Plasma exosomal ncRNA biomarkers for recurrent depression and uses thereof

Abstract

The application discloses a plasma exosome ncRNA biomarker of recurrent depression and application thereof, and the biomarker comprises miR-618 and / or miR-223-3p. It is verified by RT-qPCR that the average expression levels of miR-618 and miR-223-3p of patients with recurrent depression are significantly higher than those of healthy controls, ROC curve analysis shows that miR-618 and miR-223-3p both show good diagnostic performance, both have the potential of being biomarkers of recurrent depression, and have good application prospect. In addition, the molecular function of miR-618 is verified through in-vivo experiments, and the result shows that miR-618 regulates PI3K-Akt and other signal pathways, and then causes depressive behaviors.

Description

Technical Field

[0001] This invention relates to the fields of biotechnology and medical diagnostics, specifically to plasma exosomal ncRNA biomarkers for recurrent depression and their applications. Background Technology

[0002] Major depression disorder (MDD) is a group of mood or affective disorders caused by various factors, characterized by depressed mood and anhedonia as the main symptoms. As a mental illness with a high incidence and long course, MDD poses significant risks to patients, severely impairing their quality of life and seriously threatening their daily lives, work, and even their safety. The etiology of MDD is complex, and its pathogenesis is not fully understood, but it is generally believed to be related to the combined effects of genetic, psychological, social, and neurobiochemical factors. MDD can achieve ideal therapeutic effects with standardized treatment, and the prognosis is generally good, but there is a risk of relapse. Recurrent depressive disorder (RDD) is characterized by two or more independent depressive episodes, with asymptomatic intervals lasting at least two months between episodes. RDD patients have complex conditions, typical symptoms, and are difficult to treat, causing significant psychological and economic burdens. Furthermore, research indicates that a large part of the burden for MDD patients stems from recurrent depressive episodes, with a relapse rate as high as 70%, and an individual relapse rate positively correlated with the number of episodes. Currently, there is a lack of reliable diagnostic biomarkers for RDD, forcing clinical diagnosis to rely on clinical interviews and behavioral observations. This subjective approach increases the risk of diagnostic delays or misdiagnosis. Therefore, identifying biomarkers for RDD is urgent and of great significance.

[0003] Exosomes are extracellular vesicles released by cells, with a diameter of approximately 40–160 nm. They are formed by the invagination of intracellular lysosomal granules. Due to their relatively stable double-membrane structure, exosomes serve as ideal carriers of DNA, RNA, proteins, and other metabolites, playing a crucial role in intercellular communication. Exosomes encapsulate a large number of bioactive molecules, such as proteins, lipids, and nucleic acids, including non-coding RNAs (ncRNAs). With the development of sequencing technology, researchers have gradually discovered that ncRNAs participate in various stages of life processes and play an important role in the occurrence and development of various diseases. ncRNAs mainly include relatively conserved microRNAs (miRNAs) and circRNAs, as well as long non-coding RNAs (lncRNAs) with poor cross-species conservation. Increasing evidence suggests that ncRNAs can act as regulators of many physiological and pathological processes, regulating gene expression at multiple levels through interactions with DNA, RNA, or proteins.

[0004] Ruting Wang et al. found that Exo-miR-144-3p could serve as a potential diagnostic biomarker for depressive symptoms in patients with heart failure. Rekha S Patel et al. found that lncRNA VLDLR-AS1 could serve as a blood biomarker for identifying chronic minor traumatic brain injury and depression in patients. Previous studies have shown the presence of dysregulated miRNAs in patients with depression, but few studies have investigated the relationship between ncRNAs and recurrent depression (RDD). Summary of the Invention

[0005] The purpose of this invention is to identify differentially expressed ncRNAs in plasma exosomes of patients with recurrent depression through high-throughput sequencing, predict the pathogenesis of recurrent depression from the perspective of CeRNA regulatory network through bioinformatics analysis, search for potential biomarkers through RT-qPCR and ROC analysis, and verify the molecular function of miR-618 through in vivo experiments.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] The present invention first provides an ncRNA biomarker for recurrent depression, the biomarker comprising miR-618 and / or miR-223-3p; the sequence of miR-618 is AAACUCUACUUGUCCUUCUGAGU, and the sequence of miR-223-3p is UGUCAGUUUGUCAAAUACCCCA.

[0008] Furthermore, the biomarker is derived from plasma exosomes.

[0009] Furthermore, the ncRNA biomarkers impair nerve cell and synaptic plasticity by regulating the PI3K-Akt signaling pathway, thereby leading to depressive-like behavior.

[0010] The present invention also provides the application of the above-mentioned ncRNA biomarkers (miR-618 and / or miR-223-3p) in the preparation of diagnostic products for recurrent depression.

[0011] Furthermore, the ncRNA biomarker was significantly overexpressed in plasma samples of recurrent depression.

[0012] Furthermore, the expression of miR-618 and / or miR-223-3p in plasma was detected by RT-qPCR.

[0013] The present invention also provides a diagnostic kit for recurrent depression, the kit comprising reagents for detecting miR-618 and / or miR-223-3p.

[0014] Furthermore, the reagents include reverse transcription reagents for miR-618 and / or miR-223-3p, as well as RT-qPCR detection reagents and primers.

[0015] Furthermore, the upstream primer for miR-618 RT-qPCR is: GTGCGAAACTCTACTTGTCCTT, and the downstream primer is the universal primer AGTGCAGGGTCCGAGGTATT.

[0016] Furthermore, the upstream primer for miR-223-3p RT-qPCR is: GCGCGTGTCAGTTTGTCAAA, and the downstream primer is the universal primer AGTGCAGGGTCCGAGGTAT.

[0017] The beneficial effects of this invention are as follows:

[0018] This invention utilizes plasma samples from clinically diagnosed recurrent depression (RDD) patients. Exosomes were extracted using a commercial kit (centrifugation column method), and the extracted exosomes were characterized and identified from three perspectives: morphology, particle size analysis, and marker proteins. Total RNA was extracted using the Trizol method, and library sequencing analysis was performed using high-throughput sequencing to screen for differentially expressed ncRNAs in RDD. A ceRNA regulatory network was constructed and bioinformatics analysis was conducted to explore the potential regulatory mechanism of ncRNAs on RDD. RT-qPCR confirmed that the expression levels of miR-618 and miR-223-3p in patients with RDD were significantly higher than in healthy controls. ROC analysis showed that both miR-618 and miR-223-3p exhibited good diagnostic performance and have the potential to serve as biomarkers for RDD, demonstrating promising application prospects. Furthermore, in vivo experiments validated the molecular function of miR-618, indicating that miR-618 impairs nerve cell and synaptic plasticity by regulating the PI3K-Akt signaling pathway, thereby leading to depressive-like behavior. Attached Figure Description

[0019] Figure 1 This is a high-throughput sequencing route.

[0020] Figure 2 A route for constructing the CeRNA regulatory network.

[0021] Figure 3 The images show the morphological structure and characteristics of plasma exosomes under a transmission electron microscope, with a scale bar of 100 nm.

[0022] Figure 4 Figure 1 shows the results of plasma exosome particle size analysis. Figure A shows the single representative particle size analysis results of exosomes from the HC group, and Figure B shows the single representative particle size analysis results of exosomes from the RDD group.

[0023] Figure 5 The bands are for detecting plasma exosome marker proteins.

[0024] Figure 6 Volcano plot / scatter plot of differentially expressed RNAs between the RDD and HC groups; red dots represent genes upregulated in the RDD group relative to the HC group, green dots represent genes downregulated, and gray dots represent genes with no significant difference. The vertical axis represents the p-value; the smaller the p-value, the lower the corresponding -log 10 The larger the pValue, the more significant the difference; the horizontal axis is log2 (fold change), and the further the point is from the center, the greater the difference factor.

[0025] Figure 7This is a heatmap of differentially expressed RNAs clusters; each column represents a different sample number, and each row represents a different gene; the corresponding colors represent the expression level of the gene in the sample: red indicates high expression, and blue indicates low expression.

[0026] Figure 8 This is a LncRNA / CircRNA-miRNA-mRNA regulatory network, where green nodes represent LncRNAs, red nodes represent miRNAs, blue nodes represent CircRNAs, and yellow nodes represent mRNAs.

[0027] Figure 9 This is a PPI network diagram; the 12 nodes in the inner ring are hub genes, and the larger the node, the darker the color, representing a higher degree of connectivity.

[0028] Figure 10 This is a bar chart showing the GO enrichment of mRNA in the CeRNA network; where -log is the GO enrichment value. 10 The longer the (pvalue) line, the smaller the p-value and the more significant the difference; the longer the Gene count line, the more gene enrichment there is.

[0029] Figure 11 This is a KEGG enrichment Sanguis bubble plot of mRNA in the CeRNA network; the left plot shows the enrichment relationship between genes and pathways; the horizontal axis Ratio in the right plot refers to the ratio of the number of differentially expressed genes located in that pathway to the total number of annotated genes located in that pathway. The larger the Ratio, the higher the degree of enrichment.

[0030] Figure 12 RT-qPCR quantification results for miR-618 and miR-223-3p.

[0031] Figure 13 The results of RT-qPCR quantification of 9 RNAs are shown.

[0032] Figure 14 The ROC analysis results are for miR-618 and miR-223-3p.

[0033] Figure 15 The results show the fluorescence co-localization of cells after transfection.

[0034] Figure 16 Figure 1 shows the exosome characterization results; Figure (A) shows the morphology of exosomes under a transmission electron microscope, Figure (B) shows the exosome particle size analysis diagram, and Figure (C) shows the bands of exosome marker proteins.

[0035] Figure 17 The results are RT-qPCR for miR-618.

[0036] Figure 18 Results of BV2 cell uptake.

[0037] Figure 19 Figure 1 shows the results of behavioral experiments; Figure 2 shows the representative activity trajectory of mice in the open field experiment, Figure 3 shows the activity distance of mice in the open field experiment, Figure 4 shows the average speed of mice in the open field experiment, Figure 5 shows the resting time of mice in the open field experiment, Figure 6 shows the sucrose preference index of mice in the sucrose preference experiment, Figure 7 shows the resting time of mice in the forced swimming experiment, and Figure 8 shows the resting time of mice in the tail suspension experiment.

[0038] Figure 20 The results are RT-qPCR results; the relative expression levels of miR-618 (A), TP53 (B), and CCND1 (C) in hippocampal tissue were detected by RT-qPCR.

[0039] Figure 21 Figure AE shows the Western blot results; these are representative immunoblot bands from the Western blot. The expression levels of BDNF (A), Bax (B), Bcl2 (C), p-PI3K / t-PI3K (D), and p-Akt / t-Akt (E) were normalized using β-actin as an internal reference. The expression levels of phosphorylated Akt (F) and phosphorylated PI3K (G) were calculated with their respective total protein levels as a reference.

[0040] Figure 22 Representative images of H&E-stained dentate gyrus, scale bars (from top to bottom): 600 μm, 100 μm, 50 μm. Detailed Implementation

[0041] To make the content of this invention easier to understand, the technical solution of this invention will be further described below with reference to specific embodiments, but this invention is not limited thereto.

[0042] All statistical analyses in the following examples were performed using GraphPad Prism 10.1.2 software. In demographic information, data are presented as mean ± standard deviation. Comparisons between two groups were performed using t-tests, and comparisons among multiple groups were performed using one-way ANOVA. Receiver operating characteristic (ROC) curve analysis was performed using SPSS Statistics 27 software. P < 0.05 was considered statistically significant.

[0043] Example 1

[0044] (a) Sample grouping and plasma collection

[0045] This invention selected patients with recurrent depression hospitalized at Xiamen Xianyue Hospital as research subjects. Inclusion criteria: ① All patients with recurrent depression met the relevant diagnostic criteria of the Chinese Classification and Diagnostic Criteria for Mental Disorders, 3rd Edition (CCMD-3) and the International Classification of Diseases, 10th Edition (ICD-10); ② A score ≥17 on the 17-item Hamilton Depression Rating Scale (HAMD-17); ③ Age between 18 and 65 years; ④ Signed informed consent. Exclusion criteria: ① Currently receiving hormone therapy; ② History of substance use and alcoholism; ③ Comorbid serious physical illness or organic brain disease; ④ Other mental illnesses such as bipolar disorder, schizophrenia, and epilepsy. Age- and sex-matched healthy controls were recruited from health checkups conducted at Xiamen Xianyue Hospital and in the community during the same period. Inclusion criteria: No prior diagnosis of any mental illness, and no family history of mental illness, major physical illness, or neurodevelopmental disorders.

[0046] This study recruited 42 participants, divided into 21 patients with recurrent depression (RDD) (RDD group) and 21 healthy controls (HC group). Demographic information was collected for each participant via a general information questionnaire, and the levels of depression and anxiety in each participant were assessed by two experienced psychiatrists using the Hamilton Depression Rating Scale-17 (HAMD-17) and the Hamilton Anxiety Rating Scale (HAMA). There were no statistically significant differences in age and sex between the RDD and HC groups (see Table 1). Venous blood was collected from participants between 8:00 AM and 10:00 AM after an 8-hour fast in EDTA anticoagulant tubes. After the blood collection tubes were left to stand at room temperature for 10 minutes, plasma was collected by centrifugation at 3000 rpm for 5 minutes at 4°C. The plasma was then stored at -80°C. Three plasma samples from each of the RDD and HC groups were used for high-throughput sequencing, and the remaining 18 plasma samples were used for reverse transcription quantitative polymerase chain reaction (RT-qPCR).

[0047] This study involving human participants has been reviewed and approved by the Medical Ethics Committee of the Second Affiliated Hospital of Xiamen Medical College (Approval No.: 2025088, April 3, 2025), and all participants signed informed consent forms before participation. The study complies with the Declaration of Helsinki and all applicable laws and institutional guidelines.

[0048] Table 1. Demographic and clinical characteristics of the RDD and HC groups

[0049]

[0050] (II) Extraction and characterization of plasma exosomes

[0051] Exosomes were extracted and purified from 500 µL of plasma using an exosome extraction and purification kit (Umibio, China). Following the guidelines of the International Society for Extracellular Vesicles (ISEV), the extracted exosomes were characterized using several complementary methods: transmission electron microscopy (TEM), nanoparticle tracking analysis (NTA), and Western blot. The specific methods are as follows:

[0052] Transmission electron microscopy:

[0053] 10 μL of exosome suspension was dropped onto a carbon-coated copper grid. After 2 min, excess liquid was blotted off with filter paper. The copper grid was then negatively stained with 10 μL of 3% phosphotungstic acid. After 2 min, excess liquid was blotted off with filter paper, and the copper grid was then transferred to infrared light for drying. The copper grid with the fixed sample was placed under a Hitachi HT7700 EXALEN (Hitachi, Japan) electron microscope with an accelerating voltage of 120 kV to observe the morphology of the exosomes and to take photographs.

[0054] Nanoparticle tracking analysis:

[0055] The particle size and concentration of exosomes were detected using a Zeta View nanoparticle tracking analyzer (Particle Metrix, Germany). First, a calibration solution was prepared by diluting 10 μL of a 100 nm polystyrene standard solution 250,000 times with ultrapure water. This calibration solution was then injected into the instrument using a syringe to complete instrument calibration. Subsequently, 20 μL of exosome suspension was added to 6 mL of PBS, and then 5 mL of a 300-fold diluted exosome suspension was injected into the instrument for detection.

[0056] Western blot:

[0057] 100 μL of exosome suspension was mixed with 100 μL of RIPA lysis buffer (LABLEAD, China) containing 1% PMSF. After shaking on ice for 30 min, the mixture was centrifuged at 12,000 rpm for 10 min at 4°C. The supernatant was then carefully transferred to a new 1.5 mL centrifuge tube. The total protein concentration in the supernatant was determined using a BCA protein assay kit (LABLEAD, China). The remaining protein sample was mixed with 5× SDS-PAGE protein loading buffer (Servicebio, China) at a 4:1 ratio and heat-denatured in a 95°C metal bath for 5 min.

[0058] A 10% separating gel was prepared using a one-step ultra-fast gel preparation kit (Meilun, China). 40 μg of total protein was loaded for separation, and electrophoresis was performed at a constant voltage of 200 V for 40 min. Subsequently, the protein was transferred to a PVDF membrane (Immobilon, USA) at a current of 400 mA for 40 min. After incubating the PVDF membrane with TBST containing 5% BSA for 1 hour at room temperature, the membrane was washed three times with TBST for 10 minutes each time, and then incubated overnight at 4°C with the following primary antibodies: Anti-CD9 Antibody (Recombinant Rabbit monoclonal IgG, clone SA35-08, Cat# ET1601-9, 1:1000, HUABIO, China), Anti-CD63 Antibody (Recombinant Rabbit monoclonal IgG, clone SY21-02, Cat# ET1607-2, 1:500, HUABIO, China) and Anti-TSG101 Antibody (Recombinant Rabbit monoclonal IgG, clone JJ0900, Cat# ET1701-59, 1:2000, HUABIO, China). The following day, the membrane was washed three times with TBST for 10 min each time. Then, the PVDF membrane was incubated at room temperature with HRP-Labelled Goat Anti-Rabbit IgG (H+L) (Cat# A0208, 1:1000, Beyotime, China) for 1 h, followed by three washes with TBST for 10 min each time. Finally, the PVDF membrane was immersed in BeyoECL Plus (Beyotime, China) for 10 s, and then subjected to Western blot analysis using the e-BLOT Touch imaging system (e-BLOT, China).

[0059] Figure 3 The images show plasma-derived exosomes observed under a transmission electron microscope. They are approximately 100 nm in size and exhibit a cup- or saucer-like shape, consistent with the morphological characteristics of exosomes. In addition to transmission electron microscopy, ZetaView nanoparticle tracking analysis was used to analyze the particle size and concentration of the exosomes. The particle size range of plasma exosomes in the HC and RDD groups was 50-300 nm. Figure 4The peak particle sizes were 131 nm and 141 nm, respectively. Finally, Western blotting was used to randomly detect the plasma exosome marker proteins CD9 (25 kDa), CD63 (26 kDa), and TSG101 (44 kDa) in 3 RDD patients and 3 healthy controls. The target protein bands were clearly visible. Figure 5 ).

[0060] Example 2

[0061] (I) Construction and sequencing of miRNA libraries

[0062] Plasma exosomes from 3 patients with recurrent depression and 3 healthy controls were used for high-throughput RNA sequencing. For detailed procedures, please refer to [link to documentation]. Figure 1 First, total RNA was extracted from 100 μL of exosome suspension using the Exosome RNA Purification Kit (EZBioscience, USA). RNA concentration for each sample was measured using a NanoDrop ND-1000 system (Thermo Fisher Scientific, USA). Following this, high-throughput miRNA sequencing services were provided by Shanghai Yunxu Biotechnology Co., Ltd. RNA libraries were constructed using the GenSeq Small RNA Library Prep Kit (GenSeq, China) according to the supplier's instructions. After gel extraction and recovery of fragments of specific sizes, the libraries were quality-controlled and quantified using a BioAnalyzer 2100 system. The libraries were then sequenced at 50 bp single-end mode on an Illumina NovaSeq sequencer. After sequencing, image analysis, and base identification, raw data (Raw reads) were obtained. Quality control was first performed using Q30. Then, the original reads were de-linked using the cutadapt software (v1.9.3), removing low-quality reads and retaining reads ≥15 nt in length, resulting in clean reads. The clean reads for each sample were aligned to the merged pre-miRNA database (miRBase pre-miRNAs (v22) + newly predicted pre-miRNAs) using the Novoalign software (v3.02.12), allowing a maximum of one mismatch. The number of tags aligned to each mature miRNA was counted as the original expression level of that miRNA, and normalized using the TPM (tag counts per million aligned miRNAs) method.

[0063] (II) Construction and sequencing of long RNA libraries

[0064] High-throughput sequencing of long RNA was provided by Shanghai Yunxu Biotechnology Co., Ltd. First, the ribosomal RNA (rRNA) in the samples was removed using the GenSeq rRNA Removal Kit (Byotime, China). Libraries were constructed using the GenSeq Low Input RNA Library Prep Kit (Byotime, China), and then the libraries were quality-controlled and quantified using the BioAnalyzer 2100 system. The libraries were then sequenced at 150bp paired-end mode on a BGI T7 sequencer. After sequencing, long cfRNAs underwent image analysis, base identification, and quality control to obtain raw data reads. The raw reads were first quality-controlled using Q30, Fast QC, and Fast Q Screen. Adapters were removed from the raw reads using cutadapt software (v1.9.3), and low-quality reads were eliminated. Yunxu Biotechnology used different methods to analyze circRNA, lncRNA, and mRNA separately.

[0065] circRNA: High-quality reads were aligned to a reference genome / transcriptome using BWA software, and circular RNAs were detected and identified using CIRI2 software. The identified circular RNAs were then annotated using the circBase database and Circ2Traits.

[0066] LncRNA & mRNA: High-quality reads were aligned to a reference genome using hisat2 software (v2.0.4). Then, raw counts at the gene level were obtained using HTSeq software (v0.9.1) as mRNA expression profiles, and raw counts at the transcript level were obtained as LncRNA expression profiles.

[0067] (III) Bioinformatics Analysis

[0068] RNA differential expression analysis:

[0069] After obtaining the RNA sequencing results, edgeR software (v3.16.5) was used for data standardization and differentially expressed RNA screening. The fold change, P-value, and FDR of the expression levels of the four RNAs were calculated between groups, and the fold change ≥2.0 and P-value ≤0.05 were used as the screening thresholds for differentially expressed RNAs.

[0070] Construction of CeRNA regulatory network:

[0071] LncRNAs and circRNAs interacting with differentially expressed miRNAs (DEmiRNAs) were predicted in the starBase database, and their intersections with the corresponding screened differentially expressed miRNAs were then calculated. Target genes (mRNAs) of DEmiRNAs were predicted in the miRWalk, TargetScan, and miRDB databases, and their unions were calculated. Target genes related to RDDs were retrieved from the GeneCards database. By performing intersection analysis between the target genes of DEmiRNAs and RDD-related genes, potential regulatory targets of miRNAs in the pathogenesis of RDDs were identified. The results were used to construct a competitive endogenous RNA (ceRNA) network, and the data were imported into Cytoscape 3.10.0 software for network visualization.

[0072] Construction of protein-protein interaction networks (PPIs) and screening of Hub genes:

[0073] mRNAs from the CeRNA network were input into the STRING online database to construct a protein-protein interaction network (PPI). Protein pairs with a combineine score > 0.4 were selected, and the PPI network diagram was drawn using Cytoscape 3.10.0 software. Then, the CytoHubba plugin was used to identify hub genes closely related to the RDD.

[0074] Enrichment analysis of GO and KEGG pathways:

[0075] To better explain the relationship between differentially expressed genes and recurrent depression, we performed GO function and KEGG pathway analysis on mRNAs in the CeRNA network to infer the possible functions of differentially expressed genes. Figure 2 mRNA from the CeRNA network was imported into the DAVID database for GO enrichment and KEGG pathway analysis, with a P-value ≤ 0.05 as the threshold for significant enrichment.

[0076] Sequencing result quality control:

[0077] After obtaining raw reads from exosomal RNA sequencing, to ensure the quality of information analysis, Q30 was first used for quality control of the raw reads. Then, adapters were removed from the raw reads, and low-quality reads were eliminated. The resulting clean reads were then aligned to the RNA database. Q30 is an important indicator for evaluating sequencing data quality, used to count the proportion of bases with a base accuracy greater than 99.9% out of the total bases. Generally, a Q30 greater than 80% is considered acceptable for sequencing data. Tables 2 and 3 show the data quality control results; the Q30 quality control results for the samples were all good.

[0078] Table 2. Statistics on miRNA sequencing quality

[0079]

[0080] Note: Sample: Sample name; Group: Grouping; Q30: Q30 base percentage of Raw Reads; Raw Reads: Original sequences; Clean Reads: Sequences after quality control; Clean Ratio: Percentage of Clean Reads in Raw Reads.

[0081] Table 3. Statistics on the quality of long RNA sequencing

[0082]

[0083] Note: Sample: Sample name; Group: Grouping; Q30: Q30 base percentage of Raw Reads; Raw Reads: Original sequences; Clean Reads: Sequences after quality control; Clean Ratio: Percentage of Clean Reads in Raw Reads.

[0084] Results of the difference analysis:

[0085] Differential analysis of exosomal RNA expression between groups revealed 49 differentially expressed miRNAs, 4417 differentially expressed lncRNAs, 218 differentially expressed circRNAs, and 910 differentially expressed mRNAs compared to the HC group.

[0086] To make the results of differential expression between groups more intuitive, volcano plots of differentially expressed RNAs were drawn using ggplot2 software. Figure 6 The overall circRNA content was extremely low in this project, therefore there was no significant p-value, and thus a volcano plot could not be drawn. A scatter plot was drawn using the normalized average expression levels of circRNA from both groups as the raw data, after log2FC transformation.

[0087] Based on the differential expression quantification results of RNAs between groups, a differential RNA clustering heatmap was drawn to visually represent the RNA expression levels of each sample. Figure 7 Differential clustering heatmaps can visually present changes in RNA expression levels across multiple samples, and can also demonstrate clustering relationships among multiple samples or genes. Clustering diagrams allow us to observe whether samples from different groups cluster together, thus determining whether a particular sample is an outlier.

[0088] Construction of the CeRNA regulatory network:

[0089] To elucidate the relationships between lncRNAs, circRNAs, miRNAs, and mRNAs, we obtained the interaction relationships between the lncRNAs, circRNAs, and mRNAs predicted from databases as potentially binding to differentially expressed miRNAs, and their corresponding differentially expressed miRNAs. The results were then imported into Cytoscape 3.10.0 software to construct an lncRNA / circRNA-miRNA-mRNA regulatory network. Figure 8 In this diagram, green nodes represent lncRNAs, red nodes represent miRNAs, blue nodes represent circRNAs, and yellow nodes represent mRNAs.

[0090] PPI network analysis and Hub gene screening results:

[0091] We used the STRING database to analyze the interactions between potential target proteins. After removing nodes not connected to the main network, we visualized the PPI network using Cytoscape 3.10.0. Figure 9 The Cytohubba plugin was used to find key nodes in the PPI network, and then the top 8 genes were selected as hub genes based on their Degree values, including TP53, CCND1, CCND2, FOXO1, NRAS, BCL2L1, SCARB1, and MAD2.

[0092] Enrichment analysis of GO and KEGG pathways:

[0093] After performing GO and KEGG pathway enrichment analysis on potential targets in the DAVID database, 69 biological processes (BP), 30 cellular components (CC), 31 molecular functions (MF), and 33 signaling pathways were obtained. Based on the GO analysis results, the top 10 functional items with the most significant enrichment in each GO category (top 10 Fold Enrichment) are displayed below. Figure 10The potential targets mainly involve biological processes such as ceramide transport from the endoplasmic reticulum to the Golgi apparatus and calcium ion export; cellular components include histone precursor mRNA 3' processing complexes and type IV collagen trimers; molecular functions include N-terminal methionine acetyltransferase activity and inositol 1, 3, 4, 5 tetraphosphate binding. The top 10 pathways most closely associated with depression are shown in the Sankey bubble diagram. Figure 11 The potential targets are mainly enriched in the PI3K-Akt signaling pathway, the MAPK signaling pathway, and the Wnt signaling pathway.

[0094] In summary, five selected miRNAs (miR-618, miR-223-3p, miR-451a, miR-203a-3p, and let-7b-5p), three lncRNAs (Lnc-FAM169A, Lnc-OSMR, and Lnc-CMSS1), and three circRNAs (hsa_circ_0025004, hsa_circ_0007765, and hsa_circ_0047285) were finally screened for RT-qPCR validation.

[0095] The sequence of miR-618 is shown in SEQ ID NO:1, the sequence of miR-223-3p is shown in SEQ ID NO:2, the sequence of miR-451a is shown in SEQ ID NO:3, the sequence of miR-203a-3p is shown in SEQ ID NO:4, the sequence of let-7b-5p is shown in SEQ ID NO:5, the sequence of Lnc-FAM169A is shown in SEQ ID NO:6, the sequence of Lnc-OSMR is shown in SEQ ID NO:7, the sequence of Lnc-CMSS1 is shown in SEQ ID NO:8, the sequence of hsa_circ_0025004 is shown in SEQ ID NO:9, the sequence of hsa_circ_0007765 is shown in SEQ ID NO:10, and the sequence of hsa_circ_0047285 is shown in SEQ ID NO:11.

[0096] Example 3

[0097] RT-qPCR:

[0098] RT-qPCR analysis of miRNAs was performed using the stem-loop dye method. 30 ng of total RNA was used for RT-qPCR of miRNAs in each sample. miRNAs were reverse transcribed into template DNA using the BIOG miRNA Stem-loop RT Kit (BAIDAI, China), with small nuclear RNA U6 used as an internal control. The following RT reaction mixture was prepared in RNase-free centrifuge tubes: Total RNA (30 ng), BIOG RTase Mix (2 μL), 2× RT Buffer (10 μL), RT Primer (2 μM) (1 μL), and RNase-free ddH2O to a final volume of 20 μL. After centrifugation at 5000 rpm for 5 s, the tubes were incubated sequentially at 25°C for 5 min, 50°C for 15 min, and 85°C for 5 min. After the reverse transcription reaction was complete, the tubes were centrifuged again at 5000 rpm for 5 s and then immediately placed on ice. Subsequently, the qPCR reaction system was prepared in a 96-well PCR plate using the BIOG miRNA Stem-loop SYBR qPCR Kit (BAIDAI, China): Template DNA (2 μL), 2×BIOG miRNA SYBR Mastermix (10 μL), Forward primer (10 μM) (0.4 μL), Reverse primer (10 μM) (0.4 μL), and RNase-free ddH2O to a final volume of 20 μL. Three replicates were set up for each gene. After sealing the PCR plate with a sealing film, it was placed in a LightCycler 96 real-time quantitative PCR instrument (Roche, Switzerland) for PCR amplification and fluorescence signal acquisition. The reaction program is shown in Table 4. All miRNA primers used in this study were purchased from Changzhou Baidai Biotechnology Co., Ltd., and primer information is summarized in Table 5.

[0099] For RT-qPCR of lncRNA and circRNA, RNA was first reverse transcribed into template DNA using the HiScript IV RT SuperMix for qPCR kit (Vazyme, China). The specific procedure was as follows: An RNase-free centrifuge tube (labeled tube 1) was filled with 300 ng of total RNA, followed by 5 μL of 5×gDNA wiper mix. The volume was then brought to 25 μL with RNase-free ddH2O. The mixture was gently pipetted and heated in a 42°C water bath for 2 min to remove gDNA. 10 μL of the gDNA-free RNA was aliquoted into another RNase-free centrifuge tube (labeled tube 2). RNase R (Servicbio, China) was used to remove linear RNA and enrich circRNA: 2 μL of 10×Reaction buffer, 0.5 μL of RNase R, and 7.5 μL of H2O were added. The tube was heated in a 37°C water bath for 30 min, followed by a 70°C water bath for 10 min. Add 10 μL of 4×HiScript IV qRT SuperMix and 15 μL of H2O to tube 1, and add 6.67 μL of 4×HiScript IV qRT SuperMix to tube 2. Heat both tubes simultaneously in a water bath at 55°C for 15 min and then at 85°C for 5 s. After the reverse transcription reaction is complete, centrifuge at 5000 rpm for 5 s and then immediately place on ice. Prepare the following qPCR reaction system in a 96-well PCR plate: 10 μL of 2×TaqPro Universal SYBR qPCR Master Mix (Vazyme, China), 0.8 μL each of the front and back primers, 2 μL of template DNA, and RNase-free ddH2O to a final volume of 20 μL. Use β-actin as an internal control, and set up three replicates for each gene. When preparing the qPCR reaction system for lcRNA and β-actin, take the template DNA from tube 1; when preparing the qPCR reaction system for circRNA, take the template DNA from tube 2. After sealing the PCR plate with a sealing film, place it in a LightCycler 96 real-time quantitative PCR instrument (Roche, Switzerland) for PCR amplification and fluorescence signal acquisition. The reaction program is shown in Table 6. All primers used in this study were purchased from Guangzhou Ribo Biotechnology Co., Ltd., and primer information is summarized in Table 7.

[0100] Table 4 miRNA qPCR program

[0101]

[0102] Table 5 Primer information for miRNA

[0103]

[0104] Table 6 qPCR procedures for lncRNA and circRNA

[0105]

[0106] Table 7 Primer information for LncRNA and CircRNA

[0107]

[0108] The relative expression level of RNA was measured using 2 -ΔΔCq Calculation method: ΔCq = Cq (target gene) - Cq (internal reference), ΔΔCq = ΔCq (RDD group) - ΔCq (HC group), relative expression level = 2 -ΔΔCq Where Cq represents the cycle number at which the real-time fluorescence intensity reaches the preset threshold during the amplification process.

[0109] To validate the results of high-throughput sequencing, RT-qPCR analysis was performed on plasma exosome samples from 18 RDD patients and 18 healthy controls (HC) to assess the expression levels of five selected miRNAs (miR-618, miR-223-3p, miR-451a, miR-203a-3p, and let-7b-5p), three lncRNAs (Lnc-FAM169A, Lnc-OSMR, and Lnc-CMSS1), and three circRNAs (hsa_circ_0025004, hsa_circ_0007765, and hsa_circ_0047285). Among the selected RNAs, the mean expression levels of miR-618 and miR-223-3p in the RDD group were significantly higher than those in the HC group. Figure 12 (A and 12B), consistent with high-throughput sequencing results. However, the expression levels of the remaining nine RNAs showed no statistically significant difference between the two groups. Figure 13 ).

[0110] Based on the RT-qPCR results, the potential diagnostic value of significantly differentially expressed miRNAs was further evaluated using ROC curve analysis. The results are shown below. Figure 14The area under the ROC curve (AUC) of miR-618 was 0.782 (95% CI = 0.629–0.936, p < 0.05, sensitivity = 66.7%, specificity = 77.8%), while the AUC of miR-223-3p was 0.762 (95% CI = 0.600–0.924, p < 0.05, sensitivity = 83.3%, specificity = 66.7%). Both miR-618 and miR-223-3p exhibited good diagnostic performance, demonstrating their potential as biomarkers for the diagnosis of RDD. In addition, a combined diagnostic model of miR-618 and miR-223-3p was established, with an AUC of 0.772 (95% CI = 0.615-0.928, p < 0.05, sensitivity = 55.6%, specificity = 94.4%). The diagnostic performance of this model was not as good as that of the miR-618-only diagnostic model.

[0111] Example 4

[0112] (1) Cell culture

[0113] Both 293T and BV2 cells were purchased from Shanghai Jinyuan Biotechnology Co., Ltd. 500 mL of DMEM basal medium (MeilunBio, China) was mixed with 56 mL of FBS (Gibco, USA) and 5.56 mL of 100× penicillin-streptomycin mixture (MeilunBio, China) to prepare a complete medium containing 10% FBS. 293T and BV2 cells were then seeded into 10 mL of the complete medium containing 10% FBS and cultured in a 37℃ / 5% CO2 incubator.

[0114] (2) Cell transfection and verification of transfection efficiency

[0115] When the 293T cell density reaches 80%-90%, perform cell digestion, centrifuge, discard the supernatant, add 6 mL of complete culture medium containing 10% FBS to the pellet, and gently pipette to mix the cells evenly. Take 3 confocal dishes (NEST, China), add 1 mL of cell suspension to each dish, and then add 1 mL of complete culture medium containing 10% FBS. Continue culturing until the cell density reaches 50%-70%, then perform cell transfection.

[0116] One hour before cell transfection, discard the old culture medium and wash the cells twice with PBS. Add 1750 μL of Opti-MEM medium (Byotime, China) to each confocal dish and then return them to the incubator. For the cells in the confocal dishes to be transfected, take six clean, sterile 1.5 mL centrifuge tubes (labeled 1-6) and add 125 μL of Opti-MEM medium to each. Perform transfection in the dark. Add 5 μL of Lipo293 Plus transfection reagent (Byotime, China) to tubes 1-3, add cy3-labeled miR-NC mimics (synthesized by Fuzhou Zaiji Biotechnology Co., Ltd.) to tube 5, and add cy5-labeled miR-618 mimics (synthesized by Fuzhou Zaiji Biotechnology Co., Ltd.) to tube 6. Gently pipette to mix and let stand for 5 min. Add the liquid from tubes 1-3 to tubes 4-6 respectively, gently pipette to mix and let stand for 15 min. Carefully aspirate (avoid pipetting) the liquid from tubes 4-6 and add them to three confocal dishes. Label the three confocal dishes as Control group, miR-NC mimics group, and miR-618 mimics group, respectively. Gently shake to mix well and then return them to the cell culture incubator.

[0117] All procedures were performed in the dark. Six hours after cell transfection, the confocal dish was removed, the old culture medium was discarded, and the cells were washed three times with PBS. Then, 1 mL of 4% paraformaldehyde fixative (Biosharp, China) was added to fix the cells for 20 min. The fixative was discarded, and the cells were washed three times with PBS. 200 μL of 10 μg / mL ready-to-use DAPI solution (Meilunbio, China) was added to the center of the confocal dish, and the dish was allowed to stand for 5 min. The DAPI staining solution was discarded, and the cells were washed three times with PBS. The confocal dish was placed under a laser confocal microscope (Leica, Germany) in dual-channel mode to excite DAPI and cy3 / cy5 separately and to take photographs. The excitation wavelengths were set as follows: 405 nm for DAPI, 550 nm for cy3, and 650 nm for cy5.

[0118] (3) Exosome extraction and preparation

[0119] Exosome-free complete culture medium was prepared using a mixture of 90% DMEM medium, 10% exosome-free fetal bovine serum (Umibio, China), and 1% penicillin-streptomycin. When the 293T cell density in the T75 flask reached 50%-70%, the cells were centrifuged, and the cell supernatant was collected into 15 ml centrifuge tubes. The cells were washed once with 2 ml of PBS, and the PBS was combined with the cell supernatant. The cell supernatant was stored at -80°C for later use; this cell supernatant was used to extract empty exosomes (Exo).

[0120] Add 8500 μL of Opti-MEM medium to a T75 flask. After 1 h, take two clean, sterile 1.5 mL centrifuge tubes (labeled tube A and tube B) and add 750 μL of Opti-MEM medium to each. Perform transfection in the dark. Add 30 μL of Lipo293 Plus transfection reagent to tube A and add cy3-miR-NC mimics or cy5-miR-618 mimics to tube B. Gently pipette to mix and let stand for 5 min. Mix the liquids in both tubes, gently pipette to mix, and let stand for 15 min. Carefully aspirate (avoid pipetting) the transfection mixture into a T75 flask. After 6 h of transfection, discard the Opti-MEM medium, wash the cells three times with PBS, add 8 mL of complete culture medium, and return to the cell culture incubator. Continue culturing for 24-48 h, then collect the cell supernatant into a 15 mL centrifuge tube. Add 2 mL of PBS to the T75 flask and wash once, then combine the PBS with the cell supernatant. The cell supernatant was stored at -80°C for later use. This cell supernatant was used to extract exosomes (miR-NC Exo and miR-618 Exo) carrying miRNA mimics.

[0121] Take 20 mL of cell supernatant and extract and purify exosomes using a cell supernatant exosome extraction kit (Umibio, China) for subsequent characterization and functional experiments.

[0122] (4) Exosome characterization

[0123] Exosome morphology was observed using transmission electron microscopy; particle size distribution was detected using a particle size analyzer; and the expression of exosome marker proteins CD9, CD63, and TSG101 was detected using Western blotting. Total RNA was extracted from exosomes according to the method in Example 3, and the miR-618 loading level in exosomes was detected by RT-qPCR.

[0124] (5) Exosome uptake experiment

[0125] When the BV2 cell density reaches 80%-90%, perform cell digestion, centrifuge, collect the cell pellet, resuspend the cell pellet in 6 mL of complete culture medium, and pipette to mix the cells evenly. Take 3 confocal dishes, add 1 mL of cell suspension to each dish, and then add 1 mL of complete culture medium to continue culturing.

[0126] All procedures were performed in the dark. When the cell density reached approximately 70%, Exo, miR-NC Exo, and miR-618 Exo were added to the three groups of cell culture media in the confocal dish at a concentration of 200 μg / mL. After incubation for 6 h, the old culture medium was discarded, and the cells were washed three times with PBS. Then, 1 mL of fixative was added to fix the cells for 20 min. The fixative was discarded, and the cells were washed three times with PBS. 200 μL of ready-to-use DAPI solution was added to the center of the confocal dish, and the dish was allowed to stand for 5 min. The DAPI staining solution was discarded, and the cells were washed three times with PBS. The confocal dish was placed under a laser confocal microscope in dual-channel mode to excite DAPI and cy3 / cy5 separately and photographed. The excitation light was set to 405 nm for DAPI, 550 nm for cy3, and 650 nm for cy5.

[0127] Fluorescence colocalization results showed that 293T cells exhibited significant Cy3 / Cy5 fluorescence signals around their nuclei, indicating successful transfection with either miR-NC mimics or miR-618 mimics. Figure 15 ).

[0128] The extracted exosomes showed classic cup-shaped structures under a transmission electron microscope, with a size of approximately 100 nm. Figure 16 A). Particle size analysis results showed that the particle size of exosomes was 50-300 nm ( Figure 16 B). Exosome marker proteins CD9 (25KD), CD63 (26KD), and TSG101 (44KD) were detected by Western blotting, and the target protein bands were clearly visible. Figure 16 C). The above three experiments demonstrate that exosomes have been successfully extracted from cell supernatant.

[0129] RT-qPCR results showed that, compared with Exo and miR-NC Exo, the miR-618 loading in miR-618 Exo was significantly increased. Figure 17 Fluorescence co-localization observation showed that exosomes carrying miRNAs could be effectively taken up by BV2 cells, and obvious fluorescence signals were visible around the cell nucleus. Figure 18 ).

[0130] Example 5

[0131] Establishment of a mouse depression model:

[0132] SPF-grade 6-week-old C57BL / 6 mice were purchased from Xiamen Fude Xin Biotechnology Co., Ltd., and the animal quality certificate number is SCXK(Fujian)2025-0001. The experimental animals were housed in the animal room of the basic scientific research platform of Xiamen Medical College, with a temperature of 23±2°C and a humidity of 50±1°C, following a 12-hour day-night cycle rhythm, and having free access to food and water. All animal experiments were approved by the Medical Ethics Committee of Xiamen Medical College (approval number: 20251030034, October 30, 2025), and were conducted in accordance with the relevant guidelines and regulations of animal experiments. All animal experiments complied with the "3R" principle.

[0133] After one week of adaptation, the C57BL / 6 mice were evenly divided into 3 groups, namely the Control group, the miR-NC group, and the miR-618 group. Exosomes were injected into the tail vein once every 3 days for a total of 4 times, with an injection dose of 10 mg / kg. The Control group was injected with empty Exo, the miR-NC group was injected with miR-NC Exo, and the miR-618 group was injected with miR-618 Exo. The behavioral experiments began the day after the injection was completed, and the details were as follows:

[0134] (1) Sucrose preference test: The sucrose preference test was used to detect anhedonia in mice. Before the experiment began, a 72-hour sucrose drinking water training was conducted. The mice were housed individually. In the first 24 hours, only 1% sucrose water was given, and in the subsequent 48 hours, both 1% sucrose water and drinking water were given for training, and the positions of the two drinking bottles were changed every 12 hours. After the training ended, the mice were deprived of water and food for 24 hours, and then the sucrose preference test began. Mice housed individually were given free access to 1% sucrose water and drinking water simultaneously, and the consumption of the two types of water within 24 hours was recorded, and the proportion of sucrose water consumed was calculated.

[0135] (2) Open field test: The open field test was used to detect the locomotor behavior and anxiety performance of mice. The mice to be tested were gently placed in a fixed corner position of a white opaque open box with dimensions of 40 cm×40 cm×40 cm, and then the activity of the mice within 10 minutes was recorded and analyzed using the Tracking Master behavioral analysis system (Beijing Zhongshi Technology Co., Ltd.).

[0136] (3) Tail suspension test: The tail suspension test was used to detect the despair behavior of mice. The tail of the mice to be tested was suspended in a black opaque tail suspension test box, making the mice in an inverted hanging position, with a certain distance between the head and the bottom of the box. The experimental time was 6 minutes, and the immobile time of the mice within the last 4 minutes was recorded and analyzed using the Tracking Master behavioral analysis system.

[0137] (4) Forced swimming test: The forced swimming test was used to detect the despair behavior of mice. The mice were placed in a transparent cylindrical container filled with water at 24°C (the water level was 15 cm). The experiment was conducted for 6 minutes. The immobility time of the mice in the last 4 minutes was recorded and analyzed using the Tracking Master behavioral analysis system.

[0138] (5) Hippocampal RNA extraction: After intraperitoneal injection of tribromoethanol to anesthetize mice, the brains were removed by decapitation on ice and placed in pre-cooled PBS. The hippocampus was carefully separated into 1.5 mL centrifuge tubes, and miRNA was extracted from the hippocampus using a cell / tissue miRNA extraction kit (centrifuge column method). The collected mRNA samples were stored at -80°C.

[0139] RT-qPCR quantification of miR-168 was performed according to the method described in Example 3.

[0140] RT-qPCR of mRNA was performed using the BeyoFast SYBR Green One-Step qRT-PCR Kit (Byotime, China). The specific steps were as follows: All required solutions were thawed and mixed thoroughly, and the kit was placed on an ice pack. A 96-well PCR plate was placed on the ice pack, and the reaction mixture was prepared in each well according to Table 8. β-actin was used as an internal control, and three replicates were set up for each gene. After sealing the PCR plate with a sealing film, it was placed in a LightCycler 96 real-time quantitative PCR instrument for PCR amplification and fluorescence signal acquisition. The reaction program is shown in Table 9. (The last sentence appears to be incomplete and requires further context.) -ΔΔCq The relative expression level of the target gene was calculated. Primers used in this experiment were purchased from Beijing Dingguo Changsheng Biotechnology Co., Ltd., and their sequences are listed in Table 10.

[0141] Table 8 RT-qPCR reaction system for mRNA

[0142]

[0143] Table 9. RT-qPCR reaction procedure for mRNA

[0144]

[0145] Table 10 Primer sequences for mRNA

[0146]

[0147] Western Blot:

[0148] Mice were anesthetized with tribromoethanol via intraperitoneal injection, decapitated on ice, and their brains were removed and placed in pre-chilled PBS. The hippocampus was carefully separated and weighed. A suitable amount of RIPA lysis buffer (strong) and a 50× proteinase phosphatase inhibitor mixture (Byotime, China) were mixed at a volume ratio of 50:1 and used immediately. 500 µL of lysis buffer was added to every 50 mg of hippocampus, and the mixture was homogenized thoroughly on crushed ice using a glass homogenizer. The mixture was centrifuged at 12000 × g, 4 °C for 20 min, and the supernatant was carefully transferred to a new 1.5 mL centrifuge tube. This supernatant was rich in total protein. The total protein concentration was determined using a BCA protein assay kit. The remaining protein sample was mixed with 5× SDS-PAGE protein loading buffer at a ratio of 4:1 and heat-denatured in a 95 °C metal bath for 5 min.

[0149] A 10% separating gel was prepared using a one-step ultra-fast gel preparation kit. 40 μg of total protein was loaded onto the gel for separation. Electrophoresis was performed at a constant voltage of 200 V for 40 min. Subsequently, the protein was transferred to a PVDF membrane at a current of 400 mA for 40 min.After incubating the PVDF membrane with TBST containing 5% BSA for 1.5 h at room temperature, the membrane was washed three times with TBST for 10 min each time, and then incubated overnight at 4°C with the following primary antibodies: BDNF Recombinant Rabbit Monoclonal Antibody (Clone NO. SJ12-09, Cat# ET1606-42, 1:5000, HUABIO, China), Bax Recombinant Rabbit Monoclonal Antibody (Clone NO. R03-1D3, Cat# R22708, 1:5000, zenbio, China), Bcl2 Recombinant Rabbit Monoclonal Antibody (Clone NO. R07-2A1, Cat# R23309, 1:500, zenbio, China), Phospho-PI3K Recombinant Rabbit Monoclonal Antibody (Clone NO. PSH01-38, Cat#...). HA721672, 1:1000, HUABIO, China), PI3 Kinase p110 beta Recombinant Rabbit Monoclonal Antibody (Clone NO. JE65-38, Cat# HA722474, 1:1000, HUABIO, China), Phospho-Akt Recombinant Rabbit Monoclonal Antibody (Clone NO. 2E17, Cat# 80455-1-RR, 1:500, proteintech, China), Akt1 / 2 / 3 Recombinant Rabbit Monoclonal Antibody (Clone NO. ST48-09, Cat# ET1609-51, 1:5000, HUABIO, China), Beta Actin Recombinant Rabbit Monoclonal Antibody (Clone NO. 4H1, Cat# 81115-1-RR, 1:5000, HUABIO, China) and GAPDH Rabbit Monoclonal Antibody (Clone NO. R09-4E-1, Cat# R380626, 1:10000, zenbio, China).The following day, the membrane was washed three times with TBST for 10 min each time. The PVDF membrane was then incubated with HRP-Labelled Goat Anti-Rabbit IgG (H+L) at room temperature for 1 h, followed by three washes with TBST for 10 min each time. Finally, the PVDF membrane was immersed in BeyoECL Plus for 10 s, and then subjected to Western blot analysis using the e-BLOT Touch imaging system.

[0150] After anesthetizing the mice with the above treatment by intraperitoneal injection of tribromoethanol, the thoracic cavity was opened, the heart was perfused with physiological saline, the head was removed on ice, the brain was removed and immersed in tissue fixation solution at room temperature for 6 h, and then dehydrated, embedded and stained with HE to obtain tissue sections.

[0151] Experimental results showed that in the sucrose preference experiment, the sucrose preference rate in the miR-618 group was significantly lower than that in the miR-NC group, while there was no significant difference in sucrose preference rate between the control group and the miR-NC group. Figure 19 E). In the open field experiment, compared with the miR-NC group, the miR-618 group had a longer range of motion (E). Figure 19 A and 19B) and average speed ( Figure 19 C) significantly reduced, immobility time ( Figure 19 D) significantly increased, while there was no significant difference between the control group and the miR-NC group. In the tail suspension test and forced swimming test, the immobility time in the miR-618 group was significantly longer than that in the miR-NC group, while there was no significant difference between the control group and the miR-NC group. Figure 19 F and 19G).

[0152] The relative expression levels of miR-618, tp53, and ccnd1 in the hippocampus of mice in each group were detected by RT-qPCR. Compared with the miR-NC group, the expression level of miR-618 in the hippocampus of the miR-618 group was significantly increased, while the expression levels of TP53 and CCnd1 were significantly decreased. There was no significant difference in gene expression levels between the control group and the miR-NC group. Figure 20 ).

[0153] The expression levels of PI3K-Akt pathway-related proteins, apoptosis-related proteins (Bax and Bcl2), and synaptic plasticity-related protein BDNF in the hippocampus of mice in each group were detected by Western blotting. Compared with the miR-NC group, the miR-618 group showed a higher expression level of BDNF in the hippocampus. Figure 21 A) Bcl2 ( Figure 21 C), p-PI3K / t-PI3K and p-Akt / t-Akt ( Figure 21 The expression levels of DG were significantly reduced, and Bax ( Figure 21The expression levels of B) were significantly increased. However, there was no significant difference in the expression levels of the above proteins between the control group and the miR-NC group.

[0154] In the control group and the miR-NC group, the granule cells in the hippocampal DG region were intact and plump. In contrast, many granule cells in the hippocampal DG region of the miR-618 group were damaged, with ruptured nuclei and deep staining. Figure 22 ).

[0155] These results indicate that miR-618 impairs nerve cell and synaptic plasticity by regulating signaling pathways such as PI3K-Akt, thereby leading to depressive-like behavior.

[0156] The above description is only a preferred embodiment of the present invention. All equivalent changes and modifications made within the scope of the claims of the present invention should be included in the scope of the present invention.

Claims

1. An ncRNA biomarker for recurrent depression, characterized in that: The biomarkers include miR-618 and / or miR-223-3p; the sequence of miR-618 is AAACUCUACUUGUCCUUCUGAGU, and the sequence of miR-223-3p is UGUCAGUUUGUCAAAUACCCCA.

2. The ncRNA biomarker according to claim 1, characterized in that: The biomarkers are derived from plasma exosomes.

3. The ncRNA biomarker according to claim 1, characterized in that: The ncRNA biomarkers impair nerve cell and synaptic plasticity by regulating the PI3K-Akt signaling pathway, thereby leading to depressive-like behavior.

4. The use of the ncRNA biomarker as described in any one of claims 1 to 3 in the preparation of diagnostic products for recurrent depression.

5. The application according to claim 4, characterized in that: The ncRNA biomarker was significantly overexpressed in plasma samples of recurrent depression.

6. The application according to claim 4, characterized in that: The expression of miR-618 and / or miR-223-3p in plasma was detected by RT-qPCR.

7. A diagnostic kit for recurrent depression, characterized in that: The kit includes reagents for detecting miR-618 and / or miR-223-3p.

8. The diagnostic kit for recurrent depression according to claim 7, characterized in that: The reagents include reverse transcription reagents for miR-618 and / or miR-223-3p, as well as RT-qPCR detection reagents and primers.

9. The diagnostic kit for recurrent depression according to claim 8, characterized in that: The upstream primer for miR-618 RT-qPCR is: GGCGAAACTCTACTTGTCCTT, and the downstream primer is the universal primer AGTGCAGGGTCCGAGGTATT.

10. The diagnostic kit for recurrent depression according to claim 8, characterized in that: The upstream primer for miR-223-3p RT-qPCR is: GCGCGTGTCAGTTTGTCAAA, and the downstream primer is the universal primer AGTGCAGGGTCCGAGGTATT.

Images