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Targeting the RUNX3–miR-186-3p–DAT–IGF1R axis as a therapeutic strategy in a Parkinson’s disease model

Abstract

With the increasing age of the population worldwide, the incidence rate of Parkinson’s disease (PD) is increasing annually. Currently, the treatment strategy for PD only improves clinical symptoms. No effective treatment strategy can slow down the progression of the disease. In the present study, whole transcriptome sequencing was used to obtain the mRNA and miRNA expression profiles in a PD mouse model, which revealed the pathogenesis of PD. The transcription factor RUNX3 upregulated the miR-186-3p expression in the PD model. Furthermore, the high miR-186-3p expression in PD can be targeted to inhibit the DAT expression, resulting in a decrease in the dopamine content of dopaminergic neurons. Moreover, miR-186-3p can be targeted to inhibit the IGF1R expression and prevent the activation of the IGF1RP-PI3KP-AKT pathway, thus increasing the apoptosis of dopaminergic neurons by regulating the cytochrome cBaxcleaved caspase-3 pathway. Our research showed that the RUNX3miR-186-3pDATIGF1R axis plays a key role in the pathogenesis of PD, and miR-186-3p is a potential target for the treatment of PD.

Introduction

In terms of incidence rate, Parkinson’s disease (PD) is the second most common neurodegenerative disease after Alzheimer’s disease, mainly affecting the motor function of the mesencephalic-striatal extrapyramidal system [1]. The clinical manifestations of PD in patients include symptoms and signs related to the motor system, such as resting tremor, muscle stiffness and motor delay, as well as non-motor symptoms, such as constipation, sleep disorders and depression [2, 3]. These symptoms gradually worsen with age and severely affect the quality of life of PD patients. With the advancements in PD research, the pathogenic mechanism underlying the formation of Lewy bodies by the key pathological protein α-synuclein (α-syn) in PD has been revealed [4]. Lewy bodies can cause destabilize mitochondrial electron transport chains, disrupt the mitochondrial oxidative metabolism, and damage the lysosomal and proteasomal degradation systems. They can spread from neuron synapses to the surrounding healthy neurons, further disrupting the neuronal membrane structure and synaptic transmission, ultimately leading to the degeneration of dopaminergic neurons [5, 6]. Currently, an effective treatment for PD is oral levodopa, which increases the dopamine (DA) content in the midbrain striatum. The drug has good therapeutic effects for early-to-middle-stage PD patients, representing the “honeymoon period” of treatment. As PD progresses to its advanced stages, the dopaminergic neurons continue to degenerate, leading to severe movement disorders, such as levodopa-induced dyskinesia [7, 8]. The current PD treatment can only improve clinical symptoms but cannot effectively prevent disease progression, imposing a heavy economic burden on families and society [9]. Therefore, this study investigated the pathogenesis of PD and explored novel therapeutic targets for PD.

Transcription factors (TFs) recognize specific sequences on gene promoters and play a role in regulating gene expression with tissue specificity [10, 11]. Research has found that transcription factor EB (TFEB) plays a regulatory role in various diseases, participating in cell stress response, autophagy, and signaling pathways related to lysosomal dysfunction and neurodegenerative diseases [12]. TFEB overexpression or increased nuclear translocation can reduce the aggregation of α-syn protein in PD. Co-immunoprecipitation of TFEB and α-syn protein reveals that α-syn can prevent TFEB activation, leading to abnormal α-syn aggregation and the development of PD [13]. In addition, transcriptional activator STAT3 transfer to the promoter region of miR-7 to activate its expression. High miR-7 expression inhibits the NEDD4 gene expression, leading to a decrease in LRRK2 protein expression through ubiquitination degradation and thus participating in the occurrence of PD [14]. The AT motif binding factor 1 binds to the runt domain transcription factor 3 (RUNX3) in response to TGF-β signaling transduction, further activating TGF-β translocation into the nucleus, playing a role in tumor suppression [15]. In addition, RUNX3 can increase miR-148a-3p expression, leading to a decrease in cell proliferation and promoting cell apoptosis [16]. In summary, the regulation of gene expression by TFs has an key role in the pathogenesis of PD, and research on RUNX3 can improve our understanding of the pathogenesis of PD.

microRNAs (miRNAs) have the important function in the pathogenesis of neurodegenerative diseases [17, 18]. For instance, miR-3473b is involved in the pathogenesis of PD by regulating neuronal autophagy [19]. MiR-29c activates the microglial inflammatory response by inhibiting NLRP3 expression, leading to the development of PD [20]. MiR-186-3p is located on chromosome 3 and has a mature sequence length of 22nt. It is highly conserved and inhibits the proliferation and migration ability of cervical cancer cells by suppressing the expression of insulin-like growth factor 1 (IGF1) protein, increasing the apoptosis rate of cervical cancer cells [21]. Additionally, it can suppress the expression of keratin 18 and negatively regulate the mitogen-activated protein kinase (MAPK) signaling pathway to inhibit proliferation and promote apoptosis in colon cancer cells [22]. In addition, mini-chromosome maintenance complex component 2 (MCM2) can promote cervical cancer cell proliferation and inhibit apoptosis. However, high expression levels of miR-186-3p can suppress MCM2 protein expression, thereby inhibiting cervical cancer cell proliferation and promoting apoptosis [23]. These studies reveal the important role of miRNA in neurodegeneration. Consequently, we explored the pathogenic mechanism underlying the role of miR-186-3p in the PD model.

The solute carrier family 6 member 3 (slc6a3) gene encodes the dopamine transporter (DAT) protein, which plays a crucial role in transporting extracellular DA into dopaminergic neurons [24]. DAT is dependent on the membrane potential during the process of DA transportation. The slc6a3 gene expression directly affects the quantity of DAT protein, thereby affecting DA transportation [25]. Previous research on DAT has mainly focused on the association between polymorphism of a 40-base pair repeat sequence in the 3ʹUTR of the slc6a3 gene and the onset of PD, as well as the effect of slc6a3 gene mutations on the transport function of DAT. Studies have found that the rs397595 polymorphism in the slc6a3 gene has a significant correlation with the risk of PD [26, 27]. The insulin-like growth factor 1 receptor (IGF1R) protein is classified into the receptor tyrosine kinase family. IGF1R is activated by insulin-like growth factors and initiates intracellular signal transduction by phosphorylating its tyrosine kinase domain [28]. IGF1R mainly activates the P-PI3KP-AKT signaling pathways. The IRS-1 phosphorylation by the activated tyrosine kinase can activate PI3K, initiating the P-PI3KP-AKT pathway to inhibit cell apoptosis [29, 30]. Research has found that upregulating the IGF1 protein expression in the PD model can activate the IGF1RPI3KAktmTOR signaling pathway and inhibit autophagy induced by MPTP/MPP+ in dopaminergic neurons [31]. Previous research has confirmed that the pathway regulated by IGF1R plays a critical role in the occurrence and development of PD. In this study, we explored the function of DAT and the mechanism underlying the role of IGF1R in PD, which can provide an important strategy for PD treatment.

In our study, we revealed that inhibiting the miR-186-3p expression in the midbrain of the PD mouse model can improve the motor ability and alleviate pathological changes (Scheme 1A). Furthermore, the RUNX3 protein expression was significantly higher in the PD model than in the control. RUNX3 can bind to the miR-186 promoter region and upregulate the expression of miR-186-3p in the PD model (Scheme 1B). The high expression of miR-186-3p in the PD model can inhibit the expression of the DAT protein, leading to a decrease in the DA content of dopaminergic neurons (Scheme 1C). In addition, miR-186-3p inhibited the IGF1R protein expression, which significantly increased the expression of the pro-apoptotic protein cytochrome c, cleaved caspase-3 and Bax while inhibiting the anti-apoptotic protein P-PI3KP-AKT and Bcl-2 expression, leading to dopaminergic neuron apoptosis (Scheme 1D). In summary, this study revealed the involvement of the RUNX3miR-186-3pDATIGF1R axis in the pathogenesis of the PD model and provided a new approach for PD treatment.

Scheme.1
scheme 1

Schematic of the RUNX3–miR-186-3p–DAT–IGF1R axis as a strategy for targeted treatment of PD. A AAV stereotactic injection into the substantia nigra region of the PD mouse model inhibits the expression of miR-186-3p in dopaminergic neurons. B The transcription factor RUNX3 binds to the upstream promoter region of miR-186-3p, upregulating the expression of miR-186-3p. C Regulation of dopamine content in midbrain tissue of PD models by the RUNX3–miR-186-3p–DAT axis. D The RUNX3–miR-186-3p–IGF1R axis regulates apoptosis of dopaminergic neurons in PD models

Results

Construction and validation of a chronic PD mouse model

To reveal the key pathogenic gene expression profiles of PD, we constructed a chronic PD mouse model by intraperitoneal injection (i.p.) of neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) (30 mg/kg, i.p., twice a week for 5 weeks). The PD mouse model was screened by behavioral tests [32] (Fig. 1A). The open field test showed that the total distance traveled by PD mice was significantly lower than that by normal mice (1059.28 ± 109.75 cm vs. 1453.35 ± 182.53 cm, P < 0.0001) (Fig. 1B, C). The results of the grasping test showed that PD mice had a significant decrease in the hanging time (47.50 ± 22.32 s vs. 143.30 ± 32.07 s, P < 0.0001) (Fig. 1D). Furthermore, the rotarod test results showed that the latency of falling time in PD mice was significantly shorter than that in normal mice (30.20 ± 11.05 s vs. 99.67 ± 28.97 s, P < 0.0001) (Fig. 1E). Moreover, we extracted the total proteins from midbrain tissue and detected changes in protein expression using western blotting (WB). The expression of tyrosine hydroxylase (TH) protein in the midbrain of PD mice was significantly lower than that of normal mice (1.03 ± 0.12 vs. 0.37 ± 0.12, P = 0.0059) (Fig. 1F, G). Immunohistochemistry detected a significant decrease in the number of TH-positive dopaminergic neurons in the midbrain tissue of PD mice (0.27 ± 0.06 vs. 2.67 ± 0.21, P < 0.0001) (Fig. 1H, I). The abovementioned results indicate that we successfully established a chronic PD mouse model, providing reliable samples for subsequent sequencing to reveal PD model gene expression profiling.

Fig. 1
figure 1

Behavioral tests and TH protein detection were used to assess the successful construction of the chronic PD mouse model. A Schematic of the construction of the chronic PD mouse model. B, C Open field test to detect the locomotor activity of mice. D Grasping test to detect the coordination ability of mice. E Rotarod test to detect the locomotor activity of mice. F WB to detect TH protein expression. G Statistical graph for TH protein expression. H IHC detection TH positive dopaminergic neurons; Scale bar: 200 µm. I Statistical chart of average optical density. Behavioral tests n = 10/group. Data are presented as mean ± standard deviation. Unpaired t-test was used for comparison between two groups. ***P < 0.001, ****P < 0.0001

MiR-186-3p is highly expressed in a chronic PD mouse model

To comprehensively analyze the miRNA expression profile in PD, we sequenced the midbrain tissues of both PD and normal mice that were successfully constructed in the aforementioned experiment (Supplementary Table 1). Bioinformatics analysis of the sequencing data revealed that the number of miRNAs from the X chromosome was the highest, followed by chromosome 1 (Fig. 2A). In addition, Fig. 2B shows the expression profile of miRNAs on different chromosomes in PD and normal mice. The inner three circles represent the expression levels of miRNAs in PD mice, while the outer three circles represent the expression levels of miRNAs in control mice. The peaks indicate a higher number of miRNAs from that chromosome. Further analysis revealed that miRNAs from exons were the most abundant, followed by introns (Fig. 2C). The expression profiles of all short-stranded RNAs in the control group are shown in Figure S1A–D, while the expression profiles of all short-stranded RNAs in the MPTP group are shown in Figure S1E–H. Principal component analysis of differential gene expression between the control and MPTP groups indicated differences in the component samples (Figure S1I). By comparing the mature miR-186-3p sequences between different species, we found that miR-186-3p has high conservatism, indicating that miR-186-3p has important functions in organisms (Figure S1J).

Fig. 2
figure 2

Bioinformatics analysis, combined with RT-qPCR and FISH detection, revealed that miR-186-3p was highly expressed in PD models. A Number of miRNAs on different chromosomes. B Expression levels of miRNAs on different chromosomes in PD and control samples. C Proportion of miRNAs from introns, exons, and intergenic regions. D Differential expression analysis revealed that miR-186 is highly expressed in the brain tissue of PD mouse models. E Through preliminary screening with a Venn diagram, we found that miR-186 was a target for further research. F A CCK-8 assay was used to detect the cell viability after 24 h treatment with different concentrations of MPP+. G RT-qPCR was used to detect the high expression of miR-186-3p in PD cells. H RT-qPCR detection of high expression of miR-186-3p in midbrain tissue of PD mice. I Detection of the expression of miR-186-3p in PD cell using FISH. Scale bar: 10 µm. J Statistical graph of average fluorescence intensity of FISH. Data are presented as mean ± standard deviation, and unpaired t-test was used for comparison between the two groups. **P < 0.01; ***P < 0.001

We further analyzed the differentially expressed miRNAs and explored the overexpression of miRNAs in PD mice. Compared with normal mice, there were 250 upregulated and 272 downregulated miRNAs in PD mice (Fig. 2D) (Supplementary Table 2). Through extensive literature review and joint sequencing results, we found that miR-186-3p leads to a decrease in cell proliferation and exerts a pro-apoptotic effect [21,22,23] (Fig. 2E). We selected miR-186-3p for further experiments to detect the expression and function of miR-186-3p in the PD model. Furthermore, we treated MN9D cells with different concentrations of 1-methyl-4-phenylpyridinium-iodide (MPP+) for 24 h and found that the cell viability decreased to approximately 50% after treatment with 1 mM MPP+ (52.91 ± 2.37%) (Fig. 2F). In subsequent experiments, we treated MN9D cells with 1 mM MPP+ for 24 h to construct a PD cell model [33]. Using real-time quantitative PCR (RT-qPCR) detection, we found that miR-186-3p was significantly upregulated in the PD cell model (1.90 ± 0.17 vs. 1.00 ± 0, P = 0.0015) (Fig. 2G) and PD mouse model (1.00 ± 0 vs. 4.85 ± 0.91, P = 0.0039) (Fig. 2H). Subsequently, we constructed ribonucleic acid (RNA) probes (labeled by Cy3) that specifically recognize miR-186-3p and used fluorescence in situ hybridization (FISH) experiments to detect the expression of miR-186-3p and localization in the PD cell model. The FISH experiment revealed that the average fluorescence intensity of miR-186-3p in PD cells was significantly higher than that of control cells (5.77 ± 0.282 vs. 2.33 ± 0.18, P = 0.0001) (Fig. 2I, J), and miR-186-3p was mainly located in the cytoplasm. The abovementioned results indicate that miR-186-3p is highly expressed in the PD model and mainly exerts its effects through post-transcriptional regulation as miR-186-3p is located in the cytoplasm [34].

Dopaminergic neurons in PD models exert their pro-apoptosis effects in a high miR-186-3p expression-dependent manner

To comprehensively reveal the mechanism of miR-186-3p in the PD model, we analyzed the biological functions of the potential target genes regulated by miR-186-3p through bioinformatics (Supplementary Table 3). Gene Ontology annotation of these target genes revealed their involvement in cellular receptor signaling pathways and apoptosis (Figure S2A). We further performed pathway enrichment analysis of miR-186-3p-regulated target genes using the Kyoto Encyclopedia of Genes and Genomes. The results revealed that the signaling pathways of the target genes were mainly PI3K–AKT and MAPK signaling pathways, which regulate cell growth, metabolism, proliferation, and apoptosis [35, 36] (Fig. 3A). Using gene set enrichment analysis, we revealed that the signaling pathways primarily activated in the PD mouse model compared with the normal group include PD, apoptosis, and MAPK signaling pathways (Figure S2B). Furthermore, using gene set variation analysis, it was found that the signaling pathways primarily activated in the PD mouse model are the PI3K–AKT signaling pathway, apoptosis, and oxidative phosphorylation (Figure S2C). The abovementioned analysis suggests that the pathways regulated by miR-186-3p are mainly related to cell apoptosis and survival.

Fig. 3
figure 3

The high expression of miR-186-3p in PD cellular models promotes the activation of apoptotic pathways, leading to increased levels of dopaminergic neuron apoptosis. A KEGG analysis of the functions enriched by the target genes possibly regulated by miR-186-3p. B Detection of miR-186-3p transfection efficiency using FISH; Scale bar: 10 µm. C Statistical graph of fluorescence intensity. D RT-qPCR to detect miR-186-3p transfection efficiency. E WB analysis was used to detect the expression of TH protein in PD cell models after transfection with miR-186-3p. F TH protein expression statistical graph. G Detection of cell apoptosis levels using FCM assay in PD cell models after transfection with miR-186-3p. H Statistical graph of apoptosis levels. I Detection of cell viability using CCK8 assay. J WB analysis for the detection of P-PI3K, PI3K, P-AKT and AKT protein expression. K, L P-PI3K and P-AKT protein expression statistical graph. M WB analysis for the detection the expression of Cleaved caspase-3, Cytochrome c, Bax, and Bcl-2 protein. N, O Protein expression statistical graph. Data are presented as mean ± standard deviation. One-way ANOVA was used to compare differences among multiple groups. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. *P < 0.05 inhibitor group vs. NC group.. #P < 0.05 mimic group vs. NC group

The aforementioned bioinformatics analysis confirmed that the miR-186-3p can participate in cell apoptosis and proliferation regulation. We further studied the pathogenic mechanism of miR-186-3p in the PD model by interfering with miR-186-3p expression. FISH and RT-qPCR were used to detect the transfection efficiency of miR-186-3p in the PD cell model. Those results revealed that the miR-186-3p expression was increased in the PD cell model. In addition, miR-186-3p was significantly decreased in the inhibitor group (0.26 ± 0.08 vs. 1.69 ± 0.13, P < 0.0001). The mimic group showed significantly increased miR-186-3p expression (93.05 ± 4.50 vs. 1.69 ± 0.13, P < 0.0001) (Fig. 3B–D). TH is the rate-limiting enzyme in the synthesis of the catecholamine DA. DA is an important neurotransmitter, and absent or insufficient DA secretion by dopaminergic neurons can lead to PD [37]. We found that the PD cell model showed diminished TH protein levels. The TH protein expression in the inhibitor group was increased. In contrast, the mimic group showed a lower TH protein expression than the PD cell model (Fig. 3E, F).

Furthermore, the PD cell model was transfected with the inhibitor or mimic of miR-186-3p, and flow cytometry (FCM) analysis of apoptosis showed that the apoptosis rate in the PD cell model was significantly increased. The apoptosis rate in the inhibitor group was decreased (13.93 ± 0.39% vs. 21.03 ± 2.36%, P = 0.006), while the mimic group showed a higher apoptosis rate than the PD cell model (27.73 ± 0.74% vs. 21.03 ± 2.36%, P = 0.008) (Fig. 3G, H). We detected the cell viability using cell counting kit-8 (CCK8). Compared with the control group, we found that the cell viability of the PD cell model was significantly reduced. The cell viability was increased in the inhibitor group (24 h: 0.48 ± 0.03 vs. 0.37 ± 0.03, P = 0.015). The mimic group showed reduced cell viability (24 h: 0.29 ± 0.01 vs. 0.37 ± 0.03, P = 0.02) (Fig. 3I).

The functional experiments found that miR-186-3p promotes apoptosis and inhibits the activity of the PD cell model. Based on these findings, we speculated that miR-186-3p can participate in the pathogenesis of PD by regulating apoptosis and cell activity pathways. Therefore, we conducted WB to detect the apoptotic and proliferation pathway-related proteins. The results revealed that P-PI3K and P-AKT, which can stimulate cell growth and proliferation, and activation of the P-PI3K/P-AKT signaling pathway is crucial for maintaining cell activity and survival [38], were significantly decreased in the PD cell model. The expression of P-PI3K and P-AKT proteins was significantly increased in the inhibitor group. In contrast, the expression of P-PI3K and P-AKT proteins was downregulated in the mimic group (Fig. 3J–L).

Bcl-2 protein has a significant inhibitory effect on apoptosis, and the P-PI3K/P-AKT pathway activates Bcl-2 and maintains the inhibitory effect of Bcl-2 protein on apoptosis [39]. In addition, the P-PI3K/P-AKT pathway can inhibit the activity of the protein cleaved caspase-3, thus preventing the initiation of the cascade reaction and promoting apoptosis [40]. The WB results showed that the expression of cytochrome c, cleaved caspase-3 and Bax, which promote cell apoptosis, was significantly increased, while the expression of Bcl-2 protein was significantly decreased in the PD cell model. In contrast, the expression of pro-apoptosis proteins was downregulated, while the Bcl-2 expression was upregulated in the inhibitor group, indicating a reduction in cell apoptosis. Similarly, the expression of pro-apoptosis proteins was significantly increased, while the Bcl-2 expression was significantly decreased in the mimic group (0.21 ± 0.04 vs. 0.38 ± 0.03, P = 0.008), indicating an activation of the apoptotic pathway by miR-186-3p overexpression in the PD cell model (Fig. 3M–O). To further verify the function of the P-PI3K/P-AKT signaling pathway by miR-186-3p regulation in the PD cell model, we used a highly selective inhibitor of PI3K kinase (LY294002) to inhibit the activation of the P-PI3K/P-AKT pathway [41, 42]. The expression of P-PI3K/P-AKT proteins was increased in the inhibitor group. However, LY294002 markedly attenuated the P-PI3K/P-AKT proteins expression (Figure S3A–C). Collectively, the expression of cleaved caspase-3, cytochrome c, and Bax was significantly increased, while the expression of Bcl-2 was significantly decreased with LY294002 treatment (Figure S3D–G). These results indicate that the high miR-186-3p expression in the PD model can activate the apoptotic pathway and participate in the pathogenesis of PD.

Inhibition of the miR-186-3p expression can improve the motor ability and inhibit the degeneration of dopaminergic neurons in a chronic PD mouse model

The abovementioned studies indicate that miR-186-3p is involved in the pathogenesis of PD by promoting dopaminergic neuron apoptosis in the PD cell model. We further investigate the mechanism of miR-186-3p in the chronic PD mouse model. Furthermore, we stereotaxically injected adeno-associated virus 9 (AAV-9) to inhibit the expression of miR-186-3p in the midbrain of the PD mouse model. Then, we performed behavioral tests to determine whether the motor ability of mice was improved (Fig. 4A). In the behavioral tests, the open field test showed that the total distance traveled by PD mice was significantly reduced, while the total distance traveled by those in the AAV-miR-186-3p sponge group was significantly increased (3946.30 ± 600.32 cm vs. 2335.80 ± 767.38 cm, P = 0.0001) (Fig. 4B, C). Additionally, the grasping test showed that the hanging time of PD mice was significantly reduced, while the hanging time of mice in the AAV-miR-186-3p sponge group was significantly increased (25.23 ± 9.39 s vs. 15.40 ± 8.27 s, P = 0.02) (Fig. 4D). The rotarod test showed that PD mice fell off the pole significantly earlier than normal mice. The AAV-miR-186-3p sponge group showed a significant increase in the time to fall off the pole (132.15 ± 21.65 s vs. 52.72 ± 21.01 s, P < 0.0001) (Fig. 4E). The pole-climbing test showed that PD mice took significantly longer to climb down from the top of the pole to the bottom than the saline group. The AAV-miR-186-3p sponge group showed a significant reduction in the time to climb down from the pole (7.77 ± 3.51 s vs. 21.53 ± 7.29 s, P < 0.0001) (Fig. 4F). The results of the behavioral tests showed that the use of AAV-miR-186-3p sponge to inhibit miR-186-3p expression can improve the motor ability of PD mice. Furthermore, AAV expressed green fluorescent protein (GFP). After 6 weeks of injection, in vivo fluorescence imaging results of PD mice showed that the AAV was effectively expressed in brain tissue (Figure S4A). In addition, we found significant co-localization between dopaminergic neurons (TH antibodies labeled with dopaminergic neurons) and GFP through immunofluorescence (IF) detection, indicating that the AAV was effectively expressed in dopaminergic neurons (Figure S4B–C). Furthermore, after injection of the AAV-miR-186-3p sponge to suppress miR-186-3p expression, the number of TH-positive neurons in the mouse midbrain tissue was significantly increased (Figure S4B–C).

Fig. 4
figure 4

Knocking down the expression of miR-186-3p in dopaminergic neurons in the midbrain tissue of PD mice can enhance the motor ability of mice and reduce the degeneration and death of dopaminergic neurons. A Schematic of AAV stereotaxic injection in PD mice. B Open field test to detect the locomotor activity of mice. C Statistical graph of total distance. D Grasping test to detect the coordination ability of mice. E Rotarod test to detect the locomotor activity of mice. F Pole-climbing test to detect the locomotor activity of mice; and mouse behavioral tests (n = 15/group). G WB to detect the expression of TH and α-syn proteins in the midbrain tissue of mice. H, I Statistical graph for TH and α-syn protein expression. J IF detection and co-localization of AAV and TH protein. Scale bar: 10 µm. K Statistical chart of average fluorescence intensity. L RT-qPCR to detect the expression of miR-186-3p in the midbrain tissue of mice. Data are presented as mean ± standard deviation. One-way ANOVA was used to compare differences among multiple groups. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001

Furthermore, we extracted the total protein from mouse midbrain tissue. The WB results showed that the TH protein expression in PD mice was significantly decreased (0.57 ± 0.038 vs. 1.15 ± 0.15, P = 0.0003), while the TH expression in the AAV-miR-186-3p sponge group was significantly increased (0.91 ± 0.012 vs. 0.51 ± 0.019, P = 0.0036) (Fig. 4G, H). Conversely, the α-syn protein expression in the midbrain of PD mice was significantly increased, while it was significantly decreased in the AAV-miR-186-3p sponge group (0.27 ± 0.024 vs. 1.13 ± 0.076, P < 0.0001) (Fig. 4G, I). We performed stereotaxic injection of AAV into the substantia nigra of PD mice and detected whether AAV was expressed in dopaminergic neurons based on IF staining of frozen midbrain tissue sections. The results of the IF revealed that the average fluorescence intensity of the TH protein was decreased in PD mice and increased in the AAV-miR-186-3p sponge group (9.59 ± 0.56 vs. 6.34 ± 1.05, P = 0.025). We also found that the AAV (GFP) expression was co-localized with TH-positive dopaminergic neurons (marked by the white arrow) (Fig. 4J, K). In addition, RT-qPCR analysis the expression of miR-186-3p in midbrain tissue revealed that miR-186-3p was significantly increased in PD mice and significantly decreased in the AAV-miR-186-3p sponge group (0.71 ± 0.07 vs. 4.53 ± 0.87, P = 0.0008) (Fig. 4L). Those results show that the AAV-miR-186-3p sponge is expressed in dopaminergic neurons and inhibits the miR-186-3p expression in the midbrain, thereby increasing the TH protein expression and improving the motor ability of PD mice.

Inhibition of the miR-186-3p expression can inhibit the apoptosis pathway and increase the content of DA in chronic PD mouse model

We further revealed the regulatory pathway of miR-186-3p in the PD mouse model. The WB results revealed that the expression of P-PI3K/P-AKT protein in PD mice was significantly decreased. In the AAV-miR-186-3p sponge group, the P-PI3K/P-AKT protein was significantly increased (P-PI3K: 0.34 ± 0.049 vs. 0.12 ± 0.012, P = 0.0014) (P-AKT: 0.39 ± 0.04 vs. 0.16 ± 0.044, P = 0.0052), while there was no change in the total PI3K/AKT protein (Fig. 5A–C). WB for apoptosis-related proteins showed that the pro-apoptotic proteins expression was significantly increased, while the anti-apoptotic protein Bcl-2 expression was significantly decreased in PD mice. In the AAV-miR-186-3p sponge group, the pro-apoptotic proteins expression was significantly decreased, while the expression of anti-apoptotic proteins was increased (Fig. 5D–F).

Fig. 5
figure 5

Knocking down the expression of miR-186-3p in dopaminergic neurons of PD mouse midbrain tissue can inhibit the activation of apoptosis pathways and increase the content of dopamine and its metabolites. A WB analysis for the detection the expression of P-PI3K, PI3K, P-AKT and AKT protein. B, C P-PI3K and P-AKT protein expression statistical graph. D WB analysis for the detection the expression of Cleaved caspase-3, Cytochrome c, Bax and Bcl-2 protein. E, F Protein expression statistical graph. G Dopamine peak chart. H LC–MS/MS detection of dopamine content in midbrain tissue. I Homovanillic acid peak chart. J LC–MS/MS detection of homovanillic acid content in midbrain tissue. K Tyrosine peak chart. L LC–MS/MS detection of tyrosine content in midbrain tissue. Data are presented as mean ± standard deviation. One-way ANOVA was used to compare differences among multiple groups. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001

Furthermore, we investigated the neurotransmitter content in the midbrain tissue of PD mice. The 3-hydroxytyramine in the substantia nigra of the midbrain can effectively maintain the motor ability, and a decrease in the DA content can lead to a decrease in the motor ability and slowed reactions, such as limb stiffness and slow movement observed in PD [43]. Liquid chromatography-tandem mass spectrometry (LC–MS/MS) detected a decrease in the DA and homovanillic acid content in PD mice. However, in the AAV-miR-186-3p sponge group, the content of DA and homovanillic acid was increased (DA: 1239.22 ± 316.76 ng/g vs 494.61 ± 196.69 ng/g, P = 0.031) (homovanillic acid: 1171.74 ± 108.92 ng/g vs 391.89 ± 114.24 ng/g, P = 0.0053) (Fig. 5G–J). There was no difference in the tyrosine content between the groups (Fig. 5K, L). These results showed that inhibiting the miR-186-3p expression in the midbrain of PD mice can suppress the activation of the apoptotic pathways and increase the content of DA and its metabolites, independent of the changes in the tyrosine content. Inhibition of miR-186-3p is beneficial for improving the motor ability of PD mice.

Targeted inhibition of DAT and IGF1R protein expression by miR-186-3p in the PD model

The abovementioned experiments showed that miR-186-3p can inhibit the activation of the P-PI3KP-AKT signaling pathway, activate the cytochrome cBaxcleaved caspase-3 pathway, and lead to DA neuron apoptosis in the PD model. We further investigated the involvement of target genes regulated by miR-186-3p that participate in the pathogenesis of the PD model. MiR-186-3p is highly expressed in the PD model, and the mechanism of miRNAs mainly involves the inhibition of the expression of target genes [44], so the target genes regulated by miR-186-3p had a low expression in the PD model. Using bioinformatics analysis of the target genes involved in the PI3K/AKT, MAPK, and dopaminergic synapse pathways, we found 55 potential target genes for miR-186-3p (Fig. 6A). We analyzed the expression of target genes and found that the expression of slc6a3 and igf1r genes was lower in the MPTP group than control group (Fig. 6B). Furthermore, by analyzing the target genes regulated by miR-186-3p using the Targetscan database [45] and combining with the low-expression target genes in the miR-186-3p regulatory pathway, we identified the most suitable genes slc6a3 and igf1r (Fig. 6C).

Fig. 6
figure 6

MiR-186-3p binds to the 3’UTR regions of slc6a3 and igf1r genes, inhibiting the expression of target genes in PD cellular models. A Bioinformatics analysis of target genes regulated by miR-186-3p. B Bioinformatics analysis of target gene expression in PD model. C The Venn diagram presents the potential target genes slc6a3 and igf1r that may be regulated by miR-186-3p. D WB to detect IGF1R and DAT protein expression in the PD cell model. E IGF1R and DAT protein expression statistical graph. F WB to detect IGF1R and DAT protein expression in the PD mouse model. G IGF1R and DAT protein expression statistical graph. H Binding site of miR-186-3p with the 3’UTR region of the slc6a3 gene. I Luciferase activity of igf1r reporter after co-transfection with miR-186-3p. J Binding site of miR-186-3p with the 3’UTR region of the igf1r gene. K Luciferase activity of igf1r reporter after co-transfection with miR-186-3p. Data are presented as mean ± standard deviation. One-way ANOVA was used to compare differences among multiple groups. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001

To further explore whether miR-186-3p inhibits the expression of slc6a3 and igf1r, we transfected with miR-186-3p inhibitor or mimic in the PD cell model and detected the expression of DAT and IGF1R using WB. The results found that the DAT and IGF1R proteins expression was significantly decreased in the PD cell model. In addition, the DAT and IGF1R proteins expression was significantly increased in the inhibitor group (DAT: 0.55 ± 0.02 vs. 0.42 ± 0.03, P = 0.0025) (IGF1R: 0.91 ± 0.02 vs. 0.31 ± 0.04, P < 0.0001), while the proteins were decreased in the mimic group (DAT: 0.24 ± 0.02 vs. 0.42 ± 0.03, P = 0.0001) (IGF1R: 0.16 ± 0.03 vs. 0.31 ± 0.04, P = 0.0002) (Fig. 6D, E). Furthermore, the WB analysis found that the DAT and IGF1R proteins expression was significantly decreased in PD mice and significantly increased in the AAV-miR-186-3p sponge group (DAT: 0.68 ± 0.10 vs. 0.25 ± 0.02, P = 0.0014) (IGF1R: 0.59 ± 0.12 vs. 0.31 ± 0.022, P = 0.018) (Fig. 6F, G).

Furthermore, we predicted that the binding site of miR-186-3p to the slc6a3 is within the sequence region of 656–663 in the 3'UTR (Fig. 6H) and that the binding site of miR-186-3p to the igf1r is within the sequence region of 5564–5570 in the 3'UTR (Fig. 6J) using the Targetscan database[45]. In addition, we constructed wild-type and mutant-type dual-luciferase reporter (DLR) assay plasmids of slc6a3 and igf1r 3'UTR binding sites and co-transfected them with miR-186-3p NC or mimic into 293 T cells. The DLR results showed that there was no statistically significant difference in the ratio of renilla luciferase/firefly luciferase between the psiCheck-2 control groups. The miR-186-3p mimic markedly decreased the renilla luciferase /firefly luciferase of the slc6a3 wild-type reporter (0.97 ± 0.02 vs. 0.78 ± 0.04, P = 0.0007) but had minimal effects on the slc6a3 mutant reporter (Fig. 6I). Similarly, the miR-186-3p mimic markedly decreased the luciferase activity of the igf1r wild-type reporter (1.08 ± 0.06 vs. 0.75 ± 0.03, P = 0.002) but had minimal effects on the igf1r mutant reporter (Fig. 6K). These results showed that miR-186-3p can directly bind to the 3’UTRs of the slc6a3 and igf1r genes, leading to a decrease in DAT and IGF1R protein expression.

Targeted inhibition of DAT and IGF1R expression by miR-186-3p directly regulates the DA content and apoptosis in the PD cell model

We revealed that miR-186-3p can inhibit the expression of DAT protein in the PD model. DAT is located in the presynaptic membrane and is an important marker of dopaminergic neurons. DAT actively transports DA from the synaptic space into neurons to ensure the physiological function of synapses, which is crucial for maintaining DA homeostasis in the midbrain and striatum [46, 47]. Furthermore, we constructed a DAT overexpression plasmid (DATOE) and evaluated the efficiency of overexpression using WB. The results found that the expression of DAT protein was significantly decreased in the PD cell model, while it was increased in the DATOE group (Fig. 7A, B). We demonstrated that miR-186-3p can regulate the DA content in the PD cell model through the DAT protein. The DA content in the cell supernatant was determined using ELISA. The results found that the content of DA in the cell supernatant was significantly decreased in the PD cell model (713.71 ± 4.67 ng/mL vs. 780.43 ± 5.36 ng/mL, P < 0.0001). Inhibiting the miR-186-3p expression led to an increase in the DA content in the cell supernatant, while the mimic group led to a decrease in the DA content (695.61 ± 3.83 ng/mL vs. 712.01 ± 6.04 ng/mL, P = 0.043). Overexpression of DAT protein led to a significant increase in the DA content (742.48 ± 6.33 ng/mL vs. 700.79 ± 1.43 ng/mL, P < 0.0001) (Fig. 7C). These results show that the high miR-186-3p expression in the PD cell model inhibited the DAT protein expression, resulting in a decrease in the extracellular DA content, while DAT protein overexpression led to a significant recovery of the extracellular DA content.

Fig. 7
figure 7

MiR-186-3p reduces the content of dopamine in the supernatant of dopaminergic neurons by inhibiting the expression of DAT protein and increases the apoptosis level of dopaminergic neurons by inhibiting the expression of IGF1R protein. A WB analysis for the detection of DAT protein expression. B DAT protein expression statistical graph. C Detection of extracellular DA content using ELISA. D WB analysis for the detection of IGF1R protein expression. E IGF1R protein expression statistical graph. F Detection of apoptosis levels using FCM assay; G statistical graph of apoptosis levels. Data are presented as mean ± standard deviation. One-way ANOVA was used to compare differences among multiple groups. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001

Similarly, miR-186-3p can inhibit the IGF1R protein expression, which regulates cell proliferation and apoptosis [31]. We further constructed IGF1R-overexpression plasmids (IGF1ROE) and detected the overexpression efficiency using WB. The expression of IGF1R protein was significantly decreased in the PD cell model and increased in the IGF1ROE group (Fig. 7D, E). In addition, the FCM results revealed that the apoptosis rate was significantly increased in the PD cell model and decreased in the inhibitor group (12.3 ± 0.90% vs. 17.77 ± 1.70%, P = 0.039). However, the apoptosis rate was significantly increased in the mimic group (29.3 ± 2.05% vs. 17.77 ± 1.70%, P < 0.0001) and reduced in the IGF1ROE group (14.77 ± 1.60% vs. 30.47 ± 2.39%, P < 0.0001) (Fig. 7F, G). These results indicate that miR-186-3p can exert its pro-apoptotic function in the PD cell model by inhibiting the IGF1R expression.

Transcriptional factor RUNX3 activates the expression of miR-186-3p in the PD cell model

To reveal the mechanism of the high miR-186-3p expression in the PD model, we constructed a deoxyribonucleic acid (DNA) probe that recognizes the promoter region of miR-186-3p within 2000 bp (Figure S5A). We extracted chromosomes from the PD cell model and the control group. Then, we used ultrasound to break the chromosomes into sequences of 500–1000 bp. Agarose gel electrophoresis showed that the DNA sequence lengths reached 500–1000 bp (Figure S5B). The 500–1000-bp DNA sequence length is conducive to the binding of miR-186-3p DNA probes. When the DNA sequence fragments reached 500–1000 bp, we further incubated them with miR-186-3p DNA probes through reverse chromatin immunoprecipitation (reverse-ChIP) assay, which can capture proteins that bind to DNA, including TFs [48] (Figure S5C). Silver staining showed that the miR-186-3p probe group had different protein bands compared with the control probe groups (Figure S5D).

After the reverse-ChIP assay, we obtained a protein solution that could bind to the miR-186-3p promoter region. We detected the proteins bound by the miR-186-3p DNA probes using the LC–MS/MS analysis. The results showed that there were 153 different proteins in the miR-186-3p probe group (Fig. 8A) (Supplementary Table 4). Subsequently, we analyzed the TFs that can bind to regulate mmu-miR-186 using the TransmiR database (Fig. 8B). The TransmiR database can accurately predict the regulatory relationship between TFs and miRNA [49]. Based on the regulatory apoptosis of the miR-186-3p in the PD model, we found that the TF that regulates miR-186-3p also has apoptotic regulatory functions. Combined with the LC–MS/MS results, we found that the runt-related transcription factor 3 (RUNX3) in the RUNX family can regulate apoptosis [16] (Fig. 8C).

Fig. 8
figure 8

RUNX3 is highly expressed in PD models, which upregulates the expression level of miR-186-3p, and inhibits the expression of DAT protein and the content of dopamine in cell supernatant. A LC–MS/MS analysis of TFs binding to the miR-186-3p promoter region. B Analysis of TFs regulating mmu-miR-186 in the TransmiR database. C The Venn diagram shows that the preliminary screening of transcription factors regulating miR-186 combined with the TransmiR database and LC–MS/MS analysis is the RUNX protein family. D WB analysis for the detection the expression of RUNX3 protein in the PD cell model. E RUNX3 protein expression statistical graph. F WB analysis for the detection of RUNX3 protein in the midbrain tissue of PD mouse model. G RUNX3 protein expression statistical graph. H WB analysis for the detection of the knockdown efficiency of RUNX3 protein in the PD cell model. I RUNX3 protein expression statistical graph. J RT-qPCR for the detection of the miR-186-3p expression after RUNX3 knockdown in the PD cell model. K WB analysis for the detection the expression of DAT protein in the PD cell model. L DAT protein expression statistical graph. M Extracellular DA content was detected using ELISA. Data are presented as mean ± standard deviation. Unpaired t-test was used to compare the protein expression levels of RUNX3 between two groups. One-way ANOVA was used to compare differences among multiple groups. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001

Therefore, we further revealed the expression of RUNX3 in the PD model and its regulatory role in miR-186-3p. The WB results found that the expression of RUNX3 protein was significantly increased in the PD cell model (0.93 ± 0.09 vs. 0.17 ± 0.03, P = 0.0004) (Fig. 8D, E) and the midbrain tissue of the PD mouse model (0.47 ± 0.03 vs. 0.22 ± 0.03, P = 0.0013) (Fig. 8F, G). We speculated that the high RUNX3 protein expression can upregulate the miR-186-3p expression in the PD model. Furthermore, we transfected small interfering RNAs (siRNAs) into the PD cell model to knockdown RUNX3, and WB was used to detect the knockdown efficiency. The results found that the RUNX3 protein expression was significantly increased in the PD cell model but decreased in the si-RUNX3-1 and si-RUNX3-2 groups (0.11 ± 0.011 vs. 1.097 ± 0.15, P < 0.0001) (0.12 ± 0.013 vs. 1.097 ± 0.15, P < 0.0001) (Fig. 8H, I). Next, si-RUNX3-1 or si-RUNX3-2 was transfected into the PD cell model, and RT-qPCR was performed to detect the miR-186-3p expression in the RUNX3-knockdown PD cell model. The results showed that the miR-186-3p expression was significantly increased in the PD cell model but significantly decreased in the RUNX3-knockdown PD cell model (0.74 ± 0.05 vs. 1.26 ± 0.10, P < 0.0001) (0.66 ± 0.06 vs. 1.26 ± 0.10, P < 0.0001) (Fig. 8J). These results suggest that RUNX3 knockdown in the PD cell model leads to a decrease in the miR-186-3p expression.

To elucidate the function of the RUNX3miR-186-3pDAT axis in the PD cell model, we transfected si-RUNX3-1, miR-186-3p mimic, and DATOE into the PD cell model. The DAT protein expression was detected using WB, and the results found that the DAT protein was significantly decreased in the PD cell model and increased after RUNX3 knockdown. Furthermore, the DAT protein expression was decreased in the mimic group (0.15 ± 0.033 vs. 0.46 ± 0.029, P = 0.0026). However, the DAT protein was increased in the DATOE group (0.97 ± 0.15 vs. 0.10 ± 0.02, P < 0.0001) (Fig. 8K, L). ELISA showed a significant decrease in the extracellular DA content of the PD cell model and an increase after RUNX3 knockdown (742.92 ± 12.47 ng/mL vs. 703.72 ± 8.16 ng/mL, P = 0.03). Furthermore, the DA content was decreased in the mimic group (701.66 ± 12.28 ng/mL vs. 747.25 ± 6.98 ng/mL, P = 0.009) and increased in the DATOE group (784.86 ± 12.47 ng/mL vs. 718.38 ± 4.19 ng/mL, P = 0.0002) (Fig. 8M). Those results indicate that RUNX3 upregulates the miR-186-3p expression, which inhibits the DAT protein expression, leading to a decrease in the DA content in the supernatant of dopaminergic neurons.

RUNX3–miR-186-3p–IGF1R axis regulates apoptosis in the PD cell model

To reveal the function of the RUNX3miR-186-3pIGF1R axis in PD, we performed si-RUNX3-1 transfection in the PD cell model while simultaneously transfecting the miR-186-3p mimic and IGF1ROE. We used WB to detect the IGF1R protein and found that the expression of IGF1R protein was significantly decreased in the PD cell model. The si-RUNX3-1 group showed an increase in the expression of IGF1R protein, while the mimic group showed a significant decrease in the IGF1R protein. Conversely, the IGF1ROE group showed an increase in the expression of IGF1R protein (Fig. 9A, B).

Fig. 9
figure 9

The high expression of RUNX3 upregulates the expression level of miR-186-3p, inhibits the expression of IGF1R protein, and promotes the activation of dopaminergic neuron apoptosis pathway in the PD cell model. A WB analysis for the detection of IGF1R protein expression. B IGF1R protein expression statistical graph. C Detection of cell apoptosis levels using FCM assay. D Statistical graph of apoptosis levels. E WB analysis for the detection the expression of P-PI3K, PI3K, P-AKT and AKT protein. F, G Protein expression statistical graph. H WB analysis for the detection the expression of Cleaved caspase-3, Bax, Cytochrom c, Bcl-2 protein. IL Protein expression statistical graph. Data are presented as mean ± standard deviation. One-way ANOVA was used to compare differences among multiple groups. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001

Furthermore, FCM was used to detect the apoptosis rate of different transfection groups, and the results found that the apoptosis of the PD cell model was significantly increased (19.43 ± 2.59% vs. 5.37 ± 0.53%, P = 0.0017). Knockdown of RUNX3 in the PD cell model found a decrease in the level of cell apoptosis (11.43 ± 0.78% vs. 19.23 ± 1.56%, P = 0.0032). The mimic group showed an increase in the cell apoptosis rate (24.37 ± 2.31% vs. 12 ± 0.16%, P = 0.0016). However, the IGF1ROE group showed a decrease in the level of cell apoptosis (14.43 ± 0.52% vs. 25.17 ± 4.08%, P = 0.0211) (Fig. 9C, D). Those results reveal that RUNX3 upregulates the miR-186-3p expression, which inhibits the IGF1R protein expression, leading to an increase in the apoptosis rate of dopaminergic neurons.

To reveal the mechanism of the RUNX3miR-186-3pIGF1R axis in the PD model, we used WB to detect the expression of cellular activity and apoptosis pathway proteins. The results found that the P-PI3K/P-AKT proteins were significantly decreased in the PD cell model. The P-PI3K/P-AKT proteins expression was significantly increased in the si-RUNX3-1 group and downregulated in the mimic group. However, we revealed a significant increase in the P-PI3K/P-AKT proteins in the IGF1R overexpression group (Fig. 9E–G). In addition, the pro-apoptotic proteins expression was significantly increased in the PD cell model. However, the anti-apoptotic protein Bcl-2 was significantly decreased in the PD cell model. The si-RUNX3-1 group showed a decrease in the expression of pro-apoptotic proteins and a significant increase in the anti-apoptotic proteins. In contrast, the pro-apoptotic proteins were significantly increased in the mimic group. However, we found a significant decrease in the pro-apoptotic proteins in the IGF1R overexpression group, while the anti-apoptotic proteins were significantly increased (Fig. 9H–L). The abovementioned results indicate that RUNX3 upregulates the miR-186-3p expression, which can inhibit the IGF1R protein expression, leading to the activation of the dopaminergic neuronal apoptosis pathway and a significant increase in the apoptosis rate.

Discussion

The pathogenesis of PD is unclear, and the main treatment strategy for PD involves levodopa supplementation, which inevitably leads to further degeneration of dopaminergic neurons in the substantia nigra of the midbrain of PD patients [7, 8]. A thorough understanding of the genetic and molecular pathogenic mechanisms of PD and the key mechanisms underlying the death of dopaminergic neurons can help in developing treatment targets for PD.

This study aimed to reveal the pathogenesis of PD. First, we obtained the gene expression profile of the midbrain tissue of PD mice using whole genome sequencing. Bioinformatics analysis showed high miRNA expression in the PD model. We confirmed that miR-186-3p was highly expressed in the PD model. No previous study has reported the function of miR-186-3p in neurodegeneration, but studies have found that the high miR-186-3p expression can inhibit the development of cervical cancer by inhibiting the PI3K/AKT pathway through the suppression of IGF1 protein [21]. This study also found that miR-186-3p overexpression led to a decreased activity and increased apoptosis rate in the PD model. Furthermore, inhibiting the expression of miR-186-3p in the midbrain of the PD mouse model can increase the DA content and improve the motor ability.

The activated P-PI3K/P-AKT pathway can regulate the activity of Bcl-2 family protein members and inhibit the pro-apoptotic proteins Bax and caspase-3 expression [39]. Members of the Bcl-2 family protect the mitochondrial integrity, prevent the release of cytochrome c, and causes subsequent activation of caspase-3 [40]. Activated AKT can also prevent mitochondria from releasing cytochrome c, inhibit the release of apoptotic factors, and block the activation efficiency of the caspase apoptotic family protein cascade, thereby inhibiting cell apoptosis [50]. It has been shown that angiotensin (Ang) 1–7 have new therapeutic potential against the neurotoxic movement disorders associated with PD. Ang 1–7 can increase DA synthesis and exert a therapeutic effect on PD by binding to MASR and activating the PI3K/Akt/CREB/BDNF/TrKB signaling pathway [51]. In addition, WYP may protect against the loss of dopaminergic neurons in MPTP-induced PD mice by activating the PI3K/Akt signaling pathway, inhibiting apoptosis, and increasing the secretion of neurotrophic factors [52]. We found that miR-186-3p can induce apoptosis of dopaminergic neurons and participate in the pathogenesis of PD. We further investigated the mechanism underlying the role of miR-186-3p in the PD model. The results revealed that inhibiting the miR-186-3p expression led to an increase in the P-PI3K/P-AKT protein expression and downregulation of the pro-apoptotic proteins while upregulating the anti-apoptotic proteins.

Furthermore, bioinformatics analysis revealed that miR-186-3p may regulate the target genes slc6a3 and igf1r in the PD model. The DAT encoded by the slc6a3 gene plays a crucial role in DA transport. Genetic variations of the slc6a3 gene may affect the DAT expression, thereby affecting the DA transport, which is reflected in the clinical treatment and affects the drug efficacy. The genetic variations of the slc6a3 gene are involved in the occurrence of PD [46, 47]. In addition, IGF1 activates the IGF1R/PI3K signaling pathway to regulate the expression of G protein-coupled estrogen receptor in primary astrocytes, which may contribute to the anti-inflammatory effect of MPTP/MPP+-induced astrocyte activation [53]. The DLR experiments are often used to examine the regulatory relationships between genes, such as miRNA regulation of target gene expression [54]. Our study confirmed that miR-186-3p can directly connect to the 3ʹUTR regions of slc6a3 and igf1r genes. WB assays found that miR-186-3p inhibition increased the DAT and IGF1R protein expression. Further results found that the high miR-186-3p expression inhibited the DAT protein expression, resulting in a decrease in the extracellular DA content, while DAT protein overexpression led to a significant recovery of extracellular DA content. In addition, miR-186-3p can exert its pro-apoptotic function in the PD cell model by inhibiting the IGF1R protein expression. These results indicate that miR-186-3p can participate in the pathogenesis of PD by inhibiting the expression of DAT and IGF1R proteins.

TFs play an important role in neurodegeneration. DJ-1 can regulate various TFs, including nuclear factor 2, and protect neurons from oxidative stress. DJ-1 is a co-activator of nuclear factor kappa-B and alters the redox balance to protect neurons from damage caused by α-syn aggregation and oligomer-induced neurodegeneration [55]. In our study, the mechanism underlying the effects of the high miR-186-3p expression in the PD model was explored. We constructed DNA probes specific for the miR-186-3p promoter region and performed reverse-ChIP combined with LC–MS/MS to analyze the TFs bound to the miR-186-3p. This experiment preliminarily identified RUNX3. Many studies have reported that high RUNX3 protein expression can increase the level of cell apoptosis [15, 16]. In addition, the overexpression of lncRNA-GAS5 in activated NK cells increases the RUNX3 expression, leading to an increase in the apoptosis rate of HepG2 cells [56]. This study revealed that RUNX3 protein was highly expressed in the PD model. After knocking down RUNX3, the expression of miR-186-3p was also significantly reduced, indicating that high RUNX3 expression can upregulate the expression of miR-186-3p in the PD model.

To further investigate the mechanisms underlying the effects of the RUNX3miR-186-3pDAT axis in the PD model, we transfected cells with si-RUNX3-1, miR-186-3p mimic, and DAT-overexpression plasmids in the PD cell model and detected the DA content in the supernatant using ELISA. The results showed that RUNX3 knockdown increased the DA content, while miR-186-3p mimic resulted in decreased DA content. Interestingly, simultaneous overexpression of the DAT protein led to an increase in the DA content in the PD cell model. Overall, the high RUNX3 expression in the PD model upregulates the miR-186-3p expression while leading to a decrease in the DAT protein, resulting in abnormal DA uptake and imbalance in dopaminergic neurons.

Furthermore, revealing the mechanisms underlying the effects of the RUNX3miR-186-3pIGF1R axis in the PD model, we transfected cells with si-RUNX3-1, miR-186-3p mimic, and IGF1R-overexpression plasmids in the PD cell model and used FCM to detect the apoptosis rate. The results showed that RUNX3 knockdown reduced the apoptosis rate. However, simultaneous transfection with the miR-186-3p mimic resulted in an increased apoptosis rate. Interestingly, IGF1R protein overexpression led to a decrease in the apoptosis rate. The pathway regulated by the regulatory axis in the PD model was further evaluated. The WB results showed that RUNX3 protein knockdown resulted in decreased expression of pro-apoptotic proteins, while the expression of anti-apoptotic proteins was increased. Simultaneous transfection with miR-186-3p mimic led to a significant increase in the expression of pro-apoptotic proteins and a significant decrease in the expression of anti-apoptotic proteins. Additionally, when overexpressing IGF1R, the expression of pro-apoptotic proteins was significantly decreased, while anti-apoptotic proteins were significantly increased. Overall, the high RUNX3 expression in the PD model upregulates the miR-186-3p expression, leading to a decrease in the IGF1R protein, thereby activating the dopaminergic neuronal apoptosis pathway and increasing the apoptosis rate.

The primary mechanism of action for anti-PD medications is to adjust the metabolism of central dopamine, achieving the therapeutic effect by supplementing exogenous dopamine and stimulating dopamine receptors. The main therapeutic drugs are divided into six categories as follows: (1) levodopa combination; (2) dopamine receptor agonists; (3) monoamine oxidase B (MAO-B) inhibitors; (4) catechol-o-methyltransferase inhibitors (COMT); (5) anticholinergic drugs; and (6) amantadine [57]. The currently used treatment methods, whether pharmacological or surgical, can only alleviate symptoms and cannot stop the progression of the disease, nor can they cure it. Moreover, these drugs have many adverse reactions, such as the on–off phenomenon, heart failure, hepatotoxicity, vasculitis, edema, and diarrhea [58]. The etiology of PD is the massive death of dopamine neurons in the substantia nigra region of the midbrain, which leads to an imbalance in the activity of two key neural pathways in the basal ganglia motor control center, namely the direct and indirect pathways, manifesting as a series of clinical symptoms primarily characterized by movement disorders [59]. Therefore, in this study, by using gene therapy to inhibit the expression of miR-186-3p, the degeneration and death of midbrain dopaminergic neurons were effectively delayed, which could be beneficial to reverse the progression of the disease, thereby providing a new target for the treatment of PD. First, miRNA, a type of noncoding RNA, does not translate into proteins, and thus it results in a lower immune response from the body. Second, miRNA targets with high specificity, allowing for modular development through the replacement of RNA sequences, predictability in pharmacokinetics and pharmacodynamics, and relative safety. Additionally, aside from surgical methods to inject miRNA viral vectors, it is easy to encapsulate miRNA within biodegradable, biocompatible, and low-toxicity nanomaterials that can protect miRNA from degradation and deliver it into cells to exert its function [60, 61].

This study also has some limitations. It has been found that the acute PD mouse model induced by MPTP exhibits a short-term reduction in striatal DA content, with dopaminergic neurons showing signs of necrosis. However, the chronic model demonstrates a progressive development of the disease, with the number of DA neurons gradually decreasing by apoptosis, which can effectively simulate the pathological characteristics of PD patients and the morphological features of substantia nigra dopaminergic neurons, thereby offering an advantage in exploring the pathogenesis of PD [62]. Moreover, the pathogenic mechanism of MPTP-induced PD is singular, primarily causing dopaminergic neuron apoptosis by blocking mitochondrial function, whereas the pathogenic factors in PD patients are often diverse, including oxidative stress, genetic mutations, and the accumulation of pathological proteins.

In the next phase of our research, we plan to specifically knock down the expression of miR-186-3p in the substantia nigra region of primate PD animal models through stereotactic injection of adeno-associated virus, assess its efficacy and safety, and further evaluate the feasibility of clinical trials [63].

In conclusion, we successfully obtained the mRNA and miRNA expression profiles in a PD mouse model and screened for highly expressed miRNAs in PD model. We revealed the mechanism of upregulation of miR-186-3p by transcription factor RUNX3 in PD model. We demonstrated that miR-186-3p can inhibit the DAT expression, resulting in a decrease in the DA content of dopaminergic neurons. Moreover, miR-186-3p inhibits the IGF1R expression, thus activating the apoptosis pathway leading to the apoptosis of dopaminergic neurons. We clarified that the RUNX3miR-186-3pDATIGF1R axis can be involved in the pathogenesis of PD.

Materials and methods

Cells culture

The cell line (MN9D, 293 T) used in this study was obtained from the Department of Neurology, Nanfang Hospital, Southern Medical University. Cells were cultured at 37 °C and 5% CO2 in Dulbecco's Modified Eagle Medium (DMEM) (Gibco, Carlsbad, CA, USA) containing 10% fetal bovine serum (Gibco, Carlsbad, CA, USA) and 1% penicillin–streptomycin-amphotericin B mixture solution (Solarbio, Beijing, China) in a constant-temperature incubator.

C57BL/6J mice and experimental protocols

The mice were divided into four groups: saline group, MPTP single treatment group, AAV-miR-186-3p NC + MPTP group, and AAV-miR-186-3p sponge + MPTP treatment group. The chronic PD mouse model was established by i.p. of MPTP solution. AAV stereotactic injection was administered to the left substantia nigra of the mouse (relative to the bregma position: − 1.3 mm lateral; − 3.2 mm caudal; and 4.3 mm ventral). The AAV was injected at a rate of 0.5 µL/min, followed by waiting for 5 min after the injection was completed [64]. In the control group of mice, an equal volume of artificial cerebrospinal fluid was injected into the substantia nigra region of the midbrain. The AAV was purchased from Hanyi Biotech (Guangzhou, China) (Supplementary Table 5).

Established PD model

PD cell model: MPP+ stock solutions were prepared in phosphate buffered saline (PBS) at a concentration of 100 mM and the MPP+ stock solutions were stored at − 80 °C for use. MN9D cells were treated with MPP+ at a concentration of 1 mM for 24 h to construct a PD cell model. The control group cells were cultured with normal culture medium for the same period as the experimental groups.

PD mouse model: A chronic PD mouse model was given 30 mg/kg MPTP twice a week for 5 weeks by intraperitoneal injection. In the control group, mice were intraperitoneally injected with an equal volume of saline.

Cell transfections

Cell transfections with 50 nMol miRNA, 50 nMol siRNA, or 2 µg of plasmid were performed using Lipofectamine 2000 (lipo2000) (Thermo Fisher Scientific, Waltham, MA, USA) following the manufacturer’s protocol. In brief, we inoculated 3 × 105 cells into each well of the six-well plate and then added 20 µM miRNA or siRNA and lipo2000 to each well. After 8 h of cell culture using basic medium, the cells were transferred to serum-containing medium and treated with MPP+. The control group cells were cultured with normal culture medium for the same period as the experimental groups. After 24 h of transfection, the cells were collected. The miRNAs and siRNAs were purchased from GenePharm (Suzhou, China) (Supplementary Table 6).

For overexpression of DAT or IGF1R protein, cells were seeded at 3 × 105 cells/well in a six-well plate and then mixed with 2 µg of vector, DAT, or IGF1R plasmid and lipo2000 in each well. After 8 h of cell culture using basic medium, the cells were transferred to serum-containing medium and treated with MPP+. Control group cells were cultured with normal culture medium for the same period as the experimental groups. After 24 h of transfection, the cells were collected. The DAT and IGF1R plasmids were purchased from FulenGen (Guangzhou, China) or MiaoLingBio (Wuhan, China) (Supplementary Table 7).

Immunohistochemistry

Immunohistochemistry experiments were performed as previously reported [65]. Immunohistochemistry was used to detect the TH expression level in the substantia nigra of the mouse midbrain. Briefly, the sections were gently rinsed in phosphate-buffered saline to avoid detachment. Subsequently, the sections were incubated with 3% hydrogen peroxide for 10 min to terminate the endogenous peroxidase activity. After using 0.1% Triton X-100 (Beyotime Biotechnology, Shanghai, China) to penetrate the cell membrane for 20 min, sealing was performed with 5% BSA for 1 h. After diluting the TH antibody with an antibody dilution buffer at a ratio of 1:500, incubate the tissue sections with the TH antibody overnight at 4 °C. Anti-TH (sc-25269) antibodies were purchased from Santa Cruz Biotechnology (Dallas, TX, USA). On the second day, the slices were removed and restored to room temperature. Then, they were gently rinsed in phosphate-buffered saline, incubated with HRP-labeled secondary antibodies, stained with DAB reagent (zsbio, Beijing, China), and observed under an optical microscope (Olympus, Japan).

Statistical analysis

The experiments were performed independently at least three times. The number of mice in each group in animal experiment is shown in the figure legend. The data collected are analyzed with GraphPad Prism 8.0 software, and all results are presented as mean ± standard deviation (SD). Comparisons between two samples were performed using the student’s t-test, while comparisons among three or more groups were conducted using one-way ANOVA. The grayscale values and fluorescence intensity were analyzed using Image-J software. P < 0.05 indicates a statistically significant difference.

Data availability

All data associated with this study are present in the paper or the Supplementary Materials.

Abbreviations

AAV-9:

Adeno-associated virus 9

α-syn:

α-Synuclein

CCK8:

Cell counting kit-8

DA:

Dopamine

DAT:

Dopamine transporter

DATOE :

DAT overexpression plasmid

DLR:

Dual-luciferase reporter

DNA:

Deoxyribonucleic acid

FCM:

Flow cytometry

FISH:

Fluorescence in situ hybridization

GFP:

Green fluorescent protein

IF:

Immunofluorescence

IGF1:

Insulin-like growth factor 1

IGF1R:

Insulin-like growth factor 1 receptor

i.p.:

Intraperitoneal injection

LC–MS/MS:

Liquid chromatography-tandem mass spectrometry

MAPK:

Mitogen-activated protein kinase

MCM2:

Maintenance complex component 2

miRNAs:

MicroRNAs

MPP+ :

1-Methyl-4-phenylpyridinium-iodide

MPTP:

1-Methyl-4-phenyl-1,2,3,6-tetrahydropyridine

PD:

Parkinson’s disease

reverse-ChIP:

Reverse chromatin immunoprecipitation

RT-qPCR:

Real-time quantitative PCR

RNA:

Ribonucleic acid

RUNX3:

Runt domain transcription factor 3

siRNAs:

Small interfering RNAs

slc6a3:

Solute carrier family 6 member 3

TFEB:

Transcription factor EB

TFs:

Transcription factors

TH:

Tyrosine hydroxylase

WB:

Western blotting

References

  1. Wen X, Chi S, Yu Y, Wang G, Zhang X, Wang Z, Gesang M, Luo B. The cerebellum is involved in motor improvements after repetitive transcranial magnetic stimulation in Parkinson’s disease patients. Neuroscience. 2022;499:1–11.

    Article  CAS  PubMed  Google Scholar 

  2. Zhu X, Gan J, Wu N, Zhang Y, Liu Z. The simultaneous presence of demoralization, apathy, and depression has a detrimental impact on both cognitive function and motor symptoms in Parkinson’s disease patients. Front Psychiatry. 2024;15:1345280.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Aarsland D, Batzu L, Halliday G, Geurtsen G, Ballard C, Ray Chaudhuri K, Weintraub D. Parkinson disease-associated cognitive impairment. Nat Rev Dis Primers. 2021;7:47.

    Article  PubMed  Google Scholar 

  4. Rocha EM, De Miranda B, Sanders LH. Alpha-synuclein: pathology, mitochondrial dysfunction and neuroinflammation in Parkinson’s disease. Neurobiol Dis. 2018;109:249–57.

    Article  CAS  PubMed  Google Scholar 

  5. Tolleson CM, Fang JY. Advances in the mechanisms of Parkinson’s disease. Discov Med. 2013;15:61–6.

    PubMed  Google Scholar 

  6. Shadrina MI, Slominsky PA, Limborska SA. Molecular mechanisms of pathogenesis of Parkinson’s disease. Int Rev Cell Mol Biol. 2010;281:229–66.

    Article  CAS  PubMed  Google Scholar 

  7. Sarkar S, Roy A, Choudhury S, Banerjee R, Dey S, Kumar H. Levodopa-induced dyskinesia in Parkinson’s disease: plausible inflammatory and oxidative stress biomarkers. Can J Neurol Sci. 2024;51:104–9.

    Article  PubMed  Google Scholar 

  8. Deuschl G, de Bie R. New therapeutic developments for Parkinson disease. Nat Rev Neurosci. 2019;15:68–9.

    Google Scholar 

  9. Vijiaratnam N, Simuni T, Bandmann O, Morris H, Foltynie T. Progress towards therapies for disease modification in Parkinson’s disease. Lancet Neurol. 2021;20:559–72.

    Article  CAS  PubMed  Google Scholar 

  10. Kumar DK, Jonas F, Jana T, Brodsky S, Carmi M, Barkai N. Complementary strategies for directing in vivo transcription factor binding through DNA binding domains and intrinsically disordered regions. Mol Cell. 2023;83:1462-1473.e1465.

    Article  CAS  PubMed  Google Scholar 

  11. Hajheidari M, Huang SC. Elucidating the biology of transcription factor-DNA interaction for accurate identification of cis-regulatory elements. Curr Opin Plant Biol. 2022;68:102232.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Dassati S, Schweigreiter R, Buechner S, Waldner A. Celecoxib promotes survival and upregulates the expression of neuroprotective marker genes in two different in vitro models of Parkinson’s disease. Neuropharmacology. 2021;194:108378.

    Article  CAS  PubMed  Google Scholar 

  13. Li Z, Yao Q, Tian Y, Jiang Y, Xu M, Wang H, Xiong Y, Fang J, Lu W, Yu D, Shi H. Trehalose protects against cisplatin-induced cochlear hair cell damage by activating TFEB-mediated autophagy. Biochem Pharmacol. 2022;197:114904.

    Article  CAS  PubMed  Google Scholar 

  14. Huang D, Zhang M, Tan Z. Bone marrow stem cell-exo-derived TSG-6 attenuates 1-methyl-4-phenylpyridinium+-induced neurotoxicity via the STAT3/miR-7/NEDD4/LRRK2 axis. J Neuropathol Exp Neurol. 2022;81:621–34.

    Article  CAS  PubMed  Google Scholar 

  15. Mabuchi M, Kataoka H, Miura Y, Kim TS, Kawaguchi M, Ebi M, Tanaka M, Mori Y, Kubota E, Mizushima T, Shimura T, Mizoshita T, Tanida S, Kamiya T, Asai K, Joh T. Tumor suppressor, AT motif binding factor 1 (ATBF1), translocates to the nucleus with runt domain transcription factor 3 (RUNX3) in response to TGF-beta signal transduction. Biochem Biophys Res Commun. 2010;398:321–5.

    Article  CAS  PubMed  Google Scholar 

  16. Su H, Fan G, Huang J, Qiu X. YBX1 regulated by Runx3-miR-148a-3p axis facilitates non-small-cell lung cancer progression. Cell Signal. 2021;85:110049.

    Article  CAS  PubMed  Google Scholar 

  17. Liu C, Wang Y, Li JW, Zhu X, Jiang HS, Zhao H, Zhang LM. MiR-184 mediated the expression of ZNF865 in exosome to promote procession in the PD model. Mol Neurobiol. 2024;61:3397–408.

    Article  CAS  PubMed  Google Scholar 

  18. Wu YY, Kuo HC. Functional roles and networks of non-coding RNAs in the pathogenesis of neurodegenerative diseases. J Biomed Sci. 2020;27:49.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Lv Q, Zhong Z, Hu B, Yan S, Yan Y, Zhang J, Shi T, Jiang L, Li W, Huang W. MicroRNA-3473b regulates the expression of TREM2/ULK1 and inhibits autophagy in inflammatory pathogenesis of Parkinson disease. J Neurochem. 2021;157:599–610.

    Article  CAS  PubMed  Google Scholar 

  20. Wang R, Li Q, He Y, Yang Y, Ma Q, Li C. miR-29c-3p inhibits microglial NLRP3 inflammasome activation by targeting NFAT5 in Parkinson’s disease. Genes Cells. 2020;25:364–74.

    Article  CAS  PubMed  Google Scholar 

  21. Lu X, Song X, Hao X, Liu X, Zhang X, Yuan N, Ma H, Zhang Z. MiR-186-3p attenuates tumorigenesis of cervical cancer by targeting IGF1. World J Surg Oncol. 2021;19:207.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Xia T, Zhang Z, Zhang X, Li Q. Hsa-miR-186-3p suppresses colon cancer progression by inhibiting KRT18/MAPK signaling pathway. Cell Cycle. 2022;21:741–53.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Lu X, Song X, Hao X, Liu X, Zhang X, Yuan N, Ma H, Zhang Z. MicroRNA-186-3p attenuates tumorigenesis of cervical cancer by targeting MCM2. Oncol Lett. 2021;22:539.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. McHugh PC, Buckley DA. The structure and function of the dopamine transporter and its role in CNS diseases. Vitam Horm. 2015;98:339–69.

    Article  CAS  PubMed  Google Scholar 

  25. Ducrot C, de Carvalho G, Delignat-Lavaud B, Delmas CVL, Halder P, Giguère N, Pacelli C, Mukherjee S, Bourque MJ, Parent M, Chen LY, Trudeau LE. Conditional deletion of neurexins dysregulates neurotransmission from dopamine neurons. Elife. 2023;12: e87902.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Michałowska M, Chalimoniuk M, Jówko E, Przybylska I, Langfort J, Toczylowska B, Krygowska-Wajs A, Fiszer U. Gene polymorphisms and motor levodopa-induced complications in Parkinson’s disease. Brain Behav. 2020;10: e01537.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Tafani X, Pascale E, Fattapposta F, Pucci M, D’Addario C, Adriani W. Cross-correlations between motifs in the 5ʹ-UTR of DAT1 gene: findings from Parkinson’s disease. Adv Biol Regul. 2020;78:100753.

    Article  CAS  PubMed  Google Scholar 

  28. Crudden C, Shibano T, Song D, Suleymanova N, Girnita A, Girnita L. Blurring boundaries: receptor tyrosine kinases as functional G protein-coupled receptors. Int Rev Cell Mol Biol. 2018;339:1–40.

    Article  CAS  PubMed  Google Scholar 

  29. Martínez Báez A, Ayala G, Pedroza-Saavedra A, González-Sánchez HM, Chihu Amparan L. Phosphorylation codes in IRS-1 and IRS-2 are associated with the activation/inhibition of insulin canonical signaling pathways. Curr Issues Mol Biol. 2024;46:634–49.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Cannarella R, Condorelli RA, La Vignera S, Calogero AE. Effects of the insulin-like growth factor system on testicular differentiation and function: a review of the literature. Andrology. 2018;6:3–9.

    Article  CAS  PubMed  Google Scholar 

  31. Wang XW, Yuan LJ, Yang Y, Zhang M, Chen WF. IGF-1 inhibits MPTP/MPP(+)-induced autophagy on dopaminergic neurons through the IGF-1R/PI3K-Akt-mTOR pathway and GPER. Am J Physiol Endocrinol Metab. 2020;319:E734-e743.

    Article  CAS  PubMed  Google Scholar 

  32. Dawson T, Golde T, Lagier-Tourenne C. Animal models of neurodegenerative diseases. Nat Neurosci. 2018;21:1370–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Feng Z, Zhu Z, Chen W, Bai Y, Hu D, Cheng J. Chloride intracellular channel 4 participate in the protective effect of Ginkgolide B in MPP+ injured MN9D cells: insight from proteomic analysis. Clin Proteomics. 2020;17:32.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Viridiana CA, Ángel VM, Ruth RE. MicroRNAs: beyond post-transcriptional regulation of mRNAs. Microrna. 2021;10:229–39.

    Article  CAS  PubMed  Google Scholar 

  35. Rai SN, Dilnashin H, Birla H, Singh SS, Zahra W, Rathore AS, Singh BK, Singh SP. The role of PI3K/Akt and ERK in neurodegenerative disorders. Neurotox Res. 2019;35:775–95.

    Article  CAS  PubMed  Google Scholar 

  36. Ju DT, Sivalingam K, Kuo WW, Ho TJ, Chang RL, Chung LC, Day CH, Viswanadha VP, Liao PH, Huang CY. Effect of vasicinone against paraquat-induced MAPK/p53-mediated apoptosis via the IGF-1R/PI3K/AKT pathway in a Parkinson’s disease-associated SH-SY5Y cell model. Nutrients. 2019;11:1655.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Latif S, Jahangeer M, Maknoon Razia D, Ashiq M, Ghaffar A, Akram M, El Allam A, Bouyahya A, Garipova L, Ali Shariati M, Thiruvengadam M, Azam Ansari M. Dopamine in Parkinson’s disease. Clin Chim Acta. 2021;522:114–26.

    Article  CAS  PubMed  Google Scholar 

  38. Wang T, Li C, Han B, Wang Z, Meng X, Zhang L, He J, Fu F. Neuroprotective effects of Danshensu on rotenone-induced Parkinson’s disease models in vitro and in vivo. BMC Complement Med Ther. 2020;20:20.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Zhang ZD, Yang YJ, Liu XW, Qin Z, Li SH, Bai LX, Li JY. The protective effect of aspirin eugenol ester on oxidative stress to PC12 cells stimulated with H(2)O(2) through regulating PI3K/Akt signal pathway. Oxid Med Cell Longev. 2021;2021:5527475.

    PubMed  PubMed Central  Google Scholar 

  40. Wang XH, Zuo ZF, Meng L, Yang Q, Lv P, Zhao LP, Wang XB, Wang YF, Huang Y, Fu C, Liu WQ, Liu XZ, Zheng DY. Neuroprotective effect of salidroside on hippocampal neurons in diabetic mice via PI3K/Akt/GSK-3β signaling pathway. Psychopharmacology. 2023. https://doi.org/10.1007/s00213-023-06373-z.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Huang N, Huang J, Zhang Y, Chen M, Shi J, Jin F. Resveratrol against 6-OHDA-induced damage of PC12 cells via PI3K/Akt. Transl Neurosci. 2021;12:138–44.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Jiang D, Peng Y. The protective effect of decoction of Rehmanniae via PI3K/Akt/mTOR pathway in MPP+-induced Parkinson’s disease model cells. J Recept Signal Transduct. 2020;41:74–84.

    Article  Google Scholar 

  43. Szász JA, Dulamea AO, Constantin VA, Mureşanu DF, Dumbravă LP, Tiu C, Jianu DC, Simu M, Ene A, Axelerad A, Falup-Pecurariu C, Lungu M, Danci AG, Sabau M, Strilciuc Ş, Popescu BO. Levodopa-carbidopa-entacapone intestinal gel in advanced Parkinson disease: a multicenter real-life experience. Am J Ther. 2024;31:e209–18.

    Article  PubMed  Google Scholar 

  44. Stevenson M, Varghese R, Hebron ML, Liu X, Ratliff N, Smith A, Turner RS, Moussa C. Inhibition of discoidin domain receptor (DDR)-1 with nilotinib alters CSF miRNAs and is associated with reduced inflammation and vascular fibrosis in Alzheimer’s disease. J Neuroinflammation. 2023;20:116.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Chava S, Reynolds CP, Pathania AS, Gorantla S, Poluektova LY, Coulter DW, Gupta SC, Pandey MK, Challagundla KB. miR-15a-5p, miR-15b-5p, and miR-16-5p inhibit tumor progression by directly targeting MYCN in neuroblastoma. Mol Oncol. 2020;14:180–96.

    Article  CAS  PubMed  Google Scholar 

  46. Robertson BD, Al Jaja AS, MacDonald AA, Hiebert NM, Tamjeedi R, Seergobin KN, Schwarz UI, Kim RB, MacDonald PA. SLC6A3 polymorphism predisposes to dopamine overdose in Parkinson’s disease. Front Neurol. 2018;9:693.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Roussakis AA, Gennaro M, Lao-Kaim NP, Towey D, Piccini P. Dopamine transporter density in de novo Parkinson’s disease does not relate to the development of levodopa-induced dyskinesias. J Neuroinflamm Neurodegener Dis. 2019;3:10000.

    PubMed  PubMed Central  Google Scholar 

  48. Luo X, Xia Y, Li XD, Wang JY. The effect of AP-2δ on transcription of the Prestin gene in HEI-OC1 cells upon oxidative stress. Cell Mol Biol Lett. 2019;24:45.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Tong Z, Cui Q, Wang J, Zhou Y. TransmiR v2.0: an updated transcription factor-microRNA regulation database. Nucleic Acids Res. 2019;47:D253–8.

    Article  CAS  PubMed  Google Scholar 

  50. Zhu W, Lei J, Bai X, Wang R, Ye Y, Bao J. MicroRNA-503 regulates hypoxia-induced cardiomyocytes apoptosis through PI3K/Akt pathway by targeting IGF-1R. Biochem Biophys Res Commun. 2018;506:1026–31.

    Article  CAS  PubMed  Google Scholar 

  51. Rabie MA, Abd El Fattah MA, Nassar NN, El-Abhar HS, Abdallah DM. Angiotensin 1–7 ameliorates 6-hydroxydopamine lesions in hemiparkinsonian rats through activation of MAS receptor/PI3K/Akt/BDNF pathway and inhibition of angiotensin II type-1 receptor/NF-κB axis. Biochem Pharmacol. 2018;151:126–34.

    Article  CAS  PubMed  Google Scholar 

  52. Hang W, Fan HJ, Li YR, Xiao Q, Jia L, Song LJ, Gao Y, Jin XM, Xiao BG, Yu JZ, Ma CG, Chai Z. Wuzi Yanzong pill attenuates MPTP-induced Parkinson’s Disease via PI3K/Akt signaling pathway. Metab Brain Dis. 2022;37:1435–50.

    Article  CAS  PubMed  Google Scholar 

  53. Yuan LJ, Zhang M, Chen S, Chen WF. Anti-inflammatory effect of IGF-1 is mediated by IGF-1R cross talk with GPER in MPTP/MPP(+)-induced astrocyte activation. Mol Cell Endocrinol. 2021;519:111053.

    Article  CAS  PubMed  Google Scholar 

  54. Ye M, Zhao L, Zhang L, Wu S, Li Z, Qin Y, Lin F, Pan L. LncRNA NALT1 promotes colorectal cancer progression via targeting PEG10 by sponging microRNA-574-5p. Cell Death Dis. 2022;13:960.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Dolgacheva LP, Berezhnov AV, Fedotova EI, Zinchenko VP, Abramov AY. Role of DJ-1 in the mechanism of pathogenesis of Parkinson’s disease. J Bioenerg Biomembr. 2019;51:175–88.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Fang P, Xiang L, Chen W, Li S, Huang S, Li J, Zhuge L, Jin L, Feng W, Chen Y, Pan C. LncRNA GAS5 enhanced the killing effect of NK cell on liver cancer through regulating miR-544/RUNX3. Innate Immun. 2019;25:99–109.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Zhuang Y, Xu P, Mao C, Wang L, Krumm B, Zhou XE, Huang S, Liu H, Cheng X, Huang XP, Shen DD, Xu T, Liu YF, Wang Y, Guo J, Jiang Y, Jiang H, Melcher K, Roth BL, Zhang Y, Zhang C, Xu HE. Structural insights into the human D1 and D2 dopamine receptor signaling complexes. Cell. 2021;184:931-942.e918.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Ostrea MC, Rosales RL, Joya-Tanglao M. Efficacy and safety of apomorphine pump infusion in Filipino patients insufficiently controlled on oral anti-Parkinson medications: an open-label, pilot study. Int J Neurosci. 2024;134:131–6.

    Article  CAS  PubMed  Google Scholar 

  59. Morris HR, Spillantini MG, Sue CM, Williams-Gray CH. The pathogenesis of Parkinson’s disease. Lancet. 2024;403:293–304.

    Article  CAS  PubMed  Google Scholar 

  60. Gareev I, Beylerli O, Tamrazov R, Ilyasova T, Shumadalova A, Du W, Yang B. Methods of miRNA delivery and possibilities of their application in neuro-oncology. Noncoding RNA Res. 2023;8:661–74.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Goleij P, Babamohamadi M, Rezaee A, Sanaye PM, Tabari MAK, Sadreddini S, Arefnezhad R, Motedayyen H. Types of RNA therapeutics. Prog Mol Biol Transl Sci. 2024;203:41–63.

    Article  PubMed  Google Scholar 

  62. Mustapha M, Taib CNM. MPTP-induced mouse model of Parkinson’s disease: a promising direction of therapeutic strategies. Bosn J Basic Med Sci. 2021;21:422–33.

    CAS  PubMed  PubMed Central  Google Scholar 

  63. Winkle M, El-Daly SM, Fabbri M, Calin GA. Noncoding RNA therapeutics—challenges and potential solutions. Nat Rev Drug Discov. 2021;20:629–51.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Karikari AA, McFleder RL, Ribechini E, Blum R, Bruttel V, Knorr S, Gehmeyr M, Volkmann J, Brotchie JM, Ahsan F, Haack B, Monoranu CM, Keber U, Yeghiazaryan R, Pagenstecher A, Heckel T, Bischler T, Wischhusen J, Koprich JB, Lutz MB, Ip CW. Neurodegeneration by α-synuclein-specific T cells in AAV-A53T-α-synuclein Parkinson’s disease mice. Brain Behav Immun. 2022;101:194–210.

    Article  CAS  PubMed  Google Scholar 

  65. Ozdemir HS, Yunusoglu O, Sagmanligil V, Yasar S, Colcimen N, Goceroglu R, Catalkaya E. Investigation of the pharmacological, behavioral, and biochemical effects of boron in Parkinson-indicated rats. Cell Mol Biol. 2022;68:13–21.

    Article  PubMed  Google Scholar 

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Acknowledgements

This work was supported by Grants from the National Natural Science Foundation of China (81870991), the Natural Science Foundation of Guangdong Province (2022A1515010352), the Jiangxi Provincial Natural Science Foundation (20232ACB206021) and the Science and Technology Projects in Guangzhou (2024B03J1257).

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S.Q. performed study design, project supervision, data analysis, and critical revision of the manuscript. P.H. performed the experiments and statistical analyses and wrote the first draft of the manuscript. Z.W. conducted experiments and statistical analyses. All authors discussed the results and reviewed the manuscript.

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Correspondence to Shaogang Qu.

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Huang, P., Wan, Z. & Qu, S. Targeting the RUNX3–miR-186-3p–DAT–IGF1R axis as a therapeutic strategy in a Parkinson’s disease model. J Transl Med 22, 719 (2024). https://doi.org/10.1186/s12967-024-05535-7

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