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Integrated network analysis reveals potentially novel molecular mechanisms and therapeutic targets of refractory epilepsies

View Article: PubMed Central - PubMed

ABSTRACT

Epilepsy is a complex neurological disorder and a significant health problem. The pathogenesis of epilepsy remains obscure in a significant number of patients and the current treatment options are not adequate in about a third of individuals which were known as refractory epilepsies (RE). Network medicine provides an effective approach for studying the molecular mechanisms underlying complex diseases. Here we integrated 1876 disease-gene associations of RE and located those genes to human protein-protein interaction (PPI) network to obtain 42 significant RE-associated disease modules. The functional analysis of these disease modules showed novel molecular pathological mechanisms of RE, such as the novel enriched pathways (e.g., “presynaptic nicotinic acetylcholine receptors”, “signaling by insulin receptor”). Further analysis on the relationships between current drug targets and the RE-related disease genes showed the rational mechanisms of most antiepileptic drugs. In addition, we detected ten potential novel drug targets (e.g., KCNA1, KCNA4-6, KCNC3, KCND2, KCNMA1, CAMK2G, CACNB4 and GRM1) located in three RE related disease modules, which might provide novel insights into the new drug discovery for RE therapy.

No MeSH data available.


Related in: MedlinePlus

Refractory Epilepsies (RE) disease-gene network and relationships statistics.(A) Disease-gene network showing the relationships of 1,086 genes corresponding to 23 MeSH Headings. The long label big nodes denote diseases in MeSH terminologies; the small nodes denote genes. The size of the node is positively related to the number of linked genes. Different colors represent different diseases. Genes located in the center of the network are associated with several diseases (e.g. SCN1A, KCNQ2). Genes located at the periphery of the network are associated with a single disease (e.g. CHRNA5, CHRNB4). (B) The gene-related MeSH heading numbers are distributed from 1 to 10, with different numbers for different colors. The total number of seed genes is 1086, of which 711 (accounting for 65.47%) are only associated with one disease subtype (MeSH heading).
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pone.0174964.g002: Refractory Epilepsies (RE) disease-gene network and relationships statistics.(A) Disease-gene network showing the relationships of 1,086 genes corresponding to 23 MeSH Headings. The long label big nodes denote diseases in MeSH terminologies; the small nodes denote genes. The size of the node is positively related to the number of linked genes. Different colors represent different diseases. Genes located in the center of the network are associated with several diseases (e.g. SCN1A, KCNQ2). Genes located at the periphery of the network are associated with a single disease (e.g. CHRNA5, CHRNB4). (B) The gene-related MeSH heading numbers are distributed from 1 to 10, with different numbers for different colors. The total number of seed genes is 1086, of which 711 (accounting for 65.47%) are only associated with one disease subtype (MeSH heading).

Mentions: After filtering the relationships with significant correlations (i.e. p-value < 0.05), total 3,219 disease-gene relationships were obtained with the corresponding number of occurrences in the CoreMine PubMed search engine system[27]. All literatures related to the 3,219 relationships in the PubMed database were analyzed and only 1,852 disease-gene relationships with 1,065 distinct genes were identified. There were additional 24 disease-gene relationships with 21 distinct genes, which were not included in the CoreMine data sources by checking the Online Mendelian Inheritance in Man (OMIM)[28] and DiseaseConnect[29] databases. All together we finally obtain 1,086 RE-related genes for further analysis. To further validate the reliability of the genes, we also conducted the external validation analysis of epilepsy disease-gene associations using the latest data from the high-quality genotype-phenotype associations of Human Phenotype Ontology (HPO) database [50]. Using “seizure or seizures” as keywords, we obtained 662 genes from HPO disease-gene associations that are related to disease phenotypes with seizure manifestations. There were 215 (215/662 = 32.5%) genes were overlapped with the 1086 RE-related genes, which has 5.70-folds over random expectations (p-value<9.39E-100; binomial test). This result indicates that our curated disease-gene associations have significant overlap with the gene list associated with seizure phenotypes and thus further means that our data is reliable for further analysis. The disease-gene association network with 1876 links was visualized accordingly and it showed clearly that the 23 RE related disease phenotypes (in terms of MeSH headings) both have their own distinct genes and many shared genes among them (Fig 2A). In addition, we found that most (711/1086 = 65.47%) of the genes related to just one disease subtype (Fig 2B). However, substantial ratio (~35%) of the genes is associated with multiple disease subtypes. For example, SCN1A associates with 10 disease subtypes, while the four genes: KCNQ2, NHLRC1, PCDH19 and SCN1B associate with 9 subtypes.


Integrated network analysis reveals potentially novel molecular mechanisms and therapeutic targets of refractory epilepsies
Refractory Epilepsies (RE) disease-gene network and relationships statistics.(A) Disease-gene network showing the relationships of 1,086 genes corresponding to 23 MeSH Headings. The long label big nodes denote diseases in MeSH terminologies; the small nodes denote genes. The size of the node is positively related to the number of linked genes. Different colors represent different diseases. Genes located in the center of the network are associated with several diseases (e.g. SCN1A, KCNQ2). Genes located at the periphery of the network are associated with a single disease (e.g. CHRNA5, CHRNB4). (B) The gene-related MeSH heading numbers are distributed from 1 to 10, with different numbers for different colors. The total number of seed genes is 1086, of which 711 (accounting for 65.47%) are only associated with one disease subtype (MeSH heading).
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC5384674&req=5

pone.0174964.g002: Refractory Epilepsies (RE) disease-gene network and relationships statistics.(A) Disease-gene network showing the relationships of 1,086 genes corresponding to 23 MeSH Headings. The long label big nodes denote diseases in MeSH terminologies; the small nodes denote genes. The size of the node is positively related to the number of linked genes. Different colors represent different diseases. Genes located in the center of the network are associated with several diseases (e.g. SCN1A, KCNQ2). Genes located at the periphery of the network are associated with a single disease (e.g. CHRNA5, CHRNB4). (B) The gene-related MeSH heading numbers are distributed from 1 to 10, with different numbers for different colors. The total number of seed genes is 1086, of which 711 (accounting for 65.47%) are only associated with one disease subtype (MeSH heading).
Mentions: After filtering the relationships with significant correlations (i.e. p-value < 0.05), total 3,219 disease-gene relationships were obtained with the corresponding number of occurrences in the CoreMine PubMed search engine system[27]. All literatures related to the 3,219 relationships in the PubMed database were analyzed and only 1,852 disease-gene relationships with 1,065 distinct genes were identified. There were additional 24 disease-gene relationships with 21 distinct genes, which were not included in the CoreMine data sources by checking the Online Mendelian Inheritance in Man (OMIM)[28] and DiseaseConnect[29] databases. All together we finally obtain 1,086 RE-related genes for further analysis. To further validate the reliability of the genes, we also conducted the external validation analysis of epilepsy disease-gene associations using the latest data from the high-quality genotype-phenotype associations of Human Phenotype Ontology (HPO) database [50]. Using “seizure or seizures” as keywords, we obtained 662 genes from HPO disease-gene associations that are related to disease phenotypes with seizure manifestations. There were 215 (215/662 = 32.5%) genes were overlapped with the 1086 RE-related genes, which has 5.70-folds over random expectations (p-value<9.39E-100; binomial test). This result indicates that our curated disease-gene associations have significant overlap with the gene list associated with seizure phenotypes and thus further means that our data is reliable for further analysis. The disease-gene association network with 1876 links was visualized accordingly and it showed clearly that the 23 RE related disease phenotypes (in terms of MeSH headings) both have their own distinct genes and many shared genes among them (Fig 2A). In addition, we found that most (711/1086 = 65.47%) of the genes related to just one disease subtype (Fig 2B). However, substantial ratio (~35%) of the genes is associated with multiple disease subtypes. For example, SCN1A associates with 10 disease subtypes, while the four genes: KCNQ2, NHLRC1, PCDH19 and SCN1B associate with 9 subtypes.

View Article: PubMed Central - PubMed

ABSTRACT

Epilepsy is a complex neurological disorder and a significant health problem. The pathogenesis of epilepsy remains obscure in a significant number of patients and the current treatment options are not adequate in about a third of individuals which were known as refractory epilepsies (RE). Network medicine provides an effective approach for studying the molecular mechanisms underlying complex diseases. Here we integrated 1876 disease-gene associations of RE and located those genes to human protein-protein interaction (PPI) network to obtain 42 significant RE-associated disease modules. The functional analysis of these disease modules showed novel molecular pathological mechanisms of RE, such as the novel enriched pathways (e.g., &ldquo;presynaptic nicotinic acetylcholine receptors&rdquo;, &ldquo;signaling by insulin receptor&rdquo;). Further analysis on the relationships between current drug targets and the RE-related disease genes showed the rational mechanisms of most antiepileptic drugs. In addition, we detected ten potential novel drug targets (e.g., KCNA1, KCNA4-6, KCNC3, KCND2, KCNMA1, CAMK2G, CACNB4 and GRM1) located in three RE related disease modules, which might provide novel insights into the new drug discovery for RE therapy.

No MeSH data available.


Related in: MedlinePlus