Neuroinflammation and Disrupted Synaptic Plasticity, the Main Pathological Processes in Multiple Sclerosis and Obsessive-Compulsive Disorder: An Enrichment Analysis


 Background: Multiple sclerosis (MS) is an autoimmune, inflammatory demyelinating, and disabling disorder of the central nervous system (CNS) with various clinical symptoms. Approximately 30% of the patients experience a variety of psychiatric problems during their disease course. Obsessive-compulsive disorder (OCD) is correlated with MS, but little is known about common molecular mechanisms of two diseases. Methods: In this study, after a comprehensive review of the existing literature, we collected almost all the genes involved in MS and OCD, and then analyzed the common genes between MS and OCD. Next, the connections and functional interactions between these three gene sets were investigated in the STRING database and analyzed in 3 separate networks by Cytoscape software. Eventually, after a multi-part enrichment analysis, we found the main molecular and cellular pathways, biological processes, brain areas, and, more importantly, cells/tissue related to the shared genes between MS and OCD. Results: Three genes of brain-derived neurotrophic factor (BDNF), tumor necrosis factor-alpha (TNFα), and neurexin-1 (NRXN1) are the major genes that were common between MS and OCD. Also, the deficit in synaptogenesis and neurotransmitter release in the nervous system are the most common complications of MS and OCD. Signaling receptor activity and estrogen receptor activity are the most important signaling pathways that are disturbed. Moreover, the presynaptic membrane, membrane raft, and growth cone are the main microenvironments that are affected in MS and OCD.Conclusions: In addition to an enrichment analysis that showed physical and functional interactions of genes related to MS and OCD, we demonstrated and predicted some new genes and microRNAs that can be promising biomarkers/targets for future experimental studies. Also, our finding indicated that neuroinflammation and synaptic plasticity are two significant pathological processes that are affected in MS and OCD.


Introduction
Multiple sclerosis (MS) is the most common chronic inflammatory and debilitating disease of the central nervous system. In the MS patients, changes in mobility, balance, sensation, vision, and cognition are obvious. The disease is categorized according to the initial disease course into relapsing-remitting and progressive primary types [1]. The relapsing-remitting form of the disease is the most common type and occurs in 90%-85% of MS patients [2]. Also, this type of MS affects young adults more and is three times more likely to occur in women than men [3]. In addition to various clinical signs and symptoms, psychiatric manifestations such as depression, euphoria, anxiety, mania, emotional lability, and psychosis may also be seen in these patients [4][5][6]. About 30% of MS patients experience psychiatric disorders during their illnesses [4]. Research on psychiatric manifestations of MS focuses more on depression, anxiety [6], and psychosis [7]. The rate of anxiety disorder in patients with MS has been reported by the National Comorbidity Survey as 25% [8]. In some studies, anxiety disorders, including general anxiety disorder, obsessive-compulsive disorder (OCD), and panic disorder, have been reported in MS patients [9].
OCD is a neuropsychiatric disorder that is associated with intrusive thoughts and or repetitive behaviors that are created in response to obsessions and usually to reduce distress [10]. An early indication of this disorder is anxiety that can reveal itself as panic, phobic avoidance, intrusive experiences, excessive worry, and or difficulty controlling worry. Therefore, OCD may cause severe turmoil in everyday life and social relationships [11]. The global prevalence of OCD is about 2%-3%, and the World Health Organization has placed this disorder as one of the ten debilitating diseases [12][13][14].
The relationship between MS with symptoms of generalized anxiety disorder, panic attacks [15][16][17], and OCD [18] has already been mentioned. Also, the frequency of anxiety symptoms according to neuropsychiatry inventory was reported 37% in 44 patients with MS [15]. Research studies on psychiatric disorders in MS patients mainly focus on depression, anxiety [6], and psychosis [7]. Anxiety lifespan rate in patients with MS has been reported as 25% by the National Comorbidity Survey [8]. Several studies have reported that the onset of OCD was seen in MS patients [4,9,[18][19][20][21][22][23]. The association between OCD-like behavior and MS in experimental autoimmune encephalomyelitis mice also has been reported [24].
Despite many studies done on OCD and MS, there is still little information on the pathogenesis of OCD and MS. In this regard, we assume that the comorbidity of MS and OCD may reflect the common pathophysiological mechanisms between these two disorders. Therefore, our study aimed to find and create two functional networks for MS-associated and OCD-associated genes separately and then reconstruct a new network for their shared genes. Afterward, we complete the study by analyzing each network in terms of topological and physical interaction, such as degree and betweenness centrality. Then, we investigate the most important biological processes, cellular components, and molecular functions that are distrusted in MS and OCD. Finally, our study demonstrates the most significant chromosomal regions, brain areas, cell lines, and pathways related to shared genes between MS and OCD. Also, the current study predicts some new genes that are probably involved in the pathophysiology of MS and OCD.

Materials And Methods
In this study, almost all genes involved in MS and OCD were manually collected in the first phase. Then, the involved genes were uploaded separately into the STRING database to investigate and predict gene-gene connections. Finally, Cytoscape was used to interpret and analyze the physical and functional interactions between genes and access to topological parameters related to each gene set. In other words, we use Cytoscape to visualize complicated networks.

Software and hardware requirements
The system requirements for Cytoscape depends on the size of the network (number of nodes and edges) that is loaded into the software. A system with at least 512 MB of memory and 1 GHz of the processor is required to run Cytoscape. Also, it requires a 64-bit Java runtime environment to work better and improve its running. Cytoscape is easily and freely downloadable at the following address: https://cytoscape.org/.

Searching resource for finding MS-association and OCD-association genes
We found and collected MS-related and OCD-related genes through a comprehensive literature review. We surveyed genetic association studies, linkage studies, genomewide association studies, and systematic reviews, by applying some keywords in PubMed and Google Scholar databases. The key terms were "multiple sclerosis," "MS," "Disseminated," "Obsessive-compulsive," "Obsessive-compulsive disorder," and "OCD." GWAS metaanalysis papers and animal studies also were excluded from the study. After a detailed evaluation, we found almost all of the genes associated with MS and OCD structurally, and then we analyzed the shared genes between them separately.

Genetic network creation and analysis
To form gene networks for MS-related and OCD-related genes, as well as shared genes between them, we loaded the genes found from the literature review to the STRING database (https://string-db.org/). The STRING database is a very outstanding base for integrating protein-protein interactions/associations, such as direct (physical) and indirect (functional) associations [41][42][43]. Finally, all of the genes and their interactions were uploaded to Cytoscape version 3.7.0 as three separate files. Cytoscape is open-source and free software for visualizing, integrating, and analyzing molecular connections, and genetic interaction networks [44,45]. Afterward, for each gene set, some physical parameters and topological features of each network, such as diameter, centralization, the average number of neighbors, density, and clustering coefficient, were evaluated. Furthermore, to evaluate the significance of each gene in each network, we calculated the degree (number of connections) and the betweenness centrality. We used Network Analyzer Toolkit for visualizing each node/gene.

For a vertex ,
, where is the total number of shortest paths from node s to node t. Also, is the number of those paths that pass through [46]. Betweenness centrality (C B ) indicates how much each node is involved in passing information in the genetic networks. It is a great indicator for integrating and visualizing the data. The size and color of each node were matched to characterize degree and betweenness centrality, respectively.

Geneontology enrichment analysis
Gene set enrichment analysis is a statistical approach to identify classes of genes that are over-represented in a large set of genes and may have an association with disease phenotypes [47]. Gene ontology (GO) Consortium database (http://www.geneontology.org/) and a functional enrichment analysis web tool (WEB-based Gene SeT AnaLysis Toolkit) (http://www.webgestalt.org/) were used for enrichment analysis. Then the statistically significant molecular functions, biological processes, and cellular components associated with each gene set were extracted. GO calculates the probability or chance of seeing at least x number of genes out of the total n genes in the list annotated to a particular GO term, given the proportion of genes in the whole genome that are annotated to that GO term [48]. According to Google Analytics, WebGestalt (http://www.webgestalt.org/) has, on average, 26000 users from 144 countries and territories per year. WebGestalt is a popular and widespread database for the interpretation of gene sets derived from large scale-omics studies. In the last update, WebGestalt supports 12 organisms, 354 gene identifiers from numerous databases, and 321,251 functional categories from public databases and computational analyses. [49]

Cytogenetic band enrichment analysis
We used Enrichr (http://amp.pharm.mssm.edu/Enrichr/) for finding chromosomal locations related to shared genes between MS and OCD. Enrichr currently contains 302225 annotated gene set from 153 gene set libraries for analysis.

Tissue/cell specific expression analysis
Using Enrichr (http://amp.pharm.mssm.edu/Enrichr/), tissue-specific expression analysis was carried out to find the most prominent brain regions associated with genes shared between MS and OCD. Afterward, we use the Genotype-Tissue Expression (GTEx) project (https://gtexportal.org/) for demonstrating brain expression regions of most important genes (genes that have more connections and more centrality) between MS and OCD.

Genetic network reconstruction and analysis
Among the genes associated with MS and OCD, we found no interaction for 19 and 22 genes. The MS network included 363 genes and 4401 interactions ( Supplementary Fig. 1). Given the one topological feature, betweenness centrality, tumor protein p53 (TP53), interleukin 6 (IL-6), tumor necrosis factor (TNF), epidermal growth factor receptor (EGFR), mitogen-activated protein kinase 1 (MAPK1), brain-derived neurotrophic factor (BDNF) and interleukin 2 (IL-2) were the most determinant nodes in this network, in the order of importance. The OCD network included 130 genes and 661 interactions ( Supplementary Fig. 2). BDNF, discs large MAGUK scaffold protein 4 (DLG4), Fos proto-oncogene (FOS), and DLG associated protein 1 (DLGAP1) were the most outstanding genes, in the order of prominence.

Geneontology enrichment analysis
Biological process enrichment analysis for MS-associated genes indicated that this disorder develops mainly due to disturbance in the cell-surface receptor-signaling pathway, immune system process, cell communication, and response to cytokine (Supplementary Table 3). Also, enrichment analysis for OCD-associated genes showed that OCD progress was mainly due to a disruption of trans-synaptic signaling, regulation of neurotransmitter levels, chemical synaptic transmission, and cell-cell signaling (Supplementary Table 4). Biological process enrichment analysis showed that 168 processes are associated with genes shared between MS and OCD ( Table 2). In summary, the regulation of inflammatory response to antigenic stimulus and axon development besides response to external stimulus could be considered the disrupted key processes (

Cytogenetic band enrichment analysis
Cytogenetic band enrichment analysis represented 7 chromosomal regions associated significantly with the MS-OCD shared genes. However, the significance of chromosomes X, 11, and 2 was remarkable ( Table 4).

Tissue/cell specific expression analysis
Tissue/cell-specific expression analysis using the Enrichr online tool showed that five brain regions of the dorsal striatum, cerebral cortex, cingulate gyrus, prefrontal cortex, and the superior frontal gyrus besides two cell lines of astrocytes and CD19 + B cells are significantly associated with MS-OCD shared genes (Table 5). Specific analysis of 3 important genes (BDNF, TNF, and NRXN1) using GTEx, showed exact brain expression regions of them (Fig. 3).

Discussion
In this study, we found 12 common genes between MS and OCD with a wide-ranging and targeted overview of available resources. Furthermore, network analysis showed that among the 12 common genes, three genes of BDNF, TNFα, and NRXN1, were the most central genes, in the order of centrality.
BDNF is a member of the neurotrophin family, which plays essential roles in many neural processes such as synaptic plasticity, neuronal development, and cell survival [50,51]. This protein promotes ensheathing the neurites with myelin by maturating oligodendrocyte precursor cells to oligodendrocytes and increasing myelin synthesis via tropomyosin-related kinase B signaling in them [52]. It has been shown that the level of BDNF in patients with relapsing-remitting MS (RRMS) is reduced [53], and this decrease can contribute to the progression of axonal loss and demyelinating disease in MS patients [54]. It has also reported that Sequence Variants in the BDNF gene are related to OCD [40,55]. Other studies have also shown that the Val66Met BDNF gene variant is associated with OCD development [56,57].
TNFα is a cytokine released from various types of cells, such as macrophages, lymphocytes, neutrophils, and brain astrocytes [58]. This cytokine has many functions in immunity, inflammation, and cell death [59]. Various studies have shown that TNFα levels in the brain and cerebrospinal fluid of MS patients rise, and an increase in this pro-inflammatory cytokine is associated with the development of MS [60][61][62]. The presence of this gene in the regenerated gene network represents the involvement of the immune system and inflammatory processes in these disorders. Also, the role of TNFα and inflammatory reactions have been shown in the progression of OCD, and it has been shown that polymorphisms in the TNFα gene are related to OCD [63]. Besides, the plasma levels of this pro-inflammatory cytokine are related to the progress of OCD [64].
Neurexins are a family of proteins that are essential as cell adhesion molecules in the development and establishment of the nervous system synapses [65]. Reduced synaptic density in the hippocampus and cerebral cortex of MS patients and impaired function of the neural circuits in the OCD has already been documented [66][67][68]. Besides, the dysregulation of NRXN1 leads to neurodegeneration in MS patients [69]. Noh et al. study also showed that NRXN1 is a strongly linked gene with OCD [70]. Because BDNF/ TrkB signaling plays an important role in regulating synaptic strength and transmission [50], the involvement of BDNF and NRXN1 genes in MS and OCD can explain the synaptic disruption in these two disorders.
Among the new genes that entered the network, TNFRSF1A and MAP3K7 genes had the highest degree of centrality and degree of difference and importance. The Tumor Necrosis Factor Receptor superfamily member 1A (TNFRSF1A) gene encodes a variety of TNFα receptors (TNFR1), which results in many inflammatory processes, apoptosis, and cell survival [71]. Studies have shown that variation in the TNFRSF1A gene can contribute to the progression of MS [72]. Simsek et al. suggested that low levels of TNFα through the TNFRSF1A may cause OCD or worsen it [73]. Although further studies on the changes in this gene in OCD can be valuable.
Mitogen-activated protein kinase 7 is an upstream activator of Jun N-terminal kinases (JNKs), which is activated in response to various stimuli such as growth factors, pro-inflammatory cytokines, hormones, and environmental stress and plays an important role in the development of the nervous system [74]. MAP3K7 has been reported as a new autoantigen in MS patients [75]. Future studies on the possible role of the MAP3K7 gene in MS and OCD can be helpful.
The results of enrichment analysis on common genes between MS and OCD show the regulation of the inflammatory response to antigenic stimuli (CNR1, HLA-DRB1, TNF), response to external stimulus (BDNF, CNR1, EFNB1, HLA-DRB1, NRXN1, SLC1A2, TNF, UCP2) and axon development (BDNF, CNR1, EFNB1, NRXN1) are the most important processes affected by these two disorders. It is believed that cannabinoid receptor 1 (CNR1) exists on peripheral immune cells, and is strongly expressed in active T cells [76]. Class II major histocompatibility complex (MHC) genes are molecules expressed by various types of immune system cells, including B cells, activated T cells, macrophages, dendritic cells, and thymus epithelial cells. They play a central role in the immune system by presenting peptides derived from extracellular proteins [77]. BDNF is a factor that is essential for the growth and development of axons [78], and studies have shown that the expression of BDNF in the inflammation conditions is significantly reduced [79,80]. Neurexins play a significant role in synaptogenesis, and neurotransmitter releases [65,81]. The findings indicate that CNR1 is essential for the normal growth of axons [82], and the rate of expression of these receptors on peripheral blood mononuclear cells increases in inflammatory conditions by inflammatory cytokines [83]. It has also been shown that defect in EFNB1 gene leads to malformation of the corpus callosum [84]. The results also showed that estrogen receptor activity and estrogen response element-binding are other processes associated with MS and OCD common genes. It shows that estrogen may also play a role in the pathogenesis of these disorders. It has been shown that the use of the ER1 and ER2 ligands has protective effects in the animal model of MS, namely, experimental autoimmune encephalomyelitis (EAE) [85,86].
Further analyses of MS and OCD common genes indicate that the integral component of the plasma membrane, membrane raft, and growth cone are the most important areas affected by the disorders. Membrane rafts play a significant role in the adhesion and motility of growth cone, and therefore their normal function is essential for axon guidance [87].
Tissue/cell specific expression analysis showed that five major brain regions and two cell lines are associated with MS and OCD. The relationship between dorsal striatum, prefrontal cortex, cingulate cortex, and cerebral cortex with MS in neuroimaging studies has been proven in patients [88,89]. Astrocytes are the most important glial cells in the CNS. In the animal model of EAE, they have neuroprotective and anti-inflammatory effects by the expression of ER1 and the production of neurosteroids such as estrogen [90]. The reactive form of these cells is critical in the development of brain lesions and the production of scars in MS by producing pro-inflammatory cytokines and movement of innate immune cells (chemotaxis) into the brain tissue [91]. The role of CD19 + B-cell in the pathogenesis of MS has also been proven [92]. Besides, dysfunction of structures such as the striatum, cerebral cortex, prefrontal cortex, and cingulate cortex in OCD has also been reported [93]. At the cellular level, recent studies have also shown the involvement of brain astrocytes in repetitive and compulsive behaviors [94,95].
MicroRNAs are small noncoding RNA molecule that are involved in the regulation of gene expression through silencing their target mRNAs and inhibit their translation [96]. Each miRNA can regulate the expression of a large number of target genes. Recent experiments have strongly focused on these molecules. For instance miR-410 has neuroprotective effects and can regulate neurogenesis [97,98]. Also, miR-344-3p is crucial for development of nervous system and morphogenesis [99]. Interestingly, miR-221 could stimulate Schwann cell proliferation [100] and also, decrease inflammatory responses and cell death in neuronal cells [101].

Conclusions
In summary, we concluded that the three genes of BDNF, TNFα, and NRXN1 are the major genes involved in the pathogenesis of MS and OCD and deficit in synaptogenesis and neurotransmitter release in the nervous system are the most common complications of MS and OCD. Also, disruption of signaling receptor and estrogen receptor activity are the most important signaling pathways that are disturbed and, the presynaptic membrane, membrane raft, and growth cone are the main areas that are affected in MS and OCD. On the other hand, we predicted ten new genes, seven chromosomal regions, five brain areas, ten miRNAs, and two cell lines that are common between MS and OCD. Finally, our study showed that the commonality between MS and OCD is related to the dysfunction of genes involved in synaptogenesis, plasticity, and neuroinflammation in some brain regions, especially in the dorsal striatum, cerebral cortex, cingulate gyrus, and prefrontal cortex. Also, it seems that astrocytes are among the cells target responsible for the neuropathological change in MS and OCD. We suggest that experimental studies in the future confirm some of these findings and our predicted miRNAs can be a therapeutic target for MS and OCD. Not applicable.

Funding
Funding information is not applicable / No funding was received.

Authors' contributions
Ali Sepehrinezhad, Ali Bozorgmehr, and Ali Shahbazi designed the study, carried out the literature review, and drafted the manuscript. Ali Shahbazi, Sajad Sahab Negah and Minoo Karimi carried out the literature review and participated in drafting the manuscript. Also, Ali Shahbazi and Sajad Sahab Negah critically edited the manuscript and corrected grammatical errors in the revised manuscript. All authors read and approved the final manuscript.

Availability of data and materials
The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.

Ethics approval and consent to participate
Not applicable.

Consent for publication
Not applicable.

Figure 1
This genetic network represents interactions between shared genes in MS and OCD. This network consists of 12 nodes and 16 edges. The larger nodes indicate a higher degree and more connections, while darker orange color means greater betweenness centrality. This genetic network represents interactions between MS-OCD shared genes and novel genes that are added. The current network comprised 22 nodes and 65 edges. Circular nodes indicate common genes between MS and OCD based on the literature review, while hexagonal nodes represent novel genes that are added based on the interaction data. The larger nodes indicate a higher degree and more connections, while darker orange color means greater betweenness centrality.

Figure 3
Genotype-Tissue expression analysis results for BDNF, TNF, and NRXN1. Expression value for each gene displayed in TPM (Transcripts Per Million). Darker color indicates more expression in that area.

Figure 4
Predicted microRNAs families in MS-OCD shared genes. Each miRNA family adjusted with p-value (Benjamini and Hochberg).

Supplementary Files
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