1. Introduction
Migraine is known as a public and sometimes devastating disorder (Goadsby et al., 2002). Migraine has been reported to be associated with several disorders, such as cardiovascular diseases, gastrointestinal disorders, and vertigo (Adelborg et al., 2018; Felisati et al., 2010) Documents exist about the association between migraine and the development of brain tumors (Chen et al., 2018). Several studies discussed the molecular mechanism of migraine and pointed to the genes and proteins involved in migraine development (Goadsby, 2007; Olesen et al., 1993). 
Protein-protein interaction network analysis is a suitable method to assess the molecular mechanism of diseases. In this method, a set of proteins or genes involved in the evaluated disease are connected to form an interactome. Since the number of interactions and first neighbors of each protein may differ from others, the role of elements of the network is different from the other proteins. In scale-free networks, top nodes are limited by the number of first neighbors or connections to the first neighbors. These nodes are known as hubs and play a crucial role in network construction (Farahani et al., 2022; Zamanian-Azodi et al., 2021). Based on the shortest paths attributed to a node, bottleneck nodes are announced. Bottlenecks are known as central nodes of a network, which play a significant role in the integration of the network (Heidari et al., 2020). A hub node that acts as a bottleneck is known as a hub bottleneck. The hub-bottleneck nodes are powerful elements of the network and are considered critical nodes (Mateus Pellenz et al., 2022).
Hub, bottleneck, and hub-bottleneck nodes are used to detect the molecular mechanisms of many diseases (Gupta et al., 2015; Huo et al., 2017). 
Data sources in network analysis can be considered databases or an experimental investigation. STRING is a well-known database that includes many diseases and related dysregulated proteins (Szklarczyk et al., 2016). In the present study, the dysregulated proteins of migraine and gliosarcoma are extracted from the STRING database and analyzed by network analysis to find central nodes that link migraine to gliosarcoma.

2. Methods and Materials
A total of 200 related proteins for migraine were searched from “the disease query” of the STRING database. The extracted proteins were interacted via undirected edges by using Cytoscpe software, version 3.7.2. The network was analyzed by “the network analyzer” application of Cytoscape software, version 3.7.2. The top 10% of nodes of the main connected component were selected as hubs and bottlenecks, respectively, based on degree value and betweenness centrality. The common hubs and bottlenecks were identified as hub bottlenecks.
As with migraine, 200 dysregulated proteins that were related to gliosarcoma were extracted from the STRING database. These proteins were interacted by Cytoscape software to form an interactome. To identify the central nodes of the network, the main connected component of the network was analyzed by “network analyzer”. The hub bottlenecks were introduced as the main analyzed component. 
Hub-bottleneck nodes of the two diseases were compared and the common individuals were identified. To find the critical role of the common hub bottlenecks, 10 first neighbors of each one or each set were determined from the STRING database. Finally, the common hub bottlenecks and the first neighbors were assessed and discussed. 

3. Results
The retrieved proteins related to migraine were included in a network. The network included 14 isolated proteins, a subnetwork contains a pair of proteins, and a main connected component subnetwork was formed. The main connected component was constructed from 184 nodes and 2388 edges. To find the central nodes, 10% (18 proteins) of top nodes based on degree value were identified as hubs and similarly, 18 bottlenecks were determined. Among hubs and bottlenecks, 11 hub-bottleneck nodes were introduced. Table 1 presents the hub bottlenecks. 

The main connected component of the gliosarcoma network was constructed from 187 nodes and 3732 undirected connections. A number of 13 proteins were isolated. Among 19 hubs and also 19 bottlenecks, 11 common hub bottlenecks were identified. Table 2 presents the list of hub-bottleneck nodes. 

A comparison of Tables 1 and 2 indicates that albumin (ALB) and interleukin 6 (IL6) are the two common hub bottlenecks between migraine and gliosarcoma diseases. To better understand the role of ALB and IL6, Figures 1-3 shows 10 first neighbors of ALB, IL6, and ALB-IL6. 

4. Discussion
Many common features exist between diseases, especially aspects of the molecular mechanisms of diseases. Investigating common key proteins which are common between migraine and brain cancers is a way to understand migraine as a risk factor for these types of cancers. In the present study, ALB and IL6 were identified as two central common proteins which play a critical role in the protein-protein interaction networks of the two studied diseases.
Jacobsen et al investigated urinary albumin excretion as an endothelial dysfunction marker in patients with migraine (Jacobsen et al., 2013). Based on this research, no significant increase was observed in the excreted albumin level and systemic endothelial dysfunction. Therefore, they concluded that systemic endothelial dysfunction is not a prominent feature of migraine. The other document refers to low levels of serum albumin in migraine patients compared to the control group (Yazar et al., 2020).
It is pointed out that albumin is a cancer marker (Lv et al., 2018). It is reported that apo A1 and albumin play a crucial role in glioma tumor growth, migration, and angiogenesis (Hashemi et al., 2014). Based on this investigation, upregulation of apolipoprotein A1 and albumin occurs in astrocytoma brain tumors. Nieder et al suggested that the patients with brain metastasis who present dysregulated albumin levels in combination with elevated lactate dehydrogenase and also the occurrence of extracranial metastases to at least two organs should be considered for the finest kind of care (Nieder et al., 2014). 
As shown in Figure 1, IL6 is the first neighbor of ALB, another common central node (hub-bottleneck) of migraine and gliosarcoma cancer networks. Comparing Figure 1 and Table 2 indicates that VEGFA, IL6, and FN1 are the first neighbors of ALB which are central nodes of the gliosarcoma cancer network. On the other hand, the comparison of Tables 1, 2 and Figure 2 show no common proteins between the first neighbors of IL6 and central nodes of migraine and gliosarcoma cancer networks.
Il6 is the second common hub bottleneck between migraine and gliosarcoma. It is reported that glioma stem cells, but not the bulk glioma cells, are responsible to initiate microglial IL-6 secretion. This process occurs via Toll-like receptor-4 signaling, which regulates secretion of IL-6 in glioma development (Dzaye et al., 2016). On the other hand, documents exist about the elevation of intracranial interleukin-6 in patients during migraine attacks. The involvement of IL6 and IL1β in the pathogenesis of migraine is investigated by D Han (Han, 2019; Yan et al., 2012).
The first neighbors of ALB-IL6 paired nodes that are linked to the migraine and gliosarcoma networks are VEGFA, neurofibromatosis type I (NF1), and KNG1. KNG1 is a common protein between central nodes of the migraine network and the first neighbors of ALB-IL6 while VEGFA and NF1 like central nodes of the gliosarcoma cancer network to the first neighbors of ALB-IL6 paired proteins. The role of KNG1 in migraine is highlighted by Zamanian-Azodi et al. Based on this assessment, KNG1 inhibits nitric oxide synthase 3 (NOS3) which is a hub node in the protein-protein interaction network of migraine (Zamanian-Azodi et al., 2019). Zhang et al suggested VEGFA Fms-related receptor tyrosine kinase 1 (FLT1) and kinase insert domain receptor (KDR) messenger ribonucleic acid (mRNA) expression as prognostic factors in brain tumors (Zhang et al., 2015). NF1 is associated with abnormalities in the regulation of astrocytes and also the promotion of brain tumors. As reported by Dasgupta et al, neurofibromin is involved in the proliferation and survival of neural stem cells and also regulates astroglial differentiation (Dasgupta & Gutmann, 2005). 

5. Conclusion
In conclusion, several molecular linkers are observed between migraine and brain cancers; however, ALB and IL6 can be considered two critical individuals. Also, network analysis revealed that several ALB-IL6 first neighbors are connected to the central elements of protein-protein interaction networks of migraine and gliosarcom. 

Ethical Considerations
Compliance with ethical guidelines
This project is approved by Shahid Beheshti University of Medical Sciences (Code: IR.SBMU.RETECH.REC.1399.1203).

Funding
This project is supported by Shahid Beheshti University of Medical Sciences.

Authors' contributions
Project is designed by Vahid Mansouri and all authors are participated equally in project administration and manuscript preparation.

Conflict of interest
The authors declared no conflict of interest.

Acknowledgments
The authors would like to thank Shahid Beheshti University of Medical Sciences for the support.


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