Alzheimer's disease (AD), also known as senile dementia, is a progressive neurodegenerative disease. The etiology and pathogenesis of AD have not yet been elucidated. We examined common differentially expressed genes (DEGs) from different AD tissue microarray datasets by meta-analysis and screened the AD-associated genes from the common DEGs using GCBI. Then we studied the gene expression network using the STRING database and identified the hub genes using Cytoscape. Furthermore, we analyzed the microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and single nucleotide polymorphisms (SNPs) associated with the AD-associated genes, and then identified feed-forward loops. Finally, we performed SNP analysis of the AD-associated genes. Our results identified 207 common DEGs, of which 57 have previously been reported to be associated with AD. The common DEG expression network identified eight hub genes, all of which were previously known to be associated with AD. Further study of the regulatory miRNAs associated with the AD-associated genes and other genes specific to neurodegenerative diseases revealed 65 AD-associated miRNAs. Analysis of the miRNA associated transcription factor-miRNA-gene-gene associated TF (mTF-miRNA-gene-gTF) network around the AD-associated genes revealed 131 feed-forward loops (FFLs). Among them, one important FFL was found between the gene SERPINA3 , hsa-miR-27a, and the transcription factor MYC. Furthermore, SNP analysis of the AD-associated genes identified 173 SNPs, and also found a role in AD for miRNAs specific to other neurodegenerative diseases, including hsa-miR-34c, hsa-miR-212, hsa-miR-34a, and hsa-miR-7. The regulatory network constructed in this study describes the mechanism of cell regulation in AD, in which miRNAs and lncRNAs can be considered AD regulatory factors.

Axon regeneration is crucial for recovery from neurological diseases. Numerous studies have identified several genes, microRNAs (miRNAs), and transcription factors (TFs) that influence axon regeneration. However, the regulatory networks involved have not been fully elucidated. In the present study, we analyzed a regulatory network of 51 miRNAs, 27 TFs, and 59 target genes, which is involved in axon regeneration. We identified 359 pairs of feed-forward loops (FFLs), seven important genes (Nap1l1, Arhgef12, Sema6d, Akt3, Trim2, Rab11fip2, and Rps6ka3), six important miRNAs (hsa-miR-204-5p, hsa-miR-124-3p, hsa-miR-26a-5p, hsa-miR-16-5p, hsa-miR-17-5p, and hsa-miR-15b-5p), and eight important TFs (Smada2, Fli1, Wt1, Sp6, Sp3, Smad4, Smad5, and Creb1), which appear to play an important role in axon regeneration. Functional enrichment analysis revealed that axon-associated genes are involved mainly in the regulation of cellular component organization, axonogenesis, and cell morphogenesis during neuronal differentiation. However, these findings need to be validated by further studies.

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BackgroundParkinson’s disease (PD) is a long-term degenerative disease that is caused by environmental and genetic factors. The networks of genes and their regulators that control the progression and development of PD require further elucidation.MethodsWe examine common differentially expressed genes (DEGs) from several PD blood and substantia nigra (SN) microarray datasets by meta-analysis. Further we screen the PD-specific genes from common DEGs using GCBI. Next, we used a series of bioinformatics software to analyze the miRNAs, lncRNAs and SNPs associated with the common PD-specific genes, and then identify the mTF-miRNA-gene-gTF network.ResultOur results identified 36 common DEGs in PD blood studies and 17 common DEGs in PD SN studies, and five of the genes were previously known to be associated with PD. Further study of the regulatory miRNAs associated with the common PD-specific genes revealed 14 PD-specific miRNAs in our study. Analysis of the mTF-miRNA-gene-gTF network about PD-specific genes revealed two feed-forward loops: one involving the SPRK2 gene, hsa-miR-19a-3p and SPI1, and the second involving the SPRK2 gene, hsa-miR-17-3p and SPI. The long non-coding RNA (lncRNA)-mediated regulatory network identified lncRNAs associated with PD-specific genes and PD-specific miRNAs. Moreover, single nucleotide polymorphism (SNP) analysis of the PD-specific genes identified two significant SNPs, and SNP analysis of the neurodegenerative disease-specific genes identified seven significant SNPs. Most of these SNPs are present in the 3′-untranslated region of genes and are controlled by several miRNAs.ConclusionOur study identified a total of 53 common DEGs in PD patients compared with healthy controls in blood and brain datasets and five of these genes were previously linked with PD. Regulatory network analysis identified PD-specific miRNAs, associated long non-coding RNA and feed-forward loops, which contribute to our understanding of the mechanisms underlying PD. The SNPs identified in our study can determine whether a genetic variant is associated with PD. Overall, these findings will help guide our study of the complex molecular mechanism of PD.Electronic supplementary materialThe online version of this article (10.1186/s12920-018-0357-7) contains supplementary material, which is available to authorized users.

In order to improve the therapeutic effects of mesenchymal stem cell (MSC)-based therapies for a number of intractable neurological disorders, a more favorable strategy to regulate the outcome of bone marrow MSCs (bMSCs) was examined in the present study. In view of the wide range of neurotrophic and neuroprotective effects, Tetramethylpyrazine (TMP), a biologically active alkaloid isolated from the herbal medicine Ligusticum wallichii, was used. It was revealed that treatment with 30–50 mg/l TMP for 4 days significantly increased cell viability, alleviated senescence by suppressing NF-κB signaling, and promoted bMSC proliferation by regulating the cell cycle. In addition, 40–50 mg/l TMP treatment may facilitate the neuronal differentiation of bMSCs, verified in the present study by presentation of neuronal morphology and expression of neuronal markers: microtubule-associated protein 2 (MAP-2) and neuron-specific enolase (NSE). The quantitative real-time polymerase chain reaction (qRT-PCR) revealed that TMP treatment may promote the expression of neurogenin 1 (Ngn1), neuronal differentiation 1 (NeuroD) and mammalian achaete–scute homolog 1 (Mash1). In conclusion, 4 days of 40–50 mg/l TMP treatment may significantly delay bMSC senescence by suppressing NF-κB signaling, and enhancing the self-renewal ability of bMSCs, and their potential for neuronal differentiation.