Upregulation of circ-0069561 promotes diabetic kidney disease progression

Upregulation of circ-0069561 promotes diabetic kidney disease progression | 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 Upregulation of circ-0069561 promotes diabetic kidney disease progression Chaoyi Chen, Xinran Liu, Sai Zhu, Xueqi Liu, Yukai Wang, Yu Ma, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5465308/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 Circular RNAs (circRNAs) are non-coding RNAs that play a critical role in disease etiology. But the role of circRNAs in diabetic kidney disease (DKD) remains unknown. We performed whole high-throughput RNA sequencing (RNA-seq) of kidney tissues from clinical DKD patients and controls. The top 10 up-regulated circular RNAs were selected by RT-PCR validation, and the findings showed a substantial increase in the expression level of circ-0069561. RT-PCR and fluorescent in situ hybridization (FISH) confirmed that circ-0069561 expression increased both renal tissues of type 2 diabetic mice and DKD patients, with a glomerulus-specific location. Circ-0069561 expression in kidney tissue was significantly correlated with UACR, glomerular lesions, arteriolar hyalinosis and arteriosclerosis. The expression level of circ-0069561 and plasma albumin (ALB) level were independent risk factors for macroalbuminuria. Circ-0069561 demonstrated a strong diagnostic value in major proteinuria, according to the ROC curves (area under the curve = 0.889). CircRNA-miRNA-mRNA network indicated that the pathophysiology of DKD may involve ferroptosis. Podocyte damage and ferroptosis caused by high glucose were attenuated by silencing circ-0069561, according to in vitro examinations. Together, the findings suggest that circ-0069561 may influence the progression of DKD by causing ferroptosis of podocytes. The findings of this study provide new insights into the cause and progression of DKD. CircRNAs Diabetic kidney disease Transcriptome sequencing Ferroptosis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction The diabetic kidney disease (DKD) is one of the most serious microvascular chronic consequences in diabetic patients[ 1 ]. Diabetes mellitus (DM) is an international health crisis. According to the prediction of the World Health Organization, diabetes mellitus will affect about 642 million people globally by 2040. Diabetes can involve all important organs in the body, including central nervous complications, peripheral neuropathy, renal disease, cardiovascular disease, various infections, etc., seriously damaging the quality of life of patients[ 2 , 3 ]. DM is classified into two types: type 1 (inadequate the production of insulin from pancreatic β-cells) and type 2 (insulin resistance). Around 40% of DM patients progress to DKD, and 30–50% of these cases attributed to T2D[ 4 ]. DKD is the main cause of dialysis treatment for end-stage renal disease (ESRD), resulting in significant economic burdens[ 5 ]. The molecular pathophysiology of DKD remains unknown. Thus, it's critical to investigate novel treatment targets and gain a deeper understanding of the molecular mechanism behind DKD. In eukaryotes, circular RNA (circRNA) is an ubiquitous type of noncoding RNA [ 6 ]. CircRNAs exhibit greater stability than linear non-coding RNAs because of their covalent closed-loop structure[ 7 ]. Circ_104075 may be used as a biomarker for identifying hepatocellular cancer[ 8 ]. Researchers revealed that circRNAs play a role in the onset and progress of different diseases, including metabolic illnesses like diabetes[ 9 , 10 ]. Our earlier study discovered that the absence of circ-0000953 in DM caused podocyte damage and defective autophagy[ 11 ]. Peng et al. discovered that renal fibrosis in DM is a result of down-regulation of circRNA_010383[ 12 ]. CircRNA is intimately linked to the progression of numerous disease. The mechanisms of DKD are complex. Medical researchers have recently become interested in ferroptosis[ 13 ]. Ferroptosis is a new kind of planned cell death that requires iron overload and ROS production, in relative to apoptosis and necrosis[ 14 ]. Recent evidence suggests that ferroptosis plays a significant role in the development of DKD[ 15 , 16 ]. In this research, whole high-throughput RNA sequencing (RNA-seq) was utilized to explore circRNA expression profiles, and real-time PCR (RT-PCR) analysis was used to select circ-0069561, which had significantly higher expression levels. The clinical data analysis showed that circ-0069561 has a good value in the detection of massive proteinuria. The pathophysiology of DKD may involve ferroptosis, according to the circRNA-miRNA-mRNA network. Ferroptosis and podocyte damage brought on by elevated glucose can be lessened by silencing circ-0069561. This work suggests that circ-0069561 could be a novel therapeutic target and diagnostic biomarker to preventing DM development. Materials and methods Clinical specimens and collection Biopsy specimens from the kidneys of four people diagnosed with DKD and healthy kidney tissue samples adjacent to tumours from four patients who underwent nephrectomy for renal tumours were collected for RNA-seq and analysis of genomics. From January 2022 to June 2023, 46 volunteers who had received a kidney biopsy diagnosis of DKD were gathered from Anhui Medical University's First Affiliated Hospital. One criterion for the advancement of UACR was a urine albumin/creatinine ratio (UACR) of ≥ 300 mg/g. Diabetic nephropathy patients were further separated into two groups: DKD1 patients (those with microalbuminuria or negative protein urine) and DKD2 patients (those with macroalbuminuria) with UACR ≥ 300 mg/g. Renal biopsy was also used to harvest kidney tissue from the minimal change disease (MCD) group. Renal tissues from the normal control (NC) group were removed from sections of adjacent cancerous tissue following urological surgery. All specimens were verified by histopathology. RNA-seq results were confirmed with real-time PCR (RT-PCR) in 46 kidney tissues from DKD patients and 12 healthy kidney tissues. Consent for this study was given by the First Affiliated Hospital's Research Ethics Committee of Anhui Medical University (NO.2022311), which was executed in accordance with the Helsinki Declaration. Everyone who participated signed a consent form. Chemicals and antibodies In this research, the following chemicals and antibodies were used: Lipofectamine RNAiMAX Reagent (Invitrogen Life Technologies, 13,778 − 030) was used for transfection techniques, closely adhering to the manufacturer's recommendations. Proteintech's 66009-1-Ig anti-β-actin antibody, 60004-1-Ig anti-GAPDH antibody, Abcam's ab267377 anti-WT-1 antibody, Abcam's ab181143 anti-podocin antibody, HUABIO's ET7111-43 anti-ACSL4 antibody, and HUABIO's ET1706-45 anti-GPX4 antibody are among the antibodies. Biochemical Assays: Superoxide dismutase (SOD), glutathione (GSH), and malondialdehyde (MDA) were measured using assay kits purchased from Jiancheng (Nanjing, China). Iron content was quantified using an assay kit from Leagene (Beijing, China). The DHE were achieved in accordance with the kits provided by Beyotime (Jiangsu, China). CircRNA sequencing RNA-seq was performed by Kang Cheng Bio (Shanghai, China). The total RNA samples were subjected to oligo dT enrichment (rRNA removal), after which the KAPA Stranded RNA-Seq Library Prep Kit (Illumina) was employed to construct the libraries. Further data mining analyses were done through the Kang Cheng Biologicals program. Inclusion and exclusion criteria The criteria for including participants in DM group were established as follows[ 17 ]: Clinically and pathologically diagnosed type 2 diabetes, aged 18–80 years. Individuals with type 1 diabetes, secondary diabetes, and other diabetes types were not considered eligible; Patients with diabetic ketoacidosis were excluded; Patients with severe infection, pregnancy, other endocrine diseases, connective tissue diseases, malignant tumors, myocardial infarction, and severe liver dysfunction were excluded. This study included two control groups: MCD and NC. In total, the study comprised 73 participants (NC:MCD:DKD1:DKD2 = 12:15:10:36). Pathological examination of renal tissue utilized staining techniques and transmission electron microscopy (TEM) Solarbio Corporation (Beijing, China) provided the following staining kits: haematoxylin and eosin (H&E), periodate-schiff (PAS), Masson, and periodic acid-silver methenamine (PASM). Tissue slices were fixed in formalin, embedded in paraffin, and stained with H&E, PAS, Masson, and PASM according to the manufacturer's instructions. Renal cortical tissues were fixed in 2.5% glutaraldehyde, dried and embedded, and examined under a transmission electron microscope. Type 2 diabetes mouse model The study utilized a db/db mouse model of type 2 diabetes. Male db/db mice and db/m control mice aged 6 weeks were purchased from GemPharmatech (Nanjing, China). These mice were housed in a specific-pathogen-free (SPF) environment with a stable temperature of 22°C ± 2°C and a humidity level of 60%, following a 12-hour light-dark cycle. Refer to our previous research[ 18 ], the db/m control mice (n = 6) and db/db mice were maintained until 8 weeks (n = 6), 12 weeks (n = 6), 16 weeks (n = 5), and 20 weeks (n = 6), the mice were randomly placed in cages with 2–3 mice per cage. There was no loss of mice during feeding. For each mouse, three different researchers were involved, and the first researcher was responsible for random grouping and feeding. Two researchers were left to measure and evaluate the results. All animals were treated in compliance with the principles of the Declaration of Helsinki and the ARRIVE recommendations. This research was carried out in accordance with the Declaration of Helsinki and approved by Anhui Medical University's Animal Research Ethics Committee (NO.20220759). Immunohistochemical staining After deparaffinizing kidney paraffin sections, they underwent high-pressure antigen repair using citric acid solution, hydrogen peroxide incubation for 20 minutes, goat serum blocking for 40 minutes, goat serum removal, primary antibody addition, and overnight incubation at 4°C in a humidified refrigerator. The sections were then cleaned and incubated with the secondary antibody for 30 minutes at 37°C. The color development of 3,3'-diaminobenzidine (DAB) was carried out. Hematoxylin was used to stain the cell nuclei. Use a Leica microscope (Bensheim, Germany) to examine the sections. Utilize ImageJ software (NIH, Bethesda, MD, USA) to analyze and quantify the staining. Cell culture The Institute of Basic Medical Sciences at the Chinese Academy of Medical Sciences provided the conditionally immortalized mouse podocytes (MPC5). These cells were maintained at 33°C in RPMI 1640 supplemented with 20 U/mL of mouse recombinant interferon-g (IFN-g) and 10% fetal bovine serum. The podocytes were maintained at 37°C for seven days without IFN-γ under non-permissive conditions in order to induce differentiation. Professor Lan HY of the Chinese University of Hong Kong kindly provided mouse tubular epithelial cells (mTECs). Vascular endothelial cells (VECs) and mouse mesangial cells (SV40) were obtained from the Chinese Academy of Sciences Cell Bank and cultivated in DMEM supplemented with 5% serum. MPC5 cells were transfected with siRNA or an overexpression plasmid (Hanbio Biotechnology, China) using Lipofectamine RNAiMAX Reagent (Invitrogen) in accordance with the manufacturer's recommendations. Table S1 lists the siRNA sequences that were employed in this investigation. A negative scrambled siRNA or plasmid (provided by Hanbio Biotechnology, China) was used as the control. The diluted siRNA or plasmid was combined with Lipofectamine RNAiMAX and incubated for 20 minutes prior to being introduced to the cells in OPTI-MEM medium. Following a six-hour incubation period, the medium was replaced with a complete medium. The treatments employed in this study included high glucose (HG) (30 mM glucose), mannitol, and moderate glucose (MG) (24.5 mM mannitol + 5.5 mM glucose), as well as normal glucose (NG) (5.5 mM glucose). Fluorescence in situ hybridization (FISH) For the hybridization process, circ-0069561-specific fluorescent dye-labeled nucleic acid probes were employed. First, 4% paraformaldehyde was used to fix the samples, and then hydrochloric alcohol was used to wash them. After ten minutes of air drying at 46°C, they were put through a five-minute gradient ethanol dehydration process. After that, 1 µL of the probe was mixed with 10 µL of the previously made hybridization buffer. For one and a half hours, the hybridization was carried out in a sealed chamber with washing buffer at 46°C in the dark. The slides were then incubated for a further half hour at 48°C once the temperature was raised to that level. Following hybridization, distilled water was used to rinse the slides and an anti-fading solution was used. The Leica microscope (Bensheim, Germany) was used to investigate the location of circ-0069561 expression. Table S2 contains a list of the probe sequences that were employed. Real-Time PCR analysis (RT-PCR) Total RNA was isolated from human paraffin-embedded tissue sections using the Paraffin Tissue Total RNA Kit (Simgen, Hangzhou, China). Following the manufacturer's instructions, RNA extraction was carried out using Trizol (Invitrogen) for cellular or renal samples. Mean ± SEM was utilized to display the results, with β-actin serving as an internal control for normalization. Table S3 lists all of the primer sequences used in this investigation. Western Blotting Cell and kidney tissue samples were lysed using ice-cold radio-immunoprecipitation assay (RIPA) buffer supplemented with protease and phosphatase inhibitors (Beyotime, China). Following denaturation, proteins were separated using SDS-PAGE and transferred to a membrane for further immunoblotting using specific antibodies. The protein bands were identified using an Enhanced ECL Chemiluminescent Substrate Kit (Yeasen, 36222ES76), and images were captured using the Amersham Imager 600 System. KEGG pathway enrichment analysis and construction of a circRNA-miRNA-mRNA network We constructed a circRNA-miRNA-mRNA network to study their interactions. Moreover, the FerrDb database was used to identify mRNAs associated with ferroptosis. Ferroptosis-associated mRNAs and differentially expressed mRNAs intersected in the ceRNA network for KEGG pathway analysis of ferroptosis-associated DEGs. CircRNA-miRNA-ferroptosis-associated mRNA networks were then constructed using Cytoscape software (v3.7.1). Statistical analyses Each experiment was carried out at least three times. For statistical analysis, R (version 4.2.1) and SPSS (version 26.0) were utilized. First, the normality of the data was evaluated using the Shapiro-Wilk test. When describing quantitative data with a normal distribution, the mean ± SD is utilized. One-way analysis of variance was employed for comparisons between several groups, whereas the t-test was employed for comparisons between two groups. Group variances and multiple comparisons were evaluated using Tamhane's T2 and LSD tests, respectively, and Levene's test for equality of variances. When displaying variables that are not normally distributed, interquartile ranges and medians are utilized. The Kruskal–Wallis H-test and the Mann–Whitney U-test were used to assess differences between two and three groups, respectively. Pearson's and Spearman's correlation coefficients were used to assess the normality of normally and non-normally distributed variables, respectively. Covariates were initially evaluated using univariate regression analysis, and then multivariate logistic regression analysis, in order to develop prediction models. The models were evaluated using receiver operating characteristic (ROC) curves. Graphing was done using GraphPad Prism (version 8). P < 0.05 was set as the significant level. Results Expression profile of circRNA in DKD Four patients with diabetic nephropathy and four paracancerous tissues were used for RNA sequencing, with the objective of identifying functional circRNAs involved in the progression of the disease. Fig. 1A and Fig. 1B illustrate the results of the heatmaps and scatter plots, which demonstrate that a total of 2,580 circRNAs were identified, with notable differences observed between the DKD and NC groups. The length and reverse shear reads of the detected circRNAs are presented in Fig. 1C and D. Volcano plots demonstrated that, using log2FC absolute value ≥0.585 and P value <0.05 as the cut-off value, 21 circRNAs were upregulated in diabetic nephropathic tissues, and 52 were downregulated in diabetic nephropathic tissues (Fig. 1E). Of the 73 identified circRNAs, four were novel discoveries, while 69 were previously reported (Fig. 1F). These circRNAs were predominantly distributed across autosomes, with two downregulated circRNAs originating from sex chromosomes (Fig. 1G). Screening for Differentially Expressed circRNAs The baseline characteristics of 46 patients with DKD (including 10 patients with microproteinuria DKD and 36 patients with massive proteinuria DKD), 15 patients with MCD, and 12 patients with urological tumours postoperatively are shown in Table 1 . There were no statistically significant differences between the groups in terms of age or gender distribution (P > 0.05). Additionally, as Table 2 illustrates, DKD patients with UACR ≥300 mg/g did not significantly differ from DKD patients with UACR <300 mg/g in terms of DM, systolic blood pressure (SBP), diastolic blood pressure (DBP), blood urea nitrogen (BUN), serum creatinine (Scr), estimated glomerular filtration rate (eGFR), fasting blood glucose (FBG), glycosylated hemoglobin (HbAc1), triglyceride (TG), C-reactive protein (CRP), and urinary-β2-microglobulin (U-β2-MG). Total cholesterol (TC), urinary creatinine (UACR), urinary transferrin (U-TRF), urinary immunoglobulin G (uIgG) and urinary-α1-microglobulin (U-α1-MG) were increased in the DKD2 group compared to the DKD1 group. And albumin (ALB) was decreased in the DKD2 group compared to the DKD1 group. The differences were statistically significant (P < 0.05). We performed HE, PAS, Masson and PASM staining on the sections of each group and observed the characteristic changes of DKD under electron microscope. Representative pathological pictures of each group are shown in Fig. 2A-E. A comparative examination of DKD individuals' pathological data is presented in Table 3. The glomerular lesions, arteriolar hyalinosis and arteriosclerosis of DKD2 group were higher than that of DKD1 (P 0.05). Table S4 lists the top 10 circRNAs that are up-regulated. As the GC content and Tm value of the sequences in the vicinity of the chr1:245180543-245180628:+ and circ-0057338 cyclisation sites were low and did not meet the requirements of the primer design, we opted to employ RT-PCR in 46 DKD patients and 12 NC controls to verify the expression of the remaining 8 upregulated circRNAs. As illustrated in Fig. 2F, we identified circ-0069561, which exhibited notable distinctions between the DKD and NC groups. To this end, we consulted the circBase database (http://www.circbase.org). We obtained that circ-0069561 is located on chromosome 4:40,892,380-40,947,087. The genomic structure indicated that circ-0069561 was generated by closing shear cyclisation of four exons (exons 7, 8, 9 and 10) of the APBB2 locus (Fig. 2G). Further evidence was provided by Sanger sequencing after PCR, which demonstrated the cyclic structure of circ-0069561. The GA of the cyclisation site is depicted in Fig. 2H. Circ-0069561 expression is elevated in kidney of type 2 diabetic mice and DKD patients First, we investigated the expression of circ-0069561 using db/db type 2 diabetic mice. The the glomerular basement membrane thickened, the mesangial matrix expanded, and the diabetic mice's blood glucose levels were much higher, according to PAS staining (Fig. 3A-B). In db/db type 2 diabetic mice, we confirmed the expression of circ-0069561 by RT-PCR at various weekly ages. We discovered that circ-0069561 expression was markedly increased (Fig. 3C). Furthermore, we validated that circ-0069561 expression was greatly enhanced in db/db type 2 diabetic mice and was mostly localized in the glomerulus by performing FISH on kidney tissue samples from these mice (Fig. 3E). To confirm the expression of circ-0069561 in renal tissues, we applied RT-PCR and FISH in renal tissue samples from 46 patients with DKD (including 10 patients with microproteinuria DKD and 36 patients with massive proteinuria DKD), 15 patients with MCD, and 12 patients with urological tumours postoperatively to circ-0069561 expression was validated, and the results were similar to those of the in vivo experiments (Fig. 3D-F). Next, we focused on the role of circ-0069561 in DKD disease. Correlation between circ-0069561 expression and clinicopathology of DKD patients We used RT-PCR to measure the expression level of circ-0069561 in kidney tissue samples from DKD patients and correlated the expression level of hsa_circRNA_0069561 with clinicopathological markers in order to assess the clinical importance of circ-0069561 expression in DKD. The results showed ( Table 4 ) that the expression level of circ-0069561 was positively correlated with serum BUN level, and urine UACR level. Circ-0069561 expression was positively linked with pathological data such as glomerular lesions, interstitial inflammation, arteriolar hyalinosis, and arteriosclerosis (p < 0.05). Regression analysis and ROC curve Binary logistic regression was employed using UACR ≥300 mg/g as the grouping criterion[17]. Clinical and pathological data were the initial subjects of univariate regression analysis. A number of indicators were then used in multivariate regression analysis (P < 0.05). The levels of circ-0069561 (β = 0.956, P < 0.05) and ALB (β = -0.261, P < 0.05) were determined to be possible risk factors using multivariate regression analysis ( Table 5 ). The following prediction model was produced from the results: In (p/1-p) = 0.956 × circ-0069561 - 0.261 × ALB + 8.179. To further explore the diagnostic significance of circ-0069561 in DKD with considerable albuminuria, we created the ROC diagnostic model by considering the kidneys in the DKD2 group as positive samples (n=36) and the kidneys in the DKD1 group as negative samples (n=10) According to the findings, the AUC (0.95 CI) was 0.889 (0.790-0.988). Fig. 4A and Table S5 both show the ROC curve. Function of mRNAs in the ceRNA network in DKD and construction of circRNA-miRNA-ferroptosis-related mRNA network Circ-0069561's circRNA-miRNA-mRNA network was built. FerrDb is a publicly accessible database that provides a comprehensive overview of genes associated with ferroptosis. This includes genes that induce, suppress, or regulate ferroptosis, as well as genes that act as markers for ferroptosis. The ferroptosis-associated mRNAs were obtained by downloading the ferroptosis dataset and overlapping it with the differentially expressed mRNAs in the ceRNA network. This resulted in the identification of 177 DEGs associated with ferroptosis, as illustrated in a shared Venn diagram (Fig. 4B). A circRNA-miRNA-ferroptosis-related mRNA network was built. The network prediction (Fig. 4C) revealed that some genes associated with ferroptosis, including ACSL4, ALOX12, ALOX15, and others, were closely linked to the biological function of circ0069561. The ferroptosis-associated DEGs were subjected to KEGG pathway analysis in order to investigate the role of 177 mRNAs in the ceRNA network. The KEGG pathway analysis in Table S6 and Fig. 4D indicated that ferroptosis may be associated with the pathogenesis of DKD. Our findings revealed that in diabetic mice, podocyte mitochondria exhibited contraction, an increase in mitochondrial membrane density, and alterations resulting from ferroptosis-induced cell death, as observed through transmission electron microscopy (Fig. 4E). Furthermore, we found that diabetic mice had higher expression levels of ACSL4 and lower expression levels of GPX4 (Fig. 4F-G). The results of the in vivo investigations suggest that ferroptosis may contribute to the pathogenesis of DKD. Significant correlation between circ-0069561 expression levels and levels of podocyte injury and ferroptosis in DKD group To learn more about circ-0069561's function in DKD, we applied immunohistochemistry to validate the expression of markers of podocyte injury and key proteins of ferroptosis in renal tissues from 46 patients with DKD (including 10 patients with microproteinuria DKD and 36 patients with massive proteinuria DKD), 15 patients with MCD, and 12 patients with urological tumours postoperatively. Immunohistochemical findings showed that the glomerulus of DKD patients had considerably lower levels of WT1 and podocin protein than those of the NC and MCD groups; DKD patients with extensive proteinuria had the lowest expression levels (Fig. 5A). The results in Fig. 5B showed a significant correlation between circ-0069561 expression levels and the level of podocyte injury in the DKD group with massive proteinuria. In contrast, the glomerulus of DKD patients showed a significantly higher level of ACSL4 protein and a significantly lower level of GPX4 protein when compared to the NC and MCD groups. The expression alterations were especially noticeable in DKD patients with massive proteinuria (Fig. 5C). Ferroptosis levels and circ-0069561 expression levels had a significant relationship in the mass proteinuria DKD group, according to the results in Fig. 5D. Therefore, we speculated that circ-0069561 may contribute to the development of DKD by inducing ferroptosis in podocytes. Silencing circRNA-0069561 attenuates high glucose-induced podocyte damage and ferroptosis The expression level of circ-0069561 was verified in high glucose-induced mTECs, VECs, MPC5, and SV40, respectively, and it was found that circ-0069561 was significantly enriched in podocytes (Fig. 6A). To further elucidate its function, we constructed an in vitro model of podocyte circ-0069561 knockdown (Fig. 6B-C). The knockdown of circ-0069561 was observed to restore the loss of the podocyte markers WT-1 and podocin that was induced by high glucose (Fig. 6D). Additionally, it was shown that circ-0069561 knockdown prevented the up-regulation of ACSL4 in podocytes caused by high hyperglycemia and restored the down-regulation of GPX4 in podocytes caused by high glucose (Fig. 6E). To further elucidate the impact of circ-0069561 knockdown on high glucose-induced iron-dependent cell death in podocytes, we examined the levels of Fe²⁺, MDA, GSH, and SOD in each group. Knocking down circ-0069561 reduced Fe²⁺ and MDA buildup in high glucose-induced podocytes while improving GSH and SOD downregulation (Fig. 6F). DHE staining revealed that the knockdown of circ-0069561 alleviated the accumulation of ROS in high glucose-induced podocytes (Fig. 6G). In conclusion, the results demonstrate that the knockdown of circ-0069561 mitigates high glucose-induced podocyte injury and ferroptosis. Discussion Chronic kidney disease (CKD) is an important and prevalent complication in patients with T2D[ 19 ] and has a significant impact on the global burden[ 20 ]. CircRNAs are novel non-coding RNA molecules that have received increasing attention[ 21 ]. CircRNAs have been identified with the beginning and progression of kidney disease[ 22 ]. In this study, we employed RNA-seq to look for circRNAs that were expressed differently in renal tissues from DKD and NC. Subsequently, circ-0069561, which exhibited markedly altered expression levels, was subjected to screening. Circ-0069561 expression levels correlate with DKD disease severity and proteinuria. Furthermore, the knockdown of circ-0069561 was observed to mitigate high glucose-induced podocyte damage and ferroptosis. Our findings indicate that circ-0069561 may toward the progress of DKD by inducing ferroptosis in podocytes. This implies that circ-0069561 might be a viable treatment option for DKD, which would have important ramifications for the clinical diagnosis and treatment of DKD. Firstly, we explored the expression profile of circRNAs in renal tissues of patients with type 2 diabetic nephropathy by RNA-seq and screened for the significantly up-regulated circ-0069561. According to the findings of numerous studies, circRNAs may be used as new biomarkers for cancer and other human disorders[ 23 , 24 ] and heart disease[ 25 ]. The function of circRNAs as biomarkers in renal disease has been attempted to be clarified in the past few years. Cao et al. discovered a correlation between the degree of renal fibrosis and urinary exosomal circ_0036649 expression[ 26 ]. Another study analyzed RNA-seq in the IMN and HC groups and found that An novel diagnostic biomarker for idiopathic membranous nephropathy was urine exosomal circ_0001250[ 27 ]. A total of 2,580 circRNAs were identified by RNA-seq in this study. Using log2FC absolute value ≥ 0.585 and P-value < 0.05 as the thresholds, 21 circRNAs were up-regulated in diabetic nephropathy tissues and 52 were down-regulated in diabetic nephropathy tissues. 10 up-regulated circRNAs were chosen for qRT-PCR validation in 46 DKD patients with 12 NC kidney tissues, and the results were in high agreement with the RNA-seq data, which validated the RNA-Seq results' Reliability. Meanwhile, we identified circ-0069561, which showed significant difference between DKD and NC groups. To this end, we consulted the circBase database ( http://www.circbase.org ). We obtained that circ-0069561 is located on chromosome 4:40,892,380 − 40,947,087. The genomic structure indicated that circ-0069561 was generated by closing shear cyclisation of four exons (exons 7, 8, 9 and 10) of the APBB2 locus. Further evidence was provided by Sanger sequencing after PCR, which demonstrated the cyclic structure of circ-0069561. The current investigation found that both diabetic mouse models and DKD patients have increased expression of circ-0069561. A correlation analysis of clinical trials demonstrated a positive correlation between the expression of circ-0069561 in DKD patients and UACR levels. It is established that a high level of proteinuria represents a significant clinical risk factor for a rapid decline in estimated eGFR and can be used to predict the progress of DKD[ 28 ]. Megumi Oshima et al. found that STING activation causes proteinuria, which assists with the development and progress of DKD[ 29 ]. We used multiple regression analysis to confirm the clinical significance of circ-0069561 in DKD and discovered that it was an independent risk factor for excessive albuminuria in DKD. The ROC curves demonstrated that circ-0069561 had a high detection value for massive proteinuria. Therefore, we conclude circ-0069561 that it is associated with the severity of DKD disease and proteinuria. Ferroptosis disease's significant significance in DKD was examined in the present study. Ferroptosis is an innovative type of controlled cell death[ 14 ]. Yi-Chun Tsai, et al. used RNA-seq to identify ferroptosis as an important pathophysiological mechanism in early DKD[ 15 ]. Another study found that tRF3-IleAAT inhibited ferroptosis in diabetic kidney disease mice[ 16 ]. Ferroptosis may be a key factor in the development of DKD, according to mounting data. We built a circRNA-miRNA-ferroptosis-related mRNA network in this research and discovered that the biological activity of circ-0069561 was tightly linked to several ferroptosis-related genes, including ACSL4, ALOX12, ALOX15, etc. The KEGG pathway investigation suggests that ferroptosis may be involved in the pathophysiology of DKD. Ferroptosis may be linked to the pathophysiology of DKD, as our work revealed elevated ferroptosis levels in diabetic mice. Subsequently, we investigated the relationship between circ-0069561 expression levels and the extent of podocyte damage and ferroptosis in patients with DKD. Podocytes are terminally differentiated cells that are unable to proliferate, and podocyte dysfunction in DKD results in proteinuria[ 30 ]. We discovered a strong relationship between the degree of podocyte damage in DKD patients and the expression levels of circ-0069561. The lipid metabolism-related gene ACSL4 is a key driver gene for ferroptosis[ 31 ]. Lipid oxidation is efficiently inhibited by GPX4, an antioxidant enzyme and structural protein. It has been found to be a vital ferroptosis regulator that influences lipid and amino acid metabolism[ 32 ]. Ferroptosis was linked to STZ-induced kidney damage in type 1 diabetic mice and db/db animals[ 33 ]. Kim et al. discovered that kidney biopsy samples from diabetic individuals had considerably lower expression levels of SLC7A11 and GPX4[ 34 ]. High fructose also induces ferroptosis in podocytes, ultimately leading to glomerular injury[ 35 ]. According of Zhang et al., reducing ferroptosis could stop podocyte damage brought on by elevated glucose[ 36 ]. Ferroptosis reduction may therefore be a therapy option for DKD, as there is mounting evidence that ferroptosis contributes to the development of DKD[ 37 ]. Ferroptosis levels in DKD patients were shown to be significantly correlated with circ-0069561 expression levels in this investigation. Furthermore, in vitro experiments demonstrated that circ-0069561 was significantly enriched in podocytes. To further elucidate its function, we constructed an in vitro model of podocyte circ-0069561 knockdown, and the results demonstrated that knockdown of circ-0069561 attenuated high glucose-induced podocyte injury and ferroptosis. Therefore, we speculated that circ-0069561 may contribute to the development of DKD by inducing ferroptosis in podocytes. Despite being instructive, the current results could be constrained by a number of reasons. First off, in order to fully evaluate the clinical utility of circ-0069561 in DKD, additional sample size expansion and survival analyses are required. The patient sample size was quite limited. Additional research is required to uncover the precise processes linked to circ-0069561 in DKD, and in vivo studies should validate the study's probable pathways. Conclusion In conclusion, we found that circ-0069561 is highly expressed in DKD. Circ-0069561 expression levels correlate with DKD disease severity and proteinuria, and circ-0069561 may cause podocytes to undergo ferroptosis, which could aid in the progression of DKD. The results of this study can be used to better understand diabetic diabetes and uncover new targets for the disease's prevention and treatment. Declarations Conflict of interest The authors declared that no competing interest exists. Ethical approval This study was approved by the Research Ethics Committee of the First Affiliated Hospital of Anhui Medical University (NO.2022311). All the Animals experiments were carried out following the approval by the Ethics Committee of Animal Research of Anhui Medical University (NO.20220759). We declare that all the patients were participated in this study were aware about the purpose and content of this research. A verbal and written consents were taken prior to their participant in this study. Funding This study was supported by the National Natural Science Foundation of China (82200806); 2022 Anhui Provincial Department of Education University research project (2022AH051180); 2022 Anhui Province translational medicine project cultivation project (2022zhyx-C31). Author Contribution LJ and YW designed the study concept. CC, XL and SZ did experiments, analyzed and interpreted the data, and wrote the final version of article. XL and YW assist in completing the experiment. YM and ZH edited the figure legends. All authors contributed to study design critically reviewed the first draft, approved the final version and agreed to be accountable for the work. Acknowledgement We are particularly grateful to all the people who have given us help on our article. Data availability The database used and data analyzed in the current study can be made available from the corresponding authors. 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Int J Biol Sci 19(9):2678–2694. http://doi.org/10.7150/ijbs.81892 Tables Table 1 Baseline demographic data of patients expression of renal tissue Variables NC (n = 12) MCD (n = 15) DKD (n = 46) P value DKD1(n = 10) (UACR 30-299 mg/g) DKD2(n=36) (UACR≥300mg/g) Age (years) 53.00(42.00,59.75) 52.00(32.00,57.00) 53.00(48.50,55.25) 53.00(42.50,56.00) 0.765 Gender (M/F) 7/5 9/6 8/2 24/12 0.593 BMI (kg/m 2 ) 25.58±3.07 24.44±5.00 26.41±3.91 25.63±3.70 0.648 BMI body mass index Table 2 Comparison of clinical data of DKD patients Variables DKD1(n = 10) (UACR 30-299 mg/g) DKD2(n = 36) (UACR≥300 mg/g) t (Z) P value DM duration(Y) 9.00(2.75,18.50) 10.00（3.00,11.75) -0.857 0.407 SBP (mmHg) 128.70±7.82 134.22±14.74 -1.135 0.263 DBP (mmHg) 84.30±10.67 83.61±6.01 0.196 0.848 ALB(g/L) 42.85(40.18,45.08) 36.55(28.08,39.90) -3.529 ＜0.001*** BUN (mmol/L) 7.01(5.79,8.90) 7.94(6.11,11.07) -1.065 0.298 Scr(μmol/L) 123.70(63.45,155.63) 129.05(92.50,175.28) -0.905 0.378 eGFR[ml/min·1.73 m 2 ] 54.00(45.50,110.50) 50.50(38.00,82.25) -1.186 0.240 FBG (mmol/L) 6.42(5.33,8.82) 6.53（4.89,9.75) -0.080 0.948 HbAc1(%) 6.65(6.15,8.30) 7.60(6.53,8.40) -0.893 0.378 TC (mmol/L) 4.30(3.36,5.11) 5.36(4.39,6.34) -2.423 0.014* TG (mmol/L) 1.46(1.00,3.62) 1.87(1.41,2.58) -0.559 0.591 CRP(mg/L) 2.58(0.92,6.66) 1.09(0.65,1.66) -1.505 0.134 UACR(mg/g) 77.00(32.50,197.03) 2409.4(627.50,4668.30) -4.714 ＜0.001*** U-TRF（mg/L） 5.17(0.58,9.42) 81.51(35.17,151.60) -4.394 ＜0.001*** uIgG（mg/L） 11.32(4.17,17.59) 154.89(59.27,450.66) -4.581 ＜0.001*** U-α1-MG (mg/L) 12.67(6.13,27.21) 33.02(16.38,54.74) -2.503 ＜0.001*** U-β2-MG (mg/L) 0.27(0.08,1.26) 0.63(0.21,8.25) -1.678 0.096 *Significant level at P ≤ 0.05 and *** significant level at P ≤ 0.001. DM diabetes mellitus; SBP systolic blood pressure; DBP diastolic blood pressure; ALB albumin; BUN blood urea nitrogen; Scr serum creatinine; eGFR estimated glomerular filtration rate; FBG fasting blood glucose; HbAc1 glycosylated haemoglobin; TC total cholesterol; TG triglyceride; CRP C-reactive protein; UACR urinary creatinine; U-TRF urinary transferrin; uIgG urinary immunoglobulin G; U-α1-MG urinary-α1-microglobulin; U-β2-MG urinary-β2-microglobulin Table 3 Comparison of pathological data of DKD patients Variables DKD1(n = 10) (UACR 30-299 mg/g) DKD2(n = 36) (UACR≥300 mg/g) Z P value Glomerular lesions, n (n%) 3.207 0.001*** I 0(0) 0(0) IIa 9(90) 12(33.33) IIb 1(10) 3(8.33) III 0(0) 14(38.89) IV 0(0) 7(19.44) IFTA, n (n%) 1.977 0.096 Score 0 0(0) 1(2.78) Score 1 5(50) 6(16.67) Score 2 5(50) 25(69.44) Score 3 0(0) 4(11.11) Interstitial inflammation, n (n%) 1.089 0.646 Score 0 1(10) 1(2.78) Score 1 9(90) 34(94.44) Score 2 0(0) 1(2.78) Arteriolar hyalinosis, n (n%) 3.143 0.005** Score 0 1(10) 1(2.78) Score 1 8(80) 11(30.56) Score 2 1(10) 24(66.67) Arteriosclerosis, n (n%) 4.129 0.000*** Score 0 2(20) 0(0) Score 1 8(80) 11(30.56) Score 2 0(0) 25(69.44) **Significant level at P ≤ 0.01 and *** significant level at P ≤ 0.001. IFTA interstitial fibrosis and tubular atrophy Table 4 Correlation analysis between circ-0069561 level and clinicopathological Variables circ-0069561 Correlation Coefficient (r) P value Renal function indices BUN 0.297 0.045* Scr 0.049 0.745 eGFR -0.034 0.825 Urine test UACR 0.306 0.039* U-TRF 0.254 0.088 uIgG 0.202 0.179 U-α1-MG 0.072 0.634 U-β2-MG 0.072 0.635 Other serum indices ALB -0.113 0.456 FBG 0.038 0.800 HbAc1 0.241 0.107 TC 0.035 0.816 TG -0.001 0.993 CRP -0.085 0.572 Pathological data Glomerular lesions 0.304 0.040* IFTA 0.149 0.323 Interstitial inflammation 0.376 0.010** Arteriolar hyalinosis 0.415 0.004** Arteriosclerosis 0.526 0.000*** *Significant level at P ≤ 0.05, **Significant level at P ≤ 0.01 and *** significant level at P ≤ 0.001. ALB albumin; BUN blood urea nitrogen; Scr serum creatinine; eGFR estimated glomerular filtration rate; FBG fasting blood glucose; HbAc1 glycosylated haemoglobin; TC total cholesterol; TG triglyceride; CRP C-reactive protein; UACR urinary creatinine; U-TRF urinary transferrin; uIgG urinary immunoglobulin G; U-α1-MG urinary-α1-microglobulin; U-β2-MG urinary-β2-microglobulin; IFTA interstitial fibrosis and tubular atrophy Table 5 Binary logistic regression analysis. Variables Univariate analysis Multivariate analysis P OR (95% CI) P OR (95% CI) circ-0069561 a 0.004** 1.382-5.426 0.013* 1.220-5.542 ALB 0.009** 0.583-0.925 0.023* 0.615-0.964 TC 0.026* 1.121-6.020 —— —— U-TRF 0.014* 1.040-1.402 —— —— uIgG 0.031* 1.014-1.352 —— —— U-α1-MG 0.031* 1.014-1.352 —— —— Glomerular lesions 0.022* 1.320-34.804 —— —— Arteriolar hyalinosis 0.009** 1.668-37.539 —— —— *Significant level at P ≤ 0.05 and ** significant level at P ≤ 0.01. Circ-0069561 a =circ-0069561*50 for inclusion in binary logistics regression; ALB albumin; TC total cholesterol; U-TRF urinary transferrin; uIgG urinary immunoglobulin G; U-α1-MG urinary-α1-microglobulin Additional Declarations No competing interests reported. Supplementary Files SupplementaryTables.doc WesternBlottingoriginaldrawing.pdf Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5465308","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":379514784,"identity":"068cfc5e-973b-49d1-9da5-faf04da64608","order_by":0,"name":"Chaoyi Chen","email":"","orcid":"","institution":"the First Affiliated Hospital of Anhui Medical University","correspondingAuthor":false,"prefix":"","firstName":"Chaoyi","middleName":"","lastName":"Chen","suffix":""},{"id":379514786,"identity":"f6acabb8-c992-4634-b5db-864a00952492","order_by":1,"name":"Xinran Liu","email":"","orcid":"","institution":"the First Affiliated Hospital of Anhui Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xinran","middleName":"","lastName":"Liu","suffix":""},{"id":379514787,"identity":"b8ede3ed-3009-44c8-8747-709ecceba6ce","order_by":2,"name":"Sai Zhu","email":"","orcid":"","institution":"the First Affiliated Hospital of Anhui Medical University","correspondingAuthor":false,"prefix":"","firstName":"Sai","middleName":"","lastName":"Zhu","suffix":""},{"id":379514788,"identity":"0d04b95d-d354-4191-b94a-d040bea437a1","order_by":3,"name":"Xueqi Liu","email":"","orcid":"","institution":"the First Affiliated Hospital of Anhui Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xueqi","middleName":"","lastName":"Liu","suffix":""},{"id":379514795,"identity":"05ddc9f7-17ec-444c-a0da-afb3a0d16251","order_by":4,"name":"Yukai Wang","email":"","orcid":"","institution":"the First Affiliated Hospital of Anhui Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yukai","middleName":"","lastName":"Wang","suffix":""},{"id":379514798,"identity":"50827b19-49c9-46dc-ac3c-bb08ad44e855","order_by":5,"name":"Yu Ma","email":"","orcid":"","institution":"the First Affiliated Hospital of Anhui Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yu","middleName":"","lastName":"Ma","suffix":""},{"id":379514799,"identity":"6b9f18ae-9dab-46cd-ba7b-3cb4d3d78c56","order_by":6,"name":"Ziyun Hu","email":"","orcid":"","institution":"the First Affiliated Hospital of Anhui Medical University","correspondingAuthor":false,"prefix":"","firstName":"Ziyun","middleName":"","lastName":"Hu","suffix":""},{"id":379514805,"identity":"72ef3831-d0cd-4b6c-8621-adcfcc66057b","order_by":7,"name":"Yonggui Wu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8UlEQVRIiWNgGAWjYDADNvYGBgYeIOIjXgvPAYgWNuKtkUgAa2EgqMXgRo7h44JftYl9kq8TH7zNsZNhY2B++OgGg10eHi3GxjP7jie2SeduNpy7LRnoMDZj4xyG5GJcWsxu5JhJ8/YcA2nZJs27jRmohYdNOofhQGIDQS2SZ7f/5t1WT6QWnh81iW0SQCt4tx0mrMX+zLNiY96GA8ZtPLmbJeduO87Dxgzyi0EyTi2S7ckbH/P8qZOd335244e326rt+dmbHz7OqbDDqYWBgcOAgbHtMJIAM4gwwKkeCNgfMDD8qcOnYhSMglEwCkY6AACz3VD4EsQZoQAAAABJRU5ErkJggg==","orcid":"","institution":"the First Affiliated Hospital of Anhui Medical University","correspondingAuthor":true,"prefix":"","firstName":"Yonggui","middleName":"","lastName":"Wu","suffix":""},{"id":379514806,"identity":"f22c9233-7837-4ff5-8a77-21faa6179f07","order_by":8,"name":"Ling Jiang","email":"","orcid":"","institution":"the First Affiliated Hospital of Anhui Medical University","correspondingAuthor":false,"prefix":"","firstName":"Ling","middleName":"","lastName":"Jiang","suffix":""}],"badges":[],"createdAt":"2024-11-16 10:38:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5465308/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5465308/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":71808537,"identity":"f47261ab-f3ec-4cf1-8b93-b1d1712a8b6f","added_by":"auto","created_at":"2024-12-18 17:57:57","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":4271744,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of differentially expressed circRNA in DKD and NC renal tissues.\u003cstrong\u003e A\u003c/strong\u003e Heatmap comparing the expression levels of circRNAs in the DKD group (n = 4) with the NC control group (n = 4). Horizontal axis markers represent DKD and NC samples, and vertical axis markers represent circRNAs expression levels. Expression values are indicated by the color scale. The intensity gradually increases from green (relatively low expression) to red (relatively high expression). Each column represents a tissue sample and each row represents a circRNAs. \u003cstrong\u003eB\u003c/strong\u003eScatterplot to assess the distribution of circRNAs between DKD and NC groups. Red dots represent up-regulated circRNAs, green dots represent down-regulated circRNAs, and grey dots represent circRNAs that were not differentially expressed. \u003cstrong\u003eC\u003c/strong\u003e Length of circRNAs. \u003cstrong\u003eD\u003c/strong\u003e Reverse shear reads of circRNAs. \u003cstrong\u003eE\u003c/strong\u003e Volcano plots of differentially expressed circRNAs in the DKD and NC groups. Red dots indicate significantly differentially expressed upregulated circRNAs and green dots indicate significantly differentially expressed downregulated circRNAs. outside the two vertical lines are circRNAs with log2FC absolute value ≥ 0.585, and the horizontal line indicates a p-value of 0.05.\u003cstrong\u003e F\u003c/strong\u003e Percentage of new and known differentially expressed circRNAs. \u003cstrong\u003eG\u003c/strong\u003e Location of differentially expressed circRNAs on the position on human chromosomes\u003c/p\u003e","description":"","filename":"Fig1.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5465308/v1/11de159cdfe93cc90bb368fc.jpg"},{"id":71808533,"identity":"311614c8-fe41-408b-b5c6-54f150a6633d","added_by":"auto","created_at":"2024-12-18 17:57:57","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2245332,"visible":true,"origin":"","legend":"\u003cp\u003eScreening for differentially expressed circRNAs. \u003cstrong\u003eA\u003c/strong\u003e H\u0026amp;E staining of human kidney. Scale bar = 50 μm. \u003cstrong\u003eB\u003c/strong\u003e PAS staining of human kidney. Scale bar = 50 μm. \u003cstrong\u003eC\u003c/strong\u003e MASSON staining of human kidney. Scale bar = 50 μm. \u003cstrong\u003eD\u003c/strong\u003e PASM staining of human kidney. Scale bar = 50 μm.\u003cstrong\u003e E\u003c/strong\u003e TEC of human kidney. scale bar = 2 μm. \u003cstrong\u003eF\u003c/strong\u003eRelative expression levels of 8 up-regulated circRNAs in renal tissues of 46 DKD patients and 12 NC controls, *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01, ***\u003cem\u003eP\u003c/em\u003e\u0026lt; 0.001. \u003cstrong\u003eG\u003c/strong\u003e Public prediction sites predicted the genomic structure of circ-0069561. (H) Sanger sequencing confirmed the circ-0069561 reverse splice site. H\u0026amp;E, haematoxylin and eosin; PAS, periodate-schiff; PASM, periodic acid-silver methenamine; TEM, transmission electron microscopy\u003c/p\u003e","description":"","filename":"Fig2.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5465308/v1/19dbb49a3969d9710ba09e1f.jpg"},{"id":71809077,"identity":"2043fff8-af96-462f-acfb-191e7b7046da","added_by":"auto","created_at":"2024-12-18 18:05:57","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1859183,"visible":true,"origin":"","legend":"\u003cp\u003eCirc-0069561 expression is up-regulated in type 2 diabetic mice and DKD patients.\u003cstrong\u003e A\u003c/strong\u003e PAS staining showing typical glomerular structure changes in different groups of mice. Scale bars: black 50 um; red 20 um. \u003cstrong\u003eB\u003c/strong\u003e Diabetic mice have significantly higher blood glucose, ***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001. \u003cstrong\u003eC\u003c/strong\u003e RT-PCR analysis revealed that circ-0069561 expression is up-regulated in renal tissues of db/db, ***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001. \u003cstrong\u003eD\u003c/strong\u003eRT-PCR analysis demonstrated that circ-0069561 expression is up-regulated in patients with clinical DKD , ***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001. \u003cstrong\u003eE\u003c/strong\u003e FISH experiment revealed that circ-0069561 expression is up-regulated in renal tissues of db/db. Scale bars: 20 um. \u003cstrong\u003eF\u003c/strong\u003e FISH experiment revealed that the expression level of circ-0069561 was significantly higher in kidney tissues of patients with clinical DKD than that of controls. Scale bars: 50 um\u003c/p\u003e","description":"","filename":"Fig3.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5465308/v1/cc58e695ffe31935fddfb960.jpg"},{"id":71808538,"identity":"07f05af9-28a3-4ddf-9532-27b3a041ca2d","added_by":"auto","created_at":"2024-12-18 17:57:57","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2649915,"visible":true,"origin":"","legend":"\u003cp\u003eFunction of mRNAs in the ceRNA network in DKD and construction of circRNA-miRNA-ferroptosis-related mRNA network. \u003cstrong\u003eA\u003c/strong\u003e ROC curve analysis of circ-0069561 expression in DKD patients.\u003cstrong\u003e B\u003c/strong\u003e Wayne diagram showing intersection analysis of ferroptosis-associated mRNAs with differentially expressed mRNAs in the ceRNA network of circ-0069561.\u003cstrong\u003e C\u003c/strong\u003e CircRNA-miRNA-ferroptosis-associated mRNA network of circ-0069561. Red circles indicate miRNAs that may be more relevant to DKD. Blue circles represent mRNAs that may be involved in DKD pathogenesis. \u003cstrong\u003eD\u003c/strong\u003eSignificant enrichment of the top 5 KEGG pathways. \u003cstrong\u003eE\u003c/strong\u003e Representative transmission electron micrographs of podocyte in control and db/db groups. Scale bar: 500 nm (n = 6). \u003cstrong\u003eF\u003c/strong\u003e Immunohistochemistry results showed that ACSL4 levels were increased and GPX4 levels were decreased in the db/db groups. Scale bar: 20 um (n = 6), ***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001. \u003cstrong\u003eG\u003c/strong\u003e Western blot results also showed that ACSL4 levels were increased and GPX4 levels were decreased in the db/db groups. (n = 6), ***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001\u003c/p\u003e","description":"","filename":"Fig4.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5465308/v1/b8e817dd5861928603d80518.jpg"},{"id":71808535,"identity":"2a9f335e-6b92-4060-828d-aa07970fac1b","added_by":"auto","created_at":"2024-12-18 17:57:57","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":2364366,"visible":true,"origin":"","legend":"\u003cp\u003eSignificant correlation between circ-0069561 expression levels and levels of podocyte injury and ferroptosis in DKD group with massive proteinuria. \u003cstrong\u003eA\u003c/strong\u003e Immunohistochemistry staining of glomerulus WT1 and podocin. Scale bar: 50 um, *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, ***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001. \u003cstrong\u003eB\u003c/strong\u003e Correlation analysis between circ-0069561 expression level and levels of podocyte injury in DKD group with massive proteinuria. \u003cstrong\u003eC\u003c/strong\u003e Immunohistochemistry staining of glomerulus ACSL4 and GPX4. Scale bar: 20 um, ***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001. \u003cstrong\u003eD\u003c/strong\u003e Correlation analysis between circ-0069561 expression level and levels of ferroptosis in DKD group with massive proteinuria\u003c/p\u003e","description":"","filename":"Fig5.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5465308/v1/dfdf46ed40dda72be1c18f0d.jpg"},{"id":71808532,"identity":"204f217f-8b2c-4378-a80a-0e61d28662c6","added_by":"auto","created_at":"2024-12-18 17:57:57","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":5713,"visible":true,"origin":"","legend":"\u003cp\u003eSilencing circRNA-0069561 attenuates high glucose-induced podocyte damage and ferroptosis. \u003cstrong\u003eA\u003c/strong\u003e Real-time PCR showed that circ-0069561 expression was significantly elevated in high glucose-induced MPC5. mTEC: mouse tubular epithelial cells; vascular endothelial cells: VECs; MPC5: mouse podocyte clone 5; SV40-MES13: mouse glomerulus mesangial cells, *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, ***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001. \u003cstrong\u003eB\u003c/strong\u003eReal-time PCR screening of circ-0069561 siRNA sequences for the best knockdown effect, ***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001. \u003cstrong\u003eC\u003c/strong\u003e The expression level of circ-0069561 was verified by FISH experiment. Scale: 10 μm, ***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001. \u003cstrong\u003eD\u003c/strong\u003eWestern blot and quantification showed that silencing circ-0069561 attenuated high glucose-induced loss of the podocyte marker proteins WT1 and podocin, *\u003cem\u003eP\u003c/em\u003e\u0026lt; 0.05, **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01, ***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001.\u003cstrong\u003e E\u003c/strong\u003e Western blot and quantification showed that silencing circ-0069561 attenuated high glucose-induced ferroptosis levels in podocytes, *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, ***\u003cem\u003eP\u003c/em\u003e\u0026lt; 0.001. \u003cstrong\u003eF\u003c/strong\u003e Fe2+, MDA, GSH and SOD level in each group. \u003cstrong\u003eG\u003c/strong\u003e Fluorescent probe DHE staining to detect ROS levels in each group of MPC5 cells. Scale bar: 50 um, *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01, ***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-5465308/v1/da01912a0b7c1f5e4a5b6505.png"},{"id":71810423,"identity":"4de7e880-3628-4569-8847-413b25549660","added_by":"auto","created_at":"2024-12-18 18:22:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":14356657,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5465308/v1/f7f90564-31b0-44fd-9735-d10caee398a4.pdf"},{"id":71809078,"identity":"7e332591-db44-4521-8894-f885a1e531ce","added_by":"auto","created_at":"2024-12-18 18:05:57","extension":"doc","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":61440,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTables.doc","url":"https://assets-eu.researchsquare.com/files/rs-5465308/v1/fc48cf8405de5328bc6245a5.doc"},{"id":71808540,"identity":"e4560bde-7a6d-4c34-89f2-7e9df1df9902","added_by":"auto","created_at":"2024-12-18 17:57:57","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":459565,"visible":true,"origin":"","legend":"","description":"","filename":"WesternBlottingoriginaldrawing.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5465308/v1/8f25672e1fcf510f7fd132a0.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Upregulation of circ-0069561 promotes diabetic kidney disease progression","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe diabetic kidney disease (DKD) is one of the most serious microvascular chronic consequences in diabetic patients[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Diabetes mellitus (DM) is an international health crisis. According to the prediction of the World Health Organization, diabetes mellitus will affect about 642\u0026nbsp;million people globally by 2040. Diabetes can involve all important organs in the body, including central nervous complications, peripheral neuropathy, renal disease, cardiovascular disease, various infections, etc., seriously damaging the quality of life of patients[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. DM is classified into two types: type 1 (inadequate the production of insulin from pancreatic β-cells) and type 2 (insulin resistance). Around 40% of DM patients progress to DKD, and 30\u0026ndash;50% of these cases attributed to T2D[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. DKD is the main cause of dialysis treatment for end-stage renal disease (ESRD), resulting in significant economic burdens[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The molecular pathophysiology of DKD remains unknown. Thus, it's critical to investigate novel treatment targets and gain a deeper understanding of the molecular mechanism behind DKD.\u003c/p\u003e \u003cp\u003eIn eukaryotes, circular RNA (circRNA) is an ubiquitous type of noncoding RNA [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. CircRNAs exhibit greater stability than linear non-coding RNAs because of their covalent closed-loop structure[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Circ_104075 may be used as a biomarker for identifying hepatocellular cancer[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Researchers revealed that circRNAs play a role in the onset and progress of different diseases, including metabolic illnesses like diabetes[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Our earlier study discovered that the absence of circ-0000953 in DM caused podocyte damage and defective autophagy[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Peng et al. discovered that renal fibrosis in DM is a result of down-regulation of circRNA_010383[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. CircRNA is intimately linked to the progression of numerous disease.\u003c/p\u003e \u003cp\u003eThe mechanisms of DKD are complex. Medical researchers have recently become interested in ferroptosis[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Ferroptosis is a new kind of planned cell death that requires iron overload and ROS production, in relative to apoptosis and necrosis[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Recent evidence suggests that ferroptosis plays a significant role in the development of DKD[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this research, whole high-throughput RNA sequencing (RNA-seq) was utilized to explore circRNA expression profiles, and real-time PCR (RT-PCR) analysis was used to select circ-0069561, which had significantly higher expression levels. The clinical data analysis showed that circ-0069561 has a good value in the detection of massive proteinuria. The pathophysiology of DKD may involve ferroptosis, according to the circRNA-miRNA-mRNA network. Ferroptosis and podocyte damage brought on by elevated glucose can be lessened by silencing circ-0069561. This work suggests that circ-0069561 could be a novel therapeutic target and diagnostic biomarker to preventing DM development.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eClinical specimens and collection\u003c/h2\u003e \u003cp\u003eBiopsy specimens from the kidneys of four people diagnosed with DKD and healthy kidney tissue samples adjacent to tumours from four patients who underwent nephrectomy for renal tumours were collected for RNA-seq and analysis of genomics. From January 2022 to June 2023, 46 volunteers who had received a kidney biopsy diagnosis of DKD were gathered from Anhui Medical University's First Affiliated Hospital. One criterion for the advancement of UACR was a urine albumin/creatinine ratio (UACR) of \u0026ge;\u0026thinsp;300 mg/g. Diabetic nephropathy patients were further separated into two groups: DKD1 patients (those with microalbuminuria or negative protein urine) and DKD2 patients (those with macroalbuminuria) with UACR\u0026thinsp;\u0026ge;\u0026thinsp;300 mg/g. Renal biopsy was also used to harvest kidney tissue from the minimal change disease (MCD) group. Renal tissues from the normal control (NC) group were removed from sections of adjacent cancerous tissue following urological surgery. All specimens were verified by histopathology. RNA-seq results were confirmed with real-time PCR (RT-PCR) in 46 kidney tissues from DKD patients and 12 healthy kidney tissues. Consent for this study was given by the First Affiliated Hospital's Research Ethics Committee of Anhui Medical University (NO.2022311), which was executed in accordance with the Helsinki Declaration. Everyone who participated signed a consent form.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eChemicals and antibodies\u003c/h3\u003e\n\u003cp\u003eIn this research, the following chemicals and antibodies were used: Lipofectamine RNAiMAX Reagent (Invitrogen Life Technologies, 13,778\u0026thinsp;\u0026minus;\u0026thinsp;030) was used for transfection techniques, closely adhering to the manufacturer's recommendations. Proteintech's 66009-1-Ig anti-β-actin antibody, 60004-1-Ig anti-GAPDH antibody, Abcam's ab267377 anti-WT-1 antibody, Abcam's ab181143 anti-podocin antibody, HUABIO's ET7111-43 anti-ACSL4 antibody, and HUABIO's ET1706-45 anti-GPX4 antibody are among the antibodies. Biochemical Assays: Superoxide dismutase (SOD), glutathione (GSH), and malondialdehyde (MDA) were measured using assay kits purchased from Jiancheng (Nanjing, China). Iron content was quantified using an assay kit from Leagene (Beijing, China). The DHE were achieved in accordance with the kits provided by Beyotime (Jiangsu, China).\u003c/p\u003e\n\u003ch3\u003eCircRNA sequencing\u003c/h3\u003e\n\u003cp\u003eRNA-seq was performed by Kang Cheng Bio (Shanghai, China). The total RNA samples were subjected to oligo dT enrichment (rRNA removal), after which the KAPA Stranded RNA-Seq Library Prep Kit (Illumina) was employed to construct the libraries. Further data mining analyses were done through the Kang Cheng Biologicals program.\u003c/p\u003e\n\u003ch3\u003eInclusion and exclusion criteria\u003c/h3\u003e\n\u003cp\u003eThe criteria for including participants in DM group were established as follows[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]: Clinically and pathologically diagnosed type 2 diabetes, aged 18\u0026ndash;80 years. Individuals with type 1 diabetes, secondary diabetes, and other diabetes types were not considered eligible; Patients with diabetic ketoacidosis were excluded; Patients with severe infection, pregnancy, other endocrine diseases, connective tissue diseases, malignant tumors, myocardial infarction, and severe liver dysfunction were excluded. This study included two control groups: MCD and NC. In total, the study comprised 73 participants (NC:MCD:DKD1:DKD2\u0026thinsp;=\u0026thinsp;12:15:10:36).\u003c/p\u003e\n\u003ch3\u003ePathological examination of renal tissue utilized staining techniques and transmission electron microscopy (TEM)\u003c/h3\u003e\n\u003cp\u003eSolarbio Corporation (Beijing, China) provided the following staining kits: haematoxylin and eosin (H\u0026amp;E), periodate-schiff (PAS), Masson, and periodic acid-silver methenamine (PASM). Tissue slices were fixed in formalin, embedded in paraffin, and stained with H\u0026amp;E, PAS, Masson, and PASM according to the manufacturer's instructions. Renal cortical tissues were fixed in 2.5% glutaraldehyde, dried and embedded, and examined under a transmission electron microscope.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eType 2 diabetes mouse model\u003c/h2\u003e \u003cp\u003eThe study utilized a db/db mouse model of type 2 diabetes. Male db/db mice and db/m control mice aged 6 weeks were purchased from GemPharmatech (Nanjing, China). These mice were housed in a specific-pathogen-free (SPF) environment with a stable temperature of 22\u0026deg;C\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C and a humidity level of 60%, following a 12-hour light-dark cycle. Refer to our previous research[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], the db/m control mice (n\u0026thinsp;=\u0026thinsp;6) and db/db mice were maintained until 8 weeks (n\u0026thinsp;=\u0026thinsp;6), 12 weeks (n\u0026thinsp;=\u0026thinsp;6), 16 weeks (n\u0026thinsp;=\u0026thinsp;5), and 20 weeks (n\u0026thinsp;=\u0026thinsp;6), the mice were randomly placed in cages with 2\u0026ndash;3 mice per cage. There was no loss of mice during feeding. For each mouse, three different researchers were involved, and the first researcher was responsible for random grouping and feeding. Two researchers were left to measure and evaluate the results. All animals were treated in compliance with the principles of the Declaration of Helsinki and the ARRIVE recommendations. This research was carried out in accordance with the Declaration of Helsinki and approved by Anhui Medical University's Animal Research Ethics Committee (NO.20220759).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eImmunohistochemical staining\u003c/h3\u003e\n\u003cp\u003eAfter deparaffinizing kidney paraffin sections, they underwent high-pressure antigen repair using citric acid solution, hydrogen peroxide incubation for 20 minutes, goat serum blocking for 40 minutes, goat serum removal, primary antibody addition, and overnight incubation at 4\u0026deg;C in a humidified refrigerator. The sections were then cleaned and incubated with the secondary antibody for 30 minutes at 37\u0026deg;C. The color development of 3,3'-diaminobenzidine (DAB) was carried out. Hematoxylin was used to stain the cell nuclei. Use a Leica microscope (Bensheim, Germany) to examine the sections. Utilize ImageJ software (NIH, Bethesda, MD, USA) to analyze and quantify the staining.\u003c/p\u003e\n\u003ch3\u003eCell culture\u003c/h3\u003e\n\u003cp\u003eThe Institute of Basic Medical Sciences at the Chinese Academy of Medical Sciences provided the conditionally immortalized mouse podocytes (MPC5). These cells were maintained at 33\u0026deg;C in RPMI 1640 supplemented with 20 U/mL of mouse recombinant interferon-g (IFN-g) and 10% fetal bovine serum. The podocytes were maintained at 37\u0026deg;C for seven days without IFN-γ under non-permissive conditions in order to induce differentiation. Professor Lan HY of the Chinese University of Hong Kong kindly provided mouse tubular epithelial cells (mTECs). Vascular endothelial cells (VECs) and mouse mesangial cells (SV40) were obtained from the Chinese Academy of Sciences Cell Bank and cultivated in DMEM supplemented with 5% serum. MPC5 cells were transfected with siRNA or an overexpression plasmid (Hanbio Biotechnology, China) using Lipofectamine RNAiMAX Reagent (Invitrogen) in accordance with the manufacturer's recommendations. \u003cb\u003eTable \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e lists the siRNA sequences that were employed in this investigation. A negative scrambled siRNA or plasmid (provided by Hanbio Biotechnology, China) was used as the control. The diluted siRNA or plasmid was combined with Lipofectamine RNAiMAX and incubated for 20 minutes prior to being introduced to the cells in OPTI-MEM medium. Following a six-hour incubation period, the medium was replaced with a complete medium. The treatments employed in this study included high glucose (HG) (30 mM glucose), mannitol, and moderate glucose (MG) (24.5 mM mannitol\u0026thinsp;+\u0026thinsp;5.5 mM glucose), as well as normal glucose (NG) (5.5 mM glucose).\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eFluorescence in situ hybridization (FISH)\u003c/h2\u003e \u003cp\u003eFor the hybridization process, circ-0069561-specific fluorescent dye-labeled nucleic acid probes were employed. First, 4% paraformaldehyde was used to fix the samples, and then hydrochloric alcohol was used to wash them. After ten minutes of air drying at 46\u0026deg;C, they were put through a five-minute gradient ethanol dehydration process. After that, 1 \u0026micro;L of the probe was mixed with 10 \u0026micro;L of the previously made hybridization buffer. For one and a half hours, the hybridization was carried out in a sealed chamber with washing buffer at 46\u0026deg;C in the dark. The slides were then incubated for a further half hour at 48\u0026deg;C once the temperature was raised to that level. Following hybridization, distilled water was used to rinse the slides and an anti-fading solution was used. The Leica microscope (Bensheim, Germany) was used to investigate the location of circ-0069561 expression. \u003cb\u003eTable S2\u003c/b\u003e contains a list of the probe sequences that were employed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eReal-Time PCR analysis (RT-PCR)\u003c/h2\u003e \u003cp\u003eTotal RNA was isolated from human paraffin-embedded tissue sections using the Paraffin Tissue Total RNA Kit (Simgen, Hangzhou, China). Following the manufacturer's instructions, RNA extraction was carried out using Trizol (Invitrogen) for cellular or renal samples. Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM was utilized to display the results, with β-actin serving as an internal control for normalization. \u003cb\u003eTable S3\u003c/b\u003e lists all of the primer sequences used in this investigation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eWestern Blotting\u003c/h2\u003e \u003cp\u003eCell and kidney tissue samples were lysed using ice-cold radio-immunoprecipitation assay (RIPA) buffer supplemented with protease and phosphatase inhibitors (Beyotime, China). Following denaturation, proteins were separated using SDS-PAGE and transferred to a membrane for further immunoblotting using specific antibodies. The protein bands were identified using an Enhanced ECL Chemiluminescent Substrate Kit (Yeasen, 36222ES76), and images were captured using the Amersham Imager 600 System.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eKEGG pathway enrichment analysis and construction of a circRNA-miRNA-mRNA network\u003c/h2\u003e \u003cp\u003eWe constructed a circRNA-miRNA-mRNA network to study their interactions. Moreover, the FerrDb database was used to identify mRNAs associated with ferroptosis. Ferroptosis-associated mRNAs and differentially expressed mRNAs intersected in the ceRNA network for KEGG pathway analysis of ferroptosis-associated DEGs. CircRNA-miRNA-ferroptosis-associated mRNA networks were then constructed using Cytoscape software (v3.7.1).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analyses\u003c/h2\u003e \u003cp\u003eEach experiment was carried out at least three times. For statistical analysis, R (version 4.2.1) and SPSS (version 26.0) were utilized. First, the normality of the data was evaluated using the Shapiro-Wilk test. When describing quantitative data with a normal distribution, the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD is utilized. One-way analysis of variance was employed for comparisons between several groups, whereas the t-test was employed for comparisons between two groups. Group variances and multiple comparisons were evaluated using Tamhane's T2 and LSD tests, respectively, and Levene's test for equality of variances. When displaying variables that are not normally distributed, interquartile ranges and medians are utilized. The Kruskal\u0026ndash;Wallis H-test and the Mann\u0026ndash;Whitney U-test were used to assess differences between two and three groups, respectively. Pearson's and Spearman's correlation coefficients were used to assess the normality of normally and non-normally distributed variables, respectively. Covariates were initially evaluated using univariate regression analysis, and then multivariate logistic regression analysis, in order to develop prediction models. The models were evaluated using receiver operating characteristic (ROC) curves. Graphing was done using GraphPad Prism (version 8). P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was set as the significant level.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eExpression profile of circRNA in DKD\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFour patients with diabetic nephropathy and four paracancerous tissues were used for RNA sequencing, with the objective of identifying functional circRNAs involved in the progression of the disease. Fig. 1A and Fig. 1B illustrate the results of the heatmaps and scatter plots, which demonstrate that a total of 2,580 circRNAs were identified, with notable differences observed between the DKD and NC groups. The length and reverse shear reads of the detected circRNAs are presented in Fig. 1C and D. Volcano plots demonstrated that, using log2FC absolute value \u0026ge;0.585 and P value \u0026lt;0.05 as the cut-off value, 21 circRNAs were upregulated in diabetic nephropathic tissues, and 52 were downregulated in diabetic nephropathic tissues (Fig. 1E). Of the 73 identified circRNAs, four were novel discoveries, while 69 were previously reported (Fig. 1F). These circRNAs were predominantly distributed across autosomes, with two downregulated circRNAs originating from sex chromosomes (Fig. 1G).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eScreening for Differentially Expressed circRNAs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe baseline characteristics of 46 patients with DKD (including 10 patients with microproteinuria DKD and 36 patients with massive proteinuria DKD), 15 patients with MCD, and 12 patients with urological tumours postoperatively are shown in \u003cstrong\u003eTable 1\u003c/strong\u003e. There were no statistically significant differences between the groups in terms of age or gender distribution (P \u0026gt; 0.05). Additionally, as \u003cstrong\u003eTable 2\u003c/strong\u003e illustrates, DKD patients with UACR \u0026ge;300 mg/g did not significantly differ from DKD patients with UACR \u0026lt;300 mg/g in terms of DM, systolic blood pressure (SBP), diastolic blood pressure (DBP), blood urea nitrogen (BUN), serum creatinine (Scr), estimated glomerular filtration rate (eGFR), fasting blood glucose (FBG), glycosylated hemoglobin (HbAc1), triglyceride (TG), C-reactive protein (CRP), and urinary-\u0026beta;2-microglobulin (U-\u0026beta;2-MG). Total cholesterol (TC), urinary creatinine (UACR), urinary transferrin (U-TRF), urinary immunoglobulin G (uIgG) and urinary-\u0026alpha;1-microglobulin (U-\u0026alpha;1-MG) were increased in the DKD2 group compared to the DKD1 group. And albumin (ALB) was decreased in the DKD2 group compared to the DKD1 group. The differences were statistically significant (P \u0026lt; 0.05). We performed HE, PAS, Masson and PASM staining on the sections of each group and observed the characteristic changes of DKD under electron microscope. Representative pathological pictures of each group are shown in Fig. 2A-E. A comparative examination of DKD individuals\u0026apos; pathological data is presented in \u003cstrong\u003eTable 3.\u0026nbsp;\u003c/strong\u003eThe glomerular lesions, arteriolar hyalinosis and arteriosclerosis of DKD2 group were higher than that of DKD1 (P \u0026lt; 0.05), and the two groups\u0026apos; differences in interstitial inflammation and IFTA were not statistically significant (P \u0026gt; 0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S4\u003c/strong\u003e lists the top 10 circRNAs that are up-regulated. As the GC content and Tm value of the sequences in the vicinity of the chr1:245180543-245180628:+ and circ-0057338 cyclisation sites were low and did not meet the requirements of the primer design, we opted to employ RT-PCR in 46 DKD patients and 12 NC controls to verify the expression of the remaining 8 upregulated circRNAs. As illustrated in Fig. 2F, we identified circ-0069561, which exhibited notable distinctions between the DKD and NC groups. To this end, we consulted the circBase database (http://www.circbase.org). We obtained that circ-0069561 is located on chromosome 4:40,892,380-40,947,087. The genomic structure indicated that circ-0069561 was generated by closing shear cyclisation of four exons (exons 7, 8, 9 and 10) of the APBB2 locus (Fig. 2G). Further evidence was provided by Sanger sequencing after PCR, which demonstrated the cyclic structure of circ-0069561. The GA of the cyclisation site is depicted in Fig. 2H.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCirc-0069561\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;expression is elevated in kidney of type 2 diabetic mice and DKD patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFirst, we investigated the expression of circ-0069561 using db/db type 2 diabetic mice. The the glomerular basement membrane thickened, the mesangial matrix expanded, and the diabetic mice\u0026apos;s blood glucose levels were much higher, according to PAS staining (Fig. 3A-B). In db/db type 2 diabetic mice, we confirmed the expression of circ-0069561 by RT-PCR at various weekly ages. We discovered that circ-0069561 expression was markedly increased (Fig. 3C). Furthermore, we validated that circ-0069561 expression was greatly enhanced in db/db type 2 diabetic mice and was mostly localized in the glomerulus by performing FISH on kidney tissue samples from these mice (Fig. 3E). To confirm the expression of circ-0069561 in renal tissues, we applied RT-PCR and FISH in renal tissue samples from 46 patients with DKD (including 10 patients with microproteinuria DKD and 36 patients with massive proteinuria DKD), 15 patients with MCD, and 12 patients with urological tumours postoperatively to circ-0069561 expression was validated, and the results were similar to those of the in vivo experiments (Fig. 3D-F). Next, we focused on the role of circ-0069561 in DKD disease.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorrelation between circ-0069561 expression and clinicopathology of DKD patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe used RT-PCR to measure the expression level of circ-0069561 in kidney tissue samples from DKD patients and correlated the expression level of hsa_circRNA_0069561 with clinicopathological markers in order to assess the clinical importance of circ-0069561 expression in DKD. The results showed (\u003cstrong\u003eTable 4\u003c/strong\u003e) that the expression level of circ-0069561 was positively correlated with serum BUN level, and urine UACR level. Circ-0069561 expression was positively linked with pathological data such as glomerular lesions, interstitial inflammation, arteriolar hyalinosis, and arteriosclerosis (p \u0026lt; 0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRegression analysis and ROC curve\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBinary logistic regression was employed using UACR\u0026nbsp;\u0026ge;300 mg/g as the grouping criterion[17]. Clinical and pathological data were the initial subjects of univariate regression analysis. A number of indicators were then used in multivariate regression analysis (P \u0026lt; 0.05). The levels of circ-0069561 (\u0026beta; = 0.956, P \u0026lt; 0.05) and ALB (\u0026beta; = -0.261, P \u0026lt; 0.05) were determined to be possible risk factors using multivariate regression analysis (\u003cstrong\u003eTable 5\u003c/strong\u003e). The following prediction model was produced from the results: In (p/1-p) = 0.956 \u0026times; circ-0069561 - 0.261 \u0026times; ALB + 8.179. To further explore the diagnostic significance of circ-0069561 in DKD with considerable albuminuria, we created the ROC diagnostic model by considering the kidneys in the DKD2 group as positive samples (n=36) and the kidneys in the DKD1 group as negative samples (n=10) According to the findings, the AUC (0.95 CI) was 0.889 (0.790-0.988). Fig. 4A and \u003cstrong\u003eTable S5\u003c/strong\u003e both show the ROC curve.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunction of mRNAs in the ceRNA network in DKD and construction of circRNA-miRNA-ferroptosis-related mRNA network\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCirc-0069561\u0026apos;s circRNA-miRNA-mRNA network was built. FerrDb is a publicly accessible database that provides a comprehensive overview of genes associated with ferroptosis. This includes genes that induce, suppress, or regulate ferroptosis, as well as genes that act as markers for ferroptosis. The ferroptosis-associated mRNAs were obtained by downloading the ferroptosis dataset and overlapping it with the differentially expressed mRNAs in the ceRNA network. This resulted in the identification of 177 DEGs associated with ferroptosis, as illustrated in a shared Venn diagram (Fig. 4B). A circRNA-miRNA-ferroptosis-related mRNA network was built. The network prediction (Fig. 4C) revealed that some genes associated with ferroptosis, including ACSL4, ALOX12, ALOX15, and others, were closely linked to the biological function of circ0069561. The ferroptosis-associated DEGs were subjected to KEGG pathway analysis in order to investigate the role of 177 mRNAs in the ceRNA network. The KEGG pathway analysis in \u003cstrong\u003eTable S6\u003c/strong\u003e and Fig. 4D indicated that ferroptosis may be associated with the pathogenesis of DKD. Our findings revealed that in diabetic mice, podocyte mitochondria exhibited contraction, an increase in mitochondrial membrane density, and alterations resulting from ferroptosis-induced cell death, as observed through transmission electron microscopy (Fig. 4E). Furthermore, we found that diabetic mice had higher expression levels of ACSL4 and lower expression levels of GPX4 (Fig. 4F-G). The results of the in vivo investigations suggest that ferroptosis may contribute to the pathogenesis of DKD.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSignificant correlation between circ-0069561 expression levels and levels of podocyte injury and ferroptosis in DKD group\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo learn more about circ-0069561\u0026apos;s function in DKD, we applied immunohistochemistry to validate the expression of markers of podocyte injury and key proteins of ferroptosis in renal tissues from 46 patients with DKD (including 10 patients with microproteinuria DKD and 36 patients with massive proteinuria DKD), 15 patients with MCD, and 12 patients with urological tumours postoperatively. Immunohistochemical findings showed that the glomerulus of DKD patients had considerably lower levels of WT1 and podocin protein than those of the NC and MCD groups; DKD patients with extensive proteinuria had the lowest expression levels (Fig. 5A). The results in Fig. 5B showed a significant correlation between circ-0069561 expression levels and the level of podocyte injury in the DKD group with massive proteinuria. In contrast, the glomerulus of DKD patients showed a significantly higher level of ACSL4 protein and a significantly lower level of GPX4 protein when compared to the NC and MCD groups. The expression alterations were especially noticeable in DKD patients with massive proteinuria (Fig. 5C). Ferroptosis levels and circ-0069561 expression levels had a significant relationship in the mass proteinuria DKD group, according to the results in Fig. 5D. Therefore, we speculated that circ-0069561 may contribute to the development of DKD by inducing ferroptosis in podocytes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSilencing circRNA-0069561 attenuates high glucose-induced podocyte damage and ferroptosis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe expression level of circ-0069561 was verified in high glucose-induced mTECs, VECs, MPC5, and SV40, respectively, and it was found that circ-0069561 was significantly enriched in podocytes (Fig. 6A). To further elucidate its function, we constructed an in vitro model of podocyte circ-0069561 knockdown (Fig. 6B-C). The knockdown of circ-0069561 was observed to restore the loss of the podocyte markers WT-1 and podocin that was induced by high glucose (Fig. 6D). Additionally, it was shown that circ-0069561 knockdown prevented the up-regulation of ACSL4 in podocytes caused by high hyperglycemia and restored the down-regulation of GPX4 in podocytes caused by high glucose (Fig. 6E). To further elucidate the impact of circ-0069561 knockdown on high glucose-induced iron-dependent cell death in podocytes, we examined the levels of Fe\u0026sup2;⁺, MDA, GSH, and SOD in each group. Knocking down circ-0069561 reduced Fe\u0026sup2;⁺ and MDA buildup in high glucose-induced podocytes while improving GSH and SOD downregulation (Fig. 6F). DHE staining revealed that the knockdown of circ-0069561 alleviated the accumulation of ROS in high glucose-induced podocytes (Fig. 6G). In conclusion, the results demonstrate that the knockdown of circ-0069561 mitigates high glucose-induced podocyte injury and ferroptosis.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eChronic kidney disease (CKD) is an important and prevalent complication in patients with T2D[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] and has a significant impact on the global burden[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. CircRNAs are novel non-coding RNA molecules that have received increasing attention[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. CircRNAs have been identified with the beginning and progression of kidney disease[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. In this study, we employed RNA-seq to look for circRNAs that were expressed differently in renal tissues from DKD and NC. Subsequently, circ-0069561, which exhibited markedly altered expression levels, was subjected to screening. Circ-0069561 expression levels correlate with DKD disease severity and proteinuria. Furthermore, the knockdown of circ-0069561 was observed to mitigate high glucose-induced podocyte damage and ferroptosis. Our findings indicate that circ-0069561 may toward the progress of DKD by inducing ferroptosis in podocytes. This implies that circ-0069561 might be a viable treatment option for DKD, which would have important ramifications for the clinical diagnosis and treatment of DKD.\u003c/p\u003e \u003cp\u003eFirstly, we explored the expression profile of circRNAs in renal tissues of patients with type 2 diabetic nephropathy by RNA-seq and screened for the significantly up-regulated circ-0069561. According to the findings of numerous studies, circRNAs may be used as new biomarkers for cancer and other human disorders[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] and heart disease[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The function of circRNAs as biomarkers in renal disease has been attempted to be clarified in the past few years. Cao et al. discovered a correlation between the degree of renal fibrosis and urinary exosomal circ_0036649 expression[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Another study analyzed RNA-seq in the IMN and HC groups and found that An novel diagnostic biomarker for idiopathic membranous nephropathy was urine exosomal circ_0001250[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. A total of 2,580 circRNAs were identified by RNA-seq in this study. Using log2FC absolute value\u0026thinsp;\u0026ge;\u0026thinsp;0.585 and P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 as the thresholds, 21 circRNAs were up-regulated in diabetic nephropathy tissues and 52 were down-regulated in diabetic nephropathy tissues. 10 up-regulated circRNAs were chosen for qRT-PCR validation in 46 DKD patients with 12 NC kidney tissues, and the results were in high agreement with the RNA-seq data, which validated the RNA-Seq results' Reliability. Meanwhile, we identified circ-0069561, which showed significant difference between DKD and NC groups. To this end, we consulted the circBase database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.circbase.org\u003c/span\u003e\u003cspan address=\"http://www.circbase.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). We obtained that circ-0069561 is located on chromosome 4:40,892,380\u0026thinsp;\u0026minus;\u0026thinsp;40,947,087. The genomic structure indicated that circ-0069561 was generated by closing shear cyclisation of four exons (exons 7, 8, 9 and 10) of the APBB2 locus. Further evidence was provided by Sanger sequencing after PCR, which demonstrated the cyclic structure of circ-0069561.\u003c/p\u003e \u003cp\u003eThe current investigation found that both diabetic mouse models and DKD patients have increased expression of circ-0069561. A correlation analysis of clinical trials demonstrated a positive correlation between the expression of circ-0069561 in DKD patients and UACR levels. It is established that a high level of proteinuria represents a significant clinical risk factor for a rapid decline in estimated eGFR and can be used to predict the progress of DKD[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Megumi Oshima et al. found that STING activation causes proteinuria, which assists with the development and progress of DKD[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. We used multiple regression analysis to confirm the clinical significance of circ-0069561 in DKD and discovered that it was an independent risk factor for excessive albuminuria in DKD. The ROC curves demonstrated that circ-0069561 had a high detection value for massive proteinuria. Therefore, we conclude circ-0069561 that it is associated with the severity of DKD disease and proteinuria.\u003c/p\u003e \u003cp\u003eFerroptosis disease's significant significance in DKD was examined in the present study. Ferroptosis is an innovative type of controlled cell death[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Yi-Chun Tsai, et al. used RNA-seq to identify ferroptosis as an important pathophysiological mechanism in early DKD[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Another study found that tRF3-IleAAT inhibited ferroptosis in diabetic kidney disease mice[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Ferroptosis may be a key factor in the development of DKD, according to mounting data. We built a circRNA-miRNA-ferroptosis-related mRNA network in this research and discovered that the biological activity of circ-0069561 was tightly linked to several ferroptosis-related genes, including ACSL4, ALOX12, ALOX15, etc. The KEGG pathway investigation suggests that ferroptosis may be involved in the pathophysiology of DKD. Ferroptosis may be linked to the pathophysiology of DKD, as our work revealed elevated ferroptosis levels in diabetic mice.\u003c/p\u003e \u003cp\u003eSubsequently, we investigated the relationship between circ-0069561 expression levels and the extent of podocyte damage and ferroptosis in patients with DKD. Podocytes are terminally differentiated cells that are unable to proliferate, and podocyte dysfunction in DKD results in proteinuria[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. We discovered a strong relationship between the degree of podocyte damage in DKD patients and the expression levels of circ-0069561. The lipid metabolism-related gene ACSL4 is a key driver gene for ferroptosis[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Lipid oxidation is efficiently inhibited by GPX4, an antioxidant enzyme and structural protein. It has been found to be a vital ferroptosis regulator that influences lipid and amino acid metabolism[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Ferroptosis was linked to STZ-induced kidney damage in type 1 diabetic mice and db/db animals[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Kim et al. discovered that kidney biopsy samples from diabetic individuals had considerably lower expression levels of SLC7A11 and GPX4[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. High fructose also induces ferroptosis in podocytes, ultimately leading to glomerular injury[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. According of Zhang et al., reducing ferroptosis could stop podocyte damage brought on by elevated glucose[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Ferroptosis reduction may therefore be a therapy option for DKD, as there is mounting evidence that ferroptosis contributes to the development of DKD[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Ferroptosis levels in DKD patients were shown to be significantly correlated with circ-0069561 expression levels in this investigation. Furthermore, in vitro experiments demonstrated that circ-0069561 was significantly enriched in podocytes. To further elucidate its function, we constructed an in vitro model of podocyte circ-0069561 knockdown, and the results demonstrated that knockdown of circ-0069561 attenuated high glucose-induced podocyte injury and ferroptosis. Therefore, we speculated that circ-0069561 may contribute to the development of DKD by inducing ferroptosis in podocytes.\u003c/p\u003e \u003cp\u003eDespite being instructive, the current results could be constrained by a number of reasons. First off, in order to fully evaluate the clinical utility of circ-0069561 in DKD, additional sample size expansion and survival analyses are required. The patient sample size was quite limited. Additional research is required to uncover the precise processes linked to circ-0069561 in DKD, and in vivo studies should validate the study's probable pathways.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, we found that circ-0069561 is highly expressed in DKD. Circ-0069561 expression levels correlate with DKD disease severity and proteinuria, and circ-0069561 may cause podocytes to undergo ferroptosis, which could aid in the progression of DKD. The results of this study can be used to better understand diabetic diabetes and uncover new targets for the disease's prevention and treatment.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eConflict of interest\u003c/strong\u003e \u003cp\u003eThe authors declared that no competing interest exists.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eEthical approval\u003c/strong\u003e \u003cp\u003eThis study was approved by the Research Ethics Committee of the First Affiliated Hospital of Anhui Medical University (NO.2022311). All the Animals experiments were carried out following the approval by the Ethics Committee of Animal Research of Anhui Medical University (NO.20220759). We declare that all the patients were participated in this study were aware about the purpose and content of this research. A verbal and written consents were taken prior to their participant in this study.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis study was supported by the National Natural Science Foundation of China (82200806); 2022 Anhui Provincial Department of Education University research project (2022AH051180); 2022 Anhui Province translational medicine project cultivation project (2022zhyx-C31).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eLJ and YW designed the study concept. CC, XL and SZ did experiments, analyzed and interpreted the data, and wrote the final version of article. XL and YW assist in completing the experiment. YM and ZH edited the figure legends. All authors contributed to study design critically reviewed the first draft, approved the final version and agreed to be accountable for the work.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe are particularly grateful to all the people who have given us help on our article.\u003c/p\u003e\u003ch2\u003eData availability\u003c/h2\u003e \u003cp\u003eThe database used and data analyzed in the current study can be made available from the corresponding authors.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eEftekhari A, Vahed SZ, Kavetskyy T et al (2020) Cell junction proteins: Crossing the glomerular filtration barrier in diabetic nephropathy. 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Life Sci 278:119529. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://doi.org/10.1016/j.lfs.2021.119529\u003c/span\u003e\u003cspan address=\"10.1016/j.lfs.2021.119529\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang H, Liu D, Zheng B et al (2023) Emerging Role of Ferroptosis in Diabetic Kidney Disease: Molecular Mechanisms and Therapeutic Opportunities. Int J Biol Sci 19(9):2678\u0026ndash;2694. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://doi.org/10.7150/ijbs.81892\u003c/span\u003e\u003cspan address=\"10.7150/ijbs.81892\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"607\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" style=\"width: 607px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e Baseline demographic data of patients expression of renal tissue\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 81px;\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 105px;\"\u003e\n \u003cp\u003eNC (n = 12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 112px;\"\u003e\n \u003cp\u003eMCD (n = 15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 236px;\"\u003e\n \u003cp\u003eDKD (n = 46)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003evalue\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003eDKD1(n = 10)\u003c/p\u003e\n \u003cp\u003e(UACR 30-299 mg/g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eDKD2(n=36) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; (UACR\u0026ge;300mg/g) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e53.00(42.00,59.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e52.00(32.00,57.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e53.00(48.50,55.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e53.00(42.50,56.00) \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.765\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003eGender (M/F)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e7/5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e9/6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e8/2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e24/12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.593\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e25.58\u0026plusmn;3.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e24.44\u0026plusmn;5.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e26.41\u0026plusmn;3.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e25.63\u0026plusmn;3.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e0.648\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 607px;\"\u003e\n \u003cp\u003e\u003cem\u003eBMI\u003c/em\u003e body mass index\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"600\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" style=\"width: 600px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e Comparison of clinical data of DKD patients\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 152px;\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003eDKD1(n = 10) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(UACR 30-299 mg/g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003eDKD2(n = 36) \u0026nbsp; \u0026nbsp; \u0026nbsp;(UACR\u0026ge;300 mg/g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003et (Z)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 152px;\"\u003e\n \u003cp\u003eDM duration(Y)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e9.00(2.75,18.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e10.00（3.00,11.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e-0.857\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.407\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 152px;\"\u003e\n \u003cp\u003eSBP (mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e128.70\u0026plusmn;7.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e134.22\u0026plusmn;14.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e-1.135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e0.263\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 152px;\"\u003e\n \u003cp\u003eDBP (mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e84.30\u0026plusmn;10.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e83.61\u0026plusmn;6.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.196\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e0.848\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 152px;\"\u003e\n \u003cp\u003eALB(g/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e42.85(40.18,45.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e36.55(28.08,39.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e-3.529\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e＜0.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 152px;\"\u003e\n \u003cp\u003eBUN (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e7.01(5.79,8.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e7.94(6.11,11.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e-1.065\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.298\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 152px;\"\u003e\n \u003cp\u003eScr(\u0026mu;mol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e123.70(63.45,155.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e129.05(92.50,175.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e-0.905\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.378\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eeGFR[ml/min\u0026middot;1.73 m\u003csup\u003e2\u003c/sup\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e54.00(45.50,110.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e50.50(38.00,82.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e-1.186\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.240\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 152px;\"\u003e\n \u003cp\u003eFBG (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e6.42(5.33,8.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e6.53（4.89,9.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e-0.080\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.948\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 152px;\"\u003e\n \u003cp\u003eHbAc1(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e6.65(6.15,8.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e7.60(6.53,8.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e-0.893\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.378\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 152px;\"\u003e\n \u003cp\u003eTC (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e4.30(3.36,5.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e5.36(4.39,6.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e-2.423\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.014*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 152px;\"\u003e\n \u003cp\u003eTG (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e1.46(1.00,3.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e1.87(1.41,2.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e-0.559\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.591\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 152px;\"\u003e\n \u003cp\u003eCRP(mg/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e2.58(0.92,6.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e1.09(0.65,1.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e-1.505\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.134\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 152px;\"\u003e\n \u003cp\u003eUACR(mg/g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e77.00(32.50,197.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e2409.4(627.50,4668.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e-4.714\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e＜0.001***\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 152px;\"\u003e\n \u003cp\u003eU-TRF（mg/L）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e5.17(0.58,9.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e81.51(35.17,151.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e-4.394\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e＜0.001***\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 152px;\"\u003e\n \u003cp\u003euIgG（mg/L）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e11.32(4.17,17.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e154.89(59.27,450.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e-4.581\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e＜0.001***\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 152px;\"\u003e\n \u003cp\u003eU-\u0026alpha;1-MG (mg/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e12.67(6.13,27.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e33.02(16.38,54.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e-2.503\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e＜0.001***\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 152px;\"\u003e\n \u003cp\u003eU-\u0026beta;2-MG (mg/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e0.27(0.08,1.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e0.63(0.21,8.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e-1.678\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.096\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 600px;\"\u003e\n \u003cp\u003e*Significant level at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026le;\u0026thinsp;0.05 and *** significant level at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026le;\u0026thinsp;0.001. \u003cem\u003eDM\u003c/em\u003e diabetes mellitus; \u003cem\u003eSBP\u003c/em\u003e systolic blood pressure; \u003cem\u003eDBP\u003c/em\u003e diastolic blood pressure; \u003cem\u003eALB\u003c/em\u003e albumin; \u003cem\u003eBUN\u003c/em\u003e blood urea nitrogen; \u003cem\u003eScr\u003c/em\u003e serum creatinine; \u003cem\u003eeGFR\u003c/em\u003e estimated glomerular filtration rate; \u003cem\u003eFBG\u003c/em\u003e fasting blood glucose; \u003cem\u003eHbAc1\u003c/em\u003e glycosylated haemoglobin; \u003cem\u003eTC\u003c/em\u003e total cholesterol; \u003cem\u003eTG\u003c/em\u003e triglyceride; \u003cem\u003eCRP\u003c/em\u003e C-reactive protein; \u003cem\u003eUACR\u003c/em\u003e urinary creatinine; \u003cem\u003eU-TRF\u003c/em\u003e urinary transferrin; \u003cem\u003euIgG\u003c/em\u003e urinary immunoglobulin G; \u003cem\u003eU-\u0026alpha;1-MG\u003c/em\u003e urinary-\u0026alpha;1-microglobulin; \u003cem\u003eU-\u0026beta;2-MG\u003c/em\u003e urinary-\u0026beta;2-microglobulin\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"614\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 443px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e Comparison of pathological data of DKD patients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eVariables\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003eDKD1(n = 10) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(UACR 30-299 mg/g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 118px;\"\u003e\n \u003cp\u003eDKD2(n = 36) \u0026nbsp; \u0026nbsp; \u0026nbsp; (UACR\u0026ge;300 mg/g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003eZ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eGlomerular lesions, n (n%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 118px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 136px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e3.207\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e0.001***\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eI\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 118px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 136px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eIIa\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 118px;\"\u003e\n \u003cp\u003e9(90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 136px;\"\u003e\n \u003cp\u003e12(33.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eIIb\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 118px;\"\u003e\n \u003cp\u003e1(10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 136px;\"\u003e\n \u003cp\u003e3(8.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eIII\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 118px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 136px;\"\u003e\n \u003cp\u003e14(38.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eIV\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 118px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 136px;\"\u003e\n \u003cp\u003e7(19.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eIFTA, n (n%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 118px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 136px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e1.977\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e0.096\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eScore 0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 118px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 136px;\"\u003e\n \u003cp\u003e1(2.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eScore 1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 118px;\"\u003e\n \u003cp\u003e5(50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 136px;\"\u003e\n \u003cp\u003e6(16.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eScore 2\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 118px;\"\u003e\n \u003cp\u003e5(50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 136px;\"\u003e\n \u003cp\u003e25(69.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eScore 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 118px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 136px;\"\u003e\n \u003cp\u003e4(11.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eInterstitial inflammation, n (n%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 118px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 136px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e1.089\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e0.646\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eScore 0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 118px;\"\u003e\n \u003cp\u003e1(10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 136px;\"\u003e\n \u003cp\u003e1(2.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eScore 1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 118px;\"\u003e\n \u003cp\u003e9(90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 136px;\"\u003e\n \u003cp\u003e34(94.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eScore 2\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 118px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 136px;\"\u003e\n \u003cp\u003e1(2.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eArteriolar hyalinosis, n (n%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 118px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 136px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e3.143\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e0.005**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eScore 0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 118px;\"\u003e\n \u003cp\u003e1(10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 136px;\"\u003e\n \u003cp\u003e1(2.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eScore 1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 118px;\"\u003e\n \u003cp\u003e8(80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 136px;\"\u003e\n \u003cp\u003e11(30.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eScore 2\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 118px;\"\u003e\n \u003cp\u003e1(10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 136px;\"\u003e\n \u003cp\u003e24(66.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eArteriosclerosis, n (n%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 118px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 136px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e4.129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e0.000***\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eScore 0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 118px;\"\u003e\n \u003cp\u003e2(20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 136px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eScore 1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 118px;\"\u003e\n \u003cp\u003e8(80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 136px;\"\u003e\n \u003cp\u003e11(30.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eScore 2\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 118px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 136px;\"\u003e\n \u003cp\u003e25(69.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"bottom\" style=\"width: 614px;\"\u003e\n \u003cp\u003e**Significant level at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026le;\u0026thinsp;0.01 and *** significant level at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026le;\u0026thinsp;0.001.\u003cem\u003e\u0026nbsp;IFTA\u003c/em\u003e interstitial fibrosis and tubular atrophy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"105%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 4\u0026nbsp;\u003c/strong\u003eCorrelation analysis between circ-0069561 level and clinicopathological\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 31px;\"\u003e\n \u003cp\u003eVariables\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003ecirc-0069561\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 31px;\"\u003e\n \u003cp\u003eCorrelation Coefficient (r)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003eRenal function indices\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003eBUN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e0.297\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e0.045*\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003eScr\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e0.049\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e0.745\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003eeGFR\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e-0.034\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e0.825\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003eUrine test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003eUACR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e0.306\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e0.039*\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003eU-TRF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e0.254\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e0.088\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003euIgG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e0.202\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e0.179\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003eU-\u0026alpha;1-MG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e0.072\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e0.634\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003eU-\u0026beta;2-MG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e0.072\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e0.635\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003eOther serum indices\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003eALB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e-0.113\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e0.456\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003eFBG\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e0.038\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e0.800\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003eHbAc1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e0.241\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e0.107\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003eTC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e0.035\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e0.816\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003eTG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e-0.001\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e0.993\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003eCRP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e-0.085\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e0.572\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003ePathological data\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003eGlomerular lesions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e0.304\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e0.040*\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003eIFTA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e0.149\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e0.323\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003eInterstitial inflammation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e0.376\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e0.010**\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003eArteriolar hyalinosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e0.415\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e0.004**\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003eArteriosclerosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e0.526\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e0.000***\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e*Significant level at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026le;\u0026thinsp;0.05, **Significant level at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026le;\u0026thinsp;0.01 and *** significant level at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026le;\u0026thinsp;0.001. \u003cem\u003eALB\u003c/em\u003e albumin; \u003cem\u003eBUN\u003c/em\u003e blood urea nitrogen; \u003cem\u003eScr\u003c/em\u003e serum creatinine; \u003cem\u003eeGFR\u003c/em\u003e estimated glomerular filtration rate; \u003cem\u003eFBG\u003c/em\u003e fasting blood glucose; \u003cem\u003eHbAc1\u003c/em\u003e glycosylated haemoglobin; \u003cem\u003eTC\u003c/em\u003e total cholesterol; \u003cem\u003eTG\u003c/em\u003e triglyceride; \u003cem\u003eCRP\u003c/em\u003e C-reactive protein; \u003cem\u003eUACR\u003c/em\u003e urinary creatinine; \u003cem\u003eU-TRF\u003c/em\u003e urinary transferrin; \u003cem\u003euIgG\u003c/em\u003e urinary immunoglobulin G; \u003cem\u003eU-\u0026alpha;1-MG\u003c/em\u003e urinary-\u0026alpha;1-microglobulin; \u003cem\u003eU-\u0026beta;2-MG\u003c/em\u003e urinary-\u0026beta;2-microglobulin; \u003cem\u003eIFTA\u003c/em\u003e interstitial fibrosis and tubular atrophy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"607\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"bottom\" style=\"width: 45.5385%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 5\u003c/strong\u003e Binary logistic regression analysis.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 18.7469%;\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 17.2823%;\"\u003e\n \u003cp\u003eUnivariate analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 20.895%;\"\u003e\n \u003cp\u003eMultivariate analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 7.0301%;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3499%;\"\u003e\n \u003cp\u003eOR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.1041%;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7909%;\"\u003e\n \u003cp\u003eOR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18.7469%;\"\u003e\n \u003cp\u003ecirc-0069561\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.0301%;\"\u003e\n \u003cp\u003e0.004**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3499%;\"\u003e\n \u003cp\u003e1.382-5.426\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.1041%;\"\u003e\n \u003cp\u003e0.013*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7909%;\"\u003e\n \u003cp\u003e1.220-5.542\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18.7469%;\"\u003e\n \u003cp\u003eALB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.0301%;\"\u003e\n \u003cp\u003e0.009**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3499%;\"\u003e\n \u003cp\u003e0.583-0.925\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.1041%;\"\u003e\n \u003cp\u003e0.023*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7909%;\"\u003e\n \u003cp\u003e0.615-0.964\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18.7469%;\"\u003e\n \u003cp\u003eTC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.0301%;\"\u003e\n \u003cp\u003e0.026*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3499%;\"\u003e\n \u003cp\u003e1.121-6.020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.1041%;\"\u003e\n \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7909%;\"\u003e\n \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18.7469%;\"\u003e\n \u003cp\u003eU-TRF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.0301%;\"\u003e\n \u003cp\u003e0.014*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3499%;\"\u003e\n \u003cp\u003e1.040-1.402\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.1041%;\"\u003e\n \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7909%;\"\u003e\n \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18.7469%;\"\u003e\n \u003cp\u003euIgG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.0301%;\"\u003e\n \u003cp\u003e0.031*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3499%;\"\u003e\n \u003cp\u003e1.014-1.352\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.1041%;\"\u003e\n \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7909%;\"\u003e\n \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18.7469%;\"\u003e\n \u003cp\u003eU-\u0026alpha;1-MG\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.0301%;\"\u003e\n \u003cp\u003e0.031*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3499%;\"\u003e\n \u003cp\u003e1.014-1.352\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.1041%;\"\u003e\n \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7909%;\"\u003e\n \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18.7469%;\"\u003e\n \u003cp\u003eGlomerular lesions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.0301%;\"\u003e\n \u003cp\u003e0.022*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3499%;\"\u003e\n \u003cp\u003e1.320-34.804\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.1041%;\"\u003e\n \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7909%;\"\u003e\n \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18.7469%;\"\u003e\n \u003cp\u003eArteriolar hyalinosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.0301%;\"\u003e\n \u003cp\u003e0.009**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3499%;\"\u003e\n \u003cp\u003e1.668-37.539\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.1041%;\"\u003e\n \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7909%;\"\u003e\n \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 59.1701%;\"\u003e\n \u003cp\u003e*Significant level at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026le;\u0026thinsp;0.05 and ** significant level at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026le;\u0026thinsp;0.01. Circ-0069561\u003csup\u003ea\u003c/sup\u003e=circ-0069561*50 for inclusion in binary logistics regression; \u003cem\u003eALB\u003c/em\u003e albumin; \u003cem\u003eTC\u003c/em\u003e total cholesterol; \u003cem\u003eU-TRF\u003c/em\u003e urinary transferrin; \u003cem\u003euIgG\u003c/em\u003e urinary immunoglobulin G; \u003cem\u003eU-\u0026alpha;1-MG\u003c/em\u003e urinary-\u0026alpha;1-microglobulin\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\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":"CircRNAs, Diabetic kidney disease, Transcriptome sequencing, Ferroptosis","lastPublishedDoi":"10.21203/rs.3.rs-5465308/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5465308/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCircular RNAs (circRNAs) are non-coding RNAs that play a critical role in disease etiology. But the role of circRNAs in diabetic kidney disease (DKD) remains unknown. We performed whole high-throughput RNA sequencing (RNA-seq) of kidney tissues from clinical DKD patients and controls. The top 10 up-regulated circular RNAs were selected by RT-PCR validation, and the findings showed a substantial increase in the expression level of circ-0069561. RT-PCR and fluorescent in situ hybridization (FISH) confirmed that circ-0069561 expression increased both renal tissues of type 2 diabetic mice and DKD patients, with a glomerulus-specific location. Circ-0069561 expression in kidney tissue was significantly correlated with UACR, glomerular lesions, arteriolar hyalinosis and arteriosclerosis. The expression level of circ-0069561 and plasma albumin (ALB) level were independent risk factors for macroalbuminuria. Circ-0069561 demonstrated a strong diagnostic value in major proteinuria, according to the ROC curves (area under the curve\u0026thinsp;=\u0026thinsp;0.889). CircRNA-miRNA-mRNA network indicated that the pathophysiology of DKD may involve ferroptosis. Podocyte damage and ferroptosis caused by high glucose were attenuated by silencing circ-0069561, according to in vitro examinations. Together, the findings suggest that circ-0069561 may influence the progression of DKD by causing ferroptosis of podocytes. The findings of this study provide new insights into the cause and progression of DKD.\u003c/p\u003e","manuscriptTitle":"Upregulation of circ-0069561 promotes diabetic kidney disease progression","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-18 17:57:52","doi":"10.21203/rs.3.rs-5465308/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":"1da0d8f2-4fb6-411a-ac95-68c304d51b61","owner":[],"postedDate":"December 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-12-18T17:57:54+00:00","versionOfRecord":[],"versionCreatedAt":"2024-12-18 17:57:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5465308","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5465308","identity":"rs-5465308","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}