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Identification of novel gene and pathway targets for human epilepsy treatment.

ABSTRACT: The aim of this study was to explore epilepsy-related mechanism so as to figure out the possible targets for epilepsy treatment.The gene expression profile dataset GES32534 was downloaded from Gene Expression Omnibus database. We identified the differentially expressed genes (DEGs) by Affy package. Then the DEGs were used to perform gene ontology (GO) and pathway enrichment analyses. Furthermore, a protein-protein interaction (PPI) network was constructed with the DEGs followed by co-expression modules construction and analysis.Total 420 DEGs were screened out, including 214 up-regulated and 206 down-regulated genes. Functional enrichment analysis revealed that down-regulated genes were mainly involved in the process of immunity regulation and biological repairing process while up-regulated genes were closely related to transporter activity. PPI network analysis showed the top ten genes with high degrees were all down-regulated, among which FN1 had the highest degree. The up-regulated and down-regulated DEGs in the PPI network generated two obvious sub-co-expression modules, respectively. In up-co-expression module, SCN3B (sodium channel, voltage gated, type III beta subunit) was enriched in GO:0006814 ~ sodium ion transport. In down-co-expression module, C1QB (complement C1s), C1S (complement component 1, S subcomponent) and CFI (complement factor I) were enriched in GO:0006955 ~ immune response.The immune response and complement system play a major role in the pathogenesis of epilepsy. Additionally, C1QB, C1S, CFI, SCN3B and FN1 may be potential therapeutic targets for epilepsy.

SUBMITTER: Jin Y

PROVIDER: S-EPMC4705636 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature

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Identification of novel gene and pathway targets for human epilepsy treatment.

Jin Ying Y Zhao Chunzhe C Chen Lihui L Liu Xiangyu X Pan Shuxiao S Ju Dongsheng D Ma Jing J Li Jinying J Wei Bo B

Biological research 20160107

<h4>Background</h4>The aim of this study was to explore epilepsy-related mechanism so as to figure out the possible targets for epilepsy treatment.<h4>Methods</h4>The gene expression profile dataset GES32534 was downloaded from Gene Expression Omnibus database. We identified the differentially expressed genes (DEGs) by Affy package. Then the DEGs were used to perform gene ontology (GO) and pathway enrichment analyses. Furthermore, a protein-protein interaction (PPI) network was constructed with ...[more]

PMID: 26742644

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Project description:Diabetic nephropathy (DN) is a major complication of type1 and type 2 diabetes. Understanding how diabetes regulate transcriptome dynamics in DN is important for understanding the biology of the disease and for guiding development of new treatments.We analyzed the kidney transcriptome of a DN mouse model, D2.B6-Ins2 Akita /MatbJ, before/after treatment with P78-PEDF. Age, weight, and gender-matched mice and wild-type (wt) littermates were treated at 6 weeks (early treatment) or 12 weeks (late treatment) of age for the duration of 6 weeks. Animals were implanted with an osmotic mini pump delivering 0.3 ug/g/day P78-PEDF or vehicle. Using RNA-seq, we identified14,316 transcripts (12,328 coding;1,988 non-coding) that were significant and reliably expressed (FPKM?>?=1) in diabetic kidneys. Expression of 1,129 (7.9%) including 901 coding genes was altered by diabetes with log2 fold changes (FC) between -86.2 and +86.0 (q?<?0.05) compared to wt. Of these, 164 (14.5%) showed increased and 965 (85.5%) decreased expression with FC?>?1.5. Coding genes with highest FC in diabetic kidneys include Nhej1 (32.04), Ept1 (8.6), Srd5a2 (-6.55), Aif1 (-6.05), and Angptl7 (-4.71). Early and late stage diabetic groups receiving continuous infusion of P78 showed altered expression of 316/14,316 (2.2%) transcripts, including 121 coding genes compared to non-treated diabetic controls. Of these, 183 were upregulated and 133 downregulated with FC +50.9--93.3 (q?<?0.05). P78 reversed diabetes-induced changes in 138/1129 (12.2%) transcripts, including 49/901 (5.44%) coding genes. Nhej1 (-37.94), Tceanc2 (5.76), Ept1 (-4.45), Ugt1a2 (3.03), and Tmsb15l (-3.0) showed the highest FC with treatment. The DNA repair gene, Nhej1 with the greatest FC in diabetic kidneys was completely restored to control levels by both early and late P78 treatments. Expression of other coding genes regulated by diabetes with FC?>?=(+/-) 1.5 and completely reversed by P78 include Mamdc4, Kdm4b, Tmem252, Selm, and Hpd. RT and QRT-PCR validated expression of gene with FC?>?(+/-)2.0. Transcriptome changes were also observed between early and late-stage treatments. Precursor non-coding miRNAs showed the highest fold changes in expression in the diabetic and P78 treatment groups. Several diabetic-induced changes were reversed in direction of expression by treatment including Gm24083, GM25953, miR1905, Gm25535, Gm27903, and miR196a1 with FC?>?=(+/-)20. From Ingenuity pathway analysis (IPA), mitochondrial dysfunction, Nrf-2- mediated oxidative stress and renal injury pathways emerged as key mechanisms in DN. DN-enriching genes in these pathways were reduced in number or regulated in the opposite direction by treatment.Unique biomarkers and canonical pathways identified in this study may hold the key to understanding mechanisms of DN pathobiology with value for clinical translation. Our data suggest that mitochondrial dysfunction, genotoxicity and oxidative stress are principal events in DN and that P78-PEDF holds promise for its management.

Dataset Information

Identification of novel gene and pathway targets for human epilepsy treatment.

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Identification of novel gene and pathway targets for human epilepsy treatment.

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