# Study on the Mechanism of circRNA Regulating the miRNA Level in Nephrotic Syndrome

Authors: Qianyu Li; Min Yin; Zhiping Zhang; Yuanzhi Yu; Feng Liu
Journal: Evidence-Based Complementary and Alternative Medicine
 (2022)

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## Abstract

Background. Nephrotic syndrome is an enormous public healthy threaten, which causes a variety of complications and secondary disease; however, the molecular mechanism of nephrotic syndrome remains unclear. Methods. In our study, RNA-seq were used to test the transcription level of patients with nephrotic syndrome, in order to investigate the interaction of circRNA-miRNA-mRNA in nephrotic syndrome patients. Results. Consistent with our hypothesis, miRNAs were confirmed to be associated with nephrotic syndrome, majority of their targeting circRNAs downregulated in nephrotic syndrome patients and at the same time, the KEGG pathway analysis found that target genes of the circRNAs bonding miRNAs was highly correlated with the occurrence of kidney diseases. Conclusion. Thus, we can draw a conclusion that downregulated circRNAs cause miRNA expressing aberrant and then affect the expression level of mRNA, finally leading to the generation of nephrotic syndrome.


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## Body

## 1. Introduction

The kidney is an important organ for the removal of metabolic waste and water electrolytes and metabolites. When inflammatory lesions and immune complexes occur that disrupt the integrity of the glomerular filtration membrane or reduce its negative charge, permeability increases and manifests as hematuria and proteinuria [1]. Nephrotic syndrome is characterized by massive proteinuria, hypoproteinemia, edema, and dyslipidemia and is a clinical condition with high morbidity and mortality in patients with kidney diseases in China [2]. Its pathogenesis is the destruction of the glomerular filtration barrier due to various causes, which may lead to an irreversible end-stage renal disease (ESRD) if patients are left untreated [3]. The diagnosis of nephrotic syndrome in recent years has been based on clinical symptoms, including features such as increased proteinuria, hypoproteinemia, and edema, and is clinically known as nephrotic syndrome and can be divided into three categories: primary, secondary, and genetic [4, 5]. In patients with nephrotic syndrome, lesions of the glomerulus and glomerular basement membrane and alterations in plasma osmolality lead to the production of proteinuria and oedema [6, 7].Primary nephrotic syndrome (PNS) is the most prevalent kidney disease and a main cause of chronic kidney disease (CKD), but the pathogenesis of PNS is not completely tangible [8]. Some researchers hypothesize that PNS may be caused by dysregulation of T lymphocytes or T cell dysfunction [9, 10]. It is known that γδT cells were involved in the progression of IgA nephropathy to renal failure, and further research found that the balance between Th17 cells and Treg cells is essential to PNS development [11, 12]. Podocyte damage is also a major cause of nephrotic syndrome. Podocytes are highly specialized cells of the visceral epithelium that are found in the glomerular membrane of the kidney, and when podocytes are broken down or destroyed, damage to the terminal barrier of the glomerular filtration membrane will lead to leakage of urinary proteins [13]. Patients in this study are just diagnosed with nephrotic syndrome excluding the interference of other disease, such as heart diseases and diabetes mellitus. Secondary nephrotic syndrome and hereditary nephropathy were excluded by renal biopsy.Circular RNA (circRNA) is a newly discovered noncoding RNA (ncRNA), which is the latest research hotspot in RNA field [13]. Unlike linear RNA that contains a 5′ cap and 3′ adenosine tail, circRNA forms a special covalently closed loop that has neither 5′-3′ nor polyA tail [14]; the inherent stability of circRNAs is conferred by their circular structure and exonuclease resistance [15]. Previous researchers found that some miRNAs are abnormally expressed in patients with nephrotic syndrome. MiRNAs are important in maintaining the homeostasis of both physiological and pathological conditions [16]. The aberrant expression of miR-148b in peripheral blood mononuclear cells is associated with aberrant glycosylation of IgA1 in IgA nephropathy [17]. Many patients with cancer, cardiovascular, and renal diseases have confirmed that their miRNA expression level is significantly different compared to that of a normal human [18]. Clement et al. found that miR-30a-5p, miR-151-3p, miR-150, miR-191, and miR-19b were highly expressed in serum of children with nephrotic syndrome as compared to healthy controls [19]. CircRNA is characterized by its universality, conservatism, specificity, stability, and high abundance expression, which make circRNAs as a potential marker of disease screening and treatment, though there is restricted evidence between circRNA and primary nephrotic syndrome. Given the relationship between circRNA and miRNA and the relationship between miRNA and nephrotic syndrome, we hypothesize that there is some connection between circRNA and nephrotic syndrome.


## 2. Methods

### 2.1. RNA-Seq Analysis

Total RNA was extracted from peripheral blood. Transcriptome high-throughput sequencing and subsequent bioinformatics analysis were done by Cloud-Seq Biotech (Shanghai, China). RNA quantification and quality assurance by nanodrop ND-1000(Thermo Fisher Scientific, Waltham, MA, USA). All RNA samples used in this study passed the quality control based on a qualified ratio of OD260 to OD280 (1.8∼2.1). Denaturalized agarose gel electrophoresis was used to measure RNA integrity and gDNA contamination. Libraries were controlled for quality and quantified using the BioAnalyzer 2100 system (Agilent Technologies, USA). 10 pM libraries were denatured as single-stranded DNA molecules, captured on Illumina flow cells, amplified in situ as clusters, and finally sequenced for 150 cycles on a Illumina HiSeq Sequencer.


### 2.2. circRNA Profiling Analysis and Quantification

The high-quality reads were aligned to the reference genome/transcriptome and circRNAs were detected and identified by DCC software. EdgeR software was used to normalize the data and perform differentially expressed circRNA analysis. Compared with the classical transcription, circRNAs are characterized by loop splicing. We use the number of loops splicing reads as the expression level of circRNA. With the TMM method of edgeR, original junction reads were standardized according to the sequencing depth and degree of variation, and log2 transformation was performed to obtain the logCPM value. Fold change ≥2 andP value ≤0.05 were used as thresholds for differentially expressed circRNAs. To generate the profiling of differentially expressed circRNAs between nephrotic syndrome patients and healthy people, the hierarchical clustering analysis was performed based on the expression levels of all identified circRNAs and the significant difference between nephrotic syndrome patients and healthy people. The predicted functions of the differentially expressed circRNAs between nephrotic syndrome patients and healthy people were obtained by GO and KEGG analysis.


### 2.3. Real-Time qPCR of circRNAs

For each sample, after image and base recognition, the raw reads were harvested from the Illumina HiSeq sequencer. We use the Cutadapt software to splice low-quality reads for high-quality clean reads. The clean reads were mapped to the human reference genome (UCSC hg19) obtained from UCSC genome database, guided by the Ensembl transcriptome (v75) gtf file; DCC software was used for loop RNA detection.


## 2.1. RNA-Seq Analysis

Total RNA was extracted from peripheral blood. Transcriptome high-throughput sequencing and subsequent bioinformatics analysis were done by Cloud-Seq Biotech (Shanghai, China). RNA quantification and quality assurance by nanodrop ND-1000(Thermo Fisher Scientific, Waltham, MA, USA). All RNA samples used in this study passed the quality control based on a qualified ratio of OD260 to OD280 (1.8∼2.1). Denaturalized agarose gel electrophoresis was used to measure RNA integrity and gDNA contamination. Libraries were controlled for quality and quantified using the BioAnalyzer 2100 system (Agilent Technologies, USA). 10 pM libraries were denatured as single-stranded DNA molecules, captured on Illumina flow cells, amplified in situ as clusters, and finally sequenced for 150 cycles on a Illumina HiSeq Sequencer.


## 2.2. circRNA Profiling Analysis and Quantification

The high-quality reads were aligned to the reference genome/transcriptome and circRNAs were detected and identified by DCC software. EdgeR software was used to normalize the data and perform differentially expressed circRNA analysis. Compared with the classical transcription, circRNAs are characterized by loop splicing. We use the number of loops splicing reads as the expression level of circRNA. With the TMM method of edgeR, original junction reads were standardized according to the sequencing depth and degree of variation, and log2 transformation was performed to obtain the logCPM value. Fold change ≥2 andP value ≤0.05 were used as thresholds for differentially expressed circRNAs. To generate the profiling of differentially expressed circRNAs between nephrotic syndrome patients and healthy people, the hierarchical clustering analysis was performed based on the expression levels of all identified circRNAs and the significant difference between nephrotic syndrome patients and healthy people. The predicted functions of the differentially expressed circRNAs between nephrotic syndrome patients and healthy people were obtained by GO and KEGG analysis.


## 2.3. Real-Time qPCR of circRNAs

For each sample, after image and base recognition, the raw reads were harvested from the Illumina HiSeq sequencer. We use the Cutadapt software to splice low-quality reads for high-quality clean reads. The clean reads were mapped to the human reference genome (UCSC hg19) obtained from UCSC genome database, guided by the Ensembl transcriptome (v75) gtf file; DCC software was used for loop RNA detection.


## 3. Result

### 3.1. Clinical Characteristics of the Patients and Healthy People

Nephrotic syndrome (NS) patients and the healthy people (normal control, NC) were divided into 5 groups, respectively (N = 3). Each group had 2 males and 1 female. RNA-seq were used to analyze the transcription level of the NS and the NC. In NS patients, urinary analysis showed proteinuria (>3.5 g/24 h) and hypoproteinemia (plasma albumin <30 g). The estimated glomerular filtration rate (eGFR) was calculated by the chronic kidney disease epidemiology collaboration (CKD-EPI) equation, there was no significant difference between NS and NC (P>0.05).After harvesting the raw reads, we spliced the low-quality reads into high-quality clean reads, with the clean reads aligned to the human reference genome. In total, we obtained 727.718 M raw reads and 649.576 M clean reads, for a total mapped reads of 476.982 M, with an average mapping ratio of 67.95%.


### 3.2. Peripheral Blood circRNA and mRNA Profile in Nephrotic Syndrome Patients

First, we analyzed the profiling of circRNA in peripheral blood of 15 patients with nephrotic syndrome and 15 healthy people. In total, 5637 distinct circRNAs were harvested, including 1451 upregulated circRNAs and 4186 downregulated circRNAs in NS compared with healthy people. Compared with circRNAs detected from the patients and the health human, the number of the circRNAs in the nephrotic syndrome patients was significantly reduced (Figure1(a)), indicating that in the nephrotic syndrome patients, either circRNA biosynthesis were suppressed or circRNA degradation is promoted, thus resulting in a low expression level. We identified that there were 5 types of circRNAs across RNA-seq, including exonic, intronic, intergenic, antisense, and sense overlap, about 37% of the circRNAs derived from exonic, while 23% of the circRNAs derived from the antisense, intronic and intergenic account for 15%, respectively; only 548 sense overlap circRNAs were detected, accounting for 10% (Figure 1(b)). Combined with the previous result, we examined the proportion of different types in differently expressed circRNAs compared with normal tissues. While the upregulated differentially expressed circRNAs show almost no change compared with the total circRNAs (Figure 1(c)), the proportion in downregulated circRNAs was significantly different; about 70% downregulated circRNAs were exonic circRNAs, only 1% were intronic circRNAs and 2% intergenic circRNAs; the antisense cricRNAs and sense overlap circRNAs with no significant different (Figures 1(d), 1(e)). Analysis of the circRNAs and their host gene revealed that one gene could produce multiple circRNAs, 2833 genes generated 5637 circRNAs in this test, which are consistent with the former research results [17].Figure 1
circRNAs in nephrotic syndrome patients are inhibited. (a) Numbers of circRNAs in nephrotic syndrome patients and healthy human. (b) Statistics of the proportion of total circRNAs after RNA-seq. (c) Statistics of the proportion of upregulated circRNAs. (d) Statistics of the proportion of downregulated circRNAs. (e) Numbers of circRNAs produce from one gene (5637 circRNAs generated from 2833 host genes).
(a)(b)(c)(d)(e)Statistically significant circRNAs and mRNAs differentially expressed between the two groups were shown by fold change andP value (fold change ≥2.0 and P<0.05). 120 circRNAs were differentially expressed between the NS and healthy groups, and of the 120 circRNAs, 21 circRNAs were significantly upregulated and 99 circRNAs were significantly downregulated on clusters heatmap (Figure 2(a)) and volcano plots(Figure 3(a)). Meanwhile, 8375 mRNAs were differentially expressed between the NS group and healthy group. 8321 mRNAs were upregulated and 54 mRNAs were downregulated on cluster heatmap (Figure 2(c)) and volcano plots (Figure 3(b)). The scatter plot confirmed this conclusion (Figures 2(b) and 2(d)). Taken together, the number and expression of circRNAs detected in NS patients were significantly different compared to controls, suggesting that fluctuations in circRNAs may be responsible for the development of nephropathy.Figure 2
Differentially expressed circRNAs and mRNAs cluster analysis. (a) Differentially expressed circRNAs cluster analysis. (b) Scatter plot analysis of different expressed circRNAs. (c) Differentially expressed mRNAs cluster analysis. (d) Scatter plot analysis of differentially expressed mRNAs.
(a)(b)(c)(d)Figure 3
Differentially expressed circRNAs and mRNAs on volcano plots. (a). Volcano plots showed the differential expression of circRNAs between NS and NC. (b). Volcano plots showed the differential expression of mRNAs between NS and NC.
(a)(b)


### 3.3. KEGG Pathway Analysis and circRNA-miRNA-mRNA Co-Network

A large number of specific miRNAs bind to circRNAs, each with its target gene, and we selected six differentially expressed circRNAs among the downregulated circRNAs by machine (Table1). Five of the six circRNAs had five miRNA predicted targets, the other had nine miRNA predicted targets. The network showed that circRNA-miRNA-mRNA had a strong connection with each other (Figure 4). KEGG analysis revealed that target genes of circRNAs that bind to miRNAs are highly associated with the development of renal disease, such as AMPK signaling, Wnt signaling, Hif signaling, and TGF-β signaling. In previous research studies, many miRNAs upregulated in nephrotic syndrome patients, such as hsa-miR-181a-5p, hsa-miR-30a-5p, hsa-miR-205, and many other miRNAs [18–20]. The co-network show that circRNA-miRNA-mRNA had a close relationship.Table 1
Six differentially expressed downregulated circRNAs.
circRNAschr4156696120–156698794+chr2106774514–106782539−chr5107684100–107703654−chr1685667520–85667738+chr4144464662–144465125+chr12109046048–109048186−Figure 4
circRNA-miRNA-mRNA co-network: The network shows the 6 circRNAs (yellow), fourteen mRNA (purple), and the 34 miRNAs (green).


### 3.4. Validation of the circRNA Expression by qPCR

RNA-seq in patients with nephrotic syndrome suggested that most of circRNAs get downregulated. We performed further qPCR validation on the selected 6 circRNAs, the levels of all 6 circRNAs were significantly downregulated in the NS patients compared with the control group (Figure5). The result suggested that the development of nephrotic syndrome may be due to the decrease of circRNAs, thus increasing the expression level of its corresponding miRNA and then activating disease-related signaling pathways, eventually lead to the occurrence of the nephrotic syndrome.Figure 5
The differentially expressed between nephrotic syndrome (NS) patients and healthy (NC). Data are expressed as means ± SD (P<0.05).


## 3.1. Clinical Characteristics of the Patients and Healthy People

Nephrotic syndrome (NS) patients and the healthy people (normal control, NC) were divided into 5 groups, respectively (N = 3). Each group had 2 males and 1 female. RNA-seq were used to analyze the transcription level of the NS and the NC. In NS patients, urinary analysis showed proteinuria (>3.5 g/24 h) and hypoproteinemia (plasma albumin <30 g). The estimated glomerular filtration rate (eGFR) was calculated by the chronic kidney disease epidemiology collaboration (CKD-EPI) equation, there was no significant difference between NS and NC (P>0.05).After harvesting the raw reads, we spliced the low-quality reads into high-quality clean reads, with the clean reads aligned to the human reference genome. In total, we obtained 727.718 M raw reads and 649.576 M clean reads, for a total mapped reads of 476.982 M, with an average mapping ratio of 67.95%.


## 3.2. Peripheral Blood circRNA and mRNA Profile in Nephrotic Syndrome Patients

First, we analyzed the profiling of circRNA in peripheral blood of 15 patients with nephrotic syndrome and 15 healthy people. In total, 5637 distinct circRNAs were harvested, including 1451 upregulated circRNAs and 4186 downregulated circRNAs in NS compared with healthy people. Compared with circRNAs detected from the patients and the health human, the number of the circRNAs in the nephrotic syndrome patients was significantly reduced (Figure1(a)), indicating that in the nephrotic syndrome patients, either circRNA biosynthesis were suppressed or circRNA degradation is promoted, thus resulting in a low expression level. We identified that there were 5 types of circRNAs across RNA-seq, including exonic, intronic, intergenic, antisense, and sense overlap, about 37% of the circRNAs derived from exonic, while 23% of the circRNAs derived from the antisense, intronic and intergenic account for 15%, respectively; only 548 sense overlap circRNAs were detected, accounting for 10% (Figure 1(b)). Combined with the previous result, we examined the proportion of different types in differently expressed circRNAs compared with normal tissues. While the upregulated differentially expressed circRNAs show almost no change compared with the total circRNAs (Figure 1(c)), the proportion in downregulated circRNAs was significantly different; about 70% downregulated circRNAs were exonic circRNAs, only 1% were intronic circRNAs and 2% intergenic circRNAs; the antisense cricRNAs and sense overlap circRNAs with no significant different (Figures 1(d), 1(e)). Analysis of the circRNAs and their host gene revealed that one gene could produce multiple circRNAs, 2833 genes generated 5637 circRNAs in this test, which are consistent with the former research results [17].Figure 1
circRNAs in nephrotic syndrome patients are inhibited. (a) Numbers of circRNAs in nephrotic syndrome patients and healthy human. (b) Statistics of the proportion of total circRNAs after RNA-seq. (c) Statistics of the proportion of upregulated circRNAs. (d) Statistics of the proportion of downregulated circRNAs. (e) Numbers of circRNAs produce from one gene (5637 circRNAs generated from 2833 host genes).
(a)(b)(c)(d)(e)Statistically significant circRNAs and mRNAs differentially expressed between the two groups were shown by fold change andP value (fold change ≥2.0 and P<0.05). 120 circRNAs were differentially expressed between the NS and healthy groups, and of the 120 circRNAs, 21 circRNAs were significantly upregulated and 99 circRNAs were significantly downregulated on clusters heatmap (Figure 2(a)) and volcano plots(Figure 3(a)). Meanwhile, 8375 mRNAs were differentially expressed between the NS group and healthy group. 8321 mRNAs were upregulated and 54 mRNAs were downregulated on cluster heatmap (Figure 2(c)) and volcano plots (Figure 3(b)). The scatter plot confirmed this conclusion (Figures 2(b) and 2(d)). Taken together, the number and expression of circRNAs detected in NS patients were significantly different compared to controls, suggesting that fluctuations in circRNAs may be responsible for the development of nephropathy.Figure 2
Differentially expressed circRNAs and mRNAs cluster analysis. (a) Differentially expressed circRNAs cluster analysis. (b) Scatter plot analysis of different expressed circRNAs. (c) Differentially expressed mRNAs cluster analysis. (d) Scatter plot analysis of differentially expressed mRNAs.
(a)(b)(c)(d)Figure 3
Differentially expressed circRNAs and mRNAs on volcano plots. (a). Volcano plots showed the differential expression of circRNAs between NS and NC. (b). Volcano plots showed the differential expression of mRNAs between NS and NC.
(a)(b)


## 3.3. KEGG Pathway Analysis and circRNA-miRNA-mRNA Co-Network

A large number of specific miRNAs bind to circRNAs, each with its target gene, and we selected six differentially expressed circRNAs among the downregulated circRNAs by machine (Table1). Five of the six circRNAs had five miRNA predicted targets, the other had nine miRNA predicted targets. The network showed that circRNA-miRNA-mRNA had a strong connection with each other (Figure 4). KEGG analysis revealed that target genes of circRNAs that bind to miRNAs are highly associated with the development of renal disease, such as AMPK signaling, Wnt signaling, Hif signaling, and TGF-β signaling. In previous research studies, many miRNAs upregulated in nephrotic syndrome patients, such as hsa-miR-181a-5p, hsa-miR-30a-5p, hsa-miR-205, and many other miRNAs [18–20]. The co-network show that circRNA-miRNA-mRNA had a close relationship.Table 1
Six differentially expressed downregulated circRNAs.
circRNAschr4156696120–156698794+chr2106774514–106782539−chr5107684100–107703654−chr1685667520–85667738+chr4144464662–144465125+chr12109046048–109048186−Figure 4
circRNA-miRNA-mRNA co-network: The network shows the 6 circRNAs (yellow), fourteen mRNA (purple), and the 34 miRNAs (green).


## 3.4. Validation of the circRNA Expression by qPCR

RNA-seq in patients with nephrotic syndrome suggested that most of circRNAs get downregulated. We performed further qPCR validation on the selected 6 circRNAs, the levels of all 6 circRNAs were significantly downregulated in the NS patients compared with the control group (Figure5). The result suggested that the development of nephrotic syndrome may be due to the decrease of circRNAs, thus increasing the expression level of its corresponding miRNA and then activating disease-related signaling pathways, eventually lead to the occurrence of the nephrotic syndrome.Figure 5
The differentially expressed between nephrotic syndrome (NS) patients and healthy (NC). Data are expressed as means ± SD (P<0.05).


## 4. Discussion

Hepatorenal syndrome is a functional renal failure that occurs late in the course of severe liver disease in patients with no apparent organic lesions of the kidneys and is characterized by renal impairment, impaired arterial circulation, and marked abnormalities in vasodilatory factors [1–3]. 80% of untreated, rapidly progressive patients with the acute form die within approximately 2 weeks. Abdominal effusion is often present and death can also occur as a result of acute transformation [21]. The exact incidence and prevalence of hepatorenal syndrome is unknown. Hepatorenal syndrome accounts for approximately 11% of kidney damage in hospitalized patients with cirrhosis-refractory ascites and is prone to progression to renal failure, with a high morbidity and mortality rate of approximately 80% to 95% [22].In the past, circRNA was not valued while it was considered as a product of abnormal splicing. With the development of high-throughput sequencing technology, the function of circRNA has gradually been understood [23]. CircRNA contains lots of miRNA response element (MRE), which could bind to miRNA and plays the role as miRNA sponge in cells; circRNA can block out the inhibitory effect of miRNA on its target mRNA and increase the expression level of their targeting mRNA [24, 25]. For example, testis-specific circRNA (SRY), with 16 miR-138 binding sites, can affect various physiological and pathological processes in human through its interaction with miRNAs [26]. EIciRNA binds to U1 snRNP form the EIciRNA-U1 snRNP complex via particular RNA-RNA combination. The complex can enhance its parental gene transcription level after binding to Pol II [27]. Chip-sequencing revealed that circRNA-regulated gene unusual expression is ubiquitous in tumors [28]. 67 circRNAs is deficit in the serum of the colon cancer patients while 257 circRNAs are newly produced, for example, the expression level of circ-KLDHC10 in serum exosomes of patient and normal human is significantly different [29].In this study, we use RNA-seq to detect transcriptome expression level in nephrotic syndrome patients and healthy people (control group), in order to investigate the transcription level in nephrotic syndrome patients and health people. Nephrotic syndrome is divided into primary and secondary nephropathies with a variety of causes. Infection, genetic, and immune factors are all possible causes of nephrotic syndrome, and if nephrotic syndrome is not treated promptly, it can easily lead to various complications and secondary complications. The pathogenesis of nephrotic syndrome is still largely unknown [30–32]. For the clinical examination of nephrotic syndrome, there are no definitive molecular markers to identify nephrotic syndrome, other than testing for general biochemical parameters and only performing re-puncture tests that are harmful to the patient [33].CircRNAs are RNA loops which spliced from transcriptome that are widely expressed in cells, furthermore, deep sequencing combined with novel bioinformatics were used to analysis circRNAs [34]. Previous researchers found that expressions of circRNAs are tissue-specific, they could participate in posttranscriptional of genes and regulate their expression level [35]. Due to circRNAs specific biological structure and characteristics [36], they have a great potential work as markers of diseases [37].In our test, 15 nephrotic syndrome patients were divided into 5 groups randomly. RNA-seq were used to detect the transcription level of patients and healthy people. After analyzing all data, we found that the circRNAs expression level in nephrotic syndrome patients and healthy people is significantly different; the amount of circRNA detected in nephropathy patients is significantly lower than that of healthy human circRNAs. MiRNAs reported in the previous research are upregulated in nephropathy, the vast majority of circRNAs targeted by these miRNAs in nephropathy patients were downregulated, indicating that the miRNAs rising level is related to the decreasing level of circRNAs. KEGG pathway analysis confirmed the former conclusion. Finally, we have identified several circRNAs that may associate with nephrotic syndrome, their downregulated expression in patients will lead to the upregulation of their targeting miRNAs, inducing targeting mRNAs to be upregulated and then generate the nephrotic syndrome. The mechanisms by which these circRNAs interact with miRNAs and mRNAs are unclear, but these circRNAs may be potential targets for the treatment of kidney disease, in line with the findings of Yu et al. that circRNAs are novel diagnostic biomarkers and therapeutic targets for kidney disease [38], but whether these circRNAs can be biomarkers for nephrotic syndromes requires further testing.The conclusion that these circRNAs in our study may be potential targets for the treatment of kidney disease is based on reasonable analogies to existing studies, such as the finding that ciRS-7 is highly expressed in renal cell carcinoma tumor tissues and cell lines and may serve as a prognostic marker, and further evidence that ciRS-7 acts as a “ceRNA” for miR-139-3p, preventing TAGLN degradation and promoting the development and metastasis of renal cell carcinoma through the PI3K/AKT signaling pathway [39]. ciRS-7 is highly expressed in RCC tumor tissues and cell lines, and this high expression correlates with tumor size, high Fuhrman grading, and low survival [40]. In vivo depletion of ciRS-7 significantly inhibited RCC cell proliferation, invasion, tumor growth, and metastasis, while the overexpression of ciRS-7 did the opposite. Mechanistically, ciRS-7 acts as a “ceRNA” for miR-139-3p, blocking TAGLN degradation through the PI3K/AKT signaling pathway and promoting RCC progression and metastasis [39]. In addition, this study developed a nanocomplex targeting drug-PBAE/si-ciRS-7 that significantly inhibited renal cell carcinoma tumor development and metastasis in vivo, and drug development of this nanocomplex may be a promising gene therapy strategy for renal cell carcinoma with important practical implications for oncology clinical treatment [39]. Our subsequent experiments could produce targeted drugs based on existing findings and posttranslational translation of proteins regulated by circRNAs.However, there are still limitations to our experiments. First, because of currently insurmountable technical limitations, it remains very challenging to investigate the physicochemical properties and mechanisms of circRNAs. Second, although many circRNAs have been demonstrated in renal tissues, their potential role in disease progression remains largely elusive as they are still largely studied in vitro.


## 5. Conclusion

In summary, it can be concluded from these experiments that the downregulation of circRNAs leads to abnormal miRNA expression, which in turn affects mRNA expression levels and ultimately leads to the development of nephrotic syndrome.



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*Source: 3729995-2022-07-11.xml*