Cited by 164Extracellular vesicles in diseaseMicroRNA in disease regulationNeuroinflammation and Neurodegeneration Mechanisms

Circulating Exosomal miRNA as Diagnostic Biomarkers of Neurodegenerative Diseases

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Wang, Lin, Zhang, Lijuan·2020·Frontiers in Molecular Neuroscience

Abstract

Neurodegenerative diseases (NDDs) are a group of diseases caused by chronic and progressive degeneration of neural tissue. The main pathological manifestations are neuronal degeneration and loss in the brain and/or spinal cord. Common NDDs include Alzheimer disease (AD), Parkinson disease (PD), Huntington disease (HD), and amyotrophic lateral sclerosis (ALS). The complicated pathological characteristics and different clinical manifestations of NDDs result in a lack of sensitive and efficient diagnostic methods. In addition, no sensitive biomarkers are available to monitor the course of NDDs, predict their prognosis, and monitor the therapeutic response. Despite extensive research in recent years, analysis of amyloid β (Aβ) and α-synuclein has failed to effectively improve NDD diagnosis. Although recent studies have indicated circulating miRNAs as promising diagnostic biomarkers of NDDs, the miRNA in the peripheral circulation is susceptible to interference by other components, making circulating miRNA results less consistent. Exosomes are small membrane vesicles with a diameter of approximately 30-100 nm that transport proteins, lipids, mRNA, and miRNA. Because recent studies have shown that exosomes have a double-membrane structure that can resist ribonuclease in the blood, giving exosomal miRNA high stability and making them resistant to degradation, they may become an ideal biomarker of circulating fluids. In this review, we discuss the applicability of circulating exosomal miRNAs as biomarkers, highlight the technical aspects of exosomal miRNA analysis, and review studies that have used circulating exosomal miRNAs as candidate diagnostic biomarkers of NDDs.

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  1. Amin Lari A. Ghavanini A. A. Bokaee H. R. (2019). A review of electrophysiological studies of lower motor neuron involvement in amyotrophic lateral sclerosis. Neurol. Sci. 40, 1125– 1136. 10.1007/s10072-019-03832-4 30877611 · DOI
  2. Arellano-Anaya Z. E. Huor A. Leblanc P. Lehmann S. Provansal M. Raposo G.. (2015). Prion strains are differentially released through the exosomal pathway. Cell. Mol. Life Sci. 72, 1185– 1196. 10.1007/s00018-014-1735-8 25227242 PMC11113346 · DOI
  3. Asai H. Ikezu S. Tsunoda S. Medalla M. Luebke J. Haydar T.. (2015). Depletion of microglia and inhibition of exosome synthesis halt tau propagation. Nat. Neurosci. 18, 1584– 1593. 10.1038/nn.4132 26436904 PMC4694577 · DOI · Paper page
  4. Bai X. Tang Y. Yu M. Wu L. Liu F. Ni J.. (2017). Downregulation of blood serum microRNA 29 family in patients with Parkinson’s disease. Sci. Rep. 7: 5411. 10.1038/s41598-017-03887-3 28710399 PMC5511199 · DOI
  5. Bang C. Thum T. (2012). Exosomes: new players in cell-cell communication. Int. J. Biochem. Cell Biol. 44, 2060– 2064. 10.1016/j.biocel.2012.08.007 22903023 · DOI
  6. Baranyai T. Herczeg K. Onódi Z. Voszka I. Módos K. Marton N.. (2015). Isolation of exosomes from blood plasma: qualitative and quantitative comparison of ultracentrifugation and size exclusion chromatography methods. PLoS One 10: e0145686. 10.1371/journal.pone.0145686 26690353 PMC4686892 · DOI
  7. Barbagallo C. Mostile G. Baglieri G. Giunta F. Luca A. Raciti L.. (2019). Specific signatures of serum mirnas as potential biomarkers to discriminate clinically similar neurodegenerative and vascular-related diseases. Cell. Mol. Neurobiol. [Epub ahead of print]. 10.1007/s10571-019-00751-y 31691877 PMC11448951 · DOI
  8. Blondal T. Jensby Nielsen S. Baker A. Andreasen D. Mouritzen P. Wrang Teilum M.. (2013). Assessing sample and miRNA profile quality in serum and plasma or other biofluids. Methods 59, S1– S6. 10.1016/j.ymeth.2012.09.015 23036329 · DOI
  9. Cao F. Gao Y. Chu Q. Wu Q. Zhao L. Lan T.. (2019). Proteomics comparison of exosomes from serum and plasma between ultracentrifugation and polymer-based precipitation kit methods. Electrophoresis 40, 3092– 3098. 10.1002/elps.201900295 31621929 · DOI
  10. Cao X. Y. Lu J. M. Zhao Z. Q. Li M. C. Lu T. An X. S.. (2017). MicroRNA biomarkers of Parkinson’s disease in serum exosome-like microvesicles. Neurosci. Lett. 644, 94– 99. 10.1016/j.neulet.2017.02.045 28223160 · DOI
  11. Cao H. Zhou X. Zeng Y. (2019). Microfluidic exponential rolling circle amplification for sensitive microRNA detection directly from biological samples. Sens Actuators B Chem. 279, 447– 457. 10.1016/j.snb.2018.09.121 30533973 PMC6284813 · DOI
  12. Chen J. J. Zhao B. Zhao J. Li S. (2017). Potential roles of exosomal MicroRNAs as diagnostic biomarkers and therapeutic application in Alzheimer’s disease. Neural Plast. 2017: 7027380. 10.1155/2017/7027380 28770113 PMC5523215 · DOI
  13. Cheng L. Doecke J. D. Sharples R. A. Villemagne V. L. Fowler C. J. Rembach A.. (2015). Prognostic serum miRNA biomarkers associated with Alzheimer’s disease shows concordance with neuropsychological and neuroimaging assessment. Mol. Psychiatry 20, 1188– 1196. 10.1038/mp.2014.127 25349172 · DOI · Paper page
  14. Cheng L. Quek C. Y. J. Sun X. Bellingham S. A. Hill A. F. (2013). The detection of microRNA associated with Alzheimer’s disease in biological fluids using next-generation sequencing technologies. Front. Genet. 4: 150. 10.3389/fgene.2013.00150 23964286 PMC3737441 · DOI
  15. Cheng L. C. Pastrana E. Tavazoie M. Doetsch F. (2009). miR-124 regulates adult neurogenesis in the subventricular zone stem cell niche. Nat. Neurosci. 12, 399– 408. 10.1038/nn.2294 19287386 PMC2766245 · DOI · Paper page
  16. Chevillet J. R. Kang Q. Ruf I. K. Briggs H. A. Vojtech L. N. Hughes S. M.. (2014). Quantitative and stoichiometric analysis of the microRNA content of exosomes. Proc. Natl. Acad. Sci. U S A 111, 14888– 14893. 10.1073/pnas.1408301111 25267620 PMC4205618 · DOI
  17. Crescitelli R. Lässer C. Szabó T. G. Kittel A. Eldh M. Dianzani I.. (2013). Distinct RNA profiles in subpopulations of extracellular vesicles: apoptotic bodies, microvesicles and exosomes. J. Extracell. Vesicles 2: 20677. 10.3402/jev.v2i0.20677 24223256 PMC3823106 · DOI
  18. D’Anca M. Fenoglio C. Serpente M. Arosio B. Cesari M. Scarpini E. A.. (2019). Exosome determinants of physiological aging and age-related neurodegenerative diseases. Front. Aging Neurosci. 11: 232. 10.3389/fnagi.2019.00232 31555123 PMC6722391 · DOI
  19. Danzer K. M. Kranich L. R. Ruf W. P. Cagsal-Getkin O. Winslow A. R. Zhu L.. (2012). Exosomal cell-to-cell transmission of α synuclein oligomers. Mol. Neurodegener. 7: 42. 10.1186/1750-1326-7-42 22920859 PMC3483256 · DOI
  20. Das E. Jana N. R. Bhattacharyya N. P. (2013). MicroRNA-124 targets CCNA2 and regulates cell cycle in STHdh(Q111)/Hdh(Q111) cells. Biochem. Biophys. Res. Commun. 437, 217– 224. 10.1016/j.bbrc.2013.06.041 23796713 · DOI
  21. De Felice B. Annunziata A. Fiorentino G. Borra M. Biffali E. Coppola C.. (2014). miR-338–3p is over-expressed in blood, CFS, serum and spinal cord from sporadic amyotrophic lateral sclerosis patients. Neurogenetics 15, 243– 253. 10.1007/s10048-014-0420-2 25130371 · DOI
  22. Díez-Planelles C. Sánchez-Lozano P. Crespo M. C. Gil-Zamorano J. Ribacoba R. González N.. (2016). Circulating microRNAs in Huntington’s disease: emerging mediators in metabolic impairment. Pharmacol. Res. 108, 102– 110. 10.1016/j.phrs.2016.05.005 27155059 · DOI
  23. Fan H.-M. Sun X.-Y. Niu W. Zhao L. Zhang Q.-L. Li W.-S.. (2015). Altered microRNA expression in peripheral blood mononuclear cells from young patients with schizophrenia. J. Mol. Neurosci. 56, 562– 571. 10.1007/s12031-015-0503-z 25665552 · DOI
  24. Freischmidt A. Müller K. Ludolph A. C. Weishaupt J. H. (2013). Systemic dysregulation of TDP-43 binding microRNAs in amyotrophic lateral sclerosis. Acta Neuropathol. Commun. 1: 42. 10.1186/2051-5960-1-42 24252274 PMC3893596 · DOI
  25. Freischmidt A. Müller K. Zondler L. Weydt P. Mayer B. von Arnim C. A.. (2015). Serum microRNAs in sporadic amyotrophic lateral sclerosis. Neurobiol. Aging 36, 2660.e15– 2620.e20. 10.1016/j.neurobiolaging.2015.06.003 26142125 · DOI
  26. Gámez-Valero A. Campdelacreu J. Vilas D. Ispierto L. Reñé R. Álvarez R.. (2019). Exploratory study on microRNA profiles from plasma-derived extracellular vesicles in Alzheimer’s disease and dementia with Lewy bodies. Transl. Neurodegener. 8: 31. 10.1186/s40035-019-0169-5 31592314 PMC6775659 · DOI
  27. Gaughwin P. M. Ciesla M. Lahiri N. Tabrizi S. J. Brundin P. Björkqvist M. (2011). Hsa-miR-34b is a plasma-stable microRNA that is elevated in pre-manifest Huntington’s disease. Hum. Mol. Genet. 20, 2225– 2237. 10.1093/hmg/ddr111 21421997 · DOI
  28. Grant B. D. Donaldson J. G. (2009). Pathways and mechanisms of endocytic recycling. Nat. Rev. Mol. Cell Biol. 10, 597– 608. 10.1038/nrm2755 19696797 PMC3038567 · DOI
  29. Gui Y. Liu H. Zhang L. Lv W. Hu X. (2015). Altered microRNA profiles in cerebrospinal fluid exosome in Parkinson disease and Alzheimer disease. Oncotarget 6, 37043– 37053. 10.18632/oncotarget.6158 26497684 PMC4741914 · DOI · Paper page
  30. Haniu M. Denis P. Young Y. Mendiaz E. A. Fuller J. Hui J. O.. (2000). Characterization of Alzheimer’s β -secretase protein BACE. A pepsin family member with unusual properties. J. Biol. Chem. 275, 21099– 21106. 10.1074/jbc.M002095200 10887202 · DOI
  31. Harischandra D. S. Ghaisas S. Rokad D. Zamanian M. Jin H. Anantharam V.. (2018). Environmental neurotoxicant manganese regulates exosome-mediated extracellular miRNAs in cell culture model of Parkinson’s disease: relevance to α-synuclein misfolding in metal neurotoxicity. Neurotoxicology 64, 267– 277. 10.1016/j.neuro.2017.04.007 28450057 PMC5654692 · DOI
  32. Hartfield E. M. Fernandes H. J. Vowles J. Cowley S. A. Wade-Martins R. (2012). Cellular reprogramming: a new approach to modelling Parkinson’s disease. Biochem. Soc. Trans. 40, 1152– 1157. 10.1042/bst20120159 22988881 · DOI
  33. Hayashi N. Doi H. Kurata Y. Kagawa H. Atobe Y. Funakoshi K.. (2019). Proteomic analysis of exosome-enriched fractions derived from cerebrospinal fluid of amyotrophic lateral sclerosis patients. Neurosci. Res. [Epub ahead of print]. 10.1016/j.neures.2019.10.010 31669371 · DOI
  34. Helwa I. Cai J. Drewry M. D. Zimmerman A. Dinkins M. B. Khaled M. L.. (2017). A comparative study of serum exosome isolation using differential ultracentrifugation and three commercial reagents. PLoS One 12: e0170628. 10.1371/journal.pone.0170628 28114422 PMC5256994 · DOI
  35. Higa G. S. de Sousa E. Walter L. T. Kinjo E. R. Resende R. R. Kihara A. H. (2014). MicroRNAs in neuronal communication. Mol. Neurobiol. 49, 1309– 1326. 10.1007/s12035-013-8603-7 24385256 · DOI
  36. Hosaka T. Yamashita T. Tamaoka A. Kwak S. (2019). Extracellular RNAs as biomarkers of sporadic amyotrophic lateral sclerosis and other neurodegenerative diseases. Int. J. Mol. Sci. 20: E3148. 10.3390/ijms20133148 31252669 PMC6651127 · DOI
  37. Hsu C. Morohashi Y. Yoshimura S. Manrique-Hoyos N. Jung S. Lauterbach M. A.. (2010). Regulation of exosome secretion by Rab35 and its GTPase-activating proteins TBC1D10A-C. J. Cell Biol. 189, 223– 232. 10.1083/jcb.200911018 20404108 PMC2856897 · DOI
  38. Huang X. Yuan T. Tschannen M. Sun Z. Jacob H. Du M.. (2013). Characterization of human plasma-derived exosomal RNAs by deep sequencing. BMC Genomics 14: 319. 10.1186/1471-2164-14-319 23663360 PMC3653748 · DOI
  39. Hwang J. Y. Zukin R. S. (2018). REST, a master transcriptional regulator in neurodegenerative disease. Curr. Opin. Neurobiol. 48, 193– 200. 10.1016/j.conb.2017.12.008 29351877 PMC5892838 · DOI
  40. Jiang R. Rong C. Ke R. Meng S. Yan X. Ke H.. (2019). Differential proteomic analysis of serum exosomes reveals alterations in progression of Parkinson disease. Medicine 98: e17478. 10.1097/md.0000000000017478 31593110 PMC6799836 · DOI
  41. Junn E. Lee K.-W. Jeong B. S. Chan T. W. Im J.-Y. Mouradian M. M. (2009). Repression of α-synuclein expression and toxicity by microRNA-7. Proc. Natl. Acad. Sci. U S A 106, 13052– 13057. 10.1073/pnas.0906277106 19628698 PMC2722353 · DOI · Paper page
  42. Kalani A. Tyagi A. Tyagi N. (2014). Exosomes: mediators of neurodegeneration, neuroprotection and therapeutics. Mol. Neurobiol. 49, 590– 600. 10.1007/s12035-013-8544-1 23999871 PMC3951279 · DOI
  43. Keerthikumar S. Gangoda L. Liem M. Fonseka P. Atukorala I. Ozcitti C.. (2015). Proteogenomic analysis reveals exosomes are more oncogenic than ectosomes. Oncotarget 6, 15375– 15396. 10.18632/oncotarget.3801 25944692 PMC4558158 · DOI
  44. Kenny A. McArdle H. Calero M. Rabano A. Madden S. F. Adamson K.. (2019). Elevated plasma microRNA-206 levels predict cognitive decline and progression to dementia from mild cognitive impairment. Biomolecules 9: E734. 10.3390/biom9110734 31766231 PMC6920950 · DOI
  45. Koga Y. Yasunaga M. Moriya Y. Akasu T. Fujita S. Yamamoto S.. (2011). Exosome can prevent RNase from degrading microRNA in feces. J. Gastrointest. Oncol. 2, 215– 222. 10.3978/j.issn.2078-6891.2011.015 22811855 PMC3397623 · DOI
  46. Lamichhane T. N. Raiker R. S. Jay S. M. (2015). Exogenous DNA loading into extracellular vesicles via electroporation is size-dependent and enables limited gene delivery. Mol. Pharm. 12, 3650– 3657. 10.1021/acs.molpharmaceut.5b00364 26376343 PMC4826735 · DOI
  47. Langfelder P. Gao F. Wang N. Howland D. Kwak S. Vogt T. F.. (2018). MicroRNA signatures of endogenous Huntingtin CAG repeat expansion in mice. PLoS One 13: e0190550. 10.1371/journal.pone.0190550 29324753 PMC5764268 · DOI
  48. Lee S. T. Im W. Ban J. J. Lee M. Jung K. H. Lee S. K.. (2017). Exosome-based delivery of miR-124 in a Huntington’s disease model. J. Mov. Disord. 10, 45– 52. 10.14802/jmd.16054 28122430 PMC5288667 · DOI · Paper page
  49. Lee L. W. Zhang S. Etheridge A. Ma L. Martin D. Galas D.. (2010). Complexity of the microRNA repertoire revealed by next-generation sequencing. RNA 16, 2170– 2180. 10.1261/rna.2225110 20876832 PMC2957056 · DOI
  50. Liu C. G. Song J. Zhang Y. Q. Wang P. C. (2014). MicroRNA-193b is a regulator of amyloid precursor protein in the blood and cerebrospinal fluid derived exosomal microRNA-193b is a biomarker of Alzheimer’s disease. Mol. Med. Rep. 10, 2395– 2400. 10.3892/mmr.2014.2484 25119742 · DOI
  51. Ludwig N. Hecksteden A. Kahraman M. Fehlmann T. Laufer T. Kern F.. (2019). Spring is in the air: seasonal profiles indicate vernal change of miRNA activity. RNA Biol. 16, 1034– 1043. 10.1080/15476286.2019.1612217 31035857 PMC6602417 · DOI
  52. Lugli G. Cohen A. M. Bennett D. A. Shah R. C. Fields C. J. Hernandez A. G.. (2015). Plasma exosomal miRNAs in persons with and without Alzheimer disease: altered expression and prospects for biomarkers. PLoS One 10: e0139233. 10.1371/journal.pone.0139233 26426747 PMC4591334 · DOI
  53. Mathivanan S. Lim J. W. Tauro B. J. Ji H. Moritz R. L. Simpson R. J. (2010). Proteomics analysis of A33 immunoaffinity-purified exosomes released from the human colon tumor cell line LIM1215 reveals a tissue-specific protein signature. Mol Cell Proteomics 9, 197– 208. 10.1074/mcp.m900152-mcp200 19837982 PMC2830834 · DOI
  54. McDade E. Bateman R. J. (2017). Stop Alzheimer’s before it starts. Nature 547, 153– 155. 10.1038/547153a 28703214 · DOI
  55. McKeever P. M. Schneider R. Taghdiri F. Weichert A. Multani N. Brown R. A.. (2018). MicroRNA expression levels are altered in the cerebrospinal fluid of patients with young-onset alzheimer’s disease. Mol. Neurobiol. 55, 8826– 8841. 10.1007/s12035-018-1032-x 29603092 PMC6208843 · DOI
  56. Mestdagh P. Hartmann N. Baeriswyl L. Andreasen D. Bernard N. Chen C.. (2014). Evaluation of quantitative miRNA expression platforms in the microRNA quality control (miRQC) study. Nat. Methods 11, 809– 815. 10.1038/nmeth.3014 24973947 · DOI · Paper page
  57. Monguió-Tortajada M. Gálvez-Montón C. Bayes-Genis A. Roura S. Borràs F. E. (2019). Extracellular vesicle isolation methods: rising impact of size-exclusion chromatography. Cell. Mol. Life Sci. 76, 2369– 2382. 10.1007/s00018-019-03071-y 30891621 PMC11105396 · DOI
  58. Niu Z. Pang R. T. K. Liu W. Li Q. Cheng R. Yeung W. S. B. (2017). Polymer-based precipitation preserves biological activities of extracellular vesicles from an endometrial cell line. PLoS One 12: e0186534. 10.1371/journal.pone.0186534 29023592 PMC5638560 · DOI
  59. Pant S. Hilton H. Burczynski M. E. (2012). The multifaceted exosome: biogenesis, role in normal and aberrant cellular function and frontiers for pharmacological and biomarker opportunities. Biochem. Pharmacol. 83, 1484– 1494. 10.1016/j.bcp.2011.12.037 22230477 PMC7110994 · DOI
  60. Pheiffer C. Dias S. Rheeder P. Adam S. (2018). Decreased expression of circulating miR-20a-5p in south african women with gestational diabetes mellitus. Mol. Diagn. Ther. 22, 345– 352. 10.1007/s40291-018-0325-0 29556924 · DOI
  61. Pinto S. Cunha C. Barbosa M. Vaz A. R. Brites D. (2017). Exosomes from NSC-34 cells transfected with hSOD1–G93A are enriched in miR-124 and drive alterations in microglia phenotype. Front. Neurosci. 11: 273. 10.3389/fnins.2017.00273 28567000 PMC5434170 · DOI · Paper page
  62. Popovic M. Mazzega E. Toffoletto B. de Marco A. (2018). Isolation of anti-extra-cellular vesicle single-domain antibodies by direct panning on vesicle-enriched fractions. Microb. Cell Fact. 17: 6. 10.1186/s12934-017-0856-9 29331148 PMC5766977 · DOI
  63. Properzi F. Ferroni E. Poleggi A. Vinci R. (2015). The regulation of exosome function in the CNS: implications for neurodegeneration. Swiss Med. Wkly. 145: w14204. 10.4414/smw.2015.14204 26561744 · DOI · Paper page
  64. Rani A. O’Shea A. Ianov L. Cohen R. A. Woods A. J. Foster T. C. (2017). miRNA in circulating microvesicles as biomarkers for age-related cognitive decline. Front. Aging Neurosci. 9: 323. 10.3389/fnagi.2017.00323 29046635 PMC5632661 · DOI
  65. Reed E. R. Latourelle J. C. Bockholt J. H. Bregu J. Smock J. Paulsen J. S.. (2018). MicroRNAs in CSF as prodromal biomarkers for Huntington disease in the PREDICT-HD study. Neurology 90, e264– e272. 10.1212/wnl.0000000000004844 29282329 PMC5798654 · DOI
  66. Rekker K. Saare M. Roost A. M. Kubo A.-L. Zarovni N. Chiesi A.. (2014). Comparison of serum exosome isolation methods for microRNA profiling. Clin. Biochem. 47, 135– 138. 10.1016/j.clinbiochem.2013.10.020 24183884 · DOI
  67. Riancho J. Vázquez-Higuera J. L. Pozueta A. Lage C. Kazimierczak M. Bravo M.. (2017). MicroRNA profile in patients with Alzheimer’s disease: analysis of miR-9–5p and miR-598 in raw and exosome enriched cerebrospinal fluid samples. J. Alzheimers Dis. 57, 483– 491. 10.3233/jad-161179 28269782 · DOI · Paper page
  68. Saito Y. (2017). DJ-1 as a biomarker of Parkinson’s disease. Adv. Exp. Med. Biol. 1037, 149– 171. 10.1007/978-981-10-6583-5_10 29147908 · DOI
  69. Saraiva C. Esteves M. Bernardino L. (2017). MicroRNA: basic concepts and implications for regeneration and repair of neurodegenerative diseases. Biochem. Pharmacol. 141, 118– 131. 10.1016/j.bcp.2017.07.008 28709951 · DOI
  70. Sarko D. K. McKinney C. E. (2017). Exosomes: origins and therapeutic potential for neurodegenerative disease. Front. Neurosci. 11: 82. 10.3389/fnins.2017.00082 28289371 PMC5326777 · DOI
  71. Scarabino D. Veneziano L. Peconi M. Frontali M. Mantuano E. Corbo R. M. (2019). Leukocyte telomere shortening in Huntington’s disease. J. Neurol. Sci. 396, 25– 29. 10.1016/j.jns.2018.10.024 30396032 · DOI
  72. Shao H. Im H. Castro C. M. Breakefield X. Weissleder R. Lee H. (2018). New technologies for analysis of extracellular vesicles. Chem. Rev. 118, 1917– 1950. 10.1021/acs.chemrev.7b00534 29384376 PMC6029891 · DOI
  73. Stenmark H. (2009). Rab GTPases as coordinators of vesicle traffic. Nat. Rev. Mol. Cell Biol. 10, 513– 525. 10.1038/nrm2728 19603039 · DOI · Paper page
  74. Tabrizi S. J. Scahill R. I. Owen G. Durr A. Leavitt B. R. Roos R. A.. (2013). Predictors of phenotypic progression and disease onset in premanifest and early-stage Huntington’s disease in the TRACK-HD study: analysis of 36-month observational data. Lancet Neurol. 12, 637– 649. 10.1016/s1474-4422(13)70088-7 23664844 · DOI
  75. Taylor D. D. Zacharias W. Gercel-Taylor C. (2011). Exosome isolation for proteomic analyses and RNA profiling. Methods Mol. Biol. 728, 235– 246. 10.1007/978-1-61779-068-3_15 21468952 · DOI
  76. Thind A. Wilson C. (2016). Exosomal miRNAs as cancer biomarkers and therapeutic targets. J. Extracell. Vesicles 5: 31292. 10.3402/jev.v5.31292 27440105 PMC4954869 · DOI
  77. Trajkovic K. Hsu C. Chiantia S. Rajendran L. Wenzel D. Wieland F.. (2008). Ceramide triggers budding of exosome vesicles into multivesicular endosomes. Science 319, 1244– 1247. 10.1126/science.1153124 18309083 · DOI
  78. Van Giau V. An S. S. A. (2016). Emergence of exosomal miRNAs as a diagnostic biomarker for Alzheimer’s disease. J. Neurol. Sci. 360, 141– 152. 10.1016/j.jns.2015.12.005 26723991 · DOI
  79. Wagner K.-H. Cameron-Smith D. Wessner B. Franzke B. (2016). Biomarkers of aging: from function to molecular biology. Nutrients 8: E338. 10.3390/nu8060338 27271660 PMC4924179 · DOI
  80. Wang W.-X. Rajeev B. W. Stromberg A. J. Ren N. Tang G. Huang Q.. (2008). The expression of microRNA miR-107 decreases early in Alzheimer’s disease and may accelerate disease progression through regulation of β-site amyloid precursor protein-cleaving enzyme 1. J. Neurosci. 28, 1213– 1223. 10.1523/JNEUROSCI.5065-07.2008 18234899 PMC2837363 · DOI
  81. Weber J. A. Baxter D. H. Zhang S. Huang D. Y. Huang K. H. Lee M. J.. (2010). The microRNA spectrum in 12 body fluids. Clin. Chem. 56, 1733– 1741. 10.1373/clinchem.2010.147405 20847327 PMC4846276 · DOI
  82. Wei H. Xu Y. Xu W. Zhou Q. Chen Q. Yang M.. (2018). Serum exosomal miR-223 serves as a potential diagnostic and prognostic biomarker for dementia. Neuroscience 379, 167– 176. 10.1016/j.neuroscience.2018.03.016 29559383 · DOI
  83. Winkler C. W. Taylor K. G. Peterson K. E. (2014). Location is everything: let-7b microRNA and TLR7 signaling results in a painful TRP. Sci. Signal. 7: pe14. 10.1126/scisignal.2005407 24866018 · DOI
  84. Worms P. M. (2001). The epidemiology of motor neuron diseases: a review of recent studies. J. Neurol. Sci. 191, 3– 9. 10.1016/s0022-510x(01)00630-x 11676986 · DOI
  85. Xu Q. Zhao Y. Zhou X. Luan J. Cui Y. Han J. (2018). Comparison of the extraction and determination of serum exosome and miRNA in serum and the detection of miR-27a-3p in serum exosome of ALS patients. Intractable Rare Dis. Res. 7, 13– 18. 10.5582/irdr.2017.01091 29552440 PMC5849619 · DOI
  86. Yang F. Liao X. Tian Y. Li G. (2017). Exosome separation using microfluidic systems: size-based, immunoaffinity-based and dynamic methodologies. Biotechnol. J. 12: 1600699. 10.1002/biot.201600699 28166394 · DOI
  87. Yang T. T. Liu C. G. Gao S. C. Zhang Y. Wang P. C. (2018). The serum exosome derived MicroRNA-135a, -193b, and -384 were potential Alzheimer’s disease biomarkers. Biomed. Environ. Sci. 31, 87– 96. 10.3967/bes2018.011 29606187 · DOI
  88. Yao Y. F. Qu M. W. Li G. C. Zhang F. B. Rui H. C. (2018). Circulating exosomal miRNAs as diagnostic biomarkers in Parkinson’s disease. Eur. Rev. Med. Pharmacol. Sci. 22, 5278– 5283. 10.26355/eurrev_201808_15727 30178852 · DOI
  89. Zhang J. Li S. Li L. Li M. Guo C. Yao J.. (2015). Exosome and exosomal microRNA: trafficking, sorting, and function. Genomics Proteomics Bioinformatics 13, 17– 24. 10.1016/j.gpb.2015.02.001 25724326 PMC4411500 · DOI
  90. Zhang P. Zhou X. He M. Shang Y. Tetlow A. L. Godwin A. K.. (2019). Ultrasensitive detection of circulating exosomes with a 3D-nanopatterned microfluidic chip. Nat. Biomed. Eng. 3, 438– 451. 10.1038/s41551-019-0356-9 31123323 PMC6556143 · DOI
  91. Zhou Y. Fujikura K. Mkrtchian S. Lauschke V. M. (2018). Computational methods for the pharmacogenetic interpretation of next generation sequencing data. Front. Pharmacol. 9: 1437. 10.3389/fphar.2018.01437 30564131 PMC6288784 · DOI

Cited by

Sorted by citations

Authors
Wang, L., & Zhang, L.
Affiliations
Sheng Jing Hospital (CN)
Corresponding author
Zhang, Lijuan
Venue
Frontiers in Molecular Neuroscience
Published
2020-04-15
Volume
13
Pages
53-53
ISSN
1662-5099 (ISSN-L)
OpenAlex
W3017078364
Cited by
164
References
3
Citations by year
2026: 14 · 2025: 27 · 2024: 33 · 2023: 26 · 2022: 20 · 2021: 33 · 2020: 8 · 2019: 1 · 2018: 1
FWCI
2.08
Type
journal article
Language
en
Open access
Locations
  • Frontiers in Molecular Neuroscience (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Extracellular vesicles in disease
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › MicroRNA in disease regulation
  • Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
Keywords
exosomal microRNAs, circulating exosomes, neurodegenerative diseases, diagnostic biomarkers, Alzheimer's disease, Parkinson's disease, Huntington's disease, amyotrophic lateral sclerosis, liquid biopsy

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