al. Macrophage-derived galectin-3 promotes renal fibrosis and diabetic kidney disease by enhancing TGF-\u0026beta;1 signaling. Adv Sci. 2025;12(35): e04032.\u003c/li\u003e\n \u003cli\u003eRao VS, Ivey-Miranda JB, Cox ZL, Moreno-Villagomez J, Testani JM. Association of urine galectin-3 with cardiorenal outcomes in heart failure. J Card Fail. 2024;30(2):340\u0026ndash;346.\u003c/li\u003e\n \u003cli\u003eDrechsler C, Delgado G, Wanner C, et al. Galectin- 3, renal function, and clinical outcomes: results from the LURIC and 4D studies. J Am Soc Nephrol. 2015;26(9):2213\u0026ndash;2221.\u003c/li\u003e\n \u003cli\u003eWang F, Zhou L, Eliaz A, et al. The potential roles of galectin-3 in AKI and CKD. Front Physiol. 2023; 14:1090724.\u003cstrong\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Galectin-3, lupus nephritis, renal fibrosis, biomarker, non-invasive, IFTA","lastPublishedDoi":"10.21203/rs.3.rs-8444239/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8444239/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eKidney fibrosis (KF) is a key determinant of adverse outcomes in lupus nephritis (LN). Although kidney biopsy remains the diagnostic gold standard, its invasiveness limits its routine use, necessitating the development of reliable non-invasive biomarkers. Galectin-3 (Gal-3), a β-galactoside-binding lectin involved in fibrogenesis, has been proposed as a candidate marker; however, its clinical value in LN remains uncertain.\u003c/p\u003e\u003ch2\u003eObjectives\u003c/h2\u003e \u003cp\u003eOur aim was to evaluate serum/urinary Gal-3 as non-invasive biomarkers of kidney fibrosis in LN and compare their diagnostic performance with non-nephritic systemic lupus erythematosus (SLE) and healthy controls.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis cross-sectional case-control study enrolled 150 participants (50 LN, 50 non-LN SLE, 50 controls). LN patients were stratified by interstitial fibrosis and tubular atrophy (IFTA) score. Subsequently, we measured serum/urinary Gal-3, renal function indices, C3, C4, anti-dsDNA, BMI, and urinary protein-to-creatinine ratio (UPCR). Disease activity was assessed using the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eUnlike the other groups, serum/urinary Gal-3 levels were significantly higher in the LN group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Both correlated strongly with IFTA score (ρ\u0026thinsp;=\u0026thinsp;0.76\u0026ndash;0.81, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and moderately with SLEDAI. Urinary Gal-3 showed superior diagnostic accuracy for moderate\u0026ndash;severe fibrosis (AUC\u0026thinsp;=\u0026thinsp;0.87, 95% CI 0.77\u0026ndash;0.98) than serum (AUC\u0026thinsp;=\u0026thinsp;0.74). Both remained independent predictors of fibrosis severity after adjustment.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eSerum/urinary Gal-3 are reliable, non-invasive biomarkers of kidney fibrosis in LN, with urinary Gal-3 demonstrating the highest diagnostic performance.\u003c/p\u003e","manuscriptTitle":"Serum and Urinary Galectin-3 as a Non-Invasive Marker of Renal Fibrosis in Patients with Lupus Nephritis: A Cross-Sectional Controlled Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-22 08:25:30","doi":"10.21203/rs.3.rs-8444239/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f0aa2dbe-00e6-4aab-a20d-a5236e824b4f","owner":[],"postedDate":"January 22nd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-27T06:10:10+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-22 08:25:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8444239","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8444239","identity":"rs-8444239","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}