Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Prognostic serum miRNA biomarkers associated with Alzheimer’s disease shows concordance with neuropsychological and neuroimaging assessment

Abstract

There is no consensus for a blood-based test for the early diagnosis of Alzheimer’s disease (AD). Expression profiling of small non-coding RNA’s, microRNA (miRNA), has revealed diagnostic potential in human diseases. Circulating miRNA are found in small vesicles known as exosomes within biological fluids such as human serum. The aim of this work was to determine a set of differential exosomal miRNA biomarkers between healthy and AD patients, which may aid in diagnosis. Using next-generation deep sequencing, we profiled exosomal miRNA from serum (N=49) collected from the Australian Imaging, Biomarkers and Lifestyle Flagship Study (AIBL). Sequencing results were validated using quantitative reverse transcription PCR (qRT-PCR; N=60), with predictions performed using the Random Forest method. Additional risk factors collected during the 4.5-year AIBL Study including clinical, medical and cognitive assessments, and amyloid neuroimaging with positron emission tomography were assessed. An AD-specific 16-miRNA signature was selected and adding established risk factors including age, sex and apolipoprotein ɛ4 (APOE ɛ4) allele status to the panel of deregulated miRNA resulted in a sensitivity and specificity of 87% and 77%, respectively, for predicting AD. Furthermore, amyloid neuroimaging information for those healthy control subjects incorrectly classified with AD-suggested progression in these participants towards AD. These data suggest that an exosomal miRNA signature may have potential to be developed as a suitable peripheral screening tool for AD.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Buy article

Get time limited or full article access on ReadCube.

$32.00

All prices are NET prices.

Figure 1
Figure 2
Figure 3

References

  1. Cole SL, Vassar R . The role of amyloid precursor protein processing by BACE1, the beta-secretase, in Alzheimer disease pathophysiology. J Biol Chem 2008; 283: 29621–29625.

    CAS  Article  Google Scholar 

  2. Villemagne VL, Burnham S, Bourgeat P, Brown B, Ellis KA, Salvado O et al. Amyloid deposition, neurodegeneration, and cognitive decline in sporadic Alzheimer's disease: a prospective cohort study. Lancet Neurol 2013; 12: 357–367.

    CAS  Article  Google Scholar 

  3. Hansson O, Zetterberg H, Buchhave P, Londos E, Blennow K, Minthon L . Association between CSF biomarkers and incipient Alzheimer's disease in patients with mild cognitive impairment: a follow-up study. Lancet Neurol 2006; 5: 228–234.

    CAS  Article  Google Scholar 

  4. Krol J, Loedige I, Filipowicz W . The widespread regulation of microRNA biogenesis, function and decay. Nat Rev Genet 2010; 11: 597–610.

    CAS  Article  Google Scholar 

  5. He L, Hannon GJ . MicroRNAs: small RNAs with a big role in gene regulation. Nat Rev Genet 2004; 5: 522–531.

    CAS  Article  Google Scholar 

  6. Valadi H, Ekstrom K, Bossios A, Sjostrand M, Lee JJ, Lotvall JO . Exosome-mediated transfer of mRNAs and microRNAs is a novel mechanism of genetic exchange between cells. Nat Cell Biol 2007; 9: 654–659.

    CAS  Article  Google Scholar 

  7. Mitchell PS, Parkin RK, Kroh EM, Fritz BR, Wyman SK, Pogosova-Agadjanyan EL et al. Circulating microRNAs as stable blood-based markers for cancer detection. Proc Natl Acad Sci USA 2008; 105: 10513–10518.

    CAS  Article  Google Scholar 

  8. Bellingham SA, Guo BB, Coleman BM, Hill AF . Exosomes: vehicles for the transfer of toxic proteins associated with neurodegenerative diseases? Front Physiol 2012; 3: 124.

    CAS  Article  Google Scholar 

  9. Skog J, Wurdinger T, van Rijn S, Meijer DH, Gainche L, Sena-Esteves M et al. Glioblastoma microvesicles transport RNA and proteins that promote tumour growth and provide diagnostic biomarkers. Nat Cell Biol 2008; 10: 1470–1476.

    CAS  Article  Google Scholar 

  10. Hunter MP, Ismail N, Zhang X, Aguda BD, Lee EJ, Yu L et al. Detection of microRNA expression in human peripheral blood microvesicles. PLoS ONE 2008; 3: e3694.

    Article  Google Scholar 

  11. Cheng L, Sharples RA, Scicluna BJ, Hill AF . Exosomes provide a protective and enriched source of miRNA for biomarker profiling compared to intracellular and cell-free blood. J Extracell Vesicles 2014; 3. doi:10.3402/jev.v3.23743 (e-pub ahead of print)

  12. Cheng L, Quek CY, Sun X, Bellingham SA, Hill AF . The detection of microRNA associated with Alzheimer's disease in biological fluids using next-generation sequencing technologies. Front Genet 2013; 4: 150.

    Article  Google Scholar 

  13. Coleman BM, Hanssen E, Lawson VA, Hill AF . Prion-infected cells regulate the release of exosomes with distinct ultrastructural features. FASEB J 2012; 26: 4160–4173.

    CAS  Article  Google Scholar 

  14. Rowe CC, Ellis KA, Rimajova M, Bourgeat P, Pike KE, Jones G et al. Amyloid imaging results from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging. Neurobiol Aging 2010; 31: 1275–1283.

    Article  Google Scholar 

  15. Ellis KA, Rowe CC, Villemagne VL, Martins RN, Masters CL, Salvado O et al. Addressing population aging and Alzheimer's disease through the Australian imaging biomarkers and lifestyle study: collaboration with the Alzheimer's Disease Neuroimaging Initiative. Alzheimers Dement 2010; 6: 291–296.

    Article  Google Scholar 

  16. Ellis KA, Bush AI, Darby D, De Fazio D, Foster J, Hudson P et al. The Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging: methodology and baseline characteristics of 1112 individuals recruited for a longitudinal study of Alzheimer's disease. Int Psychogeriatr 2009; 21: 672–687.

    Article  Google Scholar 

  17. McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM . Clinical diagnosis of Alzheimer's disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer's Disease. Neurology 1984; 34: 939–944.

    CAS  Article  Google Scholar 

  18. Cheng L, Sun X, Scicluna BJ, Coleman BM, Hill AF . Characterization and deep sequencing analysis of exosomal and non-exosomal miRNA in human urine. Kidney Int 2013; 86: 433–444.

    Article  Google Scholar 

  19. Vandesompele J, De Preter K, Pattyn F, Poppe B, Van Roy N, De Paepe A et al. Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol 2002; 3: 34.

    Article  Google Scholar 

  20. Kirschner MB, Edelman JJ, Kao SC, Vallely MP, van Zandwijk N, Reid G . The impact of hemolysis on cell-free microRNA biomarkers. Front Genet 2013; 4: 94.

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Haqqani AS, Delaney CE, Tremblay TL, Sodja C, Sandhu JK, Stanimirovic DB . Method for isolation and molecular characterization of extracellular microvesicles released from brain endothelial cells. Fluids Barriers CNS 2013; 10: 4.

    CAS  Article  Google Scholar 

  22. Huang X, Yuan T, Tschannen M, Sun Z, Jacob H, Du M et al. Characterization of human plasma-derived exosomal RNAs by deep sequencing. BMC Genomics 2013; 14: 319.

    CAS  Article  Google Scholar 

  23. Gibbings DJ, Ciaudo C, Erhardt M, Voinnet O . Multivesicular bodies associate with components of miRNA effector complexes and modulate miRNA activity. Nat Cell Biol 2009; 11: 1143–1149.

    CAS  Article  Google Scholar 

  24. Mitchell JP, Court J, Mason MD, Tabi Z, Clayton A . Increased exosome production from tumour cell cultures using the Integra CELLine Culture System. J Immunol Methods 2008; 335: 98–105.

    CAS  Article  Google Scholar 

  25. Leidinger P, Backes C, Deutscher S, Schmitt K, Mueller SC, Frese K et al. A blood based 12-miRNA signature of Alzheimer disease patients. Genome Biol 2013; 14: R78.

    Article  Google Scholar 

  26. Kumar P, Dezso Z, MacKenzie C, Oestreicher J, Agoulnik S, Byrne M et al. Circulating miRNA biomarkers for Alzheimer's disease. PLoS ONE 2013; 8: e69807.

    CAS  Article  Google Scholar 

  27. Villarroya-Beltri C, Gutierrez-Vazquez C, Sanchez-Cabo F, Perez-Hernandez D, Vazquez J, Martin-Cofreces N et al. Sumoylated hnRNPA2B1 controls the sorting of miRNAs into exosomes through binding to specific motifs. Nat Commun 2013; 4: 2980.

    Article  Google Scholar 

  28. Vella LJ, Sharples RA, Lawson VA, Masters CL, Cappai R, Hill AF . Packaging of prions into exosomes is associated with a novel pathway of PrP processing. J Pathol 2007; 211: 582–590.

    CAS  Article  Google Scholar 

  29. Sharples RA, Vella LJ, Nisbet RM, Naylor R, Perez K, Barnham KJ et al. Inhibition of gamma-secretase causes increased secretion of amyloid precursor protein C-terminal fragments in association with exosomes. FASEB J 2008; 22: 1469–1478.

    CAS  Article  Google Scholar 

  30. Bellingham SA, Coleman BM, Hill AF . Small RNA deep sequencing reveals a distinct miRNA signature released in exosomes from prion-infected neuronal cells. Nucleic Acids Res 2012; 40: 10937–10949.

    CAS  Article  Google Scholar 

  31. Long JM, Lahiri DK . MicroRNA-101 downregulates Alzheimer's amyloid-beta precursor protein levels in human cell cultures and is differentially expressed. Biochem Biophys Res Commun 2011; 404: 889–895.

    CAS  Article  Google Scholar 

  32. Vilardo E, Barbato C, Ciotti M, Cogoni C, Ruberti F . MicroRNA-101 regulates amyloid precursor protein expression in hippocampal neurons. J Biol Chem 2010; 285: 18344–18351.

    CAS  Article  Google Scholar 

  33. Hebert SS, Papadopoulou AS, Smith P, Galas MC, Planel E, Silahtaroglu AN et al. Genetic ablation of Dicer in adult forebrain neurons results in abnormal tau hyperphosphorylation and neurodegeneration. Hum Mol Genet 2010; 19: 3959–3969.

    CAS  Article  Google Scholar 

  34. Finnerty JR, Wang WX, Hebert SS, Wilfred BR, Mao G, Nelson PT . The miR-15/107 group of microRNA genes: evolutionary biology, cellular functions, and roles in human diseases. J Mol Biol 2010; 402: 491–509.

    CAS  Article  Google Scholar 

  35. Augustin R, Endres K, Reinhardt S, Kuhn PH, Lichtenthaler SF, Hansen J et al. Computational identification and experimental validation of microRNAs binding to the Alzheimer-related gene ADAM10. BMC Med Genet 2012; 13: 35.

    CAS  Article  Google Scholar 

  36. Kim J, Yoon H, Ramirez CM, Lee SM, Hoe HS, Fernandez-Hernando C . MiR-106b impairs cholesterol efflux and increases Abeta levels by repressing ABCA1 expression. Exp Neurol 2012; 235: 476–483.

    CAS  Article  Google Scholar 

  37. Wang H, Liu J, Zong Y, Xu Y, Deng W, Zhu H et al. miR-106b aberrantly expressed in a double transgenic mouse model for Alzheimer's disease targets TGF-beta type II receptor. Brain Res 2010; 1357: 166–174.

    CAS  Article  Google Scholar 

  38. Wang WX, Huang Q, Hu Y, Stromberg AJ, Nelson PT . Patterns of microRNA expression in normal and early Alzheimer's disease human temporal cortex: white matter versus gray matter. Acta Neuropathol 2011; 121: 193–205.

    Article  Google Scholar 

  39. Cogswell JP, Ward J, Taylor IA, Waters M, Shi Y, Cannon B et al. Identification of miRNA changes in Alzheimer's disease brain and CSF yields putative biomarkers and insights into disease pathways. J Alzheimer's Dis 2008; 14: 27–41.

    CAS  Article  Google Scholar 

  40. Rowe CC, Bourgeat P, Ellis KA, Brown B, Lim YY, Mulligan R et al. Predicting Alzheimer disease with beta-amyloid imaging: results from the Australian imaging, biomarkers, and lifestyle study of ageing. Ann Neurol 2013; 74: 905–913.

    CAS  Article  Google Scholar 

  41. Blennow K, Hampel H, Weiner M, Zetterberg H . Cerebrospinal fluid and plasma biomarkers in Alzheimer disease. Nat Rev Neurol 2010; 6: 131–144.

    CAS  Article  Google Scholar 

  42. Andreasen N, Minthon L, Davidsson P, Vanmechelen E, Vanderstichele H, Winblad B et al. Evaluation of CSF-tau and CSF-Abeta42 as diagnostic markers for Alzheimer disease in clinical practice. Arch Neurol 2001; 58: 373–379.

    CAS  Article  Google Scholar 

  43. Sala Frigerio C, Lau P, Salta E, Tournoy J, Bossers K, Vandenberghe R et al. Reduced expression of hsa-miR-27a-3p in CSF of patients with Alzheimer disease. Neurol 2013; 81: 2103–2106.

    CAS  Article  Google Scholar 

  44. Mattsson N, Andreasson U, Persson S, Arai H, Batish SD, Bernardini S et al. The Alzheimer's Association external quality control program for cerebrospinal fluid biomarkers. Alzheimer's Dement 2011; 7: 386–395 e386.

    CAS  Article  Google Scholar 

  45. Mapstone M, Cheema AK, Fiandaca MS, Zhong X, Mhyre TR, MacArthur LH et al. Plasma phospholipids identify antecedent memory impairment in older adults. Nat Med 2014; 20: 415–418.

    CAS  Article  Google Scholar 

  46. Ray S, Britschgi M, Herbert C, Takeda-Uchimura Y, Boxer A, Blennow K et al. Classification and prediction of clinical Alzheimer's diagnosis based on plasma signaling proteins. Nat Med 2007; 13: 1359–1362.

    CAS  Article  Google Scholar 

  47. Rembach A, Watt AD, Wilson WJ, Villemagne VL, Burnham SC, Ellis KA et al. Plasma amyloid-beta levels are significantly associated with a transition toward Alzheimer's disease as measured by cognitive decline and change in neocortical amyloid burden. J Alzheimer's Dis 2014; 40: 95–104.

    CAS  Article  Google Scholar 

Download references

Acknowledgements

This work was supported by the National Health and Medical Research Council (628946 to AFH and CLM) and project grants from The Judith Jane Mason and Harold Stannett Williams Memorial Foundation and Alzheimer’s Australia (to LC and AFH). LC was supported by a University of Melbourne Early Career Researcher Project Grant for the work and AFH is an Australian Research Council Future Fellow (FT100100560 to AFH). This work was also supported in part by the NHMRC project grant 1071430 to VLV and VLV is supported by an NHMRC Senior Research Fellowship. AIBL was supported by the Science Industry and Endowment Fund (sief.org.au), the McCusker Alzheimer's Research Foundation and the National Health and Medical Research Council via the Dementia Collaborative Research Centres program (DCRC2).

Author information

Authors and Affiliations

Authors

Consortia

Corresponding author

Correspondence to A F Hill.

Ethics declarations

Competing interests

The authors declare no conflict of interest.

Additional information

Supplementary Information accompanies the paper on the Molecular Psychiatry website

Supplementary information

PowerPoint slides

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Cheng, L., Doecke, J., Sharples, R. et al. Prognostic serum miRNA biomarkers associated with Alzheimer’s disease shows concordance with neuropsychological and neuroimaging assessment. Mol Psychiatry 20, 1188–1196 (2015). https://doi.org/10.1038/mp.2014.127

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/mp.2014.127

This article is cited by

Search

Quick links