Role of mitochondrial lncRNA GAS5 in the pathogenesis of Multiple Sclerosis: interfering with the release of miR-651-5p-enriched exosomes from microglia cells

doi:10.21203/rs.3.rs-4673502/v1

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Role of mitochondrial lncRNA GAS5 in the pathogenesis of Multiple Sclerosis: interfering with the release of miR-651-5p-enriched exosomes from microglia cells

https://doi.org/10.21203/rs.3.rs-4673502/v1

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Multiple Sclerosis (MS) arises from immune system dysfunction and damage to the myelin sheath within the CNS. At various stages of MS, analyzing blood samples has the potential to help differentiate between individuals with MS and those without, detect the early onset of the disease, or distinguish between different types of MS. Long non-coding RNA (lncRNA) growth arrest-specific 5 (GAS5) serves a pivotal role in governing cell growth and arrest, as well as modulating the immune system by acting as the glucocorticoid receptor. This research aims to explore GAS5 expression in peripheral blood mononuclear cells (PBMCs) of Relapsing-Remitting MS (RRMS) patients and evaluate its targeted miRNAs in exosomes. Our findings revealed an elevated expression level of GAS5 in RRMS patients in contrast to control groups (P-value = 0.0121), and GAS5 demonstrated diagnostic potential for RRMS, with an AUC of 0.6498. The in-silico analysis revealed that hsa-miR-651-5p emerged as a central component in the regulatory network of GAS5, with its target genes primarily implicated in transcription and apoptosis regulation. Additionally, RUNX1, YY1, GSK3B, FMR1, and KLF2 were identified as entities linked to GAS5. In this regard, our findings indicate a significant association between redox imbalance and the dysregulation of GAS5 and miR-651-5p expression in the HMC3 cell line. Given the increased expression of miR-651-5p in exosomes under stress, the transport of miR-651-5p into serum exosomes may be varied and related to GAS5 expression in PBMCs of MS subtypes. In conclusion, GAS5 can serve as a mitochondrial marker for RRMS, and redox imbalance appears to influence its regulation, highlighting its role in the cellular stress response. Future research is suggested to focus on elucidating the molecular mechanisms underlying GAS5/miR-651-5p interaction to better understand this process.

GAS5

LncRNA

PBMCs

Multiple Sclerosis

Exosomes

HMC3

Multiple Sclerosis (MS) is a progressive autoimmune disorder caused by a malfunction of immune cells in the central nervous system (CNS). It is estimated that 1.5 to 2.5 million people worldwide have multiple sclerosis, with an average age of 15 to 55 years, although in rare cases, it has been seen in children. Environment, infection, smoking, sun exposure, and vitamin D levels are associated with MS risk (1, 2). There are three main types of MS in the world, relapsing-remitting MS (RRMS), primary progressive MS (PPMS), and secondary progressive MS (SPMS). RRMS is the most prevalent type, and 85% of all patients are diagnosed for the first time. This type of MS is characterized by intense assaults (relapse) resulting in neurological shortages over a few days or weeks, subsequently by critical or total recovery. Roughly 80% of RRMS patients will advance to create SPMS, where proceeded moderate movement of disease replaces the periods of remission. However, 5 to 10 percent of RRMS have a progressive period of disability sign without remission (3). In the CNS, antigen-presenting cells (APCs), including Dendritic Cells (DCs), secrete various cytokines, which dictate the differentiation of CD4⁺ T cells into distinct phenotypes. The type of CD4⁺ T cells that differentiate depends on the cytokine milieu. When interleukin-12 (IL-12) dominates, CD4⁺ T cells become Th1 cells that secrete interferon-γ (IFN-γ). Conversely, when IL-23 dominates, CD4⁺ T cells become Th17 cells that secrete IL-17. In normal conditions, Th1 cells are primarily responsible for defending against intracellular pathogens, while Th17 cells play a secondary role. During acute attacks, patients with MS exhibit a higher percentage of Th17 and Th1 cells in their peripheral blood (4). Alternatively, activated Th1 cells produce large numbers of proinflammatory mediators, including (IL-1b, Tumor necrosis factor-α (TNF-α), and IL- 12), and chemokines which attract other immune cells, such as B cells and macrophages (5). T-cell-mediated activation of macrophages plays a crucial role in the pathogenesis of inflammatory demyelination observed in MS (6). Moreover, B cells are also involved in MS progression, myelin depletion, and exacerbation of inflammation (5). It is worth noting that T cells constitute a significant proportion, ranging from 45–70%, of peripheral blood mononuclear cells (PBMCs) in the blood of humans (7). Neuroinflammation has been linked to the development and progression of various CNS disorders, such as multiple sclerosis. Glial cells are crucial for neural development, synaptic connections maintenance, and brain health hemostasis. While astrocyte and microglial activation is a protective response to brain damage and pathogens, it can also contribute to neuroinflammation, potentially worsening CNS injuries (8). Factors like excessive reactive oxygen species (ROS), mitochondrial dysfunction, and inadequate antioxidant defenses can lead to oxidative stress, which plays a significant role in MS pathogenesis. Ostress is particularly important in the early stages of MS and affects both the inflammatory and neurodegenerative aspects of the disease (9). Alternatively, exosomes which are small extracellular vesicles (EVs) with diameters ranging from 50 to 200 nm, may be involved. They are secreted by specific cell types under both physiological and pathological conditions and play a crucial role in mediating glial function. Glia-derived exosomes (GDEs) can transport a variety of biomolecules including miRNAs, influencing both protective and toxic effects on the nervous system (10). In recent years, there has been growing interest in the role of exosomes in various diseases and their therapeutic applications. This interest extends to exosomal non-coding RNAs (ncRNAs), which, despite not encoding proteins, can influence transcriptional and translational processes by targeting specific messenger RNAs (mRNAs) (11). Glucocorticoids are steroid hormones that can be involved in immune system regulation and cell apoptosis so that they can be associated with autoimmune inflammatory disorders such as MS. Glucocorticoid receptor (GR) as a nuclear receptor protein has a DNA-binding domain (DBD) that can regulate glucocorticoids function (12). The effects of glucocorticoids are mediated through the GR, a ligand-inducible transcription factor (TF). In target cells, glucocorticoid-activated receptors reduce inflammation by hindering the activity of proinflammatory TFs, terminating signaling pathways, or modulating the transcriptional level of anti-inflammatory proteins (13). On the other hand, many long non-coding RNAs (lncRNAs) are linked to the cerebrospinal system. They are expressed in specific neural, cellular, or intracellular brain compartments, contributing to neurological processes. Their expression changes might be involved in the pathogenesis of neurological disorders such as MS (14, 15). Mitochondrially localized Growth Arrest-Specific 5 (GAS5) is one of the lncRNAs involved in cell growth arrest and apoptosis with a suppressive effect on glucocorticoids (16). LncRNA GAS5 interacts with GR by binding to the DBD region and reducing the transcriptional activity of GR (17). It was previously determined that GAS5 acts as a GR transcription repressor by targeted "glucocorticoid response element (GRE) RNA" (18). There is an association between GAS5 variants and vulnerability to MS (19). Senousy et al. discovered that GAS5 overexpressed in MS patients compared to normal samples, and they propose the GAS5 rs2067079 variant as a marker for MS vulnerability (20). Alternatively, The previous study determined that GAS5 takes part in infection and inflammatory diseases such that its dysregulation might affect their response to immunosuppressive glucocorticoid therapy (21). As demonstrated by Sun et al., GAS5 can serve as a promising treatment target for neurological disorders due to its role in microglial polarization (22). The GAS5 transcriptional level was found to be elevated in blood samples obtained from individuals with MS in comparison to those from healthy individuals (16). Despite a few studies examining the expression of GAS5 in the blood samples of patients with MS, to the extent of our information, no prior investigations have explored its expression specifically in PBMCs, an important immune cell subset. Our hypothesis posits that GAS5 plays a critical role in the pathogenesis and pathophysiology of MS, particularly within immune cells, and can affect the loading of miRNAs into the exosomes. The primary objective of this study is to examine the expression profile of GAS5 in PBMCs and assess its potential as a mitochondrial marker in RRMS patients. Additionally, we employed bioinformatics tools to investigate the regulatory network of GAS5, including its targeted miRNAs and associated proteins. Ultimately, we employ primary cell cultures to examine whether the expression pattern of GAS5 and its targeted miRNAs in human microglia (HMC3) cell line and their exosomes is modified following distress induced by tert-Butyl Hydroperoxide (tBHP)-mediated redox imbalance and oxidative stress.

2.1. GAS5-miRNAs-mRNAs regulatory network

The GAS5 target miRNAs were identified from the StarBase v.2.0 database (https://starbase.sysu.edu.cn/) (23, 24). The CLIP data, Degradome data, and Pan-Cancer were set as “Strict stringency”, “Low stringency”, and “with or without data”, respectively. To obtain the most recent miRNA nomenclature, the identified miRNAs were processed through the miRNAmeConverter package (25) using miRbase version 22.1 (26, 27, 28, 29, 30, 31). Utilizing the multiMIR package, validated corresponding mRNAs were identified from miRecords, miRTarBase, and Tarbase databases (32). The R programming software (version R-4.2.1, 64-bit, https://www.r-project.org/) (33) and RStudio Desktop (version 2022.7.0.548) (34) were utilized for data analysis. The Cytoscape software version 3.9.1 (35) was employed to generate the GAS5-miRNAs-mRNAs axis and the CytoHubba app (36) was utilized to determine the central nodes.

2.2. GAS5-related gene set enrichment analysis

We conducted an enrichment analysis of the final mRNAs to determine the potential functions of the protein-coding genes targeted indirectly by GAS5 (The complete mRNA names are mentioned in Supplementary Material 1). The Gene Ontology (GO) enrichment analysis, including cellular component, molecular function, and biological process, as well as the pathway enrichment analysis such as Kyoto Encyclopedia of Genes and Genomes (KEGG), Wikipathway, and Reactome, were performed by the Enrichr tool (https://maayanlab.cloud/Enrichr/) (37, 38, 39). The cutoff criterion was an adjusted P-value of less than 0.05. The ggplot2 package (40) was utilized to draw the dot plot for GO enrichment analysis and pathway enrichment analysis distinctly (R programming software (version R-4.2.1, 64 bit, https://www.r-project.org/) (33) and RStudio Desktop (version 2022.7.0.548) (34)).

2.3. GAS5-related transcription factors and protein kinase

GAS5-associated transcription factors were identified using the GeneCards (www.genecards.org) (41, 42) and Harmonizome (https://maayanlab.cloud/Harmonizome/) (43) databases. The CHEA (44) and JASPAR (45, 46) transcription factor target datasets from the Harmonizome database were utilized to identify validated and predicted transcription factors, respectively. In addition, the top QIAGEN-validated transcription factors binding to the GAS5 gene promoter were also obtained from the GeneHancer section of the GeneCards database (47). On the plus side, we used the GEO Signatures of Differentially Expressed Genes for Kinase Perturbations dataset (48, 49) from the Harmonizome database to find the GAS5 corresponding protein kinase.

2.4. GAS5- mRNAs and RNA-binding proteins (RBPs) interaction analysis

The GAS5 target mRNAs and GAS5-associated RBPs were identified using the RNAInter v4.0 database (http://rnainter.org/) (50). First, the keyword "GAS5" was inputted in the textbox for the RNA/protein/DNA symbol in the database. The parameters were set as follows: Category - "LncRNA", Species - "Homo sapiens", Detection Method - "All". To identify RBPs, the RNA-protein interaction type was used with a minimum confidence score of 0.4; for identifying mRNAs, the RNA-RNA interaction type was used with a minimum confidence score of 0.35. Subsequently, the interactions of interest were filtered to include only the interactions involving RBPs and mRNAs. Finally, we utilized the SankeyMATIC online tool (https://sankeymatic.com/) to draw the Sankey diagram.

2.5. Patients and sampling

The study was approved by the Ethical Committee of Hormozgan University of Medical Sciences (IR.HUMS.REC.1399.341). We conducted it at Abu Reihan Hospital in Bandar Abbas, Iran, where we included 25 RRMS patients and age-matched healthy controls. After obtaining informed consent from the patients, we recorded demographic characteristics, such as age, sex, race, age of onset, and type of disease. We selected 25 RRMS patients based on McDonald's criteria, all of whom were in the relapse phase of the disease. Patients who had a history of consuming immunosuppressive medications like Methyl, Interferon, and Natalizumab were excluded from the study. In addition, pregnant females, individuals with a prior record of any other autoimmune disorders, and those diagnosed with cancer (either benign or malignant neoplasms) were also not considered for the study. On the other hand, we selected 25 healthy control individuals who did not have cancer, neurological conditions, or autoimmune diseases at the time of sampling. Blood samples of 10 ml were collected from 25 people with RRMS and 25 healthy controls. PBMCs were isolated using the Ficoll-Hypaque density gradient centrifugation method, which separates mononuclear cells from other blood components using a sodium diatrizoate and Ficoll solution. Blood was diluted with PBS at a 1:1 ratio and added to Falcon tubes containing the Ficoll-Hypaque solution. The tubes were centrifuged at 2,000 rpm for 20 minutes, resulting in the separation of the solution into three distinct layers. The upper phase was stored at -80°C, PBMCs were collected, and washed with PBS at 680 g for 10 min, and RNA was then isolated from the cellular pellet.

2.6. Cell Culture and Induction of Redox Imbalance and Oxidative Stress

HMC3 human microglial cells were cultured in DMEM medium supplemented with 100 IU/mL penicillin, 10 µg/mL streptomycin, and 10% fetal bovine serum (FBS) from Thermo Fisher Scientific (Waltham, MA, USA). They were maintained in a humidified incubator at 37°C with 95% air, 5% CO2 atmosphere, and 10% FCS. The cells were exposed to tBHP at concentrations of 50 µM, 100 µM, and 200 µM (Sigma) for 24 h under standard culture conditions with 1% FCS to induce redox imbalance (< 100 µM) and oxidative stress (> 100 µM). Following this, the impact of stress on the expression of GAS5 and its associated miRNAs was examined in the cells.

2.7. Exosome Extraction and Characterization

After 24 h of tBHP stimulation, the cell supernatant was collected. Centrifugation was then carried out following a standardized protocol with some modifications (51). To remove dead cells and cell fragments from the supernatant, centrifugation was first performed at 300 × g for 10 min, followed by a second centrifugation at 2000 × g for 20 min. The resulting supernatant was subjected to ultracentrifugation at 8000 × g for 45 min. The pellet was discarded, and the supernatant underwent further ultracentrifugation at 118,000 × g for 105 min. The isolated exosomes (pellet) were resuspended in 100 µL of PBS and subjected to another ultracentrifugation at 118,000 × g for 105 min. The size and purity of the exosomes were evaluated using Nanoparticle tracking analysis (NTA) with NanoSight NS300 and Western blotting, respectively (52, 53). RNA extraction was then performed on the purified exosomes to analyze GAS5 and its associated miRNAs (Fig. 6A).

2.8. GAS5 and its related miRNAs expression analysis

The TRIZOL method, combined with the RNX-PLUS kit protocol (Sinaclon, Iran), was used to extract RNA from PBMCs. Moreover, RNA was isolated from HMC3 cells, and their medium-derived exosomes using RNA-Solv® Reagent (Omega Bio-Tek Inc., USA) as per the manufacturer's guidelines. The RNA concentration and quality were assessed using the Nanodrop instrument (Thermo Scientific™). RNA purity was confirmed by electrophoresis on 2% agarose gels. Following this, cDNA synthesis was carried out for PBMC-derived RNA using the cDNA synthesis kit (TAKARA, Japan) with an equal amount of RNA from PBMCs. For cDNA synthesis of HMC3 cells and exosome-derived RNAs, 1 µg of RNA was reverse transcribed using the M-MLV RT kit and random hexanucleotide primers (Invitrogen, Braunschweig Germany). Different software tools, including Primer3, Primer-BLAST, Gene Runner, and Oligo Analyzer, were used for primer design and validation. Semi-quantitative real-time PCR (qRT-PCR) was performed using SYBR Green. The β-Actin gene was selected as the internal control gene to evaluate GAS5 expression in PBMCs. For miRNA expression assessment in cells and exosomes, the cel-miR-39 spike-in kit (NORGEN) was chosen as the internal control. Gene amplification was performed using RealQ Plus Master Mix Green Denmark and quantified using the 2^−ΔΔCt method. Primary sequences for this study are delineated in Table 1.

Table 1

Primer sequences used for gene expression study.
Name	Primer sequences
GAS5 (PBMCs)	F: TTTCGAGGTATGGTGCTGGG R: CTGTGTGCCAATGGCTTGAG
GAS5 (HMC3)	F: CTCTGGATAGCACCTTATGGAC R: CTTCCAGCTTTCTGTCTAATGCC
β actin (PBMCs)	F: AGCCTTCCTTCCTGGGCATGG R: AGCACTGTGTTGGCGTACAGGTC
miR-651-5p (HMC3)	F: GTGTGGTTTAGGATAAGCTTGAC R: AGGTCCGGTTTTTTTTTTTTTTTAAC
miR-345-5p (HMC3)	F: GTATTGCTGACTCCTAGTCCA R: AGGTCCAGTTTTTTTTTTTTTTTTGAG
miR-520a-5p (HMC3)	F: GTGTTCTCCAGAGGGAAGTA R: AGGTCCGGTTTTTTTTTTTTTTTTAGA
miR-520d-5p (HMC3)	F: GTGTTCTACAAAGGGAAGCC R: AGGTCCGGTTTTTTTTTTTTTTTTGAA
cel-miR-39 (HMC3)	F: TCACCGGGTGTAAATCAGCTTG R: GGTCCAGTTTTTTTTTTTTTTTCAAG

2.9. Statistical analysis

The Shapiro-Wilk test was used to assess data normality. Parametric methodologies, including independent t-tests, were utilized for the analysis of the data with normal distribution. Conversely, for data exhibiting non-normal distribution, the Mann-Whitney U test served as the preferred analysis tool for contrasting gene expression in both patient and control individuals. The capacity of lncRNA to serve as a diagnostic marker for MS was ascertained through the employment of receiver operating characteristic curves (ROC), assessment of the area under these curves (AUC), and delineation of the 95 percent confidence interval (CI). The statistical analysis was performed using SPSS 26.0 and GraphPad Prism 9.5.0, and a p-value of less than 0.05 was deemed statistically significant.

3.1. GAS5-miRNAs-mRNAs regulatory network

The regulatory network, comprising eight miRNAs and six mRNAs, was constructed and visualized using Cytoscape (Fig. 1). The top 15 nodes in this network, determined by the MCC method, are listed in Table 2.

Table 2

Top 15 nodes in GAS5-miRNAs-mRNAs regulatory network ranked by MCC method.
Rank	Node Name	Score
1	hsa-miR-651-5p	423
2	hsa-miR-345-5p	281
3	hsa-miR-520a-5p	236
4	hsa-miR-520d-5p	230
5	hsa-miR-524-5p	173
6	hsa-miR-525-5p	140
7	hsa-miR-6807-3p	61
8	GAS5	8
9	hsa-miR-217-5p	4
10	RBM23	4
11	ALDH5A1	4
12	ZNF35	4
13	TOP2A	4
14	SON	4
15	IGF1R	4

3.2. GAS5-related gene set enrichment analysis

To obtain an enhanced understanding of the underlying bio-molecular framework of the protein-encoding genes indirectly targeted by GAS5, we undertook an extensive GO enrichment analysis. We noticed that they are significantly involved in transcription regulation by RNA polymerase II, gene expression regulation, cellular macromolecule biosynthetic process regulation, and apoptotic procedure regulation. In addition, most of the genes were enriched in RNA binding, nuclear receptor binding, protein kinase binding, and GTPase binding. They are mostly found in various cellular components, including the nucleus, intracellular membrane-bounded organelle, focal adhesion, serine/threonine protein kinase complex, cyclin-depended protein kinase holoenzyme complex, and chromosome. We also indicated the top 10 pathways based on KEGG, Wiki, and Reactome databases, consisting of the FoxO singling pathway, pathways in cancer, glioblastoma signaling pathway, cellular response to stress, gene expression, genetic transcription pathway, and RNA polymerase II transcription (Fig. 2).

3.3. GAS5-related transcription factors and protein kinase

Using GeneCards and Harmonizome databases, we demonstrated that GAS5 is associated with 30 transcription factors. In addition, GSK3B was identified as the only differentially expressed protein kinase associated with GAS5. Full details are presented in Table 3.

Table 3

GAS5-associated transcription factors and protein kinase.
Database		Transcription factors and protein kinase
Harmonizome
	CHEA Transcription Factor Targets	ASH2L, ATF3, BCL3, CREM, ERG, ESR1, FLI1, HOXC9, RBPJ, RUNX1, SIN3B, SMAD3, SMAD4, TAF7L, TAL1, TFEB, TTF2, VDR, XRN2
	JASPAR Predicted Transcription Factor Targets	YY1
	GEO signatures of differentially expressed genes for kinase perturbations	GSK3B
GeneCards
	GeneHancer	AP-1, c-Fos, c-Jun, C/EBPalpha, CREB, deltaCREB, Ik-2, IRF-1, LCR-F1, Pax-4a

3.4. GAS5- related mRNAs and RBPs

Through an analysis using the RNAInter database, we have identified specific interactions involving GAS5. Our findings reveal that GAS5 interacts with a total of 10 mRNAs, including notable targets such as KLF2, VEGFA, and IL10. Additionally, we observed interactions between GAS5 and 21 RBPs, including prominent RBPs such as HNRNPA1, FMR1, and QKI. For comprehensive information and visualization of these interactions, refer to Fig. 3.

3.5. Patient characteristics

The demographic characteristics of 25 patients with RRMS and 25 healthy individuals encompassed sex, age, smoking habits, history of viral infection, and familial autoimmune diseases are consolidated in Table 4. Statistical assessments did not reveal any significant disparities between different age groups, smoker and non-smoker ones, and between MS, patients with viral infection history compared to no viral infected ones. The study found a significant correlation between the expression of GAS5 and a positive familial autoimmune disorder history. More specifically, the patients with a positive family history displayed an overexpression of GAS5 (P-value = 0.0018, Fig. 4A). The study findings indicated a notably elevated transcriptional level of lncRNA GAS5 in females compared to males (P-value < 0.0001, Fig. 4B).

Table 4

The demographic data of RRMS patients and healthy controls.
Characteristics	Frequency (%) in Cases	Frequency (%) in controls
Sex Female Male	12 (48%) 13 (52%)	12 (48%) 13 (52%)
Age ≤ 30 ˃30	15 (60%) 10 (40%)	15 (60%) 10 (40%)
Smoking smoker non-smoker	8 (32%) 17 (68%)	- 25 (100%)
Viral Infection yes no	6 (24%) 19 (76%)	- 25 (100%)
Family History Positive Negative	8 (32%) 17 (68%)	4 (16%) 21 (84%)

3.6. The GAS5 diagnostic potential analysis

GAS5 expression was detected using real-time PCR in 25 RRMS patients, and 25 age-matched controls. The up-regulation of lncRNA GAS5 was significantly reported in the PBMC of the patients as opposed to the healthy individuals (P-value = 0.0121, Fold Change = 1.845, Fig. 5A). The diagnostic potential of GAS5 in RRMS was evaluated using a ROC curve analysis. The AUC was measured at 0.6498 (95% CI [0.5353, 0.7643], P-value = 0.0098, Fig. 5B).

3.7. In-vitro expression analysis of GAS5 and its related miRNAs in HMC3 cells and exosomes

The size distribution of exosomes was assessed using NTA, revealing a size range between 50–200 nm. This analysis confirmed the purification of exosomes derived from our sequential ultracentrifugation process. Additionally, Western blotting was used to evaluate the purity of exosomes by detecting the presence of CD9 and CD81 (commonly found in exosomes), G protein Ras-associated binding 7 (Rab7, a lysosome marker), and Early Endosome Antigen 1 (EEA1) in both cell lysates and exosomes. The results showed high levels of CD81 and CD9 in exosomes and increased levels of Rab7 and EEA1 in cells, confirming the quality of the extracted exosomes (Fig. 6A). Expression analysis of GAS5 in cells and exosomes showed a significant upregulation of GAS5 (P-value < 0.01) in cells exposed to 50 µm tBHP compared to the control and a downregulation (P-value < 0.05) in cells exposed to 200 µm tBHP (Fig. 6B). However, there was no significant difference in GAS5 expression in exosomes among the examined groups (Fig. 6C). The evaluation of cell expression of the top four associated miRNAs in the regulatory network of GAS5 revealed that none of them showed significant changes compared to the control after exposure to different doses of tBHP (Fig. 6B). Interestingly, miR-651-5p showed significant upregulation in cells after exposure to 100 µm tBHP (P-value < 0.05) and 200 µm tBHP (P-value < 0.01) compared to the 50 µm tBHP group (Fig. 6B). The expression of miR-520a-5p and miR-520d-5p also significantly increased in cells following treatment with 200 µm tBHP (P-value < 0.05) compared to the 50 µm tBHP group (Fig. 6B).

In exosomes, only miR-651-5p showed significant changes across the different experimental groups with unexpected patterns. MiR-651-5p was significantly downregulated (P-value < 0.05) in exosomes from cells treated with 50 µm tBHP compared to the control group (Fig. 6C). Additionally, it was significantly upregulated (P-value < 0.001) in exosomes from cells treated with 200 µm tBHP compared to the 50 µm tBHP group (Fig. 6C). Furthermore, miR-651-5p was significantly upregulated (P-value < 0.05) in exosomes from cells treated with 200 µm tBHP compared to the 100 µm tBHP group (Fig. 6C). Remarkably, the decrease in GAS5 in cells treated with a higher dose of tBHP was associated with an increase in the expression of miR-651-5p in both cells and exosomes and vice versa.

GAS5 is a lncRNA involved in cell cycle regulation and takes part in normal growth arrest in T cells and non-transformed lymphocytes (54). The GAS5 has several different activities, including different effects on the pathogenesis/pathophysiology of autoimmune diseases and inflammatory diseases; in addition, it can have a suppressive effect on glucocorticoids (18). A previous investigation into identifying significant genes in RRMS involved the analysis of regulatory networks (55). Building on this work, we analyzed the GAS5-miRNAs-mRNAs network and found that miR-651-5p, hsa-miR-345-5p, hsa-miR-520a-5p, hsa-miR-520d-5p, hsa-miR-524-5p, and hsa-miR-525-5p are highly associated with GAS5 in this network, respectively. Additionally, Chen et al. investigated this in 2021 and identified dysregulation of miR-651-5p in Parkinson's disease (56). However, to our knowledge, there hasn't been any study on the involvement of these miRNAs in MS. Nonetheless, our findings suggest that miR-651-5p and GAS5 may interact and potentially serve as a new mitochondrial hallmark for MS. We used gene set enrichment analysis tools to evaluate the GAS5 protein targets functionally. These genes mainly regulate gene expression, apoptosis, cellular response to stress, and FoxO singling pathways. In addition, these genes enrich RNA binding, protein kinase binding, and nuclear receptor binding. It was elucidated that GAS5 exerts regulatory control over the CD4 + T cell response and apoptosis in HIV patients by modulating miR-21 expression. They also explained that targeting these genes might be beneficial to create T cell over-activation in other infectious or inflammatory diseases (57). Furthermore, it has been demonstrated that the down-regulation of GAS5 in patients with atherosclerosis can effectively attenuate both inflammation and oxidative stress. This is supported by findings indicating that the overexpression of GAS5 in T helper I cells of these patients leads to increased levels of inflammation and oxidative stress (58), suggesting that overexpression of GAS5 could be a contributing factor to the development of these conditions. Alternatively, Zhao et al. provided evidence that GAS5 performs as a tumor suppressor in human glioma stem cells by up-regulating FoxO expression through the repression of miR196-a-5p (59). Meanwhile, in MS patients, de Oliveira et al. observed a reduction in the transcription level of genes that promote cell death, including BAD, BAX, and FASL in PBMCs. The abnormal expression of genes associated with apoptosis may contribute to the expansion of persistent memory autoreactive lymphocytes and ultimately worsen MS (60). Wang et al. identified In two families, loss of functional activity of a nuclear receptor called NR1H3 has been associated with primary progressive multiple sclerosis due to substituting glutamine for arginine in the NR1H3 protein (61). The results from these investigations provide supporting evidence for our enrichment analysis findings concerning the functional role of proteins associated with GAS5 and their involvement in specific pathways. Using GeneCards and Harmonizome databases, we identified transcription factors and protein kinases that are associated with GAS5. A previous study has demonstrated a down-regulation of RUNX1 in Multiple Sclerosis (MS) patients, and as the disease progressed, the down-regulation of GAS5 was further enhanced (62). Miao et al. conducted an in-depth analysis of the interaction between RUNX1 and GAS5, wherein they observed that the overexpression of GAS5 impeded cell cycle progression and proliferation in Diffuse Large B-cell lymphoma (DLBCL). Furthermore, their investigation demonstrated the inverse relationship between the inhibition of cell proliferation induced by GAS5 in DLBCL and the down-regulation of RUNX1 expression (63). In addition, YY1, a transcription factor, has a negative effect on GAS5 expression levels by binding to its promoter and inhibiting its transcription. The interaction of YY1 with lncRNA GAS5 leads to increased PFKFB3 transcription, intensifying neuronal glycolysis, thereby worsening brain I/R (ischemia/reperfusion) injury (64). Propofol induces GAS5 in oral squamous cell carcinoma (OSCC) cells, which competes with miR-1297, reducing its inhibitory effect on GSK3β, leading to increased GSK3β and decreased Mcl1. FoxO1 facilitates GAS5 transcription in response to propofol treatment. These findings suggest that propofol has antitumor effects in OSCC cells, and the FoxO1-GAS5-miR-1297-GSK3β axis is crucial to propofol-induced apoptosis (65). Our findings indicate that GAS5-related transcription factors and protein kinase contribute significantly to various human diseases, especially neurodegenerative conditions, demonstrating the importance of these factors in such diseases. Through our investigation of GAS5 target mRNAs and GAS5-associated RBPs, we identified 10 mRNA targets and 21 RBPs. hnRNPA1, an RBP, has been implicated in the pathogenesis of MS. Specifically, this study identified nine single nucleotide variants (SNVs) within the hnRNPA1-M9 domain, which resulted in the mislocalization of hnRNPA1 to the cytoplasm and the formation of stress granules. These disease-associated SNVs were also found to induce cell apoptosis in MS patients. Consequently, the researchers concluded that mutations in hnRNPA1 may contribute to the underlying mechanisms of MS pathogenesis (66). A case-report study demonstrated that the presence of permutation FMR1 (55–200 CGG repeats), acting as an RBP, can lead to Lamin A/C and αβ-crystallin aggregation within neural cells. These aggregated proteins are postulated to be involved in developing autoimmune diseases, particularly MS (67). Moreover, QKI is known to be involved in the regulation of normal myelinogenesis. The decreased expression of QKI has been associated with disturbances in axonal myelination and the pathogenesis of MS (68). Alternatively, in a comparative study between MS patients and control subjects, the transcriptional level of vascular endothelial growth factor A (VEGFA) was examined in PBMC. The results revealed a down-regulation of VEGFA expression in both cerebrospinal fluid (CSF) and PBMC of MS patients (69). Gayo et al., in their study on MS patients, observed an increase in the level of IL-10 following treatment with glucocorticoids. They proposed that the up-regulation of IL10 contributes to the effectiveness of steroids in controlling MS (70). Dysregulation of KLF2, a transcription factor, has been observed to contribute to the aggravation of demyelination in the spinal cord within the experimental autoimmune encephalomyelitis (EAE) murine model, suggesting that KLF2 plays a protective role in EAE and serves to suppress neuronal degeneration (71). This investigation revealed that both GAS5 target mRNAs and GAS5-related RBPs are significantly instrumental in either the advancement or protection of MS. This suggests that these biomolecules could potentially serve as a diagnostic and therapeutic target for MS. MS researchers are currently prioritizing the search for specific biomarkers to improve diagnosis. Additionally, there is an insufficiency of efficacious therapeutic interventions for progressive MS, making the development of new treatments imperative (72). In this study, we examined the potential roles of LncRNA GAS5 on RRMS vulnerability. Therefore, we assessed the relationship between GAS5 expression level in PBMC and clinical data of RRMS patients, and we determined the significant correlation between GAS5 expression and family history and gender. Consequently, GAS5 was up-regulated in the patients with family history and in females compared to the patients without family history and males, respectively. In addition, we observed overexpression of GAS5 in RRMS patients compared to the normal group. Based on the obtained results, we investigated prior studies and identified relevant studies that corroborate our findings, including Gharesouran et al., which demonstrated that GAS5 expression in MS patients was higher than in controls (16). Additionally, Senousy et al. performed a study in 2020 and showed serum up-regulation of GAS5 in MS patients (20). Previous investigations have primarily examined the transcriptional level of GAS5 in the patient's serum. However, the main goal of the current study was to evaluate the expression of GAS5 exclusively within PBMCs derived from the samples. This methodological approach facilitated the removal of erythrocytes and granulocytes from the analyzed samples. Considering the crucial involvement of T cells within PBMCs in the pathogenesis of multiple sclerosis (MS), evaluating GAS5 expression in PBMCs bears significant implications for comprehensive MS sample studies. Although we obtained the diagnostic potential of GAS5 as AUC = 0.6498, Senousy et al. indicated that GAS5 could distinguish MS patients from controls by ROC curve with AUC = 0.73 (20). Notably, if future studies increase the number of samples, the power discrimination of GAS5 will be enhanced. Overall, the transcriptional level of GAS5, particularly in PBMCs, has been identified as a potential hallmark for future evaluation of the role of mitochondria in MS disease. Exosomes exhibit a non-random assortment of components derived from their parent cells, displaying a distinct composition that mirrors the cellular activation status and susceptibility to pathological states of the originating tissue. Moreover, extracellular RNA, RNA-binding proteins, and various cellular proteins demonstrate differential expression in exosomes. Notably, the cargo of exosomes released from cell cultures is predominantly composed of diverse classes of RNA, such as miRNA and long non-coding RNAs (73). In this study, cell cultures were employed to explore, for the first time, potential changes in the expression profiles of GAS5 and its targeted miRNAs in HMC3 cells and their derived exosomes following induction of redox imbalance and oxidative stress via tBHP. Following treatment, a significant upregulation of GAS5 expression was observed with a 50 µm tBHP concentration (redox imbalance) compared to both control and 200 µm tBHP conditions (oxidative stress). Additionally, a direct relationship was found between the expression levels of miR-651-5p and oxidative stress in both HMC3 cells and their derived exosomes. These findings indicate a significant association between redox imbalance and oxidative stress and the dysregulation of GAS5 and miR-651-5p expression in cells, underscoring their potential roles in the cellular stress response. Moreover, our results suggest that miR-651-5p may be transported into exosomes, especially under conditions of oxidative stress associated with MS. This transportation process could potentially be regulated by the interaction between GAS5 and miR-651-5p. While Farr et al. previously identified miR-651-5p as an indicator of lyssavirus infection in a human stem cell-derived neural model (74), there is a lack of studies investigating this miRNA in the context of MS, highlighting its potential for further exploration within the realm of MS research. Elucidating the intricate mechanisms governing the role of GAS5/miR-651-5p could offer valuable insights into disease pathogenesis and the role of mitochondria in MS. Mechanistically, it has been shown that energy-stress-induced GAS5 modulates mitochondrial tricarboxylic acid flux by disrupting the tandem association of metabolic enzymes: fumarate hydratase, malate dehydrogenase, and citrate synthase, which are canonical members of the tricarboxylic acid cycle. GAS5 negatively correlates with the levels of these associated mitochondrial metabolic enzymes in tumors and is beneficial for overall survival in individuals with breast cancer (75). It has been also reported that the knockdown of Yin-Yang 1 or GAS5 protects against ischemia/reperfusion-induced ischemic brain damage and improves overall neurological functions in vivo. Overall, Yin-Yang 1 interacts with lncRNA GAS5 to promote PFKFB3 transcription, enhancing neuronal glycolysis, which in turn exacerbates cerebral ischemia/reperfusion injury (76). Another study showed that GAS5 overexpression inhibited inflammation, oxidative stress, and pyroptosis in high-glucose-induced renal tubular cells by downregulating the expression of miR-452-5p (77). A recent study indicates that GAS5 is involved in pathways associated with neurodegeneration. The study suggests that a GAS5-targeting small molecule, NPC86, has significant therapeutic potential to prevent the onset of neurodegenerative diseases and dementias (78). Additionally, it was shown that silencing of the GAS5 alleviates neuronal cell apoptosis and inflammatory responses by sponging microRNA-93 to repress phosphatase and tensin homolog expression in spinal cord injury (79). Findings also indicate that GAS5 plays a role in regulating apoptosis, cell cycle, homeostasis of reactive oxygen species, and redox balance in MM cells. Reduced GAS5 expression is suggested to contribute to disease progression in malignant melanoma patients (80). In a study more relevant to MS, it was found that interference with GAS5 in transplanted microglia attenuates the progression of experimental autoimmune encephalomyelitis (EAE) and promotes remyelination in a lysolecithin-induced demyelination model. Consistently, higher levels of GAS5 are found in amoeboid-shaped microglia in MS patients. Further functional studies show that GAS5 suppresses the transcription of TRF4, a key factor controlling M2 macrophage polarization, by recruiting the polycomb repressive complex 2 (PRC2), thereby inhibiting M2 polarization (81). Altogether, uncovering the molecular basis of the interaction between oxidative stress, GAS5 expression, and loading of miR-651-5p in exosomes could reveal potential signaling pathways involved in MS pathobiology.

The alteration in GAS5 transcription levels in PBMCs shows potential as an indicator of mitochondrial dysregulation in RRMS. Moreover, GAS5 may exert a pivotal influence on MS development by modulating mRNA expression through miRNA-mediated mechanisms. Alternatively, the exploration of the GAS5 and its target miR-651-5p in HMC3 cells and derived exosomes sheds light on the link between redox imbalance/oxidative stress and GAS5 dysregulation, emphasizing their roles in the cellular stress response. Future research focusing on elucidating the molecular mechanisms underlying GAS5 and miR-651-5p in the context of MS as well as assessing miR-651-5p levels in serum-derived exosomes from MS patients could pave the way for innovative therapeutic and diagnostic strategies in the management of this complex neurological disorder.

Multiple Sclerosis

RRMS

Relapsing-Remitting Multiple sclerosis

PPMS

Primary Progressive MS

SPMS

Secondary Progressive MS

APC

Antigen Presenting Cell

Dendritic Cell

T Helper

IFN

Interferon

Interleukin

TNF

Tumor Necrosis Factor

CNS

Nervous System

ROS

Reactive Oxygen Species

HMC3

human microglia cell line 3

GDE

Glia-Derived Exosome

mRNA

Messenger RNA

Glucocorticoid Receptor

DBD

DNA-binding domain

Transcription Factor

RBPs

RNA binding proteins

LncRNA

Long non-coding RNA

Extracellular Vesicles

GAS5

Growth Arrest-Specific 5

GRE

Glucocorticoid Response Element

tBHP

Tert-Butyl Hydroperoxide

RBP

RNA-Binding protein

PBMC

Peripheral Blood Mononuclear Cell

HBSS

Hank's Balanced Salt Solution

FBS

Fetal Bovine Serum

FCS

Fetal Calf Serum

PBS

Phosphate Buffered Saline

EDTA

Ethylenediaminetetraacetic acid

NTA

Nanoparticle Tracking Analysis

IQR

InterQuartile Range

ROC

Receiver Operating Curve

AUC

Area Under the Curve

Confidence Interval

Gene Ontology

KEGG

Kyoto Encyclopedia of Genes and Genomes

DLBCL

Diffuse Large B‑Cell Lymphoma

OSCC

Oral Squamous Cell Carcinoma

SNV

Single Nucleotide Variant

VEGFA

Vascular Endothelial Growth Factor A

CSF

CerebroSpinal Fluid

EAE

Experimental Autoimmune Encephalomyelitis

Ethics approval and consent to participate

This research was approved by the ethics committee of the Hormozgan University of Medical Science (Ethical Code: IR.HUMS.REC.1398.031).

Consent for publication

Not applicable

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Competing interests

The authors declare that they have no competing interests

Funding

This study was supported by grant number (990324) from the Hormozgan University of Medical Sciences, Bandar Abbas, Iran. This study was also partially supported by the Alexander von Humboldt Foundation (N. Sanadgol).

Authors' contributions

Amirhossein Mohajeri Khorasani: Investigation, Data Analysis, and Writing Article. Elham Karimi: Methodology and Writing Article. Mahboobeh Zarei: Methodology and Writing Article. Hanieh Azari: Methodology and Writing Article. Cordian Beyer: Resources, and review article. Ahmad Agha Negahi: resources, and review article. Pegah Mousavi: conceptualization, methodology, supervision, and review article. Nima Sanadgol: conceptualization, methodology, and review article.

Acknowledgments

We thank all of the patients and their families for participating in this research and the Abu Reyhan MS Center Hospital and Hormozgan Molecular Medicine Research Center.

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Role of mitochondrial lncRNA GAS5 in the pathogenesis of Multiple Sclerosis: interfering with the release of miR-651-5p-enriched exosomes from microglia cells

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Version 1

Abstract

Figures

1. Introduction

2. Material and methods

2.1. GAS5-miRNAs-mRNAs regulatory network

2.2. GAS5-related gene set enrichment analysis

2.3. GAS5-related transcription factors and protein kinase

2.4. GAS5- mRNAs and RNA-binding proteins (RBPs) interaction analysis

2.5. Patients and sampling

2.6. Cell Culture and Induction of Redox Imbalance and Oxidative Stress

2.7. Exosome Extraction and Characterization

2.8. GAS5 and its related miRNAs expression analysis

2.9. Statistical analysis

3. Results

3.1. GAS5-miRNAs-mRNAs regulatory network

3.2. GAS5-related gene set enrichment analysis

3.3. GAS5-related transcription factors and protein kinase

3.4. GAS5- related mRNAs and RBPs

3.5. Patient characteristics

3.6. The GAS5 diagnostic potential analysis

3.7. In-vitro expression analysis of GAS5 and its related miRNAs in HMC3 cells and exosomes

4. Discussion

5. Conclusion

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

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