Abstract
The purpose of this study was to explore the key mechanism involved in the pathogenesis of Parkinson’s disease (PD) based on microarray analysis. The expression profile data of GSE7621, which contained 9 substantia nigra tissues isolated from normals and 16 substantia nigra tissues isolated from PD patients, was obtained from Gene Expression Omnibus. The differentially expressed genes (DEGs) were screened, followed by functional enrichment analysis and protein-protein interaction (PPI) network construction. After the miRNAs regulating the DEGs were predicted, the miRNA-DEG regulatory network was then constructed. Besides, the 6-hydroxydopamine rat model of PD was established and the expression of key DEGs and miRNA was detected. A total of 388 DEGs were identified, including 218 upregulated genes and 170 downregulated ones. Tyrosine hydroxylase (TH) and solute carrier family 6 member 3 (SLC6A3) were significantly related to the functional terms of catecholamine biosynthetic process and dopamine biosynthetic process. TH and SLC6A3 were hub nodes in the PPI network. EBF3 could be targeted by miR-218. Moreover, TH and SLC6A3 were found downregulated in the 6-OHDA rat model of PD, while miR-218 was markedly upregulated. Our results reveal that SLC6A3, TH, and EBF3 targeted by miR-218 could be involved in PD. These molecules might provide a new insight into the development of therapeutic strategies for PD.
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Alvord G, Roayaei J, Stephens R, Baseler MW, Lane HC, Lempicki RA (2007) The DAVID Gene Functional Classification Tool: a novel biological module-centric algorithm to functionally analyze large gene lists. Genome Biol 8:R183
Aoki-Kinoshita KF, Kanehisa M (2007) Gene annotation and pathway mapping in KEGG. In Comparative genomics, Eds Springer, 71–91
Baek S, Choi H, Kim J (2014) Ebf3-miR218 regulation is involved in the development of dopaminergic neurons. Brain Res 1587:23–32
Dauer W, Przedborski S (2003) Parkinson’s disease: mechanisms and models. Neuron 39:889–909
de Lau LM, Breteler MM (2006) Epidemiology of Parkinson’s disease. Lancet Neurol 5:525–535
Diboun I, Wernisch L, Orengo CA, Koltzenburg M (2006) Microarray analysis after RNA amplification can detect pronounced differences in gene expression using limma. BMC Genomics 7:252
Farrer MJ (2006) Genetics of Parkinson disease: paradigm shifts and future prospects. Nat Rev Genet 7:306–318
Fauss D, Motter R, Dofiles L, Rodrigues MAV, You M, Diep L, Yang Y, Seto P, Tanaka K, Baker J, Bergeron M (2013) Development of an enzyme-linked immunosorbent assay (ELISA) to measure the level of tyrosine hydroxylase protein in brain tissue from Parkinson’s disease models. J Neurosci Methods 215:245–257
Franceschini A, Szklarczyk D, Frankild S et al (2013) STRING v9. 1: protein-protein interaction networks, with increased coverage and integration. Nucleic Acids Res 41:D808–D815
Habak C, Noreau A, Nagano-Saito A, Mejía-Constaín B, Degroot C, Strafella AP, Chouinard S, Lafontaine AL, Rouleau GA, Monchi O (2014) Dopamine transporter SLC6A3 genotype affects cortico-striatal activity of set-shifts in Parkinson’s disease. Brain 137:3025–3035
Haugarvoll K, Bindoff LA (2011) A novel compound heterozygous tyrosine hydroxylase mutation (p. R441P) with complex phenotype. J Parkinsons Dis 1:119–122
Hulsegge I, Kommadath A, Smits MA (2009) Globaltest and GOEAST: two different approaches for Gene Ontology analysis. BMC Proc 3(Suppl 4):S10
Kelada SN, Checkoway H, Kardia SL et al (2006) 5′ and 3′ region variability in the dopamine transporter gene (SLC6A3), pesticide exposure and Parkinson’s disease risk: a hypothesis-generating study. Hum Mol Genet 15:3055–3062
Leranth C, Roth RH, Elsworth JD, Naftolin F, Horvath TL, Redmond DE (2000) Estrogen is essential for maintaining nigrostriatal dopamine neurons in primates: implications for Parkinson’s disease and memory. J Neurosci 20:8604–8609
Lesnick TG, Papapetropoulos S, Mash DC, Ffrench-Mullen J, Shehadeh L, de Andrade M, Henley JR, Rocca WA, Ahlskog JE, Maraganore DM (2007) A genomic pathway approach to a complex disease: axon guidance and Parkinson disease. PLoS Genet 3:e98
Li X, Chen Z, Yang F, Pan J, Li Y (2013) Development of a microchip-pulsed electrochemical method for rapid determination of L-DOPA and tyrosine in Mucuna pruriens. J Sep Sci 36:1590–1596
Lim L, Jackson-Lewis V, Wong L et al (2011) Lanosterol induces mitochondrial uncoupling and protects dopaminergic neurons from cell death in a model for Parkinson’s disease. Cell Death Differ 19:416–427
Liu Z, Hamamichi S, Lee BD et al (2011) Inhibitors of LRRK2 kinase attenuate neurodegeneration and Parkinson-like phenotypes in Caenorhabditis elegans and Drosophila Parkinson’s disease models. Hum Mol Genet 20:3933–3942
Livak KJ, Schmittgen TD (2001) Analysis of relative gene expression data using real-time quantitative PCR and the 2−ΔΔCT method. Methods 25:402–408
Mcdonnell SK, Schaid DJ, Elbaz A et al (2006) Complex segregation analysis of Parkinson’s disease: the Mayo Clinic Family Study. Ann Neurol 59:788–795
Miñones-Moyano E, Friedländer MR, Pallares J, Kagerbauer B, Porta S, Escaramís G, Ferrer I, Estivill X, Martí E (2013) Upregulation of a small vault RNA (svtRNA2-1a) is an early event in Parkinson disease and induces neuronal dysfunction. RNA Biol 10:1093–1106
Nakashima A, Ota A, Kaneko YS, Mori K, Nagasaki H, Nagatsu T (2013) A possible pathophysiological role of tyrosine hydroxylase in Parkinson’s disease suggested by postmortem brain biochemistry: a contribution for the special 70th birthday symposium in honor of Prof. Peter Riederer. J Neural Transm 120:49–54
Nepusz T, Yu H, Paccanaro A (2012) Detecting overlapping protein complexes in protein-protein interaction networks. Nat Methods 9:471–472
Papapetropoulos S, Ffrench-Mullen J, Mccorquodale D, Qin Y, Pablo J, Mash DC (2006) Multiregional gene expression profiling identifies MRPS6 as a possible candidate gene for Parkinson’s disease. Gene Expr 13:205–215
Paxinos G, Watson C (1986) The rat brain in stereotaxic coordinates. Academic Press
Rhee Y-H, Ko J-Y, Chang M-Y, Yi SH, Kim D, Kim CH, Shim JW, Jo AY, Kim BW, Lee H, Lee SH, Suh W, Park CH, Koh HC, Lee YS, Lanza R, Kim KS, Lee SH (2011) Protein-based human iPS cells efficiently generate functional dopamine neurons and can treat a rat model of Parkinson disease. J Clin Invest 121:2326–2335
Saito R, Smoot ME, Ono K, Ruscheinski J, Wang PL, Lotia S, Pico AR, Bader GD, Ideker T (2012) A travel guide to Cytoscape plugins. Nat Methods 9:1069–1076
Sawada H, Oeda T, Yamamoto K (2013) Catecholamines and neurodegeneration in Parkinson’s disease—from diagnostic marker to aggregations of α-synuclein. Diagnostics 3:210–221
Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 13:2498–2504
Sun AG, Lin AQ, Huang SY, Huo D, Cong CH (2015) Identification of potential drugs for Parkinson’s disease based on a sub-pathway method. Int J Neurosci 126:318
Uhl GR (1998) Hypothesis: the role of dopaminergic transporters in selective vulnerability of cells in Parkinson’s disease. Ann Neurol 43:555–560
Yang Q, Liu S, Yin M, Yin Y, Zhou G, Zhou J (2015) Ebf2 is required for development of dopamine neurons in the midbrain periaqueductal gray matter of mouse. Dev Neurobiol 75:1282–1294
Yao SC, Hart AD, Terzella MJ (2013) An evidence-based osteopathic approach to Parkinson disease. Osteopathic Family Physician 5:96–101
Zhang B, Kirov S, Snoddy J (2005) WebGestalt: an integrated system for exploring gene sets in various biological contexts. Nucleic Acids Res 33:W741–W748
Zhang B, Xia C, Lin Q, Huang J (2012) Identification of key pathways and transcription factors related to Parkinson disease in genome wide. Mol Biol Rep 39:10881–10887
Zimprich A, Benet-Pagès A, Struhal W, Graf E, Eck SH, Offman MN, Haubenberger D, Spielberger S, Schulte EC, Lichtner P, Rossle SC, Klopp N, Wolf E, Seppi K, Pirker W, Presslauer S, Mollenhauer B, Katzenschlager R, Foki T, Hotzy C, Reinthaler E, Harutyunyan A, Kralovics R, Peters A, Zimprich F, Brücke T, Poewe W, Auff E, Trenkwalder C, Rost B, Ransmayr G, Winkelmann J, Meitinger T, Strom TM (2011) A mutation in VPS35, encoding a subunit of the retromer complex, causes late-onset Parkinson disease. Am J Hum Genet 89:168–175
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This study was supported by the Parkinson-related lncRNA differential expression analysis and Jilin Province Neurological Diseases Precision Medicine Science and Technology Innovation Center (No. 20170623006TC).
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The study was conducted following the “Guiding Principles in the Care and Use of Animals” endorsed by the State Department of China.
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Li, J., Sun, Y. & Chen, J. Identification of Critical Genes and miRNAs Associated with the Development of Parkinson’s Disease. J Mol Neurosci 65, 527–535 (2018). https://doi.org/10.1007/s12031-018-1129-8
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DOI: https://doi.org/10.1007/s12031-018-1129-8