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MicroRNA Profiling in Aging Brain of PSEN1/PSEN2 Double Knockout Mice

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Abstract

MicroRNAs are small non-coding RNAs that function as regulators of gene expression. The altered expression of microRNAs influences the pathogenesis of Alzheimer’s disease. Many researchers have focused on studies based on the relatively distinctive etiology of familial Alzheimer’s disease due to the absence of risk factors in the pathogenesis of sporadic Alzheimer’s disease. Although there is a limitation in Alzheimer’s disease studies, both Alzheimer’s disease types have a common risk factor—aging. No study to date has examined the aging factor in Alzheimer’s disease animal models with microRNAs. To investigate the effect of aging on the changes in microRNA expressions in the Alzheimer’s disease animal model, we selected 37 hippocampal microRNAs whose expression in 12- and 18-month aged mice changed significantly using microRNA microarray. On the basis of bioinformatics databases, 30 hippocampal microRNAs and their putative targets of PSEN1/PSEN2 double knockout mice were included in 28 pathways such as the wnt signaling pathway and ubiquitin-mediated proteolysis pathway. Cortical microRNAs and its putative targets involved in pathological aging were included in only four pathways such as the heparin sulfate biosynthesis. The altered expressions of these hippocampal microRNAs were associated to the imbalance between neurotoxic and neuroprotective functions and seemed to affect neurodegeneration in PSEN1/PSEN2 double knockout mice more severely than in wild-type mice. This microRNA profiling suggests that microRNAs play potential roles in the normal aging process, as well as in the Alzheimer’s disease process.

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Abbreviations

AD:

Alzheimer’s diseases

APP:

Amyloid precursor protein

DAVID:

Database for annotation, visualization, and integrated discovery

SAD:

Sporadic Alzheimer’s disease

FAD:

Familial Alzheimer’s disease

KEGG:

Kyoto Encyclopedia of Genes and Genomes

mRNA:

Messenger RNA

MiRNA:

microRNA

TGF:

Transforming growth factor

PSEN dKO:

PSEN1/PSEN2 conditional double knockout

WT:

Wild type

XIAP:

X-linked inhibitor of apoptosis

BID:

BH3 interacting domain death agonist

PS:

Presenilins

References

  1. Huntzinger E, Izaurralde E (2011) Gene silencing by microRNAs: contributions of translational repression and mRNA decay. Nat Rev Genet 12(2):99–110

    Article  CAS  PubMed  Google Scholar 

  2. Yan K, Jianban W, Liudi Y (2014) MicroRNA expression analysis of adult-onset drosophila Alzheimer’s disease model. Curr Alzheimer Res 11(9):882–891

    Google Scholar 

  3. Delay C, Hébert SS (2011) MicroRNAs and Alzheimer’s disease mouse models: current insights and future research avenues. International Journal of Alzheimer Disease 2011:6

    Google Scholar 

  4. Li N et al (2011) Up-regulation of key microRNAs, and inverse down-regulation of their predicted oxidative phosphorylation target genes, during aging in mouse brain. Neurobiol Aging 32(5):944–955

    Article  CAS  PubMed  Google Scholar 

  5. Cheng L et al (2013) The detection of microRNA associated with Alzheimer’s disease in biological fluids using next-generation sequencing technologies. Front Genet 4:150

    Article  PubMed  PubMed Central  Google Scholar 

  6. Gabrielle, S. What is early onset familial alzheimer disease (eFAD)? ; Available from: http://www.alzforum.org/early-onset-familial-ad/overview/what-early-onset-familial-alzheimer-disease-efad

  7. Richard F, Amouyel P (2001) Genetic susceptibility factors for Alzheimer’s disease. Eur J Pharmacol 412(1):1–12

    Article  CAS  PubMed  Google Scholar 

  8. Mirnics K et al (2008) Molecular signatures of neurodegeneration in the cortex of PS1/PS2 double knockout mice. Mol Neurodegener 3(1):14

    Article  PubMed  PubMed Central  Google Scholar 

  9. Chen Q et al (2008) Loss of presenilin function causes Alzheimer’s disease-like neurodegeneration in the mouse. J Neurosci Res 86(7):1615–1625

    Article  CAS  PubMed  Google Scholar 

  10. Saura CA et al (2004) Loss of presenilin function causes impairments of memory and synaptic plasticity followed by age-dependent neurodegeneration. Neuron 42(1):23–36

    Article  CAS  PubMed  Google Scholar 

  11. Beglopoulos V et al (2004) Reduced beta-amyloid production and increased inflammatory responses in presenilin conditional knock-out mice. J Biol Chem 279(45):46907–46914

    Article  CAS  PubMed  Google Scholar 

  12. Wines-Samuelson M et al (2010) Characterization of age-dependent and progressive cortical neuronal degeneration in presenilin conditional mutant mice. PLoS One 5(4):e10195

    Article  PubMed  PubMed Central  Google Scholar 

  13. Elder GA, Gama Sosa MA, De Gasperi R (2010) Transgenic mouse models of Alzheimer’s disease. Mt Sinai J Med 77(1):69–81

    Article  PubMed  PubMed Central  Google Scholar 

  14. Corbett A, Williams G, Ballard C (2015) Drug repositioning in Alzheimer’s disease. Front Biosci (Schol Ed) 7:184–188

    Article  Google Scholar 

  15. Radde R et al (2006) Abeta42-driven cerebral amyloidosis in transgenic mice reveals early and robust pathology. EMBO Rep 7(9):940–946

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Bezprozvanny I, Mattson MP (2008) Neuronal calcium mishandling and the pathogenesis of Alzheimer’s disease. Trends Neurosci 31(9):454–463

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Lee JH et al (2015) Presenilin 1 maintains lysosomal ca(2+) homeostasis via TRPML1 by regulating vATPase-mediated lysosome acidification. Cell Rep 12(9):1430–1444

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Nixon RA, Cataldo AM (2006) Lysosomal system pathways: genes to neurodegeneration in Alzheimer’s disease. J Alzheimers Dis 9(3 Suppl):277–289

    Article  CAS  PubMed  Google Scholar 

  19. Nixon RA, Yang DS (2011) Autophagy failure in Alzheimer’s disease—locating the primary defect. Neurobiol Dis 43(1):38–45

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Tu H et al (2006) Presenilins form ER Ca2+ leak channels, a function disrupted by familial Alzheimer’s disease-linked mutations. Cell 126(5):981–993

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Cui X et al (2015) Network fingerprint: a knowledge-based characterization of biomedical networks. Sci Rep 5:13286

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Christie LA et al (2007) Differential regulation of inhibitors of apoptosis proteins in Alzheimer’s disease brains. Neurobiol Dis 26(1):165–173

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Hirota M et al (2008) Smad2 functions as a co-activator of canonical Wnt/beta-catenin signaling pathway independent of Smad4 through histone acetyltransferase activity of p300. Cell Signal 20(9):1632–1641

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Song L et al (2014) Dab2 attenuates brain injury in APP/PS1 mice via targeting transforming growth factor-beta/SMAD signaling. Neural Regen Res 9(1):41–50

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Chou JJ et al (1999) Solution structure of BID, an intracellular amplifier of apoptotic signaling. Cell 96(5):615–624

    Article  CAS  PubMed  Google Scholar 

  26. Treadway JL, Mendys P, Hoover DJ (2001) Glycogen phosphorylase inhibitors for treatment of type 2 diabetes mellitus. Expert Opin Investig Drugs 10(3):439–454

    Article  CAS  PubMed  Google Scholar 

  27. Watanabe H et al (2014) Partial loss of presenilin impairs age-dependent neuronal survival in the cerebral cortex. J Neurosci 34(48):15912–15922

    Article  PubMed  PubMed Central  Google Scholar 

  28. Inestrosa NC, Varela-Nallar L (2014) Wnt signaling in the nervous system and in Alzheimer’s disease. J Mol Cell Biol 6(1):64–74

    Article  PubMed  Google Scholar 

  29. Rosso SB, Inestrosa NC (2013) WNT signaling in neuronal maturation and synaptogenesis. Front Cell Neurosci 7:103

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Sun Q et al (2015) Cross-talk between TGF-beta/Smad pathway and Wnt/beta-catenin pathway in pathological scar formation. Int J Clin Exp Pathol 8(6):7631–7639

    CAS  PubMed  PubMed Central  Google Scholar 

  31. Caraci F et al (2011) TGF-beta1 pathway as a new target for neuroprotection in Alzheimer’s disease. CNS Neurosci Ther 17(4):237–249

    Article  CAS  PubMed  Google Scholar 

  32. von Bernhardi R et al (2015) Role of TGFbeta signaling in the pathogenesis of Alzheimer’s disease. Front Cell Neurosci 9:426

    Google Scholar 

  33. Vilchez D, Saez I, Dillin A (2014) The role of protein clearance mechanisms in organismal ageing and age-related diseases. Nat Commun 5:5659

    Article  CAS  PubMed  Google Scholar 

  34. Ciechanover A, Kwon YT (2015) Degradation of misfolded proteins in neurodegenerative diseases: therapeutic targets and strategies. Exp Mol Med 47:e147

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Galban S, Duckett CS (2010) XIAP as a ubiquitin ligase in cellular signaling. Cell Death Differ 17(1):54–60

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Vogt MC, Bruning JC (2013) CNS insulin signaling in the control of energy homeostasis and glucose metabolism—from embryo to old age. Trends Endocrinol Metab 24(2):76–84

    Article  CAS  PubMed  Google Scholar 

  37. Tomlinson DR, Gardiner NJ (2008) Glucose neurotoxicity. Nat Rev Neurosci 9(1):36–45

    Article  CAS  PubMed  Google Scholar 

  38. Jin K et al (2004) Enhanced neurogenesis in Alzheimer’s disease transgenic (PDGF-APPSw, Ind) mice. Proc Natl Acad Sci U S A 101(36):13363–13367

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Lopez-Toledano MA, Shelanski ML (2007) Increased neurogenesis in young transgenic mice overexpressing human APP(Sw, Ind). J Alzheimers Dis 12(3):229–240

    Article  CAS  PubMed  Google Scholar 

  40. RF, Z, (2015) Of mice and men and Alzheimer disease: aging versus time. JSM Alzheimer’s Dis Relat Dement 2(2):1017

  41. Age converter. Available from: http://www.age-converter.com/mouse-age-calculator. Accessed 13 July 2016

  42. Life span as a biomarker. Available from: https://www.jax.org/research-and-faculty/research-labs/the-harrison-lab/gerontology/life-span-as-a-biomarker. Accessed 13 July 2016

  43. Huang da W, Sherman BT, Lempicki RA (2009) Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc 4(1):44–57

    Article  PubMed  Google Scholar 

  44. Huang da W, Sherman BT, Lempicki RA (2009) Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res 37(1):1–13

    Article  PubMed  Google Scholar 

  45. Kanehisa M, Goto S (2000) KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res 28(1):27–30

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Kanehisa M et al (2014) Data, information, knowledge and principle: back to metabolism in KEGG. Nucleic Acids Res 42(Database issue):D199–D205

    Article  CAS  PubMed  Google Scholar 

  47. Cline MS et al (2007) Integration of biological networks and gene expression data using Cytoscape. Nat Protoc 2(10):2366–2382

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

This research was funded by the National Research Council of Science & Technology (NST) grant by the Korean government (MSIP) (No. CRC-15-04-KIST).

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Authors and Affiliations

  1. Convergence Research Center for Diagnosis, Treatment and Care System of Dementia, Korea Institute of Science and Technology (KIST), Seoul, 02792, Republic of Korea

    Suji Ham, Tae Kyoo Kim & Heh-In Im

  2. Division of Bio-Medical Science &Technology, KIST School, Korea University of Science and Technology, Seoul, 02792, Republic of Korea

    Suji Ham & Heh-In Im

  3. Department of Biology, Boston University, Boston, 02215, USA

    Tae Kyoo Kim

  4. Center for Neuroscience, Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, 02792, Republic of Korea

    Sangjoon Lee & Heh-In Im

  5. Neuroscience Center of Excellence, Louisiana State University Health New Orleans Sciences Center, New Orleans, LA, 70112, USA

    Ya-Ping Tang

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  1. Suji Ham
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Contributions

H-II and Y-PT designed the study. H-II carried out the RNA isolation and microarray, and reviewed and commented on the manuscript. SH analyzed, interpreted data, and drafted the manuscript. SL interpreted data and helped in drafting the manuscript. Y-PT helped to design and review the study. TK discussed and edited the manuscript for submission. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Heh-In Im.

Ethics declarations

All procedures regarding the use and handling of mice were conducted as approved by the Institutional Animal Care and Use Committee (IACUC) of the Korea Institute of Science and Technology.

Conflict of Interest

The authors declare that they have no conflict of interest.

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Ham, S., Kim, T.K., Lee, S. et al. MicroRNA Profiling in Aging Brain of PSEN1/PSEN2 Double Knockout Mice. Mol Neurobiol 55, 5232–5242 (2018). https://doi.org/10.1007/s12035-017-0753-6

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  • DOI: https://doi.org/10.1007/s12035-017-0753-6

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