Irbesartan ameliorates diabetic kidney injury in db/db mice by restoring circadian rhythm and cell cycle

Introduction

Diabetes mellitus (DM) accounts for more than 30% morbidity of diabetic kidney disease (DKD) patients, which has been regarded as a leading cause of kidney failure and end-stage renal disease worldwide.^[1] Efforts have been made to explore the pathogenesis of DKD and to develop new therapeutic strategies. However, there is still no effective intervention to prevent renal function decline in patients with DKD. Interestingly, although the incidence of diabetes is increasing, multiple studies have demonstrated that strict blood glucose control and the use of renin–angiotensin system (RAS) blockers cause a significant decline in the incidence of DKD.^[2] RAS blockers used in DKD not only reduce proteinuria, but also delay disease progression, which is only partly explained by their hemodynamic effects.^[3]

The intrarenal activation of RAS plays a pivotal role in the pathophysiology of DKD and participates in its progression. As the main effector molecule produced by RAS, angiotensin II (Ang II) can activate Ang II type 1 receptors (AT1R) and type 2 receptors (AT2R), which are crucial for the development of DKD. The activation of AT1R, associated with vasoconstriction, sodium reabsorption, and growth promotion, leads to inflammation and the production of reactive oxygen species (ROS).^[4,5] Therefore, blocking Ang II with an AT1 antagonist has become one of the best clinical options in the treatment of renal disease. Irbesartan is widely used for the treatment of DKD and was shown to ameliorate progressive glomerulosclerosis in animal models and slow disease progression in DKD patients.^[6] However, the molecular mechanisms of how RAS inhibition is used to delay the progression of DKD disease have not been fully elucidated.

Several studies have highlighted the importance of gene expression profiling to elucidate the mechanisms of disease progression and drug therapy.^[7,8] To the best of our knowledge, there is no gene expression profile analysis of irbesartan in DKD treatment. In the present study, high-throughput microarray screening was used to identify the differentially expressed genes (DEGs) in the kidneys of DKD model mice with or without irbesartan treatment. Then, the DEGs were used for gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, gene set enrichment analyses, protein–protein interaction (PPI) network and modules, and microRNA (miRNA)-DEGs network analysis to identify the genes critically involved in the development of DKD, which were followed with validation of DEGs by quantitative real-time polymerase chain reaction (qRT-PCR). These results will provide new insights into the role of irbesartan in the treatment of DKD and guide the clinical use of irbesartan.

Materials and methods

Results

Irbesartan alleviated proteinuria and athological changes in kidney

At the end of the experiment, we detected blood glucose, weight, and urinary albumin excretion, which were markedly increased in db/db mice compared to db/m mice. After 16 weeks of treatment with irbesartan, only urinary albumin excretion showed significantly lower values in the irbesartan treatment group than that in db/db mice (Figure 1A–C), indicating that irbesartan significantly improved the renal function in db/db mice.

Figure 1

Irbesartan alleviates proteinuria and pathological injuries of kidney in db/db mice. (A and B) Body weight and blood glucose were measured at the end of the experiment. (C) Twenty-four-hour urinary albumin was found. The magnification of the images is 400×. (D) PAS staining was used to evaluate the renal injuries (scale bar, 50 μm). (E) Semi-quantitative measurements of mesangial matrix area were performed using PAS staining. Data are presented as the mean ± SEM. ^*P < 0.05, ^**P < 0.01. PAS: periodic acid-Schiff, SEM: standard error of the mean.

Consistent with the proteinuria results, greater mesangial matrix dilation and thicker glomerular basement membrane of kidney were observed in db/db mice than in db/m mice, and these histological injuries were significantly ameliorated in db/db mice treated with irbesartan, as shown in Figure 1D and E.

Microarray data analysis

To explore the pharmacological target of irbesartan for T2DM kidney injury, three mice in each group were selected for renal mRNA expression profile analysis and the DEGs were analyzed. Only genes with |Log FC| <0.5 and FDR <0.25 were considered as DEGs. A total of 472 DEGs were identified, including 300 upregulated genes and 172 downregulated genes in db/db mice with irbesartan treatment, compared to untreated db/db mice. The top 30 genes with the most significant differences are listed in Table 2. DEGs were selected to generate the clustering heat map according to the fold change, and the clustering analysis of DEGs could well distinguish the db/db mice with or without irbesartan treatment (Figure 2A, B).

Figure 2

Identification of DEGs in kidneys of db/db mice with or without irbesartan treatment. (A) Heat map of DEGs between db/db mice and db/db mice + irbesartan. (B) Volcano plot shows the distribution of DEGs. DEGs: differentially expressed genes.

Table 2

Top 30 differentially expressed genes between db/db mice with and without irbesartan

Genes	logFC	P. adj	P-value
Ciart	1.99	0.01748	8.70E-07
Ypel2	-1.19	0.042906	4.27E-06
Gm25279	1.09	0.050326	7.51E-06
Arntl	-1.81	0.06402	1.27E-05
Nfil3	-1.40	0.067422	2.10E-05
Gm26226	-0.83	0.067422	2.28E-05
Gm25401	-1.18	0.067422	2.35E-05
Plk1	0.95	0.071817	3.10E-05
Dbp	1.48	0.071817	3.22E-05
Lama1	0.87	0.07415	4.08E-05
Cdh11	0.74	0.07415	4.40E-05
Ldlr	0.90	0.07415	4.43E-05
Ren1	-0.77	0.085439	5.53E-05
Gm5779	-0.82	0.091245	6.74E-05
Rasl11a	-0.69	0.091245	6.81E-05
Slc16a1	-1.19	0.098574	8.80E-05
Slc25a30	-0.68	0.098574	9.11E-05
Rorc	-0.80	0.098574	9.18E-05
Wsb1	-1.00	0.098574	9.63E-05
Defb19	0.71	0.098574	0.0001
Zbtb16	-1.17	0.098574	0.000106
Nr1d1	1.43	0.098574	0.000114
Gm25383	-0.73	0.098574	0.000116
Gm25099	-0.89	0.098574	0.000127
Gm7241	-0.72	0.098574	0.000133
Ccnb2	1.08	0.098574	0.000135
Gm8765	0.68	0.098574	0.000142
Stard4	0.63	0.098574	0.000143
Hes6	0.63	0.098574	0.000145
Narf	0.70	0.098574	0.000147

1. FC: fold change; P. adj: adjusted P-value.

Functional enrichment analysis and KEGG pathway analysis

To further investigate the biological functions of the DEGs, we performed GO and pathway analysis using DAVID. The results showed that DEGs were involved in several biological process (BP) and KEGG pathways. In the BP ontology, the DEGs were mainly enriched in rhythmic process (GO:0048511), circadian rhythm (GO:0007623), circadian regulation of gene expression (GO:0032922), regulation of circadian rhythm (GO:0042752), and positive regulation of circadian rhythm (GO:0042753) (Figure 3A). To gain further insight into the function of the identified DEGs, KEGG analysis identified four enriched pathways of the DEGs, including circadian rhythm (mmu04710), cell cycle (mmu04110), PI3K-AKT signaling pathway (mmu05206), and miRNAs in cancer (Figure 3B).

Figure 3

GO classification and KEGG pathway analysis of related DEGs. (A) GO enrichment analysis of DEGs in the biological process. (B) KEGG pathway analysis of DEGs. DEGs: differentially expressed genes, GO: gene ontology, KEGG: Kyoto Encyclopedia of Genes and Genomes.

PPI network construction and module analysis

To evaluate the associations between the identified DEGs, a PPI network constructed with the DEGs consisted of 3844 nodes and 6727 edges (Figure 4A). Based on information from the STRING database, the DEGs with higher degrees (degree ≥20) were screened and selected as hub genes, including Mki67, Rps15a-ps5, Rps13, Cdk1, Rps11, Ccna2, Plk1, Gm13777, Rps13a-ps1, Gm6570, Rpl17, Gm17541, Gm8973, Gm16519, Gm4978, Rpl13-ps3, and Rpl28-ps4 (Figure 4B). In addition, the top four most significant modules were selected, and module 1 was mainly enriched in cell cycle. Module 2 was mainly enriched in circadian rhythm. Furthermore, module 3, screened from the PPI network, was enriched in ribosome. Module 4 was enriched in drug metabolism (Figure 5A–D and Table 3).

Figure 4

PPI network constructed with the DEGs to screen crucial genes. (A) PPI network for DEGs between db/db mice with and without irbesartan. Circles represent nodes and lines between nodes represent edges, which indicate DEGs and interactions between two DEGs, respectively. The red circle is the upregulated gene, and the green circle is the downregulated gene. (B) The most significant 30 node degree genes in the PPI network. DEGs: differentially expressed genes, PPI: protein–protein interaction.

Figure 5

Significant modules screened from PPI network. Red circles represent upregulated genes and green ones represent downregulated genes in db/db mice treated with irbesartan. (A) Significant module is related with cell cycle. (B) Significant module is related with circadian rhythm. (C) Significant module is related with ribosome. (D) Significant module is related with drug metabolism. PPI: protein–protein interaction.

Table 3

Significantly enriched functions for differentially expressed genes of the PPI network

Term ID	Term description	Gene count	FDR	Genes
GO:0007623	Circadian rhythm	12	0.0012	Cry1, Rorc, Bhlhe41, Arntl, Npas2, Nfil3, Nr1d1, Klf10, Dbp, Per3, Arntl2, Ciart
GO:0032922	Circadian regulation of gene expression	8	0.0013	Cry1, Rorc, Bhlhe41, Arntl, Npas2, Nr1d1, Per3, Ciart
GO:0042752	Regulation of circadian rhythm	10	0.0013	Cry1, Rorc, Arntl, Npas2, Top2a, Nr1d1, Klf10, Nr1d2, Per3, Arntl2
GO:0048511	Rhythmic process	15	0.0013	Cry1, Rorc, Bhlhe41, Arntl, Npas2, Nfil3, Top2a, Nr1d1, Egr1, Klf10, Dbp, Nr1d2, Per3, Arntl2, Ciart
mmu04710	Circadian rhythm	7	2.55E-05	Cry1, Rorc, Bhlhe41, Arntl, Npas2, Nr1d1, Per3
mmu03010	Ribosome	9	0.002	Rps11, Rplp1, Rpl21, Rps15, Rpl17, Rps2, Rpl30, Rps15a, Rps13
mmu04110	Cell cycle	8	0.006	Cdk1, Myc, Mcm6, Ccna2, Plk1, Ccnb2, Cdc6, Ccnd1

1. FDR: false discovery rate; PPI: protein–protein interaction.

DEGs-related miRNAs

After searching the Mirwalk2 database, we used 222 miRNAs that regulated the above DEGs to construct a miRNA-DEGs network, including 432 interaction pairs and 24 DEGs. Among them, mmu-miR-1970, mmu-miR-703, mmu-miR-466f, mmu-miR-5135, and miR-132-3p were identified to be the differentiated miRNAs according to DEGs from our microarray data, as shown in Figure 6. Tagap1 and Narf were regulated by mmu-miR-1970; Ldlr was regulated by miR-132-3p; Acot2 was regulated by mmu-miR-466f; and Acot2 and Ldlrad2 were regulated by mmu-miR-5135. The results indicate that irbesartan may regulate DEGs by regulating miRNA to improve DKD.

Figure 6

The miRNA–gene interaction network. Red ellipses indicate upregulated genes, and green ellipses indicate downregulated genes. Blue hexagons indicate the identified differential miRNAs from the DEGs. DEGs: differentially expressed genes, miRNA: microRNA.

Validation of hub genes in kidneys of db/db mice with or without irbesartan treatment

According to the PPI network analysis, we verified the mRNA expression of representative genes in two pathways: circadian rhythm and cell cycle. As shown in Figure 7, significant upregulation of Per3 and Dbp genes and significant downregulation of Arntl gene were confirmed in the kidney of db/db mice, which was significantly reversed in irbesartan-treated db/db mice (Figure 7A–C). In addition, the upregulated genes related to cell cycle in db/db mice, Prc1, Ccna2, and Ccnb2, were significantly downregulated by irbesartan (Figure 7D–E). These outcomes were consistent with the microarray results, demonstrating that circadian rhythm and cell cycle may be particularly important mechanisms in the treatment of DKD by irbesartan.

Figure 7

The differentially expressed genes validated by qRT-PCR. (A–C) The expression of circadian rhythm-related genes, including Arntl, Dbp, and Per3. (D, E) The expression of cell cycle-related genes, including Prc1, Ccna2, and Ccnb2. Data are expressed as the mean ± SEM, ^**P < 0.01. qRT-PCR: quantitative real-time polymerase chain reaction, SEM: standard error of the mean.

Discussion

DKD is a major public health problem that harms people’s lives and health, and the main clinical features of DKD are proteinuria and a progressive decline in renal function, which are associated with structural and functional changes in the kidney.^[10] The pathogenesis of DKD is multifactorial, including genetic, metabolic, and hemodynamic factors.^[11] ARBs can effectively reduce urinary protein and delay the decline of renal function, so they are recommended as the first-line treatment of DKD.^[12] There is increasing evidence showing that irbesartan plays a key role in the treatment of DKD, which may be due to blocking the effects of Ang II on blood pressure, renal hemodynamic and nonhemodynamic effects, thereby inhibiting the growth-promoting, profibrotic, and other actions.^[13,14] Previous studies have also shown that irbesartan ameliorates DKD by suppressing the RANKL–RANK–NF-κB pathway in type 2 diabetic db/db mice.^[15] However, the protective mechanism of irbesartan on kidney may be complicated. Microarray gene expression profile is a high-throughput technique that can quickly generate the gene expression pattern of the sample at a given time point, and bioinformatics analysis helps to identify potential DEGs. Therefore, we used microarray gene expression profiles to explore the key genes and pathways of irbesartan in the treatment of DKD, so as to further improve the molecular mechanism of irbesartan therapy for DKD.

In the present study, we observed the kidney injury of db/m mice and db/db mice with or without irbesartan treatment. We found that irbesartan significantly reduced urinary albumin secretion and ameliorated renal histological injuries. To elucidate the underlying molecular mechanisms, we performed microarray profile screening of DEGs in db/db mice with or without irbesartan treatment. Four hundred and seventy-two DEGs were identified, including 300 upregulated genes and 172 downregulated genes, in db/db mice with irbesartan treatment compared to db/db mice. Functional enrichment analysis and KEGG pathway analysis showed DEGs were mainly enriched in circadian rhythm, cell cycle, miRNAs in cancer, and PI3K–AKT signaling pathway. PPI network construction and module analysis were also performed with the DEGs, and several DEGs with higher degrees were identified, including cell cycle, circadian rhythm, ribosome, and drug metabolism. What is more, the results of qRT-PCR were consistent with the results of gene expression microarray, which indicated that specific DEGs might play a key role in the treatment of DKD with irbesartan.

To the best of our knowledge, this study is the first to conduct a high-throughput analysis of gene expression patterns in the kidney of db/db mice and compare it with irbesartan treatment. Analysis of significant enrichment of DEGs in the BP showed the DEGs were mainly enriched in rhythmic process, circadian rhythm, and circadian regulation of gene expression. Circadian rhythm also showed the most significant difference in KEGG analysis, suggesting that abnormal circadian rhythm plays a key role in the occurrence of DKD and may be the vital target for irbesartan treatment. Therefore, renal tissue of mice was used to verify and analyze the expression of three key genes related to the circadian rhythm, including Arntl, Per3, and Dbp. The results revealed that compared to control mice, the model mice had lower expression of Arntl and higher expression of Per3 and Dbp. Importantly, when db/db mice were treated with irbesartan, the expression of Arntl was significantly increased and the expression of Per3 and Dbp was markedly downregulated. It is widely accepted that circadian rhythm is essential for maintaining physiological functions and homeostasis.^[16,17] Circadian rhythm is a universal phenomenon that plays an important role in maintaining physiological processes and regulating the adaptability of the body to internal and external environments. Currently, it is widely believed that the generation and maintenance of circadian rhythm depends on the clock feedback regulation system, which is composed of clock genes (BMAL1, CLOCK, CRY, PER) and clock control genes (Rev-ERBα, RORα, DBP, TEF, and HLF). Mammalian major feedback loops are activated by heterodimeric transcriptional activation of Brain and Muscle ARNT-like 1 (BMAL1 or ARNTL) and Circadian Locomotor Output Cycles protein Kaput (CLOCK). CLOCK and BMAL1 form a heterodimer and combine with the E response element (E-box) in the upstream promoter region of target genes (PER, CRY, Rev-ERBα, and RORα) to initiate the transcription process. The accumulation of PER and CRY proteins negatively regulates transcription of CLOCK–BMAL1 heterodimers. Moreover, Rev-ERBα binds to BMAL1 promoter to inhibit BMAL1 transcription, whereas RORα acts as a positive regulator to promote BMAL1 transcription. In addition, DBP, TEF, HLF, and other CLOCK control genes are also direct target genes of BMAL1–CLOCK heterodimer and participate in the regulation of circadian rhythm.^[18] It has been reported that BMAL1-knockout mice developed circadian rhythm disorders and metabolic damage, including impaired glucose and fatty acid metabolism, which are potential factors that accelerate the development of DKD.^[19]

Circadian rhythm disorders increase the risk of various diseases, including sleep disorders, metabolic diseases, and cancer.^[20,21,22] As far as we know, there are few studies on the biological rhythm of DKD. Several studies have shown that circadian rhythm is strongly associated with chronic kidney disease (CKD), suggesting that it may be a potential mechanism for DKD.^[23,24] Disruption of the circadian clock in animal models has been shown to lead to abnormal blood pressure and disruption of the circadian rhythm pattern of water and electrolyte excretion in urine.^[25] A disrupted circadian rhythm is associated with an increased risk of hypertension, kidney fibrosis, and kidney stones.^[26,27,28] In addition, the renal circadian clock may interfere with the pharmacokinetics and/or pharmacodynamics of various drugs and is, therefore, an important consideration during the treatment of some renal diseases.^[29,30] Temporal pharmacological studies have shown that duration of treatment affects blood pressure control. A clinical study of patients with CKD has shown that antihypertensive drugs taken at night are more effective in controlling the blood pressure than those taken in the morning, suggesting that taking antihypertensive drugs such as valsartan before bedtime can improve the blood pressure in patients with CKD.^[24,31] Irbesartan, an ARB, is widely used in blood pressure control. Previous studies have shown that taking irbesartan once a night has a greater therapeutic effect on blood pressure during sleep than in the morning, as it significantly promotes reduction in blood pressure during sleep.^[32] Circadian rhythm of blood pressure exists in most healthy people, and loss of circadian rhythm of blood pressure can lead to damage of target organs, such as stroke and left ventricular hypertrophy. Irbesartan not only has a good antihypertensive effect, but also can restore the circadian rhythm of blood pressure, which is an effective choice for reducing cardiovascular risk.^[33] The present study demonstrates that irbesartan may improve diabetic renal injuries by restoring the circadian rhythm.

Many studies have shown that excessive proliferation of renal cells can aggravate the progression of glomerular sclerosis and renal interstitial fibrosis.^[34,35] The proliferation of glomerular cells causes the accumulation of extracellular matrix (ECM), which eventually leads to glomerular sclerosis. Inhibition of glomerular cell proliferation significantly reduced ECM accumulation.^[36] Renal interstitial fibrosis is an important pathological change in the progression of DKD to end-stage renal failure, and excessive proliferation of fibroblast cells is the key factor leading to renal interstitial fibrosis.^[35] Therefore, inhibition of fibroblasts may slow down or even reverse renal interstitial fibrosis. In this study, we found that irbesartan can regulate the expression of genes related to cell cycle in the kidney of db/db mice, suggesting that irbesartan may improve DKD by regulating cell proliferation. The protein encoded by Prc1 is involved in cytokinesis and has been shown to be the substrate for a variety of cyclin-dependent kinases (CDKs), and it is present at high levels during the S and G2/M phases of mitosis, but decreases sharply when cells enter the G1 phase.^[37]Ccna2 encodes a highly conserved cyclin protein that promotes transition through G1/S and G2/M by activating CDK2.^[38] It has been found that G2/M arrest in renal tubular epithelial cells leads to renal fibrosis by activating JNK signals and upregulating the production of profibrotic cytokines. Renal fibrosis can be reversed by bypassing G2/M arrest with a p53 inhibitor, suggesting that the cell cycle is a key target for the treatment of CKD.^[39] It has been found that irbesartan regulates the cell cycle by antagonizing AT1R, thus inhibiting the proliferation of breast cancer cells.^[40] Studies have shown that hypertrophy is an important pathological feature of renal diseases such as diabetic nephropathy. Ang II induced renal tubular epithelial cell cycle arrest in G0/G1 phase, resulting in hypertrophy. It was found that cell cycle was significantly reversed after irbesartan treatment, to improve cell hypertrophy.^[41] Our results support the idea that irbesartan may reduce diabetic kidney injury by regulating the cell cycle; however, further mechanistic studies are required.

miRNAs are small noncoding RNAs that regulate gene expression by inducing mRNA degradation to block protein translation. Increasing research evidence shows that miRNAs play a key role in the development of DKD and are expected to become potential biomarkers for DKD. Expression of miRNAs has been analyzed in renal biopsy, urine/urinary exosomes, and total blood/plasma/serum.^[42] Multiple miRNAs, including miR-21-5p, miR-29a-3p, miR-126-3p, miR-192-5p, miR-214-3p, and miR-342-3p, were persistently dysregulated in patients with DKD. These miRNAs are associated with multiple pathways related to the pathogenesis of DKD, such as apoptosis, fibrosis, and accumulation of ECM. ^[43] Therefore, miRNAs play an important role in the treatment and clinical diagnosis of DKD. Experimental evidence showed that Ang II could significantly reduce the expression of miR-133a and miR-29b in cardiomyocytes and increase the expression of its target gene Col1A1, leading to myocardial fibrosis. Irbesartan effectively prevented the downregulation of miR-133a and miR-29b in cardiomyocytes and inhibited the expression of Col1A1 and myocardial fibrosis.^[44] In order to explore whether the therapeutic effect of irbesartan on DKD involved miRNAs, we also predicted miRNAs related to key DEGs. The results suggested that there were five miRNAs with significant differences in our data, including miR-1970, miR-703, miR-466f, miR-5135, and miR-132-3p. In an expression profile of miRNA in the kidney of DKD model mice, it was found that the expression of miR-703 and miR-466f in the kidney of DKD mice was significantly increased, which is consistent with our results.^[45] Studies have found that miR-132-3p promotes cell proliferation by directly regulating BCL2L11, an apoptosis activator, leading to tuberous sclerosis.^[46] In addition, miR-132-3p could also promote oxidative stress by targeting FOXO3, leading to autosomal dominant polycystic kidney disease.^[47] However, there is no report on the above five miRNAs in DKD. Therefore, further experimental studies are needed to prove their role in the occurrence of DKD.

Conclusion

Our study suggests Irbesartan is an effective treatment for DKD, and its mechanism is related to the restoration of circadian rhythm and cell proliferation, and the key role of miRNA may be involved. These conclusions need to be confirmed by further mechanistic studies, and the potential mechanisms need to be further verified.