Journal of Molecular Neuroscience

, Volume 51, Issue 1, pp 9–12 | Cite as

Identification of Regulatory Relationships in Parkinson's Disease

  • Hao Wang
  • Cheng Sun
  • Yusi Liang
  • Heying Zhang
  • Yonggang Tan
Article

Abstract

Parkinson's disease is a complex chronic neurodegenerative disease common in elderly people and greatly affects the quality of their life. However, the pathogenesis of Parkinson's disease is still incompletely understood to date. The purpose of this present study is to explore the pathogenesis of Parkinson's disease using a computational bioinformatics analysis of gene expression. We downloaded gene expression profiles on Parkinson's disease from the Gene Expression Omnibus database and predicted the miRNAs and transcription factors of differentially expressed genes in Parkinson's disease. A total of 11 genes associated with Parkinson's disease initiation were identified, including junction plakoglobin (JUP). Besides, we identified a new transcription factor, N-Myc down-regulated gene 1 (NDRG1), which is regulated by miRNA-133 in Parkinson's disease. Furthermore, we proposed a hypothesis that there may be two kinds of regulatory relationships among miRNA-133, NDRG1, and JUP: direct regulatory relationship and indirect relationship. The results presented in this work confirmed the role of miRNA-133 in Parkinson's disease and substantiated our understanding of miRNA-related neurodegenerative states in general.

Keywords

Parkinson's disease MicroRNA Transcription factor Differentially expressed genes 

Abbreviations

PD

Parkinson's disease

GEO

Gene Expression Omnibus

JUP

Junction plakoglobin

NDRG1

N-Myc down-regulated gene 1

UTR

Untranslated region

miRNAs

MicroRNAs

DEGs

Differentially expressed genes

RMA

Robust multiarray average

DN

Dopamine neuron

TF

Transcription factor

NCBI

National Center of Biotechnology Information

Notes

Conflict of Interest

The authors declare that they have no competing interests.

References

  1. Alibes A, Yankilevich P, Canada A, Diaz-Uriarte R (2007) IDconverter and IDClight: conversion and annotation of gene and protein IDs. BMC Bioinforma 8:9CrossRefGoogle Scholar
  2. Ang SL (2006) Transcriptional control of midbrain dopaminergic neuron development. Development 133:3499–3506PubMedCrossRefGoogle Scholar
  3. Bartel DP (2004) MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 116:281–297PubMedCrossRefGoogle Scholar
  4. Ben-Ze’ev A, Geiger B (1998) Differential molecular interactions of beta-catenin and plakoglobin in adhesion, signaling and cancer. Curr Opin Cell Biol 10:629–639PubMedCrossRefGoogle Scholar
  5. Cookson MR (2009) Alpha-synuclein and neuronal cell death. Mol Neurodegener 4Google Scholar
  6. Cowin P, Kapprell HP, Franke WW, Tamkun J, Hynes RO (1986) Plakoglobin: a protein common to different kinds of intercellular adhering junctions. Cell 46:1063–1073PubMedCrossRefGoogle Scholar
  7. de Lau LM, Breteler MM (2006) Epidemiology of Parkinson's disease. Lancet Neurol 5:525–535PubMedCrossRefGoogle Scholar
  8. de Mena L, Coto E, Cardo LF et al (2010) Analysis of the micro-RNA-133 and PITX3 genes in Parkinson's disease. Am J Med Genet B Neuropsychiatr Genet 153B:1234–1239PubMedGoogle Scholar
  9. Hebert SS, De Strooper B (2007) Molecular biology. miRNAs in neurodegeneration. Science 317:1179–1180PubMedCrossRefGoogle Scholar
  10. Holen I, Whitworth J, Nutter F et al (2012) Loss of plakoglobin promotes decreased cell-cell contact, increased invasion, and breast cancer cell dissemination in vivo. Breast Cancer Res 14:R86PubMedCrossRefGoogle Scholar
  11. Irizarry RA, Hobbs B, Collin F et al (2003) Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics 4:249–264PubMedCrossRefGoogle Scholar
  12. Jankovic J (2008) Parkinson's disease: clinical features and diagnosis. J Neurol Neurosurg Psychiatry 79:368–376PubMedCrossRefGoogle Scholar
  13. Jinek M, Doudna JA (2009) A three-dimensional view of the molecular machinery of RNA interference. Nature 457:405–412PubMedCrossRefGoogle Scholar
  14. Kalaydjieva L, Gresham D, Gooding R et al (2000) N-myc downstream-regulated gene 1 is mutated in hereditary motor and sensory neuropathy-Lom. Am J Hum Genet 67:47–58PubMedCrossRefGoogle Scholar
  15. Khan NL, Graham E, Critchley P et al (2003) Parkin disease: a phenotypic study of a large case series. Brain 126:1279–1292PubMedCrossRefGoogle Scholar
  16. Kim J, Inoue K, Ishii J et al (2007) A microRNA feedback circuit in midbrain dopamine neurons. Science 317:1220–1224PubMedCrossRefGoogle Scholar
  17. Knudsen KA, Wheelock MJ (1992) Plakoglobin, or an 83-kD homologue distinct from beta-catenin, interacts with E-cadherin and N-cadherin. J Cell Biol 118:671–679PubMedCrossRefGoogle Scholar
  18. Langston JW (2006) The Parkinson's complex: parkinsonism is just the tip of the iceberg. Ann Neurol 59:591–596PubMedCrossRefGoogle Scholar
  19. Lee RC, Feinbaum RL, Ambros V (1993) The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14. Cell 75:843–854PubMedCrossRefGoogle Scholar
  20. Lewis BP, Burge CB, Bartel DP (2005) Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell 120:15–20PubMedCrossRefGoogle Scholar
  21. Lucking CB, Durr A, Bonifati V et al (2000) Association between early-onset Parkinson's disease and mutations in the parkin gene. N Engl J Med 342:1560–1567PubMedCrossRefGoogle Scholar
  22. Min H, Yoon S (2010) Got target? Computational methods for microRNA target prediction and their extension. Exp Mol Med 42:233–244PubMedCrossRefGoogle Scholar
  23. Peifer M, McCrea PD, Green KJ, Wieschaus E, Gumbiner BM (1992) The vertebrate adhesive junction proteins beta-catenin and plakoglobin and the Drosophila segment polarity gene armadillo form a multigene family with similar properties. J Cell Biol 118:681–691PubMedCrossRefGoogle Scholar
  24. Schaefer A, O’Carroll D, Tan CL et al (2007) Cerebellar neurodegeneration in the absence of microRNAs. J Exp Med 204:1553–1558PubMedCrossRefGoogle Scholar
  25. Troyanskaya O, Cantor M, Sherlock G et al (2001) Missing value estimation methods for DNA microarrays. Bioinformatics 17:520–525PubMedCrossRefGoogle Scholar
  26. Van Den Eeden SK, Tanner CM, Bernstein AL et al (2003) Incidence of Parkinson's disease: variation by age, gender, and race/ethnicity. Am J Epidemiol 157:1015–1022CrossRefGoogle Scholar
  27. Wakabayashi K, Takahashi H (1997) Neuropathology of autonomic nervous system in Parkinson's disease. Eur Neurol 38(Suppl 2):2–7PubMedCrossRefGoogle Scholar
  28. Wallen A, Perlmann T (2003) Transcriptional control of dopamine neuron development. Ann N Y Acad Sci 991:48–60PubMedCrossRefGoogle Scholar
  29. West AB, Kapatos G, O’Farrell C et al (2004) N-myc regulates parkin expression. J Biol Chem 279:28896–28902PubMedCrossRefGoogle Scholar
  30. Wightman B, Ha I, Ruvkun G (1993) Posttranscriptional regulation of the heterochronic gene lin-14 by lin-4 mediates temporal pattern formation in C. elegans. Cell 75:855–862PubMedCrossRefGoogle Scholar
  31. Wingender E (2008) The TRANSFAC project as an example of framework technology that supports the analysis of genomic regulation. Brief Bioinform 9:326–332PubMedCrossRefGoogle Scholar
  32. Zheng B, Liao Z, Locascio JJ et al (2010) PGC-1alpha, a potential therapeutic target for early intervention in Parkinson’s disease. Sci Transl Med 2:52ra73PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Hao Wang
    • 1
  • Cheng Sun
    • 2
  • Yusi Liang
    • 2
  • Heying Zhang
    • 3
  • Yonggang Tan
    • 3
  1. 1.Department of Neurosurgery, Luhe HospitalCapital Medical UniversityBeijingChina
  2. 2.Clinical Medicine of Seven-Year-ProgrammeChina Medical UniversityShenyangChina
  3. 3.Department of Oncology, Shengjing HospitalChina Medical UniversityShenyangChina

Personalised recommendations