Hydronephrosis-Associated Renal Fibrosis: Clinical Validation of Spp1 as a Biomarker and Therapeutic Target

Authors: Xiao Wang, Jie-Hao Zhou, Guang Chen, Ji-Dong Chen, Hui Li, Wei-Min Shan, Wei-xiao Li

Abstract

Background

Renal fibrosis is a key driver of chronic kidney disease, often leading to end-stage renal disease (ESRD). Secreted phosphoprotein 1 (Spp1) is implicated in fibrotic processes, but its specific role in renal fibrosis, particularly associated with hydronephrosis, remains underexplored. This study investigates Spp1’s involvement using transcriptomic analysis, machine learning, and clinical data integration.

Methods

Renal tissues from sham-operated mice with unilateral ureteral obstruction for 7 days were analyzed via transcriptome sequencing to identify differentially expressed genes (DEGs). Hub genes were identified through Weighted Gene Co-Expression Network Analysis and pathway enrichment. LASSO regression pinpointed potential biomarkers, with Spp1 validated in mouse and human samples through RT-PCR and immunohistochemistry. Clinical correlations were drawn from hydronephrosis patient data.

Results

Transcriptomic analysis revealed 5,219 DEGs, highlighting key pathways including IL-17, TNF, and PI3K/AKT. Spp1 emerged as a significant biomarker, strongly associated with tubular injury and fibrosis markers such as neutrophil gelatinase-associated lipocalin. Logistic regression and receiver operating characteristic (ROC) analysis confirmed Spp1 and urinary transferrin (U-TRF) as predictors of severe hydronephrosis, with high diagnostic accuracy (area under the ROC 0.898 for Spp1; 0.938 for U-TRF).

Conclusions

Spp1 is a critical mediator in renal fibrosis and a promising biomarker for assessing hydronephrosis severity. Its diagnostic value, particularly when combined with U-TRF, underscores the need for further research into Spp1-targeted therapies in renal fibrosis.

Introduction

Kidney stone disease is a multifactorial disorder characterized by high prevalence and recurrence rates, imposing a substantial global health and economic burden [1]. Although surgical intervention can alleviate symptoms by relieving obstruction, patients with recurrent kidney stones are at a significantly increased risk of developing chronic kidney disease (CKD) and experiencing adverse cardiovascular outcomes [2]. Recent research has highlighted the complex pathophysiology of kidney stone disease, involving not only metabolic and nutritional factors but also genetic regulation and cellular mechanisms underlying crystal formation [3, 4].

Early intervention can typically preserve kidney function, but if the condition progresses, even surgical relief may not prevent ongoing renal damage, potentially leading to ESRD [5]. This presents a significant global health challenge as renal fibrosis – a hallmark of CKD – is marked by the pathological accumulation of extracellular matrix (ECM) proteins, disrupting kidney structure and function [6].

Despite advances in understanding renal fibrosis, effective therapies remain elusive. Secreted phosphoprotein 1 (Spp1) has emerged as a key player in renal fibrosis. Spp1, a multifunctional glycoprotein, is involved in inflammation, tissue remodeling, and fibrosis [5, 7]. It interacts with integrins and CD44 receptors, facilitating the recruitment of macrophages and fibroblasts, which are central to the fibrotic response [8]. These cells contribute to ECM deposition and activate pro-fibrotic signaling pathways, such as transforming growth factor-beta (TGF-β) [7].

Recent studies suggest that Spp1 is not only a marker of kidney injury but also actively drives the fibrotic process, making it a promising therapeutic target [9–13]. Moreover, machine learning techniques have identified Spp1 as a critical predictor of disease progression, further highlighting its potential as a biomarker.

This study aimed to elucidate Spp1’s role in renal fibrosis using a multifaceted approach, including transcriptome sequencing, machine learning-based biomarker identification, protein expression analysis, and clinical data integration. By examining both mouse models of unilateral ureteral obstruction (UUO) and human kidney tissues, we aimed to unravel the molecular mechanisms through which Spp1 contributes to renal fibrosis and to explore its potential as a diagnostic and therapeutic target.

Materials and Methods

Transcriptome Sequencing

Transcriptome sequencing was conducted on renal samples from sham-operated mice with unilateral ureteral obstruction for 7 days (UUO7) mice using the Illumina HiSeq platform. Differentially expressed genes (DEGs) were identified using a significance threshold of p < 0.05. To explore the biological functions of these DEGs, Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using TopGO software and the KEGG database. Additionally, Gene Set Enrichment Analysis (GSEA) was conducted using the “limma” and “GSEABase” packages within R (version 4.1.3). Data visualization was achieved through heatmaps and bubble charts generated in R Studio.

Target Gene Screening through Weighted Gene Co-Expression Network Analysis

Weighted Gene Co-Expression Network Analysis (WGCNA) was employed to identify gene co-expression modules associated with renal fibrosis. Data preprocessing, including the screening of missing values and clustering, was performed to ensure data integrity. A “soft” threshold power (β) was determined to construct a biologically relevant network, followed by the generation of a topological overlap matrix. Dynamic tree-cutting algorithms were utilized to detect gene modules, with Gene Significance and Module Membership values calculated to link these modules to clinical features. Further analyses of these modules were conducted using KEGG and TopGO.

Screening and Validation of Diagnostic Markers

To identify potential biomarkers, machine learning techniques, particularly LASSO regression, were applied. This analysis identified six candidate genes as potential biomarkers for UUO-induced renal fibrosis. Spp1 was among these biomarkers and was further validated in both mouse and human kidney tissues using RT-PCR and immunohistochemistry.

External Dataset Validation

Gene expression data from the Gene Expression Omnibus repository, including datasets GSE96571 and GSE149915, were analyzed using GEO2R and GraphPad Prism (version 8) for statistical validation of the identified biomarkers. The expression levels of Spp1 were compared across different groups to assess its relevance.

Human Fibrotic Kidney Samples Collection

Fibrotic and normal renal tissues were collected from patients undergoing nephrectomy at Fuyang People’s Hospital, Anhui Medical University. Fibrotic tissues were obtained from 20 patients with urinary obstruction and 12 patients with renal pelvis cancer, while normal tissues were collected from 20 patients with renal cancer undergoing radical nephrectomy. The study adhered to the Declaration of Helsinki and received approval from the Medical Ethics Committee of Fuyang People’s Hospital of Anhui Medical University (Approval No.: [2024]19). The study was conducted from January 2023 to August 2024; all participants provided written informed consent before surgery.

Hydronephrotic Kidney Patient Classification

Hydronephrotic kidney (HK) patients were classified into severe hydronephrosis (SHK) and mild to moderate hydronephrosis (MHK) groups based on CT imaging [14, 15]. The SHK group exhibited significant renal enlargement, cystic dilation in the renal sinus area, and thinning or atrophy of the renal parenchyma. The MHK group showed minimal changes in parenchymal thickness, renal calyceal hydronephrosis, increased renal volume, and some parenchymal thinning.

Inclusion and Exclusion Criteria

Inclusion Criteria

Patients were included if they had unilateral renal hydronephrosis due to upper urinary tract obstruction with the contralateral kidney confirmed healthy, and had completed preoperative blood, urine tests, and imaging within 1 week of admission. They had no history of solitary kidney, renal anatomical abnormalities, prior renal surgeries, radiotherapy, chemotherapy, nephrotoxic drug use, or acute or chronic pyelonephritis or glomerulonephritis.

Exclusion Criteria

Patients were excluded if they had conditions such as glomerulonephritis, allergic purpura nephritis, nephrotic syndrome, hepatitis B-related nephritis, or any condition leading to renal function deterioration. Exclusions also included patients with polycystic kidneys, sponge kidneys, horseshoe kidneys, solitary kidneys, renal transplants, or acute renal infarction, as well as those with severe systemic diseases like cardiac, hepatic, or pulmonary failure, coagulation disorders, or incomplete clinical data.

Clinical Biochemistry and Pathology Data Collection

Baseline characteristics, including age, sex, height, and weight, were recorded upon admission. Biochemical tests on blood and urine were conducted after fasting for 6–8 h the following morning. These tests included measurements of blood lipids, fasting blood glucose, plasma albumin, hemoglobin, serum creatinine (Scr), blood urea nitrogen (BUN), uric acid, low-density lipoprotein cholesterol, very low-density lipoprotein, hemoglobin A1c (HbA1c), cystatin C (U-cyc), urinary transferrin (U-TRF), urinary IgG (U-IgG), urinary albumin (U-ALB), urine microalbumin (U-MA), urinary retinol-binding protein (U-RBP), and urinary creatinine (U-Cr). The extent of renal tubular damage, interstitial fibrosis and tubular atrophy (IFTA), and interstitial inflammation were graded according to established pathological criteria.

Animal Models

All animal experiments were conducted in compliance with guidelines from the Animal Care and Use Committee of Anhui Medical University, following NIH guidelines. Male C57BL/6 mice (weighing 18–22 g, 8 weeks old) were obtained from GemPharmatech Co., Ltd. Mice were anesthetized with pentobarbital (70 mg/kg) and randomly assigned to four sham and UUO3, UUO7, UUO14, with six mice per group. Ureteral obstruction was induced by double ligation of the left ureter using 5-0 silk through a left lumbar incision. Fibrotic kidneys were collected at 3, 7, and 14 days post-operation. Sham group mice underwent identical procedures without ureteral ligation.

Pathological Assays

Kidneys from each group (n = 6) were fixed in 4% paraformaldehyde, sectioned into 4 μm slices using a microtome (RM2235, Leica, Wetzlar, Germany), and subjected to hematoxylin and eosin (HE) and Masson trichrome staining for histopathological evaluation under an Olympus BX53F microscope (Tokyo, Japan).

HE Staining

Tissue sections were deparaffinized, rehydrated, and stained with hematoxylin for 5–10 min, followed by eosin for 1–3 min. After dehydration and clearing, sections were mounted with coverslips. To ensure consistency, three experienced pathologists independently reviewed the slides. The assessment

Tubular Damage Score

Scoring was based on the extent of necrosis, loss of brush border, cast formation, and tubular dilatation, on a scale of 0 (no damage) to 4 (very severe damage, >75% of tubules affected).

IFTA Score

This score evaluated the degree of fibrosis and atrophy in the tubules, graded on a scale from 0 to 3, with 3 indicating severe fibrosis and tubular atrophy.

Interstitial Inflammation

Scored from 0 to 2, where 0 indicates no inflammation, 1 indicates mild inflammation, and 2 indicates severe inflammation.

Masson’s Trichrome Staining

Sections were deparaffinized, rehydrated, and treated with Bouin’s solution at 56°C for 1 h. They were then stained with Weigert’s hematoxylin, Biebrich scarlet-acid fuchsin, and aniline blue to highlight collagen fibers. After dehydration and clearing, sections were mounted for analysis. Collagen deposition, indicative of fibrosis, was quantified using ImageJ software to calculate the Collagen Proportionate Area (CPA), representing the ratio of blue-stained collagen to total tissue area, with higher CPA indicating more extensive fibrosis.

Immunohistochemical Staining

Slides were deparaffinized in xylene and rehydrated in graded alcohols. Following antigen retrieval with EDTA buffer under high pressure, slides were treated with 3% H2O2 (PBS) for 10 min to block endogenous peroxidase activity. Blocking was performed using 20% goat serum (PBS) for 30 min. Primary antibodies (WanLeiBio, WL00691) were incubated overnight at 4°C, followed by secondary antibody incubation for 1 h at 37°C. Slides were rinsed with PBS for 3–5 min after each step and finally stained with 3,3-diaminobenzidine (DAB) (Zhongshan Jinqiao, China). Imaging was performed using an Olympus BX53F microscope, and quantification was carried out using ImageJ software (Bethesda, MD, USA).

RNA Extraction and qRT-PCR

Total RNA was extracted from renal tissues using TRIzol (Invitrogen, Massachusetts, USA). cDNA synthesis was performed using the cDNA Synthesis Kit (Takara, Japan). The SYBR Premix ExTaqTM II Kit (Takara, Japan) was used for RT-PCR on the CFX ConnectTM real-time system (CFX96, Bio-RAD, Singapore, USA). Primers were synthesized by GENERAL BIOL (Anhui, China), and relative mRNA levels were calculated using the 2^−ΔΔ^Ct method, with β-actin serving as the reference control.

Spp1 Protein Expression in Mouse Serum

Serum samples from Sham and UUO3, UUO7, and UUO14 mice (n = 6) were collected. Spp1 concentrations in serum were measured using ELISA kits (SenbeiJia Biotechnology, SBJ-H1123) according to the manufacturer’s instructions.

Statistical Analysis

Statistical analysis and data visualization were performed using R (version 4.4.0, https://www.r-project.org/). Sample sizes were calculated using PASS (version 15.0). ImageJ was used for image data analysis. SPSS (version 29.0) was employed for statistical evaluations. Normally distributed data were analyzed using the Shapiro-Wilk test, while categorical and non-normally distributed data were compared using chi-square or rank-sum tests. Quantitative data were presented as mean ± standard deviation (SD) or mean ± standard error of the mean (SEM). Group comparisons for normally distributed data were made using independent sample t-tests and one-way ANOVA. Non-normally distributed data were analyzed using the Mann-Whitney U-test. Spearman’s test was utilized for linear correlation analysis. Stepwise regression identified influencing factors, and binary logistic regression was conducted to evaluate their associations with HK progression. Receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic value of factors related to HK.

Results

Identification of DEGs in Transcriptome Sequencing

Transcriptome analysis of renal tissues from sham-operated and UUO7 mice identified 5,219 DEGs, with 2,347 downregulated and 2,872 upregulated in the UUO7 group. Principal Component Analysis (PCA) revealed distinct clustering between the sham and UUO7 groups, underscoring significant transcriptomic alterations (Fig. 1a). Visualization of the DEGs through volcano and heatmaps highlighted the most significantly altered genes (Fig. 1b, c). GSEA pinpointed key pathways, including IL-17, TNF, and PI3K/AKT, which are involved in inflammation and fibrosis (Fig. 1d).

Hub Gene Screening Using WGCNA and Functional Enrichment Analysis

WGCNA identified gene modules significantly associated with the UUO model. Modules with an eigenvalue greater than 0.75 and containing at least 20 genes were selected for further analysis. The turquoise module showed the strongest association with the UUO model, with genes enriched in molecular functions related to cell adhesion, ECM binding, and GTP binding (Fig. 2a–d). KEGG pathway analysis revealed that these genes are significantly involved in TNF, Rap1, and PI3K/AKT signaling pathways, which are critical in the pathogenesis of renal fibrosis (Fig. 2e, f).

Machine Learning-Based Biomarker Screening in HKs of UUO

Machine learning techniques, particularly LASSO regression, were utilized to identify potential biomarkers from 955 key targets. The analysis highlighted six candidate genes, including SPP1, as potential biomarkers for UUO-induced renal fibrosis (Fig. 3a, b). These candidate genes were validated in both human kidney tissues and C57 mouse kidneys using RT-PCR, with SPP1 emerging as a particularly promising biomarker for hydronephrosis-associated renal damage (Fig. 3c, d).

Validation of Spp1’s Diagnostic Significance in HK

To further assess the diagnostic potential of SPP1, its expression was analyzed using the GSE96571 and GSE149915 datasets. ROC curve analysis demonstrated that SPP1 has significant diagnostic value, with an area under the ROC curve (AUC) of 0.718 (95% CI: 0.624–0.812) in GSE96571 and a perfect AUC of 1.000 (95% CI: 1.000–1.000) in GSE149915 (Fig. 3e, f). These results suggest that SPP1 could serve as a reliable biomarker for evaluating the severity of hydronephrosis and predicting the progression of renal fibrosis.

Spp1 Protein Expression in Mouse Serum and Kidney Tissues

Pathological analysis of UUO mouse kidney tissues revealed a progressive increase in renal damage over time. HE staining showed a marked escalation in tubular injury, with scores rising from 0.2 ± 0.12 in normal kidneys to 3.85 ± 0.20 in UUO14 mice, indicating significant epithelial cell damage, luminal occlusion, and necrosis (Fig. 4a, c). Masson’s Trichrome staining illustrated a corresponding increase in fibrosis, with minimal collagen deposition in the Sham group (mean: 1.80 ± 0.96) and extensive fibrosis in UUO14 mice (mean: 23.02 ± 2.61), indicating severe tissue remodeling (Fig. 4b, d).

Simultaneously, SPP1 levels were measured, showing a progressive increase from the lowest levels in the Sham group (mean: 1.80 ± 0.96) to the highest in UUO14 (mean: 23.02 ± 2.61), correlating strongly with the progression of renal injury (Fig. 4e). Immunohistochemical (IHC) analysis confirmed significantly elevated SPP1 protein levels in UUO7 and UUO14 kidney tissues (Fig. 5a). Similarly, IHC detection of neutrophil gelatinase-associated lipocalin (NGAL) demonstrated increased levels of this marker, aligning with heightened SPP1 expression and reinforcing its involvement in kidney damage (Fig. 5b). Quantitative analysis further supported these findings, with significant differences in SPP1 and NGAL expression between UUO groups and sham controls (Fig. 5c, d).

Spp1 Protein Expression in Human Kidney

The diagnostic value of SPP1 in renal injury and fibrosis was assessed using samples from NK, M-HK, and S-HK groups. HE staining revealed a clear progression in tubular injury, with the NK group exhibiting the lowest injury score (mean: 1.03 ± 0.19), followed by a significant increase in the M-HK group (mean: 2.35 ± 0.59), and reaching the highest severity in the S-HK group (mean: 3.13 ± 0.34) (Fig. 6a, b). Masson’s Trichrome staining mirrored this progression, showing minimal collagen deposition in the NK group (mean: 4.51 ± 0.65), a substantial increase in the M-HK group (mean: 13.47 ± 3.38), and the most extensive fibrosis in the S-HK group (mean: 22.31 ± 3.57) (Fig. 6c, d). Critical areas of damage are highlighted with black arrows in the magnified images.

IHC analysis demonstrated that SPP1 was predominantly localized in renal tubules, with significantly elevated expression in HK patients, particularly in the S-HK group (p < 0.001) (Fig. 6e, f). Moreover, SPP1 expression showed a strong positive correlation with both NGAL (Spearman’s ρ = 0.906) and fibronectin (FN) (Spearman’s ρ = 0.862), underscoring its role in the progression of tubular injury and fibrosis in HKs (Fig. 7e, f).

Clinical Biochemical and Pathological Data of HK

Patients’ clinical data revealed that SHK patients exhibited increased levels of cystatin C (Cys-C), Scr, BUN, and CT area-corrected GFR (aGFRsingle) (Table 1) [15] (p < 0.05). Additionally, higher urinary protein levels were observed, including U-RBP, U-TRF, and U-Cr (Table 2). Pathological analyses indicated severe interstitial fibrosis, tubular damage, and elevated interstitial inflammation and collagen deposition in SHK patients (Table 3).

Correlation analysis of renal tubular Spp1 protein levels and clinicopathological features to assess Spp1’s clinical relevance, we correlated its IHC results with various clinical and pathological features (Table 4). Spp1 protein levels in renal tubules showed positive associations with BUN, aGFRsingle, High-Density Lipoprotein Cholesterol, very low-density lipoprotein, and urinary tract infection. Additionally, Spp1 correlated with markers of kidney damage, such as CYC, U-Cr, U-IgG, and U-TRF. Moreover, increased Spp1 expression was positively linked with tubular damage scores, IFTA scores, interstitial inflammation, and collagen deposition, further supporting its utility as a marker of renal tubular damage and fibrosis.

Correlation Analysis and Diagnostic Value Assessment

Binary logistic regression, with stepwise selection due to sample size constraints, identified SPP1 (β = 1.601, p = 0.032) and U-TRF (β = 0.347, p = 0.038) as significant predictors for SHK. The final predictive model was formulated In(p/1 − p) = 3.371 + 0.471 × SPP1 − 1.059 × U-TRF (Table 5). To assess the diagnostic potential of SPP1 and U-TRF for HK, kidneys from the SHK group (n = 20) were used as positive samples, and those from the M-HK group (n = 12) as negative controls to construct an ROC model.

The analysis revealed that SPP1 had an AUC of 0.898 (95% CI: 0.790–1.006, p = 0.0002), with a sensitivity of 85% and specificity of 83.3% at a cutoff value of 16.625. U-TRF demonstrated an even higher AUC of 0.938 (95% CI: 0.858–1.017, p = 0.0001), with 80% sensitivity and 91.7% specificity at a cutoff of 9.295. The combination of SPP1 and U-TRF significantly enhanced diagnostic accuracy, yielding an AUC of 0.975 (95% CI: 0.931–1.019, p = 0.0001), with 90% sensitivity and 100% specificity. These findings indicate that the combined use of these markers offers superior diagnostic performance (Table 6; Fig. 8).

Discussion

Renal fibrosis is a critical pathological feature of CKD, marked by the excessive accumulation of ECM proteins, leading to progressive kidney dysfunction [16, 17]. This study highlights the significant role of Spp1 in the development of renal fibrosis, particularly in the context of hydronephrosis-induced injury. Spp1 has emerged as a crucial mediator in the fibrotic processes within the kidney, influencing multiple signaling pathways and cellular interactions [9, 10, 18]. Our findings demonstrate that Spp1 is not only upregulated in both murine models and human renal tissues affected by hydronephrosis but also closely associated with the activation of key fibrotic and inflammatory pathways, including those mediated by IL-17, TNF, and PI3K/AKT signaling. Importantly, our IHC analysis revealed that Spp1 is predominantly localized to injured proximal tubules (PTs) in human and mouse kidneys (Fig. 6e, f), consistent with its correlation with PT-specific damage markers such as NGAL (Fig. 7f). This spatial specificity aligns with recent single-cell transcriptomic studies identifying Spp1+ tubule cells as a fibrotic subpopulation enriched in PT injury pathways [19, 20]. These findings suggest that PT-derived Spp1 may act as a paracrine signal to recruit fibroblasts and macrophages, amplifying fibrosis in a segment-specific manner.

Spp1 is a multifunctional protein essential for cellular processes such as migration, adhesion, and survival, all integral to tissue repair and fibrosis [21, 22]. In renal fibrosis, Spp1 interacts with integrins and CD44 receptors on the cell surface, promoting the recruitment and retention of inflammatory cells, particularly macrophages, at injury sites [8, 23, 24]. This interaction not only amplifies the inflammatory response but also drives the transformation of fibroblasts into myofibroblasts – key cells responsible for ECM production, leading to collagen and other fibrotic material deposition. This process is further enhanced by TGF-β, a potent cytokine closely linked to Spp1 activity [25]. Prior work has demonstrated that Spp1 potentiates TGFβ/Smad3 signaling to drive fibroblast-to-myofibroblast transition [26], and our observed correlation between Spp1 and FN (ρ = 0.862; Fig. 7e) supports this synergistic relationship. Future studies should explore whether Spp1 inhibition disrupts TGFβ-driven fibrogenesis. TGF-β is known to accelerate fibrosis by promoting fibroblast differentiation into myofibroblasts, increasing ECM production, and inhibiting its degradation [27, 28].

The upregulation of Spp1 observed in both UUO models and human kidney tissue underscores its central role in these fibrotic processes. The elevated levels of Spp1 were strongly correlated with increased structural and functional kidney damage, highlighting its potential as a diagnostic biomarker for renal fibrosis. This finding aligns with previous studies demonstrating that higher Spp1 levels are associated with more severe disease states in conditions like HKs, diabetic nephropathy, lupus nephritis, and acute kidney injury [9, 20, 29–33].

Notably, Spp1’s role extends beyond obstruction-induced fibrosis. Emerging evidence positions it as a convergent mediator across CKD In diabetic nephropathy, Spp1 drives fibrosis via CD44/NF-κB signaling independent of hyperglycemic injury [34]. In hypertensive nephropathy, Spp1+ tubule cells correlate with fibrosis severity in mineralocorticoid antagonist studies [19]. Circulating Spp1-enriched extracellular vesicles exacerbate vascular calcification in CKD [18], suggesting systemic effects. These injury-agnostic roles highlight Spp1’s potential as a broad therapeutic target, though its upstream regulators may vary by disease context.

Given the pivotal role of Spp1 in renal fibrosis, targeting its activity presents a promising therapeutic strategy. Inhibiting Spp1 or its downstream signaling pathways could potentially mitigate fibrosis and alleviate associated renal damage. This approach is particularly appealing due to Spp1's influence on not only fibrosis but also inflammation and cellular apoptosis.

Recent advances in the development of Spp1 inhibitors and other therapeutic agents targeting Spp1-related pathways offer promising avenues for treating renal fibrosis. Preclinical studies have shown these agents’ efficacy in reducing fibrosis and improving renal function, highlighting their clinical translation potential [35]. Combining Spp1-targeted therapies with existing treatments, such as angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers, could enhance therapeutic efficacy and provide a synergistic effect in reducing fibrosis and improving renal outcomes [36].

Using advanced genomic and proteomic techniques, such as transcriptome sequencing and machine learning-based biomarker screening, our study has provided a comprehensive understanding of the gene expression changes associated with Spp1 upregulation in renal fibrosis. These approaches enhance the diagnostic potential of Spp1, facilitating early detection and effective monitoring of renal disease. The ROC analysis further confirms the diagnostic accuracy of Spp1, solidifying its role as a reliable indicator of renal disease severity and progression. We also have identified key signaling pathways, including TGF-β, TNF, Rapp1, JAK/ATAT, and PI3K/AKT, known to drive the inflammatory and fibrotic processes characteristic of CKD [25, 32, 37]. Integrating these findings with clinical data and pathological insights further strengthens the case for Spp1 as a central player in renal fibrosis. The positive correlation between Spp1 levels and markers of renal injury and fibrosis, such as NGAL and FN, provides compelling evidence of its involvement in both the initiation and progression of renal fibrosis. This makes Spp1 a promising target for therapeutic intervention aimed at halting or reversing fibrosis.

Our study’s findings regarding the correlation between Spp1 levels and clinical biochemistry and pathology provide further evidence of its significance in renal fibrosis. Elevated Spp1 levels were associated with higher levels of serum markers such as Cys-C, Scr, and BUN, all indicators of impaired kidney function. Additionally, the observed increase in urinary proteins, including U-RBP, U-TRF, and U-Cr, in patients with severe hydronephrosis corresponds with elevated Spp1 levels, suggesting its involvement in renal damage and fibrosis. Pathological data from SHK patients revealed severe interstitial fibrosis, tubular damage, interstitial inflammation, and collagen deposition, all positively correlated with changes in Spp1 protein expression. The ROC curve analysis, demonstrating high AUC values for Spp1 and U-TRF, further validates their diagnostic accuracy. These findings suggest that the combined assessment of Spp1 and U-TRF could improve the early detection and monitoring of hydronephrosis-associated renal fibrosis. Spp1’s use as a marker of renal tubular damage and fibrosis highlights its clinical utility for early detection and monitoring of renal disease progression.

While our study provides compelling evidence of Spp1’s role in renal fibrosis, further research is needed to fully elucidate the underlying mechanisms and validate these findings in larger and more diverse patient cohorts. Longitudinal studies involving patients at different stages of kidney disease, as well as those with varying underlying causes of fibrosis, will be essential to determine Spp1’s broader applicability as a biomarker and therapeutic target. Future research should focus on exploring Spp1-targeted therapies in renal fibrosis, including developing novel inhibitors and investigating combination therapies that address multiple aspects of the fibrotic process. For example, combining Spp1 inhibition with therapies that reduce ECM deposition or directly inhibit other cytokines involved in fibrosis progression could offer a more comprehensive treatment approach. Additionally, exploring Spp1 as a therapeutic target in other kidney diseases, such as polycystic kidney disease or glomerulonephritis, could expand its clinical application scope.

Conclusion

This study reaffirms the critical role of Spp1 in the pathogenesis of renal fibrosis and highlights its potential as both a diagnostic biomarker and a therapeutic target. The findings provide a strong foundation for future research aimed at developing targeted therapies to mitigate the progression of CKD. The integration of Spp1-targeted treatments with existing therapeutic strategies offers a promising approach to managing renal fibrosis, with the potential to improve patient outcomes and reduce the burden of CKD. As research into Spp1 continues to evolve, it is likely that new therapeutic strategies will emerge, offering hope for patients suffering from a wide range of fibrotic conditions.

Acknowledgment

The authors would like to express our sincere gratitude to Professor Zhang Shangrong from Fuyang Normal University for his valuable technical guidance throughout this study.

Statement of Ethics

This retrospective study utilized anonymized human tissue data with no individual interventions or potential risks involved. All animal experiments were approved by the Anhui Medical University Animal Ethics Committee (Approval No. 20241644). The analysis of anonymized human data was reviewed and approved by the Anhui Medical University Human Ethics Committee (Ethics Approval No. 83244685). Written informed consent was waived by the Ethics Committee for the following 1.Retrospective design using fully anonymized data2.Absence of sensitive information or participant interaction3.No foreseeable risks to individuals

The study strictly adhered to the World Medical Association Declaration of Helsinki and national ethical standards for biomedical research.

Conflict of Interest Statement

No potential conflict of interest was reported by the authors.

Funding Sources

This work was supported by the Health Commission of Anhui Province Foundation (No. AHWJ2023A30219); the Higher Education Institution Scientific Research Projects of Anhui Province (2024AH050758), and support from the Health Commission of Fuyang City (No. FY2023-034).

Author Contributions

Xiao Wang and Wei-xiao Li designed the research. Xiao Wang and Guang Chen performed the experiments and Jie-Hao Zhou and Ji-Dong Chen analyzed the data. Xiao Wang, Hui Li, and Wei-Min Shan wrote the manuscript.