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miR-212 and miR-132 Are Downregulated in Neurally Derived Plasma Exosomes of Alzheimer’s Patients

Cha, Diana J., Mengel, David, Mustapic, Maja, Liu, Wen, Selkoe, Dennis J., Kapogiannis, Dimitrios, Galasko, Douglas, Rissman, Robert A., Bennett, David A., Walsh, Dominic M.·2019·Frontiers in Neuroscience
DOI 10.3389/fnins.2019.01208PMC PMC6902042
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FIGURE 1 miRNAs are differentially expressed in AD compared to control and HPC brains. (A) Workflow of miRNA candidate discovery. RNA was isolated from cortical brain tissue of individuals who were cognitively intact (n = 5), AD (n = 5) or HPC (n = 5) (see Table 1 for demographic data). RNA from the 5 control, 5 AD or 5 HPC brains were pooled and used as template for cDNA synthesis. cDNA from pooled control, AD or HPC were used as templates for qRT-PCR. (B) Comparative analysis of profiled miRNAs between disease groups. miRNAs that are upregulated (red) and downregulated (blue) by >2-fold are indicated. Each point represents log10(2-ΔΔCt) average values from each cDNA pool run in triplicate (3 plates). (C) miRNAs that were significantly altered by >2-fold. A total of 16 miRNAs were dysregulated in AD brains compared to control or HPC brains. Six of those miRNAs were consistently altered specifically in AD brains (miR-608, -219a-5p, 1304-5p, -182-5p, -566, -591). Six additional miRNAs were upregulated >2-fold in AD brains compared to control, but <2-fold compared to HPC brains (miR-32-5p, -519e-5p, 132-3p, 212-3p, -662, -138-3p). Red text = upregulated miRNAs; blue text = downregulated miRNAs.
FIGURE 1 miRNAs are differentially expressed in AD compared to control and HPC brains. (A) Workflow of miRNA candidate discovery. RNA was isolated from cortical brain tissue of individuals who were cognitively intact (n = 5), AD (n = 5) or HPC (n = 5) (see Table 1 for demographic data). RNA from the 5 control, 5 AD or 5 HPC brains were pooled and used as template for cDNA synthesis. cDNA from pooled control, AD or HPC were used as templates for qRT-PCR. (B) Comparative analysis of profiled miRNAs between disease groups. miRNAs that are upregulated (red) and downregulated (blue) by >2-fold are indicated. Each point represents log10(2-ΔΔCt) average values from each cDNA pool run in triplicate (3 plates). (C) miRNAs that were significantly altered by >2-fold. A total of 16 miRNAs were dysregulated in AD brains compared to control or HPC brains. Six of those miRNAs were consistently altered specifically in AD brains (miR-608, -219a-5p, 1304-5p, -182-5p, -566, -591). Six additional miRNAs were upregulated >2-fold in AD brains compared to control, but <2-fold compared to HPC brains (miR-32-5p, -519e-5p, 132-3p, 212-3p, -662, -138-3p). Red text = upregulated miRNAs; blue text = downregulated miRNAs.CC BY · PubMed Central
FIGURE 2 miRNA validation in AD brain tissue by qRT-PCR. miRNA candidates were measured by miRNA-specific qRT PCR. (A) Neuron-specific miR-9 levels, which was similar between disease groups in array analysis, were also unchanged by qRT-PCR [X2(2) = 0.5263, p = 0.769]. Two of the original hits (B) miR-182-5p (∗∗ = 0.009) and (C) miR-32-5p (control vs. HPC, ∗ = 0.049; control vs. HPC, ∗ = 0.025) identified by miRNA arrays were validated by qRT-PCR. (D) miR-132-3p was significantly changed between disease groups [X2(2) = 6.156, p = 0.046], but did not reach statistical significance in pair-wise comparisons. (E) MiR-219a-5p showed a strong trend for change between the three disease groups [X2(2) = 5.906, p = 0.051]. (F) miR-212-3p levels were not significantly changed between disease groups. Fold change was determined by 2–ΔΔCt relative to miR-16. Significance was determined by Kruskal–Wallis test followed by Dunn‘s post hoc test.
FIGURE 2 miRNA validation in AD brain tissue by qRT-PCR. miRNA candidates were measured by miRNA-specific qRT PCR. (A) Neuron-specific miR-9 levels, which was similar between disease groups in array analysis, were also unchanged by qRT-PCR [X2(2) = 0.5263, p = 0.769]. Two of the original hits (B) miR-182-5p (∗∗ = 0.009) and (C) miR-32-5p (control vs. HPC, ∗ = 0.049; control vs. HPC, ∗ = 0.025) identified by miRNA arrays were validated by qRT-PCR. (D) miR-132-3p was significantly changed between disease groups [X2(2) = 6.156, p = 0.046], but did not reach statistical significance in pair-wise comparisons. (E) MiR-219a-5p showed a strong trend for change between the three disease groups [X2(2) = 5.906, p = 0.051]. (F) miR-212-3p levels were not significantly changed between disease groups. Fold change was determined by 2–ΔΔCt relative to miR-16. Significance was determined by Kruskal–Wallis test followed by Dunn‘s post hoc test.CC BY · PubMed Central
FIGURE 3 miRNA analysis of brain-derived exosomes in blood. (A) C(t) values for neuron-specific miR-9, plasma abundant miR-451a, and ubiquitously expressed miR-16 from induced neuronal (iNs) cell lysates (CL), and iN exosomes isolated by ultracentrifugation of iN conditioned medium. (B) Flow chart for the detection of miRNAs from plasma exosomes. RNAs were isolated from total plasma exosomes (Exoquick pellets), or neural exosomes immunoprecipitated (IP) from total plasma exosomes with anti-L1CAM antibody. RNA was reverse transcribed with Qiagen’s HiFlex buffer to generate cDNAs, and subsequently used as template for qPCR using miRNA-specific primers for miRNA detection. C(t) values for miR-9, miR-451a, and miR-16 from (C) plasma-derived total- and L1CAM (L1)- immunoprecipitated exosomes. As a negative control, an irrelevant antibody, 46-4 was used for immunoisolation. Total and IP’ed exosomes were isolated in duplicate (#1 and #2) from 2 healthy control donors (Plasma 1 and plasma 2). Low Ct values indicate high levels of miRNA, and high Ct values indicate low levels of miRNA. The reliable CT limit is ∼40.
FIGURE 3 miRNA analysis of brain-derived exosomes in blood. (A) C(t) values for neuron-specific miR-9, plasma abundant miR-451a, and ubiquitously expressed miR-16 from induced neuronal (iNs) cell lysates (CL), and iN exosomes isolated by ultracentrifugation of iN conditioned medium. (B) Flow chart for the detection of miRNAs from plasma exosomes. RNAs were isolated from total plasma exosomes (Exoquick pellets), or neural exosomes immunoprecipitated (IP) from total plasma exosomes with anti-L1CAM antibody. RNA was reverse transcribed with Qiagen’s HiFlex buffer to generate cDNAs, and subsequently used as template for qPCR using miRNA-specific primers for miRNA detection. C(t) values for miR-9, miR-451a, and miR-16 from (C) plasma-derived total- and L1CAM (L1)- immunoprecipitated exosomes. As a negative control, an irrelevant antibody, 46-4 was used for immunoisolation. Total and IP’ed exosomes were isolated in duplicate (#1 and #2) from 2 healthy control donors (Plasma 1 and plasma 2). Low Ct values indicate high levels of miRNA, and high Ct values indicate low levels of miRNA. The reliable CT limit is ∼40.CC BY · PubMed Central
FIGURE 4 miR-132/212 is significantly decreased in AD neural exosomes isolated from plasma. (A) neural-specific miR-9 was abundantly detected in all measured samples and was not significantly different between disease groups [X2(2) = 1.195, p = 0.550]. (B) non-specific miR-451a were also detected in samples, but was unchanged between disease groups [F(2) = 0.035, p = 0.965]. Of the miRNAs significantly altered in AD brains, (C) miR-132 was significantly decreased in neural-derived plasma exosomes from AD subjects (∗∗ = 0.0333). (D) miR-212, a miRNA transcribed in tandem to miR-132, was also significantly decreased in AD (∗∗∗ = 0.001). Significance was determined by one-way ANOVA followed by Tukey‘s post hoc test for normally distributed data. Otherwise, Kruskal–Wallis test followed by Dunn‘s post hoc test was used.
FIGURE 4 miR-132/212 is significantly decreased in AD neural exosomes isolated from plasma. (A) neural-specific miR-9 was abundantly detected in all measured samples and was not significantly different between disease groups [X2(2) = 1.195, p = 0.550]. (B) non-specific miR-451a were also detected in samples, but was unchanged between disease groups [F(2) = 0.035, p = 0.965]. Of the miRNAs significantly altered in AD brains, (C) miR-132 was significantly decreased in neural-derived plasma exosomes from AD subjects (∗∗ = 0.0333). (D) miR-212, a miRNA transcribed in tandem to miR-132, was also significantly decreased in AD (∗∗∗ = 0.001). Significance was determined by one-way ANOVA followed by Tukey‘s post hoc test for normally distributed data. Otherwise, Kruskal–Wallis test followed by Dunn‘s post hoc test was used.CC BY · PubMed Central
FIGURE 5 Receiver-operator-characteristics (ROC) curves demonstrate that miR-132 and miR 212 in neural exosomes evidence good separation between NCI and AD. ROC curves of (A) miR-132, and (B) miR-212 allowed good separation of NCI from AD patients. Neither (C) miR-132, nor (D) miR-212 levels in NCI vs. AD-MCI patients allowed good separation. Area under the curves (AUC) for all ROC analyses were calculated using a non-parametric approach.
FIGURE 5 Receiver-operator-characteristics (ROC) curves demonstrate that miR-132 and miR 212 in neural exosomes evidence good separation between NCI and AD. ROC curves of (A) miR-132, and (B) miR-212 allowed good separation of NCI from AD patients. Neither (C) miR-132, nor (D) miR-212 levels in NCI vs. AD-MCI patients allowed good separation. Area under the curves (AUC) for all ROC analyses were calculated using a non-parametric approach.CC BY · PubMed Central

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Research works printed but not linked: 36

  1. Abner, 2016, Plasma neuronal exosomal levels of Alzheimer’s disease biomarkers in normal aging., Ann. Clin. Transl. Neurol., 3, 399, 10.1002/acn3.309 · DOI
  2. Banzhaf-Strathmann, 2014, MicroRNA-125b induces tau hyperphosphorylation and cognitive deficits in Alzheimer’s disease., EMBO J., 33, 1667, 10.15252/embj.201387576 · DOI · Paper page
  3. Bao, 2017, PET Imaging for Early Detection of Alzheimer’s Disease: from pathologic to physiologic biomarkers., PET Clin., 12, 329, 10.1016/j.cpet.2017.03.001 · DOI
  4. Bateman, 2019, Plasma biomarkers of AD emerging as essential tools for drug development: an EU/US CTAD task force report., J. Prev. Alzheimers Dis., 6, 169, 10.14283/jpad.2019.21 · DOI
  5. Bhatnagar, 2014, Increased microRNA-34c abundance in Alzheimer’s disease circulating blood plasma., Front. Mol. Neurosci., 7, 10.3389/fnmol.2014.00002 · DOI
  6. Chevillet, 2014, Quantitative and stoichiometric analysis of the microRNA content of exosomes., Proc. Natl. Acad. Sci. U.SA., 111, 14888, 10.1073/pnas.1408301111 · DOI
  7. Coolen, 2013, miR-9: a versatile regulator of neurogenesis., Front. Cell Neurosci., 7, 10.3389/fncel.2013.00220 · DOI · Paper page
  8. Denk, 2018, Specific serum and CSF microRNA profiles distinguish sporadic behavioural variant of frontotemporal dementia compared with Alzheimer patients and cognitively healthy controls., PLoS One, 13, 10.1371/journal.pone.0197329 · DOI
  9. El Fatimy, 2018, MicroRNA-132 provides neuroprotection for tauopathies via multiple signaling pathways., Acta Neuropathol., 136, 537, 10.1007/s00401-018-1880-5 · DOI · Paper page
  10. Galasko, 2015, Expanding the repertoire of biomarkers for alzheimer’s disease: targeted and non-targeted approaches., Front. Neurol., 6, 10.3389/fneur.2015.00256 · DOI
  11. Goetzl, Altered lysosomal proteins in neural-derived plasma exosomes in preclinical Alzheimer disease., Neurology, 85, 40, 10.1212/WNL.0000000000001702 · DOI · Paper page
  12. Goetzl, Low neural exosomal levels of cellular survival factors in Alzheimer’s disease., Ann. Clin. Transl. Neurol., 2, 769, 10.1002/acn3.211 · DOI
  13. Goetzl, 2019, Neuron-derived exosome proteins may contribute to progression from repetitive mild traumatic brain injuries to chronic traumatic encephalopathy., Front. Neurosci., 13, 10.3389/fnins.2019.00452 · DOI
  14. Guix, 2018, Detection of aggregation-competent tau in neuron-derived extracellular vesicles., Int. J. Mol. Sci., 19, 10.3390/ijms19030663 · DOI
  15. Hebert, 2008, Loss of microRNA cluster miR-29a/b-1 in sporadic Alzheimer’s disease correlates with increased BACE1/beta-secretase expression., Proc. Natl. Acad. Sci. U.S.A., 105, 6415, 10.1073/pnas.0710263105 · DOI · Paper page
  16. Heinzelman, 2016, Nanoscale extracellular vesicle analysis in Alzheimer’s disease diagnosis and therapy., Int. J. Alzheimers Dis., 2016, 10.1155/2016/8053139 · DOI
  17. Hernandez-Rapp, 2016, microRNA-132/212 deficiency enhances Abeta production and senile plaque deposition in Alzheimer’s disease triple transgenic mice., Sci. Rep., 6, 10.1038/srep30953 · DOI
  18. Herrera-Espejo, 2019, A Systematic Review of MicroRNA Expression as Biomarker of Late-Onset Alzheimer’s Disease., Mol. Neurobiol, 10.1007/s12035-019-01676-9 · DOI · Paper page
  19. Jack, 2013, Tracking pathophysiological processes in Alzheimer’s disease: an updated hypothetical model of dynamic biomarkers., Lancet Neurol., 12, 207, 10.1016/S1474-4422(12)70291-0 · DOI · Paper page
  20. Kapogiannis, 2015, Dysfunctionally phosphorylated type 1 insulin receptor substrate in neural-derived blood exosomes of preclinical Alzheimer’s disease., FASEB J., 29, 589, 10.1096/fj.14-262048 · DOI
  21. Kosik, 2006, The neuronal microRNA system., Nat. Rev. Neurosci., 7, 911, 10.1038/nrn2037 · DOI
  22. Lau, 2013, Alteration of the microRNA network during the progression of Alzheimer’s disease., EMBO Mol. Med., 5, 1613, 10.1002/emmm.201201974 · DOI · Paper page
  23. Okamoto, 2018, MicroRNA-451a in extracellular, blood-resident vesicles attenuates macrophage and dendritic cell responses to influenza whole-virus vaccine., J. Biol. Chem., 293, 18585, 10.1074/jbc.RA118.003862 · DOI
  24. Pan, 1985, Electron microscopic evidence for externalization of the transferrin receptor in vesicular form in sheep reticulocytes., J. Cell Biol., 101, 942, 10.1083/jcb.101.3.942 · DOI
  25. Paolicelli, 2019, Cell-to-cell communication by extracellular vesicles: focus on microglia., Neuroscience, 405, 148, 10.1016/j.neuroscience.2018.04.003 · DOI · Paper page
  26. Patrick, 2017, Dissecting the role of non-coding RNAs in the accumulation of amyloid and tau neuropathologies in Alzheimer’s disease., Mol. Neurodegener., 12, 10.1186/s13024-017-0191-y · DOI · Paper page
  27. Pichler, 2017, The miRNome of Alzheimer’s disease: consistent downregulation of the miR-132/212 cluster., Neurobiol. Aging, 50, 10.1016/j.neurobiolaging.2016.09.019 · DOI · Paper page
  28. Pucella, 2015, miR-182 is largely dispensable for adaptive immunity: lack of correlation between expression and function., J. Immunol., 194, 2635, 10.4049/jimmunol.1402261 · DOI
  29. Salta, 2016, miR-132 loss de-represses ITPKB and aggravates amyloid and TAU pathology in Alzheimer’s brain., EMBO Mol. Med., 8, 1005, 10.15252/emmm.201606520 · DOI · Paper page
  30. Sambandan, 2017, Activity-dependent spatially localized miRNA maturation in neuronal dendrites., Science, 355, 634, 10.1126/science.aaf8995 · DOI
  31. Swarbrick, 2019, Systematic review of miRNA as biomarkers in alzheimer’s disease., Mol. Neurobiol., 56, 6156, 10.1007/s12035-019-1500-y · DOI
  32. Vella, 2016, Focus on extracellular vesicles: exosomes and their role in protein trafficking and biomarker potential in Alzheimer’s and Parkinson’s disease., Int. J. Mol. Sci., 17, 10.3390/ijms17020173 · DOI
  33. Wanet, 2012, miR-212/132 expression and functions: within and beyond the neuronal compartment., Nucleic Acids Res., 40, 4742, 10.1093/nar/gks151 · DOI
  34. Weinberg, 2015, Evidence for a neuroprotective microRNA pathway in amnestic mild cognitive impairment., Front. Neurosci., 9, 10.3389/fnins.2015.00430 · DOI
  35. Winston, 2016, Prediction of conversion from mild cognitive impairment to dementia with neuronally derived blood exosome protein profile., Alzheimers Dement., 3, 63, 10.1016/j.dadm.2016.04.001 · DOI
  36. Wong, 2013, De-repression of FOXO3a death axis by microRNA-132 and -212 causes neuronal apoptosis in Alzheimer’s disease., Hum. Mol. Genet., 22, 3077, 10.1093/hmg/ddt164 · DOI · Paper page

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Metadata

Authors
Cha, D. J., Mengel, D., Mustapic, M., Liu, W., Selkoe, D. J., Kapogiannis, D., Galasko, D., Rissman, R. A., Bennett, D. A., & Walsh, D. M.
Venue
Frontiers in Neuroscience
Publisher
Frontiers Media SA
Published
2019-11-26
Volume
13
ISSN
1662-453X
DOI
10.3389/fnins.2019.01208
PMC
PMC6902042
Cited by
204
References
12
Licence
creativecommons.org/licenses/by/4.0/ (vor)
Funders
  • Alzheimer's Drug Discovery Foundation
  • Alzheimer's Association
  • Deutsche Forschungsgemeinschaft

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